unique network structure: Topics by Science.gov

Sample records for unique network structure

Finding overlapping communities in multilayer networks

PubMed Central

Liu, Weiyi; Suzumura, Toyotaro; Ji, Hongyu; Hu, Guangmin

2018-01-01

Finding communities in multilayer networks is a vital step in understanding the structure and dynamics of these layers, where each layer represents a particular type of relationship between nodes in the natural world. However, most community discovery methods for multilayer networks may ignore the interplay between layers or the unique topological structure in a layer. Moreover, most of them can only detect non-overlapping communities. In this paper, we propose a new community discovery method for multilayer networks, which leverages the interplay between layers and the unique topology in a layer to reveal overlapping communities. Through a comprehensive analysis of edge behaviors within and across layers, we first calculate the similarities for edges from the same layer and the cross layers. Then, by leveraging these similarities, we can construct a dendrogram for the multilayer networks that takes both the unique topological structure and the important interplay into consideration. Finally, by introducing a new community density metric for multilayer networks, we can cut the dendrogram to get the overlapping communities for these layers. By applying our method on both synthetic and real-world datasets, we demonstrate that our method has an accurate performance in discovering overlapping communities in multilayer networks. PMID:29694387
Finding overlapping communities in multilayer networks.

PubMed

Liu, Weiyi; Suzumura, Toyotaro; Ji, Hongyu; Hu, Guangmin

2018-01-01

Finding communities in multilayer networks is a vital step in understanding the structure and dynamics of these layers, where each layer represents a particular type of relationship between nodes in the natural world. However, most community discovery methods for multilayer networks may ignore the interplay between layers or the unique topological structure in a layer. Moreover, most of them can only detect non-overlapping communities. In this paper, we propose a new community discovery method for multilayer networks, which leverages the interplay between layers and the unique topology in a layer to reveal overlapping communities. Through a comprehensive analysis of edge behaviors within and across layers, we first calculate the similarities for edges from the same layer and the cross layers. Then, by leveraging these similarities, we can construct a dendrogram for the multilayer networks that takes both the unique topological structure and the important interplay into consideration. Finally, by introducing a new community density metric for multilayer networks, we can cut the dendrogram to get the overlapping communities for these layers. By applying our method on both synthetic and real-world datasets, we demonstrate that our method has an accurate performance in discovering overlapping communities in multilayer networks.
Geometry in Biomimetic Network: Double Gyroid to Pseudo-Single Gyroid in Nanohybrid Materials

NASA Astrophysics Data System (ADS)

Hsueh, Han-Yu; Ho, Rong-Ming; Hung, Yu-Chueh; Ling, Yi-Chun; Hasegawa, Hirokazu

2013-03-01

Biological systems have developed delicately arranged micro- and architectures to produce striking optical effects since millions of years ago. Inspired by the textures of butterfly wings with single gyroid (SG) structure, herein, we aim to fabricate biocompatible and robust materials with SG-like structure in nanometer size so as to give new materials with unprecedented optical properties for applications. Biommicking from the biological photonic structures of butterfly wings, a double gyroid (DG) structure in nanometer size is obtained from the self-assembly of polystyrene-b-poly(L-lactide) (PS-PLLA). To acquire robust backbone networks, inorganic networks in polymer matrix are fabricated by using the hydrolyzed PS-PLLA with DG structure as a template for sol-gel reaction. Owing to the soft polymer matrix, two co-continuous inorganic networks embedded in the polymer matrix can be rearranged by thermal annealing at temperature above the glass transition of the polymer. Consequently, the rearrangement of these inorganic networks leads the formation of SG-like structure possessing unique nanohybrids with ordered texture. This unique nanomaterials with SG-like structure is referred as a pseudo-SG (p-SG) nanohybrids.
Brain structural covariance network centrality in maltreated youth with PTSD and in maltreated youth resilient to PTSD.

PubMed

Sun, Delin; Haswell, Courtney C; Morey, Rajendra A; De Bellis, Michael D

2018-04-10

Child maltreatment is a major cause of pediatric posttraumatic stress disorder (PTSD). Previous studies have not investigated potential differences in network architecture in maltreated youth with PTSD and those resilient to PTSD. High-resolution magnetic resonance imaging brain scans at 3 T were completed in maltreated youth with PTSD (n = 31), without PTSD (n = 32), and nonmaltreated controls (n = 57). Structural covariance network architecture was derived from between-subject intraregional correlations in measures of cortical thickness in 148 cortical regions (nodes). Interregional positive partial correlations controlling for demographic variables were assessed, and those correlations that exceeded specified thresholds constituted connections in cortical brain networks. Four measures of network centrality characterized topology, and the importance of cortical regions (nodes) within the network architecture were calculated for each group. Permutation testing and principle component analysis method were employed to calculate between-group differences. Principle component analysis is a methodological improvement to methods used in previous brain structural covariance network studies. Differences in centrality were observed between groups. Larger centrality was found in maltreated youth with PTSD in the right posterior cingulate cortex; smaller centrality was detected in the right inferior frontal cortex compared to youth resilient to PTSD and controls, demonstrating network characteristics unique to pediatric maltreatment-related PTSD. Larger centrality was detected in right frontal pole in maltreated youth resilient to PTSD compared to youth with PTSD and controls, demonstrating structural covariance network differences in youth resilience to PTSD following maltreatment. Smaller centrality was found in the left posterior cingulate cortex and in the right inferior frontal cortex in maltreated youth compared to controls, demonstrating attributes of structural covariance network topology that is unique to experiencing maltreatment. This work is the first to identify cortical thickness-based structural covariance network differences between maltreated youth with and without PTSD. We demonstrated network differences in both networks unique to maltreated youth with PTSD and those resilient to PTSD. The networks identified are important for the successful attainment of age-appropriate social cognition, attention, emotional processing, and inhibitory control. Our findings in maltreated youth with PTSD versus those without PTSD suggest vulnerability mechanisms for developing PTSD.
The function of neurocognitive networks. Comment on “Understanding brain networks and brain organization” by Pessoa

NASA Astrophysics Data System (ADS)

Bressler, Steven L.

2014-09-01

Pessoa [5] has performed a valuable service by reviewing the extant literature on brain networks and making a number of interesting proposals about their cognitive function. The term function is at the core of understanding the brain networks of cognition, or neurocognitive networks (NCNs) [1]. The great Russian neuropsychologist, Luria [4], defined brain function as the common task executed by a distributed brain network of complex dynamic structures united by the demands of cognition. Casting Luria in a modern light, we can say that function emerges from the interactions of brain regions in NCNs as they dynamically self-organize according to cognitive demands. Pessoa rightly details the mapping between brain function and structure, emphasizing both its pluripotency (one structure having multiple functions) and degeneracy (many structures having the same function). However, he fails to consider the potential importance of a one-to-one mapping between NCNs and function. If NCNs are uniquely composed of specific collections of brain areas, then each NCN has a unique function determined by that composition.
Toward Developmental Connectomics of the Human Brain

PubMed Central

Cao, Miao; Huang, Hao; Peng, Yun; Dong, Qi; He, Yong

2016-01-01

Imaging connectomics based on graph theory has become an effective and unique methodological framework for studying structural and functional connectivity patterns of the developing brain. Normal brain development is characterized by continuous and significant network evolution throughout infancy, childhood, and adolescence, following specific maturational patterns. Disruption of these normal changes is associated with neuropsychiatric developmental disorders, such as autism spectrum disorders or attention-deficit hyperactivity disorder. In this review, we focused on the recent progresses regarding typical and atypical development of human brain networks from birth to early adulthood, using a connectomic approach. Specifically, by the time of birth, structural networks already exhibit adult-like organization, with global efficient small-world and modular structures, as well as hub regions and rich-clubs acting as communication backbones. During development, the structure networks are fine-tuned, with increased global integration and robustness and decreased local segregation, as well as the strengthening of the hubs. In parallel, functional networks undergo more dramatic changes during maturation, with both increased integration and segregation during development, as brain hubs shift from primary regions to high order functioning regions, and the organization of modules transitions from a local anatomical emphasis to a more distributed architecture. These findings suggest that structural networks develop earlier than functional networks; meanwhile functional networks demonstrate more dramatic maturational changes with the evolution of structural networks serving as the anatomical backbone. In this review, we also highlighted topologically disorganized characteristics in structural and functional brain networks in several major developmental neuropsychiatric disorders (e.g., autism spectrum disorders, attention-deficit hyperactivity disorder and developmental dyslexia). Collectively, we showed that delineation of the brain network from a connectomics perspective offers a unique and refreshing view of both normal development and neuropsychiatric disorders. PMID:27064378
Control Centrality and Hierarchical Structure in Complex Networks

PubMed Central

Liu, Yang-Yu; Slotine, Jean-Jacques; Barabási, Albert-László

2012-01-01

We introduce the concept of control centrality to quantify the ability of a single node to control a directed weighted network. We calculate the distribution of control centrality for several real networks and find that it is mainly determined by the network’s degree distribution. We show that in a directed network without loops the control centrality of a node is uniquely determined by its layer index or topological position in the underlying hierarchical structure of the network. Inspired by the deep relation between control centrality and hierarchical structure in a general directed network, we design an efficient attack strategy against the controllability of malicious networks. PMID:23028542
Low-rank network decomposition reveals structural characteristics of small-world networks

NASA Astrophysics Data System (ADS)

Barranca, Victor J.; Zhou, Douglas; Cai, David

2015-12-01

Small-world networks occur naturally throughout biological, technological, and social systems. With their prevalence, it is particularly important to prudently identify small-world networks and further characterize their unique connection structure with respect to network function. In this work we develop a formalism for classifying networks and identifying small-world structure using a decomposition of network connectivity matrices into low-rank and sparse components, corresponding to connections within clusters of highly connected nodes and sparse interconnections between clusters, respectively. We show that the network decomposition is independent of node indexing and define associated bounded measures of connectivity structure, which provide insight into the clustering and regularity of network connections. While many existing network characterizations rely on constructing benchmark networks for comparison or fail to describe the structural properties of relatively densely connected networks, our classification relies only on the intrinsic network structure and is quite robust with respect to changes in connection density, producing stable results across network realizations. Using this framework, we analyze several real-world networks and reveal new structural properties, which are often indiscernible by previously established characterizations of network connectivity.
Cooperative Tertiary Interaction Network Guides RNA Folding

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

Behrouzi, Reza; Roh, Joon Ho; Kilburn, Duncan

2013-04-08

Noncoding RNAs form unique 3D structures, which perform many regulatory functions. To understand how RNAs fold uniquely despite a small number of tertiary interaction motifs, we mutated the major tertiary interactions in a group I ribozyme by single-base substitutions. The resulting perturbations to the folding energy landscape were measured using SAXS, ribozyme activity, hydroxyl radical footprinting, and native PAGE. Double- and triple-mutant cycles show that most tertiary interactions have a small effect on the stability of the native state. Instead, the formation of core and peripheral structural motifs is cooperatively linked in near-native folding intermediates, and this cooperativity depends onmore » the native helix orientation. The emergence of a cooperative interaction network at an early stage of folding suppresses nonnative structures and guides the search for the native state. We suggest that cooperativity in noncoding RNAs arose from natural selection of architectures conducive to forming a unique, stable fold.« less
Uniform rotating field network structure to efficiently package a magnetic bubble domain memory

NASA Technical Reports Server (NTRS)

Murray, Glen W. (Inventor); Chen, Thomas T. (Inventor); Wolfshagen, Ronald G. (Inventor); Ypma, John E. (Inventor)

1978-01-01

A unique and compact open coil rotating magnetic field network structure to efficiently package an array of bubble domain devices is disclosed. The field network has a configuration which effectively enables selected bubble domain devices from the array to be driven in a vertical magnetic field and in an independent and uniform horizontal rotating magnetic field. The field network is suitably adapted to minimize undesirable inductance effects, improve capabilities of heat dissipation, and facilitate repair or replacement of a bubble device.
Structure Shapes Dynamics and Directionality in Diverse Brain Networks: Mathematical Principles and Empirical Confirmation in Three Species

NASA Astrophysics Data System (ADS)

Moon, Joon-Young; Kim, Junhyeok; Ko, Tae-Wook; Kim, Minkyung; Iturria-Medina, Yasser; Choi, Jee-Hyun; Lee, Joseph; Mashour, George A.; Lee, Uncheol

2017-04-01

Identifying how spatially distributed information becomes integrated in the brain is essential to understanding higher cognitive functions. Previous computational and empirical studies suggest a significant influence of brain network structure on brain network function. However, there have been few analytical approaches to explain the role of network structure in shaping regional activities and directionality patterns. In this study, analytical methods are applied to a coupled oscillator model implemented in inhomogeneous networks. We first derive a mathematical principle that explains the emergence of directionality from the underlying brain network structure. We then apply the analytical methods to the anatomical brain networks of human, macaque, and mouse, successfully predicting simulation and empirical electroencephalographic data. The results demonstrate that the global directionality patterns in resting state brain networks can be predicted solely by their unique network structures. This study forms a foundation for a more comprehensive understanding of how neural information is directed and integrated in complex brain networks.
Vibration reduction for smart periodic structures via periodic piezoelectric arrays with nonlinear interleaved-switched electronic networks

NASA Astrophysics Data System (ADS)

Bao, Bin; Guyomar, Daniel; Lallart, Mickaël

2017-01-01

Smart periodic structures covered by periodically distributed piezoelectric patches have drawn more and more attention in recent years for wave propagation attenuation and corresponding structural vibration suppression. Since piezoelectric materials are special type of energy conversion materials that link mechanical characteristics with electrical characteristics, shunt circuits coupled with such materials play a key role in the wave propagation and/or vibration control performance in smart periodic structures. Conventional shunt circuit designs utilize resistive shunt (R-shunt) and resonant shunt (RL-shunt). More recently, semi-passive nonlinear approaches have also been developed for efficiently controlling the vibrations of such structures. In this paper, an innovative smart periodic beam structure with nonlinear interleaved-switched electric networks based on synchronized switching damping on inductor (SSDI) is proposed and investigated for vibration reduction and wave propagation attenuation. Different from locally resonant band gap mechanism forming narrow band gaps around the desired resonant frequencies, the proposed interleaved electrical networks can induce new broadly low-frequency stop bands and broaden primitive Bragg stop bands by virtue of unique interleaved electrical configurations and the SSDI technique which has the unique feature of realizing automatic impedance adaptation with a small inductance. Finite element modeling of a Timoshenko electromechanical beam structure is also presented for validating dispersion properties of the structure. Both theoretical and experimental results demonstrate that the proposed beam structure not only shows better vibration and wave propagation attenuation than the smart beam structure with independent switched networks, but also has technical simplicity of requiring only half of the number of switches than the independent switched network needs.
Cooperation dynamics of generalized reciprocity in state-based social dilemmas

NASA Astrophysics Data System (ADS)

Stojkoski, Viktor; Utkovski, Zoran; Basnarkov, Lasko; Kocarev, Ljupco

2018-05-01

We introduce a framework for studying social dilemmas in networked societies where individuals follow a simple state-based behavioral mechanism based on generalized reciprocity, which is rooted in the principle "help anyone if helped by someone." Within this general framework, which applies to a wide range of social dilemmas including, among others, public goods, donation, and snowdrift games, we study the cooperation dynamics on a variety of complex network examples. By interpreting the studied model through the lenses of nonlinear dynamical systems, we show that cooperation through generalized reciprocity always emerges as the unique attractor in which the overall level of cooperation is maximized, while simultaneously exploitation of the participating individuals is prevented. The analysis elucidates the role of the network structure, here captured by a local centrality measure which uniquely quantifies the propensity of the network structure to cooperation by dictating the degree of cooperation displayed both at the microscopic and macroscopic level. We demonstrate the applicability of the analysis on a practical example by considering an interaction structure that couples a donation process with a public goods game.
Improving link prediction in complex networks by adaptively exploiting multiple structural features of networks

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

PubMed

Binder, Jens F; Buglass, Sarah L; Betts, Lucy R; Underwood, Jean D M

2017-10-01

Data from online social networks carry enormous potential for psychological research, yet their use and the ethical implications thereof are currently hotly debated. The present work aims to outline in detail the unique information richness of this data type and, in doing so, to support researchers when deciding on ethically appropriate ways of collecting, storing, publishing, and sharing data from online sources. Focusing on the very nature of social networks, their structural characteristics, and depth of information, we provide a detailed and accessible account of the challenges associated with data management and data storage. In particular, the general nonanonymity of network data sets is discussed, and an approach is developed to quantify the level of uniqueness that a particular online network bestows upon the individual maintaining it. Using graph enumeration techniques, we show that comparatively sparse information on a network is suitable as a sociometric marker that allows for the identification of an individual from the global population of online users. The impossibility of anonymizing specific types of network data carries implications for ethical guidelines and research practice. At the same time, network uniqueness opens up opportunities for novel research in psychology. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
A Novel Characterization of Amalgamated Networks in Natural Systems

PubMed Central

Barranca, Victor J.; Zhou, Douglas; Cai, David

2015-01-01

Densely-connected networks are prominent among natural systems, exhibiting structural characteristics often optimized for biological function. To reveal such features in highly-connected networks, we introduce a new network characterization determined by a decomposition of network-connectivity into low-rank and sparse components. Based on these components, we discover a new class of networks we define as amalgamated networks, which exhibit large functional groups and dense connectivity. Analyzing recent experimental findings on cerebral cortex, food-web, and gene regulatory networks, we establish the unique importance of amalgamated networks in fostering biologically advantageous properties, including rapid communication among nodes, structural stability under attacks, and separation of network activity into distinct functional modules. We further observe that our network characterization is scalable with network size and connectivity, thereby identifying robust features significant to diverse physical systems, which are typically undetectable by conventional characterizations of connectivity. We expect that studying the amalgamation properties of biological networks may offer new insights into understanding their structure-function relationships. PMID:26035066
Unique sodium phosphosilicate glasses designed through extended topological constraint theory.

PubMed

Zeng, Huidan; Jiang, Qi; Liu, Zhao; Li, Xiang; Ren, Jing; Chen, Guorong; Liu, Fude; Peng, Shou

2014-05-15

Sodium phosphosilicate glasses exhibit unique properties with mixed network formers, and have various potential applications. However, proper understanding on the network structures and property-oriented methodology based on compositional changes are lacking. In this study, we have developed an extended topological constraint theory and applied it successfully to analyze the composition dependence of glass transition temperature (Tg) and hardness of sodium phosphosilicate glasses. It was found that the hardness and Tg of glasses do not always increase with the content of SiO2, and there exist maximum hardness and Tg at a certain content of SiO2. In particular, a unique glass (20Na2O-17SiO2-63P2O5) exhibits a low glass transition temperature (589 K) but still has relatively high hardness (4.42 GPa) mainly due to the high fraction of highly coordinated network former Si((6)). Because of its convenient forming and manufacturing, such kind of phosphosilicate glasses has a lot of valuable applications in optical fibers, optical amplifiers, biomaterials, and fuel cells. Also, such methodology can be applied to other types of phosphosilicate glasses with similar structures.
Congenital blindness is associated with large-scale reorganization of anatomical networks.

PubMed

Hasson, Uri; Andric, Michael; Atilgan, Hicret; Collignon, Olivier

2016-03-01

Blindness is a unique model for understanding the role of experience in the development of the brain's functional and anatomical architecture. Documenting changes in the structure of anatomical networks for this population would substantiate the notion that the brain's core network-level organization may undergo neuroplasticity as a result of life-long experience. To examine this issue, we compared whole-brain networks of regional cortical-thickness covariance in early blind and matched sighted individuals. This covariance is thought to reflect signatures of integration between systems involved in similar perceptual/cognitive functions. Using graph-theoretic metrics, we identified a unique mode of anatomical reorganization in the blind that differed from that found for sighted. This was seen in that network partition structures derived from subgroups of blind were more similar to each other than they were to partitions derived from sighted. Notably, after deriving network partitions, we found that language and visual regions tended to reside within separate modules in sighted but showed a pattern of merging into shared modules in the blind. Our study demonstrates that early visual deprivation triggers a systematic large-scale reorganization of whole-brain cortical-thickness networks, suggesting changes in how occipital regions interface with other functional networks in the congenitally blind. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.
Using graphene networks to build bioinspired self-monitoring ceramics

PubMed Central

Picot, Olivier T.; Rocha, Victoria G.; Ferraro, Claudio; Ni, Na; D'Elia, Eleonora; Meille, Sylvain; Chevalier, Jerome; Saunders, Theo; Peijs, Ton; Reece, Mike J.; Saiz, Eduardo

2017-01-01

The properties of graphene open new opportunities for the fabrication of composites exhibiting unique structural and functional capabilities. However, to achieve this goal we should build materials with carefully designed architectures. Here, we describe the fabrication of ceramic-graphene composites by combining graphene foams with pre-ceramic polymers and spark plasma sintering. The result is a material containing an interconnected, microscopic network of very thin (20–30 nm), electrically conductive, carbon interfaces. This network generates electrical conductivities up to two orders of magnitude higher than those of other ceramics with similar graphene or carbon nanotube contents and can be used to monitor ‘in situ' structural integrity. In addition, it directs crack propagation, promoting stable crack growth and increasing the fracture resistance by an order of magnitude. These results demonstrate that the rational integration of nanomaterials could be a fruitful path towards building composites combining unique mechanical and functional performances. PMID:28181518
Topology of Innovation Spaces in the Knowledge Networks Emerging through Questions-And-Answers

PubMed Central

Andjelković, Miroslav; Tadić, Bosiljka; Mitrović Dankulov, Marija; Rajković, Milan; Melnik, Roderick

2016-01-01

The communication processes of knowledge creation represent a particular class of human dynamics where the expertise of individuals plays a substantial role, thus offering a unique possibility to study the structure of knowledge networks from online data. Here, we use the empirical evidence from questions-and-answers in mathematics to analyse the emergence of the network of knowledge contents (or tags) as the individual experts use them in the process. After removing extra edges from the network-associated graph, we apply the methods of algebraic topology of graphs to examine the structure of higher-order combinatorial spaces in networks for four consecutive time intervals. We find that the ranking distributions of the suitably scaled topological dimensions of nodes fall into a unique curve for all time intervals and filtering levels, suggesting a robust architecture of knowledge networks. Moreover, these networks preserve the logical structure of knowledge within emergent communities of nodes, labeled according to a standard mathematical classification scheme. Further, we investigate the appearance of new contents over time and their innovative combinations, which expand the knowledge network. In each network, we identify an innovation channel as a subgraph of triangles and larger simplices to which new tags attach. Our results show that the increasing topological complexity of the innovation channels contributes to network’s architecture over different time periods, and is consistent with temporal correlations of the occurrence of new tags. The methodology applies to a wide class of data with the suitable temporal resolution and clearly identified knowledge-content units. PMID:27171149

Terminal-oriented computer-communication networks.

NASA Technical Reports Server (NTRS)

Schwartz, M.; Boorstyn, R. R.; Pickholtz, R. L.

1972-01-01

Four examples of currently operating computer-communication networks are described in this tutorial paper. They include the TYMNET network, the GE Information Services network, the NASDAQ over-the-counter stock-quotation system, and the Computer Sciences Infonet. These networks all use programmable concentrators for combining a multiplicity of terminals. Included in the discussion for each network is a description of the overall network structure, the handling and transmission of messages, communication requirements, routing and reliability consideration where applicable, operating data and design specifications where available, and unique design features in the area of computer communications.
Unattended wireless proximity sensor networks for counterterrorism, force protection, littoral environments, PHM, and tamper monitoring ground applications

NASA Astrophysics Data System (ADS)

Forcier, Bob

2003-09-01

This paper describes a digital-ultrasonic ground network, which forms an unique "unattended mote sensor system" for monitoring the environment, personnel, facilities, vehicles, power generation systems or aircraft in Counter-Terrorism, Force Protection, Prognostic Health Monitoring (PHM) and other ground applications. Unattended wireless smart sensor/tags continuously monitor the environment and provide alerts upon changes or disruptions to the environment. These wireless smart sensor/tags are networked utilizing ultrasonic wireless motes, hybrid RF/Ultrasonic Network Nodes and Base Stations. The network is monitored continuously with a 24/7 remote and secure monitoring system. This system utilizes physical objects such as a vehicle"s structure or a building to provide the media for two way secure communication of key metrics and sensor data and eliminates the "blind spots" that are common in RF solutions because of structural elements of buildings, etc. The digital-ultrasonic sensors have networking capability and a 32-bit identifier, which provide a platform for a robust data acquisition (DAQ) for a large amount of sensors. In addition, the network applies a unique "signature" of the environment by comparing sensor-to-sensor data to pick up on minute changes, which would signal an invasion of unknown elements or signal a potential tampering in equipment or facilities. The system accommodates satellite and other secure network uplinks in either RF or UWB protocols. The wireless sensors can be dispersed by ground or air maneuvers. In addition, the sensors can be incorporated into the structure or surfaces of vehicles, buildings, or clothing of field personnel.
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
Co-residence patterns in hunter-gatherer societies show unique human social structure.

PubMed

Hill, Kim R; Walker, Robert S; Bozicević, Miran; Eder, James; Headland, Thomas; Hewlett, Barry; Hurtado, A Magdalena; Marlowe, Frank; Wiessner, Polly; Wood, Brian

2011-03-11

Contemporary humans exhibit spectacular biological success derived from cumulative culture and cooperation. The origins of these traits may be related to our ancestral group structure. Because humans lived as foragers for 95% of our species' history, we analyzed co-residence patterns among 32 present-day foraging societies (total n = 5067 individuals, mean experienced band size = 28.2 adults). We found that hunter-gatherers display a unique social structure where (i) either sex may disperse or remain in their natal group, (ii) adult brothers and sisters often co-reside, and (iii) most individuals in residential groups are genetically unrelated. These patterns produce large interaction networks of unrelated adults and suggest that inclusive fitness cannot explain extensive cooperation in hunter-gatherer bands. However, large social networks may help to explain why humans evolved capacities for social learning that resulted in cumulative culture.
Stretchable Platinum Network-Based Transparent Electrodes for Highly Sensitive Wearable Electronics.

PubMed

Wang, Yuting; Cheng, Jing; Xing, Yan; Shahid, Muhammad; Nishijima, Hiroki; Pan, Wei

2017-07-01

A platinum network-based transparent electrode has been fabricated by electrospinning. The unique nanobelt structured electrode demonstrates low sheet resistance (about 16 Ω sq -1 ) and high transparency of 80% and excellent flexibility. One of the most interesting demonstrations of this Pt nanobelt electrode is its excellent reversibly resilient characteristic. The electric conductivity of the flexible Pt electrode can recover to its initial value after 160% extending and this performance is repeatable and stable. The good linear relationship between the resistance and strain of the unique structured Pt electrode makes it possible to assemble a wearable high sensitive strain sensor. Present reported Pt nanobelt electrode also reveals potential applications in electrode for flexible fuel cells and highly transparent ultraviolet (UV) sensors. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Structural and functional connectivity underlying grey matter covariance: impact of developmental insult.

PubMed

Paquola, Casey; Bennett, Maxwell; Lagopoulos, Jim

2018-05-15

Structural covariance networks (SCNs) may offer unique insights into the developmental impact of childhood maltreatment because they are thought to reflect coordinated maturation of distinct grey matter regions. T1-weighted magnetic resonance images were acquired from 121 young people with emerging mental illness. Diffusion weighted and resting state functional imaging was also acquired from a random subset of the participants (n=62). Ten study-specific SCNs were identified using a whole brain grey matter independent component analysis. The effects of childhood maltreatment and age on average grey matter density and the expression of each SCN were calculated. Childhood maltreatment was linked to age-related decreases in grey matter density across a SCN that overlapped with the default mode and fronto-parietal networks. Resting state functional connectivity and structural connectivity were calculated in the study-specific SCN and across the whole brain. Grey matter covariance was significantly correlated with rsFC across the SCN, and rsFC fully mediated the relationship between grey matter covariance and structural connectivity in the non-maltreated group. A unique association of grey matter covariance with structural connectivity was detected amongst individuals with a history of childhood maltreatment. Perturbation of grey matter development across the default mode and fronto-parietal networks following childhood maltreatment may have significant implications for mental well-being, given the networks' roles in self-referential activity. Cross-modal comparisons suggest reduced grey matter following childhood maltreatment could arise from deficient functional activity earlier in life.
Analyzing heterogeneity in the effects of physical activity in children on social network structure and peer selection dynamics

PubMed Central

Henry, Teague; Gesell, Sabina B.; Ip, Edward H.

2016-01-01

Background Social networks influence children and adolescents’ physical activity. The focus of this paper is to examine the differences in the effects of physical activity on friendship selection, with eye to the implications on physical activity interventions for young children. Network interventions to increase physical activity are warranted but have not been conducted. Prior to implementing a network intervention in the field, it is important to understand potential heterogeneities in the effects that activity level have on network structure. In this study, the associations between activity level and cross sectional network structure, and activity level and change in network structure are assessed. Methods We studied a real-world friendship network among 81 children (average age 7.96 years) who lived in low SES neighborhoods, attended public schools, and attended one of two structured aftercare programs, of which one has existed and the other was new. We used the exponential random graph model (ERGMs) and its longitudinal extension to evaluate the association between activity level and various demographic factors in having, forming, and dissolving friendship. Due to heterogeneity between the friendship networks within the aftercare programs, separate analyses were conducted for each network. Results There was heterogeneity in the effect of physical activity on both cross sectional network structure and the formation and dissolution processes, both across time and between networks. Conclusions Network analysis could be used to assess the unique structure and dynamics of a social network before an intervention is implemented, so as to optimize the effects of the network intervention for increasing childhood physical activity. Additionally, if peer selection processes are changing within a network, a static network intervention strategy for childhood physical activity could become inefficient as the network evolves. PMID:27867518
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
Visual analysis of large heterogeneous social networks by semantic and structural abstraction.

PubMed

Shen, Zeqian; Ma, Kwan-Liu; Eliassi-Rad, Tina

2006-01-01

Social network analysis is an active area of study beyond sociology. It uncovers the invisible relationships between actors in a network and provides understanding of social processes and behaviors. It has become an important technique in a variety of application areas such as the Web, organizational studies, and homeland security. This paper presents a visual analytics tool, OntoVis, for understanding large, heterogeneous social networks, in which nodes and links could represent different concepts and relations, respectively. These concepts and relations are related through an ontology (also known as a schema). OntoVis is named such because it uses information in the ontology associated with a social network to semantically prune a large, heterogeneous network. In addition to semantic abstraction, OntoVis also allows users to do structural abstraction and importance filtering to make large networks manageable and to facilitate analytic reasoning. All these unique capabilities of OntoVis are illustrated with several case studies.
Toward link predictability of complex networks

PubMed Central

Lü, Linyuan; Pan, Liming; Zhou, Tao; Zhang, Yi-Cheng; Stanley, H. Eugene

2015-01-01

The organization of real networks usually embodies both regularities and irregularities, and, in principle, the former can be modeled. The extent to which the formation of a network can be explained coincides with our ability to predict missing links. To understand network organization, we should be able to estimate link predictability. We assume that the regularity of a network is reflected in the consistency of structural features before and after a random removal of a small set of links. Based on the perturbation of the adjacency matrix, we propose a universal structural consistency index that is free of prior knowledge of network organization. Extensive experiments on disparate real-world networks demonstrate that (i) structural consistency is a good estimation of link predictability and (ii) a derivative algorithm outperforms state-of-the-art link prediction methods in both accuracy and robustness. This analysis has further applications in evaluating link prediction algorithms and monitoring sudden changes in evolving network mechanisms. It will provide unique fundamental insights into the above-mentioned academic research fields, and will foster the development of advanced information filtering technologies of interest to information technology practitioners. PMID:25659742
Understanding Classrooms through Social Network Analysis: A Primer for Social Network Analysis in Education Research

PubMed Central

Wiggins, Benjamin L.; Goodreau, Steven M.

2014-01-01

Social interactions between students are a major and underexplored part of undergraduate education. Understanding how learning relationships form in undergraduate classrooms, as well as the impacts these relationships have on learning outcomes, can inform educators in unique ways and improve educational reform. Social network analysis (SNA) provides the necessary tool kit for investigating questions involving relational data. We introduce basic concepts in SNA, along with methods for data collection, data processing, and data analysis, using a previously collected example study on an undergraduate biology classroom as a tutorial. We conduct descriptive analyses of the structure of the network of costudying relationships. We explore generative processes that create observed study networks between students and also test for an association between network position and success on exams. We also cover practical issues, such as the unique aspects of human subjects review for network studies. Our aims are to convince readers that using SNA in classroom environments allows rich and informative analyses to take place and to provide some initial tools for doing so, in the process inspiring future educational studies incorporating relational data. PMID:26086650
Deterministic ripple-spreading model for complex networks.

PubMed

Hu, Xiao-Bing; Wang, Ming; Leeson, Mark S; Hines, Evor L; Di Paolo, Ezequiel

2011-04-01

This paper proposes a deterministic complex network model, which is inspired by the natural ripple-spreading phenomenon. The motivations and main advantages of the model are the following: (i) The establishment of many real-world networks is a dynamic process, where it is often observed that the influence of a few local events spreads out through nodes, and then largely determines the final network topology. Obviously, this dynamic process involves many spatial and temporal factors. By simulating the natural ripple-spreading process, this paper reports a very natural way to set up a spatial and temporal model for such complex networks. (ii) Existing relevant network models are all stochastic models, i.e., with a given input, they cannot output a unique topology. Differently, the proposed ripple-spreading model can uniquely determine the final network topology, and at the same time, the stochastic feature of complex networks is captured by randomly initializing ripple-spreading related parameters. (iii) The proposed model can use an easily manageable number of ripple-spreading related parameters to precisely describe a network topology, which is more memory efficient when compared with traditional adjacency matrix or similar memory-expensive data structures. (iv) The ripple-spreading model has a very good potential for both extensions and applications.
Residual Network Data Structures in Android Devices

DTIC Science & Technology

2011-09-01

Apple’s iOS, Google’s Android, RIM’s Blackberry and Nokia’s Symbian. Each Smartphone presents unique characteristics for forensic examiners. In...another. • Home Agent: A router on mobile node’s home network that tunnels traffic to mobile node when not on home network. Also maintains mobile nodes...Address notification to the Home Agent. When traffic arrives at the Home Agent for the mobile node, the Home Agent tunnels the traffic to the Care-of
Field Measurement-Based System Identification and Dynamic Response Prediction of a Unique MIT Building.

PubMed

Cha, Young-Jin; Trocha, Peter; Büyüköztürk, Oral

2016-07-01

Tall buildings are ubiquitous in major cities and house the homes and workplaces of many individuals. However, relatively few studies have been carried out to study the dynamic characteristics of tall buildings based on field measurements. In this paper, the dynamic behavior of the Green Building, a unique 21-story tall structure located on the campus of the Massachusetts Institute of Technology (MIT, Cambridge, MA, USA), was characterized and modeled as a simplified lumped-mass beam model (SLMM), using data from a network of accelerometers. The accelerometer network was used to record structural responses due to ambient vibrations, blast loading, and the October 16th 2012 earthquake near Hollis Center (ME, USA). Spectral and signal coherence analysis of the collected data was used to identify natural frequencies, modes, foundation rocking behavior, and structural asymmetries. A relation between foundation rocking and structural natural frequencies was also found. Natural frequencies and structural acceleration from the field measurements were compared with those predicted by the SLMM which was updated by inverse solving based on advanced multiobjective optimization methods using the measured structural responses and found to have good agreement.
Field Measurement-Based System Identification and Dynamic Response Prediction of a Unique MIT Building

PubMed Central

Cha, Young-Jin; Trocha, Peter; Büyüköztürk, Oral

2016-01-01

Tall buildings are ubiquitous in major cities and house the homes and workplaces of many individuals. However, relatively few studies have been carried out to study the dynamic characteristics of tall buildings based on field measurements. In this paper, the dynamic behavior of the Green Building, a unique 21-story tall structure located on the campus of the Massachusetts Institute of Technology (MIT, Cambridge, MA, USA), was characterized and modeled as a simplified lumped-mass beam model (SLMM), using data from a network of accelerometers. The accelerometer network was used to record structural responses due to ambient vibrations, blast loading, and the October 16th 2012 earthquake near Hollis Center (ME, USA). Spectral and signal coherence analysis of the collected data was used to identify natural frequencies, modes, foundation rocking behavior, and structural asymmetries. A relation between foundation rocking and structural natural frequencies was also found. Natural frequencies and structural acceleration from the field measurements were compared with those predicted by the SLMM which was updated by inverse solving based on advanced multiobjective optimization methods using the measured structural responses and found to have good agreement. PMID:27376303
Structure of Radical-Induced Cell Death1 Hub Domain Reveals a Common αα-Scaffold for Disorder in Transcriptional Networks.

PubMed

Bugge, Katrine; Staby, Lasse; Kemplen, Katherine R; O'Shea, Charlotte; Bendsen, Sidsel K; Jensen, Mikael K; Olsen, Johan G; Skriver, Karen; Kragelund, Birthe B

2018-05-01

Communication within cells relies on a few protein nodes called hubs, which organize vast interactomes with many partners. Frequently, hub proteins are intrinsically disordered conferring multi-specificity and dynamic communication. Conversely, folded hub proteins may organize networks using disordered partners. In this work, the structure of the RST domain, a unique folded hub, is solved by nuclear magnetic resonance spectroscopy and small-angle X-ray scattering, and its complex with a region of the transcription factor DREB2A is provided through data-driven HADDOCK modeling and mutagenesis analysis. The RST fold is unique, but similar structures are identified in the PAH (paired amphipathic helix), TAFH (TATA-box-associated factor homology), and NCBD (nuclear coactivator binding domain) domains. We designate them as a group the αα hubs, as they share an αα-hairpin super-secondary motif, which serves as an organizing platform for malleable helices of varying topology. This allows for partner adaptation, exclusion, and selection. Our findings provide valuable insights into structural features enabling signaling fidelity. Copyright © 2018 Elsevier Ltd. All rights reserved.
On the design of wave digital filters with low sensitivity properties.

NASA Technical Reports Server (NTRS)

Renner, K.; Gupta, S. C.

1973-01-01

The wave digital filter patterned after doubly terminated maximum available power (MAP) networks by means of the Richard's transformation has been shown to have low-coefficient-sensitivity properties. This paper examines the exact nature of the relationship between the wave-digital-filter structure and the MAP networks and how the sensitivity property arises, which permits implementation of the digital structure with a lower coefficient word length than that possible with the conventional structures. The proper design procedure is specified and the nature of the unique complementary outputs is discussed. Finally, an example is considered which illustrates the design, the conversion techniques, and the low sensitivity properties.
Analysis of quasi-periodic pore-network structure of centric marine diatom frustules

NASA Astrophysics Data System (ADS)

Cohoon, Gregory A.; Alvarez, Christine E.; Meyers, Keith; Deheyn, Dimitri D.; Hildebrand, Mark; Kieu, Khanh; Norwood, Robert A.

2015-03-01

Diatoms are a common type of phytoplankton characterized by their silica exoskeleton known as a frustule. The diatom frustule is composed of two valves and a series of connecting girdle bands. Each diatom species has a unique frustule shape and valves in particular species display an intricate pattern of pores resembling a photonic crystal structure. We used several numerical techniques to analyze the periodic and quasi-periodic valve pore-network structure in diatoms of the Coscinodiscophyceae order. We quantitatively identify defect locations and pore spacing in the valve and use this information to better understand the optical and biological properties of the diatom.
Seafloor massive sulfide deposits support unique megafaunal assemblages: Implications for seabed mining and conservation.

PubMed

Boschen, Rachel E; Rowden, Ashley A; Clark, Malcolm R; Pallentin, Arne; Gardner, Jonathan P A

2016-04-01

Mining of seafloor massive sulfides (SMS) is imminent, but the ecology of assemblages at SMS deposits is poorly known. Proposed conservation strategies include protected areas to preserve biodiversity at risk from mining impacts. Determining site suitability requires biological characterisation of the mine site and protected area(s). Video survey of a proposed mine site and protected area off New Zealand revealed unique megafaunal assemblages at the mine site. Significant relationships were identified between assemblage structure and environmental conditions, including hydrothermal features. Unique assemblages occurred at both active and inactive chimneys and are particularly at risk from mining-related impacts. The occurrence of unique assemblages at the mine site suggests that the proposed protected area is insufficient alone and should instead form part of a network. These results provide support for including hydrothermally active and inactive features within networks of protected areas and emphasise the need for quantitative survey data of proposed sites. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
Exploration of the nature of a unique natural polymer-based thermosensitive hydrogel.

PubMed

Lu, Shanling; Yang, Yuhong; Yao, Jinrong; Shao, Zhengzhong; Chen, Xin

2016-01-14

The chitosan (CS)/β-glycerol phosphate (GP) system is a heat induced gelling system with a promising potential application, such as an injectable biomedical material. Unlike most thermosensitive gelling systems, the CS/GP system is only partially reversible. That is once the hydrogel is fully matured, it only softens but cannot go back to its initial liquid state when cooled down. Here, we perform both the small and large amplitude oscillatory shear (SAOS and LAOS) tests on the fully matured CS/GP hydrogel samples at a variety of temperatures within the cooling process. The purpose of such tests is to investigate the structural change of the hydrogel network and thus to understand the possible gelation mechanism of this unique thermosensitive hydrogel. From the LAOS results and the further analysis with the Chebyshev expansion method, it shows that the CS/GP hydrogel is composed of a colloidal network dominated by hydrophobic interactions at high temperature, and gradually turns into a flexible network dominated by hydrogen bonding when the temperature goes down. Therefore, we may conclude that LOAS is a powerful tool to study the nonlinear behaviour of a polymer system that is closely related to its structure, and as a practical example, we achieve a clearer vision on the gelation mechanism of the unique CS/GP thermosensitive hydrogel on the basis of considerable previous studies and assumptions in this laboratory and other research groups.

Dynamic Network Drivers of Seizure Generation, Propagation and Termination in Human Neocortical Epilepsy

PubMed Central

Khambhati, Ankit N.; Davis, Kathryn A.; Oommen, Brian S.; Chen, Stephanie H.; Lucas, Timothy H.; Litt, Brian; Bassett, Danielle S.

2015-01-01

The epileptic network is characterized by pathologic, seizure-generating ‘foci’ embedded in a web of structural and functional connections. Clinically, seizure foci are considered optimal targets for surgery. However, poor surgical outcome suggests a complex relationship between foci and the surrounding network that drives seizure dynamics. We developed a novel technique to objectively track seizure states from dynamic functional networks constructed from intracranial recordings. Each dynamical state captures unique patterns of network connections that indicate synchronized and desynchronized hubs of neural populations. Our approach suggests that seizures are generated when synchronous relationships near foci work in tandem with rapidly changing desynchronous relationships from the surrounding epileptic network. As seizures progress, topographical and geometrical changes in network connectivity strengthen and tighten synchronous connectivity near foci—a mechanism that may aid seizure termination. Collectively, our observations implicate distributed cortical structures in seizure generation, propagation and termination, and may have practical significance in determining which circuits to modulate with implantable devices. PMID:26680762
Data quality of seismic records from the Tohoku, Japan earthquake as recorded across the Albuquerque Seismological Laboratory networks

USGS Publications Warehouse

Ringler, A.T.; Gee, L.S.; Marshall, B.; Hutt, C.R.; Storm, T.

2012-01-01

Great earthquakes recorded across modern digital seismographic networks, such as the recent Tohoku, Japan, earthquake on 11 March 2011 (Mw = 9.0), provide unique datasets that ultimately lead to a better understanding of the Earth's structure (e.g., Pesicek et al. 2008) and earthquake sources (e.g., Ammon et al. 2011). For network operators, such events provide the opportunity to look at the performance across their entire network using a single event, as the ground motion records from the event will be well above every station's noise floor.
The Structure of Male Adolescent Peer Networks and Risk for Intimate Partner Violence Perpetration: Findings from a National Sample

PubMed Central

Casey, Erin A.; Beadnell, Blair

2015-01-01

Although peer networks have been implicated as influential in a range of adolescent behaviors, little is known about relationships between peer network structures and risk for intimate partner violence (IPV) among youth. This study is a descriptive analysis of how peer network “types” may be related to subsequent risk for IPV perpetration among adolescents using data from 3,030 male respondents to the National Longitudinal Study of Adolescent Health. Sampled youth were a mean of 16 years of age when surveyed about the nature of their peer networks, and 21.9 when asked to report about IPV perpetration in their adolescent and early adulthood relationships. A latent class analysis of the size, structure, gender composition and delinquency level of friendship groups identified four unique profiles of peer network structures. Men in the group type characterized by small, dense, mostly male peer networks with higher levels of delinquent behavior reported higher rates of subsequent IPV perpetration than men whose adolescent network type was characterized by large, loosely connected groups of less delinquent male and female friends. Other factors known to be antecedents and correlates of IPV perpetration varied in their distribution across the peer group types, suggesting that different configurations of risk for relationship aggression can be found across peer networks. Implications for prevention programming and future research are addressed. PMID:20422351
Structure of Particle Networks in Capillary Suspensions with Wetting and Nonwetting Fluids

PubMed Central

2016-01-01

The mechanical properties of a suspension can be dramatically altered by adding a small amount of a secondary fluid that is immiscible with the bulk phase. The substantial changes in the strength of these capillary suspensions arise due to the capillary force inducing a percolating particle network. Spatial information on the structure of the particle networks is obtained using confocal microscopy. It is possible, for the first time, to visualize the different types of percolating structures of capillary suspensions in situ. These capillary networks are unique from other types of particulate networks due to the nature of the capillary attraction. We investigate the influence of the three-phase contact angle on the structure of an oil-based capillary suspension with silica microspheres. Contact angles smaller than 90° lead to pendular networks of particles connected with single capillary bridges or clusters comparable to the funicular state in wet granular matter, whereas a different clustered structure, the capillary state, forms for angles larger than 90°. Particle pair distribution functions are obtained by image analysis, which demonstrate differences in the network microstructures. When porous particles are used, the pendular conformation also appears for apparent contact angles larger than 90°. The complex shear modulus can be correlated to these microstructural changes. When the percolating structure is formed, the complex shear modulus increases by nearly three decades. Pendular bridges lead to stronger networks than the capillary state network conformations, but the capillary state clusters are nevertheless much stronger than pure suspensions without the added liquid. PMID:26807651
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.
Alternations of White Matter Structural Networks in First Episode Untreated Major Depressive Disorder with Short Duration.

PubMed

Lu, Yi; Shen, Zonglin; Cheng, Yuqi; Yang, Hui; He, Bo; Xie, Yue; Wen, Liang; Zhang, Zhenguang; Sun, Xuejin; Zhao, Wei; Xu, Xiufeng; Han, Dan

2017-01-01

It is crucial to explore the pathogenesis of major depressive disorder (MDD) at the early stage for the better diagnostic and treatment strategies. It was suggested that MDD might be involving in functional or structural alternations at the brain network level. However, at the onset of MDD, whether the whole brain white matter (WM) alterations at network level are already evident still remains unclear. In the present study, diffusion MRI scanning was adopt to depict the unique WM structural network topology across the entire brain at the early stage of MDD. Twenty-one first episode, short duration (<1 year) and drug-naïve depression patients, and 25 healthy control (HC) subjects were recruited. To construct the WM structural network, atlas-based brain regions were used for nodes, and the value of multiplying fiber number by the mean fractional anisotropy along the fiber bundles connected a pair of brain regions were used for edges. The structural network was analyzed by graph theoretic and network-based statistic methods. Pearson partial correlation analysis was also performed to evaluate their correlation with the clinical variables. Compared with HCs, the MDD patients had a significant decrease in the small-worldness (σ). Meanwhile, the MDD patients presented a significantly decreased subnetwork, which mainly involved in the frontal-subcortical and limbic regions. Our results suggested that the abnormal structural network of the orbitofrontal cortex and thalamus, involving the imbalance with the limbic system, might be a key pathology in early stage drug-naive depression. And the structural network analysis might be potential in early detection and diagnosis of MDD.
Alternations of White Matter Structural Networks in First Episode Untreated Major Depressive Disorder with Short Duration

PubMed Central

Lu, Yi; Shen, Zonglin; Cheng, Yuqi; Yang, Hui; He, Bo; Xie, Yue; Wen, Liang; Zhang, Zhenguang; Sun, Xuejin; Zhao, Wei; Xu, Xiufeng; Han, Dan

2017-01-01

It is crucial to explore the pathogenesis of major depressive disorder (MDD) at the early stage for the better diagnostic and treatment strategies. It was suggested that MDD might be involving in functional or structural alternations at the brain network level. However, at the onset of MDD, whether the whole brain white matter (WM) alterations at network level are already evident still remains unclear. In the present study, diffusion MRI scanning was adopt to depict the unique WM structural network topology across the entire brain at the early stage of MDD. Twenty-one first episode, short duration (<1 year) and drug-naïve depression patients, and 25 healthy control (HC) subjects were recruited. To construct the WM structural network, atlas-based brain regions were used for nodes, and the value of multiplying fiber number by the mean fractional anisotropy along the fiber bundles connected a pair of brain regions were used for edges. The structural network was analyzed by graph theoretic and network-based statistic methods. Pearson partial correlation analysis was also performed to evaluate their correlation with the clinical variables. Compared with HCs, the MDD patients had a significant decrease in the small-worldness (σ). Meanwhile, the MDD patients presented a significantly decreased subnetwork, which mainly involved in the frontal–subcortical and limbic regions. Our results suggested that the abnormal structural network of the orbitofrontal cortex and thalamus, involving the imbalance with the limbic system, might be a key pathology in early stage drug-naive depression. And the structural network analysis might be potential in early detection and diagnosis of MDD. PMID:29118724
Determination of the hydrogen-bond network and the ferrimagnetic structure of a rockbridgeite-type compound, [Formula: see text].

PubMed

Röska, B; Park, S-H; Behal, D; Hess, K-U; Günther, A; Benka, G; Pfleiderer, C; Hoelzel, M; Kimura, T

2018-06-13

Applying neutron powder diffraction, four unique hydrogen positions were determined in a rockbridgeite-type compound, [Formula: see text] [Formula: see text]. Its honeycomb-like H-bond network running without interruption along the crystallographic [Formula: see text] axis resembles those in alkali sulphatic and arsenatic oxyhydroxides. They provide the so-called dynamically disordered H-bond network over which protons are superconducting in a vehicle mechanism. This is indicated by dramatic increases of dielectric constant and loss factor at room temperature. The relevance of static and dynamic disorder of OH and HOH groups are explained in terms of a high number of structural defects at octahedral chains alternatingly half-occupied by [Formula: see text] cations. The structure is built up by unusual octahedral doublet, triplet, and quartet clusters of aliovalent 3d transition metal cations, predicting complicate magnetic ordering and interaction. The ferrimagnetic structure below the Curie temperature [Formula: see text]-83 K could be determined from the structure analysis with neutron diffraction data at 25 K.
Fragmented Romanian sociology: growth and structure of the collaboration network.

PubMed

Hâncean, Marian-Gabriel; Perc, Matjaž; Vlăsceanu, Lazăr

2014-01-01

Structural patterns in collaboration networks are essential for understanding how new ideas, research practices, innovation or cooperation circulate and develop within academic communities and between and within university departments. In our research, we explore and investigate the structure of the collaboration network formed by the academics working full-time within all the 17 sociology departments across Romania. We show that the collaboration network is sparse and fragmented, and that it constitutes an environment that does not promote the circulation of new ideas and innovation within the field. Although recent years have witnessed an increase in the productivity of Romanian sociologists, there is still ample room for improvement in terms of the interaction infrastructure that ought to link individuals together so that they could maximize their potentials. We also fail to discern evidence in favor of the Matthew effect governing the growth of the network, which suggests scientific success and productivity are not rewarded. Instead, the structural properties of the collaboration network are partly those of a core-periphery network, where the spread of innovation and change can be explained by structural equivalence rather than by interpersonal influence models. We also provide support for the idea that, within the observed network, collaboration is the product of homophily rather than prestige effects. Further research on the subject based on data from other countries in the region is needed to place our results in a comparative framework, in particular to discern whether the behavior of the Romanian sociologist community is unique or rather common.
Fragmented Romanian Sociology: Growth and Structure of the Collaboration Network

PubMed Central

Hâncean, Marian-Gabriel; Perc, Matjaž; Vlăsceanu, Lazăr

2014-01-01

Structural patterns in collaboration networks are essential for understanding how new ideas, research practices, innovation or cooperation circulate and develop within academic communities and between and within university departments. In our research, we explore and investigate the structure of the collaboration network formed by the academics working full-time within all the 17 sociology departments across Romania. We show that the collaboration network is sparse and fragmented, and that it constitutes an environment that does not promote the circulation of new ideas and innovation within the field. Although recent years have witnessed an increase in the productivity of Romanian sociologists, there is still ample room for improvement in terms of the interaction infrastructure that ought to link individuals together so that they could maximize their potentials. We also fail to discern evidence in favor of the Matthew effect governing the growth of the network, which suggests scientific success and productivity are not rewarded. Instead, the structural properties of the collaboration network are partly those of a core-periphery network, where the spread of innovation and change can be explained by structural equivalence rather than by interpersonal influence models. We also provide support for the idea that, within the observed network, collaboration is the product of homophily rather than prestige effects. Further research on the subject based on data from other countries in the region is needed to place our results in a comparative framework, in particular to discern whether the behavior of the Romanian sociologist community is unique or rather common. PMID:25409180
Optimizing topological cascade resilience based on the structure of terrorist networks.

PubMed

Gutfraind, Alexander

2010-11-10

Complex socioeconomic networks such as information, finance and even terrorist networks need resilience to cascades--to prevent the failure of a single node from causing a far-reaching domino effect. We show that terrorist and guerrilla networks are uniquely cascade-resilient while maintaining high efficiency, but they become more vulnerable beyond a certain threshold. We also introduce an optimization method for constructing networks with high passive cascade resilience. The optimal networks are found to be based on cells, where each cell has a star topology. Counterintuitively, we find that there are conditions where networks should not be modified to stop cascades because doing so would come at a disproportionate loss of efficiency. Implementation of these findings can lead to more cascade-resilient networks in many diverse areas.
Using structural equation modeling for network meta-analysis.

PubMed

Tu, Yu-Kang; Wu, Yun-Chun

2017-07-14

Network meta-analysis overcomes the limitations of traditional pair-wise meta-analysis by incorporating all available evidence into a general statistical framework for simultaneous comparisons of several treatments. Currently, network meta-analyses are undertaken either within the Bayesian hierarchical linear models or frequentist generalized linear mixed models. Structural equation modeling (SEM) is a statistical method originally developed for modeling causal relations among observed and latent variables. As random effect is explicitly modeled as a latent variable in SEM, it is very flexible for analysts to specify complex random effect structure and to make linear and nonlinear constraints on parameters. The aim of this article is to show how to undertake a network meta-analysis within the statistical framework of SEM. We used an example dataset to demonstrate the standard fixed and random effect network meta-analysis models can be easily implemented in SEM. It contains results of 26 studies that directly compared three treatment groups A, B and C for prevention of first bleeding in patients with liver cirrhosis. We also showed that a new approach to network meta-analysis based on the technique of unrestricted weighted least squares (UWLS) method can also be undertaken using SEM. For both the fixed and random effect network meta-analysis, SEM yielded similar coefficients and confidence intervals to those reported in the previous literature. The point estimates of two UWLS models were identical to those in the fixed effect model but the confidence intervals were greater. This is consistent with results from the traditional pairwise meta-analyses. Comparing to UWLS model with common variance adjusted factor, UWLS model with unique variance adjusted factor has greater confidence intervals when the heterogeneity was larger in the pairwise comparison. The UWLS model with unique variance adjusted factor reflects the difference in heterogeneity within each comparison. SEM provides a very flexible framework for univariate and multivariate meta-analysis, and its potential as a powerful tool for advanced meta-analysis is still to be explored.
Emotional intelligence skills for maintaining social networks in healthcare organizations.

PubMed

Freshman, Brenda; Rubino, Louis

2004-01-01

For healthcare organizations to survive in these increasingly challenging times, leadership and management must face mounting interpersonal concerns. The authors present the boundaries of internal and external social networks with respect to leadership and managerial functions: Social networks within the organization are stretched by reductions in available resources and structural ambiguity, whereas external social networks are stressed by interorganizational competitive pressures. The authors present the development of emotional intelligence skills in employees as a strategic training objective that can strengthen the internal and external social networks of healthcare organizations. The authors delineate the unique functions of leadership and management with respect to the application of emotional intelligence skills and discuss training and future research implications for emotional intelligence skill sets and social networks.
Co-expression networks reveal the tissue-specific regulation of transcription and splicing

PubMed Central

Saha, Ashis; Kim, Yungil; Gewirtz, Ariel D.H.; Jo, Brian; Gao, Chuan; McDowell, Ian C.; Engelhardt, Barbara E.

2017-01-01

Gene co-expression networks capture biologically important patterns in gene expression data, enabling functional analyses of genes, discovery of biomarkers, and interpretation of genetic variants. Most network analyses to date have been limited to assessing correlation between total gene expression levels in a single tissue or small sets of tissues. Here, we built networks that additionally capture the regulation of relative isoform abundance and splicing, along with tissue-specific connections unique to each of a diverse set of tissues. We used the Genotype-Tissue Expression (GTEx) project v6 RNA sequencing data across 50 tissues and 449 individuals. First, we developed a framework called Transcriptome-Wide Networks (TWNs) for combining total expression and relative isoform levels into a single sparse network, capturing the interplay between the regulation of splicing and transcription. We built TWNs for 16 tissues and found that hubs in these networks were strongly enriched for splicing and RNA binding genes, demonstrating their utility in unraveling regulation of splicing in the human transcriptome. Next, we used a Bayesian biclustering model that identifies network edges unique to a single tissue to reconstruct Tissue-Specific Networks (TSNs) for 26 distinct tissues and 10 groups of related tissues. Finally, we found genetic variants associated with pairs of adjacent nodes in our networks, supporting the estimated network structures and identifying 20 genetic variants with distant regulatory impact on transcription and splicing. Our networks provide an improved understanding of the complex relationships of the human transcriptome across tissues. PMID:29021288
2D reentrant auxetic structures of graphene/CNT networks for omnidirectionally stretchable supercapacitors.

PubMed

Kim, Byoung Soo; Lee, Kangsuk; Kang, Seulki; Lee, Soyeon; Pyo, Jun Beom; Choi, In Suk; Char, Kookheon; Park, Jong Hyuk; Lee, Sang-Soo; Lee, Jonghwi; Son, Jeong Gon

2017-09-14

Stretchable energy storage systems are essential for the realization of implantable and epidermal electronics. However, high-performance stretchable supercapacitors have received less attention because currently available processing techniques and material structures are too limited to overcome the trade-off relationship among electrical conductivity, ion-accessible surface area, and stretchability of electrodes. Herein, we introduce novel 2D reentrant cellular structures of porous graphene/CNT networks for omnidirectionally stretchable supercapacitor electrodes. Reentrant structures, with inwardly protruded frameworks in porous networks, were fabricated by the radial compression of vertically aligned honeycomb-like rGO/CNT networks, which were prepared by a directional crystallization method. Unlike typical porous graphene structures, the reentrant structure provided structure-assisted stretchability, such as accordion and origami structures, to otherwise unstretchable materials. The 2D reentrant structures of graphene/CNT networks maintained excellent electrical conductivities under biaxial stretching conditions and showed a slightly negative or near-zero Poisson's ratio over a wide strain range because of their structural uniqueness. For practical applications, we fabricated all-solid-state supercapacitors based on 2D auxetic structures. A radial compression process up to 1/10 th densified the electrode, significantly increasing the areal and volumetric capacitances of the electrodes. Additionally, vertically aligned graphene/CNT networks provided a plentiful surface area and induced sufficient ion transport pathways for the electrodes. Therefore, they exhibited high gravimetric and areal capacitance values of 152.4 F g -1 and 2.9 F cm -2 , respectively, and had an excellent retention ratio of 88% under a biaxial strain of 100%. Auxetic cellular and vertically aligned structures provide a new strategy for the preparation of robust platforms for stretchable energy storage electrodes.
Structure, Function, and Propagation of Information across Living Two, Four, and Eight Node Degree Topologies.

PubMed

Alagapan, Sankaraleengam; Franca, Eric; Pan, Liangbin; Leondopulos, Stathis; Wheeler, Bruce C; DeMarse, Thomas B

2016-01-01

In this study, we created four network topologies composed of living cortical neurons and compared resultant structural-functional dynamics including the nature and quality of information transmission. Each living network was composed of living cortical neurons and were created using microstamping of adhesion promoting molecules and each was "designed" with different levels of convergence embedded within each structure. Networks were cultured over a grid of electrodes that permitted detailed measurements of neural activity at each node in the network. Of the topologies we tested, the "Random" networks in which neurons connect based on their own intrinsic properties transmitted information embedded within their spike trains with higher fidelity relative to any other topology we tested. Within our patterned topologies in which we explicitly manipulated structure, the effect of convergence on fidelity was dependent on both topology and time-scale (rate vs. temporal coding). A more detailed examination using tools from network analysis revealed that these changes in fidelity were also associated with a number of other structural properties including a node's degree, degree-degree correlations, path length, and clustering coefficients. Whereas information transmission was apparent among nodes with few connections, the greatest transmission fidelity was achieved among the few nodes possessing the highest number of connections (high degree nodes or putative hubs). These results provide a unique view into the relationship between structure and its affect on transmission fidelity, at least within these small neural populations with defined network topology. They also highlight the potential role of tools such as microstamp printing and microelectrode array recordings to construct and record from arbitrary network topologies to provide a new direction in which to advance the study of structure-function relationships.
Self-Healing Nanocomposite Hydrogel with Well-Controlled Dynamic Mechanics

NASA Astrophysics Data System (ADS)

Li, Qiaochu; Mishra, Sumeet; Chen, Pangkuan; Tracy, Joseph; Holten-Andersen, Niels

Network dynamics is a crucial factor that determines the macroscopic self-healing rate and efficiency in polymeric hydrogel materials, yet its controllability is seldom studied in most reported self-healing hydrogel systems. Inspired by mussel's adhesion chemistry, we developed a novel approach to assemble inorganic nanoparticles and catechol-decorated PEG polymer into a hydrogel network. When utilized as reversible polymer-particle crosslinks, catechol-metal coordination bonds yield a unique gel network with dynamic mechanics controlled directly by interfacial crosslink structure. Taking advantage of this structure-property relationship at polymer-particle interfaces, we next designed a hierarchically structured hybrid gel with two distinct relaxation timescales. By tuning the relative contribution of the two hierarchical relaxation modes, we are able to finely control the gel's dynamic mechanical behavior from a viscoelastic fluid to a stiff solid, yet preserving its fast self-healing property without the need for external stimuli.
Rapid Self-healing Nanocomposite Hydrogel with Tunable Dynamic Mechanics

NASA Astrophysics Data System (ADS)

Li, Qiaochu; Mishra, Sumeet; Chapman, Brian; Chen, Pangkuan; Tracy, Joseph; Holten-Andersen, Niels

The macroscopic healing rate and efficiency in self-repairing hydrogel materials are largely determined by the dissociation dynamics of their polymer network, which is hardly achieved in a controllable manner. Inspired by mussel's adhesion chemistry, we developed a novel approach to assemble inorganic nanoparticles and catechol-decorated PEG polymer into a hydrogel network. When utilized as reversible polymer-particle crosslinks, catechol-metal coordination bonds yield a unique gel network with dynamic mechanics controlled directly by interfacial crosslink structure. Taking advantage of this structure-property relationship at polymer-particle interfaces, we designed a hierarchically structured hybrid gel with two distinct relaxation timescales. By tuning the relative contribution of the two relaxation modes, we are able to finely control the gel's dynamic mechanical behavior from a viscoelastic fluid to a stiff solid, yet preserving its rapid self-healing property without the need for external stimuli.

Physical properties of mixed dairy food proteins

USDA-ARS?s Scientific Manuscript database

Mixed food protein gels are complex systems, which changes functional behaviors such as gelling properties and viscosity depending on the miscibility of the proteins. We have noted that differences in co-solubility of mixed proteins created unique network structures and gel properties. The effects o...
A generalised significance test for individual communities in networks.

PubMed

Kojaku, Sadamori; Masuda, Naoki

2018-05-09

Many empirical networks have community structure, in which nodes are densely interconnected within each community (i.e., a group of nodes) and sparsely across different communities. Like other local and meso-scale structure of networks, communities are generally heterogeneous in various aspects such as the size, density of edges, connectivity to other communities and significance. In the present study, we propose a method to statistically test the significance of individual communities in a given network. Compared to the previous methods, the present algorithm is unique in that it accepts different community-detection algorithms and the corresponding quality function for single communities. The present method requires that a quality of each community can be quantified and that community detection is performed as optimisation of such a quality function summed over the communities. Various community detection algorithms including modularity maximisation and graph partitioning meet this criterion. Our method estimates a distribution of the quality function for randomised networks to calculate a likelihood of each community in the given network. We illustrate our algorithm by synthetic and empirical networks.
Characterization of actin filament deformation in response to actively driven microspheres propagated through entangled actin networks

NASA Astrophysics Data System (ADS)

Falzone, Tobias; Blair, Savanna; Robertson-Anderson, Rae

2014-03-01

The semi-flexible biopolymer actin is a ubiquitous component of nearly all biological organisms, playing an important role in many biological processes such as cell structure and motility, cancer invasion and metastasis, muscle contraction, and cell signaling. Concentrated actin networks possess unique viscoelastic properties that have been the subject of much theoretical and experimental work. However, much is still unknown regarding the correlation of the applied stress on the network to the induced filament strain at the molecular level. Here, we use dual optical traps alongside fluorescence microscopy to carry out active microrheology measurements that link mechanical stress to structural response at the micron scale. Specifically, we actively drive microspheres through entangled actin networks while simultaneously measuring the force the surrounding filaments exert on the sphere and visualizing the deformation and subsequent relaxation of fluorescent labeled filaments within the network. These measurements, which provide much needed insight into the link between stress and strain in actin networks, are critical for clarifying our theoretical understanding of the complex viscoelastic behavior exhibited in actin networks.
Social network analysis in identifying influential webloggers: A preliminary study

NASA Astrophysics Data System (ADS)

Hasmuni, Noraini; Sulaiman, Nor Intan Saniah; Zaibidi, Nerda Zura

2014-12-01

In recent years, second generation of internet-based services such as weblog has become an effective communication tool to publish information on the Web. Weblogs have unique characteristics that deserve users' attention. Some of webloggers have seen weblogs as appropriate medium to initiate and expand business. These webloggers or also known as direct profit-oriented webloggers (DPOWs) communicate and share knowledge with each other through social interaction. However, survivability is the main issue among DPOW. Frequent communication with influential webloggers is one of the way to keep survive as DPOW. This paper aims to understand the network structure and identify influential webloggers within the network. Proper understanding of the network structure can assist us in knowing how the information is exchanged among members and enhance survivability among DPOW. 30 DPOW were involved in this study. Degree centrality and betweenness centrality measurement in Social Network Analysis (SNA) were used to examine the strength relation and identify influential webloggers within the network. Thus, webloggers with the highest value of these measurements are considered as the most influential webloggers in the network.
Gift-giving and network structure in rural China: utilizing long-term spontaneous gift records.

PubMed

Chen, Xi

2014-01-01

The tradition of keeping written records of gift received during household ceremonies in many countries offers researchers an underutilized means of data collection for social network analysis. This paper first summarizes unique features of the gift record data that circumvent five prevailing sampling and measurement issues in the literature, and we discuss their advantages over existing studies at both the individual level and the dyadic link level using previous data sources. We then document our research project in rural China that implements a multiple wave census-type household survey and a long-term gift record collection. The pattern of gift-giving in major household social events and its recent escalation is analyzed. There are significantly positive correlations between gift network centrality and various forms of informal insurance. Finally, economic inequality and competitive marriage market are among the main demographic and socioeconomic determinants of the observed gift network structure.
Gift-Giving and Network Structure in Rural China: Utilizing Long-Term Spontaneous Gift Records

PubMed Central

Chen, Xi

2014-01-01

The tradition of keeping written records of gift received during household ceremonies in many countries offers researchers an underutilized means of data collection for social network analysis. This paper first summarizes unique features of the gift record data that circumvent five prevailing sampling and measurement issues in the literature, and we discuss their advantages over existing studies at both the individual level and the dyadic link level using previous data sources. We then document our research project in rural China that implements a multiple wave census-type household survey and a long-term gift record collection. The pattern of gift-giving in major household social events and its recent escalation is analyzed. There are significantly positive correlations between gift network centrality and various forms of informal insurance. Finally, economic inequality and competitive marriage market are among the main demographic and socioeconomic determinants of the observed gift network structure. PMID:25111696
Parasites Affect Food Web Structure Primarily through Increased Diversity and Complexity

PubMed Central

Dunne, Jennifer A.; Lafferty, Kevin D.; Dobson, Andrew P.; Hechinger, Ryan F.; Kuris, Armand M.; Martinez, Neo D.; McLaughlin, John P.; Mouritsen, Kim N.; Poulin, Robert; Reise, Karsten; Stouffer, Daniel B.; Thieltges, David W.; Williams, Richard J.; Zander, Claus Dieter

2013-01-01

Comparative research on food web structure has revealed generalities in trophic organization, produced simple models, and allowed assessment of robustness to species loss. These studies have mostly focused on free-living species. Recent research has suggested that inclusion of parasites alters structure. We assess whether such changes in network structure result from unique roles and traits of parasites or from changes to diversity and complexity. We analyzed seven highly resolved food webs that include metazoan parasite data. Our analyses show that adding parasites usually increases link density and connectance (simple measures of complexity), particularly when including concomitant links (links from predators to parasites of their prey). However, we clarify prior claims that parasites “dominate” food web links. Although parasites can be involved in a majority of links, in most cases classic predation links outnumber classic parasitism links. Regarding network structure, observed changes in degree distributions, 14 commonly studied metrics, and link probabilities are consistent with scale-dependent changes in structure associated with changes in diversity and complexity. Parasite and free-living species thus have similar effects on these aspects of structure. However, two changes point to unique roles of parasites. First, adding parasites and concomitant links strongly alters the frequency of most motifs of interactions among three taxa, reflecting parasites' roles as resources for predators of their hosts, driven by trophic intimacy with their hosts. Second, compared to free-living consumers, many parasites' feeding niches appear broader and less contiguous, which may reflect complex life cycles and small body sizes. This study provides new insights about generic versus unique impacts of parasites on food web structure, extends the generality of food web theory, gives a more rigorous framework for assessing the impact of any species on trophic organization, identifies limitations of current food web models, and provides direction for future structural and dynamical models. PMID:23776404
Parasites affect food web structure primarily through increased diversity and complexity

USGS Publications Warehouse

Dunne, Jennifer A.; Lafferty, Kevin D.; Dobson, Andrew P.; Hechinger, Ryan F.; Kuris, Armand M.; Martinez, Neo D.; McLaughlin, John P.; Mouritsen, Kim N.; Poulin, Robert; Reise, Karsten; Stouffer, Daniel B.; Thieltges, David W.; Williams, Richard J.; Zander, Claus Dieter

2013-01-01

Comparative research on food web structure has revealed generalities in trophic organization, produced simple models, and allowed assessment of robustness to species loss. These studies have mostly focused on free-living species. Recent research has suggested that inclusion of parasites alters structure. We assess whether such changes in network structure result from unique roles and traits of parasites or from changes to diversity and complexity. We analyzed seven highly resolved food webs that include metazoan parasite data. Our analyses show that adding parasites usually increases link density and connectance (simple measures of complexity), particularly when including concomitant links (links from predators to parasites of their prey). However, we clarify prior claims that parasites ‘‘dominate’’ food web links. Although parasites can be involved in a majority of links, in most cases classic predation links outnumber classic parasitism links. Regarding network structure, observed changes in degree distributions, 14 commonly studied metrics, and link probabilities are consistent with scale-dependent changes in structure associated with changes in diversity and complexity. Parasite and free-living species thus have similar effects on these aspects of structure. However, two changes point to unique roles of parasites. First, adding parasites and concomitant links strongly alters the frequency of most motifs of interactions among three taxa, reflecting parasites’ roles as resources for predators of their hosts, driven by trophic intimacy with their hosts. Second, compared to free-living consumers, many parasites’ feeding niches appear broader and less contiguous, which may reflect complex life cycles and small body sizes. This study provides new insights about generic versus unique impacts of parasites on food web structure, extends the generality of food web theory, gives a more rigorous framework for assessing the impact of any species on trophic organization, identifies limitations of current food web models, and provides direction for future structural and dynamical models.
Parasites affect food web structure primarily through increased diversity and complexity.

PubMed

Dunne, Jennifer A; Lafferty, Kevin D; Dobson, Andrew P; Hechinger, Ryan F; Kuris, Armand M; Martinez, Neo D; McLaughlin, John P; Mouritsen, Kim N; Poulin, Robert; Reise, Karsten; Stouffer, Daniel B; Thieltges, David W; Williams, Richard J; Zander, Claus Dieter

2013-01-01

Comparative research on food web structure has revealed generalities in trophic organization, produced simple models, and allowed assessment of robustness to species loss. These studies have mostly focused on free-living species. Recent research has suggested that inclusion of parasites alters structure. We assess whether such changes in network structure result from unique roles and traits of parasites or from changes to diversity and complexity. We analyzed seven highly resolved food webs that include metazoan parasite data. Our analyses show that adding parasites usually increases link density and connectance (simple measures of complexity), particularly when including concomitant links (links from predators to parasites of their prey). However, we clarify prior claims that parasites "dominate" food web links. Although parasites can be involved in a majority of links, in most cases classic predation links outnumber classic parasitism links. Regarding network structure, observed changes in degree distributions, 14 commonly studied metrics, and link probabilities are consistent with scale-dependent changes in structure associated with changes in diversity and complexity. Parasite and free-living species thus have similar effects on these aspects of structure. However, two changes point to unique roles of parasites. First, adding parasites and concomitant links strongly alters the frequency of most motifs of interactions among three taxa, reflecting parasites' roles as resources for predators of their hosts, driven by trophic intimacy with their hosts. Second, compared to free-living consumers, many parasites' feeding niches appear broader and less contiguous, which may reflect complex life cycles and small body sizes. This study provides new insights about generic versus unique impacts of parasites on food web structure, extends the generality of food web theory, gives a more rigorous framework for assessing the impact of any species on trophic organization, identifies limitations of current food web models, and provides direction for future structural and dynamical models.
Uncovering the overlapping community structure of complex networks by maximal cliques

NASA Astrophysics Data System (ADS)

Li, Junqiu; Wang, Xingyuan; Cui, Yaozu

2014-12-01

In this paper, a unique algorithm is proposed to detect overlapping communities in the un-weighted and weighted networks with considerable accuracy. The maximal cliques, overlapping vertex, bridge vertex and isolated vertex are introduced. First, all the maximal cliques are extracted by the algorithm based on the deep and bread searching. Then two maximal cliques can be merged into a larger sub-graph by some given rules. In addition, the proposed algorithm successfully finds overlapping vertices and bridge vertices between communities. Experimental results using some real-world networks data show that the performance of the proposed algorithm is satisfactory.
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.
Evaluating methods of inferring gene regulatory networks highlights their lack of performance for single cell gene expression data.

PubMed

Chen, Shuonan; Mar, Jessica C

2018-06-19

A fundamental fact in biology states that genes do not operate in isolation, and yet, methods that infer regulatory networks for single cell gene expression data have been slow to emerge. With single cell sequencing methods now becoming accessible, general network inference algorithms that were initially developed for data collected from bulk samples may not be suitable for single cells. Meanwhile, although methods that are specific for single cell data are now emerging, whether they have improved performance over general methods is unknown. In this study, we evaluate the applicability of five general methods and three single cell methods for inferring gene regulatory networks from both experimental single cell gene expression data and in silico simulated data. Standard evaluation metrics using ROC curves and Precision-Recall curves against reference sets sourced from the literature demonstrated that most of the methods performed poorly when they were applied to either experimental single cell data, or simulated single cell data, which demonstrates their lack of performance for this task. Using default settings, network methods were applied to the same datasets. Comparisons of the learned networks highlighted the uniqueness of some predicted edges for each method. The fact that different methods infer networks that vary substantially reflects the underlying mathematical rationale and assumptions that distinguish network methods from each other. This study provides a comprehensive evaluation of network modeling algorithms applied to experimental single cell gene expression data and in silico simulated datasets where the network structure is known. Comparisons demonstrate that most of these assessed network methods are not able to predict network structures from single cell expression data accurately, even if they are specifically developed for single cell methods. Also, single cell methods, which usually depend on more elaborative algorithms, in general have less similarity to each other in the sets of edges detected. The results from this study emphasize the importance for developing more accurate optimized network modeling methods that are compatible for single cell data. Newly-developed single cell methods may uniquely capture particular features of potential gene-gene relationships, and caution should be taken when we interpret these results.
Co-expression networks reveal the tissue-specific regulation of transcription and splicing.

PubMed

Saha, Ashis; Kim, Yungil; Gewirtz, Ariel D H; Jo, Brian; Gao, Chuan; McDowell, Ian C; Engelhardt, Barbara E; Battle, Alexis

2017-11-01

Gene co-expression networks capture biologically important patterns in gene expression data, enabling functional analyses of genes, discovery of biomarkers, and interpretation of genetic variants. Most network analyses to date have been limited to assessing correlation between total gene expression levels in a single tissue or small sets of tissues. Here, we built networks that additionally capture the regulation of relative isoform abundance and splicing, along with tissue-specific connections unique to each of a diverse set of tissues. We used the Genotype-Tissue Expression (GTEx) project v6 RNA sequencing data across 50 tissues and 449 individuals. First, we developed a framework called Transcriptome-Wide Networks (TWNs) for combining total expression and relative isoform levels into a single sparse network, capturing the interplay between the regulation of splicing and transcription. We built TWNs for 16 tissues and found that hubs in these networks were strongly enriched for splicing and RNA binding genes, demonstrating their utility in unraveling regulation of splicing in the human transcriptome. Next, we used a Bayesian biclustering model that identifies network edges unique to a single tissue to reconstruct Tissue-Specific Networks (TSNs) for 26 distinct tissues and 10 groups of related tissues. Finally, we found genetic variants associated with pairs of adjacent nodes in our networks, supporting the estimated network structures and identifying 20 genetic variants with distant regulatory impact on transcription and splicing. Our networks provide an improved understanding of the complex relationships of the human transcriptome across tissues. © 2017 Saha et al.; Published by Cold Spring Harbor Laboratory Press.
Nanoreinforced biocompatible hydrogels from wood hemicelluloses and cellulose whiskers

Treesearch

Muzaffer Ahmet Karaaslan; Mandla A. Tshabalala; Daniel J. Yelle; Gisela Buschle-Diller

2011-01-01

Nanoreinforced hydrogels with a unique network structure were prepared from wood cellulose whiskers coated with chemically modified wood hemicelluloses. The hemicelluloses were modified with 2-hydroxyethylmethacrylate prior to adsorption onto the cellulose whiskers in aqueous medium. Synthesis of the hydrogels was accomplished by in situ radical polymerization of the...
Physical properties of beeswax, sunflower wax, and candelilla wax mixtures and organogels

USDA-ARS?s Scientific Manuscript database

There is increased interest in natural waxes as alternatives to partially hydrogenated oils and saturated fats as oil structuring agents. Using relatively low concentrations (0.5-5%), natural waxes are able to form crystalline networks, or organogels, which bind liquid oil. Each natural wax is uniqu...
Determination of the hydrogen-bond network and the ferrimagnetic structure of a rockbridgeite-type compound, {Fe^{2+Fe^{3+}_{3.2}(Mn^{2+}, Zn)_{0.8}(PO_{4})_{3}(OH)_{4.2}(HOH)_{0.8}}}

NASA Astrophysics Data System (ADS)

Röska, B.; Park, S.-H.; Behal, D.; Hess, K.-U.; Günther, A.; Benka, G.; Pfleiderer, C.; Hoelzel, M.; Kimura, T.

2018-06-01

Applying neutron powder diffraction, four unique hydrogen positions were determined in a rockbridgeite-type compound, . Its honeycomb-like H-bond network running without interruption along the crystallographic axis resembles those in alkali sulphatic and arsenatic oxyhydroxides. They provide the so-called dynamically disordered H-bond network over which protons are superconducting in a vehicle mechanism. This is indicated by dramatic increases of dielectric constant and loss factor at room temperature. The relevance of static and dynamic disorder of OH and HOH groups are explained in terms of a high number of structural defects at octahedral chains alternatingly half-occupied by cations. The structure is built up by unusual octahedral doublet, triplet, and quartet clusters of aliovalent 3d transition metal cations, predicting complicate magnetic ordering and interaction. The ferrimagnetic structure below the Curie temperature –83 K could be determined from the structure analysis with neutron diffraction data at 25 K.
Ultrafast and Wide Range Analysis of DNA Molecules Using Rigid Network Structure of Solid Nanowires

PubMed Central

Rahong, Sakon; Yasui, Takao; Yanagida, Takeshi; Nagashima, Kazuki; Kanai, Masaki; Klamchuen, Annop; Meng, Gang; He, Yong; Zhuge, Fuwei; Kaji, Noritada; Kawai, Tomoji; Baba, Yoshinobu

2014-01-01

Analyzing sizes of DNA via electrophoresis using a gel has played an important role in the recent, rapid progress of biology and biotechnology. Although analyzing DNA over a wide range of sizes in a short time is desired, no existing electrophoresis methods have been able to fully satisfy these two requirements. Here we propose a novel method using a rigid 3D network structure composed of solid nanowires within a microchannel. This rigid network structure enables analysis of DNA under applied DC electric fields for a large DNA size range (100 bp–166 kbp) within 13 s, which are much wider and faster conditions than those of any existing methods. The network density is readily varied for the targeted DNA size range by tailoring the number of cycles of the nanowire growth only at the desired spatial position within the microchannel. The rigid dense 3D network structure with spatial density control plays an important role in determining the capability for analyzing DNA. Since the present method allows the spatial location and density of the nanostructure within the microchannels to be defined, this unique controllability offers a new strategy to develop an analytical method not only for DNA but also for other biological molecules. PMID:24918865
Ultrafast and Wide Range Analysis of DNA Molecules Using Rigid Network Structure of Solid Nanowires

NASA Astrophysics Data System (ADS)

Rahong, Sakon; Yasui, Takao; Yanagida, Takeshi; Nagashima, Kazuki; Kanai, Masaki; Klamchuen, Annop; Meng, Gang; He, Yong; Zhuge, Fuwei; Kaji, Noritada; Kawai, Tomoji; Baba, Yoshinobu

2014-06-01

Analyzing sizes of DNA via electrophoresis using a gel has played an important role in the recent, rapid progress of biology and biotechnology. Although analyzing DNA over a wide range of sizes in a short time is desired, no existing electrophoresis methods have been able to fully satisfy these two requirements. Here we propose a novel method using a rigid 3D network structure composed of solid nanowires within a microchannel. This rigid network structure enables analysis of DNA under applied DC electric fields for a large DNA size range (100 bp-166 kbp) within 13 s, which are much wider and faster conditions than those of any existing methods. The network density is readily varied for the targeted DNA size range by tailoring the number of cycles of the nanowire growth only at the desired spatial position within the microchannel. The rigid dense 3D network structure with spatial density control plays an important role in determining the capability for analyzing DNA. Since the present method allows the spatial location and density of the nanostructure within the microchannels to be defined, this unique controllability offers a new strategy to develop an analytical method not only for DNA but also for other biological molecules.
Structural organization of process zones in upland watersheds of central Nevada and its influence on basin connectivity, dynamics, and wet meadow complexes

Treesearch

Jerry R. Miller; Mark L. Lord; Lionel F. Villarroel; Dru Germanoski; Jeanne C. Chambers

2012-01-01

The drainage network within upland watersheds in central Nevada can be subdivided into distinct zones each dominated by a unique set of processes on the basis of valley form, the geological materials that comprise the valley floor, and the presence or absence of surficial channels. On hillslopes, the type and structure (frequency, length, and spatial arrangement) of...
DSSTox chemical-index files for exposure-related ...

EPA Pesticide Factsheets

The Distributed Structure-Searchable Toxicity (DSSTox) ARYEXP and GEOGSE files are newly published, structure-annotated files of the chemical-associated and chemical exposure-related summary experimental content contained in the ArrayExpress Repository and Gene Expression Omnibus (GEO) Series (based on data extracted on September 20, 2008). ARYEXP and GEOGSE contain 887 and 1064 unique chemical substances mapped to 1835 and 2381 chemical exposure-related experiment accession IDs, respectively. The standardized files allow one to assess, compare and search the chemical content in each resource, in the context of the larger DSSTox toxicology data network, as well as across large public cheminformatics resources such as PubChem (http://pubchem.ncbi.nlm.nih.gov). The Distributed Structure-Searchable Toxicity (DSSTox) ARYEXP and GEOGSE files are newly published, structure-annotated files of the chemical-associated and chemical exposure-related summary experimental content contained in the ArrayExpress Repository and Gene Expression Omnibus (GEO) Series (based on data extracted on September 20, 2008). ARYEXP and GEOGSE contain 887 and 1064 unique chemical substances mapped to 1835 and 2381 chemical exposure-related experiment accession IDs, respectively. The standardized files allow one to assess, compare and search the chemical content in each resource, in the context of the larger DSSTox toxicology data network, as well as across large public cheminformatics resourc

The protist, Monosiga brevicollis, has a tyrosine kinase signaling network more elaborate and diverse than found in any known metazoan.

PubMed

Manning, Gerard; Young, Susan L; Miller, W Todd; Zhai, Yufeng

2008-07-15

Tyrosine kinase signaling has long been considered a hallmark of intercellular communication, unique to multicellular animals. Our genomic analysis of the unicellular choanoflagellate Monosiga brevicollis discovers a remarkable count of 128 tyrosine kinases, 38 tyrosine phosphatases, and 123 phosphotyrosine (pTyr)-binding SH2 proteins, all higher counts than seen in any metazoan. This elaborate signaling network shows little orthology to metazoan counterparts yet displays many innovations reminiscent of metazoans. These include extracellular domains structurally related to those of metazoan receptor kinases, alternative methods for membrane anchoring and phosphotyrosine interaction in cytoplasmic kinases, and domain combinations that link kinases to small GTPase signaling and transcription. These proteins also display a wealth of combinations of known signaling domains. This uniquely divergent and elaborate signaling network illuminates the early evolution of pTyr signaling, explores innovative ways to traverse the cellular signaling circuitry, and shows extensive convergent evolution, highlighting pervasive constraints on pTyr signaling.
"They're younger… it's harder." Primary providers' perspectives on hypertension management in young adults: a multicenter qualitative study.

PubMed

Johnson, Heather M; Warner, Ryan C; Bartels, Christie M; LaMantia, Jamie N

2017-01-03

Young adults (18-39 year-olds) have the lowest hypertension control rates among adults with hypertension in the United States. Unique barriers to hypertension management in young adults with primary care access compared to older adults have not been evaluated. Understanding these differences will inform the development of hypertension interventions tailored to young adults. The goals of this multicenter study were to explore primary care providers' perspectives on barriers to diagnosing, treating, and controlling hypertension among young adults with regular primary care. Primary care providers (physicians and advanced practice providers) actively managing young adults with uncontrolled hypertension were recruited by the Wisconsin Research & Education Network (WREN), a statewide practice-based research network. Semi-structured qualitative interviews were conducted in three diverse Midwestern clinical practices (academic, rural, and urban clinics) using a semi-structured interview guide, and content analysis was performed. Primary care providers identified unique barriers across standard hypertension healthcare delivery practices for young adults. Altered self-identity, greater blood pressure variability, and unintended consequences of medication initiation were critical hypertension control barriers among young adults. Gender differences among young adults were also noted as barriers to hypertension follow-up and antihypertensive medication initiation. Tailored interventions addressing the unique barriers of young adults are needed to improve population hypertension control. Augmenting traditional clinic structure to support the "health identity" of young adults and self-management skills are promising next steps to improve hypertension healthcare delivery.
Structural Connectivity Networks of Transgender People

PubMed Central

Hahn, Andreas; Kranz, Georg S.; Küblböck, Martin; Kaufmann, Ulrike; Ganger, Sebastian; Hummer, Allan; Seiger, Rene; Spies, Marie; Winkler, Dietmar; Kasper, Siegfried; Windischberger, Christian; Swaab, Dick F.; Lanzenberger, Rupert

2015-01-01

Although previous investigations of transsexual people have focused on regional brain alterations, evaluations on a network level, especially those structural in nature, are largely missing. Therefore, we investigated the structural connectome of 23 female-to-male (FtM) and 21 male-to-female (MtF) transgender patients before hormone therapy as compared with 25 female and 25 male healthy controls. Graph theoretical analysis of whole-brain probabilistic tractography networks (adjusted for differences in intracranial volume) showed decreased hemispheric connectivity ratios of subcortical/limbic areas for both transgender groups. Subsequent analysis revealed that this finding was driven by increased interhemispheric lobar connectivity weights (LCWs) in MtF transsexuals and decreased intrahemispheric LCWs in FtM patients. This was further reflected on a regional level, where the MtF group showed mostly increased local efficiencies and FtM patients decreased values. Importantly, these parameters separated each patient group from the remaining subjects for the majority of significant findings. This work complements previously established regional alterations with important findings of structural connectivity. Specifically, our data suggest that network parameters may reflect unique characteristics of transgender patients, whereas local physiological aspects have been shown to represent the transition from the biological sex to the actual gender identity. PMID:25217469
Process-based network decomposition reveals backbone motif structure

PubMed Central

Wang, Guanyu; Du, Chenghang; Chen, Hao; Simha, Rahul; Rong, Yongwu; Xiao, Yi; Zeng, Chen

2010-01-01

A central challenge in systems biology today is to understand the network of interactions among biomolecules and, especially, the organizing principles underlying such networks. Recent analysis of known networks has identified small motifs that occur ubiquitously, suggesting that larger networks might be constructed in the manner of electronic circuits by assembling groups of these smaller modules. Using a unique process-based approach to analyzing such networks, we show for two cell-cycle networks that each of these networks contains a giant backbone motif spanning all the network nodes that provides the main functional response. The backbone is in fact the smallest network capable of providing the desired functionality. Furthermore, the remaining edges in the network form smaller motifs whose role is to confer stability properties rather than provide function. The process-based approach used in the above analysis has additional benefits: It is scalable, analytic (resulting in a single analyzable expression that describes the behavior), and computationally efficient (all possible minimal networks for a biological process can be identified and enumerated). PMID:20498084
How structure sculpts function: Unveiling the contribution of anatomical connectivity to the brain's spontaneous correlation structure

NASA Astrophysics Data System (ADS)

Bettinardi, R. G.; Deco, G.; Karlaftis, V. M.; Van Hartevelt, T. J.; Fernandes, H. M.; Kourtzi, Z.; Kringelbach, M. L.; Zamora-López, G.

2017-04-01

Intrinsic brain activity is characterized by highly organized co-activations between different regions, forming clustered spatial patterns referred to as resting-state networks. The observed co-activation patterns are sustained by the intricate fabric of millions of interconnected neurons constituting the brain's wiring diagram. However, as for other real networks, the relationship between the connectional structure and the emergent collective dynamics still evades complete understanding. Here, we show that it is possible to estimate the expected pair-wise correlations that a network tends to generate thanks to the underlying path structure. We start from the assumption that in order for two nodes to exhibit correlated activity, they must be exposed to similar input patterns from the entire network. We then acknowledge that information rarely spreads only along a unique route but rather travels along all possible paths. In real networks, the strength of local perturbations tends to decay as they propagate away from the sources, leading to a progressive attenuation of the original information content and, thus, of their influence. Accordingly, we define a novel graph measure, topological similarity, which quantifies the propensity of two nodes to dynamically correlate as a function of the resemblance of the overall influences they are expected to receive due to the underlying structure of the network. Applied to the human brain, we find that the similarity of whole-network inputs, estimated from the topology of the anatomical connectome, plays an important role in sculpting the backbone pattern of time-average correlations observed at rest.
The Complex Nature of Family Support across the Lifespan: Implications for Psychological Well-being

PubMed Central

Fuller-Iglesias, Heather R.; Webster, Noah J.; Antonucci, Toni C.

2015-01-01

This study examines the complex role of family networks in shaping adult psychological well-being over time. We examine the unique and interactive longitudinal influences of family structure (i.e., composition and size) and negative family relationship quality on psychological well-being among young (aged 18-34), middle-aged (aged 35-49), and older adults (aged 50+). A sample of 881 adults (72% White; 26% Black) was drawn from the longitudinal Social Relations, Age and Health Study. Structural equation modeling indicated that among young and middle-aged adults, increasing family negativity was associated with increases in depressive symptoms over time. In contrast, among older adults, lowered proportion of family in network and an increasing number of family members in the network (i.e. family size) were associated with decreases in depressive symptoms. These findings were moderated by family negativity. Among older adults with low family negativity, having a lower proportion family and larger family size were associated with decreasing depressive symptoms, but there was no effect among those reporting high family negativity. Overall, these results contribute to an increased understanding of the complex, developmental nature of how family support influences well-being across the lifespan and highlights unique age differences. PMID:25602936
The use of social networking to improve the quality of interprofessional education.

PubMed

Pittenger, Amy L

2013-10-14

To evaluate the feasibility and effectiveness of using an online social networking platform for interprofessional education. Three groups of 6 students were formed with 1 student in each group from medicine, nursing, dentistry, pharmacy, veterinary medicine, and public health. Each group followed a different collaborative educational model with a unique pedagogical structure. Students in all groups interacted via an online social networking platform for a minimum of 15 weeks and met in person once at the end of the 15-week experience for a focus group session. The students were tasked with developing a collaborative recommendation for using social networking in interprofessional education programs. Most of the students who reported in a post-experience survey that their expectations were not met were in the minimally structured group. Almost all students in the facilitated and highly structured groups indicated that this experience positively impacted their knowledge of other health professions. Most students stated that interacting within a social networking space for 15 weeks with other members of the university's health professions programs was a positive and effective interprofessional education experience. Social networking is feasible and can be used effectively within an overall strategy for interprofessional education, but design and placement within a core content course is critical to success.
Exploring Maps with Greedy Navigators

NASA Astrophysics Data System (ADS)

Lee, Sang Hoon; Holme, Petter

2012-03-01

During the last decade of network research focusing on structural and dynamical properties of networks, the role of network users has been more or less underestimated from the bird’s-eye view of global perspective. In this era of global positioning system equipped smartphones, however, a user’s ability to access local geometric information and find efficient pathways on networks plays a crucial role, rather than the globally optimal pathways. We present a simple greedy spatial navigation strategy as a probe to explore spatial networks. These greedy navigators use directional information in every move they take, without being trapped in a dead end based on their memory about previous routes. We suggest that the centralities measures have to be modified to incorporate the navigators’ behavior, and present the intriguing effect of navigators’ greediness where removing some edges may actually enhance the routing efficiency, which is reminiscent of Braess’s paradox. In addition, using samples of road structures in large cities around the world, it is shown that the navigability measure we define reflects unique structural properties, which are not easy to predict from other topological characteristics. In this respect, we believe that our routing scheme significantly moves the routing problem on networks one step closer to reality, incorporating the inevitable incompleteness of navigators’ information.
The Use of Social Networking to Improve the Quality of Interprofessional Education

PubMed Central

2013-01-01

Objective. To evaluate the feasibility and effectiveness of using an online social networking platform for interprofessional education. Design. Three groups of 6 students were formed with 1 student in each group from medicine, nursing, dentistry, pharmacy, veterinary medicine, and public health. Each group followed a different collaborative educational model with a unique pedagogical structure. Students in all groups interacted via an online social networking platform for a minimum of 15 weeks and met in person once at the end of the 15-week experience for a focus group session. The students were tasked with developing a collaborative recommendation for using social networking in interprofessional education programs. Assessment. Most of the students who reported in a post-experience survey that their expectations were not met were in the minimally structured group. Almost all students in the facilitated and highly structured groups indicated that this experience positively impacted their knowledge of other health professions. Most students stated that interacting within a social networking space for 15 weeks with other members of the university’s health professions programs was a positive and effective interprofessional education experience. Conclusion. Social networking is feasible and can be used effectively within an overall strategy for interprofessional education, but design and placement within a core content course is critical to success. PMID:24159215
Abnormal network connectivity in frontotemporal dementia: evidence for prefrontal isolation.

PubMed

Farb, Norman A S; Grady, Cheryl L; Strother, Stephen; Tang-Wai, David F; Masellis, Mario; Black, Sandra; Freedman, Morris; Pollock, Bruce G; Campbell, Karen L; Hasher, Lynn; Chow, Tiffany W

2013-01-01

Degraded social function, disinhibition, and stereotypy are defining characteristics of frontotemporal dementia (FTD), manifesting in both the behavioral variant of frontotemporal dementia (bvFTD) and semantic dementia (SD) subtypes. Recent neuroimaging research also associates FTD with alterations in the brain's intrinsic connectivity networks. The present study explored the relationship between neural network connectivity and specific behavioral symptoms in FTD. Resting-state functional magnetic resonance imaging was employed to investigate neural network changes in bvFTD and SD. We used independent components analysis (ICA) to examine changes in frontolimbic network connectivity, as well as several metrics of local network strength, such as the fractional amplitude of low-frequency fluctuations, regional homogeneity, and seed-based functional connectivity. For each analysis, we compared each FTD subgroup to healthy controls, characterizing general and subtype-unique network changes. The relationship between abnormal connectivity in FTD and behavior disturbances was explored. Across multiple analytic approaches, both bvFTD and SD were associated with disrupted frontolimbic connectivity and elevated local connectivity within the prefrontal cortex. Even after controlling for structural atrophy, prefrontal hyperconnectivity was robustly associated with apathy scores. Frontolimbic disconnection was associated with lower disinhibition scores, suggesting that abnormal frontolimbic connectivity contributes to positive symptoms in dementia. Unique to bvFTD, stereotypy was associated with elevated default network connectivity in the right angular gyrus. The behavioral variant was also associated with marginally higher apathy scores and a more diffuse pattern of prefrontal hyperconnectivity than SD. The present findings support a theory of FTD as a disorder of frontolimbic disconnection leading to unconstrained prefrontal connectivity. Prefrontal hyperconnectivity may represent a compensatory response to the absence of affective feedback during the planning and execution of behavior. Increased reliance upon prefrontal processes in isolation from subcortical structures appears to be maladaptive and may drive behavioral withdrawal that is commonly observed in later phases of neurodegeneration. Copyright © 2012 Elsevier Ltd. All rights reserved.
Do motifs reflect evolved function?--No convergent evolution of genetic regulatory network subgraph topologies.

PubMed

Knabe, Johannes F; Nehaniv, Chrystopher L; Schilstra, Maria J

2008-01-01

Methods that analyse the topological structure of networks have recently become quite popular. Whether motifs (subgraph patterns that occur more often than in randomized networks) have specific functions as elementary computational circuits has been cause for debate. As the question is difficult to resolve with currently available biological data, we approach the issue using networks that abstractly model natural genetic regulatory networks (GRNs) which are evolved to show dynamical behaviors. Specifically one group of networks was evolved to be capable of exhibiting two different behaviors ("differentiation") in contrast to a group with a single target behavior. In both groups we find motif distribution differences within the groups to be larger than differences between them, indicating that evolutionary niches (target functions) do not necessarily mold network structure uniquely. These results show that variability operators can have a stronger influence on network topologies than selection pressures, especially when many topologies can create similar dynamics. Moreover, analysis of motif functional relevance by lesioning did not suggest that motifs were of greater importance to the functioning of the network than arbitrary subgraph patterns. Only when drastically restricting network size, so that one motif corresponds to a whole functionally evolved network, was preference for particular connection patterns found. This suggests that in non-restricted, bigger networks, entanglement with the rest of the network hinders topological subgraph analysis.
Topological Structure of the Space of Phenotypes: The Case of RNA Neutral Networks

PubMed Central

Aguirre, Jacobo; Buldú, Javier M.; Stich, Michael; Manrubia, Susanna C.

2011-01-01

The evolution and adaptation of molecular populations is constrained by the diversity accessible through mutational processes. RNA is a paradigmatic example of biopolymer where genotype (sequence) and phenotype (approximated by the secondary structure fold) are identified in a single molecule. The extreme redundancy of the genotype-phenotype map leads to large ensembles of RNA sequences that fold into the same secondary structure and can be connected through single-point mutations. These ensembles define neutral networks of phenotypes in sequence space. Here we analyze the topological properties of neutral networks formed by 12-nucleotides RNA sequences, obtained through the exhaustive folding of sequence space. A total of 412 sequences fragments into 645 subnetworks that correspond to 57 different secondary structures. The topological analysis reveals that each subnetwork is far from being random: it has a degree distribution with a well-defined average and a small dispersion, a high clustering coefficient, and an average shortest path between nodes close to its minimum possible value, i.e. the Hamming distance between sequences. RNA neutral networks are assortative due to the correlation in the composition of neighboring sequences, a feature that together with the symmetries inherent to the folding process explains the existence of communities. Several topological relationships can be analytically derived attending to structural restrictions and generic properties of the folding process. The average degree of these phenotypic networks grows logarithmically with their size, such that abundant phenotypes have the additional advantage of being more robust to mutations. This property prevents fragmentation of neutral networks and thus enhances the navigability of sequence space. In summary, RNA neutral networks show unique topological properties, unknown to other networks previously described. PMID:22028856
Metacommunity theory as a multispecies, multiscale framework for studying the influence of river network structure on riverine communities and ecosystems

USGS Publications Warehouse

Brown, B.L.; Swan, C.M.; Auerbach, D.A.; Campbell, Grant E.H.; Hitt, N.P.; Maloney, K.O.; Patrick, C.

2011-01-01

Explaining the mechanisms underlying patterns of species diversity and composition in riverine networks is challenging. Historically, community ecologists have conceived of communities as largely isolated entities and have focused on local environmental factors and interspecific interactions as the major forces determining species composition. However, stream ecologists have long embraced a multiscale approach to studying riverine ecosystems and have studied both local factors and larger-scale regional factors, such as dispersal and disturbance. River networks exhibit a dendritic spatial structure that can constrain aquatic organisms when their dispersal is influenced by or confined to the river network. We contend that the principles of metacommunity theory would help stream ecologists to understand how the complex spatial structure of river networks mediates the relative influences of local and regional control on species composition. From a basic ecological perspective, the concept is attractive because new evidence suggests that the importance of regional processes (dispersal) depends on spatial structure of habitat and on connection to the regional species pool. The role of local factors relative to regional factors will vary with spatial position in a river network. From an applied perspective, the long-standing view in ecology that local community composition is an indicator of habitat quality may not be uniformly applicable across a river network, but the strength of such bioassessment approaches probably will depend on spatial position in the network. The principles of metacommunity theory are broadly applicable across taxa and systems but seem of particular consequence to stream ecology given the unique spatial structure of riverine systems. By explicitly embracing processes at multiple spatial scales, metacommunity theory provides a foundation on which to build a richer understanding of stream communities.
Passively Damped Laminated Piezoelectric Shell Structures with Integrated Electric Networks

NASA Technical Reports Server (NTRS)

Saravanos, Dimitris A.

1999-01-01

Multi-field mechanics are presented for curvilinear piezoelectric laminates interfaced with distributed passive electric components. The equations of motion for laminated piezoelectric shell structures with embedded passive electric networks are directly formulated and solved using a finite element methodology. The modal damping and frequencies of the piezoelectric shell are calculated from the poles of the system. Experimental and numerical results are presented for the modal damping and frequency of composite beams with a resistively shunted piezoceramic patch. The modal damping and frequency of plates, cylindrical shells and cylindrical composite blades with piezoelectric-resistor layers are predicted. Both analytical and experimental studies illustrate a unique dependence of modal damping and frequencies on the shunting resistance and show the effect of structural shape and curvature on piezoelectric damping.
Conducting Polymeric Hydrogel Electrolyte Based on Carboxymethylcellulose and Polyacrylamide/Polyaniline for Supercapacitor Applications

NASA Astrophysics Data System (ADS)

Suganya, N.; Jaisankar, V.; Sivakumar, E. K. T.

Conducting polymer hydrogels represent a unique class of materials that possess enormous application in flexible electronic devices. In the present work, conducting carboxymethylcellulose (CMC)-co-polyacrylamide (PAAm)/polyaniline was synthesized by a two-step interpenetrating network solution polymerization technique. The synthesized CMC-co-PAAm/polyaniline with interpenetrating network structure was prepared by in situ polymerization of aniline to enhance conductivity. The molecular structure and morphology of the copolymer hydrogels were characterized by Fourier transform infrared spectroscopy and scanning electron microscopy. The novel conducting polymer hydrogels show good electrical and electrochemical behavior, which makes them potentially useful in electronic devices such as supercapacitors, biosensors, bioelectronics, solar cells and memory devices.
Multiplex congruence network of natural numbers.

PubMed

Yan, Xiao-Yong; Wang, Wen-Xu; Chen, Guan-Rong; Shi, Ding-Hua

2016-03-31

Congruence theory has many applications in physical, social, biological and technological systems. Congruence arithmetic has been a fundamental tool for data security and computer algebra. However, much less attention was devoted to the topological features of congruence relations among natural numbers. Here, we explore the congruence relations in the setting of a multiplex network and unveil some unique and outstanding properties of the multiplex congruence network. Analytical results show that every layer therein is a sparse and heterogeneous subnetwork with a scale-free topology. Counterintuitively, every layer has an extremely strong controllability in spite of its scale-free structure that is usually difficult to control. Another amazing feature is that the controllability is robust against targeted attacks to critical nodes but vulnerable to random failures, which also differs from ordinary scale-free networks. The multi-chain structure with a small number of chain roots arising from each layer accounts for the strong controllability and the abnormal feature. The multiplex congruence network offers a graphical solution to the simultaneous congruences problem, which may have implication in cryptography based on simultaneous congruences. Our work also gains insight into the design of networks integrating advantages of both heterogeneous and homogeneous networks without inheriting their limitations.
Ground-state coding in partially connected neural networks

NASA Technical Reports Server (NTRS)

Baram, Yoram

1989-01-01

Patterns over (-1,0,1) define, by their outer products, partially connected neural networks, consisting of internally strongly connected, externally weakly connected subnetworks. The connectivity patterns may have highly organized structures, such as lattices and fractal trees or nests. Subpatterns over (-1,1) define the subcodes stored in the subnetwork, that agree in their common bits. It is first shown that the code words are locally stable stares of the network, provided that each of the subcodes consists of mutually orthogonal words or of, at most, two words. Then it is shown that if each of the subcodes consists of two orthogonal words, the code words are the unique ground states (absolute minima) of the Hamiltonian associated with the network. The regions of attraction associated with the code words are shown to grow with the number of subnetworks sharing each of the neurons. Depending on the particular network architecture, the code sizes of partially connected networks can be vastly greater than those of fully connected ones and their error correction capabilities can be significantly greater than those of the disconnected subnetworks. The codes associated with lattice-structured and hierarchical networks are discussed in some detail.
Multiplex congruence network of natural numbers

NASA Astrophysics Data System (ADS)

Yan, Xiao-Yong; Wang, Wen-Xu; Chen, Guan-Rong; Shi, Ding-Hua

2016-03-01

Congruence theory has many applications in physical, social, biological and technological systems. Congruence arithmetic has been a fundamental tool for data security and computer algebra. However, much less attention was devoted to the topological features of congruence relations among natural numbers. Here, we explore the congruence relations in the setting of a multiplex network and unveil some unique and outstanding properties of the multiplex congruence network. Analytical results show that every layer therein is a sparse and heterogeneous subnetwork with a scale-free topology. Counterintuitively, every layer has an extremely strong controllability in spite of its scale-free structure that is usually difficult to control. Another amazing feature is that the controllability is robust against targeted attacks to critical nodes but vulnerable to random failures, which also differs from ordinary scale-free networks. The multi-chain structure with a small number of chain roots arising from each layer accounts for the strong controllability and the abnormal feature. The multiplex congruence network offers a graphical solution to the simultaneous congruences problem, which may have implication in cryptography based on simultaneous congruences. Our work also gains insight into the design of networks integrating advantages of both heterogeneous and homogeneous networks without inheriting their limitations.
Structure-Based Network Analysis of Activation Mechanisms in the ErbB Family of Receptor Tyrosine Kinases: The Regulatory Spine Residues Are Global Mediators of Structural Stability and Allosteric Interactions

PubMed Central

James, Kevin A.; Verkhivker, Gennady M.

2014-01-01

The ErbB protein tyrosine kinases are among the most important cell signaling families and mutation-induced modulation of their activity is associated with diverse functions in biological networks and human disease. We have combined molecular dynamics simulations of the ErbB kinases with the protein structure network modeling to characterize the reorganization of the residue interaction networks during conformational equilibrium changes in the normal and oncogenic forms. Structural stability and network analyses have identified local communities integrated around high centrality sites that correspond to the regulatory spine residues. This analysis has provided a quantitative insight to the mechanism of mutation-induced “superacceptor” activity in oncogenic EGFR dimers. We have found that kinase activation may be determined by allosteric interactions between modules of structurally stable residues that synchronize the dynamics in the nucleotide binding site and the αC-helix with the collective motions of the integrating αF-helix and the substrate binding site. The results of this study have pointed to a central role of the conserved His-Arg-Asp (HRD) motif in the catalytic loop and the Asp-Phe-Gly (DFG) motif as key mediators of structural stability and allosteric communications in the ErbB kinases. We have determined that residues that are indispensable for kinase regulation and catalysis often corresponded to the high centrality nodes within the protein structure network and could be distinguished by their unique network signatures. The optimal communication pathways are also controlled by these nodes and may ensure efficient allosteric signaling in the functional kinase state. Structure-based network analysis has quantified subtle effects of ATP binding on conformational dynamics and stability of the EGFR structures. Consistent with the NMR studies, we have found that nucleotide-induced modulation of the residue interaction networks is not limited to the ATP site, and may enhance allosteric cooperativity with the substrate binding region by increasing communication capabilities of mediating residues. PMID:25427151
How Relations are Built within a SNS World -- Social Network Analysis on Mixi --

NASA Astrophysics Data System (ADS)

Matsuo, Yutaka; Yasud, Yuki

Our purpose here is to (1) investigate the structure of the personal networks developed on mixi, a Japanese social networking service (SNS), and (2) to consider the governing mechanism which guides participants of a SNS to form an aggregate network. Our findings are as follows:the clustering coefficient of the network is as high as 0.33 while the characteristic path lenght is as low as 5.5. A network among central users (over 300 edges) consist of two cliques, which seems to be very fragile. Community-affiliation network suggests there are several easy-entry communities which later lead users to more high-entry, unique-theme communities. The analysis on connectedness within a community reveals the importance of real-world interaction. Lastly, we depict a probable image of the entire ecology on {\\\\em mixi} among users and communities, which contributes broadly to social systems on the Web.

Communications network design and costing model technical manual

NASA Technical Reports Server (NTRS)

Logan, K. P.; Somes, S. S.; Clark, C. A.

1983-01-01

This computer model provides the capability for analyzing long-haul trunking networks comprising a set of user-defined cities, traffic conditions, and tariff rates. Networks may consist of all terrestrial connectivity, all satellite connectivity, or a combination of terrestrial and satellite connectivity. Network solutions provide the least-cost routes between all cities, the least-cost network routing configuration, and terrestrial and satellite service cost totals. The CNDC model allows analyses involving three specific FCC-approved tariffs, which are uniquely structured and representative of most existing service connectivity and pricing philosophies. User-defined tariffs that can be variations of these three tariffs are accepted as input to the model and allow considerable flexibility in network problem specification. The resulting model extends the domain of network analysis from traditional fixed link cost (distance-sensitive) problems to more complex problems involving combinations of distance and traffic-sensitive tariffs.
A systematic approach to infer biological relevance and biases of gene network structures.

PubMed

Antonov, Alexey V; Tetko, Igor V; Mewes, Hans W

2006-01-10

The development of high-throughput technologies has generated the need for bioinformatics approaches to assess the biological relevance of gene networks. Although several tools have been proposed for analysing the enrichment of functional categories in a set of genes, none of them is suitable for evaluating the biological relevance of the gene network. We propose a procedure and develop a web-based resource (BIOREL) to estimate the functional bias (biological relevance) of any given genetic network by integrating different sources of biological information. The weights of the edges in the network may be either binary or continuous. These essential features make our web tool unique among many similar services. BIOREL provides standardized estimations of the network biases extracted from independent data. By the analyses of real data we demonstrate that the potential application of BIOREL ranges from various benchmarking purposes to systematic analysis of the network biology.
An operating system for future aerospace vehicle computer systems

NASA Technical Reports Server (NTRS)

Foudriat, E. C.; Berman, W. J.; Will, R. W.; Bynum, W. L.

1984-01-01

The requirements for future aerospace vehicle computer operating systems are examined in this paper. The computer architecture is assumed to be distributed with a local area network connecting the nodes. Each node is assumed to provide a specific functionality. The network provides for communication so that the overall tasks of the vehicle are accomplished. The O/S structure is based upon the concept of objects. The mechanisms for integrating node unique objects with node common objects in order to implement both the autonomy and the cooperation between nodes is developed. The requirements for time critical performance and reliability and recovery are discussed. Time critical performance impacts all parts of the distributed operating system; e.g., its structure, the functional design of its objects, the language structure, etc. Throughout the paper the tradeoffs - concurrency, language structure, object recovery, binding, file structure, communication protocol, programmer freedom, etc. - are considered to arrive at a feasible, maximum performance design. Reliability of the network system is considered. A parallel multipath bus structure is proposed for the control of delivery time for time critical messages. The architecture also supports immediate recovery for the time critical message system after a communication failure.
Evidence of social network influence on multiple HIV risk behaviors and normative beliefs among young Tanzanian men

PubMed Central

Mulawa, Marta; Yamanis, Thespina J.; Hill, Lauren; Balvanz, Peter; Kajula, Lusajo J.; Maman, Suzanne

2016-01-01

Research on network-level influences on HIV risk behaviors among young men in sub-Saharan Africa is severely lacking. One significant gap in the literature that may provide direction for future research with this population is understanding the degree to which various HIV risk behaviors and normative beliefs cluster within men’s social networks. Such research may help us understand which HIV-related norms and behaviors have the greatest potential to be changed through social influence. Additionally, few network-based studies have described the structure of social networks of young men in sub-Saharan Africa. Understanding the structure of men’s peer networks may motivate future research examining the ways in which network structures shape the spread of information, adoption of norms, and diffusion of behaviors. We contribute to filling these gaps by using social network analysis and multilevel modeling to describe a unique dataset of mostly young men (n= 1,249 men and 242 women) nested within 59 urban social networks in Dar es Salaam, Tanzania. We examine the means, ranges, and clustering of men’s HIV-related normative beliefs and behaviors. Networks in this urban setting varied substantially in both composition and structure and a large proportion of men engaged in risky behaviors including inconsistent condom use, sexual partner concurrency, and intimate partner violence perpetration. We found significant clustering of normative beliefs and risk behaviors within these men’s social networks. Specifically, network membership explained between 5.78 and 7.17% of variance in men’s normative beliefs and between 1.93 and 15.79% of variance in risk behaviors. Our results suggest that social networks are important socialization sites for young men and may influence the adoption of norms and behaviors. We conclude by calling for more research on men’s social networks in Sub-Saharan Africa and map out several areas of future inquiry. PMID:26874081
Evidence of social network influence on multiple HIV risk behaviors and normative beliefs among young Tanzanian men.

PubMed

Mulawa, Marta; Yamanis, Thespina J; Hill, Lauren M; Balvanz, Peter; Kajula, Lusajo J; Maman, Suzanne

2016-03-01

Research on network-level influences on HIV risk behaviors among young men in sub-Saharan Africa is severely lacking. One significant gap in the literature that may provide direction for future research with this population is understanding the degree to which various HIV risk behaviors and normative beliefs cluster within men's social networks. Such research may help us understand which HIV-related norms and behaviors have the greatest potential to be changed through social influence. Additionally, few network-based studies have described the structure of social networks of young men in sub-Saharan Africa. Understanding the structure of men's peer networks may motivate future research examining the ways in which network structures shape the spread of information, adoption of norms, and diffusion of behaviors. We contribute to filling these gaps by using social network analysis and multilevel modeling to describe a unique dataset of mostly young men (n = 1249 men and 242 women) nested within 59 urban social networks in Dar es Salaam, Tanzania. We examine the means, ranges, and clustering of men's HIV-related normative beliefs and behaviors. Networks in this urban setting varied substantially in both composition and structure and a large proportion of men engaged in risky behaviors including inconsistent condom use, sexual partner concurrency, and intimate partner violence perpetration. We found significant clustering of normative beliefs and risk behaviors within these men's social networks. Specifically, network membership explained between 5.78 and 7.17% of variance in men's normative beliefs and between 1.93 and 15.79% of variance in risk behaviors. Our results suggest that social networks are important socialization sites for young men and may influence the adoption of norms and behaviors. We conclude by calling for more research on men's social networks in Sub-Saharan Africa and map out several areas of future inquiry. Copyright © 2016 Elsevier Ltd. All rights reserved.
Examining the nomological network of satisfaction with work-life balance.

PubMed

Grawitch, Matthew J; Maloney, Patrick W; Barber, Larissa K; Mooshegian, Stephanie E

2013-07-01

This study expands on past work-life research by examining the nomological network of satisfaction with work-life balance-the overall appraisal or global assessment of how one manages time and energy across work and nonwork domains. Analyses using 456 employees at a midsized organization indicated expected relationships with bidirectional conflict, bidirectional facilitation, and satisfaction with work and nonwork life. Structural equation modeling supported the utility of satisfaction with balance as a unique component of work-life interface perceptions. Results also indicated that satisfaction with balance mediated the relationship between some conflict/facilitation and life satisfaction outcomes, though conflict and facilitation maintained unique predictive validity on domain specific outcomes (i.e., work-to-life conflict and facilitation with work life satisfaction; life-to-work conflict and facilitation with nonwork life satisfaction). PsycINFO Database Record (c) 2013 APA, all rights reserved.
Hierarchical network architectures of carbon fiber paper supported cobalt oxide nanonet for high-capacity pseudocapacitors.

PubMed

Yang, Lei; Cheng, Shuang; Ding, Yong; Zhu, Xingbao; Wang, Zhong Lin; Liu, Meilin

2012-01-11

We present a high-capacity pseudocapacitor based on a hierarchical network architecture consisting of Co(3)O(4) nanowire network (nanonet) coated on a carbon fiber paper. With this tailored architecture, the electrode shows ideal capacitive behavior (rectangular shape of cyclic voltammograms) and large specific capacitance (1124 F/g) at high charge/discharge rate (25.34 A/g), still retaining ~94% of the capacitance at a much lower rate of 0.25 A/g. The much-improved capacity, rate capability, and cycling stability may be attributed to the unique hierarchical network structures, which improves electron/ion transport, enhances the kinetics of redox reactions, and facilitates facile stress relaxation during cycling. © 2011 American Chemical Society
A neuro-fuzzy architecture for real-time applications

NASA Technical Reports Server (NTRS)

Ramamoorthy, P. A.; Huang, Song

1992-01-01

Neural networks and fuzzy expert systems perform the same task of functional mapping using entirely different approaches. Each approach has certain unique features. The ability to learn specific input-output mappings from large input/output data possibly corrupted by noise and the ability to adapt or continue learning are some important features of neural networks. Fuzzy expert systems are known for their ability to deal with fuzzy information and incomplete/imprecise data in a structured, logical way. Since both of these techniques implement the same task (that of functional mapping--we regard 'inferencing' as one specific category under this class), a fusion of the two concepts that retains their unique features while overcoming their individual drawbacks will have excellent applications in the real world. In this paper, we arrive at a new architecture by fusing the two concepts. The architecture has the trainability/adaptibility (based on input/output observations) property of the neural networks and the architectural features that are unique to fuzzy expert systems. It also does not require specific information such as fuzzy rules, defuzzification procedure used, etc., though any such information can be integrated into the architecture. We show that this architecture can provide better performance than is possible from a single two or three layer feedforward neural network. Further, we show that this new architecture can be used as an efficient vehicle for hardware implementation of complex fuzzy expert systems for real-time applications. A numerical example is provided to show the potential of this approach.
Urban occupational structures as information networks: The effect on network density of increasing number of occupations.

PubMed

Shutters, Shade T; Lobo, José; Muneepeerakul, Rachata; Strumsky, Deborah; Mellander, Charlotta; Brachert, Matthias; Farinha, Teresa; Bettencourt, Luis M A

2018-01-01

Urban economies are composed of diverse activities, embodied in labor occupations, which depend on one another to produce goods and services. Yet little is known about how the nature and intensity of these interdependences change as cities increase in population size and economic complexity. Understanding the relationship between occupational interdependencies and the number of occupations defining an urban economy is relevant because interdependence within a networked system has implications for system resilience and for how easily can the structure of the network be modified. Here, we represent the interdependencies among occupations in a city as a non-spatial information network, where the strengths of interdependence between pairs of occupations determine the strengths of the links in the network. Using those quantified link strengths we calculate a single metric of interdependence-or connectedness-which is equivalent to the density of a city's weighted occupational network. We then examine urban systems in six industrialized countries, analyzing how the density of urban occupational networks changes with network size, measured as the number of unique occupations present in an urban workforce. We find that in all six countries, density, or economic interdependence, increases superlinearly with the number of distinct occupations. Because connections among occupations represent flows of information, we provide evidence that connectivity scales superlinearly with network size in information networks.
Urban occupational structures as information networks: The effect on network density of increasing number of occupations

PubMed Central

Lobo, José; Muneepeerakul, Rachata; Strumsky, Deborah; Mellander, Charlotta; Brachert, Matthias; Farinha, Teresa; Bettencourt, Luis M. A.

2018-01-01

Urban economies are composed of diverse activities, embodied in labor occupations, which depend on one another to produce goods and services. Yet little is known about how the nature and intensity of these interdependences change as cities increase in population size and economic complexity. Understanding the relationship between occupational interdependencies and the number of occupations defining an urban economy is relevant because interdependence within a networked system has implications for system resilience and for how easily can the structure of the network be modified. Here, we represent the interdependencies among occupations in a city as a non-spatial information network, where the strengths of interdependence between pairs of occupations determine the strengths of the links in the network. Using those quantified link strengths we calculate a single metric of interdependence–or connectedness–which is equivalent to the density of a city’s weighted occupational network. We then examine urban systems in six industrialized countries, analyzing how the density of urban occupational networks changes with network size, measured as the number of unique occupations present in an urban workforce. We find that in all six countries, density, or economic interdependence, increases superlinearly with the number of distinct occupations. Because connections among occupations represent flows of information, we provide evidence that connectivity scales superlinearly with network size in information networks. PMID:29734354
Light scattering optimization of chitin random network in ultrawhite beetle scales

NASA Astrophysics Data System (ADS)

Utel, Francesco; Cortese, Lorenzo; Pattelli, Lorenzo; Burresi, Matteo; Vignolini, Silvia; Wiersma, Diederik

2017-09-01

Among the natural white colored photonics structures, a bio-system has become of great interest in the field of disordered optical media: the scale of the white beetle Chyphochilus. Despite its low thickness, on average 7 μm, and low refractive index, this beetle exhibits extreme high brightness and unique whiteness. These properties arise from the interaction of light with a complex network of chitin nano filaments embedded in the interior of the scales. As it's been recently claimed, this could be a consequence of the peculiar morphology of the filaments network that, by means of high filling fraction (0.61) and structural anisotropy, optimizes the multiple scattering of light. We therefore performed a numerical analysis on the structural properties of the chitin network in order to understand their role in the enhancement of the scale scattering intensity. Modeling the filaments as interconnected rod shaped scattering centers, we numerically generated the spatial coordinates of the network components. Controlling the quantities that are claimed to play a fundamental role in the brightness and whiteness properties of the investigated system (filling fraction and average rods orientation, i.e. the anisotropy of the ensemble of scattering centers), we obtained a set of customized random networks. FDTD simulations of light transport have been performed on these systems, observing high reflectance for all the visible frequencies and proving the implemented algorithm to numerically generate the structures is suitable to investigate the dependence of reflectance by anisotropy.
DNA-nanoparticle assemblies go organic: macroscopic polymeric materials with nanosized features.

PubMed

Mentovich, Elad D; Livanov, Konstantin; Prusty, Deepak K; Sowwan, Mukules; Richter, Shachar

2012-05-30

One of the goals in the field of structural DNA nanotechnology is the use of DNA to build up 2- and 3-D nanostructures. The research in this field is motivated by the remarkable structural features of DNA as well as by its unique and reversible recognition properties. Nucleic acids can be used alone as the skeleton of a broad range of periodic nanopatterns and nanoobjects and in addition, DNA can serve as a linker or template to form DNA-hybrid structures with other materials. This approach can be used for the development of new detection strategies as well as nanoelectronic structures and devices. Here we present a new method for the generation of unprecedented all-organic conjugated-polymer nanoparticle networks guided by DNA, based on a hierarchical self-assembly process. First, microphase separation of amphiphilic block copolymers induced the formation of spherical nanoobjects. As a second ordering concept, DNA base pairing has been employed for the controlled spatial definition of the conjugated-polymer particles within the bulk material. These networks offer the flexibility and the diversity of soft polymeric materials. Thus, simple chemical methodologies could be applied in order to tune the network's electrical, optical and mechanical properties. One- two- and three-dimensional networks have been successfully formed. Common to all morphologies is the integrity of the micelles consisting of DNA block copolymer (DBC), which creates an all-organic engineered network.
A Facile Method for Synthesizing Dendritic Core–Shell Structured Ternary Metallic Aerogels and Their Enhanced Electrochemical Performances

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

Shi, Qiurong; Zhu, Chengzhou; Li, Yijing

2016-11-08

Currently, three dimensional self-supported metallic structures are attractive for their unique properties of high porosity, low density, excellent conductivity etc. that promote their wide application in fuel cells. Here, for the first time, we report a facile synthesis of dendritic core-shell structured Au/Pt3Pd ternary metallic aerogels via a one-pot self-assembly gelation strategy. The as-prepared Au/Pt3Pd ternary metallic aerogels demonstrated superior electrochemical performances toward oxygen reduction reaction compared to commercial Pt/C. The unique dendritic core-shell structures, Pt3Pd alloyed shells and the cross-linked network structures are beneficial for the electrochemical oxygen reduction reaction performances of the Pt-based materials via the electronic effect,more » geometric effect and synergistic effect. This strategy of fabrication of metallic hydrogels and aerogels as well as their exceptional properties hold great promise in a variety of applications.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)

Bradonjic, Milan; Hagberg, Aric; Hengartner, Nick

We analyze component evolution in general random intersection graphs (RIGs) and give conditions on existence and uniqueness of the giant component. Our techniques generalize the existing methods for analysis on component evolution in RIGs. That is, we analyze survival and extinction properties of a dependent, inhomogeneous Galton-Watson branching process on general RIGs. Our analysis relies on bounding the branching processes and inherits the fundamental concepts from the study on component evolution in Erdos-Renyi graphs. The main challenge becomes from the underlying structure of RIGs, when the number of offsprings follows a binomial distribution with a different number of nodes andmore » different rate at each step during the evolution. RIGs can be interpreted as a model for large randomly formed non-metric data sets. Besides the mathematical analysis on component evolution, which we provide in this work, we perceive RIGs as an important random structure which has already found applications in social networks, epidemic networks, blog readership, or wireless sensor networks.« less
Obtaining Arbitrary Prescribed Mean Field Dynamics for Recurrently Coupled Networks of Type-I Spiking Neurons with Analytically Determined Weights

PubMed Central

Nicola, Wilten; Tripp, Bryan; Scott, Matthew

2016-01-01

A fundamental question in computational neuroscience is how to connect a network of spiking neurons to produce desired macroscopic or mean field dynamics. One possible approach is through the Neural Engineering Framework (NEF). The NEF approach requires quantities called decoders which are solved through an optimization problem requiring large matrix inversion. Here, we show how a decoder can be obtained analytically for type I and certain type II firing rates as a function of the heterogeneity of its associated neuron. These decoders generate approximants for functions that converge to the desired function in mean-squared error like 1/N, where N is the number of neurons in the network. We refer to these decoders as scale-invariant decoders due to their structure. These decoders generate weights for a network of neurons through the NEF formula for weights. These weights force the spiking network to have arbitrary and prescribed mean field dynamics. The weights generated with scale-invariant decoders all lie on low dimensional hypersurfaces asymptotically. We demonstrate the applicability of these scale-invariant decoders and weight surfaces by constructing networks of spiking theta neurons that replicate the dynamics of various well known dynamical systems such as the neural integrator, Van der Pol system and the Lorenz system. As these decoders are analytically determined and non-unique, the weights are also analytically determined and non-unique. We discuss the implications for measured weights of neuronal networks. PMID:26973503
Obtaining Arbitrary Prescribed Mean Field Dynamics for Recurrently Coupled Networks of Type-I Spiking Neurons with Analytically Determined Weights.

PubMed

Nicola, Wilten; Tripp, Bryan; Scott, Matthew

2016-01-01

A fundamental question in computational neuroscience is how to connect a network of spiking neurons to produce desired macroscopic or mean field dynamics. One possible approach is through the Neural Engineering Framework (NEF). The NEF approach requires quantities called decoders which are solved through an optimization problem requiring large matrix inversion. Here, we show how a decoder can be obtained analytically for type I and certain type II firing rates as a function of the heterogeneity of its associated neuron. These decoders generate approximants for functions that converge to the desired function in mean-squared error like 1/N, where N is the number of neurons in the network. We refer to these decoders as scale-invariant decoders due to their structure. These decoders generate weights for a network of neurons through the NEF formula for weights. These weights force the spiking network to have arbitrary and prescribed mean field dynamics. The weights generated with scale-invariant decoders all lie on low dimensional hypersurfaces asymptotically. We demonstrate the applicability of these scale-invariant decoders and weight surfaces by constructing networks of spiking theta neurons that replicate the dynamics of various well known dynamical systems such as the neural integrator, Van der Pol system and the Lorenz system. As these decoders are analytically determined and non-unique, the weights are also analytically determined and non-unique. We discuss the implications for measured weights of neuronal networks.
Unsupervised learning of contextual constraints in neural networks for simultaneous visual processing of multiple objects

NASA Astrophysics Data System (ADS)

Marshall, Jonathan A.

1992-12-01

A simple self-organizing neural network model, called an EXIN network, that learns to process sensory information in a context-sensitive manner, is described. EXIN networks develop efficient representation structures for higher-level visual tasks such as segmentation, grouping, transparency, depth perception, and size perception. Exposure to a perceptual environment during a developmental period serves to configure the network to perform appropriate organization of sensory data. A new anti-Hebbian inhibitory learning rule permits superposition of multiple simultaneous neural activations (multiple winners), while maintaining contextual consistency constraints, instead of forcing winner-take-all pattern classifications. The activations can represent multiple patterns simultaneously and can represent uncertainty. The network performs parallel parsing, credit attribution, and simultaneous constraint satisfaction. EXIN networks can learn to represent multiple oriented edges even where they intersect and can learn to represent multiple transparently overlaid surfaces defined by stereo or motion cues. In the case of stereo transparency, the inhibitory learning implements both a uniqueness constraint and permits coactivation of cells representing multiple disparities at the same image location. Thus two or more disparities can be active simultaneously without interference. This behavior is analogous to that of Prazdny's stereo vision algorithm, with the bonus that each binocular point is assigned a unique disparity. In a large implementation, such a NN would also be able to represent effectively the disparities of a cloud of points at random depths, like human observers, and unlike Prazdny's method
Understanding Classrooms through Social Network Analysis: A Primer for Social Network Analysis in Education Research.

PubMed

Grunspan, Daniel Z; Wiggins, Benjamin L; Goodreau, Steven M

2014-01-01

Social interactions between students are a major and underexplored part of undergraduate education. Understanding how learning relationships form in undergraduate classrooms, as well as the impacts these relationships have on learning outcomes, can inform educators in unique ways and improve educational reform. Social network analysis (SNA) provides the necessary tool kit for investigating questions involving relational data. We introduce basic concepts in SNA, along with methods for data collection, data processing, and data analysis, using a previously collected example study on an undergraduate biology classroom as a tutorial. We conduct descriptive analyses of the structure of the network of costudying relationships. We explore generative processes that create observed study networks between students and also test for an association between network position and success on exams. We also cover practical issues, such as the unique aspects of human subjects review for network studies. Our aims are to convince readers that using SNA in classroom environments allows rich and informative analyses to take place and to provide some initial tools for doing so, in the process inspiring future educational studies incorporating relational data. © 2014 D. Z. Grunspan et al. CBE—Life Sciences Education © 2014 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).
Religious networking organizations and social justice: an ethnographic case study.

PubMed

Todd, Nathan R

2012-09-01

The current study provides an innovative examination of how and why religious networking organizations work for social justice in their local community. Similar to a coalition or community coordinating council, religious networking organizations are formal organizations comprised of individuals from multiple religious congregations who consistently meet to organize around a common goal. Based on over a year and a half of ethnographic participation in two separate religious networking organizations focused on community betterment and social justice, this study reports on the purpose and structure of these organizations, how each used networking to create social capital, and how religion was integrated into the organizations' social justice work. Findings contribute to the growing literature on social capital, empowering community settings, and the unique role of religious settings in promoting social justice. Implications for future research and practice also are discussed.
Structures of the Bacillus subtilis Glutamine Synthetase Dodecamer Reveal Large Intersubunit Catalytic Conformational Changes Linked to a Unique Feedback Inhibition Mechanism*

PubMed Central

Murray, David S.; Chinnam, Nagababu; Tonthat, Nam Ky; Whitfill, Travis; Wray, Lewis V.; Fisher, Susan H.; Schumacher, Maria A.

2013-01-01

Glutamine synthetase (GS), which catalyzes the production of glutamine, plays essential roles in nitrogen metabolism. There are two main bacterial GS isoenzymes, GSI-α and GSI-β. GSI-α enzymes, which have not been structurally characterized, are uniquely feedback-inhibited by Gln. To gain insight into GSI-α function, we performed biochemical and cellular studies and obtained structures for all GSI-α catalytic and regulatory states. GSI-α forms a massive 600-kDa dodecameric machine. Unlike other characterized GS, the Bacillus subtilis enzyme undergoes dramatic intersubunit conformational alterations during formation of the transition state. Remarkably, these changes are required for active site construction. Feedback inhibition arises from a hydrogen bond network between Gln, the catalytic glutamate, and the GSI-α-specific residue, Arg62, from an adjacent subunit. Notably, Arg62 must be ejected for proper active site reorganization. Consistent with these findings, an R62A mutation abrogates Gln feedback inhibition but does not affect catalysis. Thus, these data reveal a heretofore unseen restructuring of an enzyme active site that is coupled with an isoenzyme-specific regulatory mechanism. This GSI-α-specific regulatory network could be exploited for inhibitor design against Gram-positive pathogens. PMID:24158439

Social network types and well-being among South Korean older adults.

PubMed

Park, Sojung; Smith, Jacqui; Dunkle, Ruth E

2014-01-01

The social networks of older individuals reflect personal life history and cultural factors. Despite these two sources of variation, four similar network types have been identified in Europe, North America, Japan, and China: namely 'restricted', 'family', 'friend', and 'diverse'. This study identified the social network types of Korean older adults and examined differential associations of the network types with well-being. The analysis used data from the 2008 wave of the Korean Longitudinal Study of Aging (KLoSA: N = 4251, age range 65-108). We used a two-step cluster analytical approach to identify network types from seven indicators of network structure and function. Regression models determined associations between network types and well-being outcomes, including life satisfaction and depressive symptomatology. Cluster analysis of indicators of network structure and function revealed four types, including the restricted, friend, and diverse types. Instead of a family type, we found a couple-focused type. The young-old (age 65-74) were more likely to be in the couple-focused type and more of the oldest old (age 85+) belonged to the restricted type. Compared with the restricted network, older adults in all other networks were more likely to report higher life satisfaction and lower depressive symptomatology. Life course and cohort-related factors contribute to similarities across societies in network types and their associations with well-being. Korean-specific life course and socio-historical factors, however, may contribute to our unique findings about network types.
Structural Mechanisms of Plant Glucan Phosphatases in Starch Metabolism

PubMed Central

Meekins, David A.; Vander Kooi, Craig W.; Gentry, Matthew S.

2016-01-01

Glucan phosphatases are a recently discovered class of enzymes that dephosphorylate starch and glycogen, thereby regulating energy metabolism. Plant genomes encode for two glucan phosphatases called Starch EXcess4 (SEX4) and Like Sex Four2 (LSF2) that regulate starch metabolism by selectively dephosphorylating glucose moieties within starch glucan chains. Recently, the structures of both SEX4 and LSF2 were determined, with and without phosphoglucan products bound, revealing the mechanism for their unique activities. This review explores the structural and enzymatic features of the plant glucan phosphatases and outlines how they are uniquely adapted for carrying out their cellular functions. We outline the physical mechanisms employed by SEX4 and LSF2 to interact with starch glucans: SEX4 binds glucan chains via a continuous glucan binding platform comprised of its Dual Specificity Phosphatase (DSP) domain and Carbohydrate Binding Module (CBM) while LSF2 utilizes Surface Binding Sites (SBSs). SEX4 and LSF2 both contain a unique network of aromatic residues in their catalytic DSP domains that serve as glucan engagement platforms and are unique to the glucan phosphatases. We also discuss the phosphoglucan substrate specificities inherent to SEX4 and LSF2 and outline structural features within the active site that govern glucan orientation. This review defines the structural mechanism of the plant glucan phosphatases with respect to phosphatases, starch metabolism, and protein-glucan interaction; thereby providing a framework for their applications in both agricultural and industrial settings. PMID:26934589
An economic model of friendship and enmity for measuring social balance in networks

NASA Astrophysics Data System (ADS)

Lee, Kyu-Min; Shin, Euncheol; You, Seungil

2017-12-01

We propose a dynamic economic model of networks where agents can be friends or enemies with one another. This is a decentralized relationship model in that agents decide whether to change their relationships so as to minimize their imbalanced triads. In this model, there is a single parameter, which we call social temperature, that captures the degree to which agents care about social balance in their relationships. We show that the global structure of relationship configuration converges to a unique stationary distribution. Using this stationary distribution, we characterize the maximum likelihood estimator of the social temperature parameter. Since the estimator is computationally challenging to calculate from real social network datasets, we provide a simple simulation algorithm and verify its performance with real social network datasets.
The ground truth about metadata and community detection in networks.

PubMed

Peel, Leto; Larremore, Daniel B; Clauset, Aaron

2017-05-01

Across many scientific domains, there is a common need to automatically extract a simplified view or coarse-graining of how a complex system's components interact. This general task is called community detection in networks and is analogous to searching for clusters in independent vector data. It is common to evaluate the performance of community detection algorithms by their ability to find so-called ground truth communities. This works well in synthetic networks with planted communities because these networks' links are formed explicitly based on those known communities. However, there are no planted communities in real-world networks. Instead, it is standard practice to treat some observed discrete-valued node attributes, or metadata, as ground truth. We show that metadata are not the same as ground truth and that treating them as such induces severe theoretical and practical problems. We prove that no algorithm can uniquely solve community detection, and we prove a general No Free Lunch theorem for community detection, which implies that there can be no algorithm that is optimal for all possible community detection tasks. However, community detection remains a powerful tool and node metadata still have value, so a careful exploration of their relationship with network structure can yield insights of genuine worth. We illustrate this point by introducing two statistical techniques that can quantify the relationship between metadata and community structure for a broad class of models. We demonstrate these techniques using both synthetic and real-world networks, and for multiple types of metadata and community structures.
Time-dependent breakdown of fiber networks: Uncertainty of lifetime

NASA Astrophysics Data System (ADS)

Mattsson, Amanda; Uesaka, Tetsu

2017-05-01

Materials often fail when subjected to stresses over a prolonged period. The time to failure, also called the lifetime, is known to exhibit large variability of many materials, particularly brittle and quasibrittle materials. For example, a coefficient of variation reaches 100% or even more. Its distribution shape is highly skewed toward zero lifetime, implying a large number of premature failures. This behavior contrasts with that of normal strength, which shows a variation of only 4%-10% and a nearly bell-shaped distribution. The fundamental cause of this large and unique variability of lifetime is not well understood because of the complex interplay between stochastic processes taking place on the molecular level and the hierarchical and disordered structure of the material. We have constructed fiber network models, both regular and random, as a paradigm for general material structures. With such networks, we have performed Monte Carlo simulations of creep failure to establish explicit relationships among fiber characteristics, network structures, system size, and lifetime distribution. We found that fiber characteristics have large, sometimes dominating, influences on the lifetime variability of a network. Among the factors investigated, geometrical disorders of the network were found to be essential to explain the large variability and highly skewed shape of the lifetime distribution. With increasing network size, the distribution asymptotically approaches a double-exponential form. The implication of this result is that, so-called "infant mortality," which is often predicted by the Weibull approximation of the lifetime distribution, may not exist for a large system.
MISS-Prot: web server for self/non-self discrimination of protein residue networks in parasites; theory and experiments in Fasciola peptides and Anisakis allergens.

PubMed

González-Díaz, Humberto; Muíño, Laura; Anadón, Ana M; Romaris, Fernanda; Prado-Prado, Francisco J; Munteanu, Cristian R; Dorado, Julián; Sierra, Alejandro Pazos; Mezo, Mercedes; González-Warleta, Marta; Gárate, Teresa; Ubeira, Florencio M

2011-06-01

Infections caused by human parasites (HPs) affect the poorest 500 million people worldwide but chemotherapy has become expensive, toxic, and/or less effective due to drug resistance. On the other hand, many 3D structures in Protein Data Bank (PDB) remain without function annotation. We need theoretical models to quickly predict biologically relevant Parasite Self Proteins (PSP), which are expressed differentially in a given parasite and are dissimilar to proteins expressed in other parasites and have a high probability to become new vaccines (unique sequence) or drug targets (unique 3D structure). We present herein a model for PSPs in eight different HPs (Ascaris, Entamoeba, Fasciola, Giardia, Leishmania, Plasmodium, Trypanosoma, and Toxoplasma) with 90% accuracy for 15 341 training and validation cases. The model combines protein residue networks, Markov Chain Models (MCM) and Artificial Neural Networks (ANN). The input parameters are the spectral moments of the Markov transition matrix for electrostatic interactions associated with the protein residue complex network calculated with the MARCH-INSIDE software. We implemented this model in a new web-server called MISS-Prot (MARCH-INSIDE Scores for Self-Proteins). MISS-Prot was programmed using PHP/HTML/Python and MARCH-INSIDE routines and is freely available at: . This server is easy to use by non-experts in Bioinformatics who can carry out automatic online upload and prediction with 3D structures deposited at PDB (mode 1). We can also study outcomes of Peptide Mass Fingerprinting (PMFs) and MS/MS for query proteins with unknown 3D structures (mode 2). We illustrated the use of MISS-Prot in experimental and/or theoretical studies of peptides from Fasciola hepatica cathepsin proteases or present on 10 Anisakis simplex allergens (Ani s 1 to Ani s 10). In doing so, we combined electrophoresis (1DE), MALDI-TOF Mass Spectroscopy, and MASCOT to seek sequences, Molecular Mechanics + Molecular Dynamics (MM/MD) to generate 3D structures and MISS-Prot to predict PSP scores. MISS-Prot also allows the prediction of PSP proteins in 16 additional species including parasite hosts, fungi pathogens, disease transmission vectors, and biotechnologically relevant organisms.
The Network Structure of Symptoms of the Diagnostic and Statistical Manual of Mental Disorders.

PubMed

Boschloo, Lynn; van Borkulo, Claudia D; Rhemtulla, Mijke; Keyes, Katherine M; Borsboom, Denny; Schoevers, Robert A

2015-01-01

Although current classification systems have greatly contributed to the reliability of psychiatric diagnoses, they ignore the unique role of individual symptoms and, consequently, potentially important information is lost. The network approach, in contrast, assumes that psychopathology results from the causal interplay between psychiatric symptoms and focuses specifically on these symptoms and their complex associations. By using a sophisticated network analysis technique, this study constructed an empirically based network structure of 120 psychiatric symptoms of twelve major DSM-IV diagnoses using cross-sectional data of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC, second wave; N = 34,653). The resulting network demonstrated that symptoms within the same diagnosis showed differential associations and indicated that the strategy of summing symptoms, as in current classification systems, leads to loss of information. In addition, some symptoms showed strong connections with symptoms of other diagnoses, and these specific symptom pairs, which both concerned overlapping and non-overlapping symptoms, may help to explain the comorbidity across diagnoses. Taken together, our findings indicated that psychopathology is very complex and can be more adequately captured by sophisticated network models than current classification systems. The network approach is, therefore, promising in improving our understanding of psychopathology and moving our field forward.
A review and analysis of neural networks for classification of remotely sensed multispectral imagery

NASA Technical Reports Server (NTRS)

Paola, Justin D.; Schowengerdt, Robert A.

1993-01-01

A literature survey and analysis of the use of neural networks for the classification of remotely sensed multispectral imagery is presented. As part of a brief mathematical review, the backpropagation algorithm, which is the most common method of training multi-layer networks, is discussed with an emphasis on its application to pattern recognition. The analysis is divided into five aspects of neural network classification: (1) input data preprocessing, structure, and encoding; (2) output encoding and extraction of classes; (3) network architecture, (4) training algorithms; and (5) comparisons to conventional classifiers. The advantages of the neural network method over traditional classifiers are its non-parametric nature, arbitrary decision boundary capabilities, easy adaptation to different types of data and input structures, fuzzy output values that can enhance classification, and good generalization for use with multiple images. The disadvantages of the method are slow training time, inconsistent results due to random initial weights, and the requirement of obscure initialization values (e.g., learning rate and hidden layer size). Possible techniques for ameliorating these problems are discussed. It is concluded that, although the neural network method has several unique capabilities, it will become a useful tool in remote sensing only if it is made faster, more predictable, and easier to use.
N-doped yolk-shell hollow carbon sphere wrapped with graphene as sulfur host for high-performance lithium-sulfur batteries

NASA Astrophysics Data System (ADS)

Zhang, Yongzheng; Sun, Kai; Liang, Zhan; Wang, Yanli; Ling, Licheng

2018-01-01

N-doped yolk-shell hollow carbon sphere wrapped with reduced graphene oxide (rGO/N-YSHCS) is designed and fabricated as sulfur host for lithium-sulfur batteries. The shuttle effect of polysulfides can be suppressed effectively by the porous yolk-shell structure, graphene layer and N-doping. A good conductivity network is provided for electron transportation through the graphene layer coupled with the unique yolk-shell carbon matrix. Such unique structure offers the synthesized rGO/N-YSHCS/S electrode with a high reversible capacity (800 mAh g-1 at 0.2 C after 100 cycles) and good high-rate capability (636 mAh g-1 at 1 C and 540 mAh g-1 at 2 C).
Enabling Community Through Social Media

PubMed Central

Haythornthwaite, Caroline

2013-01-01

Background Social network analysis provides a perspective and method for inquiring into the structures that comprise online groups and communities. Traces from interaction via social media provide the opportunity for understanding how a community is formed and maintained online. Objective The paper aims to demonstrate how social network analysis provides a vocabulary and set of techniques for examining interaction patterns via social media. Using the case of the #hcsmca online discussion forum, this paper highlights what has been and can be gained by approaching online community from a social network perspective, as well as providing an inside look at the structure of the #hcsmca community. Methods Social network analysis was used to examine structures in a 1-month sample of Twitter messages with the hashtag #hcsmca (3871 tweets, 486 unique posters), which is the tag associated with the social media–supported group Health Care Social Media Canada. Network connections were considered present if the individual was mentioned, replied to, or had a post retweeted. Results Network analyses revealed patterns of interaction that characterized the community as comprising one component, with a set of core participants prominent in the network due to their connections with others. Analysis showed the social media health content providers were the most influential group based on in-degree centrality. However, there was no preferential attachment among people in the same professional group, indicating that the formation of connections among community members was not constrained by professional status. Conclusions Network analysis and visualizations provide techniques and a vocabulary for understanding online interaction, as well as insights that can help in understanding what, and who, comprises and sustains a network, and whether community emerges from a network of online interactions. PMID:24176835
Reducing emergency bed-days for older people? Network governance lessons from the 'Improving the Future for Older People' programme.

PubMed

Sheaff, Rod; Windle, Karen; Wistow, Gerald; Ashby, Sue; Beech, Roger; Dickinson, Angela; Henderson, Catherine; Knapp, Martin

2014-04-01

In 2007, the UK government set performance targets and public service agreements to control the escalation of emergency bed-days. Some years earlier, nine English local authorities had each created local networks with their health and third sector partners to tackle this increase. These networks formed the 'Improving the Future for Older People' initiative (IFOP), one strand of the national 'Innovation Forum' programme, set up in 2003. The nine sites set themselves one headline target to be achieved jointly over three years; a 20 per cent reduction in the number of emergency bed-days used by people aged 75 and over. Three ancillary targets were also monitored: emergency admissions, delayed discharges and project sustainability. Collectively the sites exceeded their headline target. Using a realistic evaluation approach, we explored which aspects of network governance appeared to have contributed to these emergency bed-day reductions. We found no simple link between network governance type and outcomes. The governance features associated with an effective IFOP network appeared to suggest that the selection and implementation of a small number of evidence-based services was central to networks' effectiveness. Each service needed to be coordinated by a network-based strategic group and hierarchically implemented at operational level by the responsible network member. Having a network-based implementation group with a 'joined-at-the-top' governance structure also appeared to promote network effectiveness. External factors, including NHS incentives, health reorganisations and financial targets similarly contributed to differences in performance. Targets and financial incentives could focus action but undermine horizontal networking. Local networks should specify which interventions network structures are intended to deliver. Effective projects are those likely to be evidence based, unique to the network and difficult to implement through vertical structures alone. Copyright © 2014 Elsevier Ltd. All rights reserved.
Cooperation and coexpression: How coexpression networks shift in response to multiple mutualists.

PubMed

Palakurty, Sathvik X; Stinchcombe, John R; Afkhami, Michelle E

2018-04-01

A mechanistic understanding of community ecology requires tackling the nonadditive effects of multispecies interactions, a challenge that necessitates integration of ecological and molecular complexity-namely moving beyond pairwise ecological interaction studies and the "gene at a time" approach to mechanism. Here, we investigate the consequences of multispecies mutualisms for the structure and function of genomewide differential coexpression networks for the first time, using the tractable and ecologically important interaction between legume Medicago truncatula, rhizobia and mycorrhizal fungi. First, we found that genes whose expression is affected nonadditively by multiple mutualists are more highly connected in gene networks than expected by chance and had 94% greater network centrality than genes showing additive effects, suggesting that nonadditive genes may be key players in the widespread transcriptomic responses to multispecies symbioses. Second, multispecies mutualisms substantially changed coexpression network structure of 18 modules of host plant genes and 22 modules of the fungal symbionts' genes, indicating that third-party mutualists can cause significant rewiring of plant and fungal molecular networks. Third, we found that 60% of the coexpressed gene sets that explained variation in plant performance had coexpression structures that were altered by interactive effects of rhizobia and fungi. Finally, an "across-symbiosis" approach identified sets of plant and mycorrhizal genes whose coexpression structure was unique to the multiple mutualist context and suggested coupled responses across the plant-mycorrhizal interaction to rhizobial mutualists. Taken together, these results show multispecies mutualisms have substantial effects on the molecular interactions in host plants, microbes and across symbiotic boundaries. © 2018 John Wiley & Sons Ltd.
Water: a responsive small molecule.

PubMed

Shultz, Mary Jane; Vu, Tuan Hoang; Meyer, Bryce; Bisson, Patrick

2012-01-17

Unique among small molecules, water forms a nearly tetrahedral yet flexible hydrogen-bond network. In addition to its flexibility, this network is dynamic: bonds are formed or broken on a picosecond time scale. These unique features make probing the local structure of water challenging. Despite the challenges, there is intense interest in developing a picture of the local water structure due to water's fundamental importance in many fields of chemistry. Understanding changes in the local network structure of water near solutes likely holds the key to unlock problems from analyzing parameters that determine the three dimensional structure of proteins to modeling the fate of volatile materials released into the atmosphere. Pictures of the local structure of water are heavily influenced by what is known about the structure of ice. In hexagonal I(h) ice, the most stable form of solid water under ordinary conditions, water has an equal number of donor and acceptor bonds; a kind of symmetry. This symmetric tetrahedral coordination is only approximately preserved in the liquid. The most obvious manifestation of this altered tetrahedral bonding is the greater density in the liquid compared with the solid. Formation of an interface or addition of solutes further modifies the local bonding in water. Because the O-H stretching frequency is sensitive to the environment, vibrational spectroscopy provides an excellent probe for the hydrogen-bond structure in water. In this Account, we examine both local interactions between water and small solutes and longer range interactions at the aqueous surface. Locally, the results suggest that water is not a symmetric donor or acceptor, but rather has a propensity to act as an acceptor. In interactions with hydrocarbons, action is centered at the water oxygen. For soluble inorganic salts, interaction is greater with the cation than the anion. The vibrational spectrum of the surface of salt solutions is altered compared with that of neat water. Studies of local salt-water interactions suggest that the picture of the local water structure and the ion distribution at the surface deduced from the surface vibrational spectrum should encompass both ions of the salt.
Hybrid aerogel-derived Sn-Ni alloy immobilized within porous carbon/graphene dual matrices for high-performance lithium storage.

PubMed

Zhang, Hao; Zhang, Mengru; Zhang, Meiling; Zhang, Lin; Zhang, Anping; Zhou, Yiming; Wu, Ping; Tang, Yawen

2017-09-01

Nanoporous networks of tin-based alloys immobilized within carbon matrices possess unique structural and compositional superiorities toward lithium-storage, and are expected to manifest improved strain-accommodation and charge-transport capabilities and thus desirable anodic performance for advanced lithium-ion batteries (LIBs). Herein, a facile and scalable hybrid aerogel-derived thermal-autoreduction route has been developed for the construction of nanoporous network of SnNi alloy immobilized within carbon/graphene dual matrices (SnNi@C/G network). When applied as an anode material for LIBs, the SnNi@C/G network manifests desirable lithium-storage performances in terms of specific capacities, cycle life, and rate capability. The facile aerogel-derived route and desirable Li-storage performance of the SnNi@C/G network facilitate its practical application as a high-capacity, long-life, and high-rate anode material for advanced LIBs. Copyright © 2017 Elsevier Inc. All rights reserved.
Liking and hyperlinking: Community detection in online child sexual exploitation networks.

PubMed

Westlake, Bryce G; Bouchard, Martin

2016-09-01

The online sexual exploitation of children is facilitated by websites that form virtual communities, via hyperlinks, to distribute images, videos, and other material. However, how these communities form, are structured, and evolve over time is unknown. Collected using a custom-designed webcrawler, we begin from known child sexual exploitation (CE) seed websites and follow hyperlinks to connected, related, websites. Using a repeated measure design we analyze 10 networks of 300 + websites each - over 4.8 million unique webpages in total, over a period of 60 weeks. Community detection techniques reveal that CE-related networks were dominated by two large communities hosting varied material -not necessarily matching the seed website. Community stability, over 60 weeks, varied across networks. Reciprocity in hyperlinking between community members was substantially higher than within the full network, however, websites were not more likely to connect to homogeneous-content websites. Copyright © 2016 Elsevier Inc. All rights reserved.
The Impact of Large Urban Structural Elements on Traffic Flow a Case Study of Danwei and Xiaoqu in Shanghai

NASA Astrophysics Data System (ADS)

Lyu, H.; Ding, L.; Fan, H.; Meng, L.

2017-09-01

Danwei (working unit) and Xiaoqu (residential community) are two typical and unique structural urban elements in China. The interior roads of Danwei and Xiaoqu are usually not accessible for the public. Recently, there is a call for opening these interior roads to the public to improve road network structure and optimize traffic flow. In this paper we investigate the impact of Danwei and Xiaoqu on their neighbouring traffic quantitatively. By taking into consideration of origins and destinations (ODs) distributions and route selection behaviours (e.g., shortest paths), we propose an extended betweenness centrality to investigate the traffic flow in two scenarios 1) the interior roads of Danwei and Xiaoqu are excluded from urban road network, 2) the interior roads are integrated into road network. A Danwei and a Xiaoqu in Shanghai are used as the study area. The preliminary results show the feasibility of our extended betweenness centrality in investigating the traffic flow patterns and reveal the quantitative changes of the traffic flow after opening interior roads.
The Complex Nature of Family Support across the Life Span: Implications for Psychological Well-Being

ERIC Educational Resources Information Center

Fuller-Iglesias, Heather R.; Webster, Noah J.; Antonucci, Toni C.

2015-01-01

This study examines the complex role of family networks in shaping adult psychological well-being over time. We examine the unique and interactive longitudinal influences of family structure (i.e., composition and size) and negative family relationship quality on psychological well-being among young (ages 18-34), middle-aged (ages 35-49), and…
CaseLog: semantic network interface to a student computer-based patient record system.

PubMed Central

Cimino, C.; Goldman, E. K.; Curtis, J. A.; Reichgott, M. J.

1993-01-01

We have developed a computer program called CaseLog, which serves as an exemplary, computer-based patient record (CPR) system. The program allows for the introduction of the students to issues unique to patient record systems. These include record security, unique patient identifiers, and the use of controlled vocabularies. A particularly challenging aspect of the development of this program was allowing for student entry of controlled vocabulary terms. There were four goals we wished to achieve: students should be able to find the terms they are looking for; once a term has been found, it should be easy to find contextually related terms; it should be easy to determine that a sought-for term is not in the vocabulary; and the structure of the vocabulary should be dynamically altered by contextual information to allow its use for a variety of purposes. We chose a semantic network for our vocabulary structure. Within the processing power of the equipment we were working with, we achieved our goals. This paper will describe the development of the vocabulary, the design of the CaseLog program, and the feedback from student users of the program. PMID:8130581
Modeling cascading failures with the crisis of trust in social networks

NASA Astrophysics Data System (ADS)

Yi, Chengqi; Bao, Yuanyuan; Jiang, Jingchi; Xue, Yibo

2015-10-01

In social networks, some friends often post or disseminate malicious information, such as advertising messages, informal overseas purchasing messages, illegal messages, or rumors. Too much malicious information may cause a feeling of intense annoyance. When the feeling exceeds a certain threshold, it will lead social network users to distrust these friends, which we call the crisis of trust. The crisis of trust in social networks has already become a universal concern and an urgent unsolved problem. As a result of the crisis of trust, users will cut off their relationships with some of their untrustworthy friends. Once a few of these relationships are made unavailable, it is likely that other friends will decline trust, and a large portion of the social network will be influenced. The phenomenon in which the unavailability of a few relationships will trigger the failure of successive relationships is known as cascading failure dynamics. To our best knowledge, no one has formally proposed cascading failures dynamics with the crisis of trust in social networks. In this paper, we address this potential issue, quantify the trust between two users based on user similarity, and model the minimum tolerance with a nonlinear equation. Furthermore, we construct the processes of cascading failures dynamics by considering the unique features of social networks. Based on real social network datasets (Sina Weibo, Facebook and Twitter), we adopt two attack strategies (the highest trust attack (HT) and the lowest trust attack (LT)) to evaluate the proposed dynamics and to further analyze the changes of the topology, connectivity, cascading time and cascade effect under the above attacks. We numerically find that the sparse and inhomogeneous network structure in our cascading model can better improve the robustness of social networks than the dense and homogeneous structure. However, the network structure that seems like ripples is more vulnerable than the other two network structures. Our findings will be useful in further guiding the construction of social networks to effectively avoid the cascading propagation with the crisis of trust. Some research results can help social network service providers to avoid severe cascading failures.
Persistent homology analysis of ion aggregations and hydrogen-bonding networks.

PubMed

Xia, Kelin

2018-05-16

Despite the great advancement of experimental tools and theoretical models, a quantitative characterization of the microscopic structures of ion aggregates and their associated water hydrogen-bonding networks still remains a challenging problem. In this paper, a newly-invented mathematical method called persistent homology is introduced, for the first time, to quantitatively analyze the intrinsic topological properties of ion aggregation systems and hydrogen-bonding networks. The two most distinguishable properties of persistent homology analysis of assembly systems are as follows. First, it does not require a predefined bond length to construct the ion or hydrogen-bonding network. Persistent homology results are determined by the morphological structure of the data only. Second, it can directly measure the size of circles or holes in ion aggregates and hydrogen-bonding networks. To validate our model, we consider two well-studied systems, i.e., NaCl and KSCN solutions, generated from molecular dynamics simulations. They are believed to represent two morphological types of aggregation, i.e., local clusters and extended ion networks. It has been found that the two aggregation types have distinguishable topological features and can be characterized by our topological model very well. Further, we construct two types of networks, i.e., O-networks and H2O-networks, for analyzing the topological properties of hydrogen-bonding networks. It is found that for both models, KSCN systems demonstrate much more dramatic variations in their local circle structures with a concentration increase. A consistent increase of large-sized local circle structures is observed and the sizes of these circles become more and more diverse. In contrast, NaCl systems show no obvious increase of large-sized circles. Instead a consistent decline of the average size of the circle structures is observed and the sizes of these circles become more and more uniform with a concentration increase. As far as we know, these unique intrinsic topological features in ion aggregation systems have never been pointed out before. More importantly, our models can be directly used to quantitatively analyze the intrinsic topological invariants, including circles, loops, holes, and cavities, of any network-like structures, such as nanomaterials, colloidal systems, biomolecular assemblies, among others. These topological invariants cannot be described by traditional graph and network models.

Distinct population structure for co-occurring Anopheles goeldii and Anopheles triannulatus in Amazonian Brazil

PubMed Central

McKeon, Sascha Naomi; Moreno, Marta; Sallum, Maria Anise; Povoa, Marinete Marins; Conn, Jan Evelyn

2013-01-01

To evaluate whether environmental heterogeneity contributes to the genetic heterogeneity in Anopheles triannulatus, larval habitat characteristics across the Brazilian states of Roraima and Pará and genetic sequences were examined. A comparison with Anopheles goeldii was utilised to determine whether high genetic diversity was unique to An. triannulatus. Student t test and analysis of variance found no differences in habitat characteristics between the species. Analysis of population structure of An. triannulatus and An. goeldii revealed distinct demographic histories in a largely overlapping geographic range. Cytochrome oxidase I sequence parsimony networks found geographic clustering for both species; however nuclear marker networks depicted An. triannulatus with a more complex history of fragmentation, secondary contact and recent divergence. Evidence of Pleistocene expansions suggests both species are more likely to be genetically structured by geographic and ecological barriers than demography. We hypothesise that niche partitioning is a driving force for diversity, particularly in An. triannulatus. PMID:23903977
DNA-nanoparticle assemblies go organic: Macroscopic polymeric materials with nanosized features

PubMed Central

2012-01-01

Background One of the goals in the field of structural DNA nanotechnology is the use of DNA to build up 2- and 3-D nanostructures. The research in this field is motivated by the remarkable structural features of DNA as well as by its unique and reversible recognition properties. Nucleic acids can be used alone as the skeleton of a broad range of periodic nanopatterns and nanoobjects and in addition, DNA can serve as a linker or template to form DNA-hybrid structures with other materials. This approach can be used for the development of new detection strategies as well as nanoelectronic structures and devices. Method Here we present a new method for the generation of unprecedented all-organic conjugated-polymer nanoparticle networks guided by DNA, based on a hierarchical self-assembly process. First, microphase separation of amphiphilic block copolymers induced the formation of spherical nanoobjects. As a second ordering concept, DNA base pairing has been employed for the controlled spatial definition of the conjugated-polymer particles within the bulk material. These networks offer the flexibility and the diversity of soft polymeric materials. Thus, simple chemical methodologies could be applied in order to tune the network's electrical, optical and mechanical properties. Results and conclusions One- two- and three-dimensional networks have been successfully formed. Common to all morphologies is the integrity of the micelles consisting of DNA block copolymer (DBC), which creates an all-organic engineered network. PMID:22646980
Comparison of Point Matching Techniques for Road Network Matching

NASA Astrophysics Data System (ADS)

Hackeloeer, A.; Klasing, K.; Krisp, J. M.; Meng, L.

2013-05-01

Map conflation investigates the unique identification of geographical entities across different maps depicting the same geographic region. It involves a matching process which aims to find commonalities between geographic features. A specific subdomain of conflation called Road Network Matching establishes correspondences between road networks of different maps on multiple layers of abstraction, ranging from elementary point locations to high-level structures such as road segments or even subgraphs derived from the induced graph of a road network. The process of identifying points located on different maps by means of geometrical, topological and semantical information is called point matching. This paper provides an overview of various techniques for point matching, which is a fundamental requirement for subsequent matching steps focusing on complex high-level entities in geospatial networks. Common point matching approaches as well as certain combinations of these are described, classified and evaluated. Furthermore, a novel similarity metric called the Exact Angular Index is introduced, which considers both topological and geometrical aspects. The results offer a basis for further research on a bottom-up matching process for complex map features, which must rely upon findings derived from suitable point matching algorithms. In the context of Road Network Matching, reliable point matches provide an immediate starting point for finding matches between line segments describing the geometry and topology of road networks, which may in turn be used for performing a structural high-level matching on the network level.
Development of a computational model on the neural activity patterns of a visual working memory in a hierarchical feedforward Network

NASA Astrophysics Data System (ADS)

An, Soyoung; Choi, Woochul; Paik, Se-Bum

2015-11-01

Understanding the mechanism of information processing in the human brain remains a unique challenge because the nonlinear interactions between the neurons in the network are extremely complex and because controlling every relevant parameter during an experiment is difficult. Therefore, a simulation using simplified computational models may be an effective approach. In the present study, we developed a general model of neural networks that can simulate nonlinear activity patterns in the hierarchical structure of a neural network system. To test our model, we first examined whether our simulation could match the previously-observed nonlinear features of neural activity patterns. Next, we performed a psychophysics experiment for a simple visual working memory task to evaluate whether the model could predict the performance of human subjects. Our studies show that the model is capable of reproducing the relationship between memory load and performance and may contribute, in part, to our understanding of how the structure of neural circuits can determine the nonlinear neural activity patterns in the human brain.
Multifunctional Nanostructured Conductive Polymer Gels: Synthesis, Properties, and Applications

DOE PAGES

Zhao, Fei; Shi, Ye; Pan, Lijia; ...

2017-06-26

Conductive polymers have attracted significant interest over the past few decades because they synergize the advantageous features of conventional polymeric materials and organic conductors. With rationally designed nanostructures, conductive polymers can further exhibit exceptional mechanical, electrical, and optical properties because of their confined dimensions at the nanoscale level. Among various nanostructured conductive polymers, conductive polymer gels (CPGs) with synthetically tunable hierarchical 3D network structures show great potential for a wide range of applications, such as bioelectronics, and energy storage/conversion devices owing to their structural features. CPGs retain the properties of nanosized conductive polymers during the assembly of the nanobuilding blocksmore » into a monolithic macroscopic structure while generating structure-derived features from the highly cross-linked network. In this Account, we review our recent progress on the synthesis, properties, and novel applications of dopant cross-linked CPGs. We first describe the synthetic strategies, in which molecules with multiple functional groups are adopted as cross-linkers to cross-link conductive polymer chains into a 3D molecular network. These cross-linking molecules also act as dopants to improve the electrical conductivity of the gel network. The microstructure and physical/chemical properties of CPGs can be tuned by controlling the synthetic conditions such as species of monomers and cross-linkers, reaction temperature, and solvents. By incorporating other functional polymers or particles into the CPG matrix, hybrid gels have been synthesized with tailored structures. These hybrid gel materials retain the functionalities from each component, as well as enable synergic effects to improve mechanical and electrical properties of CPGs. We then introduce the unique structure-derived properties of the CPGs. The network facilitates both electronic and ionic transport owing to the continuous pathways for electrons and hierarchical pores for ion diffusion. CPGs also provide high surface area and solvent compatibility, similar to natural gels. With these improved properties, CPGs have been explored to enable novel conceptual devices in diverse applications from smart electronics and ultrasensitive biosensors, to energy storage and conversion devices. CPGs have also been adopted for developing hybrid materials with multifunctionalities, such as stimuli responsiveness, self-healing properties, and super-repellency to liquid. With synthetically tunable physical/chemical properties, CPGs emerge as a unique material platform to develop novel multifunctional materials that have the potential to impact electronics, energy, and environmental technologies. Our hope is that this Account promotes further efforts toward synthetic control, fundamental investigation, and application exploration of CPGs.« less
Multifunctional Nanostructured Conductive Polymer Gels: Synthesis, Properties, and Applications

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

Zhao, Fei; Shi, Ye; Pan, Lijia

Conductive polymers have attracted significant interest over the past few decades because they synergize the advantageous features of conventional polymeric materials and organic conductors. With rationally designed nanostructures, conductive polymers can further exhibit exceptional mechanical, electrical, and optical properties because of their confined dimensions at the nanoscale level. Among various nanostructured conductive polymers, conductive polymer gels (CPGs) with synthetically tunable hierarchical 3D network structures show great potential for a wide range of applications, such as bioelectronics, and energy storage/conversion devices owing to their structural features. CPGs retain the properties of nanosized conductive polymers during the assembly of the nanobuilding blocksmore » into a monolithic macroscopic structure while generating structure-derived features from the highly cross-linked network. In this Account, we review our recent progress on the synthesis, properties, and novel applications of dopant cross-linked CPGs. We first describe the synthetic strategies, in which molecules with multiple functional groups are adopted as cross-linkers to cross-link conductive polymer chains into a 3D molecular network. These cross-linking molecules also act as dopants to improve the electrical conductivity of the gel network. The microstructure and physical/chemical properties of CPGs can be tuned by controlling the synthetic conditions such as species of monomers and cross-linkers, reaction temperature, and solvents. By incorporating other functional polymers or particles into the CPG matrix, hybrid gels have been synthesized with tailored structures. These hybrid gel materials retain the functionalities from each component, as well as enable synergic effects to improve mechanical and electrical properties of CPGs. We then introduce the unique structure-derived properties of the CPGs. The network facilitates both electronic and ionic transport owing to the continuous pathways for electrons and hierarchical pores for ion diffusion. CPGs also provide high surface area and solvent compatibility, similar to natural gels. With these improved properties, CPGs have been explored to enable novel conceptual devices in diverse applications from smart electronics and ultrasensitive biosensors, to energy storage and conversion devices. CPGs have also been adopted for developing hybrid materials with multifunctionalities, such as stimuli responsiveness, self-healing properties, and super-repellency to liquid. With synthetically tunable physical/chemical properties, CPGs emerge as a unique material platform to develop novel multifunctional materials that have the potential to impact electronics, energy, and environmental technologies. Our hope is that this Account promotes further efforts toward synthetic control, fundamental investigation, and application exploration of CPGs.« less
Multifunctional Nanostructured Conductive Polymer Gels: Synthesis, Properties, and Applications.

PubMed

Zhao, Fei; Shi, Ye; Pan, Lijia; Yu, Guihua

2017-07-18

Conductive polymers have attracted significant interest over the past few decades because they synergize the advantageous features of conventional polymeric materials and organic conductors. With rationally designed nanostructures, conductive polymers can further exhibit exceptional mechanical, electrical, and optical properties because of their confined dimensions at the nanoscale level. Among various nanostructured conductive polymers, conductive polymer gels (CPGs) with synthetically tunable hierarchical 3D network structures show great potential for a wide range of applications, such as bioelectronics, and energy storage/conversion devices owing to their structural features. CPGs retain the properties of nanosized conductive polymers during the assembly of the nanobuilding blocks into a monolithic macroscopic structure while generating structure-derived features from the highly cross-linked network. In this Account, we review our recent progress on the synthesis, properties, and novel applications of dopant cross-linked CPGs. We first describe the synthetic strategies, in which molecules with multiple functional groups are adopted as cross-linkers to cross-link conductive polymer chains into a 3D molecular network. These cross-linking molecules also act as dopants to improve the electrical conductivity of the gel network. The microstructure and physical/chemical properties of CPGs can be tuned by controlling the synthetic conditions such as species of monomers and cross-linkers, reaction temperature, and solvents. By incorporating other functional polymers or particles into the CPG matrix, hybrid gels have been synthesized with tailored structures. These hybrid gel materials retain the functionalities from each component, as well as enable synergic effects to improve mechanical and electrical properties of CPGs. We then introduce the unique structure-derived properties of the CPGs. The network facilitates both electronic and ionic transport owing to the continuous pathways for electrons and hierarchical pores for ion diffusion. CPGs also provide high surface area and solvent compatibility, similar to natural gels. With these improved properties, CPGs have been explored to enable novel conceptual devices in diverse applications from smart electronics and ultrasensitive biosensors, to energy storage and conversion devices. CPGs have also been adopted for developing hybrid materials with multifunctionalities, such as stimuli responsiveness, self-healing properties, and super-repellency to liquid. With synthetically tunable physical/chemical properties, CPGs emerge as a unique material platform to develop novel multifunctional materials that have the potential to impact electronics, energy, and environmental technologies. We hope that this Account promotes further efforts toward synthetic control, fundamental investigation, and application exploration of CPGs.
Diffusion tractography and graph theory analysis reveal the disrupted rich-club organization of white matter structural networks in early Tourette Syndrome children

NASA Astrophysics Data System (ADS)

Wen, Hongwei; Liu, Yue; Wang, Shengpei; Zhang, Jishui; Peng, Yun; He, Huiguang

2017-03-01

Tourette syndrome (TS) is a childhood-onset neurobehavioral disorder. At present, the topological disruptions of the whole brain white matter (WM) structural networks remain poorly understood in TS children. Considering the unique position of the topologically central role of densely interconnected brain hubs, namely the rich club regions, therefore, we aimed to investigate whether the rich club regions and their related connections would be particularly vulnerable in early TS children. In our study, we used diffusion tractography and graph theoretical analyses to explore the rich club structures in 44 TS children and 48 healthy children. The structural networks of TS children exhibited significantly increased normalized rich club coefficient, suggesting that TS is characterized by increased structural integrity of this centrally embedded rich club backbone, potentially resulting in increased global communication capacity. In addition, TS children showed a reorganization of rich club regions, as well as significantly increased density and decreased number in feeder connections. Furthermore, the increased rich club coefficients and feeder connections density of TS children were significantly positively correlated to tic severity, indicating that TS may be characterized by a selective alteration of the structural connectivity of the rich club regions, tending to have higher bridging with non-rich club regions, which may increase the integration among tic-related brain circuits with more excitability but less inhibition for information exchanges between highly centered brain regions and peripheral areas. In all, our results suggest the disrupted rich club organization in early TS children and provide structural insights into the brain networks.
Crystal Structure Prediction via Deep Learning.

PubMed

Ryan, Kevin; Lengyel, Jeff; Shatruk, Michael

2018-06-06

We demonstrate the application of deep neural networks as a machine-learning tool for the analysis of a large collection of crystallographic data contained in the crystal structure repositories. Using input data in the form of multi-perspective atomic fingerprints, which describe coordination topology around unique crystallographic sites, we show that the neural-network model can be trained to effectively distinguish chemical elements based on the topology of their crystallographic environment. The model also identifies structurally similar atomic sites in the entire dataset of ~50000 crystal structures, essentially uncovering trends that reflect the periodic table of elements. The trained model was used to analyze templates derived from the known binary and ternary crystal structures in order to predict the likelihood to form new compounds that could be generated by placing elements into these structural templates in combinatorial fashion. Statistical analysis of predictive performance of the neural-network model, which was applied to a test set of structures never seen by the model during training, indicates its ability to predict known elemental compositions with a high likelihood of success. In ~30% of cases, the known compositions were found among top-10 most likely candidates proposed by the model. These results suggest that the approach developed in this work can be used to effectively guide the synthetic efforts in the discovery of new materials, especially in the case of systems composed of 3 or more chemical elements.
Three key residues form a critical contact network in a protein folding transition state

NASA Astrophysics Data System (ADS)

Vendruscolo, Michele; Paci, Emanuele; Dobson, Christopher M.; Karplus, Martin

2001-02-01

Determining how a protein folds is a central problem in structural biology. The rate of folding of many proteins is determined by the transition state, so that a knowledge of its structure is essential for understanding the protein folding reaction. Here we use mutation measurements-which determine the role of individual residues in stabilizing the transition state-as restraints in a Monte Carlo sampling procedure to determine the ensemble of structures that make up the transition state. We apply this approach to the experimental data for the 98-residue protein acylphosphatase, and obtain a transition-state ensemble with the native-state topology and an average root-mean-square deviation of 6Å from the native structure. Although about 20 residues with small positional fluctuations form the structural core of this transition state, the native-like contact network of only three of these residues is sufficient to determine the overall fold of the protein. This result reveals how a nucleation mechanism involving a small number of key residues can lead to folding of a polypeptide chain to its unique native-state structure.
Ads' click-through rates predicting based on gated recurrent unit neural networks

NASA Astrophysics Data System (ADS)

Chen, Qiaohong; Guo, Zixuan; Dong, Wen; Jin, Lingzi

2018-05-01

In order to improve the effect of online advertising and to increase the revenue of advertising, the gated recurrent unit neural networks(GRU) model is used as the ads' click through rates(CTR) predicting. Combined with the characteristics of gated unit structure and the unique of time sequence in data, using BPTT algorithm to train the model. Furthermore, by optimizing the step length algorithm of the gated unit recurrent neural networks, making the model reach optimal point better and faster in less iterative rounds. The experiment results show that the model based on the gated recurrent unit neural networks and its optimization of step length algorithm has the better effect on the ads' CTR predicting, which helps advertisers, media and audience achieve a win-win and mutually beneficial situation in Three-Side Game.
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.
A random spatial network model based on elementary postulates

USGS Publications Warehouse

Karlinger, Michael R.; Troutman, Brent M.

1989-01-01

A model for generating random spatial networks that is based on elementary postulates comparable to those of the random topology model is proposed. In contrast to the random topology model, this model ascribes a unique spatial specification to generated drainage networks, a distinguishing property of some network growth models. The simplicity of the postulates creates an opportunity for potential analytic investigations of the probabilistic structure of the drainage networks, while the spatial specification enables analyses of spatially dependent network properties. In the random topology model all drainage networks, conditioned on magnitude (number of first-order streams), are equally likely, whereas in this model all spanning trees of a grid, conditioned on area and drainage density, are equally likely. As a result, link lengths in the generated networks are not independent, as usually assumed in the random topology model. For a preliminary model evaluation, scale-dependent network characteristics, such as geometric diameter and link length properties, and topologic characteristics, such as bifurcation ratio, are computed for sets of drainage networks generated on square and rectangular grids. Statistics of the bifurcation and length ratios fall within the range of values reported for natural drainage networks, but geometric diameters tend to be relatively longer than those for natural networks.
Flexible, High-Wettability and Fire-Resistant Separators Based on Hydroxyapatite Nanowires for Advanced Lithium-Ion Batteries.

PubMed

Li, Heng; Wu, Dabei; Wu, Jin; Dong, Li-Ying; Zhu, Ying-Jie; Hu, Xianluo

2017-11-01

Separators play a pivotal role in the electrochemical performance and safety of lithium-ion batteries (LIBs). The commercial microporous polyolefin-based separators often suffer from inferior electrolyte wettability, low thermal stability, and severe safety concerns. Herein, a novel kind of highly flexible and porous separator based on hydroxyapatite nanowires (HAP NWs) with excellent thermal stability, fire resistance, and superior electrolyte wettability is reported. A hierarchical cross-linked network structure forms between HAP NWs and cellulose fibers (CFs) via hybridization, which endows the separator with high flexibility and robust mechanical strength. The high thermal stability of HAP NW networks enables the separator to preserve its structural integrity at temperatures as high as 700 °C, and the fire-resistant property of HAP NWs ensures high safety of the battery. In particular, benefiting from its unique composition and highly porous structure, the as-prepared HAP/CF separator exhibits near zero contact angle with the liquid electrolyte and high electrolyte uptake of 253%, indicating superior electrolyte wettability compared with the commercial polyolefin separator. The as-prepared HAP/CF separator has unique advantages of superior electrolyte wettability, mechanical robustness, high thermal stability, and fire resistance, thus, is promising as a new kind of separator for advanced LIBs with enhanced performance and high safety. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
New Constraints on Upper Mantle Structure Underlying the Diamondiferous Central Slave Craton, Canada, from Teleseismic Body Wave Tomography

NASA Astrophysics Data System (ADS)

Esteve, C.; Schaeffer, A. J.; Audet, P.

2017-12-01

Over the past number of decades, the Slave Craton (Canada) has been extensively studied for its diamondiferous kimberlites. Not only are diamonds a valuable resource, but their kimberlitic host rocks provide an otherwise unique direct source of information on the deep upper mantle (and potentially transition zone). Many of the Canadian Diamond mines are located within the Slave Craton. As a result of the propensity for diamondiferous kimberlites, it is imperative to probe the deep mantle structure beneath the Slave Craton. This work is further motivated by the increase in high-quality broadband seismic data across the Northern Canadian Cordillera over the past decade. To this end we have generated a P and S body wave tomography model of the Slave Craton and its surroundings. Furthermore, tomographic inversion techniques are growing ever more capable of producing high resolution Earth models which capture detailed structure and dynamics across a range of scale lengths. Here, we present preliminary results on the structure of the upper mantle underlying the Slave Craton. These results are generated using data from eight different seismic networks such as the Canadian National Seismic Network (CNSN), Yukon Northwest Seismic Network (YNSN), older Portable Observatories for Lithospheric Analysis and Reseach Investigating Seismicity (POLARIS), Regional Alberta Observatory for Earthquake Studies Network (RV), USArray Transportable Array (TA), older Canadian Northwest Experiment (CANOE), Batholith Broadband (XY) and the Yukon Observatory (YO). This regional model brings new insights about the upper mantle structure beneath the Slave Craton, Canada.
Contributions of identifiable neurons and neuron classes to lamprey vertebrate neurobiology.

PubMed

Buchanan, J T

2001-03-01

Among the advantages offered by the lamprey brainstem and spinal cord for studies of the structure and function of the nervous system is the unique identifiability of several pairs of reticulospinal neurons in the brainstem. These neurons have been exploited in investigations of the patterns of sensory input to these cells and the patterns of their outputs to spinal neurons, but no doubt these cells could be used much more effectively in exploring their roles in descending control of the spinal cord. The variability of cell positions of neurons in the spinal cord has precluded the recognition of unique spinal neurons. However, classes of nerve cells can be readily defined and characterized within the lamprey spinal cord and this has led to progress in understanding the cellular and synaptic mechanisms of locomotor activity. In addition, both the identifiable reticulospinal cells and the various spinal nerve cell classes and their known synaptic interactions have been used to demonstrate the degree and specificity of regeneration within the lamprey nervous system. The lack of uniquely identifiable cells within the lamprey spinal cord has hampered progress in these areas, especially in gaining a full understanding of the locomotor network and how neuromodulation of the network is accomplished.
Complex networks as a unified framework for descriptive analysis and predictive modeling in climate

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

Steinhaeuser, Karsten J K; Chawla, Nitesh; Ganguly, Auroop R

The analysis of climate data has relied heavily on hypothesis-driven statistical methods, while projections of future climate are based primarily on physics-based computational models. However, in recent years a wealth of new datasets has become available. Therefore, we take a more data-centric approach and propose a unified framework for studying climate, with an aim towards characterizing observed phenomena as well as discovering new knowledge in the climate domain. Specifically, we posit that complex networks are well-suited for both descriptive analysis and predictive modeling tasks. We show that the structural properties of climate networks have useful interpretation within the domain. Further,more » we extract clusters from these networks and demonstrate their predictive power as climate indices. Our experimental results establish that the network clusters are statistically significantly better predictors than clusters derived using a more traditional clustering approach. Using complex networks as data representation thus enables the unique opportunity for descriptive and predictive modeling to inform each other.« less
Neural network for nonsmooth pseudoconvex optimization with general convex constraints.

PubMed

Bian, Wei; Ma, Litao; Qin, Sitian; Xue, Xiaoping

2018-05-01

In this paper, a one-layer recurrent neural network is proposed for solving a class of nonsmooth, pseudoconvex optimization problems with general convex constraints. Based on the smoothing method, we construct a new regularization function, which does not depend on any information of the feasible region. Thanks to the special structure of the regularization function, we prove the global existence, uniqueness and "slow solution" character of the state of the proposed neural network. Moreover, the state solution of the proposed network is proved to be convergent to the feasible region in finite time and to the optimal solution set of the related optimization problem subsequently. In particular, the convergence of the state to an exact optimal solution is also considered in this paper. Numerical examples with simulation results are given to show the efficiency and good characteristics of the proposed network. In addition, some preliminary theoretical analysis and application of the proposed network for a wider class of dynamic portfolio optimization are included. Copyright © 2018 Elsevier Ltd. All rights reserved.
Minimum spanning tree analysis of the human connectome

PubMed Central

Sommer, Iris E.; Bohlken, Marc M.; Tewarie, Prejaas; Draaisma, Laurijn; Zalesky, Andrew; Di Biase, Maria; Brown, Jesse A.; Douw, Linda; Otte, Willem M.; Mandl, René C.W.; Stam, Cornelis J.

2018-01-01

Abstract One of the challenges of brain network analysis is to directly compare network organization between subjects, irrespective of the number or strength of connections. In this study, we used minimum spanning tree (MST; a unique, acyclic subnetwork with a fixed number of connections) analysis to characterize the human brain network to create an empirical reference network. Such a reference network could be used as a null model of connections that form the backbone structure of the human brain. We analyzed the MST in three diffusion‐weighted imaging datasets of healthy adults. The MST of the group mean connectivity matrix was used as the empirical null‐model. The MST of individual subjects matched this reference MST for a mean 58%–88% of connections, depending on the analysis pipeline. Hub nodes in the MST matched with previously reported locations of hub regions, including the so‐called rich club nodes (a subset of high‐degree, highly interconnected nodes). Although most brain network studies have focused primarily on cortical connections, cortical–subcortical connections were consistently present in the MST across subjects. Brain network efficiency was higher when these connections were included in the analysis, suggesting that these tracts may be utilized as the major neural communication routes. Finally, we confirmed that MST characteristics index the effects of brain aging. We conclude that the MST provides an elegant and straightforward approach to analyze structural brain networks, and to test network topological features of individual subjects in comparison to empirical null models. PMID:29468769
Data collection framework for energy efficient privacy preservation in wireless sensor networks having many-to-many structures.

PubMed

Bahşi, Hayretdin; Levi, Albert

2010-01-01

Wireless sensor networks (WSNs) generally have a many-to-one structure so that event information flows from sensors to a unique sink. In recent WSN applications, many-to-many structures evolved due to the need for conveying collected event information to multiple sinks. Privacy preserved data collection models in the literature do not solve the problems of WSN applications in which network has multiple un-trusted sinks with different level of privacy requirements. This study proposes a data collection framework bases on k-anonymity for preventing record disclosure of collected event information in WSNs. Proposed method takes the anonymity requirements of multiple sinks into consideration by providing different levels of privacy for each destination sink. Attributes, which may identify an event owner, are generalized or encrypted in order to meet the different anonymity requirements of sinks at the same anonymized output. If the same output is formed, it can be multicasted to all sinks. The other trivial solution is to produce different anonymized outputs for each sink and send them to related sinks. Multicasting is an energy efficient data sending alternative for some sensor nodes. Since minimization of energy consumption is an important design criteria for WSNs, multicasting the same event information to multiple sinks reduces the energy consumption of overall network.

Hierarchicality of trade flow networks reveals complexity of products.

PubMed

Shi, Peiteng; Zhang, Jiang; Yang, Bo; Luo, Jingfei

2014-01-01

With globalization, countries are more connected than before by trading flows, which amounts to at least 36 trillion dollars today. Interestingly, around 30-60 percents of exports consist of intermediate products in global. Therefore, the trade flow network of particular product with high added values can be regarded as value chains. The problem is weather we can discriminate between these products from their unique flow network structure? This paper applies the flow analysis method developed in ecology to 638 trading flow networks of different products. We claim that the allometric scaling exponent η can be used to characterize the degree of hierarchicality of a flow network, i.e., whether the trading products flow on long hierarchical chains. Then, it is pointed out that the flow networks of products with higher added values and complexity like machinary, transport equipment etc. have larger exponents, meaning that their trade flow networks are more hierarchical. As a result, without the extra data like global input-output table, we can identify the product categories with higher complexity, and the relative importance of a country in the global value chain by the trading network solely.
Hierarchicality of Trade Flow Networks Reveals Complexity of Products

PubMed Central

Shi, Peiteng; Zhang, Jiang; Yang, Bo; Luo, Jingfei

2014-01-01

With globalization, countries are more connected than before by trading flows, which amounts to at least trillion dollars today. Interestingly, around percents of exports consist of intermediate products in global. Therefore, the trade flow network of particular product with high added values can be regarded as value chains. The problem is weather we can discriminate between these products from their unique flow network structure? This paper applies the flow analysis method developed in ecology to 638 trading flow networks of different products. We claim that the allometric scaling exponent can be used to characterize the degree of hierarchicality of a flow network, i.e., whether the trading products flow on long hierarchical chains. Then, it is pointed out that the flow networks of products with higher added values and complexity like machinary, transport equipment etc. have larger exponents, meaning that their trade flow networks are more hierarchical. As a result, without the extra data like global input-output table, we can identify the product categories with higher complexity, and the relative importance of a country in the global value chain by the trading network solely. PMID:24905753
Facile solid-state synthesis of Ni@C nanosheet-assembled hierarchical network for high-performance lithium storage

NASA Astrophysics Data System (ADS)

Gu, Jinghe; Li, Qiyun; Zeng, Pan; Meng, Yulin; Zhang, Xiukui; Wu, Ping; Zhou, Yiming

2017-08-01

Micro/nano-architectured transition-metal@C hybrids possess unique structural and compositional features toward lithium storage, and are thus expected to manifest ideal anodic performances in advanced lithium-ion batteries (LIBs). Herein, we propose a facile and scalable solid-state coordination and subsequent pyrolysis route for the formation of a novel type of micro/nano-architectured transition-metal@C hybrid (i.e., Ni@C nanosheet-assembled hierarchical network, Ni@C network). Moreover, this coordination-pyrolysis route has also been applied for the construction of bare carbon network using zinc salts instead of nickel salts as precursors. When applied as potential anodic materials in LIBs, the Ni@C network exhibits Ni-content-dependent electrochemical performances, and the partially-etched Ni@C network manifests markedly enhanced Li-storage performances in terms of specific capacities, cycle life, and rate capability than the pristine Ni@C network and carbon network. The proposed solid-state coordination and pyrolysis strategy would open up new opportunities for constructing micro/nano-architectured transition-metal@C hybrids as advanced anode materials for LIBs.
Development and Optimization of Viable Human Platforms through 3D Printing

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

Parker, Paul R.; Moya, Monica L.; Wheeler, Elizabeth K.

2015-08-21

3D printing technology offers a unique method for creating cell cultures in a manner far more conducive to accurate representation of human tissues and systems. Here we print cellular structures capable of forming vascular networks and exhibiting qualities of natural tissues and human systems. This allows for cheaper and readily available sources for further study of biological and pharmaceutical agents.
Sexual networks, surveillance, and geographical space during syphilis outbreaks in rural North Carolina.

PubMed

Doherty, Irene A; Serre, Marc L; Gesink, Dionne; Adimora, Adaora A; Muth, Stephen Q; Leone, Peter A; Miller, William C

2012-11-01

Sexually transmitted infections (STIs) spread along sexual networks whose structural characteristics promote transmission that routine surveillance may not capture. Cases who have partners from multiple localities may operate as spatial network bridges, thereby facilitating geographical dissemination. We investigated how surveillance, sexual networks, and spatial bridges relate to each other for syphilis outbreaks in rural counties of North Carolina. We selected from the state health department's surveillance database cases diagnosed with primary, secondary, or early latent syphilis during October 1998 to December 2002 and who resided in central and southeastern North Carolina, along with their sex partners and their social contacts irrespective of infection status. We applied matching algorithms to eliminate duplicate names and create a unique roster of partnerships from which networks were compiled and graphed. Network members were differentiated by disease status and county of residence. In the county most affected by the outbreak, densely connected networks indicative of STI outbreaks were consistent with increased incidence and a large case load. In other counties, the case loads were low with fluctuating incidence, but network structures suggested the presence of outbreaks. In a county with stable, low incidence and a high number of cases, the networks were sparse and dendritic, indicative of endemic spread. Outbreak counties exhibited densely connected networks within well-defined geographic boundaries and low connectivity between counties; spatial bridges did not seem to facilitate transmission. Simple visualization of sexual networks can provide key information to identify communities most in need of resources for outbreak investigation and disease control.
Assessing the challenges of multi-scope clinical research sites: an example from NIH HIV/AIDS clinical trials networks.

PubMed

Rosas, Scott R; Cope, Marie T; Villa, Christie; Motevalli, Mahnaz; Utech, Jill; Schouten, Jeffrey T

2014-04-01

Large-scale, multi-network clinical trials are seen as a means for efficient and effective utilization of resources with greater responsiveness to new discoveries. Formal structures instituted within the National Institutes of Health (NIH) HIV/AIDS Clinical Trials facilitate collaboration and coordination across networks and emphasize an integrated approach to HIV/AIDS vaccine, prevention and therapeutics clinical trials. This study examines the joint usage of clinical research sites as means of gaining efficiency, extending capacity, and adding scientific value to the networks. A semi-structured questionnaire covering eight clinical management domains was administered to 74 (62% of sites) clinical site coordinators at single- and multi-network sites to identify challenges and efficiencies related to clinical trials management activities and coordination with multi-network units. Overall, respondents at multi-network sites did not report more challenges than single-network sites, but did report unique challenges to overcome including in the areas of study prioritization, community engagement, staff education and training, and policies and procedures. The majority of multi-network sites reported that such affiliations do allow for the consolidation and cost-sharing of research functions. Suggestions for increasing the efficiency or performance of multi-network sites included streamlining standards and requirements, consolidating protocol activation methods, using a single cross-network coordinating centre, and creating common budget and payment mechanisms. The results of this assessment provide important information to consider in the design and management of multi-network configurations for the NIH HIV/AIDS Clinical Trials Networks, as well as others contemplating and promoting the concept of multi-network settings. © 2013 John Wiley & Sons Ltd.
A network approach to policy framing: A case study of the National Aboriginal and Torres Strait Islander Health Plan.

PubMed

Browne, Jennifer; de Leeuw, Evelyne; Gleeson, Deborah; Adams, Karen; Atkinson, Petah; Hayes, Rick

2017-01-01

Aboriginal health policy in Australia represents a unique policy subsystem comprising a diverse network of Aboriginal-specific and "mainstream" organisations, often with competing interests. This paper describes the network structure of organisations attempting to influence national Aboriginal health policy and examines how the different subgroups within the network approached the policy discourse. Public submissions made as part of a policy development process for the National Aboriginal and Torres Strait Islander Health Plan were analysed using a novel combination of network analysis and qualitative framing analysis. Other organisational actors in the network in each submission were identified, and relationships between them determined; these were used to generate a network map depicting the ties between actors. A qualitative framing analysis was undertaken, using inductive coding of the policy discourses in the submissions. The frames were overlaid with the network map to identify the relationship between the structure of the network and the way in which organisations framed Aboriginal health problems. Aboriginal organisations were central to the network and strongly connected with each other. The network consisted of several densely connected subgroups, whose central nodes were closely connected to one another. Each subgroup deployed a particular policy frame, with a frame of "system dysfunction" also adopted by all but one subgroup. Analysis of submissions revealed that many of the stakeholders in Aboriginal health policy actors are connected to one another. These connections help to drive the policy discourse. The combination of network and framing analysis illuminates competing interests within a network, and can assist advocacy organisations to identify which network members are most influential. Copyright © 2016 Elsevier Ltd. All rights reserved.
Hardwiring stem cell communication through tissue structure

PubMed Central

Xin, Tianchi; Greco, Valentina; Myung, Peggy

2016-01-01

Adult stem cells across diverse organs self-renew and differentiate to maintain tissue homeostasis. How stem cells receive input to preserve tissue structure and function largely relies on their communication with surrounding cellular and non-cellular elements. As such, how tissues are organized and patterned not only reflects organ function but also inherently hardwires networks of communication between stem cells and their environment to direct tissue homeostasis and injury repair. This review highlights how different methods of stem cell communication reflect the unique organization and function of diverse tissues. PMID:26967287
Atmospheric reaction systems as null-models to identify structural traces of evolution in metabolism.

PubMed

Holme, Petter; Huss, Mikael; Lee, Sang Hoon

2011-05-06

The metabolism is the motor behind the biological complexity of an organism. One problem of characterizing its large-scale structure is that it is hard to know what to compare it to. All chemical reaction systems are shaped by the same physics that gives molecules their stability and affinity to react. These fundamental factors cannot be captured by standard null-models based on randomization. The unique property of organismal metabolism is that it is controlled, to some extent, by an enzymatic machinery that is subject to evolution. In this paper, we explore the possibility that reaction systems of planetary atmospheres can serve as a null-model against which we can define metabolic structure and trace the influence of evolution. We find that the two types of data can be distinguished by their respective degree distributions. This is especially clear when looking at the degree distribution of the reaction network (of reaction connected to each other if they involve the same molecular species). For the Earth's atmospheric network and the human metabolic network, we look into more detail for an underlying explanation of this deviation. However, we cannot pinpoint a single cause of the difference, rather there are several concurrent factors. By examining quantities relating to the modular-functional organization of the metabolism, we confirm that metabolic networks have a more complex modular organization than the atmospheric networks, but not much more. We interpret the more variegated modular arrangement of metabolism as a trace of evolved functionality. On the other hand, it is quite remarkable how similar the structures of these two types of networks are, which emphasizes that the constraints from the chemical properties of the molecules has a larger influence in shaping the reaction system than does natural selection.
Polymorphism and metal-induced structural transformation in 5,5'-bis(4-pyridyl)(2,2'-bispyrimidine) adlayers on Au(111).

PubMed

Hötger, Diana; Carro, Pilar; Gutzler, Rico; Wurster, Benjamin; Chandrasekar, Rajadurai; Klyatskaya, Svetlana; Ruben, Mario; Salvarezza, Roberto C; Kern, Klaus; Grumelli, Doris

2018-05-31

Metal-organic coordination networks self-assembled on surfaces have emerged as functional low-dimensional architectures with potential applications ranging from the fabrication of functional nanodevices to electrocatalysis. Among them, bis-pyridyl-bispyrimidine (PBP) and Fe-PBP on noble metal surfaces appear as interesting systems in revealing the details of the molecular self-assembly and the effect of metal incorporation on the organic network arrangement. Herein, we report a combined STM, XPS, and DFT study revealing polymorphism in bis-pyridyl-bispyrimidine adsorbed adlayers on the reconstructed Au(111) surface. The polymorphic structures are converted by the addition of Fe adatoms into one unique Fe-PBP surface structure. DFT calculations show that while all PBP phases exhibit a similar thermodynamic stability, metal incorporation selects the PBP structure that maximizes the number of metal-N close contacts. Charge transfer from the Fe adatoms to the Au substrate and N-Fe interactions stabilize the Fe-PBP adlayer. The increased thermodynamic stability of the metal-stabilized structure leads to its sole expression on the surface.
Time development in the early history of social networks: link stabilization, group dynamics, and segregation.

PubMed

Bruun, Jesper; Bearden, Ian G

2014-01-01

Studies of the time development of empirical networks usually investigate late stages where lasting connections have already stabilized. Empirical data on early network history are rare but needed for a better understanding of how social network topology develops in real life. Studying students who are beginning their studies at a university with no or few prior connections to each other offers a unique opportunity to investigate the formation and early development of link patterns and community structure in social networks. During a nine week introductory physics course, first year physics students were asked to identify those with whom they communicated about problem solving in physics during the preceding week. We use these students' self reports to produce time dependent student interaction networks. We investigate these networks to elucidate possible effects of different student attributes in early network formation. Changes in the weekly number of links show that while roughly half of all links change from week to week, students also reestablish a growing number of links as they progress through their first weeks of study. Using the Infomap community detection algorithm, we show that the networks exhibit community structure, and we use non-network student attributes, such as gender and end-of-course grade to characterize communities during their formation. Specifically, we develop a segregation measure and show that students structure themselves according to gender and pre-organized sections (in which students engage in problem solving and laboratory work), but not according to end-of-coure grade. Alluvial diagrams of consecutive weeks' communities show that while student movement between groups are erratic in the beginning of their studies, they stabilize somewhat towards the end of the course. Taken together, the analyses imply that student interaction networks stabilize quickly and that students establish collaborations based on who is immediately available to them and on observable personal characteristics.
Temporal Information Partitioning Networks (TIPNets): A process network approach to infer ecohydrologic shifts

NASA Astrophysics Data System (ADS)

Goodwell, Allison E.; Kumar, Praveen

2017-07-01

In an ecohydrologic system, components of atmospheric, vegetation, and root-soil subsystems participate in forcing and feedback interactions at varying time scales and intensities. The structure of this network of complex interactions varies in terms of connectivity, strength, and time scale due to perturbations or changing conditions such as rainfall, drought, or land use. However, characterization of these interactions is difficult due to multivariate and weak dependencies in the presence of noise, nonlinearities, and limited data. We introduce a framework for Temporal Information Partitioning Networks (TIPNets), in which time-series variables are viewed as nodes, and lagged multivariate mutual information measures are links. These links are partitioned into synergistic, unique, and redundant information components, where synergy is information provided only jointly, unique information is only provided by a single source, and redundancy is overlapping information. We construct TIPNets from 1 min weather station data over several hour time windows. From a comparison of dry, wet, and rainy conditions, we find that information strengths increase when solar radiation and surface moisture are present, and surface moisture and wind variability are redundant and synergistic influences, respectively. Over a growing season, network trends reveal patterns that vary with vegetation and rainfall patterns. The framework presented here enables us to interpret process connectivity in a multivariate context, which can lead to better inference of behavioral shifts due to perturbations in ecohydrologic systems. This work contributes to more holistic characterizations of system behavior, and can benefit a wide variety of studies of complex systems.
Structural health monitoring to detect the presence, location and magnitude of structural damage in cadaveric porcine spines.

PubMed

Kawchuk, Gregory Neil; Decker, Colleen; Dolan, Ryan; Carey, Jason

2009-01-19

Structural health monitoring has been used successfully to identify defects in civil infrastructure and aerospace applications. Given that the majority of low back pain is thought to be mechanical in nature, our objective was to determine if structural health monitoring techniques could be employed successfully to identify the presence, location and magnitude of structural alterations within the spine. In six eviscerated cadaveric pigs, bone screws were drilled into the anterior bodies of L1-L5 and tri-axial accelerometers fixed to each spinous process. Vibration was then applied to the L3 spinous and frequency response functions obtained from each sensor axis before and after specific alterations of spinal structure. These alterations were produced at four unique locations and included (1) use of a cable tie to link anterior bone pins together and (2) progressive disc sectioning. Eighty percent of all data were used to train a neural network while the remaining data were used to test the network's ability to distinguish between structural states. The presence, location and magnitude of structural change within the spine was identified correctly in 5030/5040 possible neural network decisions. The diagnostic sensitivity and specificity of this technique ranged from 0.994 to 1.000. These results indicate that there is sufficient information embedded in frequency response data to identify the presence, location and magnitude of specific structural changes in the spine. If these techniques can be evolved for human use, structural health monitoring may provide a new approach toward understanding the underlying relations between spinal structure and function.
High capacity fiber optic sensor networks using hybrid multiplexing techniques and their applications

NASA Astrophysics Data System (ADS)

Sun, Qizhen; Li, Xiaolei; Zhang, Manliang; Liu, Qi; Liu, Hai; Liu, Deming

2013-12-01

Fiber optic sensor network is the development trend of fiber senor technologies and industries. In this paper, I will discuss recent research progress on high capacity fiber sensor networks with hybrid multiplexing techniques and their applications in the fields of security monitoring, environment monitoring, Smart eHome, etc. Firstly, I will present the architecture of hybrid multiplexing sensor passive optical network (HSPON), and the key technologies for integrated access and intelligent management of massive fiber sensor units. Two typical hybrid WDM/TDM fiber sensor networks for perimeter intrusion monitor and cultural relics security are introduced. Secondly, we propose the concept of "Microstructure－Optical X Domin Refecltor (M-OXDR)" for fiber sensor network expansion. By fabricating smart micro-structures with the ability of multidimensional encoded and low insertion loss along the fiber, the fiber sensor network of simple structure and huge capacity more than one thousand could be achieved. Assisted by the WDM/TDM and WDM/FDM decoding methods respectively, we built the verification systems for long-haul and real-time temperature sensing. Finally, I will show the high capacity and flexible fiber sensor network with IPv6 protocol based hybrid fiber/wireless access. By developing the fiber optic sensor with embedded IPv6 protocol conversion module and IPv6 router, huge amounts of fiber optic sensor nodes can be uniquely addressed. Meanwhile, various sensing information could be integrated and accessed to the Next Generation Internet.
Effective connectivity within the frontoparietal control network differentiates cognitive control and working memory.

PubMed

Harding, Ian H; Yücel, Murat; Harrison, Ben J; Pantelis, Christos; Breakspear, Michael

2015-02-01

Cognitive control and working memory rely upon a common fronto-parietal network that includes the inferior frontal junction (IFJ), dorsolateral prefrontal cortex (dlPFC), pre-supplementary motor area/dorsal anterior cingulate cortex (pSMA/dACC), and intraparietal sulcus (IPS). This network is able to flexibly adapt its function in response to changing behavioral goals, mediating a wide range of cognitive demands. Here we apply dynamic causal modeling to functional magnetic resonance imaging data to characterize task-related alterations in the strength of network interactions across distinct cognitive processes. Evidence in favor of task-related connectivity dynamics was accrued across a very large space of possible network structures. Cognitive control and working memory demands were manipulated using a factorial combination of the multi-source interference task and a verbal 2-back working memory task, respectively. Both were found to alter the sensitivity of the IFJ to perceptual information, and to increase IFJ-to-pSMA/dACC connectivity. In contrast, increased connectivity from the pSMA/dACC to the IPS, as well as from the dlPFC to the IFJ, was uniquely driven by cognitive control demands; a task-induced negative influence of the dlPFC on the pSMA/dACC was specific to working memory demands. These results reflect a system of both shared and unique context-dependent dynamics within the fronto-parietal network. Mechanisms supporting cognitive engagement, response selection, and action evaluation may be shared across cognitive domains, while dynamic updating of task and context representations within this network are potentially specific to changing demands on cognitive control. Copyright © 2014 Elsevier Inc. All rights reserved.
Image understanding systems based on the unifying representation of perceptual and conceptual information and the solution of mid-level and high-level vision problems

NASA Astrophysics Data System (ADS)

Kuvychko, Igor

2001-10-01

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

PubMed

Wang, Xiao-Min; Zhu, Jin-Qi; Liu, Ming; Gong, Hai-Gang

2010-01-01

Routing in delay tolerant mobile sensor networks (DTMSNs) is challenging due to the networks' intermittent connectivity. Most existing routing protocols for DTMSNs use simplistic random mobility models for algorithm design and performance evaluation. In the real world, however, due to the unique characteristics of human mobility, currently existing random mobility models may not work well in environments where mobile sensor units are carried (such as DTMSNs). Taking a person's social activities into consideration, in this paper, we seek to improve DTMSN routing in terms of social structure and propose an agenda based routing protocol (ARP). In ARP, humans are classified based on their agendas and data transmission is made according to sensor nodes' transmission rankings. The effectiveness of ARP is demonstrated through comprehensive simulation studies.
Optical data communication: fundamentals and future directions

NASA Astrophysics Data System (ADS)

DeCusatis, Casimer M.

1998-12-01

An overview of optical data communications is provided, beginning with a brief history and discussion of the unique requirements that distinguish this subfield from related areas such as telecommunications. Each of the major datacom standards is then discussed, including the physical layer specification, distances and data rates, fiber and connector types, data frame structures, and network considerations. These standards can be categorized by their prevailing applications, either storage [Enterprise System Connection, Fiber Channel Connection, and Fiber Channel], coupling (Fiber Channel), or networking [Fiber Distributed Data Interface, Gigabit Ethernet, and asynchronous transfer mode/synchronous optical network]. We also present some emerging technologies and their applications, including parallel optical interconnects, plastic optical fiber, wavelength multiplexing, and free- space optical links. We conclude with some cost/performance trade-offs and predictions of future bandwidth trends.
Elementary Mode Analysis: A Useful Metabolic Pathway Analysis Tool for Characterizing Cellular Metabolism

PubMed Central

Trinh, Cong T.; Wlaschin, Aaron; Srienc, Friedrich

2010-01-01

Elementary Mode Analysis is a useful Metabolic Pathway Analysis tool to identify the structure of a metabolic network that links the cellular phenotype to the corresponding genotype. The analysis can decompose the intricate metabolic network comprised of highly interconnected reactions into uniquely organized pathways. These pathways consisting of a minimal set of enzymes that can support steady state operation of cellular metabolism represent independent cellular physiological states. Such pathway definition provides a rigorous basis to systematically characterize cellular phenotypes, metabolic network regulation, robustness, and fragility that facilitate understanding of cell physiology and implementation of metabolic engineering strategies. This mini-review aims to overview the development and application of elementary mode analysis as a metabolic pathway analysis tool in studying cell physiology and as a basis of metabolic engineering. PMID:19015845
Mindfulness training induces structural connectome changes in insula networks.

PubMed

Sharp, Paul B; Sutton, Bradley P; Paul, Erick J; Sherepa, Nikolai; Hillman, Charles H; Cohen, Neal J; Kramer, Arthur F; Prakash, Ruchika Shaurya; Heller, Wendy; Telzer, Eva H; Barbey, Aron K

2018-05-21

Although mindfulness meditation is known to provide a wealth of psychological benefits, the neural mechanisms involved in these effects remain to be well characterized. A central question is whether the observed benefits of mindfulness training derive from specific changes in the structural brain connectome that do not result from alternative forms of experimental intervention. Measures of whole-brain and node-level structural connectome changes induced by mindfulness training were compared with those induced by cognitive and physical fitness training within a large, multi-group intervention protocol (n = 86). Whole-brain analyses examined global graph-theoretical changes in structural network topology. A hypothesis-driven approach was taken to investigate connectivity changes within the insula, which was predicted here to mediate interoceptive awareness skills that have been shown to improve through mindfulness training. No global changes were observed in whole-brain network topology. However, node-level results confirmed a priori hypotheses, demonstrating significant increases in mean connection strength in right insula across all of its connections. Present findings suggest that mindfulness strengthens interoception, operationalized here as the mean insula connection strength within the overall connectome. This finding further elucidates the neural mechanisms of mindfulness meditation and motivates new perspectives about the unique benefits of mindfulness training compared to contemporary cognitive and physical fitness interventions.

Ultrastructural networks in growth cones and neurites of cultured central nervous system neurons.

PubMed

Tsui, H C; Ris, H; Klein, W L

1983-09-01

We have examined growth cones and neurites of cultured central nervous system neurons by high-voltage electron microscopy. Embryonic chicken retina cells were cultured on polylysine-treated and Formvar-coated gold grids for 2-6 days, fixed, and critical point dried. Growth cones and neurites were examined as unembedded whole mounts. Three-dimensional images from stereo-pair electron micrographs of these regions showed a high degree of ultrastructural articulation, with distinct, non-tapering filaments (5-9 nm in diameter) joining both cytoskeletal and membranous components. In the central regions of growth cones, interconnected structures included microtubules, large membranous sacs (up to 400 nm), and irregular vesicles (25-75 nm). A denser filamentous network was prevalent at the edges of growth cones. This network, which frequently adjoined the surface membrane, linked vesicles of uniform size (35-40 nm). Such vesicles often were seen densely packed in growth cone protrusions that were about the size of small synaptic boutons. Prevalent structural interconnections within growth cones conceivably could play a logistic role in specific membrane assembly, intracellular transport, endocytosis, and secretion. Because such processes are not unique to growth cones, the extensive linkages we have observed may have implications for cytoplasmic structure in general.
Elastic properties, reaction kinetics, and structural relaxation of an epoxy resin polymer during cure

NASA Astrophysics Data System (ADS)

Heili, Manon; Bielawski, Andrew; Kieffer, John

The cure kinetics of a DGEBA/DETA epoxy is investigated using concurrent Raman and Brillouin light scattering. Raman scattering allows us to monitor the in-situ reaction and quantitatively assess the degree of cure. Brillouin scattering yields the elastic properties of the system, providing a measure of network connectivity. We show that the adiabatic modulus evolves non-uniquely as a function of cure degree, depending on the cure temperature and the molar ratio of the epoxy. Two mechanisms contribute to the increase in the elastic modulus of the material during curing. First, there is the formation of covalent bonds in the network during the curing process. Second, following bond formation, the epoxy undergoes structural relaxation toward an optimally packed network configuration, enhancing non-bonded interactions. We investigate to what extent the non-bonded interaction contribution to structural rigidity in cross-linked polymers is reversible, and to what extent it corresponds to the difference between adiabatic and isothermal moduli obtained from static tensile, i.e. the so-called relaxational modulus. To this end, we simultaneously measure the adiabatic and isothermal elastic moduli as a function of applied strain and deformation rate.
Axial and radial nanostructures in electrospun polymer fibers

NASA Astrophysics Data System (ADS)

Greenfeld, Israel; Camposeo, Andrea; Tantussi, Francesco; Pagliara, Stefano; Fuso, Francesco; Allegrini, Maria; Pisignano, Dario; Zussman, Eyal

2013-03-01

The high tensional stresses during electrospinning of semidilute polymer solutions affect the dynamic conformation of the polymer network within the liquid jet, leaving a distinctive trace in the molecular structure after solidification. We investigated such effects in electrospun nanofibers made of conjugated polymers. Modeling the polymer network evolution during electrospinning showed that as the network stretches axially, it contracts towards the jet core. The model represents the semi-flexible conjugated polymer chains as flexible freely-jointed chains, whose joints are bonding defects. Using the conjugated polymer MEH-PPV dissolved in a mixture of THF and DMF solvents, and taking advantage of its unique photophysical characteristics, we investigated optically the variations in the density and orientation of the polymer macromolecules in electrospun nanofibers. In agreement with our model, we found higher density and axial orientation at the fiber core, while lower density and radial orientation closer to the fiber surface. The non-uniformity of the resulting molecular structure can be tuned and exploited in diverse optical and structural applications. We acknowledge: V. Fasano, G. Potente, S. Girardo and E. Caldi for assistance in measurements; United States-Israel BSF, RBNI Institute, and the Israel Science Foundation for financial support.
Transient Binding and Viscous Dissipation in Semi-flexible Polymer Networks

NASA Astrophysics Data System (ADS)

Lieleg, Oliver; Claessens, Mireille; Bausch, Andreas

2008-03-01

Nature specifically chooses from a myriad of actin binding proteins (ABPs) to tailor the cytoskeletal microstructure. Herein, cells rely on the dynamics of the cytoskeleton as its structural and mechanical adaptability is crucial to allow for dynamic processes. A molecular understanding of such biological complexity calls for an in vitro system with well-defined structural rearrangements and cross-linker dynamics to elucidate the physical origin of the unique viscoelastic properties of cells. As we present here, the frequency-dependent viscoelastic response of cross-linked in vitro actin networks is determined by the binding kinetics of cross-linking molecules. Independent from the particular network structure, the viscous dissipation (loss modulus) exhibits a pronounced minimum in an intermediate frequency which is dominated by elasticity. We show that in this frequency regime the molecular origin of the viscoelastic response is given by the non-static nature of actin/ABP bonds as they are subjugated to chemical on/off kinetics. The time scale of the resulting stress release is set by the lifetime distribution of the cross-linking molecule and therefore can be tuned independently from other relaxation mechanisms. We speculate that unbinding of distinct cross-links might be the molecular mechanism employed by cells for mechanosensing.
Decoding Network Structure in On-Chip Integrated Flow Cells with Synchronization of Electrochemical Oscillators

NASA Astrophysics Data System (ADS)

Jia, Yanxin; Kiss, István Z.

2017-04-01

The analysis of network interactions among dynamical units and the impact of the coupling on self-organized structures is a challenging task with implications in many biological and engineered systems. We explore the coupling topology that arises through the potential drops in a flow channel in a lab-on-chip device that accommodates chemical reactions on electrode arrays. The networks are revealed by analysis of the synchronization patterns with the use of an oscillatory chemical reaction (nickel electrodissolution) and are further confirmed by direct decoding using phase model analysis. In dual electrode configuration, a variety coupling schemes, (uni- or bidirectional positive or negative) were identified depending on the relative placement of the reference and counter electrodes (e.g., placed at the same or the opposite ends of the flow channel). With three electrodes, the network consists of a superposition of a localized (upstream) and global (all-to-all) coupling. With six electrodes, the unique, position dependent coupling topology resulted spatially organized partial synchronization such that there was a synchrony gradient along the quasi-one-dimensional spatial coordinate. The networked, electrode potential (current) spike generating electrochemical reactions hold potential for construction of an in-situ information processing unit to be used in electrochemical devices in sensors and batteries.
New patterns in human biogeography revealed by networks of contacts between linguistic groups.

PubMed

Capitán, José A; Bock Axelsen, Jacob; Manrubia, Susanna

2015-03-07

Human languages differ broadly in abundance and are distributed highly unevenly on the Earth. In many qualitative and quantitative aspects, they strongly resemble biodiversity distributions. An intriguing and previously unexplored issue is the architecture of the neighbouring relationships between human linguistic groups. Here we construct and characterize these networks of contacts and show that they represent a new kind of spatial network with uncommon structural properties. Remarkably, language networks share a meaningful property with food webs: both are quasi-interval graphs. In food webs, intervality is linked to the existence of a niche space of low dimensionality; in language networks, we show that the unique relevant variable is the area occupied by the speakers of a language. By means of a range model analogous to niche models in ecology, we show that a geometric restriction of perimeter covering by neighbouring linguistic domains explains the structural patterns observed. Our findings may be of interest in the development of models for language dynamics or regarding the propagation of cultural innovations. In relation to species distribution, they pose the question of whether the spatial features of species ranges share architecture, and eventually generating mechanism, with the distribution of human linguistic groups. © 2015 The Author(s) Published by the Royal Society. All rights reserved.
Network analysis of corticocortical connections reveals ventral and dorsal processing streams in mouse visual cortex

PubMed Central

Wang, Quanxin; Sporns, Olaf; Burkhalter, Andreas

2012-01-01

Much of the information used for visual perception and visually guided actions is processed in complex networks of connections within the cortex. To understand how this works in the normal brain and to determine the impact of disease, mice are promising models. In primate visual cortex, information is processed in a dorsal stream specialized for visuospatial processing and guided action and a ventral stream for object recognition. Here, we traced the outputs of 10 visual areas and used quantitative graph analytic tools of modern network science to determine, from the projection strengths in 39 cortical targets, the community structure of the network. We found a high density of the cortical graph that exceeded that previously shown in monkey. Each source area showed a unique distribution of projection weights across its targets (i.e. connectivity profile) that was well-fit by a lognormal function. Importantly, the community structure was strongly dependent on the location of the source area: outputs from medial/anterior extrastriate areas were more strongly linked to parietal, motor and limbic cortex, whereas lateral extrastriate areas were preferentially connected to temporal and parahippocampal cortex. These two subnetworks resemble dorsal and ventral cortical streams in primates, demonstrating that the basic layout of cortical networks is conserved across species. PMID:22457489
[Buying and distribution of drugs: perceptions of officers of a network of primary health care in the interior of the state of Sao Paulo].

PubMed

Juliani, C M

1995-12-01

The study present analyse the process to buy and distribution of medicaments for the Basic Unit of Health in municipal district of state São Paulo. To achieve some general considerations about the National Politic of Medicaments in Brazil, to emphasize feature relative the its structuration in the Unique System of Health.
The ground truth about metadata and community detection in networks

PubMed Central

Peel, Leto; Larremore, Daniel B.; Clauset, Aaron

2017-01-01

Across many scientific domains, there is a common need to automatically extract a simplified view or coarse-graining of how a complex system’s components interact. This general task is called community detection in networks and is analogous to searching for clusters in independent vector data. It is common to evaluate the performance of community detection algorithms by their ability to find so-called ground truth communities. This works well in synthetic networks with planted communities because these networks’ links are formed explicitly based on those known communities. However, there are no planted communities in real-world networks. Instead, it is standard practice to treat some observed discrete-valued node attributes, or metadata, as ground truth. We show that metadata are not the same as ground truth and that treating them as such induces severe theoretical and practical problems. We prove that no algorithm can uniquely solve community detection, and we prove a general No Free Lunch theorem for community detection, which implies that there can be no algorithm that is optimal for all possible community detection tasks. However, community detection remains a powerful tool and node metadata still have value, so a careful exploration of their relationship with network structure can yield insights of genuine worth. We illustrate this point by introducing two statistical techniques that can quantify the relationship between metadata and community structure for a broad class of models. We demonstrate these techniques using both synthetic and real-world networks, and for multiple types of metadata and community structures. PMID:28508065
Sexual networks: measuring sexual selection in structured, polyandrous populations.

PubMed

McDonald, Grant C; James, Richard; Krause, Jens; Pizzari, Tommaso

2013-03-05

Sexual selection is traditionally measured at the population level, assuming that populations lack structure. However, increasing evidence undermines this approach, indicating that intrasexual competition in natural populations often displays complex patterns of spatial and temporal structure. This complexity is due in part to the degree and mechanisms of polyandry within a population, which can influence the intensity and scale of both pre- and post-copulatory sexual competition. Attempts to measure selection at the local and global scale have been made through multi-level selection approaches. However, definitions of local scale are often based on physical proximity, providing a rather coarse measure of local competition, particularly in polyandrous populations where the local scale of pre- and post-copulatory competition may differ drastically from each other. These limitations can be solved by social network analysis, which allows us to define a unique sexual environment for each member of a population: 'local scale' competition, therefore, becomes an emergent property of a sexual network. Here, we first propose a novel quantitative approach to measure pre- and post-copulatory sexual selection, which integrates multi-level selection with information on local scale competition derived as an emergent property of networks of sexual interactions. We then use simple simulations to illustrate the ways in which polyandry can impact estimates of sexual selection. We show that for intermediate levels of polyandry, the proposed network-based approach provides substantially more accurate measures of sexual selection than the more traditional population-level approach. We argue that the increasing availability of fine-grained behavioural datasets provides exciting new opportunities to develop network approaches to study sexual selection in complex societies.
Small-sized PdCu nanocapsules on 3D graphene for high-performance ethanol oxidation

NASA Astrophysics Data System (ADS)

HuThese Authors Contributed Equally To This Work., Chuangang; Zhai, Xiangquan; Zhao, Yang; Bian, Ke; Zhang, Jing; Qu, Liangti; Zhang, Huimin; Luo, Hongxia

2014-02-01

A one-pot solvothermal process has been developed for direct preparation of PdCu nanocapsules (with a size of ca. 10 nm) on three-dimensional (3D) graphene. Due to the 3D pore-rich network of graphene and the unique hollow structure of PdCu nanocapsules with a wall thickness of ca. 3 nm, the newly-prepared PdCu/3D graphene hybrids activated electrochemically have great electrocatalytic activity towards ethanol oxidation in alkaline media, much better than single-phase Pd and commercial E-TEK 20% Pt/C catalysts promising for application in direct ethanol fuel cells.A one-pot solvothermal process has been developed for direct preparation of PdCu nanocapsules (with a size of ca. 10 nm) on three-dimensional (3D) graphene. Due to the 3D pore-rich network of graphene and the unique hollow structure of PdCu nanocapsules with a wall thickness of ca. 3 nm, the newly-prepared PdCu/3D graphene hybrids activated electrochemically have great electrocatalytic activity towards ethanol oxidation in alkaline media, much better than single-phase Pd and commercial E-TEK 20% Pt/C catalysts promising for application in direct ethanol fuel cells. Electronic supplementary information (ESI) available. See DOI: 10.1039/c3nr05722d
Epithelial structure revealed by chemical dissection and unembedded electron microscopy.

PubMed

Fey, E G; Capco, D G; Krochmalnic, G; Penman, S

1984-07-01

Cytoskeletal structures obtained after extraction of Madin-Darby canine kidney epithelial cell monolayers with Triton X-100 were examined in transmission electron micrographs of cell whole mounts and unembedded thick sections. The cytoskeleton, an ordered structure consisting of a peripheral plasma lamina, a complex network of filaments, and chromatin-containing nuclei, was revealed after extraction of intact cells with a nearly physiological buffer containing Triton X-100. The cytoskeleton was further fractionated by extraction with (NH4)2SO4, which left a structure enriched in intermediate filaments and desmosomes around the nuclei. A further digestion with nuclease and elution with (NH4)2SO4 removed the chromatin. The stable structure that remained after this procedure retained much of the epithelial morphology and contained essentially all of the cytokeratin filaments and desmosomes and the chromatin-depleted nuclear matrices. This structural network may serve as a scaffold for epithelial organization. The cytoskeleton and the underlying nuclear matrix intermediate filament scaffold, when examined in both conventional embedded thin sections and in unembedded whole mounts and thick sections, showed the retention of many of the detailed morphological aspects of the intact cells, which suggests a structural continuum linking the nuclear matrix, the intermediate filament network, and the intercellular desmosomal junctions. Most importantly, the protein composition of each of the four fractions obtained by this sequential procedure was essentially unique. Thus, the proteins constituting the soluble fraction, the cytoskeleton, the chromatin fraction, and the underlying nuclear matrix-intermediate filament scaffold are biochemically distinct.
Epithelial structure revealed by chemical dissection and unembedded electron microscopy

PubMed Central

Fey, E. G.; Capco, D. G.; Krochmalnic, G.; Penman, S.

1984-01-01

Cytoskeletal structures obtained after extraction of Madin-Darby canine kidney epithelial cell monolayers with Triton X-100 were examined in transmission electron micrographs of cell whole mounts and unembedded thick sections. The cytoskeleton, an ordered structure consisting of a peripheral plasma lamina, a complex network of filaments, and chromatin-containing nuclei, was revealed after extraction of intact cells with a nearly physiological buffer containing Triton X-100. The cytoskeleton was further fractionated by extraction with (NH4)2SO4, which left a structure enriched in intermediate filaments and desmosomes around the nuclei. A further digestion with nuclease and elution with (NH4)2SO4 removed the chromatin. The stable structure that remained after this procedure retained much of the epithelial morphology and contained essentially all of the cytokeratin filaments and desmosomes and the chromatin-depleted nuclear matrices. This structural network may serve as a scaffold for epithelial organization. The cytoskeleton and the underlying nuclear matrix intermediate filament scaffold, when examined in both conventional embedded thin sections and in unembedded whole mounts and thick sections, showed the retention of many of the detailed morphological aspects of the intact cells, which suggests a structural continuum linking the nuclear matrix, the intermediate filament network, and the intercellular desmosomal junctions. Most importantly, the protein composition of each of the four fractions obtained by this sequential procedure was essentially unique. Thus, the proteins constituting the soluble fraction, the cytoskeleton, the chromatin fraction, and the underlying nuclear matrix-intermediate filament scaffold are biochemically distinct. PMID:6540264
Investigating Molecular Level Stress-Strain Relationships in Entangled F-Actin Networks by Combined Force-Measuring Optical Tweezers and Fluorescence Microscopy

NASA Astrophysics Data System (ADS)

Lee, Kent; Henze, Dean; Robertson-Anderson, Rae

2013-03-01

Actin is an important cytoskeletal protein involved in cell structure and motility, cancer invasion and metastasis, and muscle contraction. The intricate viscoelastic properties of filamentous actin (F-actin) networks allow for the many dynamic roles of actin, thus warranting investigation. Exploration of this unique stress-strain/strain-rate relationship in complex F-actin networks can also improve biomimetic materials engineering. Here, we use optical tweezers with fluorescence microscopy to study the viscoelastic properties of F-actin networks on the microscopic level. Optically trapped microspheres embedded in various F-actin networks are moved through the network using a nanoprecision piezoelectric stage. The force exerted on the microspheres by the F-actin network and subsequent force relaxation are measured, while a fraction of the filaments in the network are fluorescent-labeled to observe filament deformation in real-time. The dependence of the viscoelastic properties of the network on strain rates and amplitudes as well as F-actin concentration is quantified. This approach provides the much-needed link between induced force and deformation over localized regimes (tens of microns) and down to the single molecule level.
Structures including network and topology for identifying, locating and quantifying physical phenomena

DOEpatents

Richardson, John G.; Moore, Karen A.; Carrington, Robert A.

2006-04-25

A method and system for detecting, locating and quantifying a physical phenomena such as strain or a deformation in a structure. A plurality of laterally adjacent conductors may each include a plurality of segments. Each segment is constructed to exhibit a unit value representative of a defined energy transmission characteristic. A plurality of identity groups are defined with each identity group comprising a plurality of segments including at least one segment from each of the plurality of conductors. The segments contained within an identity group are configured and arranged such that each of their associated unit values may be represented by a concatenated digit string which is a unique number relative to the other identity groups. Additionally, the unit values of the segments within an identity group maintain unique ratios with respect to the other unit values in the identity group.
Loneliness in late-life depression: structural and functional connectivity during affective processing.

PubMed

Wong, N M L; Liu, H-L; Lin, C; Huang, C-M; Wai, Y-Y; Lee, S-H; Lee, T M C

2016-09-01

Late-life depression (LLD) in the elderly was reported to present with emotion dysregulation accompanied by high perceived loneliness. Previous research has suggested that LLD is a disorder of connectivity and is associated with aberrant network properties. On the other hand, perceived loneliness is found to adversely affect the brain, but little is known about its neurobiological basis in LLD. The current study investigated the relationships between the structural connectivity, functional connectivity during affective processing, and perceived loneliness in LLD. The current study included 54 participants aged >60 years of whom 31 were diagnosed with LLD. Diffusion tensor imaging (DTI) data and task-based functional magnetic resonance imaging (fMRI) data of an affective processing task were collected. Network-based statistics and graph theory techniques were applied, and the participants' perceived loneliness and depression level were measured. The affective processing task included viewing affective stimuli. Structurally, a loneliness-related sub-network was identified across all subjects. Functionally, perceived loneliness was related to connectivity differently in LLD than that in controls when they were processing negative stimuli, with aberrant networking in subcortical area. Perceived loneliness was identified to have a unique role in relation to the negative affective processing in LLD at the functional brain connectional and network levels. The findings increas our understanding of LLD and provide initial evidence of the neurobiological mechanisms of loneliness in LLD. Loneliness might be a potential intervention target in depressive patients.
Dimensionless, Scale Invariant, Edge Weight Metric for the Study of Complex Structural Networks

PubMed Central

Colon-Perez, Luis M.; Spindler, Caitlin; Goicochea, Shelby; Triplett, William; Parekh, Mansi; Montie, Eric; Carney, Paul R.; Price, Catherine; Mareci, Thomas H.

2015-01-01

High spatial and angular resolution diffusion weighted imaging (DWI) with network analysis provides a unique framework for the study of brain structure in vivo. DWI-derived brain connectivity patterns are best characterized with graph theory using an edge weight to quantify the strength of white matter connections between gray matter nodes. Here a dimensionless, scale-invariant edge weight is introduced to measure node connectivity. This edge weight metric provides reasonable and consistent values over any size scale (e.g. rodents to humans) used to quantify the strength of connection. Firstly, simulations were used to assess the effects of tractography seed point density and random errors in the estimated fiber orientations; with sufficient signal-to-noise ratio (SNR), edge weight estimates improve as the seed density increases. Secondly to evaluate the application of the edge weight in the human brain, ten repeated measures of DWI in the same healthy human subject were analyzed. Mean edge weight values within the cingulum and corpus callosum were consistent and showed low variability. Thirdly, using excised rat brains to study the effects of spatial resolution, the weight of edges connecting major structures in the temporal lobe were used to characterize connectivity in this local network. The results indicate that with adequate resolution and SNR, connections between network nodes are characterized well by this edge weight metric. Therefore this new dimensionless, scale-invariant edge weight metric provides a robust measure of network connectivity that can be applied in any size regime. PMID:26173147
Dimensionless, Scale Invariant, Edge Weight Metric for the Study of Complex Structural Networks.

PubMed

Colon-Perez, Luis M; Spindler, Caitlin; Goicochea, Shelby; Triplett, William; Parekh, Mansi; Montie, Eric; Carney, Paul R; Price, Catherine; Mareci, Thomas H

2015-01-01

High spatial and angular resolution diffusion weighted imaging (DWI) with network analysis provides a unique framework for the study of brain structure in vivo. DWI-derived brain connectivity patterns are best characterized with graph theory using an edge weight to quantify the strength of white matter connections between gray matter nodes. Here a dimensionless, scale-invariant edge weight is introduced to measure node connectivity. This edge weight metric provides reasonable and consistent values over any size scale (e.g. rodents to humans) used to quantify the strength of connection. Firstly, simulations were used to assess the effects of tractography seed point density and random errors in the estimated fiber orientations; with sufficient signal-to-noise ratio (SNR), edge weight estimates improve as the seed density increases. Secondly to evaluate the application of the edge weight in the human brain, ten repeated measures of DWI in the same healthy human subject were analyzed. Mean edge weight values within the cingulum and corpus callosum were consistent and showed low variability. Thirdly, using excised rat brains to study the effects of spatial resolution, the weight of edges connecting major structures in the temporal lobe were used to characterize connectivity in this local network. The results indicate that with adequate resolution and SNR, connections between network nodes are characterized well by this edge weight metric. Therefore this new dimensionless, scale-invariant edge weight metric provides a robust measure of network connectivity that can be applied in any size regime.
Inequalities in Global Trade: A Cross-Country Comparison of Trade Network Position, Economic Wealth, Pollution and Mortality.

PubMed

Prell, Christina; Sun, Laixiang; Feng, Kuishuang; Myroniuk, Tyler W

2015-01-01

In this paper we investigate how structural patterns of international trade give rise to emissions inequalities across countries, and how such inequality in turn impact countries' mortality rates. We employ Multi-regional Input-Output analysis to distinguish between sulfur-dioxide (SO2) emissions produced within a country's boarders (production-based emissions) and emissions triggered by consumption in other countries (consumption-based emissions). We use social network analysis to capture countries' level of integration within the global trade network. We then apply the Prais-Winsten panel estimation technique to a panel data set across 172 countries over 20 years (1990-2010) to estimate the relationships between countries' level of integration and SO2 emissions, and the impact of trade integration and SO2 emission on mortality rates. Our findings suggest a positive, (log-) linear relationship between a country's level of integration and both kinds of emissions. In addition, although more integrated countries are mainly responsible for both forms of emissions, our findings indicate that they also tend to experience lower mortality rates. Our approach offers a unique combination of social network analysis with multiregional input-output analysis, which better operationalizes intuitive concepts about global trade and trade structure.
Data identification for improving gene network inference using computational algebra.

PubMed

Dimitrova, Elena; Stigler, Brandilyn

2014-11-01

Identification of models of gene regulatory networks is sensitive to the amount of data used as input. Considering the substantial costs in conducting experiments, it is of value to have an estimate of the amount of data required to infer the network structure. To minimize wasted resources, it is also beneficial to know which data are necessary to identify the network. Knowledge of the data and knowledge of the terms in polynomial models are often required a priori in model identification. In applications, it is unlikely that the structure of a polynomial model will be known, which may force data sets to be unnecessarily large in order to identify a model. Furthermore, none of the known results provides any strategy for constructing data sets to uniquely identify a model. We provide a specialization of an existing criterion for deciding when a set of data points identifies a minimal polynomial model when its monomial terms have been specified. Then, we relax the requirement of the knowledge of the monomials and present results for model identification given only the data. Finally, we present a method for constructing data sets that identify minimal polynomial models.

Youth's social network structures and peer influences: study protocol MyMovez project - Phase I.

PubMed

Bevelander, Kirsten E; Smit, Crystal R; van Woudenberg, Thabo J; Buijs, Laura; Burk, William J; Buijzen, Moniek

2018-04-16

Youth are an important target group for social network interventions, because they are particularly susceptible to the adaptation of healthy and unhealthy habits and behaviors of others. They are surrounded by 'social influence agents' (i.e., role models such as family, friends and peers) that co-determine their dietary intake and physical activity. However, there is a lack of systematic and comprehensive research on the implementation of a social network approach in health campaigns. The MyMovez research project aims to fill this gap by developing a method for effective social network campaign implementation. This protocol paper describes the design and methods of Phase I of the MyMovez project, aiming to unravel youth's social network structures in combination with individual, psychosocial, and environmental factors related to energy intake and expenditure. In addition, the Wearable Lab is developed to enable an attractive and state-of-the-art way of collecting data and online campaign implementation via social networks. Phase I of the MyMovez project consists of a large-scale cross-sequential cohort study (N = 953; 8-12 and 12-15 y/o). In five waves during a 3-year period (2016-2018), data are collected about youth's social network exposure, media consumption, socialization experiences, psychological determinants of behavior, physical environment, dietary intake (snacking and drinking behavior) and physical activity using the Wearable Lab. The Wearable Lab exists of a smartphone-based research application (app) connected to an activity tracking bracelet, that is developed throughout the duration of the project. It generates peer- and self-reported (e.g., sociometric data and surveys) and experience sampling data, social network beacon data, real-time physical activity data (i.e., steps and cycling), location information, photos and chat conversation data from the app's social media platform Social Buzz. The MyMovez project - Phase I is an innovative cross-sequential research project that investigates how social influences co-determine youth's energy intake and expenditure. This project utilizes advanced research technologies (Wearable Lab) that provide unique opportunities to better understand the underlying processes that impact youths' health-related behaviors. The project is theoretically and methodologically pioneering and produces a unique and useful method for successfully implementing and improving health campaigns.
Deep learning for computational chemistry.

PubMed

Goh, Garrett B; Hodas, Nathan O; Vishnu, Abhinav

2017-06-15

The rise and fall of artificial neural networks is well documented in the scientific literature of both computer science and computational chemistry. Yet almost two decades later, we are now seeing a resurgence of interest in deep learning, a machine learning algorithm based on multilayer neural networks. Within the last few years, we have seen the transformative impact of deep learning in many domains, particularly in speech recognition and computer vision, to the extent that the majority of expert practitioners in those field are now regularly eschewing prior established models in favor of deep learning models. In this review, we provide an introductory overview into the theory of deep neural networks and their unique properties that distinguish them from traditional machine learning algorithms used in cheminformatics. By providing an overview of the variety of emerging applications of deep neural networks, we highlight its ubiquity and broad applicability to a wide range of challenges in the field, including quantitative structure activity relationship, virtual screening, protein structure prediction, quantum chemistry, materials design, and property prediction. In reviewing the performance of deep neural networks, we observed a consistent outperformance against non-neural networks state-of-the-art models across disparate research topics, and deep neural network-based models often exceeded the "glass ceiling" expectations of their respective tasks. Coupled with the maturity of GPU-accelerated computing for training deep neural networks and the exponential growth of chemical data on which to train these networks on, we anticipate that deep learning algorithms will be a valuable tool for computational chemistry. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Minimum spanning tree analysis of the human connectome.

PubMed

van Dellen, Edwin; Sommer, Iris E; Bohlken, Marc M; Tewarie, Prejaas; Draaisma, Laurijn; Zalesky, Andrew; Di Biase, Maria; Brown, Jesse A; Douw, Linda; Otte, Willem M; Mandl, René C W; Stam, Cornelis J

2018-06-01

One of the challenges of brain network analysis is to directly compare network organization between subjects, irrespective of the number or strength of connections. In this study, we used minimum spanning tree (MST; a unique, acyclic subnetwork with a fixed number of connections) analysis to characterize the human brain network to create an empirical reference network. Such a reference network could be used as a null model of connections that form the backbone structure of the human brain. We analyzed the MST in three diffusion-weighted imaging datasets of healthy adults. The MST of the group mean connectivity matrix was used as the empirical null-model. The MST of individual subjects matched this reference MST for a mean 58%-88% of connections, depending on the analysis pipeline. Hub nodes in the MST matched with previously reported locations of hub regions, including the so-called rich club nodes (a subset of high-degree, highly interconnected nodes). Although most brain network studies have focused primarily on cortical connections, cortical-subcortical connections were consistently present in the MST across subjects. Brain network efficiency was higher when these connections were included in the analysis, suggesting that these tracts may be utilized as the major neural communication routes. Finally, we confirmed that MST characteristics index the effects of brain aging. We conclude that the MST provides an elegant and straightforward approach to analyze structural brain networks, and to test network topological features of individual subjects in comparison to empirical null models. © 2018 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.
The molecular origins of specificity in the assembly of a multienzyme complex.

PubMed

Frank, René A W; Pratap, J Venkatesh; Pei, Xue Y; Perham, Richard N; Luisi, Ben F

2005-08-01

The pyruvate dehydrogenase (PDH) multienzyme complex is central to oxidative metabolism. We present the first crystal structure of a complex between pyruvate decarboxylase (E1) and the peripheral subunit binding domain (PSBD) of the dihydrolipoyl acetyltransferase (E2). The interface is dominated by a "charge zipper" of networked salt bridges. Remarkably, the PSBD uses essentially the same zipper to alternately recognize the dihydrolipoyl dehydrogenase (E3) component of the PDH assembly. The PSBD achieves this dual recognition largely through the addition of a network of interfacial water molecules unique to the E1-PSBD complex. These structural comparisons illuminate our observations that the formation of this water-rich E1-E2 interface is largely enthalpy driven, whereas that of the E3-PSBD complex (from which water is excluded) is entropy driven. Interfacial water molecules thus diversify surface complementarity and contribute to avidity, enthalpically. Additionally, the E1-PSBD structure provides insight into the organization and active site coupling within the approximately 9 MDa PDH complex.
Improving quantitative structure-activity relationship models using Artificial Neural Networks trained with dropout.

PubMed

Mendenhall, Jeffrey; Meiler, Jens

2016-02-01

Dropout is an Artificial Neural Network (ANN) training technique that has been shown to improve ANN performance across canonical machine learning (ML) datasets. Quantitative Structure Activity Relationship (QSAR) datasets used to relate chemical structure to biological activity in Ligand-Based Computer-Aided Drug Discovery pose unique challenges for ML techniques, such as heavily biased dataset composition, and relatively large number of descriptors relative to the number of actives. To test the hypothesis that dropout also improves QSAR ANNs, we conduct a benchmark on nine large QSAR datasets. Use of dropout improved both enrichment false positive rate and log-scaled area under the receiver-operating characteristic curve (logAUC) by 22-46 % over conventional ANN implementations. Optimal dropout rates are found to be a function of the signal-to-noise ratio of the descriptor set, and relatively independent of the dataset. Dropout ANNs with 2D and 3D autocorrelation descriptors outperform conventional ANNs as well as optimized fingerprint similarity search methods.
Improving Quantitative Structure-Activity Relationship Models using Artificial Neural Networks Trained with Dropout

PubMed Central

Mendenhall, Jeffrey; Meiler, Jens

2016-01-01

Dropout is an Artificial Neural Network (ANN) training technique that has been shown to improve ANN performance across canonical machine learning (ML) datasets. Quantitative Structure Activity Relationship (QSAR) datasets used to relate chemical structure to biological activity in Ligand-Based Computer-Aided Drug Discovery (LB-CADD) pose unique challenges for ML techniques, such as heavily biased dataset composition, and relatively large number of descriptors relative to the number of actives. To test the hypothesis that dropout also improves QSAR ANNs, we conduct a benchmark on nine large QSAR datasets. Use of dropout improved both Enrichment false positive rate (FPR) and log-scaled area under the receiver-operating characteristic curve (logAUC) by 22–46% over conventional ANN implementations. Optimal dropout rates are found to be a function of the signal-to-noise ratio of the descriptor set, and relatively independent of the dataset. Dropout ANNs with 2D and 3D autocorrelation descriptors outperform conventional ANNs as well as optimized fingerprint similarity search methods. PMID:26830599
Supramolecular self-assembly on the B-Si(111)-(√3x√3) R30° surface: From single molecules to multicomponent networks

NASA Astrophysics Data System (ADS)

Makoudi, Younes; Jeannoutot, Judicaël; Palmino, Frank; Chérioux, Frédéric; Copie, Guillaume; Krzeminski, Christophe; Cleri, Fabrizio; Grandidier, Bruno

2017-09-01

Understanding the physical and chemical processes in which local interactions lead to ordered structures is of particular relevance to the realization of supramolecular architectures on surfaces. While spectacular patterns have been demonstrated on metal surfaces, there have been fewer studies of the spontaneous organization of supramolecular networks on semiconductor surfaces, where the formation of covalent bonds between organics and adatoms usually hamper the diffusion of molecules and their subsequent interactions with each other. However, the saturation of the dangling bonds at a semiconductor surface is known to make them inert and offers a unique way for the engineering of molecular patterns on these surfaces. This review describes the physicochemical properties of the passivated B-Si(111)-(√3x√3) R30° surface, that enable the self-assembly of molecules into a rich variety of extended and regular structures on silicon. Particular attention is given to computational methods based on multi-scale simulations that allow to rationalize the relative contribution of the dispersion forces involved in the self-assembled networks observed with scanning tunneling microscopy. A summary of state of the art studies, where a fine tuning of the molecular network topology has been achieved, sheds light on new frontiers for exploiting the construction of supramolecular structures on semiconductor surfaces.
Self-Template-Directed Metal-Organic Frameworks Network and the Derived Honeycomb-Like Carbon Flakes via Confinement Pyrolysis.

PubMed

Wang, Jie; Tang, Jing; Ding, Bing; Chang, Zhi; Hao, Xiaodong; Takei, Toshiaki; Kobayashi, Naoya; Bando, Yoshio; Zhang, Xiaogang; Yamauchi, Yusuke

2018-04-01

Metal-organic frameworks (MOFs) have become a research hotspot since they have been explored as convenient precursors for preparing various multifunctional nanomaterials. However, the preparation of MOF networks with controllable flake morphology in large scale is not realized yet. Herein, a self-template strategy is developed to prepare MOF networks. In this work, layered double-metal hydroxide (LDH) and other layered metal hydroxides are used not only as a scaffold but also as a self-sacrificed metal source. After capturing the abundant metal cations identically from the LDH by the organic linkers, MOF networks are in situ formed. It is interesting that the MOF network-derived carbon materials retain the flake morphology and exhibit a unique honeycomb-like macroporous structure due to the confined shrinkage of the polyhedral facets. The overall properties of the carbon networks are adjustable according to the tailored metal compositions in LDH and the derived MOFs, which are desirable for target-oriented applications as exemplified by the electrochemical application in supercapacitors. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Face Patch Resting State Networks Link Face Processing to Social Cognition

PubMed Central

Schwiedrzik, Caspar M.; Zarco, Wilbert; Everling, Stefan; Freiwald, Winrich A.

2015-01-01

Faces transmit a wealth of social information. How this information is exchanged between face-processing centers and brain areas supporting social cognition remains largely unclear. Here we identify these routes using resting state functional magnetic resonance imaging in macaque monkeys. We find that face areas functionally connect to specific regions within frontal, temporal, and parietal cortices, as well as subcortical structures supporting emotive, mnemonic, and cognitive functions. This establishes the existence of an extended face-recognition system in the macaque. Furthermore, the face patch resting state networks and the default mode network in monkeys show a pattern of overlap akin to that between the social brain and the default mode network in humans: this overlap specifically includes the posterior superior temporal sulcus, medial parietal, and dorsomedial prefrontal cortex, areas supporting high-level social cognition in humans. Together, these results reveal the embedding of face areas into larger brain networks and suggest that the resting state networks of the face patch system offer a new, easily accessible venue into the functional organization of the social brain and into the evolution of possibly uniquely human social skills. PMID:26348613
Strain-Induced Alignment in Collagen Gels

PubMed Central

Vader, David; Kabla, Alexandre; Weitz, David; Mahadevan, Lakshminarayana

2009-01-01

Collagen is the most abundant extracellular-network-forming protein in animal biology and is important in both natural and artificial tissues, where it serves as a material of great mechanical versatility. This versatility arises from its almost unique ability to remodel under applied loads into anisotropic and inhomogeneous structures. To explore the origins of this property, we develop a set of analysis tools and a novel experimental setup that probes the mechanical response of fibrous networks in a geometry that mimics a typical deformation profile imposed by cells in vivo. We observe strong fiber alignment and densification as a function of applied strain for both uncrosslinked and crosslinked collagenous networks. This alignment is found to be irreversibly imprinted in uncrosslinked collagen networks, suggesting a simple mechanism for tissue organization at the microscale. However, crosslinked networks display similar fiber alignment and the same geometrical properties as uncrosslinked gels, but with full reversibility. Plasticity is therefore not required to align fibers. On the contrary, our data show that this effect is part of the fundamental non-linear properties of fibrous biological networks. PMID:19529768
On the stochastic dissemination of faults in an admissible network

NASA Technical Reports Server (NTRS)

Kyrala, A.

1987-01-01

The dynamic distribution of faults in a general type network is discussed. The starting point is a uniquely branched network in which each pair of nodes is connected by a single branch. Mathematical expressions for the uniquely branched network transition matrix are derived to show that sufficient stationarity exists to ensure the validity of the use of the Markov Chain model to analyze networks. In addition the conditions for the use of Semi-Markov models are discussed. General mathematical expressions are derived in an examination of branch redundancy techniques commonly used to increase reliability.
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
Scale-free networks of the earth’s surface

NASA Astrophysics Data System (ADS)

Liu, Gang; He, Jing; Luo, Kaitian; Gao, Peichao; Ma, Lei

2016-06-01

Studying the structure of real complex systems is of paramount importance in science and engineering. Despite our understanding of lots of real systems, we hardly cognize our unique living environment — the earth. The structural complexity of the earth’s surface is, however, still unknown in detail. Here, we define the modeling of graph topology for the earth’s surface, using the satellite images of the earth’s surface under different spatial resolutions derived from Google Earth. We find that the graph topologies of the earth’s surface are scale-free networks regardless of the spatial resolutions. For different spatial resolutions, the exponents of power-law distributions and the modularity are both quite different; however, the average clustering coefficient is approximately equal to a constant. We explore the morphology study of the earth’s surface, which enables a comprehensive understanding of the morphological feature of the earth’s surface.
Experimental demonstration of topologically protected efficient sound propagation in an acoustic waveguide network

NASA Astrophysics Data System (ADS)

Wei, Qi; Tian, Ye; Zuo, Shu-Yu; Cheng, Ying; Liu, Xiao-Jun

2017-03-01

Acoustic topological states support sound propagation along the boundary in a one-way direction with inherent robustness against defects and disorders, leading to the revolution of the manipulation on acoustic waves. A variety of acoustic topological states relying on circulating fluid, chiral coupling, or temporal modulation have been proposed theoretically. However, experimental demonstration has so far remained a significant challenge, due to the critical limitations such as structural complexity and high losses. Here, we experimentally demonstrate an acoustic anomalous Floquet topological insulator in a waveguide network. The acoustic gapless edge states can be found in the band gap when the waveguides are strongly coupled. The scheme features simple structure and high-energy throughput, leading to the experimental demonstration of efficient and robust topologically protected sound propagation along the boundary. The proposal may offer a unique, promising application for design of acoustic devices in acoustic guiding, switching, isolating, filtering, etc.
White matter tract network disruption explains reduced conscientiousness in multiple sclerosis.

PubMed

Fuchs, Tom A; Dwyer, Michael G; Kuceyeski, Amy; Choudhery, Sanjeevani; Carolus, Keith; Li, Xian; Mallory, Matthew; Weinstock-Guttman, Bianca; Jakimovski, Dejan; Ramasamy, Deepa; Zivadinov, Robert; Benedict, Ralph H B

2018-05-08

Quantifying white matter (WM) tract disruption in people with multiple sclerosis (PwMS) provides a novel means for investigating the relationship between defective network connectivity and clinical markers. PwMS exhibit perturbations in personality, where decreased Conscientiousness is particularly prominent. This trait deficit influences disease trajectory and functional outcomes such as work capacity. We aimed to identify patterns of WM tract disruption related to decreased Conscientiousness in PwMS. Personality assessment and brain MRI were obtained in 133 PwMS and 49 age- and sex-matched healthy controls (HC). Lesion maps were applied to determine the severity of WM tract disruption between pairs of gray matter regions. Next, the Network-Based-Statistics tool was applied to identify structural networks whose disruption negatively correlates with Conscientiousness. Finally, to determine whether these networks explain unique variance above conventional MRI measures and cognition, regression models were applied controlling for age, sex, brain volume, T2-lesion volume, and cognition. Relative to HCs, PwMS exhibited lower Conscientiousness and slowed cognitive processing speed (p = .025, p = .006). Lower Conscientiousness in PwMS was significantly associated with WM tract disruption between frontal, frontal-parietal, and frontal-cingulate pathways in the left (p = .02) and right (p = .01) hemisphere. The mean disruption of these pathways explained unique additive variance in Conscientiousness, after accounting for conventional MRI markers of pathology and cognition (ΔR 2 = .049, p = .029). Damage to WM tracts between frontal, frontal-parietal, and frontal-cingulate cortical regions is significantly correlated with reduced Conscientiousness in PwMS. Tract disruption within these networks explains decreased Conscientiousness observed in PwMS as compared with HCs. © 2018 Wiley Periodicals, Inc.
Confinement properties of 2D porous molecular networks on metal surfaces

NASA Astrophysics Data System (ADS)

Müller, Kathrin; Enache, Mihaela; Stöhr, Meike

2016-04-01

Quantum effects that arise from confinement of electronic states have been extensively studied for the surface states of noble metals. Utilizing small artificial structures for confinement allows tailoring of the surface properties and offers unique opportunities for applications. So far, examples of surface state confinement include thin films, artificial nanoscale structures, vacancy and adatom islands, self-assembled 1D chains, vicinal surfaces, quantum dots and quantum corrals. In this review we summarize recent achievements in changing the electronic structure of surfaces by adsorption of nanoporous networks whose design principles are based on the concepts of supramolecular chemistry. Already in 1993, it was shown that quantum corrals made from Fe atoms on a Cu(1 1 1) surface using single atom manipulation with a scanning tunnelling microscope confine the Shockley surface state. However, since the atom manipulation technique for the construction of corral structures is a relatively time consuming process, the fabrication of periodic two-dimensional (2D) corral structures is practically impossible. On the other side, by using molecular self-assembly extended 2D porous structures can be achieved in a parallel process, i.e. all pores are formed at the same time. The molecular building blocks are usually held together by non-covalent interactions like hydrogen bonding, metal coordination or dipolar coupling. Due to the reversibility of the bond formation defect-free and long-range ordered networks can be achieved. However, recently also examples of porous networks formed by covalent coupling on the surface have been reported. By the choice of the molecular building blocks, the dimensions of the network (pore size and pore to pore distance) can be controlled. In this way, the confinement properties of the individual pores can be tuned. In addition, the effect of the confined state on the hosting properties of the pores will be discussed in this review article.
Confinement properties of 2D porous molecular networks on metal surfaces.

PubMed

Müller, Kathrin; Enache, Mihaela; Stöhr, Meike

2016-04-20

Quantum effects that arise from confinement of electronic states have been extensively studied for the surface states of noble metals. Utilizing small artificial structures for confinement allows tailoring of the surface properties and offers unique opportunities for applications. So far, examples of surface state confinement include thin films, artificial nanoscale structures, vacancy and adatom islands, self-assembled 1D chains, vicinal surfaces, quantum dots and quantum corrals. In this review we summarize recent achievements in changing the electronic structure of surfaces by adsorption of nanoporous networks whose design principles are based on the concepts of supramolecular chemistry. Already in 1993, it was shown that quantum corrals made from Fe atoms on a Cu(1 1 1) surface using single atom manipulation with a scanning tunnelling microscope confine the Shockley surface state. However, since the atom manipulation technique for the construction of corral structures is a relatively time consuming process, the fabrication of periodic two-dimensional (2D) corral structures is practically impossible. On the other side, by using molecular self-assembly extended 2D porous structures can be achieved in a parallel process, i.e. all pores are formed at the same time. The molecular building blocks are usually held together by non-covalent interactions like hydrogen bonding, metal coordination or dipolar coupling. Due to the reversibility of the bond formation defect-free and long-range ordered networks can be achieved. However, recently also examples of porous networks formed by covalent coupling on the surface have been reported. By the choice of the molecular building blocks, the dimensions of the network (pore size and pore to pore distance) can be controlled. In this way, the confinement properties of the individual pores can be tuned. In addition, the effect of the confined state on the hosting properties of the pores will be discussed in this review article.
Adaptations and Analysis of the AFIT Noise Radar Network for Indoor Navigation

DTIC Science & Technology

2013-03-01

capable of producing bistatic/multistatic radar images. NTR is unique because it utilizes amplified random thermal noise as its transmission waveform...structure and operation of NTR is described. A minutia of the EM theory describing the various phenomenon found when operating RF devices in indoor...construction of NTR is simple in comparison to other CW radars. The system begins with a commercial thermal noise source, which produces a uniform
Perspectives for computational modeling of cell replacement for neurological disorders

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

Aimone, James B.; Weick, Jason P.

In mathematical modeling of anatomically-constrained neural networks we provide significant insights regarding the response of networks to neurological disorders or injury. Furthermore, a logical extension of these models is to incorporate treatment regimens to investigate network responses to intervention. The addition of nascent neurons from stem cell precursors into damaged or diseased tissue has been used as a successful therapeutic tool in recent decades. Interestingly, models have been developed to examine the incorporation of new neurons into intact adult structures, particularly the dentate granule neurons of the hippocampus. These studies suggest that the unique properties of maturing neurons, can impactmore » circuit behavior in unanticipated ways. In this perspective, we review the current status of models used to examine damaged CNS structures with particular focus on cortical damage due to stroke. Secondly, we suggest that computational modeling of cell replacement therapies can be made feasible by implementing approaches taken by current models of adult neurogenesis. The development of these models is critical for generating hypotheses regarding transplant therapies and improving outcomes by tailoring transplants to desired effects.« less
Perspectives for computational modeling of cell replacement for neurological disorders

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

Aimone, James B.; Weick, Jason P.

Mathematical modeling of anatomically-constrained neural networks has provided significant insights regarding the response of networks to neurological disorders or injury. A logical extension of these models is to incorporate treatment regimens to investigate network responses to intervention. The addition of nascent neurons from stem cell precursors into damaged or diseased tissue has been used as a successful therapeutic tool in recent decades. Interestingly, models have been developed to examine the incorporation of new neurons into intact adult structures, particularly the dentate granule neurons of the hippocampus. These studies suggest that the unique properties of maturing neurons, can impact circuit behaviormore » in unanticipated ways. In this perspective, we review the current status of models used to examine damaged CNS structures with particular focus on cortical damage due to stroke. Secondly, we suggest that computational modeling of cell replacement therapies can be made feasible by implementing approaches taken by current models of adult neurogenesis. The development of these models is critical for generating hypotheses regarding transplant therapies and improving outcomes by tailoring transplants to desired effects.« less

The Development of a High-Throughput/Combinatorial Workflow for the Study of Porous Polymer Networks

DTIC Science & Technology

2012-04-05

poragen composition , poragen level, and cure temperature. A total of 216 unique compositions were prepared. Changes in opacity of the blends as they cured...allowed for the identification of compositional variables and process variables that enabled the production of porous networks. Keywords: high...in polymer network cross-link density,poragen composition , poragen level, and cure temperature. A total of 216 unique compositions were prepared
Conservation of high-flux backbone in alternate optimal and near-optimal flux distributions of metabolic networks.

PubMed

Samal, Areejit

2008-12-01

Constraint-based flux balance analysis (FBA) has proven successful in predicting the flux distribution of metabolic networks in diverse environmental conditions. FBA finds one of the alternate optimal solutions that maximizes the biomass production rate. Almaas et al. have shown that the flux distribution follows a power law, and it is possible to associate with most metabolites two reactions which maximally produce and consume a given metabolite, respectively. This observation led to the concept of high-flux backbone (HFB) in metabolic networks. In previous work, the HFB has been computed using a particular optima obtained using FBA. In this paper, we investigate the conservation of HFB of a particular solution for a given medium across different alternate optima and near-optima in metabolic networks of E. coli and S. cerevisiae. Using flux variability analysis (FVA), we propose a method to determine reactions that are guaranteed to be in HFB regardless of alternate solutions. We find that the HFB of a particular optima is largely conserved across alternate optima in E. coli, while it is only moderately conserved in S. cerevisiae. However, the HFB of a particular near-optima shows a large variation across alternate near-optima in both organisms. We show that the conserved set of reactions in HFB across alternate near-optima has a large overlap with essential reactions and reactions which are both uniquely consuming (UC) and uniquely producing (UP). Our findings suggest that the structure of the metabolic network admits a high degree of redundancy and plasticity in near-optimal flow patterns enhancing system robustness for a given environmental condition.
Superhard BC(3) in cubic diamond structure.

PubMed

Zhang, Miao; Liu, Hanyu; Li, Quan; Gao, Bo; Wang, Yanchao; Li, Hongdong; Chen, Changfeng; Ma, Yanming

2015-01-09

We solve the crystal structure of recently synthesized cubic BC(3) using an unbiased swarm structure search, which identifies a highly symmetric BC(3) phase in the cubic diamond structure (d-BC(3)) that contains a distinct B-B bonding network along the body diagonals of a large 64-atom unit cell. Simulated x-ray diffraction and Raman peaks of d-BC(3) are in excellent agreement with experimental data. Calculated stress-strain relations of d-BC(3) demonstrate its intrinsic superhard nature and reveal intriguing sequential bond-breaking modes that produce superior ductility and extended elasticity, which are unique among superhard solids. The present results establish the first boron carbide in the cubic diamond structure with remarkable properties, and these new findings also provide insights for exploring other covalent solids with complex bonding configurations.
Discriminating the Difference between Remote and Close Association with Relation to White-Matter Structural Connectivity

PubMed Central

Wu, Chinglin; Zhong, Suyu; Chen, Hsuehchih

2016-01-01

Remote association is a core ability that influences creative output. In contrast to close association, remote association is commonly agreed to be connected with more original and unique concepts. However, although existing studies have discovered that creativity is closely related to the white-matter structure of the brain, there are no studies that examine the relevance between the connectivity efficiencies and creativity of the brain regions from the perspective of networks. Consequently, this study constructed a brain white matter network structure that consisted of cerebral tissues and nerve fibers and used graph theory to analyze the connection efficiencies among the network nodes, further illuminating the differences between remote and close association in relation to the connectivity of the brain network. Researchers analyzed correlations between the scores of 35 healthy adults with regard to remote and close associations and the connectivity efficiencies of the white-matter network of the brain. Controlling for gender, age, and verbal intelligence, the remote association positively correlated with the global efficiency and negatively correlated with the levels of small-world. A close association negatively correlated with the global efficiency. Notably, the node efficiency in the middle temporal gyrus (MTG) positively correlated with remote association and negatively correlated with close association. To summarize, remote and close associations work differently as patterns in the brain network. Remote association requires efficient and convenient mutual connections between different brain regions, while close association emphasizes the limited connections that exist in a local region. These results are consistent with previous results, which indicate that creativity is based on the efficient integration and connection between different regions of the brain and that temporal lobes are the key regions for discriminating remote and close associations. PMID:27760177
A palladium-doped ceria@carbon core-sheath nanowire network: a promising catalyst support for alcohol electrooxidation reactions

NASA Astrophysics Data System (ADS)

Tan, Qiang; Du, Chunyu; Sun, Yongrong; Du, Lei; Yin, Geping; Gao, Yunzhi

2015-08-01

A novel palladium-doped ceria and carbon core-sheath nanowire network (Pd-CeO2@C CSNWN) is synthesized by a template-free and surfactant-free solvothermal process, followed by high temperature carbonization. This hierarchical network serves as a new class of catalyst support to enhance the activity and durability of noble metal catalysts for alcohol oxidation reactions. Its supported Pd nanoparticles, Pd/(Pd-CeO2@C CSNWN), exhibit >9 fold increase in activity toward the ethanol oxidation over the state-of-the-art Pd/C catalyst, which is the highest among the reported Pd systems. Moreover, stability tests show a virtually unchanged activity after 1000 cycles. The high activity is mainly attributed to the superior oxygen-species releasing capability of Pd-doped CeO2 nanowires by accelerating the removal of the poisoning intermediate. The unique interconnected one-dimensional core-sheath structure is revealed to facilitate immobilization of the metal catalysts, leading to the improved durability. This core-sheath nanowire network opens up a new strategy for catalyst performance optimization for next-generation fuel cells.A novel palladium-doped ceria and carbon core-sheath nanowire network (Pd-CeO2@C CSNWN) is synthesized by a template-free and surfactant-free solvothermal process, followed by high temperature carbonization. This hierarchical network serves as a new class of catalyst support to enhance the activity and durability of noble metal catalysts for alcohol oxidation reactions. Its supported Pd nanoparticles, Pd/(Pd-CeO2@C CSNWN), exhibit >9 fold increase in activity toward the ethanol oxidation over the state-of-the-art Pd/C catalyst, which is the highest among the reported Pd systems. Moreover, stability tests show a virtually unchanged activity after 1000 cycles. The high activity is mainly attributed to the superior oxygen-species releasing capability of Pd-doped CeO2 nanowires by accelerating the removal of the poisoning intermediate. The unique interconnected one-dimensional core-sheath structure is revealed to facilitate immobilization of the metal catalysts, leading to the improved durability. This core-sheath nanowire network opens up a new strategy for catalyst performance optimization for next-generation fuel cells. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr03023d
Pattern reverberation in networks of excitable systems with connection delays

NASA Astrophysics Data System (ADS)

Lücken, Leonhard; Rosin, David P.; Worlitzer, Vasco M.; Yanchuk, Serhiy

2017-01-01

We consider the recurrent pulse-coupled networks of excitable elements with delayed connections, which are inspired by the biological neural networks. If the delays are tuned appropriately, the network can either stay in the steady resting state, or alternatively, exhibit a desired spiking pattern. It is shown that such a network can be used as a pattern-recognition system. More specifically, the application of the correct pattern as an external input to the network leads to a self-sustained reverberation of the encoded pattern. In terms of the coupling structure, the tolerance and the refractory time of the individual systems, we determine the conditions for the uniqueness of the sustained activity, i.e., for the functionality of the network as an unambiguous pattern detector. We point out the relation of the considered systems with cyclic polychronous groups and show how the assumed delay configurations may arise in a self-organized manner when a spike-time dependent plasticity of the connection delays is assumed. As excitable elements, we employ the simplistic coincidence detector models as well as the Hodgkin-Huxley neuron models. Moreover, the system is implemented experimentally on a Field-Programmable Gate Array.
The advantage of flexible neuronal tunings in neural network models for motor learning

PubMed Central

Marongelli, Ellisha N.; Thoroughman, Kurt A.

2013-01-01

Human motor adaptation to novel environments is often modeled by a basis function network that transforms desired movement properties into estimated forces. This network employs a layer of nodes that have fixed broad tunings that generalize across the input domain. Learning is achieved by updating the weights of these nodes in response to training experience. This conventional model is unable to account for rapid flexibility observed in human spatial generalization during motor adaptation. However, added plasticity in the widths of the basis function tunings can achieve this flexibility, and several neurophysiological experiments have revealed flexibility in tunings of sensorimotor neurons. We found a model, Locally Weighted Projection Regression (LWPR), which uniquely possesses the structure of a basis function network in which both the weights and tuning widths of the nodes are updated incrementally during adaptation. We presented this LWPR model with training functions of different spatial complexities and monitored incremental updates to receptive field widths. An inverse pattern of dependence of receptive field adaptation on experienced error became evident, underlying both a relationship between generalization and complexity, and a unique behavior in which generalization always narrows after a sudden switch in environmental complexity. These results implicate a model that is flexible in both basis function widths and weights, like LWPR, as a viable alternative model for human motor adaptation that can account for previously observed plasticity in spatial generalization. This theory can be tested by using the behaviors observed in our experiments as novel hypotheses in human studies. PMID:23888141
Social support and ambulatory blood pressure: an examination of both receiving and giving.

PubMed

Piferi, Rachel L; Lawler, Kathleen A

2006-11-01

The relationship between the social network and physical health has been studied extensively and it has consistently been shown that individuals live longer, have fewer physical symptoms of illness, and have lower blood pressure when they are a member of a social network than when they are isolated. Much of the research has focused on the benefits of receiving social support from the network and the effects of giving to others within the network have been neglected. The goal of the present research was to systematically investigate the relationship between giving and ambulatory blood pressure. Systolic blood pressure, diastolic blood pressure, mean arterial pressure, and heart rate were recorded every 30 min during the day and every 60 min at night during a 24-h period. Linear mixed models analyses revealed that lower systolic and diastolic blood pressure and mean arterial pressure were related to giving social support. Furthermore, correlational analyses revealed that participants with a higher tendency to give social support reported greater received social support, greater self-efficacy, greater self-esteem, less depression, and less stress than participants with a lower tendency to give social support to others. Structural equation modeling was also used to test a proposed model that giving and receiving social support represent separate pathways predicting blood pressure and health. From this study, it appears that giving social support may represent a unique construct from receiving social support and may exert a unique effect on health.
Stem cell bioprinting for applications in regenerative medicine.

PubMed

Tricomi, Brad J; Dias, Andrew D; Corr, David T

2016-11-01

Many regenerative medicine applications seek to harness the biologic power of stem cells in architecturally complex scaffolds or microenvironments. Traditional tissue engineering methods cannot create such intricate structures, nor can they precisely control cellular position or spatial distribution. These limitations have spurred advances in the field of bioprinting, aimed to satisfy these structural and compositional demands. Bioprinting can be defined as the programmed deposition of cells or other biologics, often with accompanying biomaterials. In this concise review, we focus on recent advances in stem cell bioprinting, including performance, utility, and applications in regenerative medicine. More specifically, this review explores the capability of bioprinting to direct stem cell fate, engineer tissue(s), and create functional vascular networks. Furthermore, the unique challenges and concerns related to bioprinting living stem cells, such as viability and maintaining multi- or pluripotency, are discussed. The regenerative capacity of stem cells, when combined with the structural/compositional control afforded by bioprinting, provides a unique and powerful tool to address the complex demands of tissue engineering and regenerative medicine applications. © 2016 New York Academy of Sciences.
ANN multiscale model of anti-HIV drugs activity vs AIDS prevalence in the US at county level based on information indices of molecular graphs and social networks.

PubMed

González-Díaz, Humberto; Herrera-Ibatá, Diana María; Duardo-Sánchez, Aliuska; Munteanu, Cristian R; Orbegozo-Medina, Ricardo Alfredo; Pazos, Alejandro

2014-03-24

This work is aimed at describing the workflow for a methodology that combines chemoinformatics and pharmacoepidemiology methods and at reporting the first predictive model developed with this methodology. The new model is able to predict complex networks of AIDS prevalence in the US counties, taking into consideration the social determinants and activity/structure of anti-HIV drugs in preclinical assays. We trained different Artificial Neural Networks (ANNs) using as input information indices of social networks and molecular graphs. We used a Shannon information index based on the Gini coefficient to quantify the effect of income inequality in the social network. We obtained the data on AIDS prevalence and the Gini coefficient from the AIDSVu database of Emory University. We also used the Balaban information indices to quantify changes in the chemical structure of anti-HIV drugs. We obtained the data on anti-HIV drug activity and structure (SMILE codes) from the ChEMBL database. Last, we used Box-Jenkins moving average operators to quantify information about the deviations of drugs with respect to data subsets of reference (targets, organisms, experimental parameters, protocols). The best model found was a Linear Neural Network (LNN) with values of Accuracy, Specificity, and Sensitivity above 0.76 and AUROC > 0.80 in training and external validation series. This model generates a complex network of AIDS prevalence in the US at county level with respect to the preclinical activity of anti-HIV drugs in preclinical assays. To train/validate the model and predict the complex network we needed to analyze 43,249 data points including values of AIDS prevalence in 2,310 counties in the US vs ChEMBL results for 21,582 unique drugs, 9 viral or human protein targets, 4,856 protocols, and 10 possible experimental measures.
Dendritic Connectivity, Heterogeneity, and Scaling in Urban Stormwater Networks: Implications for Socio-Hydrology

NASA Astrophysics Data System (ADS)

Mejia, A.; Jovanovic, T.; Hale, R. L.; Gironas, J. A.

2017-12-01

Urban stormwater networks (USNs) are unique dendritic (tree-like) structures that combine both artificial (e.g., swales and pipes) and natural (e.g., streams and wetlands) components. They are central to stream ecosystem structure and function in urban watersheds. The emphasis of conventional stormwater management, however, has been on localized, temporal impacts (e.g., changes to hydrographs at discrete locations), and the performance of individual stormwater control measures. This is the case even though control measures are implemented to prevent impacts on the USN. We develop a modeling approach to retrospectively study hydrological fluxes and states in USNs and apply the model to an urban watershed in Scottsdale, Arizona, USA. Using outputs from the model, we analyze over space and time the network properties of dendritic connectivity, heterogeneity, and scaling. Results show that as the network growth over time, due to increasing urbanization, it tends to become more homogenous in terms of topological features but increasingly heterogeneous in terms of dynamic features. We further use the modeling results to address socio-hydrological implications for USNs. We find that the adoption over time of evolving management strategies (e.g., widespread implementation of vegetated swales and retention ponds versus pipes) may be locally beneficial to the USN but benefits may not propagate systematically through the network. The latter can be reinforced by sudden, perhaps unintended, changes to the overall dendritic connectivity.
Second language social networks and communication-related acculturative stress: the role of interconnectedness

PubMed Central

Doucerain, Marina M.; Varnaamkhaasti, Raheleh S.; Segalowitz, Norman; Ryder, Andrew G.

2015-01-01

Although a substantial amount of cross-cultural psychology research has investigated acculturative stress in general, little attention has been devoted specifically to communication-related acculturative stress (CRAS). In line with the view that cross-cultural adaptation and second language (L2) learning are social and interpersonal phenomena, the present study examines the hypothesis that migrants’ L2 social network size and interconnectedness predict CRAS. The main idea underlying this hypothesis is that L2 social networks play an important role in fostering social and cultural aspects of communicative competence. Specifically, higher interconnectedness may reflect greater access to unmodified natural cultural representations and L2 communication practices, thus fostering communicative competence through observational learning. As such, structural aspects of migrants’ L2 social networks may be protective against acculturative stress arising from chronic communication difficulties. Results from a study of first generation migrant students (N = 100) support this idea by showing that both inclusiveness and density of the participants’ L2 network account for unique variance in CRAS but not in general acculturative stress. These results support the idea that research on cross-cultural adaptation would benefit from disentangling the various facets of acculturative stress and that the structure of migrants’ L2 network matters for language related outcomes. Finally, this study contributes to an emerging body of work that attempts to integrate cultural/cross-cultural research on acculturation and research on intercultural communication and second language learning. PMID:26300809
Second language social networks and communication-related acculturative stress: the role of interconnectedness.

PubMed

Doucerain, Marina M; Varnaamkhaasti, Raheleh S; Segalowitz, Norman; Ryder, Andrew G

2015-01-01

Although a substantial amount of cross-cultural psychology research has investigated acculturative stress in general, little attention has been devoted specifically to communication-related acculturative stress (CRAS). In line with the view that cross-cultural adaptation and second language (L2) learning are social and interpersonal phenomena, the present study examines the hypothesis that migrants' L2 social network size and interconnectedness predict CRAS. The main idea underlying this hypothesis is that L2 social networks play an important role in fostering social and cultural aspects of communicative competence. Specifically, higher interconnectedness may reflect greater access to unmodified natural cultural representations and L2 communication practices, thus fostering communicative competence through observational learning. As such, structural aspects of migrants' L2 social networks may be protective against acculturative stress arising from chronic communication difficulties. Results from a study of first generation migrant students (N = 100) support this idea by showing that both inclusiveness and density of the participants' L2 network account for unique variance in CRAS but not in general acculturative stress. These results support the idea that research on cross-cultural adaptation would benefit from disentangling the various facets of acculturative stress and that the structure of migrants' L2 network matters for language related outcomes. Finally, this study contributes to an emerging body of work that attempts to integrate cultural/cross-cultural research on acculturation and research on intercultural communication and second language learning.
Ultrastructural networks in growth cones and neurites of cultured central nervous system neurons.

PubMed Central

Tsui, H C; Ris, H; Klein, W L

1983-01-01

We have examined growth cones and neurites of cultured central nervous system neurons by high-voltage electron microscopy. Embryonic chicken retina cells were cultured on polylysine-treated and Formvar-coated gold grids for 2-6 days, fixed, and critical point dried. Growth cones and neurites were examined as unembedded whole mounts. Three-dimensional images from stereo-pair electron micrographs of these regions showed a high degree of ultrastructural articulation, with distinct, non-tapering filaments (5-9 nm in diameter) joining both cytoskeletal and membranous components. In the central regions of growth cones, interconnected structures included microtubules, large membranous sacs (up to 400 nm), and irregular vesicles (25-75 nm). A denser filamentous network was prevalent at the edges of growth cones. This network, which frequently adjoined the surface membrane, linked vesicles of uniform size (35-40 nm). Such vesicles often were seen densely packed in growth cone protrusions that were about the size of small synaptic boutons. Prevalent structural interconnections within growth cones conceivably could play a logistic role in specific membrane assembly, intracellular transport, endocytosis, and secretion. Because such processes are not unique to growth cones, the extensive linkages we have observed may have implications for cytoplasmic structure in general. Images PMID:6577454
Quantum walks of correlated photon pairs in two-dimensional waveguide arrays.

PubMed

Poulios, Konstantinos; Keil, Robert; Fry, Daniel; Meinecke, Jasmin D A; Matthews, Jonathan C F; Politi, Alberto; Lobino, Mirko; Gräfe, Markus; Heinrich, Matthias; Nolte, Stefan; Szameit, Alexander; O'Brien, Jeremy L

2014-04-11

We demonstrate quantum walks of correlated photons in a two-dimensional network of directly laser written waveguides coupled in a "swiss cross" arrangement. The correlated detection events show high-visibility quantum interference and unique composite behavior: strong correlation and independence of the quantum walkers, between and within the planes of the cross. Violations of a classically defined inequality, for photons injected in the same plane and in orthogonal planes, reveal nonclassical behavior in a nonplanar structure.
a Climatology of Synoptic Scale Atmospheric Structure Prior to Severe Convective Storms

NASA Astrophysics Data System (ADS)

Taylor, Gregory Eugene

1982-03-01

This investigation determines those unique properties of the thermodynamic and kinematic structure of the atmosphere in the region where tornado bearing thunderstorms develop as compared to surrounding locations. One hundred five upper air soundings from the operational rawinsonde network, hereafter called tornado proximity soundings, comprise the core of the data base. In each instance, a confirmed tornado occurred within 50 statute miles of and within 105 minutes after the release of the radiosonde. In earlier research of this nature, the thermodynamic and kinematic properties of the atmosphere in the region of tornado bearing thunderstorm development were interpolated or inferred from upper air soundings made at locations surrounding the severe storm location. These surrounding locations, however, were characterized by at most non-tornado bearing thunderstorm development. In this investigation, however, measurements of the atmospheric structure near in space and time to the subsequent tornado bearing thunderstorm development have been utilized. This fact should enhance the probability of detecting the presumably unique properties of the atmospheric structure prior to severe storm development as compared to previous investigations. Height, temperature, mixing ratio, and U and V wind component data from the tornado proximity sounding station and surrounding upper air stations were objectively analyzed to a regularly spaced three dimensional grid network centered on the tornado proximity sounding station. From the basic data, a large number of derived variables which had been previously linked to severe storms were computed. Each case was categorized into one of six different classifications based on the geographical location and date of the tornado proximity sounding. The results from the six categories indicate that the most pronounced unique properties of the pre-severe storm environment are within the lower levels of the atmosphere. In particular, the low level moisture content and the low level V-component tended to maximize near the region of subsequent severe storm development in most of the six categories. Also, a number of variables which are highly dependent upon low level moisture content and/or low level wind data such as horizontal moisture flux and stability indices delineated well the region of subsequent severe storm development.
Visibility graphlet approach to chaotic time series

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

Mutua, Stephen; Computer Science Department, Masinde Muliro University of Science and Technology, P.O. Box 190-50100, Kakamega; Gu, Changgui, E-mail: gu-changgui@163.com, E-mail: hjyang@ustc.edu.cn

Many novel methods have been proposed for mapping time series into complex networks. Although some dynamical behaviors can be effectively captured by existing approaches, the preservation and tracking of the temporal behaviors of a chaotic system remains an open problem. In this work, we extended the visibility graphlet approach to investigate both discrete and continuous chaotic time series. We applied visibility graphlets to capture the reconstructed local states, so that each is treated as a node and tracked downstream to create a temporal chain link. Our empirical findings show that the approach accurately captures the dynamical properties of chaotic systems.more » Networks constructed from periodic dynamic phases all converge to regular networks and to unique network structures for each model in the chaotic zones. Furthermore, our results show that the characterization of chaotic and non-chaotic zones in the Lorenz system corresponds to the maximal Lyapunov exponent, thus providing a simple and straightforward way to analyze chaotic systems.« less
Long term potentiation, but not depression, in interlamellar hippocampus CA1.

PubMed

Sun, Duk-Gyu; Kang, Hyeri; Tetteh, Hannah; Su, Junfeng; Lee, Jihwan; Park, Sung-Won; He, Jufang; Jo, Jihoon; Yang, Sungchil; Yang, Sunggu

2018-03-26

Synaptic plasticity in the lamellar CA3 to CA1 circuitry has been extensively studied while interlamellar CA1 to CA1 connections have not yet received much attention. One of our earlier studies demonstrated that axons of CA1 pyramidal neurons project to neighboring CA1 neurons, implicating information transfer along a longitudinal interlamellar network. Still, it remains unclear whether long-term synaptic plasticity is present within this longitudinal CA1 network. Here, we investigate long-term synaptic plasticity between CA1 pyramidal cells, using in vitro and in vivo extracellular recordings and 3D holography glutamate uncaging. We found that the CA1-CA1 network exhibits NMDA receptor-dependent long-term potentiation (LTP) without direction or layer selectivity. By contrast, we find no significant long-term depression (LTD) under various LTD induction protocols. These results implicate unique synaptic properties in the longitudinal projection suggesting that the interlamellar CA1 network could be a promising structure for hippocampus-related information processing and brain diseases.
Atomic switch networks-nanoarchitectonic design of a complex system for natural computing.

PubMed

Demis, E C; Aguilera, R; Sillin, H O; Scharnhorst, K; Sandouk, E J; Aono, M; Stieg, A Z; Gimzewski, J K

2015-05-22

Self-organized complex systems are ubiquitous in nature, and the structural complexity of these natural systems can be used as a model to design new classes of functional nanotechnology based on highly interconnected networks of interacting units. Conventional fabrication methods for electronic computing devices are subject to known scaling limits, confining the diversity of possible architectures. This work explores methods of fabricating a self-organized complex device known as an atomic switch network and discusses its potential utility in computing. Through a merger of top-down and bottom-up techniques guided by mathematical and nanoarchitectonic design principles, we have produced functional devices comprising nanoscale elements whose intrinsic nonlinear dynamics and memorization capabilities produce robust patterns of distributed activity and a capacity for nonlinear transformation of input signals when configured in the appropriate network architecture. Their operational characteristics represent a unique potential for hardware implementation of natural computation, specifically in the area of reservoir computing-a burgeoning field that investigates the computational aptitude of complex biologically inspired systems.
Design of chemical space networks on the basis of Tversky similarity

NASA Astrophysics Data System (ADS)

Wu, Mengjun; Vogt, Martin; Maggiora, Gerald M.; Bajorath, Jürgen

2016-01-01

Chemical space networks (CSNs) have been introduced as a coordinate-free representation of chemical space. In CSNs, nodes represent compounds and edges pairwise similarity relationships. These network representations are mostly used to navigate sections of biologically relevant chemical space. Different types of CSNs have been designed on the basis of alternative similarity measures including continuous numerical similarity values or substructure-based similarity criteria. CSNs can be characterized and compared on the basis of statistical concepts from network science. Herein, a new CSN design is introduced that is based upon asymmetric similarity assessment using the Tversky coefficient and termed TV-CSN. Compared to other CSNs, TV-CSNs have unique features. While CSNs typically contain separate compound communities and exhibit small world character, many TV-CSNs are also scale-free in nature and contain hubs, i.e., extensively connected central compounds. Compared to other CSNs, these hubs are a characteristic of TV-CSN topology. Hub-containing compound communities are of particular interest for the exploration of structure-activity relationships.

Biomarker MicroRNAs for Diagnosis of Oral Squamous Cell Carcinoma Identified Based on Gene Expression Data and MicroRNA-mRNA Network Analysis

PubMed Central

Zhang, Hui; Li, Tangxin; Zheng, Linqing

2017-01-01

Oral squamous cell carcinoma is one of the most malignant tumors with high mortality rate worldwide. Biomarker discovery is critical for early diagnosis and precision treatment of this disease. MicroRNAs are small noncoding RNA molecules which often regulate essential biological processes and are good candidates for biomarkers. By integrative analysis of both the cancer-associated gene expression data and microRNA-mRNA network, miR-148b-3p, miR-629-3p, miR-27a-3p, and miR-142-3p were screened as novel diagnostic biomarkers for oral squamous cell carcinoma based on their unique regulatory abilities in the network structure of the conditional microRNA-mRNA network and their important functions. These findings were confirmed by literature verification and functional enrichment analysis. Future experimental validation is expected for the further investigation of their molecular mechanisms. PMID:29098014
Evolution of a modular software network

PubMed Central

Fortuna, Miguel A.; Bonachela, Juan A.; Levin, Simon A.

2011-01-01

“Evolution behaves like a tinkerer” (François Jacob, Science, 1977). Software systems provide a singular opportunity to understand biological processes using concepts from network theory. The Debian GNU/Linux operating system allows us to explore the evolution of a complex network in a unique way. The modular design detected during its growth is based on the reuse of existing code in order to minimize costs during programming. The increase of modularity experienced by the system over time has not counterbalanced the increase in incompatibilities between software packages within modules. This negative effect is far from being a failure of design. A random process of package installation shows that the higher the modularity, the larger the fraction of packages working properly in a local computer. The decrease in the relative number of conflicts between packages from different modules avoids a failure in the functionality of one package spreading throughout the entire system. Some potential analogies with the evolutionary and ecological processes determining the structure of ecological networks of interacting species are discussed. PMID:22106260
Inequalities in Global Trade: A Cross-Country Comparison of Trade Network Position, Economic Wealth, Pollution and Mortality

PubMed Central

Prell, Christina; Sun, Laixiang; Feng, Kuishuang; Myroniuk, Tyler W.

2015-01-01

In this paper we investigate how structural patterns of international trade give rise to emissions inequalities across countries, and how such inequality in turn impact countries’ mortality rates. We employ Multi-regional Input-Output analysis to distinguish between sulfur-dioxide (SO2) emissions produced within a country’s boarders (production-based emissions) and emissions triggered by consumption in other countries (consumption-based emissions). We use social network analysis to capture countries’ level of integration within the global trade network. We then apply the Prais-Winsten panel estimation technique to a panel data set across 172 countries over 20 years (1990–2010) to estimate the relationships between countries’ level of integration and SO2 emissions, and the impact of trade integration and SO2 emission on mortality rates. Our findings suggest a positive, (log-) linear relationship between a country’s level of integration and both kinds of emissions. In addition, although more integrated countries are mainly responsible for both forms of emissions, our findings indicate that they also tend to experience lower mortality rates. Our approach offers a unique combination of social network analysis with multiregional input-output analysis, which better operationalizes intuitive concepts about global trade and trade structure. PMID:26642202
Family ties: the multilevel effects of households and kinship on the networks of individuals.

PubMed

Koster, Jeremy

2018-04-01

Among social mammals, humans uniquely organize themselves into communities of households that are centred around enduring, predominantly monogamous unions of men and women. As a consequence of this social organization, individuals maintain social relationships both within and across households, and potentially there is conflict among household members about which social ties to prioritize or de-emphasize. Extending the logic of structural balance theory, I predict that there will be considerable overlap in the social networks of individual household members, resulting in a pattern of group-level reciprocity. To test this prediction, I advance the Group-Structured Social Relations Model, a generalized linear mixed model that tests for group-level effects in the inter-household social networks of individuals. The empirical data stem from social support interviews conducted in a community of indigenous Nicaraguan horticulturalists, and model results show high group-level reciprocity among households. Although support networks are organized around kinship, covariates that test predictions of kin selection models do not receive strong support, potentially because most kin-directed altruism occurs within households, not between households. In addition, the models show that households with high genetic relatedness in part from children born to adulterous relationships are less likely to assist each other.
Direct electrical stimulation as an input gate into brain functional networks: principles, advantages and limitations.

PubMed

Mandonnet, Emmanuel; Winkler, Peter A; Duffau, Hugues

2010-02-01

While the fundamental and clinical contribution of direct electrical stimulation (DES) of the brain is now well acknowledged, its advantages and limitations have not been re-evaluated for a long time. Here, we critically review exactly what DES can tell us about cerebral function. First, we show that DES is highly sensitive for detecting the cortical and axonal eloquent structures. Moreover, DES also provides a unique opportunity to study brain connectivity, since each area responsive to stimulation is in fact an input gate into a large-scale network rather than an isolated discrete functional site. DES, however, also has a limitation: its specificity is suboptimal. Indeed, DES may lead to interpretations that a structure is crucial because of the induction of a transient functional response when stimulated, whereas (1) this effect is caused by the backward spreading of the electro-stimulation along the network to an essential area and/or (2) the stimulated region can be functionally compensated owing to long-term brain plasticity mechanisms. In brief, although DES is still the gold standard for brain mapping, its combination with new methods such as perioperative neurofunctional imaging and biomathematical modeling is now mandatory, in order to clearly differentiate those networks that are actually indispensable to function from those that can be compensated.
Structural insights into the human RyR2 N-terminal region involved in cardiac arrhythmias

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

Borko, Ľubomír; Bauerová-Hlinková, Vladena, E-mail: vladena.bauerova@savba.sk; Hostinová, Eva

2014-11-01

X-ray and solution structures of the human RyR2 N-terminal region were obtained under near-physiological conditions. The structure exhibits a unique network of interactions between its three domains, revealing an important stabilizing role of the central helix. Human ryanodine receptor 2 (hRyR2) mediates calcium release from the sarcoplasmic reticulum, enabling cardiomyocyte contraction. The N-terminal region of hRyR2 (amino acids 1–606) is the target of >30 arrhythmogenic mutations and contains a binding site for phosphoprotein phosphatase 1. Here, the solution and crystal structures determined under near-physiological conditions, as well as a homology model of the hRyR2 N-terminal region, are presented. The N-terminusmore » is held together by a unique network of interactions among its three domains, A, B and C, in which the central helix (amino acids 410–437) plays a prominent stabilizing role. Importantly, the anion-binding site reported for the mouse RyR2 N-terminal region is notably absent from the human RyR2. The structure concurs with the differential stability of arrhythmogenic mutations in the central helix (R420W, I419F and I419F/R420W) which are owing to disparities in the propensity of mutated residues to form energetically favourable or unfavourable contacts. In solution, the N-terminus adopts a globular shape with a prominent tail that is likely to involve residues 545–606, which are unresolved in the crystal structure. Docking the N-terminal domains into cryo-electron microscopy maps of the closed and open RyR1 conformations reveals C{sup α} atom movements of up to 8 Å upon channel gating, and predicts the location of the leucine–isoleucine zipper segment and the interaction site for spinophilin and phosphoprotein phosphatase 1 on the RyR surface.« less
Interpersonal Influence Among Public Health Leaders in the United States Department of Health and Human Services

PubMed Central

Harris, Jenine K.; Carothers, Bobbi J.; Wald, Lana M.; Shelton, Sarah C.; Leischow, Scott J.

2012-01-01

Background In public health, interpersonal influence has been identified as an important factor in the spread of health information, and in understanding and changing health behaviors. However, little is known about influence in public health leadership. Influence is important in leadership settings, where public health professionals contribute to national policy and practice agendas. Drawing on social theory and recent advances in statistical network modeling, we examined influence in a network of tobacco control leaders at the United States Department of Health and Human Services (DHHS). Design and Methods Fifty-four tobacco control leaders across all 11 agencies in the DHHS were identified; 49 (91%) responded to a web-based survey. Participants were asked about communication with other tobacco control leaders, who influenced their work, and general job characteristics. Exponential random graph modeling was used to develop a network model of influence accounting for characteristics of individuals, their relationships, and global network structures. Results Higher job ranks, more experience in tobacco control, and more time devoted to tobacco control each week increased the likelihood of influence nomination, as did more frequent communication between network members. Being in the same agency and working the same number of hours per week were positively associated with mutual influence nominations. Controlling for these characteristics, the network also exhibited patterns associated with influential clusters of network members. Conclusions Findings from this unique study provide a perspective on influence within a government agency that both helps to understand decision-making and also can serve to inform organizational efforts that allow for more effective structuring of leadership. PMID:25170448
Interpersonal influence among public health leaders in the United States department of health and human services.

PubMed

Harris, Jenine K; Carothers, Bobbi J; Wald, Lana M; Shelton, Sarah C; Leischow, Scott J

2012-02-17

In public health, interpersonal influence has been identified as an important factor in the spread of health information, and in understanding and changing health behaviors. However, little is known about influence in public health leadership. Influence is important in leadership settings, where public health professionals contribute to national policy and practice agendas. Drawing on social theory and recent advances in statistical network modeling, we examined influence in a network of tobacco control leaders at the United States Department of Health and Human Services (DHHS). Fifty-four tobacco control leaders across all 11 agencies in the DHHS were identified; 49 (91%) responded to a web-based survey. Participants were asked about communication with other tobacco control leaders, who influenced their work, and general job characteristics. Exponential random graph modeling was used to develop a network model of influence accounting for characteristics of individuals, their relationships, and global network structures. Higher job ranks, more experience in tobacco control, and more time devoted to tobacco control each week increased the likelihood of influence nomination, as did more frequent communication between network members. Being in the same agency and working the same number of hours per week were positively associated with mutual influence nominations. Controlling for these characteristics, the network also exhibited patterns associated with influential clusters of network members. Findings from this unique study provide a perspective on influence within a government agency that both helps to understand decision-making and also can serve to inform organizational efforts that allow for more effective structuring of leadership.
Evolutionary Dynamics on Protein Bi-stability Landscapes can Potentially Resolve Adaptive Conflicts

PubMed Central

Sikosek, Tobias; Bornberg-Bauer, Erich; Chan, Hue Sun

2012-01-01

Experimental studies have shown that some proteins exist in two alternative native-state conformations. It has been proposed that such bi-stable proteins can potentially function as evolutionary bridges at the interface between two neutral networks of protein sequences that fold uniquely into the two different native conformations. Under adaptive conflict scenarios, bi-stable proteins may be of particular advantage if they simultaneously provide two beneficial biological functions. However, computational models that simulate protein structure evolution do not yet recognize the importance of bi-stability. Here we use a biophysical model to analyze sequence space to identify bi-stable or multi-stable proteins with two or more equally stable native-state structures. The inclusion of such proteins enhances phenotype connectivity between neutral networks in sequence space. Consideration of the sequence space neighborhood of bridge proteins revealed that bi-stability decreases gradually with each mutation that takes the sequence further away from an exactly bi-stable protein. With relaxed selection pressures, we found that bi-stable proteins in our model are highly successful under simulated adaptive conflict. Inspired by these model predictions, we developed a method to identify real proteins in the PDB with bridge-like properties, and have verified a clear bi-stability gradient for a series of mutants studied by Alexander et al. (Proc Nat Acad Sci USA 2009, 106:21149–21154) that connect two sequences that fold uniquely into two different native structures via a bridge-like intermediate mutant sequence. Based on these findings, new testable predictions for future studies on protein bi-stability and evolution are discussed. PMID:23028272
Quality assurance of chemical ingredient classification for the National Drug File - Reference Terminology.

PubMed

Zheng, Ling; Yumak, Hasan; Chen, Ling; Ochs, Christopher; Geller, James; Kapusnik-Uner, Joan; Perl, Yehoshua

2017-09-01

The National Drug File - Reference Terminology (NDF-RT) is a large and complex drug terminology consisting of several classification hierarchies on top of an extensive collection of drug concepts. These hierarchies provide important information about clinical drugs, e.g., their chemical ingredients, mechanisms of action, dosage form and physiological effects. Within NDF-RT such information is represented using tens of thousands of roles connecting drugs to classifications. In previous studies, we have introduced various kinds of Abstraction Networks to summarize the content and structure of terminologies in order to facilitate their visual comprehension, and support quality assurance of terminologies. However, these previous kinds of Abstraction Networks are not appropriate for summarizing the NDF-RT classification hierarchies, due to its unique structure. In this paper, we present the novel Ingredient Abstraction Network (IAbN) to summarize, visualize and support the audit of NDF-RT's Chemical Ingredients hierarchy and its associated drugs. A common theme in our quality assurance framework is to use characterizations of sets of concepts, revealed by the Abstraction Network structure, to capture concepts, the modeling of which is more complex than for other concepts. For the IAbN, we characterize drug ingredient concepts as more complex if they belong to IAbN groups with multiple parent groups. We show that such concepts have a statistically significantly higher rate of errors than a control sample and identify two especially common patterns of errors. Copyright © 2017 Elsevier Inc. All rights reserved.
Newberry EGS Seismic Velocity Model

DOE Data Explorer

Templeton, Dennise

2013-10-01

We use ambient noise correlation (ANC) to create a detailed image of the subsurface seismic velocity at the Newberry EGS site down to 5 km. We collected continuous data for the 22 stations in the Newberry network, together with 12 additional stations from the nearby CC, UO and UW networks. The data were instrument corrected, whitened and converted to single bit traces before cross correlation according to the methodology in Benson (2007). There are 231 unique paths connecting the 22 stations of the Newberry network. The additional networks extended that to 402 unique paths crossing beneath the Newberry site.
The q-dependent detrended cross-correlation analysis of stock market

NASA Astrophysics Data System (ADS)

Zhao, Longfeng; Li, Wei; Fenu, Andrea; Podobnik, Boris; Wang, Yougui; Stanley, H. Eugene

2018-02-01

Properties of the q-dependent cross-correlation matrices of the stock market have been analyzed by using random matrix theory and complex networks. The correlation structures of the fluctuations at different magnitudes have unique properties. The cross-correlations among small fluctuations are much stronger than those among large fluctuations. The large and small fluctuations are dominated by different groups of stocks. We use complex network representation to study these q-dependent matrices and discover some new identities. By utilizing those q-dependent correlation-based networks, we are able to construct some portfolios of those more independent stocks which consistently perform better. The optimal multifractal order for portfolio optimization is around q = 2 under the mean-variance portfolio framework, and q\\in[2, 6] under the expected shortfall criterion. These results have deepened our understanding regarding the collective behavior of the complex financial system.
Hydro-geomorphological characterization and classification of Chilean river networks using horizontal, vertical and climatological properties

NASA Astrophysics Data System (ADS)

Pereira, A. A.; Gironas, J. A.; Passalacqua, P.; Mejia, A.; Niemann, J. D.

2017-12-01

Previous work has shown that lithological, tectonic and climatic processes have a major influence in shaping the geomorphology of river networks. Accordingly, quantitative classification methods have been developed to identify and characterize network types (dendritic, parallel, pinnate, rectangular and trellis) based solely on the self-affinity of their planform properties, computed from available Digital Elevation Model (DEM) data. In contrast, this research aim is to include both horizontal and vertical properties to evaluate a quantitative classification method for river networks. We include vertical properties to consider the unique surficial conditions (e.g., large and steep height drops, volcanic activity, and complexity of stream networks) of the Andes Mountains. Furthermore, the goal of the research is also to explain the implications and possible relations between the hydro-geomorphological properties and climatic conditions. The classification method is applied to 42 basins in the southern Andes in Chile, ranging in size from 208 Km2 to 8,000 Km2. The planform metrics include the incremental drainage area, stream course irregularity and junction angles, while the vertical metrics include the hypsometric curve and the slope-area relationship. We introduce new network structures (Brush, Funnel and Low Sinuosity Rectangular), possibly unique to the Andes, that can be quantitatively differentiated from previous networks identified in other geographic regions. Then, this research evaluates the effect that excluding different Strahler order streams has on the horizontal properties and therefore in the classification. We found that climatic conditions are not only linked to horizontal parameters, but also to vertical ones, finding significant correlation between climatic variables (average near-surface temperature and rainfall) and vertical measures (parameters associated with the hypsometric curve and slope-area relation). The proposed classification shows differences among basins previously classified as the same type, which are not noticeable in their horizontal properties and helps reduce misclassifications within the old clusters. Additional hydro-geomorphological metrics are to be considered in the classification method to improve the effectiveness of it.
Social networks and well-being: a comparison of older people in Mediterranean and non-Mediterranean countries.

PubMed

Litwin, Howard

2010-09-01

This study examined whether the social networks of older persons in Mediterranean and non-Mediterranean countries were appreciably different and whether they functioned in similar ways in relation to well-being outcomes. The sample included family household respondents aged 60 years and older from the first wave of the Survey of Health, Ageing and Retirement in Europe in 5 Mediterranean (n = 3,583) and 7 non-Mediterranean (n = 5,471) countries. Region was regressed separately by gender on variables from 4 network domains: structure and interaction, exchange, engagement and relationship quality, and controlling for background and health characteristics. In addition, 2 well-being outcomes-depressive symptoms and perceived income inadequacy-were regressed on the study variables, including regional social network interaction terms. The results revealed differences across the 2 regional settings in each of the realms of social network, above and beyond the differences that exist in background characteristics and health status. The findings also showed that the social network variables had different effects on the well-being outcomes in the respective settings. The findings underscore that the social network phenomenon is contextually bound. The social networks of older people should be seen within their unique regional milieu and in relation to the values and social norms that prevail in different sets of societies.
Dragon pulse information management system (DPIMS): A unique model-based approach to implementing domain agnostic system of systems and behaviors

NASA Astrophysics Data System (ADS)

Anderson, Thomas S.

2016-05-01

The Global Information Network Architecture is an information technology based on Vector Relational Data Modeling, a unique computational paradigm, DoD network certified by USARMY as the Dragon Pulse Informa- tion Management System. This network available modeling environment for modeling models, where models are configured using domain relevant semantics and use network available systems, sensors, databases and services as loosely coupled component objects and are executable applications. Solutions are based on mission tactics, techniques, and procedures and subject matter input. Three recent ARMY use cases are discussed a) ISR SoS. b) Modeling and simulation behavior validation. c) Networked digital library with behaviors.
A Hybrid CPU-GPU Accelerated Framework for Fast Mapping of High-Resolution Human Brain Connectome

PubMed Central

Ren, Ling; Xu, Mo; Xie, Teng; Gong, Gaolang; Xu, Ningyi; Yang, Huazhong; He, Yong

2013-01-01

Recently, a combination of non-invasive neuroimaging techniques and graph theoretical approaches has provided a unique opportunity for understanding the patterns of the structural and functional connectivity of the human brain (referred to as the human brain connectome). Currently, there is a very large amount of brain imaging data that have been collected, and there are very high requirements for the computational capabilities that are used in high-resolution connectome research. In this paper, we propose a hybrid CPU-GPU framework to accelerate the computation of the human brain connectome. We applied this framework to a publicly available resting-state functional MRI dataset from 197 participants. For each subject, we first computed Pearson’s Correlation coefficient between any pairs of the time series of gray-matter voxels, and then we constructed unweighted undirected brain networks with 58 k nodes and a sparsity range from 0.02% to 0.17%. Next, graphic properties of the functional brain networks were quantified, analyzed and compared with those of 15 corresponding random networks. With our proposed accelerating framework, the above process for each network cost 80∼150 minutes, depending on the network sparsity. Further analyses revealed that high-resolution functional brain networks have efficient small-world properties, significant modular structure, a power law degree distribution and highly connected nodes in the medial frontal and parietal cortical regions. These results are largely compatible with previous human brain network studies. Taken together, our proposed framework can substantially enhance the applicability and efficacy of high-resolution (voxel-based) brain network analysis, and have the potential to accelerate the mapping of the human brain connectome in normal and disease states. PMID:23675425
Novel high-strength biocomposites based on microfibrillated cellulose having nano-order-unit web-like network structure

NASA Astrophysics Data System (ADS)

Nakagaito, A. N.; Yano, H.

2005-01-01

A completely new kind of high-strength composite was manufactured using microfibrillated cellulose (MFC) derived from kraft pulp. Because of the unique structure of nano-order-scale interconnected fibrils and microfibrils greatly expanded in the surface area that characterizes MFC, it was possible to produce composites that exploit the extremely high strength of microfibrils. The Young’s modulus (E) and bending strength (σb) of composites using phenolic resin as binder achieved values up to 19 GPa and 370 MPa, respectively, with a density of 1.45 g/cm2, exhibiting outstanding mechanical properties for a plant-fiber-based composite.
Flows in a tube structure: Equation on the graph

NASA Astrophysics Data System (ADS)

Panasenko, Grigory; Pileckas, Konstantin

2014-08-01

The steady-state Navier-Stokes equations in thin structures lead to some elliptic second order equation for the macroscopic pressure on a graph. At the nodes of the graph the pressure satisfies Kirchoff-type junction conditions. In the non-steady case the problem for the macroscopic pressure on the graph becomes nonlocal in time. In the paper we study the existence and uniqueness of a solution to such one-dimensional model on the graph for a pipe-wise network. We also prove the exponential decay of the solution with respect to the time variable in the case when the data decay exponentially with respect to time.
Sex differences in the structural connectome of the human brain.

PubMed

Ingalhalikar, Madhura; Smith, Alex; Parker, Drew; Satterthwaite, Theodore D; Elliott, Mark A; Ruparel, Kosha; Hakonarson, Hakon; Gur, Raquel E; Gur, Ruben C; Verma, Ragini

2014-01-14

Sex differences in human behavior show adaptive complementarity: Males have better motor and spatial abilities, whereas females have superior memory and social cognition skills. Studies also show sex differences in human brains but do not explain this complementarity. In this work, we modeled the structural connectome using diffusion tensor imaging in a sample of 949 youths (aged 8-22 y, 428 males and 521 females) and discovered unique sex differences in brain connectivity during the course of development. Connection-wise statistical analysis, as well as analysis of regional and global network measures, presented a comprehensive description of network characteristics. In all supratentorial regions, males had greater within-hemispheric connectivity, as well as enhanced modularity and transitivity, whereas between-hemispheric connectivity and cross-module participation predominated in females. However, this effect was reversed in the cerebellar connections. Analysis of these changes developmentally demonstrated differences in trajectory between males and females mainly in adolescence and in adulthood. Overall, the results suggest that male brains are structured to facilitate connectivity between perception and coordinated action, whereas female brains are designed to facilitate communication between analytical and intuitive processing modes.
A template for constructing Bayesian networks in forensic biology cases when considering activity level propositions.

PubMed

Taylor, Duncan; Biedermann, Alex; Hicks, Tacha; Champod, Christophe

2018-03-01

The hierarchy of propositions has been accepted amongst the forensic science community for some time. It is also accepted that the higher up the hierarchy the propositions are, against which the scientist are competent to evaluate their results, the more directly useful the testimony will be to the court. Because each case represents a unique set of circumstances and findings, it is difficult to come up with a standard structure for evaluation. One common tool that assists in this task is Bayesian networks (BNs). There is much diversity in the way that BN can be constructed. In this work, we develop a template for BN construction that allows sufficient flexibility to address most cases, but enough commonality and structure that the flow of information in the BN is readily recognised at a glance. We provide seven steps that can be used to construct BNs within this structure and demonstrate how they can be applied, using a case example. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Superhard BC 3 in cubic diamond structure

DOE PAGES

Zhang, Miao; Liu, Hanyu; Li, Quan; ...

2015-01-06

We solve the crystal structure of recently synthesized cubic BC 3 using an unbiased swarm structure search, which identifies a highly symmetric BC 3 phase in the cubic diamond structure (d–BC3) that contains a distinct B-B bonding network along the body diagonals of a large 64-atom unit cell. Simulated x-ray diffraction and Raman peaks of d–BC 3 are in excellent agreement with experimental data. Calculated stress-strain relations of d–BC 3 demonstrate its intrinsic superhard nature and reveal intriguing sequential bond-breaking modes that produce superior ductility and extended elasticity, which are unique among superhard solids. Here, the present results establish themore » first boron carbide in the cubic diamond structure with remarkable properties, and these new findings also provide insights for exploring other covalent solids with complex bonding configurations.« less
Systems Engineering Design Via Experimental Operation Research: Complex Organizational Metric for Programmatic Risk Environments (COMPRE)

NASA Technical Reports Server (NTRS)

Mog, Robert A.

1999-01-01

Unique and innovative graph theory, neural network, organizational modeling, and genetic algorithms are applied to the design and evolution of programmatic and organizational architectures. Graph theory representations of programs and organizations increase modeling capabilities and flexibility, while illuminating preferable programmatic/organizational design features. Treating programs and organizations as neural networks results in better system synthesis, and more robust data modeling. Organizational modeling using covariance structures enhances the determination of organizational risk factors. Genetic algorithms improve programmatic evolution characteristics, while shedding light on rulebase requirements for achieving specified technological readiness levels, given budget and schedule resources. This program of research improves the robustness and verifiability of systems synthesis tools, including the Complex Organizational Metric for Programmatic Risk Environments (COMPRE).
All in the Family: The Link between Kin Network Bridging and Cardiovascular Risk among Older Adults*

PubMed Central

Goldman, Alyssa

2016-01-01

While considerable work has examined the association between social relationships and health, most of this research focuses on the relevance of social network composition and quality of dyadic ties. In this study, I consider how the social network structure of ties among older adults’ close family members may affect cardiovascular health in later life. Using data from 938 older adults that participated in Waves 1 and 2 of the National Social Life, Health, and Aging Project (NSHAP), I test whether older adults who occupy bridging positions among otherwise disconnected or poorly connected kin in their personal social network are more likely to present elevated levels of C-reactive protein (CRP), a biomarker for cardiovascular risk. Results indicate that occupying a bridging position among family members is significantly associated with elevated CRP. This effect is unique to bridging kin network members. These findings suggest that ties among one’s closest kin may generate important resources and norms that influence older adults’ health, such that bridging kin network members may compromise physical wellbeing. I discuss these results in the context of prior work on social support, family solidarity, and health in later life. PMID:27566043
All in the family: The link between kin network bridging and cardiovascular risk among older adults.

PubMed

Goldman, Alyssa W

2016-10-01

While considerable work has examined the association between social relationships and health, most of this research focuses on the relevance of social network composition and the quality of dyadic ties. In this study, I consider how the social network structure of ties among older adults' close family members may affect cardiovascular health in later life. Using data from 938 older adults that participated in Waves 1 and 2 of the National Social Life, Health, and Aging Project (NSHAP), I test whether older adults who occupy bridging positions among otherwise disconnected or poorly connected kin in their personal social network are more likely to present elevated levels of C-reactive protein (CRP), a biomarker for cardiovascular risk. Results indicate that occupying a bridging position among family members is significantly associated with elevated CRP. This effect is unique to bridging kin network members. These findings suggest that ties among one's closest kin may generate important resources and norms that influence older adults' health, such that bridging kin network members may compromise physical wellbeing. I discuss these results in the context of prior work on social support, family solidarity, and health in later life. Copyright © 2016 Elsevier Ltd. All rights reserved.
Distributed Dynamic Host Configuration Protocol (D2HCP)

PubMed Central

Villalba, Luis Javier García; Matesanz, Julián García; Orozco, Ana Lucila Sandoval; Díaz, José Duván Márquez

2011-01-01

Mobile Ad Hoc Networks (MANETs) are multihop wireless networks of mobile nodes without any fixed or preexisting infrastructure. The topology of these networks can change randomly due to the unpredictable mobility of nodes and their propagation characteristics. In most networks, including MANETs, each node needs a unique identifier to communicate. This work presents a distributed protocol for dynamic node IP address assignment in MANETs. Nodes of a MANET synchronize from time to time to maintain a record of IP address assignments in the entire network and detect any IP address leaks. The proposed stateful autoconfiguration scheme uses the OLSR proactive routing protocol for synchronization and guarantees unique IP addresses under a variety of network conditions, including message losses and network partitioning. Simulation results show that the protocol incurs low latency and communication overhead for IP address assignment. PMID:22163856
Distributed Dynamic Host Configuration Protocol (D2HCP).

PubMed

Villalba, Luis Javier García; Matesanz, Julián García; Orozco, Ana Lucila Sandoval; Díaz, José Duván Márquez

2011-01-01

Mobile Ad Hoc Networks (MANETs) are multihop wireless networks of mobile nodes without any fixed or preexisting infrastructure. The topology of these networks can change randomly due to the unpredictable mobility of nodes and their propagation characteristics. In most networks, including MANETs, each node needs a unique identifier to communicate. This work presents a distributed protocol for dynamic node IP address assignment in MANETs. Nodes of a MANET synchronize from time to time to maintain a record of IP address assignments in the entire network and detect any IP address leaks. The proposed stateful autoconfiguration scheme uses the OLSR proactive routing protocol for synchronization and guarantees unique IP addresses under a variety of network conditions, including message losses and network partitioning. Simulation results show that the protocol incurs low latency and communication overhead for IP address assignment.
Building and measuring a high performance network architecture

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

Kramer, William T.C.; Toole, Timothy; Fisher, Chuck

2001-04-20

Once a year, the SC conferences present a unique opportunity to create and build one of the most complex and highest performance networks in the world. At SC2000, large-scale and complex local and wide area networking connections were demonstrated, including large-scale distributed applications running on different architectures. This project was designed to use the unique opportunity presented at SC2000 to create a testbed network environment and then use that network to demonstrate and evaluate high performance computational and communication applications. This testbed was designed to incorporate many interoperable systems and services and was designed for measurement from the very beginning.more » The end results were key insights into how to use novel, high performance networking technologies and to accumulate measurements that will give insights into the networks of the future.« less
Construction of a polyhedron decorated MOF with a unique network through the combination of two classic secondary building units.

PubMed

Ren, Guo-Jian; Chang, Ze; Xu, Jian; Hu, Zhenpeng; Liu, Yan-Qing; Xu, Yue-Ling; Bu, Xian-He

2016-02-04

A novel decorated metal-organic polyhedron (MOP) based metal-organic framework with a unique 4,9-connected network is successfully constructed, which displays a relatively strong interaction toward H2 and CO2 probably due to the existence of open metal sites in the secondary building units.
Toward Rigorous Parameterization of Underconstrained Neural Network Models Through Interactive Visualization and Steering of Connectivity Generation

PubMed Central

Nowke, Christian; Diaz-Pier, Sandra; Weyers, Benjamin; Hentschel, Bernd; Morrison, Abigail; Kuhlen, Torsten W.; Peyser, Alexander

2018-01-01

Simulation models in many scientific fields can have non-unique solutions or unique solutions which can be difficult to find. Moreover, in evolving systems, unique final state solutions can be reached by multiple different trajectories. Neuroscience is no exception. Often, neural network models are subject to parameter fitting to obtain desirable output comparable to experimental data. Parameter fitting without sufficient constraints and a systematic exploration of the possible solution space can lead to conclusions valid only around local minima or around non-minima. To address this issue, we have developed an interactive tool for visualizing and steering parameters in neural network simulation models. In this work, we focus particularly on connectivity generation, since finding suitable connectivity configurations for neural network models constitutes a complex parameter search scenario. The development of the tool has been guided by several use cases—the tool allows researchers to steer the parameters of the connectivity generation during the simulation, thus quickly growing networks composed of multiple populations with a targeted mean activity. The flexibility of the software allows scientists to explore other connectivity and neuron variables apart from the ones presented as use cases. With this tool, we enable an interactive exploration of parameter spaces and a better understanding of neural network models and grapple with the crucial problem of non-unique network solutions and trajectories. In addition, we observe a reduction in turn around times for the assessment of these models, due to interactive visualization while the simulation is computed. PMID:29937723
Interfacing Neural Network Components and Nucleic Acids

PubMed Central

Lissek, Thomas

2017-01-01

Translating neural activity into nucleic acid modifications in a controlled manner harbors unique advantages for basic neurobiology and bioengineering. It would allow for a new generation of biological computers that store output in ultra-compact and long-lived DNA and enable the investigation of animal nervous systems at unprecedented scales. Furthermore, by exploiting the ability of DNA to precisely influence neuronal activity and structure, it could be possible to more effectively create cellular therapy approaches for psychiatric diseases that are currently difficult to treat. PMID:29255707
Ordered water structure at hydrophobic graphite interfaces observed by 4D, ultrafast electron crystallography

PubMed Central

Yang, Ding-Shyue; Zewail, Ahmed H.

2009-01-01

Interfacial water has unique properties in various functions. Here, using 4-dimensional (4D), ultrafast electron crystallography with atomic-scale spatial and temporal resolution, we report study of structure and dynamics of interfacial water assembly on a hydrophobic surface. Structurally, vertically stacked bilayers on highly oriented pyrolytic graphite surface were determined to be ordered, contrary to the expectation that the strong hydrogen bonding of water on hydrophobic surfaces would dominate with suppressed interfacial order. Because of its terrace morphology, graphite plays the role of a template. The dynamics is also surprising. After the excitation of graphite by an ultrafast infrared pulse, the interfacial ice structure undergoes nonequilibrium “phase transformation” identified in the hydrogen-bond network through the observation of structural isosbestic point. We provide the time scales involved, the nature of ice-graphite structural dynamics, and relevance to properties related to confined water. PMID:19246378
Uncovering Offshore Financial Centers: Conduits and Sinks in the Global Corporate Ownership Network.

PubMed

Garcia-Bernardo, Javier; Fichtner, Jan; Takes, Frank W; Heemskerk, Eelke M

2017-07-24

Multinational corporations use highly complex structures of parents and subsidiaries to organize their operations and ownership. Offshore Financial Centers (OFCs) facilitate these structures through low taxation and lenient regulation, but are increasingly under scrutiny, for instance for enabling tax avoidance. Therefore, the identification of OFC jurisdictions has become a politicized and contested issue. We introduce a novel data-driven approach for identifying OFCs based on the global corporate ownership network, in which over 98 million firms (nodes) are connected through 71 million ownership relations. This granular firm-level network data uniquely allows identifying both sink-OFCs and conduit-OFCs. Sink-OFCs attract and retain foreign capital while conduit-OFCs are attractive intermediate destinations in the routing of international investments and enable the transfer of capital without taxation. We identify 24 sink-OFCs. In addition, a small set of five countries - the Netherlands, the United Kingdom, Ireland, Singapore and Switzerland - canalize the majority of corporate offshore investment as conduit-OFCs. Each conduit jurisdiction is specialized in a geographical area and there is significant specialization based on industrial sectors. Against the idea of OFCs as exotic small islands that cannot be regulated, we show that many sink and conduit-OFCs are highly developed countries.
Radio frequency switching network: a technique for infrared sensing

NASA Astrophysics Data System (ADS)

Mechtel, Deborah M.; Jenkins, R. Brian; Joyce, Peter J.; Nelson, Charles L.

2016-10-01

This paper describes a unique technique that implements photoconductive sensors in a radio frequency (RF) switching network designed to locate in real-time the position and intensity of IR radiation incident on a composite structure. In the implementation described here, photoconductive sensors act as rapid response switches in a two-layer RF network embedded in an FR-4 laminate. To detect radiation, phosphorous-doped silicon photoconductive sensors are inserted in GHz range RF transmission lines. By permitting signal propagation only when a sensor is illuminated, the RF signals are selectively routed from lower layer transmission lines to upper layer lines, thereby pinpointing the location and strength of incident radiation. Simulations based on a high frequency three-dimensional planar electromagnetics model are presented and compared to the experimental results. The experimental results are described for GHz range RF signal control for 300- and 180-mW incident energy from 975- to 1060-nm wavelength lasers, respectively, where upon illumination, RF transmission line signal output power doubled when compared to nonilluminated results. The experimental results are also reported for 100-W incident energy from a 1060-nm laser. Test results illustrate real-time signal processing would permit a structure to be controlled in response to incident radiation.
Network Modeling of MDM2 Inhibitor-Oxaliplatin Combination Reveals Biological Synergy in wt-p53 solid tumors

PubMed Central

Azmi, Asfar S.; Banerjee, Sanjeev; Ali, Shadan; Wang, Zhiwei; Bao, Bin; Beck, Frances W.J.; Maitah, Main; Choi, Minsig; Shields, Tony F.; Philip, Philip A.; Sarkar, Fazlul H.; Mohammad, Ramzi M.

2011-01-01

Earlier we had shown that the MDM2 inhibitor (MI-219) belonging to the spiro-oxindole family can synergistically enhance the efficacy of platinum chemotherapeutics leading to 50% tumor free survival in a genetically complex pancreatic ductal adenocarcinoma (PDAC) xenograft model. In this report, we have taken a systems and network modeling approach in order to understand central mechanisms behind MI219-oxaliplatin synergy with validation in PDAC, colon and breast cancer cell lines. Microarray profiling of drug treatments (MI-219, oxaliplatin or their combination) in capan-2 cells reveal a similar unique set of gene alterations that is duplicated in other solid tumor cells. As single agent, MI-219 or oxaliplatin induced alterations in 48 and 761 genes respectively. The combination treatment resulted in 767 gene alterations with emergence of 286 synergy unique genes. Ingenuity network modeling of combination and synergy unique genes showed the crucial role of five key local networks CREB, CARF, EGR1, NF-kB and E Cadherin. The network signatures were validated at the protein level in all three cell lines. Individually silencing central nodes in these five hubs resulted in abrogation of MI-219-oxaliplatin activity confirming their critical role in aiding p53 mediated apoptotic response. We anticipate that our MI219-oxaliplatin network blueprints can be clinically translated in the rationale design and application of this unique therapeutic combination in a genetically pre-defined subset of patients. PMID:21623005
Exfoliated-SnS2 restacked on graphene as a high-capacity, high-rate, and long-cycle life anode for sodium ion batteries

NASA Astrophysics Data System (ADS)

Liu, Yongchang; Kang, Hongyan; Jiao, Lifang; Chen, Chengcheng; Cao, Kangzhe; Wang, Yijing; Yuan, Huatang

2015-01-01

Designed as a high-capacity, high-rate, and long-cycle life anode for sodium ion batteries, exfoliated-SnS2 restacked on graphene is prepared by the hydrolysis of lithiated SnS2 followed by a facile hydrothermal method. Structural and morphological characterizations demonstrate that ultrasmall SnS2 nanoplates (with a typical size of 20-50 nm) composed of 2-5 layers are homogeneously decorated on the surface of graphene, while the hybrid structure self-assembles into a three-dimensional (3D) network architecture. The obtained SnS2/graphene nanocomposite delivers a remarkable capacity as high as 650 mA h g-1 at a current density of 200 mA g-1. More impressively, the capacity can reach 326 mA h g-1 even at 4000 mA g-1 and remains stable at ~610 mA h g-1 without fading up to 300 cycles when the rate is brought back to 200 mA g-1. The excellent electrochemical performance is attributed to the synergetic effects between the ultrasmall SnS2 and the highly conductive graphene network. The unique structure can simultaneously facilitate Na+ ion diffusion, provide more reaction sites, and suppress aggregation and volume fluctuation of the active materials during prolonged cycling.Designed as a high-capacity, high-rate, and long-cycle life anode for sodium ion batteries, exfoliated-SnS2 restacked on graphene is prepared by the hydrolysis of lithiated SnS2 followed by a facile hydrothermal method. Structural and morphological characterizations demonstrate that ultrasmall SnS2 nanoplates (with a typical size of 20-50 nm) composed of 2-5 layers are homogeneously decorated on the surface of graphene, while the hybrid structure self-assembles into a three-dimensional (3D) network architecture. The obtained SnS2/graphene nanocomposite delivers a remarkable capacity as high as 650 mA h g-1 at a current density of 200 mA g-1. More impressively, the capacity can reach 326 mA h g-1 even at 4000 mA g-1 and remains stable at ~610 mA h g-1 without fading up to 300 cycles when the rate is brought back to 200 mA g-1. The excellent electrochemical performance is attributed to the synergetic effects between the ultrasmall SnS2 and the highly conductive graphene network. The unique structure can simultaneously facilitate Na+ ion diffusion, provide more reaction sites, and suppress aggregation and volume fluctuation of the active materials during prolonged cycling. Electronic supplementary information (ESI) available: Scheme S1, Fig. S1-S4. See DOI: 10.1039/c4nr05106h
Linked 4-Way Multimodal Brain Differences in Schizophrenia in a Large Chinese Han Population.

PubMed

Liu, Shengfeng; Wang, Haiying; Song, Ming; Lv, Luxian; Cui, Yue; Liu, Yong; Fan, Lingzhong; Zuo, Nianming; Xu, Kaibin; Du, Yuhui; Yu, Qingbao; Luo, Na; Qi, Shile; Yang, Jian; Xie, Sangma; Li, Jian; Chen, Jun; Chen, Yunchun; Wang, Huaning; Guo, Hua; Wan, Ping; Yang, Yongfeng; Li, Peng; Lu, Lin; Yan, Hao; Yan, Jun; Wang, Huiling; Zhang, Hongxing; Zhang, Dai; Calhoun, Vince D; Jiang, Tianzi; Sui, Jing

2018-04-20

Multimodal fusion has been regarded as a promising tool to discover covarying patterns of multiple imaging types impaired in brain diseases, such as schizophrenia (SZ). In this article, we aim to investigate the covarying abnormalities underlying SZ in a large Chinese Han population (307 SZs, 298 healthy controls [HCs]). Four types of magnetic resonance imaging (MRI) features, including regional homogeneity (ReHo) from resting-state functional MRI, gray matter volume (GM) from structural MRI, fractional anisotropy (FA) from diffusion MRI, and functional network connectivity (FNC) resulted from group independent component analysis, were jointly analyzed by a data-driven multivariate fusion method. Results suggest that a widely distributed network disruption appears in SZ patients, with synchronous changes in both functional and structural regions, especially the basal ganglia network, salience network (SAN), and the frontoparietal network. Such a multimodal coalteration was also replicated in another independent Chinese sample (40 SZs, 66 HCs). Our results on auditory verbal hallucination (AVH) also provide evidence for the hypothesis that prefrontal hypoactivation and temporal hyperactivation in SZ may lead to failure of executive control and inhibition, which is relevant to AVH. In addition, impaired working memory performance was found associated with GM reduction and FA decrease in SZ in prefrontal and superior temporal area, in both discovery and replication datasets. In summary, by leveraging multiple imaging and clinical information into one framework to observe brain in multiple views, we can integrate multiple inferences about SZ from large-scale population and offer unique perspectives regarding the missing links between the brain function and structure that may not be achieved by separate unimodal analyses.
Topology of genetic associations between regional gray matter volume and intellectual ability: Evidence for a high capacity network.

PubMed

Bohlken, Marc M; Brouwer, Rachel M; Mandl, René C W; Hedman, Anna M; van den Heuvel, Martijn P; van Haren, Neeltje E M; Kahn, René S; Hulshoff Pol, Hilleke E

2016-01-01

Intelligence is associated with a network of distributed gray matter areas including the frontal and parietal higher association cortices and primary processing areas of the temporal and occipital lobes. Efficient information transfer between gray matter regions implicated in intelligence is thought to be critical for this trait to emerge. Genetic factors implicated in intelligence and gray matter may promote a high capacity for information transfer. Whether these genetic factors act globally or on local gray matter areas separately is not known. Brain maps of phenotypic and genetic associations between gray matter volume and intelligence were made using structural equation modeling of 3T MRI T1-weighted scans acquired in 167 adult twins of the newly acquired U-TWIN cohort. Subsequently, structural connectivity analyses (DTI) were performed to test the hypothesis that gray matter regions associated with intellectual ability form a densely connected core. Gray matter regions associated with intellectual ability were situated in the right prefrontal, bilateral temporal, bilateral parietal, right occipital and subcortical regions. Regions implicated in intelligence had high structural connectivity density compared to 10,000 reference networks (p=0.031). The genetic association with intelligence was for 39% explained by a genetic source unique to these regions (independent of total brain volume), this source specifically implicated the right supramarginal gyrus. Using a twin design, we show that intelligence is genetically represented in a spatially distributed and densely connected network of gray matter regions providing a high capacity infrastructure. Although genes for intelligence have overlap with those for total brain volume, we present evidence that there are genes for intelligence that act specifically on the subset of brain areas that form an efficient brain network. Copyright © 2015 Elsevier Inc. All rights reserved.
Modelling dendritic ecological networks in space: An integrated network perspective

Treesearch

Erin E. Peterson; Jay M. Ver Hoef; Dan J. Isaak; Jeffrey A. Falke; Marie-Josee Fortin; Chris E. Jordan; Kristina McNyset; Pascal Monestiez; Aaron S. Ruesch; Aritra Sengupta; Nicholas Som; E. Ashley Steel; David M. Theobald; Christian E. Torgersen; Seth J. Wenger

2013-01-01

Dendritic ecological networks (DENs) are a unique form of ecological networks that exhibit a dendritic network topology (e.g. stream and cave networks or plant architecture). DENs have a dual spatial representation; as points within the network and as points in geographical space. Consequently, some analytical methods used to quantify relationships in other types of...
Reactive molecular dynamics of network polymers: Generation, characterization and mechanical properties

NASA Astrophysics Data System (ADS)

Shankar, Chandrashekar

The goal of this research was to gain a fundamental understanding of the properties of networks created by the ring opening metathesis polymerization (ROMP) of dicyclopentadiene (DCPD) used in self-healing materials. To this end we used molecular simulation methods to generate realistic structures of DCPD networks, characterize their structures, and determine their mechanical properties. Density functional theory (DFT) calculations, complemented by structural information derived from molecular dynamics simulations were used to reconstruct experimental Raman spectra and differential scanning calorimetry (DSC) data. We performed coarse-grained simulations comparing networks generated via the ROMP reaction process and compared them to those generated via a RANDOM process, which led to the fundamental realization that the polymer topology has a unique influence on the network properties. We carried out fully atomistic simulations of DCPD using a novel algorithm for recreating ROMP reactions of DCPD molecules. Mechanical properties derived from these atomistic networks are in excellent agreement with those obtained from coarse-grained simulations in which interactions between nodes are subject to angular constraints. This comparison provides self-consistent validation of our simulation results and helps to identify the level of detail necessary for the coarse-grained interaction model. Simulations suggest networks can classified into three stages: fluid-like, rubber-like or glass-like delineated by two thresholds in degree of reaction alpha: The onset of finite magnitudes for the Young's modulus, alphaY, and the departure of the Poisson ration from 0.5, alphaP. In each stage the polymer exhibits a different predominant mechanical response to deformation. At low alpha < alphaY it flows. At alpha Y < alpha < alphaP the response is entropic with no change in internal energy. At alpha > alphaP the response is enthalpic change in internal energy. We developed graph theory-based network characterizations to correlate between network topology and the simulated mechanical properties. (1) Eigenvector centrality (2) Graph fractal dimension, (3) Fiedler partitioning, and (4) Cross-link fraction (Q3+Q4). Of these quantities, the Fiedler partition is the best characteristic for the prediction of Young's Modulus. The new computational tools developed in this research are of great fundamental and practical interest.
Divergent Drinking Patterns of Restaurant Workers: The Influence of Social Networks and Job Position.

PubMed

Duke, Michael R; Ames, Genevieve M; Moore, Roland S; Cunradi, Carol B

2013-01-01

Restaurant workers have higher rates of problem drinking than most occupational groups. However, little is known about the environmental risks and work characteristics that may lead to these behaviors. An exploration of restaurant workers' drinking networks may provide important insights into their alcohol consumption patterns, thus guiding workplace prevention efforts. Drawing from social capital theory, this paper examines the unique characteristics of drinking networks within and between various job categories. Our research suggests that these multiple, complex networks have unique risk characteristics, and that self-selection is based on factors such as job position and college attendance, among other factors.

Divergent Drinking Patterns of Restaurant Workers: The Influence of Social Networks and Job Position

PubMed Central

Ames, Genevieve M.; Moore, Roland S.; Cunradi, Carol B.

2013-01-01

Restaurant workers have higher rates of problem drinking than most occupational groups. However, little is known about the environmental risks and work characteristics that may lead to these behaviors. An exploration of restaurant workers’ drinking networks may provide important insights into their alcohol consumption patterns, thus guiding workplace prevention efforts. Drawing from social capital theory, this paper examines the unique characteristics of drinking networks within and between various job categories. Our research suggests that these multiple, complex networks have unique risk characteristics, and that self-selection is based on factors such as job position and college attendance, among other factors. PMID:23687470
Reproducibility and Temporal Structure in Weekly Resting-State fMRI over a Period of 3.5 Years

PubMed Central

Choe, Ann S.; Jones, Craig K.; Joel, Suresh E.; Muschelli, John; Belegu, Visar; Caffo, Brian S.; Lindquist, Martin A.; van Zijl, Peter C. M.; Pekar, James J.

2015-01-01

Resting-state functional MRI (rs-fMRI) permits study of the brain’s functional networks without requiring participants to perform tasks. Robust changes in such resting state networks (RSNs) have been observed in neurologic disorders, and rs-fMRI outcome measures are candidate biomarkers for monitoring clinical trials, including trials of extended therapeutic interventions for rehabilitation of patients with chronic conditions. In this study, we aim to present a unique longitudinal dataset reporting on a healthy adult subject scanned weekly over 3.5 years and identify rs-fMRI outcome measures appropriate for clinical trials. Accordingly, we assessed the reproducibility, and characterized the temporal structure of, rs-fMRI outcome measures derived using independent component analysis (ICA). Data was compared to a 21-person dataset acquired on the same scanner in order to confirm that the values of the single-subject RSN measures were within the expected range as assessed from the multi-participant dataset. Fourteen RSNs were identified, and the inter-session reproducibility of outcome measures—network spatial map, temporal signal fluctuation magnitude, and between-network connectivity (BNC)–was high, with executive RSNs showing the highest reproducibility. Analysis of the weekly outcome measures also showed that many rs-fMRI outcome measures had a significant linear trend, annual periodicity, and persistence. Such temporal structure was most prominent in spatial map similarity, and least prominent in BNC. High reproducibility supports the candidacy of rs-fMRI outcome measures as biomarkers, but the presence of significant temporal structure needs to be taken into account when such outcome measures are considered as biomarkers for rehabilitation-style therapeutic interventions in chronic conditions. PMID:26517540
Real-time physiological monitoring with distributed networks of sensors and object-oriented programming techniques

NASA Astrophysics Data System (ADS)

Wiesmann, William P.; Pranger, L. Alex; Bogucki, Mary S.

1998-05-01

Remote monitoring of physiologic data from individual high- risk workers distributed over time and space is a considerable challenge. This is often due to an inadequate capability to accurately integrate large amounts of data into usable information in real time. In this report, we have used the vertical and horizontal organization of the 'fireground' as a framework to design a distributed network of sensors. In this system, sensor output is linked through a hierarchical object oriented programing process to accurately interpret physiological data, incorporate these data into a synchronous model and relay processed data, trends and predictions to members of the fire incident command structure. There are several unique aspects to this approach. The first includes a process to account for variability in vital parameter values for each individual's normal physiologic response by including an adaptive network in each data process. This information is used by the model in an iterative process to baseline a 'normal' physiologic response to a given stress for each individual and to detect deviations that indicate dysfunction or a significant insult. The second unique capability of the system orders the information for each user including the subject, local company officers, medical personnel and the incident commanders. Information can be retrieved and used for training exercises and after action analysis. Finally this system can easily be adapted to existing communication and processing links along with incorporating the best parts of current models through the use of object oriented programming techniques. These modern software techniques are well suited to handling multiple data processes independently over time in a distributed network.
Social networks and self-rated health in two French-speaking Canadian community dwelling populations over 65.

PubMed

Zunzunegui, M V; Koné, A; Johri, M; Béland, F; Wolfson, C; Bergman, H

2004-05-01

The objective was to evaluate the associations between older persons' health status and their social integration and social networks (family, children, friends and community), in two French-speaking, Canadian community dwelling populations aged 65 years and over, using the conceptual framework proposed by Berkman and Thomas. Data were taken from two 1995 surveys conducted in the city of Moncton (n = 1518) and the Montreal neighbourhood of Hochelaga-Maisonneuve (n = 1500). Social engagement (a cumulative index of social activities), networks consisting of friends, family and children and social support were measured using validated scales. Multiple logistic regressions based on structured inclusion of potentially mediating variables were fitted to estimate the associations between health status and social networks. Self-rated health was better for those with a high level of social integration and a strong network of friends in both locations. In addition, in Hochelaga-Maisonneuve family and children networks were positively associated with good health, though the effect of friend networks was attenuated in the presence of disability, good social support from children was associated with good health. Age, sex and education were included as antecedent variables; smoking, alcohol consumption, exercise, locus of control and depressive symptoms were considered intermediary variables between social networks and health. In conclusion, social networks, integration and support demonstrated unique positive associations with health. The nature of these associations may vary between populations and cultures.
Abnormal rich club organization and impaired correlation between structural and functional connectivity in migraine sufferers.

PubMed

Li, Kang; Liu, Lijun; Yin, Qin; Dun, Wanghuan; Xu, Xiaolin; Liu, Jixin; Zhang, Ming

2017-04-01

Because of the unique position of the topologically central role of densely interconnected brain hubs, our study aimed to investigate whether these regions and their related connections would be particularly vulnerable to migraine. In our study, we explored the rich club structure and its role in global functional dynamics in 30 patients with migraine without aura and 30 healthy controls. DTI and resting fMRI were used to construct structural connectivity (SC) and functional connectivity (FC) networks. An independent replication data set of 26 patients and 26 controls was included to replicate and validate significant findings. As compared with the controls, the structural networks of patients exhibited altered rich club organization with higher level of feeder connection density, abnormal small-world organization with increased global efficiency and decreased strength of SC-FC coupling. As these abnormal topological properties and headache attack duration exhibited a significant association with increased density of feeder connections, our results indicated that migraine may be characterized by a selective alteration of the structural connectivity of the rich club regions, tending to have higher 'bridgeness' with non-rich club regions, which may increase the integration among pain-related brain circuits with more excitability but less inhibition for the modulation of migraine.
Disease implications of animal social network structure: A synthesis across social systems.

PubMed

Sah, Pratha; Mann, Janet; Bansal, Shweta

2018-05-01

The disease costs of sociality have largely been understood through the link between group size and transmission. However, infectious disease spread is driven primarily by the social organization of interactions in a group and not its size. We used statistical models to review the social network organization of 47 species, including mammals, birds, reptiles, fish and insects by categorizing each species into one of three social systems, relatively solitary, gregarious and socially hierarchical. Additionally, using computational experiments of infection spread, we determined the disease costs of each social system. We find that relatively solitary species have large variation in number of social partners, that socially hierarchical species are the least clustered in their interactions, and that social networks of gregarious species tend to be the most fragmented. However, these structural differences are primarily driven by weak connections, which suggest that different social systems have evolved unique strategies to organize weak ties. Our synthetic disease experiments reveal that social network organization can mitigate the disease costs of group living for socially hierarchical species when the pathogen is highly transmissible. In contrast, highly transmissible pathogens cause frequent and prolonged epidemic outbreaks in gregarious species. We evaluate the implications of network organization across social systems despite methodological challenges, and our findings offer new perspective on the debate about the disease costs of group living. Additionally, our study demonstrates the potential of meta-analytic methods in social network analysis to test ecological and evolutionary hypotheses on cooperation, group living, communication and resilience to extrinsic pressures. © 2017 The Authors. Journal of Animal Ecology © 2017 British Ecological Society.
Extracting neuronal functional network dynamics via adaptive Granger causality analysis.

PubMed

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

2018-04-24

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

PubMed

Ma, Songqi; Liu, Xiaoqing; Fan, Libo; Jiang, Yanhua; Cao, Lijun; Tang, Zhaobin; Zhu, Jin

2014-02-01

A bio-based epoxy resin (denoted TEIA) with high epoxy value (1.16) and low viscosity (0.92 Pa s, 258C) was synthesized from itaconic acid and its chemical structure was confirmed by 1H NMR and 13C NMR spectroscopy. Its curing reaction with poly(propylene glycol) bis(2-aminopropyl ether) (D230) and methyl hexahydrophthalic anhydride (MHHPA) was investigated. For comparison, the commonly used diglycidyl ether of bisphenol A (DGEBA) was also cured with the same curing agents. The results demonstrated that TEIA showed higher curing reactivity towards D230/MHHPA and lower viscosity compared with DGEBA, resulting in the better processability. Owing to its high epoxy value and unique structure, comparable or better glass transition temperature as well as mechanical properties could be obtained for the TEIA-based network relative to the DGEBA-based network. The results indicated that itaconic acid is a promising renewable feedstock for the synthesis of bio-based epoxy resin with high performance.
Chemically programmed self-sorting of gelator networks.

PubMed

Morris, Kyle L; Chen, Lin; Raeburn, Jaclyn; Sellick, Owen R; Cotanda, Pepa; Paul, Alison; Griffiths, Peter C; King, Stephen M; O'Reilly, Rachel K; Serpell, Louise C; Adams, Dave J

2013-01-01

Controlling the order and spatial distribution of self-assembly in multicomponent supramolecular systems could underpin exciting new functional materials, but it is extremely challenging. When a solution of different components self-assembles, the molecules can either coassemble, or self-sort, where a preference for like-like intermolecular interactions results in coexisting, homomolecular assemblies. A challenge is to produce generic and controlled 'one-pot' fabrication methods to form separate ordered assemblies from 'cocktails' of two or more self-assembling species, which might have relatively similar molecular structures and chemistry. Self-sorting in supramolecular gel phases is hence rare. Here we report the first example of the pH-controlled self-sorting of gelators to form self-assembled networks in water. Uniquely, the order of assembly can be predefined. The assembly of each component is preprogrammed by the pK(a) of the gelator. This pH-programming method will enable higher level, complex structures to be formed that cannot be accessed by simple thermal gelation.
l-Glutamic acid assisted eco-friendly one-pot synthesis of sheet-assembled platinum-palladium alloy networks for methanol oxidation and oxygen reduction reactions.

PubMed

Shi, Ya-Cheng; Mei, Li-Ping; Wang, Ai-Jun; Yuan, Tao; Chen, Sai-Sai; Feng, Jiu-Ju

2017-10-15

In this work, bimetallic platinum-palladium sheet-assembled alloy networks (PtPd SAANs) were facilely synthesized by an eco-friendly one-pot aqueous approach under the guidance of l-glutamic acid at room temperature, without any additive, seed, toxic or organic solvent involved. l-Glutamic acid was served as the green shape-director and weak-stabilizing agent. A series of characterization techniques were employed to examine the morphology, structure and formation mechanism of the product. The architectures exhibited improved electrocatalytic activity and durable ability toward methanol oxidation reaction (MOR) and oxygen reduction reaction (ORR) in contrast with commercial Pt black and Pd black catalysts. This is ascribed to the unique structures of the obtained PtPd SAANs and the synergistic effects of the bimetals. These results demonstrate the potential application of the prepared catalyst in fuel cells. Copyright © 2017 Elsevier Inc. All rights reserved.
Predicting Structure-Function Relations and Survival following Surgical and Bronchoscopic Lung Volume Reduction Treatment of Emphysema.

PubMed

Mondoñedo, Jarred R; Suki, Béla

2017-02-01

Lung volume reduction surgery (LVRS) and bronchoscopic lung volume reduction (bLVR) are palliative treatments aimed at reducing hyperinflation in advanced emphysema. Previous work has evaluated functional improvements and survival advantage for these techniques, although their effects on the micromechanical environment in the lung have yet to be determined. Here, we introduce a computational model to simulate a force-based destruction of elastic networks representing emphysema progression, which we use to track the response to lung volume reduction via LVRS and bLVR. We find that (1) LVRS efficacy can be predicted based on pre-surgical network structure; (2) macroscopic functional improvements following bLVR are related to microscopic changes in mechanical force heterogeneity; and (3) both techniques improve aspects of survival and quality of life influenced by lung compliance, albeit while accelerating disease progression. Our model predictions yield unique insights into the microscopic origins underlying emphysema progression before and after lung volume reduction.
Predicting Structure-Function Relations and Survival following Surgical and Bronchoscopic Lung Volume Reduction Treatment of Emphysema

PubMed Central

Mondoñedo, Jarred R.

2017-01-01

Lung volume reduction surgery (LVRS) and bronchoscopic lung volume reduction (bLVR) are palliative treatments aimed at reducing hyperinflation in advanced emphysema. Previous work has evaluated functional improvements and survival advantage for these techniques, although their effects on the micromechanical environment in the lung have yet to be determined. Here, we introduce a computational model to simulate a force-based destruction of elastic networks representing emphysema progression, which we use to track the response to lung volume reduction via LVRS and bLVR. We find that (1) LVRS efficacy can be predicted based on pre-surgical network structure; (2) macroscopic functional improvements following bLVR are related to microscopic changes in mechanical force heterogeneity; and (3) both techniques improve aspects of survival and quality of life influenced by lung compliance, albeit while accelerating disease progression. Our model predictions yield unique insights into the microscopic origins underlying emphysema progression before and after lung volume reduction. PMID:28182686
Deciding to Cooperate in Northern Ghana: Trust as an Evolutionary Constraint Across Cultural Diversity.

PubMed

Acedo-Carmona, Cristina; Gomila, Antoni

2015-11-27

The upper-east and northern regions of Ghana offers a unique opportunity to study the influence of evolutionary social dynamics in making cooperation possible, despite cultural differences. These regions are occupied by several distinct ethnic groups, in interaction, such as the Kussasi, Mamprusi, Bimoba, Konkomba, and Fulani. We will report our fieldwork related to how cooperation takes places there, both within each group and among people from the different groups. Methods included personal networks of cooperation (ego networks), interviews and analysis of group contexts. The most important result is that, while each ethnic group may differ in terms of family and clan structure, a similar pattern can be found in all of them, of cooperation structured around small groups of trust-based close relationships. The study suggests that habitual decisions about cooperation are not strategic or self-interested, but instead are based on unconscious processes sustained by the emotional bonds of trust. These kind of emotional bonds are claimed to be relevant from an evolutionary point of view.
A long-time limit for world subway networks.

PubMed

Roth, Camille; Kang, Soong Moon; Batty, Michael; Barthelemy, Marc

2012-10-07

We study the temporal evolution of the structure of the world's largest subway networks in an exploratory manner. We show that, remarkably, all these networks converge to a shape that shares similar generic features despite their geographical and economic differences. This limiting shape is made of a core with branches radiating from it. For most of these networks, the average degree of a node (station) within the core has a value of order 2.5 and the proportion of k = 2 nodes in the core is larger than 60 per cent. The number of branches scales roughly as the square root of the number of stations, the current proportion of branches represents about half of the total number of stations, and the average diameter of branches is about twice the average radial extension of the core. Spatial measures such as the number of stations at a given distance to the barycentre display a first regime which grows as r(2) followed by another regime with different exponents, and eventually saturates. These results--difficult to interpret in the framework of fractal geometry--confirm and yield a natural explanation in the geometric picture of this core and their branches: the first regime corresponds to a uniform core, while the second regime is controlled by the interstation spacing on branches. The apparent convergence towards a unique network shape in the temporal limit suggests the existence of dominant, universal mechanisms governing the evolution of these structures.
A long-time limit for world subway networks

PubMed Central

Roth, Camille; Kang, Soong Moon; Batty, Michael; Barthelemy, Marc

2012-01-01

We study the temporal evolution of the structure of the world's largest subway networks in an exploratory manner. We show that, remarkably, all these networks converge to a shape that shares similar generic features despite their geographical and economic differences. This limiting shape is made of a core with branches radiating from it. For most of these networks, the average degree of a node (station) within the core has a value of order 2.5 and the proportion of k = 2 nodes in the core is larger than 60 per cent. The number of branches scales roughly as the square root of the number of stations, the current proportion of branches represents about half of the total number of stations, and the average diameter of branches is about twice the average radial extension of the core. Spatial measures such as the number of stations at a given distance to the barycentre display a first regime which grows as r2 followed by another regime with different exponents, and eventually saturates. These results—difficult to interpret in the framework of fractal geometry—confirm and yield a natural explanation in the geometric picture of this core and their branches: the first regime corresponds to a uniform core, while the second regime is controlled by the interstation spacing on branches. The apparent convergence towards a unique network shape in the temporal limit suggests the existence of dominant, universal mechanisms governing the evolution of these structures. PMID:22593096
Agricultural trade networks and patterns of economic development.

PubMed

Shutters, Shade T; Muneepeerakul, Rachata

2012-01-01

International trade networks are manifestations of a complex combination of diverse underlying factors, both natural and social. Here we apply social network analytics to the international trade network of agricultural products to better understand the nature of this network and its relation to patterns of international development. Using a network tool known as triadic analysis we develop triad significance profiles for a series of agricultural commodities traded among countries. Results reveal a novel network "superfamily" combining properties of biological information processing networks and human social networks. To better understand this unique network signature, we examine in more detail the degree and triadic distributions within the trade network by country and commodity. Our results show that countries fall into two very distinct classes based on their triadic frequencies. Roughly 165 countries fall into one class while 18, all highly isolated with respect to international agricultural trade, fall into the other. Only Vietnam stands out as a unique case. Finally, we show that as a country becomes less isolated with respect to number of trading partners, the country's triadic signature follows a predictable trajectory that may correspond to a trajectory of development.
Reinforced Adversarial Neural Computer for de Novo Molecular Design.

PubMed

Putin, Evgeny; Asadulaev, Arip; Ivanenkov, Yan; Aladinskiy, Vladimir; Sanchez-Lengeling, Benjamin; Aspuru-Guzik, Alán; Zhavoronkov, Alex

2018-06-12

In silico modeling is a crucial milestone in modern drug design and development. Although computer-aided approaches in this field are well-studied, the application of deep learning methods in this research area is at the beginning. In this work, we present an original deep neural network (DNN) architecture named RANC (Reinforced Adversarial Neural Computer) for the de novo design of novel small-molecule organic structures based on the generative adversarial network (GAN) paradigm and reinforcement learning (RL). As a generator RANC uses a differentiable neural computer (DNC), a category of neural networks, with increased generation capabilities due to the addition of an explicit memory bank, which can mitigate common problems found in adversarial settings. The comparative results have shown that RANC trained on the SMILES string representation of the molecules outperforms its first DNN-based counterpart ORGANIC by several metrics relevant to drug discovery: the number of unique structures, passing medicinal chemistry filters (MCFs), Muegge criteria, and high QED scores. RANC is able to generate structures that match the distributions of the key chemical features/descriptors (e.g., MW, logP, TPSA) and lengths of the SMILES strings in the training data set. Therefore, RANC can be reasonably regarded as a promising starting point to develop novel molecules with activity against different biological targets or pathways. In addition, this approach allows scientists to save time and covers a broad chemical space populated with novel and diverse compounds.
IR spectroscopy of protonation in benzene-water nanoclusters: hydronium, zundel, and eigen at a hydrophobic interface.

PubMed

Cheng, Timothy C; Bandyopadhyay, Biswajit; Mosley, Jonathan D; Duncan, Michael A

2012-08-08

The structure of ions in water at a hydrophobic interface influences important processes throughout chemistry and biology. However, experiments to measure these structures are limited by the distribution of configurations present and the inability to selectively probe the interfacial region. Here, protonated nanoclusters containing benzene and water are produced in the gas phase, size-selected, and investigated with infrared laser spectroscopy. Proton stretch, free OH, and hydrogen-bonding vibrations uniquely define protonation sites and hydrogen-bonding networks. The structures consist of protonated water clusters binding to the hydrophobic interface of neutral benzene via one or more π-hydrogen bonds. Comparison to the spectra of isolated hydronium, zundel, or eigen ions reveals the inductive effects and local ordering induced by the interface. The structures and interactions revealed here represent key features expected for aqueous hydrophobic interfaces.
The structure of a bottlenose dolphin society is coupled to a unique foraging cooperation with artisanal fishermen.

PubMed

Daura-Jorge, F G; Cantor, M; Ingram, S N; Lusseau, D; Simões-Lopes, P C

2012-10-23

Diverse and localized foraging behaviours have been reported in isolated populations of many animal species around the world. In Laguna, southern Brazil, a subset of resident bottlenose dolphins (Tursiops truncatus) uses a foraging tactic involving cooperative interactions with local, beach-casting fishermen. We used individual photo-identification data to assess whether cooperative and non-cooperative dolphins were socially segregated. The social structure of the population was found to be a fission-fusion system with few non-random associations, typical for this species. However, association values were greater among cooperative dolphins than among non-cooperative dolphins or between dolphins from different foraging classes. Furthermore, the dolphin social network was divided into three modules, clustering individuals that shared or lacked the cooperative foraging tactic. Space-use patterns were not sufficient to explain this partitioning, indicating a behavioural factor. The segregation of dolphins using different foraging tactics could result from foraging behaviour driving social structure, while the closer association between dolphins engaged in the cooperation could facilitate the transmission and learning of this behavioural trait from conspecifics. This unique case of a dolphin-human interaction represents a valuable opportunity to explore hypotheses on the role of social learning in wild cetaceans.
The Postsynaptic Density Proteins Homer and Shank Form a Polymeric Network Structure

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

Hayashi, M.; Tang, C; Verpelli, C

2009-01-01

The postsynaptic density (PSD) is crucial for synaptic functions, but the molecular architecture retaining its structure and components remains elusive. Homer and Shank are among the most abundant scaffolding proteins in the PSD, working synergistically for maturation of dendritic spines. Here, we demonstrate that Homer and Shank, together, form a mesh-like matrix structure. Crystallographic analysis of this region revealed a pair of parallel dimeric coiled coils intercalated in a tail-to-tail fashion to form a tetramer, giving rise to the unique configuration of a pair of N-terminal EVH1 domains at each end of the coiled coil. In neurons, the tetramerization ismore » required for structural integrity of the dendritic spines and recruitment of proteins to synapses. We propose that the Homer-Shank complex serves as a structural framework and as an assembly platform for other PSD proteins.« less

Characterising the Architecture of New Zealand's Geothermal Structural Fluid Flow Networks Using Borehole Images

NASA Astrophysics Data System (ADS)

McNamara, David; Milicich, Sarah; Massiot, Cécile

2017-04-01

Borehole imaging has been used worldwide since the 1950's to capture vital geological information on the lithology, structure, and stress conditions of the Earth's subsurface. In New Zealand both acoustic and resistivity based borehole image logs are utilised to explore the geological nature of the basement and volcanic rocks that contain the country's unique geothermal reservoirs. Borehole image logs in wells from three geothermal fields in the Taupo Volcanic Zone (TVZ) provide the first, direct, subsurface, structural orientation measurements in New Zealand geothermal reservoir lithologies. While showing an overall structural pattern aligned to the regional tectonic trend, heterogeneities are observed that provide insight into the complexity of the structurally controlled, geothermal, fluid flow pathways. Analysis of imaged stress induced features informs us that the stress field orientation in the TVZ is also not homogenous, but is variable at a local scale.
Global Dynamics of Proteins: Bridging Between Structure and Function

PubMed Central

Bahar, Ivet; Lezon, Timothy R.; Yang, Lee-Wei; Eyal, Eran

2010-01-01

Biomolecular systems possess unique, structure-encoded dynamic properties that underlie their biological functions. Recent studies indicate that these dynamic properties are determined to a large extent by the topology of native contacts. In recent years, elastic network models used in conjunction with normal mode analyses have proven to be useful for elucidating the collective dynamics intrinsically accessible under native state conditions, including in particular the global modes of motions that are robustly defined by the overall architecture. With increasing availability of structural data for well-studied proteins in different forms (liganded, complexed, or free), there is increasing evidence in support of the correspondence between functional changes in structures observed in experiments and the global motions predicted by these coarse-grained analyses. These observed correlations suggest that computational methods may be advantageously employed for assessing functional changes in structure and allosteric mechanisms intrinsically favored by the native fold. PMID:20192781
Global dynamics of proteins: bridging between structure and function.

PubMed

Bahar, Ivet; Lezon, Timothy R; Yang, Lee-Wei; Eyal, Eran

2010-01-01

Biomolecular systems possess unique, structure-encoded dynamic properties that underlie their biological functions. Recent studies indicate that these dynamic properties are determined to a large extent by the topology of native contacts. In recent years, elastic network models used in conjunction with normal mode analyses have proven to be useful for elucidating the collective dynamics intrinsically accessible under native state conditions, including in particular the global modes of motions that are robustly defined by the overall architecture. With increasing availability of structural data for well-studied proteins in different forms (liganded, complexed, or free), there is increasing evidence in support of the correspondence between functional changes in structures observed in experiments and the global motions predicted by these coarse-grained analyses. These observed correlations suggest that computational methods may be advantageously employed for assessing functional changes in structure and allosteric mechanisms intrinsically favored by the native fold.
Hydrogen-bonded structures from adamantane-based catechols

NASA Astrophysics Data System (ADS)

Kawahata, Masatoshi; Matsuura, Miku; Tominaga, Masahide; Katagiri, Kosuke; Yamaguchi, Kentaro

2018-07-01

Adamantane-based bis- and tris-catechols were synthesized to examine the effect of hydrogen bonds on the arrangement and packing of the components in the crystalline state. Single-crystal X-ray crystallographic analysis revealed that hydrogen bonds formed by the hydroxyl groups of catechol groups play essential roles in the production of various types of unique structures. 1,3-Bis(3,4-dihydroxyphenyl)adamantane (1) provided hydrogen-bonded network structures composed of helical chains in crystal from chloroform/methanol, and layer structures in crystal from ethyl acetate/hexane. The complexation of 1 with 1,3,5-trinitrobenzene or 1,2,4,5-tetracyanobenzene resulted in the formation of co-crystals, respectively. One-dimensional hydrogen-bonded structures were constructed from the adamantane-based molecules, which participated in charge-transfer interactions with guests. 1,3,5-Tris(3,4-dihydroxyphenyl)adamantane also afforded crystal, and the components were assembled into infinite polymers.
Graphdiyne Nanoparticles with High Free Radical Scavenging Activity for Radiation Protection.

PubMed

Xie, Jiani; Wang, Ning; Dong, Xinghua; Wang, Chengyan; Du, Zhen; Mei, Linqiang; Yong, Yuan; Huang, Changshui; Li, Yuliang; Gu, Zhanjun; Zhao, Yuliang

2018-03-06

Numerous carbon networks materials comprised of benzene moieties, such as graphene and fullerene, have held great fascination for radioprotection because of their acknowledged good biocompatibility and strong free radical scavenging activity derived from their delocalized π-conjugated structure. Recently, graphdiyne, a new emerging carbon network material consisting of a unique chemical structure of benzene and acetylenic moieties, has gradually attracted attention in many research fields. Encouraged by its unique structure with strong conjugated π-system and highly reactive diacetylenic linkages, graphdiyne might have free radical activity and can thus be used as a radioprotector, which has not been investigated so far. Herein, for the first time, we synthesized bovine serum albumin (BSA)-modified graphdiyne nanoparticles (graphdiyne-BSA NPs) to evaluate their free radical scavenging ability and investigate their application for radioprotection both in cell and animal models. In vitro studies indicated that the graphdiyne-BSA NPs could effectively eliminate the free-radicals, decrease radiation-induced DNA damage in cells, and improve the viability of cells under ionizing radiation. In vivo experiments showed that the graphdiyne-BSA NPs could protect the bone marrow DNA of mice from radiation-induced damage and make the superoxide dismutase (SOD) and malondialdehyde (MDA) (two kinds of vital indicators of radiation-induced injury) recover back to normal levels. Furthermore, the good biocompatibility and negligible systemically toxicity responses of the graphdiyne-BSA NPs to mice were verified. All these results manifest the good biosafety and radioprotection activity of graphdiyne-BSA NPs to normal tissues. Therefore, our studies not only provide a new radiation protection platform based on graphdiyne for protecting normal tissues from radiation-caused injury but also provide a promising direction for the application of graphdiyne in the biomedicine field.
A Histidine Aspartate Ionic Lock Gates the Iron Passage in Miniferritins from Mycobacterium smegmatis*

PubMed Central

Williams, Sunanda Margrett; Chandran, Anu V.; Vijayabaskar, Mahalingam S.; Roy, Sourav; Balaram, Hemalatha; Vishveshwara, Saraswathi; Vijayan, Mamannamana; Chatterji, Dipankar

2014-01-01

Dps (DNA-binding protein from starved cells) are dodecameric assemblies belonging to the ferritin family that can bind DNA, carry out ferroxidation, and store iron in their shells. The ferritin-like trimeric pore harbors the channel for the entry and exit of iron. By representing the structure of Dps as a network we have identified a charge-driven interface formed by a histidine aspartate cluster at the pore interface unique to Mycobacterium smegmatis Dps protein, MsDps2. Site-directed mutagenesis was employed to generate mutants to disrupt the charged interactions. Kinetics of iron uptake/release of the wild type and mutants were compared. Crystal structures were solved at a resolution of 1.8–2.2 Å for the various mutants to compare structural alterations vis à vis the wild type protein. The substitutions at the pore interface resulted in alterations in the side chain conformations leading to an overall weakening of the interface network, especially in cases of substitutions that alter the charge at the pore interface. Contrary to earlier findings where conserved aspartate residues were found crucial for iron release, we propose here that in the case of MsDps2, it is the interplay of negative-positive potentials at the pore that enables proper functioning of the protein. In similar studies in ferritins, negative and positive patches near the iron exit pore were found to be important in iron uptake/release kinetics. The unique ionic cluster in MsDps2 makes it a suitable candidate to act as nano-delivery vehicle, as these gated pores can be manipulated to exhibit conformations allowing for slow or fast rates of iron release. PMID:24573673
Corticostriatal connectivity fingerprints: Probability maps based on resting-state functional connectivity.

PubMed

Jaspers, Ellen; Balsters, Joshua H; Kassraian Fard, Pegah; Mantini, Dante; Wenderoth, Nicole

2017-03-01

Over the last decade, structure-function relationships have begun to encompass networks of brain areas rather than individual structures. For example, corticostriatal circuits have been associated with sensorimotor, limbic, and cognitive information processing, and damage to these circuits has been shown to produce unique behavioral outcomes in Autism, Parkinson's Disease, Schizophrenia and healthy ageing. However, it remains an open question how abnormal or absent connectivity can be detected at the individual level. Here, we provide a method for clustering gross morphological structures into subregions with unique functional connectivity fingerprints, and generate network probability maps usable as a baseline to compare individual cases against. We used connectivity metrics derived from resting-state fMRI (N = 100), in conjunction with hierarchical clustering methods, to parcellate the striatum into functionally distinct clusters. We identified three highly reproducible striatal subregions, across both hemispheres and in an independent replication dataset (N = 100) (dice-similarity values 0.40-1.00). Each striatal seed region resulted in a highly reproducible distinct connectivity fingerprint: the putamen showed predominant connectivity with cortical and cerebellar sensorimotor and language processing areas; the ventromedial striatum cluster had a distinct limbic connectivity pattern; the caudate showed predominant connectivity with the thalamus, frontal and occipital areas, and the cerebellum. Our corticostriatal probability maps agree with existing connectivity data in humans and non-human primates, and showed a high degree of replication. We believe that these maps offer an efficient tool to further advance hypothesis driven research and provide important guidance when investigating deviant connectivity in neurological patient populations suffering from e.g., stroke or cerebral palsy. Hum Brain Mapp 38:1478-1491, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Mapping Multiplex Hubs in Human Functional Brain Networks

PubMed Central

De Domenico, Manlio; Sasai, Shuntaro; Arenas, Alex

2016-01-01

Typical brain networks consist of many peripheral regions and a few highly central ones, i.e., hubs, playing key functional roles in cerebral inter-regional interactions. Studies have shown that networks, obtained from the analysis of specific frequency components of brain activity, present peculiar architectures with unique profiles of region centrality. However, the identification of hubs in networks built from different frequency bands simultaneously is still a challenging problem, remaining largely unexplored. Here we identify each frequency component with one layer of a multiplex network and face this challenge by exploiting the recent advances in the analysis of multiplex topologies. First, we show that each frequency band carries unique topological information, fundamental to accurately model brain functional networks. We then demonstrate that hubs in the multiplex network, in general different from those ones obtained after discarding or aggregating the measured signals as usual, provide a more accurate map of brain's most important functional regions, allowing to distinguish between healthy and schizophrenic populations better than conventional network approaches. PMID:27471443
A taxonomy of health networks and systems: bringing order out of chaos.

PubMed Central

Bazzoli, G J; Shortell, S M; Dubbs, N; Chan, C; Kralovec, P

1999-01-01

OBJECTIVE: To use existing theory and data for empirical development of a taxonomy that identifies clusters of organizations sharing common strategic/structural features. DATA SOURCES: Data from the 1994 and 1995 American Hospital Association Annual Surveys, which provide extensive data on hospital involvement in hospital-led health networks and systems. STUDY DESIGN: Theories of organization behavior and industrial organization economics were used to identify three strategic/structural dimensions: differentiation, which refers to the number of different products/services along a healthcare continuum; integration, which refers to mechanisms used to achieve unity of effort across organizational components; and centralization, which relates to the extent to which activities take place at centralized versus dispersed locations. These dimensions were applied to three components of the health service/product continuum: hospital services, physician arrangements, and provider-based insurance activities. DATA EXTRACTION METHODS: We identified 295 health systems and 274 health networks across the United States in 1994, and 297 health systems and 306 health networks in 1995 using AHA data. Empirical measures aggregated individual hospital data to the health network and system level. PRINCIPAL FINDINGS: We identified a reliable, internally valid, and stable four-cluster solution for health networks and a five-cluster solution for health systems. We found that differentiation and centralization were particularly important in distinguishing unique clusters of organizations. High differentiation typically occurred with low centralization, which suggests that a broader scope of activity is more difficult to centrally coordinate. Integration was also important, but we found that health networks and systems typically engaged in both ownership-based and contractual-based integration or they were not integrated at all. CONCLUSIONS: Overall, we were able to classify approximately 70 percent of hospital-led health networks and 90 percent of hospital-led health systems into well-defined organizational clusters. Given the widespread perception that organizational change in healthcare has been chaotic, our research suggests that important and meaningful similarities exist across many evolving organizations. The resulting taxonomy provides a new lexicon for researchers, policymakers, and healthcare executives for characterizing key strategic and structural features of evolving organizations. The taxonomy also provides a framework for future inquiry about the relationships between organizational strategy, structure, and performance, and for assessing policy issues, such as Medicare Provider Sponsored Organizations, antitrust, and insurance regulation. Images Figure 2A Figure 2A Figure 2B Figure 2B PMID:10029504
Navigating at Will on the Water Phase Diagram

NASA Astrophysics Data System (ADS)

Pipolo, S.; Salanne, M.; Ferlat, G.; Klotz, S.; Saitta, A. M.; Pietrucci, F.

2017-12-01

Despite the simplicity of its molecular unit, water is a challenging system because of its uniquely rich polymorphism and predicted but yet unconfirmed features. Introducing a novel space of generalized coordinates that capture changes in the topology of the interatomic network, we are able to systematically track transitions among liquid, amorphous, and crystalline forms throughout the whole phase diagram of water, including the nucleation of crystals above and below the melting point. Our approach, based on molecular dynamics and enhanced sampling or free energy calculation techniques, is not specific to water and could be applied to very different structural phase transitions, paving the way towards the prediction of kinetic routes connecting polymorphic structures in a range of materials.
Social brain volume is associated with in-degree social network size among older adults

PubMed Central

2018-01-01

The social brain hypothesis proposes that large neocortex size evolved to support cognitively demanding social interactions. Accordingly, previous studies have observed that larger orbitofrontal and amygdala structures predict the size of an individual's social network. However, it remains uncertain how an individual's social connectedness reported by other people is associated with the social brain volume. In this study, we found that a greater in-degree network size, a measure of social ties identified by a subject's social connections rather than by the subject, significantly correlated with a larger regional volume of the orbitofrontal cortex, dorsomedial prefrontal cortex and lingual gyrus. By contrast, out-degree size, which is based on an individual's self-perceived connectedness, showed no associations. Meta-analytic reverse inference further revealed that regional volume pattern of in-degree size was specifically involved in social inference ability. These findings were possible because our dataset contained the social networks of an entire village, i.e. a global network. The results suggest that the in-degree aspect of social network size not only confirms the previously reported brain correlates of the social network but also shows an association in brain regions involved in the ability to infer other people's minds. This study provides insight into understanding how the social brain is uniquely associated with sociocentric measures derived from a global network. PMID:29367402
Social Networks and Well-being: A Comparison of Older People in Mediterranean and Non-Mediterranean Countries

PubMed Central

2010-01-01

Objectives. This study examined whether the social networks of older persons in Mediterranean and non-Mediterranean countries were appreciably different and whether they functioned in similar ways in relation to well-being outcomes. Methods. The sample included family household respondents aged 60 years and older from the first wave of the Survey of Health, Ageing and Retirement in Europe in 5 Mediterranean (n = 3,583) and 7 non-Mediterranean (n = 5,471) countries. Region was regressed separately by gender on variables from 4 network domains: structure and interaction, exchange, engagement and relationship quality, and controlling for background and health characteristics. In addition, 2 well-being outcomes—depressive symptoms and perceived income inadequacy—were regressed on the study variables, including regional social network interaction terms. Results. The results revealed differences across the 2 regional settings in each of the realms of social network, above and beyond the differences that exist in background characteristics and health status. The findings also showed that the social network variables had different effects on the well-being outcomes in the respective settings. Discussion. The findings underscore that the social network phenomenon is contextually bound. The social networks of older people should be seen within their unique regional milieu and in relation to the values and social norms that prevail in different sets of societies. PMID:20008485
Bi-national Social Networks and Assimilation: A Test of the Importance of Transnationalism

PubMed Central

Mouw, Ted; Chavez, Sergio; Edelblute, Heather; Verdery, Ashton

2015-01-01

While the concept of transnationalism has gained widespread popularity among scholars as a way to describe immigrants’ long-term maintenance of cross-border ties to their origin communities, critics have argued that the overall proportion of immigrants who engage in transnational behavior is low and that, as a result, transnationalism has little sustained effect on the process of immigrant adaptation and assimilation. In this paper, we argue that a key shortcoming in the current empirical debate on transnationalism is the lack of data on the social networks that connect migrants to each other and to non-migrants in communities of origin. To address this shortcoming, our analysis uses unique bi-national data on the social network connecting an immigrant sending community in Guanajuato, Mexico, to two destination areas in the United States. We test for the effect of respondents’ positions in cross-border networks on their migration intentions and attitudes towards the United States using data on the opinions of their peers, their participation in cross border and local communication networks, and their structural position in the network. The results indicate qualified empirical support for a network-based model of transnationalism; in the U.S. sample we find evidence of network clustering consistent with peer effects, while in the Mexican sample we find evidence of the importance of cross-border communication with friends. PMID:25750462
A palladium-doped ceria@carbon core-sheath nanowire network: a promising catalyst support for alcohol electrooxidation reactions.

PubMed

Tan, Qiang; Du, Chunyu; Sun, Yongrong; Du, Lei; Yin, Geping; Gao, Yunzhi

2015-08-28

A novel palladium-doped ceria and carbon core-sheath nanowire network (Pd-CeO2@C CSNWN) is synthesized by a template-free and surfactant-free solvothermal process, followed by high temperature carbonization. This hierarchical network serves as a new class of catalyst support to enhance the activity and durability of noble metal catalysts for alcohol oxidation reactions. Its supported Pd nanoparticles, Pd/(Pd-CeO2@C CSNWN), exhibit >9 fold increase in activity toward the ethanol oxidation over the state-of-the-art Pd/C catalyst, which is the highest among the reported Pd systems. Moreover, stability tests show a virtually unchanged activity after 1000 cycles. The high activity is mainly attributed to the superior oxygen-species releasing capability of Pd-doped CeO2 nanowires by accelerating the removal of the poisoning intermediate. The unique interconnected one-dimensional core-sheath structure is revealed to facilitate immobilization of the metal catalysts, leading to the improved durability. This core-sheath nanowire network opens up a new strategy for catalyst performance optimization for next-generation fuel cells.
Cellular metabolic network analysis: discovering important reactions in Treponema pallidum.

PubMed

Chen, Xueying; Zhao, Min; Qu, Hong

2015-01-01

T. pallidum, the syphilis-causing pathogen, performs very differently in metabolism compared with other bacterial pathogens. The desire for safe and effective vaccine of syphilis requests identification of important steps in T. pallidum's metabolism. Here, we apply Flux Balance Analysis to represent the reactions quantitatively. Thus, it is possible to cluster all reactions in T. pallidum. By calculating minimal cut sets and analyzing topological structure for the metabolic network of T. pallidum, critical reactions are identified. As a comparison, we also apply the analytical approaches to the metabolic network of H. pylori to find coregulated drug targets and unique drug targets for different microorganisms. Based on the clustering results, all reactions are further classified into various roles. Therefore, the general picture of their metabolic network is obtained and two types of reactions, both of which are involved in nucleic acid metabolism, are found to be essential for T. pallidum. It is also discovered that both hubs of reactions and the isolated reactions in purine and pyrimidine metabolisms play important roles in T. pallidum. These reactions could be potential drug targets for treating syphilis.
From Molecular Circuit Dysfunction to Disease: Case Studies in Epilepsy, Traumatic Brain Injury, and Alzheimer’s Disease

PubMed Central

Dulla, Chris G.; Coulter, Douglas A.; Ziburkus, Jokubas

2015-01-01

Complex circuitry with feed-forward and feed-back systems regulate neuronal activity throughout the brain. Cell biological, electrical, and neurotransmitter systems enable neural networks to process and drive the entire spectrum of cognitive, behavioral, and motor functions. Simultaneous orchestration of distinct cells and interconnected neural circuits relies on hundreds, if not thousands, of unique molecular interactions. Even single molecule dysfunctions can be disrupting to neural circuit activity, leading to neurological pathology. Here, we sample our current understanding of how molecular aberrations lead to disruptions in networks using three neurological pathologies as exemplars: epilepsy, traumatic brain injury (TBI), and Alzheimer’s disease (AD). Epilepsy provides a window into how total destabilization of network balance can occur. TBI is an abrupt physical disruption that manifests in both acute and chronic neurological deficits. Last, in AD progressive cell loss leads to devastating cognitive consequences. Interestingly, all three of these neurological diseases are interrelated. The goal of this review, therefore, is to identify molecular changes that may lead to network dysfunction, elaborate on how altered network activity and circuit structure can contribute to neurological disease, and suggest common threads that may lie at the heart of molecular circuit dysfunction. PMID:25948650
Inferring metabolic networks using the Bayesian adaptive graphical lasso with informative priors.

PubMed

Peterson, Christine; Vannucci, Marina; Karakas, Cemal; Choi, William; Ma, Lihua; Maletić-Savatić, Mirjana

2013-10-01

Metabolic processes are essential for cellular function and survival. We are interested in inferring a metabolic network in activated microglia, a major neuroimmune cell in the brain responsible for the neuroinflammation associated with neurological diseases, based on a set of quantified metabolites. To achieve this, we apply the Bayesian adaptive graphical lasso with informative priors that incorporate known relationships between covariates. To encourage sparsity, the Bayesian graphical lasso places double exponential priors on the off-diagonal entries of the precision matrix. The Bayesian adaptive graphical lasso allows each double exponential prior to have a unique shrinkage parameter. These shrinkage parameters share a common gamma hyperprior. We extend this model to create an informative prior structure by formulating tailored hyperpriors on the shrinkage parameters. By choosing parameter values for each hyperprior that shift probability mass toward zero for nodes that are close together in a reference network, we encourage edges between covariates with known relationships. This approach can improve the reliability of network inference when the sample size is small relative to the number of parameters to be estimated. When applied to the data on activated microglia, the inferred network includes both known relationships and associations of potential interest for further investigation.
Inferring metabolic networks using the Bayesian adaptive graphical lasso with informative priors

PubMed Central

PETERSON, CHRISTINE; VANNUCCI, MARINA; KARAKAS, CEMAL; CHOI, WILLIAM; MA, LIHUA; MALETIĆ-SAVATIĆ, MIRJANA

2014-01-01

Metabolic processes are essential for cellular function and survival. We are interested in inferring a metabolic network in activated microglia, a major neuroimmune cell in the brain responsible for the neuroinflammation associated with neurological diseases, based on a set of quantified metabolites. To achieve this, we apply the Bayesian adaptive graphical lasso with informative priors that incorporate known relationships between covariates. To encourage sparsity, the Bayesian graphical lasso places double exponential priors on the off-diagonal entries of the precision matrix. The Bayesian adaptive graphical lasso allows each double exponential prior to have a unique shrinkage parameter. These shrinkage parameters share a common gamma hyperprior. We extend this model to create an informative prior structure by formulating tailored hyperpriors on the shrinkage parameters. By choosing parameter values for each hyperprior that shift probability mass toward zero for nodes that are close together in a reference network, we encourage edges between covariates with known relationships. This approach can improve the reliability of network inference when the sample size is small relative to the number of parameters to be estimated. When applied to the data on activated microglia, the inferred network includes both known relationships and associations of potential interest for further investigation. PMID:24533172
From Molecular Circuit Dysfunction to Disease: Case Studies in Epilepsy, Traumatic Brain Injury, and Alzheimer's Disease.

PubMed

Dulla, Chris G; Coulter, Douglas A; Ziburkus, Jokubas

2016-06-01

Complex circuitry with feed-forward and feed-back systems regulate neuronal activity throughout the brain. Cell biological, electrical, and neurotransmitter systems enable neural networks to process and drive the entire spectrum of cognitive, behavioral, and motor functions. Simultaneous orchestration of distinct cells and interconnected neural circuits relies on hundreds, if not thousands, of unique molecular interactions. Even single molecule dysfunctions can be disrupting to neural circuit activity, leading to neurological pathology. Here, we sample our current understanding of how molecular aberrations lead to disruptions in networks using three neurological pathologies as exemplars: epilepsy, traumatic brain injury (TBI), and Alzheimer's disease (AD). Epilepsy provides a window into how total destabilization of network balance can occur. TBI is an abrupt physical disruption that manifests in both acute and chronic neurological deficits. Last, in AD progressive cell loss leads to devastating cognitive consequences. Interestingly, all three of these neurological diseases are interrelated. The goal of this review, therefore, is to identify molecular changes that may lead to network dysfunction, elaborate on how altered network activity and circuit structure can contribute to neurological disease, and suggest common threads that may lie at the heart of molecular circuit dysfunction. © The Author(s) 2015.
Development of an In-Situ Decommissioning Sensor Network Test Bed for Structural Condition Monitoring - 12156

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

Zeigler, Kristine E.; Ferguson, Blythe A.

2012-07-01

The Savannah River National Laboratory (SRNL) has established an In Situ Decommissioning (ISD) Sensor Network Test Bed, a unique, small scale, configurable environment, for the assessment of prospective sensors on actual ISD system material, at minimal cost. The Department of Energy (DOE) is presently implementing permanent entombment of contaminated, large nuclear structures via ISD. The ISD end state consists of a grout-filled concrete civil structure within the concrete frame of the original building. Validation of ISD system performance models and verification of actual system conditions can be achieved through the development a system of sensors to monitor the materials andmore » condition of the structure. The ISD Sensor Network Test Bed has been designed and deployed to addresses the DOE-Environmental Management Technology Need to develop a remote monitoring system to determine and verify ISD system performance. Commercial off-the-shelf sensors have been installed on concrete blocks taken from walls of the P Reactor Building at the Savannah River Site. Deployment of this low-cost structural monitoring system provides hands-on experience with sensor networks. The initial sensor system consists of groutable thermistors for temperature and moisture monitoring, strain gauges for crack growth monitoring, tilt-meters for settlement monitoring, and a communication system for data collection. Baseline data and lessons learned from system design and installation and initial field testing will be utilized for future ISD sensor network development and deployment. The Sensor Network Test Bed at SRNL uses COTS sensors on concrete blocks from the outer wall of the P Reactor Building to measure conditions expected to occur in ISD structures. Knowledge and lessons learned gained from installation, testing, and monitoring of the equipment will be applied to sensor installation in a meso-scale test bed at FIU and in future ISD structures. The initial data collected from the sensors installed on the P Reactor Building blocks define the baseline materials condition of the P Reactor ISD external concrete structure. Continued monitoring of the blocks will enable evaluation of the effects of aging on the P Reactor ISD structure. The collected data will support validation of the material degradation model and assessment of the condition of the ISD structure over time. The following are recommendations for continued development of the ISD Sensor Network Test Bed: - Establish a long-term monitoring program using the concrete blocks with existing sensor and/or additional sensors for trending the concrete materials and structural condition; - Continue development of a stand-alone test bed sensor system that is self-powered and provides wireless transmission of data to a user-accessible dashboard; - Develop and implement periodic NDE/DE characterization of the concrete blocks to provide verification and validation for the measurements obtained through the sensor system and concrete degradation model(s). (authors)« less

Analysis of dispersion relation in three-dimensional single gyroid

NASA Astrophysics Data System (ADS)

Jheng, Pei-Lun; Hung, Yu-Chueh

2016-03-01

Gyroid is a type of three-dimensional chiral structures and has been found in many insect species. Besides the photonic crystal properties exhibited by gyroid structures, the chirality and gyroid network morphology also provide unique opportunities for manipulating propagation of light. In this work, we present studies based on finite-difference time domain (FDTD) method for analyzing the dispersion relation characteristics of dielectric single gyroid (SG) metamaterials. The band structures, transmission spectrum, dispersion surfaces, equifrequency contours (EFCs) of SG metamaterials are examined. Some interesting wave guiding characteristics, such as negative refraction and collimation, are presented and discussed. We also show how these optical properties are predicted by analyzing the EFCs at different frequencies. These results are crucial for the design of functional devices at optical frequencies based on dielectric single gyroid metamaterials.
Fiber Bragg gratings for civil engineering applications

NASA Astrophysics Data System (ADS)

Maher, Mohamed H.; Tabrizi, Khosrow; Prohaska, John D.; Snitzer, Elias

1996-04-01

Fiber Bragg gratings sensors offer a unique opportunity in civil engineering. They can be configured as a low noise distributed sensor network for measuring mechanical deformations and temperature. They are ideally suited for strain measurements of high modulus structural materials such as steel and concrete. There is considerable interest in the use of these sensors for infrastructural nondestructive testing and there have been several papers on the subject. We present some results of our experiments with fiber Bragg sensors as applied to structural engineering. These include the use of fiber gratings to measure strain behavior of steel, reinforced concrete, and some preliminary results on bituminous materials, such as asphalt concrete. In nondestructive testing using fiber Bragg gratings of structural materials the packaging of the sensors is important and is discussed.
Excessive coupling of the salience network with intrinsic neurocognitive brain networks during rectal distension in adolescents with irritable bowel syndrome: a preliminary report

PubMed Central

Liu, Xiaolin; Silverman, Alan; Kern, Mark; Ward, B. Douglas; Li, Shi-Jiang; Shaker, Reza; Sood, Manu R.

2015-01-01

Background The neural network mechanisms underlying visceral hypersensitivity in irritable bowel syndrome (IBS) are incompletely understood. It has been proposed that an intrinsic salience network plays an important role in chronic pain and IBS symptoms. Using neuroimaging, we examined brain responses to rectal distension in adolescent IBS patients, focusing on determining the alteration of salience network integrity in IBS and its functional implications in current theoretical frameworks. We hypothesized that (1) brain responses to visceral stimulation in adolescents are similar to those in adults, and (2) IBS is associated with an altered salience network interaction with other neurocognitive networks, particularly the default mode network (DMN) and executive control network (ECN), as predicted by the theoretical models. Methods IBS patients and controls received subliminal and liminal rectal distension during imaging. Stimulus-induced brain activations were determined. Salience network integrity was evaluated by functional connectivity of its seed regions activated by rectal distension in the insular and cingulate cortices. Key Results Compared with controls, IBS patients demonstrated greater activation to rectal distension in neural structures of the homeostatic afferent and emotional arousal networks, especially the anterior cingulate and insular cortices. Greater brain responses to liminal vs. subliminal distension were observed in both groups. Particularly, IBS is uniquely associated with an excessive coupling of the salience network with the DMN and ECN in their key frontal and parietal node areas. Conclusions & Inferences Our study provided consistent evidence supporting the theoretical predictions of altered salience network functioning as a neuropathological mechanism of IBS symptoms. PMID:26467966
Network analysis of surgical innovation: Measuring value and the virality of diffusion in robotic surgery.

PubMed

Garas, George; Cingolani, Isabella; Panzarasa, Pietro; Darzi, Ara; Athanasiou, Thanos

2017-01-01

Existing surgical innovation frameworks suffer from a unifying limitation, their qualitative nature. A rigorous approach to measuring surgical innovation is needed that extends beyond detecting simply publication, citation, and patent counts and instead uncovers an implementation-based value from the structure of the entire adoption cascades produced over time by diffusion processes. Based on the principles of evidence-based medicine and existing surgical regulatory frameworks, the surgical innovation funnel is described. This illustrates the different stages through which innovation in surgery typically progresses. The aim is to propose a novel and quantitative network-based framework that will permit modeling and visualizing innovation diffusion cascades in surgery and measuring virality and value of innovations. Network analysis of constructed citation networks of all articles concerned with robotic surgery (n = 13,240, Scopus®) was performed (1974-2014). The virality of each cascade was measured as was innovation value (measured by the innovation index) derived from the evidence-based stage occupied by the corresponding seed article in the surgical innovation funnel. The network-based surgical innovation metrics were also validated against real world big data (National Inpatient Sample-NIS®). Rankings of surgical innovation across specialties by cascade size and structural virality (structural depth and width) were found to correlate closely with the ranking by innovation value (Spearman's rank correlation coefficient = 0.758 (p = 0.01), 0.782 (p = 0.008), 0.624 (p = 0.05), respectively) which in turn matches the ranking based on real world big data from the NIS® (Spearman's coefficient = 0.673;p = 0.033). Network analysis offers unique new opportunities for understanding, modeling and measuring surgical innovation, and ultimately for assessing and comparing generative value between different specialties. The novel surgical innovation metrics developed may prove valuable especially in guiding policy makers, funding bodies, surgeons, and healthcare providers in the current climate of competing national priorities for investment.
Network analysis of surgical innovation: Measuring value and the virality of diffusion in robotic surgery

PubMed Central

Cingolani, Isabella; Panzarasa, Pietro; Darzi, Ara; Athanasiou, Thanos

2017-01-01

Background Existing surgical innovation frameworks suffer from a unifying limitation, their qualitative nature. A rigorous approach to measuring surgical innovation is needed that extends beyond detecting simply publication, citation, and patent counts and instead uncovers an implementation-based value from the structure of the entire adoption cascades produced over time by diffusion processes. Based on the principles of evidence-based medicine and existing surgical regulatory frameworks, the surgical innovation funnel is described. This illustrates the different stages through which innovation in surgery typically progresses. The aim is to propose a novel and quantitative network-based framework that will permit modeling and visualizing innovation diffusion cascades in surgery and measuring virality and value of innovations. Materials and methods Network analysis of constructed citation networks of all articles concerned with robotic surgery (n = 13,240, Scopus®) was performed (1974–2014). The virality of each cascade was measured as was innovation value (measured by the innovation index) derived from the evidence-based stage occupied by the corresponding seed article in the surgical innovation funnel. The network-based surgical innovation metrics were also validated against real world big data (National Inpatient Sample–NIS®). Results Rankings of surgical innovation across specialties by cascade size and structural virality (structural depth and width) were found to correlate closely with the ranking by innovation value (Spearman’s rank correlation coefficient = 0.758 (p = 0.01), 0.782 (p = 0.008), 0.624 (p = 0.05), respectively) which in turn matches the ranking based on real world big data from the NIS® (Spearman’s coefficient = 0.673;p = 0.033). Conclusion Network analysis offers unique new opportunities for understanding, modeling and measuring surgical innovation, and ultimately for assessing and comparing generative value between different specialties. The novel surgical innovation metrics developed may prove valuable especially in guiding policy makers, funding bodies, surgeons, and healthcare providers in the current climate of competing national priorities for investment. PMID:28841648
Structural Organization of the Laryngeal Motor Cortical Network and Its Implication for Evolution of Speech Production.

PubMed

Kumar, Veena; Croxson, Paula L; Simonyan, Kristina

2016-04-13

The laryngeal motor cortex (LMC) is essential for the production of learned vocal behaviors because bilateral damage to this area renders humans unable to speak but has no apparent effect on innate vocalizations such as human laughing and crying or monkey calls. Several hypotheses have been put forward attempting to explain the evolutionary changes from monkeys to humans that potentially led to enhanced LMC functionality for finer motor control of speech production. These views, however, remain limited to the position of the larynx area within the motor cortex, as well as its connections with the phonatory brainstem regions responsible for the direct control of laryngeal muscles. Using probabilistic diffusion tractography in healthy humans and rhesus monkeys, we show that, whereas the LMC structural network is largely comparable in both species, the LMC establishes nearly 7-fold stronger connectivity with the somatosensory and inferior parietal cortices in humans than in macaques. These findings suggest that important "hard-wired" components of the human LMC network controlling the laryngeal component of speech motor output evolved from an already existing, similar network in nonhuman primates. However, the evolution of enhanced LMC-parietal connections likely allowed for more complex synchrony of higher-order sensorimotor coordination, proprioceptive and tactile feedback, and modulation of learned voice for speech production. The role of the primary motor cortex in the formation of a comprehensive network controlling speech and language has been long underestimated and poorly studied. Here, we provide comparative and quantitative evidence for the significance of this region in the control of a highly learned and uniquely human behavior: speech production. From the viewpoint of structural network organization, we discuss potential evolutionary advances of enhanced temporoparietal cortical connections with the laryngeal motor cortex in humans compared with nonhuman primates that may have contributed to the development of finer vocal motor control necessary for speech production. Copyright © 2016 the authors 0270-6474/16/364170-12$15.00/0.
Co-Option and De Novo Gene Evolution Underlie Molluscan Shell Diversity

PubMed Central

Aguilera, Felipe; McDougall, Carmel

2017-01-01

Abstract Molluscs fabricate shells of incredible diversity and complexity by localized secretions from the dorsal epithelium of the mantle. Although distantly related molluscs express remarkably different secreted gene products, it remains unclear if the evolution of shell structure and pattern is underpinned by the differential co-option of conserved genes or the integration of lineage-specific genes into the mantle regulatory program. To address this, we compare the mantle transcriptomes of 11 bivalves and gastropods of varying relatedness. We find that each species, including four Pinctada (pearl oyster) species that diverged within the last 20 Ma, expresses a unique mantle secretome. Lineage- or species-specific genes comprise a large proportion of each species’ mantle secretome. A majority of these secreted proteins have unique domain architectures that include repetitive, low complexity domains (RLCDs), which evolve rapidly, and have a proclivity to expand, contract and rearrange in the genome. There are also a large number of secretome genes expressed in the mantle that arose before the origin of gastropods and bivalves. Each species expresses a unique set of these more ancient genes consistent with their independent co-option into these mantle gene regulatory networks. From this analysis, we infer lineage-specific secretomes underlie shell diversity, and include both rapidly evolving RLCD-containing proteins, and the continual recruitment and loss of both ancient and recently evolved genes into the periphery of the regulatory network controlling gene expression in the mantle epithelium. PMID:28053006
ER bodies in plants of the Brassicales order: biogenesis and association with innate immunity

PubMed Central

Nakano, Ryohei T.; Yamada, Kenji; Bednarek, Paweł; Nishimura, Mikio; Hara-Nishimura, Ikuko

2014-01-01

The endoplasmic reticulum (ER) forms highly organized network structures composed of tubules and cisternae. Many plant species develop additional ER-derived structures, most of which are specific for certain groups of species. In particular, a rod-shaped structure designated as the ER body is produced by plants of the Brassicales order, which includes Arabidopsis thaliana. Genetic analyses and characterization of A. thaliana mutants possessing a disorganized ER morphology or lacking ER bodies have provided insights into the highly organized mechanisms responsible for the formation of these unique ER structures. The accumulation of proteins specific for the ER body within the ER plays an important role in the formation of ER bodies. However, a mutant that exhibits morphological defects of both the ER and ER bodies has not been identified. This suggests that plants in the Brassicales order have evolved novel mechanisms for the development of this unique organelle, which are distinct from those used to maintain generic ER structures. In A. thaliana, ER bodies are ubiquitous in seedlings and roots, but rare in rosette leaves. Wounding of rosette leaves induces de novo formation of ER bodies, suggesting that these structures are associated with resistance against pathogens and/or herbivores. ER bodies accumulate a large amount of β-glucosidases, which can produce substances that potentially protect against invading pests. Biochemical studies have determined that the enzymatic activities of these β-glucosidases are enhanced during cell collapse. These results suggest that ER bodies are involved in plant immunity, although there is no direct evidence of this. In this review, we provide recent perspectives of ER and ER body formation in A. thaliana, and discuss clues for the functions of ER bodies. We highlight defense strategies against biotic stress that are unique for the Brassicales order, and discuss how ER structures could contribute to these strategies. PMID:24653729
An exploratory comparison of name generator content: Data from rural India.

PubMed

Shakya, Holly B; Christakis, Nicholas A; Fowler, James H

2017-01-01

Since the 1970s sociologists have explored the best means for measuring social networks, although few name generator analyses have used sociocentric data or data from developing countries, partly because sociocentric studies in developing countries have been scant. Here, we analyze 12 different name generators used in a sociocentric network study conducted in 75 villages in rural Karnataka, India. Having unusual sociocentric data from a non-Western context allowed us to extend previous name generator research through the unique analyses of network structural measures, an extensive consideration of homophily, and investigation of status difference between egos and alters. We found that domestic interaction questions generated networks that were highly clustered and highly centralized. Similarity between respondents and their nominated contacts was strongest for gender, caste, and religion. We also found that domestic interaction name generators yielded the most homogeneous ties, while advice questions yielded the most heterogeneous. Participants were generally more likely to nominate those of higher social status, although certain questions, such as who participants talk to uncovered more egalitarian relationships, while other name generators elicited the names of social contacts distinctly higher or lower in status than the respondent. Some questions also seemed to uncover networks that were specific to the cultural context, suggesting that network researchers should balance local relevance with global generalizability when choosing name generators.
Visualization and Analysis of Wireless Sensor Network Data for Smart Civil Structure Applications Based On Spatial Correlation Technique

NASA Astrophysics Data System (ADS)

Chowdhry, Bhawani Shankar; White, Neil M.; Jeswani, Jai Kumar; Dayo, Khalil; Rathi, Manorma

2009-07-01

Disasters affecting infrastructure, such as the 2001 earthquakes in India, 2005 in Pakistan, 2008 in China and the 2004 tsunami in Asia, provide a common need for intelligent buildings and smart civil structures. Now, imagine massive reductions in time to get the infrastructure working again, realtime information on damage to buildings, massive reductions in cost and time to certify that structures are undamaged and can still be operated, reductions in the number of structures to be rebuilt (if they are known not to be damaged). Achieving these ideas would lead to huge, quantifiable, long-term savings to government and industry. Wireless sensor networks (WSNs) can be deployed in buildings to make any civil structure both smart and intelligent. WSNs have recently gained much attention in both public and research communities because they are expected to bring a new paradigm to the interaction between humans, environment, and machines. This paper presents the deployment of WSN nodes in the Top Quality Centralized Instrumentation Centre (TQCIC). We created an ad hoc networking application to collect real-time data sensed from the nodes that were randomly distributed throughout the building. If the sensors are relocated, then the application automatically reconfigures itself in the light of the new routing topology. WSNs are event-based systems that rely on the collective effort of several micro-sensor nodes, which are continuously observing a physical phenomenon. WSN applications require spatially dense sensor deployment in order to achieve satisfactory coverage. The degree of spatial correlation increases with the decreasing inter-node separation. Energy consumption is reduced dramatically by having only those sensor nodes with unique readings transmit their data. We report on an algorithm based on a spatial correlation technique that assures high QoS (in terms of SNR) of the network as well as proper utilization of energy, by suppressing redundant data transmission. The visualization and analysis of WSN data are presented in a Windows-based user interface.
Advanced mobility handover for mobile IPv6 based wireless networks.

PubMed

Safa Sadiq, Ali; Fisal, Norsheila Binti; Ghafoor, Kayhan Zrar; Lloret, Jaime

2014-01-01

We propose an Advanced Mobility Handover scheme (AMH) in this paper for seamless mobility in MIPv6-based wireless networks. In the proposed scheme, the mobile node utilizes a unique home IPv6 address developed to maintain communication with other corresponding nodes without a care-of-address during the roaming process. The IPv6 address for each MN during the first round of AMH process is uniquely identified by HA using the developed MN-ID field as a global permanent, which is identifying uniquely the IPv6 address of MN. Moreover, a temporary MN-ID is generated by access point each time an MN is associated with a particular AP and temporarily saved in a developed table inside the AP. When employing the AMH scheme, the handover process in the network layer is performed prior to its default time. That is, the mobility handover process in the network layer is tackled by a trigger developed AMH message to the next access point. Thus, a mobile node keeps communicating with the current access point while the network layer handover is executed by the next access point. The mathematical analyses and simulation results show that the proposed scheme performs better as compared with the existing approaches.
Structural and practical identifiability analysis of S-system.

PubMed

Zhan, Choujun; Li, Benjamin Yee Shing; Yeung, Lam Fat

2015-12-01

In the field of systems biology, biological reaction networks are usually modelled by ordinary differential equations. A sub-class, the S-systems representation, is a widely used form of modelling. Existing S-systems identification techniques assume that the system itself is always structurally identifiable. However, due to practical limitations, biological reaction networks are often only partially measured. In addition, the captured data only covers a limited trajectory, therefore data can only be considered as a local snapshot of the system responses with respect to the complete set of state trajectories over the entire state space. Hence the estimated model can only reflect partial system dynamics and may not be unique. To improve the identification quality, the structural and practical identifiablility of S-system are studied. The S-system is shown to be identifiable under a set of assumptions. Then, an application on yeast fermentation pathway was conducted. Two case studies were chosen; where the first case is based on a larger state trajectories and the second case is based on a smaller one. By expanding the dataset which span a relatively larger state space, the uncertainty of the estimated system can be reduced. The results indicated that initial concentration is related to the practical identifiablity.
Geographic information modeling of Econet of Northwestern Federal District territory on graph theory basis

NASA Astrophysics Data System (ADS)

Kopylova, N. S.; Bykova, A. A.; Beregovoy, D. N.

2018-05-01

Based on the landscape-geographical approach, a structural and logical scheme for the Northwestern Federal District Econet has been developed, which can be integrated into the federal and world ecological network in order to improve the environmental infrastructure of the region. The method of Northwestern Federal District Econet organization on the basis of graph theory by means of the Quantum GIS geographic information system is proposed as an effective mean of preserving and recreating the unique biodiversity of landscapes, regulation of the sphere of environmental protection.
Cellulose-pectin composite hydrogels: Intermolecular interactions and material properties depend on order of assembly.

PubMed

Lopez-Sanchez, Patricia; Martinez-Sanz, Marta; Bonilla, Mauricio R; Wang, Dongjie; Gilbert, Elliot P; Stokes, Jason R; Gidley, Michael J

2017-04-15

Plant cell walls have a unique combination of strength and flexibility however, further investigations are required to understand how those properties arise from the assembly of the relevant biopolymers. Recent studies indicate that Ca 2+ -pectates can act as load-bearing components in cell walls. To investigate this proposed role of pectins, bioinspired wall models were synthesised based on bacterial cellulose containing pectin-calcium gels by varying the order of assembly of cellulose/pectin networks, pectin degree of methylesterification and calcium concentration. Hydrogels in which pectin-calcium assembly occurred prior to cellulose synthesis showed evidence for direct cellulose/pectin interactions from small-angle scattering (SAXS and SANS), had the densest networks and the lowest normal stress. The strength of the pectin-calcium gel affected cellulose structure, crystallinity and material properties. The results highlight the importance of the order of assembly on the properties of cellulose composite networks and support the role of pectin in the mechanics of cell walls. Copyright © 2017 Elsevier Ltd. All rights reserved.
Atomic switch networks—nanoarchitectonic design of a complex system for natural computing

NASA Astrophysics Data System (ADS)

Demis, E. C.; Aguilera, R.; Sillin, H. O.; Scharnhorst, K.; Sandouk, E. J.; Aono, M.; Stieg, A. Z.; Gimzewski, J. K.

2015-05-01

Self-organized complex systems are ubiquitous in nature, and the structural complexity of these natural systems can be used as a model to design new classes of functional nanotechnology based on highly interconnected networks of interacting units. Conventional fabrication methods for electronic computing devices are subject to known scaling limits, confining the diversity of possible architectures. This work explores methods of fabricating a self-organized complex device known as an atomic switch network and discusses its potential utility in computing. Through a merger of top-down and bottom-up techniques guided by mathematical and nanoarchitectonic design principles, we have produced functional devices comprising nanoscale elements whose intrinsic nonlinear dynamics and memorization capabilities produce robust patterns of distributed activity and a capacity for nonlinear transformation of input signals when configured in the appropriate network architecture. Their operational characteristics represent a unique potential for hardware implementation of natural computation, specifically in the area of reservoir computing—a burgeoning field that investigates the computational aptitude of complex biologically inspired systems.
Template-directed assembly of metal-chalcogenide nanocrystals into ordered mesoporous networks.

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

Vamvasakis, Ioannis; Subrahmanyam, Kota S.; Kanatzidis, Mercouri G.

Although great progress in the synthesis of porous networks of metal and metal oxide nanoparticles with highly accessible pore surface and ordered mesoscale pores has been achieved, synthesis of assembled 3D mesostructures of metal-chalcogenide nanocrystals is still challenging. In this work we demonstrate that ordered mesoporous networks, which comprise well-defined interconnected metal sulfide nanocrystals, can be prepared through a polymer-templated oxidative polymerization process. The resulting self-assembled mesostructures that were obtained after solvent extraction of the polymer template impart the unique combination of light-emitting metal chalcogenide nanocrystals, three-dimensional open-pore structure, high surface area, and uniform pores. We show that the poremore » surface of these materials is active and accessible to incoming molecules, exhibiting high photocatalytic activity and stability, for instance, in oxidation of 1-phenylethanol into acetophenone. We demonstrate through appropriate selection of the synthetic components that this method is general to prepare ordered mesoporous materials from metal chalcogenide nanocrystals with various sizes and compositions.« less
Agricultural Trade Networks and Patterns of Economic Development

PubMed Central

Shutters, Shade T.; Muneepeerakul, Rachata

2012-01-01

International trade networks are manifestations of a complex combination of diverse underlying factors, both natural and social. Here we apply social network analytics to the international trade network of agricultural products to better understand the nature of this network and its relation to patterns of international development. Using a network tool known as triadic analysis we develop triad significance profiles for a series of agricultural commodities traded among countries. Results reveal a novel network “superfamily” combining properties of biological information processing networks and human social networks. To better understand this unique network signature, we examine in more detail the degree and triadic distributions within the trade network by country and commodity. Our results show that countries fall into two very distinct classes based on their triadic frequencies. Roughly 165 countries fall into one class while 18, all highly isolated with respect to international agricultural trade, fall into the other. Only Vietnam stands out as a unique case. Finally, we show that as a country becomes less isolated with respect to number of trading partners, the country's triadic signature follows a predictable trajectory that may correspond to a trajectory of development. PMID:22768310
Isotropic band gaps and freeform waveguides observed in hyperuniform disordered photonic solids

PubMed Central

Man, Weining; Florescu, Marian; Williamson, Eric Paul; He, Yingquan; Hashemizad, Seyed Reza; Leung, Brian Y. C.; Liner, Devin Robert; Torquato, Salvatore; Chaikin, Paul M.; Steinhardt, Paul J.

2013-01-01

Recently, disordered photonic media and random textured surfaces have attracted increasing attention as strong light diffusers with broadband and wide-angle properties. We report the experimental realization of an isotropic complete photonic band gap (PBG) in a 2D disordered dielectric structure. This structure is designed by a constrained optimization method, which combines advantages of both isotropy due to disorder and controlled scattering properties due to low-density fluctuations (hyperuniformity) and uniform local topology. Our experiments use a modular design composed of Al2O3 walls and cylinders arranged in a hyperuniform disordered network. We observe a complete PBG in the microwave region, in good agreement with theoretical simulations, and show that the intrinsic isotropy of this unique class of PBG materials enables remarkable design freedom, including the realization of waveguides with arbitrary bending angles impossible in photonic crystals. This experimental verification of a complete PBG and realization of functional defects in this unique class of materials demonstrate their potential as building blocks for precise manipulation of photons in planar optical microcircuits and has implications for disordered acoustic and electronic band gap materials. PMID:24043795
Facile synthesis of 3D silicon/carbon nanotube capsule composites as anodes for high-performance lithium-ion batteries

NASA Astrophysics Data System (ADS)

Yue, Xinyang; Sun, Wang; Zhang, Jing; Wang, Fang; Sun, Kening

2016-10-01

Carbon nanotubes have attracted widespread attention as ideal materials for Lithium-ion batteries (LIBs) due to their excellent conductivity, mechanical flexibility, chemical stability and extremely large surface area. Here, three-dimensional (3D) silicon/carbon nanotube capsule composites (Si/CNCs) are firstly prepared via water-in-oil (W/O) emulsion technique with more than 75 wt% loading amount of silicon. CNCs with unique hollow sphere structure act as a 3D interconnected conductive network skeleton, and the cross-linked carbon nanotubes (CNTs) of CNCs can effectively enhance the strength, flexibility and conductivity of the electrode. This Si/CNCs can not only alleviate the volume expansion, but also effectively improve the electrochemical performance of the LIBs. Such Si/CNCs electrode with the unique structure achieves a high initial discharge specific capacity of 2950 mAh g-1 and retains 1226 mAh g-1 after 100 cycles at 0.5 A g-1, as well as outstanding rate performance of 547 mAh g-1 at 10 A g-1.
Novel Piezoelectric Paper‐Based Flexible Nanogenerators Composed of BaTiO3 Nanoparticles and Bacterial Cellulose

PubMed Central

Zhang, Guangjie; Liao, Qingliang; Zhang, Zheng; Liang, Qijie; Zhao, Yingli; Zheng, Xin

2015-01-01

A piezoelectric paper based on BaTiO3 (BTO) nanoparticles and bacterial cellulose (BC) with excellent output properties for application of nanogenerators (NGs) is reported. A facile and scalable vacuum filtration method is used to fabricate the piezoelectric paper. The BTO/BC piezoelectric paper based NG shows outstanding output performance with open‐circuit voltage of 14 V and short‐circuit current density of 190 nA cm−2. The maximum power density generated by this unique BTO/BC structure is more than ten times higher than BTO/polydimethylsiloxane structure. In bending conditions, the NG device can generate output voltage of 1.5 V, which is capable of driving a liquid crystal display screen. The improved performance can be ascribed to homogeneous distribution of piezoelectric BTO nanoparticles in the BC matrix as well as the enhanced stress on piezoelectric nanoparticles implemented by the unique percolated networks of BC nanofibers. The flexible BTO/BC piezoelectric paper based NG is lightweight, eco‐friendly, and cost‐effective, which holds great promises for achieving wearable or implantable energy harvesters and self‐powered electronics. PMID:27774389

The Impact of Drainage Network Structure on Flooding in a Small Urban Watershed in Metropolitan Baltimore, MD

NASA Astrophysics Data System (ADS)

Meierdiercks, K. L.; Smith, J. A.; Miller, A. J.

2006-12-01

The impact of urban development on watershed-scale hydrology is examined in a small urban watershed in the Metropolitan Baltimore area. Analyses focus on Dead Run, a 14.3 km2 tributary of the Gwynns Falls, which is the principal study watershed of the Baltimore Ecosystem Study. Field observations of rainfall and discharge have been collected for storms occurring in the 2003, 2004, and 2005 warm seasons including the flood of record for the USGS Dead Run at Franklintown gage (7 July 2004), in which 5 inches of rain fell in less than 4 hours. Dead Run has stream gages at 6 locations with drainage areas ranging from 1.2 to 14.3 km2. Hydrologic response to storm events varies greatly in each of the subwatersheds due to the diverse development types located there. These subwatersheds range in land use from medium-density residential, with and without stormwater management control, to commercial/light industrial with large impervious lots and an extensive network of stormwater management ponds. The unique response of each subwatershed is captured using field observations in conjunction with the EPA Stormwater Management Model (SWMM), which routes storm runoff over the land surface and through the drainage network of a watershed. Of particular importance to flood response is the structure of the drainage network (both surface channels and storm drain network) and its connectivity to preferential flow paths within the watershed. The Dead Run drainage network has been delineated using geospatial data derived from aerial photography and engineering planning drawings. Model analyses are used to examine the characteristics of flow paths that control flood response in urban watersheds. These analyses aim to identify patterns in urban flow pathways and use those patterns to predict response in other urban watersheds.
Construction of monomer-free, highly crosslinked, water-compatible polymers.

PubMed

Dailing, E A; Lewis, S H; Barros, M D; Stansbury, J W

2014-12-01

Polymeric dental adhesives require the formation of densely crosslinked network structures to best ensure mechanical strength and durability in clinical service. Monomeric precursors to these materials typically consist of mixtures of hydrophilic and hydrophobic components that potentially undergo phase separation in the presence of low concentrations of water, which is detrimental to material performance and has motivated significant investigation into formulations that reduce this effect. We have investigated an approach to network formation based on nanogels that are dispersed in inert solvent and directly polymerized into crosslinked polymers. Monomers of various hydrophilic or hydrophobic characteristics were copolymerized into particulate nanogels bearing internal and external polymerizable functionality. Nanogel dispersions were stable at high concentrations in acetone or, with some exceptions, in water and produced networks with a wide range of mechanical properties. Networks formed rapidly upon light activation and reached high conversion with extremely low volumetric shrinkage. Prepolymerizing monomers into reactive nanostructures significantly changes how hydrophobic materials respond to water compared with networks obtained from polymerizations involving free monomer. The modulus of fully hydrated networks formed solely from nanogels was shown to equal or exceed the modulus in the dry state for networks based on nanogels containing a hydrophobic dimethacrylate and hydrophilic monomethacrylate, a result that was not observed in a hydroxyethyl methacrylate (HEMA) homopolymer or in networks formed from nanogels copolymerized with HEMA. These results highlight the unique approach to network development from nanoscale precursors and properties that have direct implications in functional dental materials. © International & American Associations for Dental Research.
Limited urban growth: London's street network dynamics since the 18th century.

PubMed

Masucci, A Paolo; Stanilov, Kiril; Batty, Michael

2013-01-01

We investigate the growth dynamics of Greater London defined by the administrative boundary of the Greater London Authority, based on the evolution of its street network during the last two centuries. This is done by employing a unique dataset, consisting of the planar graph representation of nine time slices of Greater London's road network spanning 224 years, from 1786 to 2010. Within this time-frame, we address the concept of the metropolitan area or city in physical terms, in that urban evolution reveals observable transitions in the distribution of relevant geometrical properties. Given that London has a hard boundary enforced by its long standing green belt, we show that its street network dynamics can be described as a fractal space-filling phenomena up to a capacitated limit, whence its growth can be predicted with a striking level of accuracy. This observation is confirmed by the analytical calculation of key topological properties of the planar graph, such as the topological growth of the network and its average connectivity. This study thus represents an example of a strong violation of Gibrat's law. In particular, we are able to show analytically how London evolves from a more loop-like structure, typical of planned cities, toward a more tree-like structure, typical of self-organized cities. These observations are relevant to the discourse on sustainable urban planning with respect to the control of urban sprawl in many large cities which have developed under the conditions of spatial constraints imposed by green belts and hard urban boundaries.
Mapping human brain networks with cortico-cortical evoked potentials

PubMed Central

Keller, Corey J.; Honey, Christopher J.; Mégevand, Pierre; Entz, Laszlo; Ulbert, Istvan; Mehta, Ashesh D.

2014-01-01

The cerebral cortex forms a sheet of neurons organized into a network of interconnected modules that is highly expanded in humans and presumably enables our most refined sensory and cognitive abilities. The links of this network form a fundamental aspect of its organization, and a great deal of research is focusing on understanding how information flows within and between different regions. However, an often-overlooked element of this connectivity regards a causal, hierarchical structure of regions, whereby certain nodes of the cortical network may exert greater influence over the others. While this is difficult to ascertain non-invasively, patients undergoing invasive electrode monitoring for epilepsy provide a unique window into this aspect of cortical organization. In this review, we highlight the potential for cortico-cortical evoked potential (CCEP) mapping to directly measure neuronal propagation across large-scale brain networks with spatio-temporal resolution that is superior to traditional neuroimaging methods. We first introduce effective connectivity and discuss the mechanisms underlying CCEP generation. Next, we highlight how CCEP mapping has begun to provide insight into the neural basis of non-invasive imaging signals. Finally, we present a novel approach to perturbing and measuring brain network function during cognitive processing. The direct measurement of CCEPs in response to electrical stimulation represents a potentially powerful clinical and basic science tool for probing the large-scale networks of the human cerebral cortex. PMID:25180306
M13 Bacteriophage-Based Self-Assembly Structures and Their Functional Capabilities.

PubMed

Moon, Jong-Sik; Kim, Won-Geun; Kim, Chuntae; Park, Geun-Tae; Heo, Jeong; Yoo, So Y; Oh, Jin-Woo

2015-06-01

Controlling the assembly of basic structural building blocks in a systematic and orderly fashion is an emerging issue in various areas of science and engineering such as physics, chemistry, material science, biological engineering, and electrical engineering. The self-assembly technique, among many other kinds of ordering techniques, has several unique advantages and the M13 bacteriophage can be utilized as part of this technique. The M13 bacteriophage (Phage) can easily be modified genetically and chemically to demonstrate specific functions. This allows for its use as a template to determine the homogeneous distribution and percolated network structures of inorganic nanostructures under ambient conditions. Inexpensive and environmentally friendly synthesis can be achieved by using the M13 bacteriophage as a novel functional building block. Here, we discuss recent advances in the application of M13 bacteriophage self-assembly structures and the future of this technology.
M13 Bacteriophage-Based Self-Assembly Structures and Their Functional Capabilities

PubMed Central

Moon, Jong-Sik; Kim, Won-Geun; Kim, Chuntae; Park, Geun-Tae; Heo, Jeong; Yoo, So Y; Oh, Jin-Woo

2015-01-01

Controlling the assembly of basic structural building blocks in a systematic and orderly fashion is an emerging issue in various areas of science and engineering such as physics, chemistry, material science, biological engineering, and electrical engineering. The self-assembly technique, among many other kinds of ordering techniques, has several unique advantages and the M13 bacteriophage can be utilized as part of this technique. The M13 bacteriophage (Phage) can easily be modified genetically and chemically to demonstrate specific functions. This allows for its use as a template to determine the homogeneous distribution and percolated network structures of inorganic nanostructures under ambient conditions. Inexpensive and environmentally friendly synthesis can be achieved by using the M13 bacteriophage as a novel functional building block. Here, we discuss recent advances in the application of M13 bacteriophage self-assembly structures and the future of this technology. PMID:26146494
Structure-property-glass transition relationships in non-isocyanate polyurethanes investigated by dynamic nanoindentation

NASA Astrophysics Data System (ADS)

Weyand, Stephan; Blattmann, Hannes; Schimpf, Vitalij; Mülhaupt, Rolf; Schwaiger, Ruth

2016-07-01

Newly developed green-chemistry approaches towards the synthesis of non-isocyanate polyurethane (NIPU) systems represent a promising alternative to polyurethanes (PU) eliminating the need for harmful ingredients. A series of NIPU systems were studied using different nanoindentation techniques in order to understand the influence of molecular parameters on the mechanical behavior. Nanoindentation revealed a unique characteristic feature of those materials, i.e. stiffening with increasing deformation. It is argued that the origin of this observed stiffening is a consequence of the thermodynamic state of the polymer network, the molecular characteristics of the chemical building blocks and resulting anisotropic elastic response of the network structure. Flat-punch nanoindentation was applied in order to characterize the constitutive viscoelastic nature of the materials. The complex modulus shows distinct changes as a function of the NIPU network topology illustrating the influence of the chemical building blocks. The reproducibility of the data indicates that the materials are homogeneous over the volumes sampled by nanoindentation. Our study demonstrates that nanoindentation is very well-suited to investigate the molecular characteristics of NIPU materials that cannot be quantified in conventional experiments. Moreover, the technique provides insight into the functional significance of complex molecular architectures thereby supporting the development of NIPU materials with tailored properties.
Reopening Openness to Experience: A Network Analysis of Four Openness to Experience Inventories.

PubMed

Christensen, Alexander P; Cotter, Katherine N; Silvia, Paul J

2018-05-10

Openness to Experience is a complex trait, the taxonomic structure of which has been widely debated. Previous research has provided greater clarity of its lower order structure by synthesizing facets across several scales related to Openness to Experience. In this study, we take a finer grained approach by investigating the item-level relations of four Openness to Experience inventories (Big Five Aspects Scale, HEXACO-100, NEO PI-3, and Woo et al.'s Openness to Experience Inventory), using a network science approach, which allowed items to form an emergent taxonomy of facets and aspects. Our results (N = 802) identified 10 distinct facets (variety-seeking, aesthetic appreciation, intellectual curiosity, diversity, openness to emotions, fantasy, imaginative, self-assessed intelligence, intellectual interests, and nontraditionalism) that largely replicate previous findings as well as three higher order aspects: two that are commonly found in the literature (intellect and experiencing; i.e., openness), and one novel aspect (open-mindedness). In addition, we demonstrate that each Openness to Experience inventory offers a unique conceptualization of the trait, and that some inventories provide broader coverage of the network space than others. Our findings establish a broader consensus of Openness to Experience at the aspect and facet level, which has important implications for researchers and the Openness to Experience inventories they use.
Advanced lesion symptom mapping analyses and implementation as BCBtoolkit.

PubMed

Foulon, Chris; Cerliani, Leonardo; Kinkingnéhun, Serge; Levy, Richard; Rosso, Charlotte; Urbanski, Marika; Volle, Emmanuelle; Thiebaut de Schotten, Michel

2018-03-01

Patients with brain lesions provide a unique opportunity to understand the functioning of the human mind. However, even when focal, brain lesions have local and remote effects that impact functionally and structurally connected circuits. Similarly, function emerges from the interaction between brain areas rather than their sole activity. For instance, category fluency requires the associations between executive, semantic, and language production functions. Here, we provide, for the first time, a set of complementary solutions for measuring the impact of a given lesion on the neuronal circuits. Our methods, which were applied to 37 patients with a focal frontal brain lesions, revealed a large set of directly and indirectly disconnected brain regions that had significantly impacted category fluency performance. The directly disconnected regions corresponded to areas that are classically considered as functionally engaged in verbal fluency and categorization tasks. These regions were also organized into larger directly and indirectly disconnected functional networks, including the left ventral fronto-parietal network, whose cortical thickness correlated with performance on category fluency. The combination of structural and functional connectivity together with cortical thickness estimates reveal the remote effects of brain lesions, provide for the identification of the affected networks, and strengthen our understanding of their relationship with cognitive and behavioral measures. The methods presented are available and freely accessible in the BCBtoolkit as supplementary software [1].
Analysis on the Operation Strategy of the 220kV External Transmission Channel for the Nujiang Power Grid after the Installation of Series Compensation

NASA Astrophysics Data System (ADS)

Liu, Xiaoxin; Feng, Peilei; Jan, Lisheng; Dai, Xiaozhong; Cai, Pengcheng

2018-01-01

In recent years, Nujiang Prefecture vigorously develop hydropower, the grid structure in the northwest of Yunnan Province is not perfect, which leads to the research and construction of the power grid lags behind the development of the hydropower. In 2015, the company in view of the nu river hydropower dilemma decided to change outside the nu river to send out a passage with series compensation device in order to improve the transmission capacity, the company to the main problems related to the system plan, but not too much in the region distribution network and detailed study. Nujiang power grid has unique structure and properties of the nujiang power grid after respectively, a whole rack respectively into two parts, namely power delivery channels, load power supply, the whole grid occurred fundamental changes, the original strategy of power network is not applicable, especially noteworthy is the main failure after network of independent operation problem, how to avoid the local series, emergency problem is more urgent, very tolerance test area power grid, this paper aims at the analysis of existing data, simulation, provide a reference for respectively after the operation for the stable operation of the power grid.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Yingjie, E-mail: yzx@ansto.gov.au; Bhadbhade, Mohan; Karatchevtseva, Inna

Three new coordination polymers of uranium(VI) with pyromellitic acid (H{sub 4}btca) have been synthesized and structurally characterized. (ED)[(UO{sub 2})(btca)]·(DMSO)·3H{sub 2}O (1) (ED=ethylenediammonium; DMSO=dimethylsulfoxide) has a lamellar structure with intercalation of ED and DMSO. (NH{sub 4}){sub 2}[(UO{sub 2}){sub 6}O{sub 2}(OH){sub 6}(btca)]·~6H{sub 2}O (2) has a 3D framework built from 7-fold coordinated uranyl trinuclear units and btca ligands with 1D diamond-shaped channels (~8.5 Å×~8.6 Å). [(UO{sub 2}){sub 2}(H{sub 2}O)(btca)]·4H{sub 2}O (3) has a 3D network constructed by two types of 7-fold coordinated uranium polyhedron. The unique μ{sub 5}-coordination mode of btca in 3 enables the formation of 1D olive-shaped large channels (~4.5more » Å×~19 Å). Vibrational modes, thermal stabilities and fluorescence properties have been investigated. - Graphical abstract: Table of content: three new uranium(VI) coordination polymers with pyromellitic acid (H{sub 4}btca) have been synthesized via room temperature and hydrothermal synthesis methods, and structurally characterized. Two to three dimensional (3D) frameworks are revealed. All 3D frameworks have unique 1D large channels. Their vibrational modes, thermal stabilities and photoluminescence properties have been investigated. - Highlights: • Three new coordination polymers of U(VI) with pyromellitic acid (H{sub 4}btca). • Structures from a 2D layer to 3D frameworks with unique 1D channels. • Unusual µ{sub 5}-(η{sub 1}:η{sub 2}:η{sub 1}:η{sub 2:}η{sub 1}) coordination mode of btca ligand. • Vibrational modes, thermal stabilities and luminescent properties reported.« less
Merging Bottom-Up with Top-Down: Continuous Lamellar Networks and Block Copolymer Lithography

NASA Astrophysics Data System (ADS)

Campbell, Ian Patrick

Block copolymer lithography is an emerging nanopatterning technology with capabilities that may complement and eventually replace those provided by existing optical lithography techniques. This bottom-up process relies on the parallel self-assembly of macromolecules composed of covalently linked, chemically distinct blocks to generate periodic nanostructures. Among the myriad potential morphologies, lamellar structures formed by diblock copolymers with symmetric volume fractions have attracted the most interest as a patterning tool. When confined to thin films and directed to assemble with interfaces perpendicular to the substrate, two-dimensional domains are formed between the free surface and the substrate, and selective removal of a single block creates a nanostructured polymeric template. The substrate exposed between the polymeric features can subsequently be modified through standard top-down microfabrication processes to generate novel nanostructured materials. Despite tremendous progress in our understanding of block copolymer self-assembly, continuous two-dimensional materials have not yet been fabricated via this robust technique, which may enable nanostructured material combinations that cannot be fabricated through bottom-up methods. This thesis aims to study the effects of block copolymer composition and processing on the lamellar network morphology of polystyrene-block-poly(methyl methacrylate) (PS-b-PMMA) and utilize this knowledge to fabricate continuous two-dimensional materials through top-down methods. First, block copolymer composition was varied through homopolymer blending to explore the physical phenomena surrounding lamellar network continuity. After establishing a framework for tuning the continuity, the effects of various processing parameters were explored to engineer the network connectivity via defect annihilation processes. Precisely controlling the connectivity and continuity of lamellar networks through defect engineering and optimizing the block copolymer lithography process thus enabled the top-down fabrication of continuous two-dimensional gold networks with nanoscale properties. The lamellar structure of these networks was found to confer unique mechanical properties on the nanowire networks and suggests that materials templated via this method may be excellent candidates for integration into stretchable and flexible devices.
Asynchronous networks: modularization of dynamics theorem

NASA Astrophysics Data System (ADS)

Bick, Christian; Field, Michael

2017-02-01

Building on the first part of this paper, we develop the theory of functional asynchronous networks. We show that a large class of functional asynchronous networks can be (uniquely) represented as feedforward networks connecting events or dynamical modules. For these networks we can give a complete description of the network function in terms of the function of the events comprising the network: the modularization of dynamics theorem. We give examples to illustrate the main results.
Mapping Power Law Distributions in Digital Health Social Networks: Methods, Interpretations, and Practical Implications.

PubMed

van Mierlo, Trevor; Hyatt, Douglas; Ching, Andrew T

2015-06-25

Social networks are common in digital health. A new stream of research is beginning to investigate the mechanisms of digital health social networks (DHSNs), how they are structured, how they function, and how their growth can be nurtured and managed. DHSNs increase in value when additional content is added, and the structure of networks may resemble the characteristics of power laws. Power laws are contrary to traditional Gaussian averages in that they demonstrate correlated phenomena. The objective of this study is to investigate whether the distribution frequency in four DHSNs can be characterized as following a power law. A second objective is to describe the method used to determine the comparison. Data from four DHSNs—Alcohol Help Center (AHC), Depression Center (DC), Panic Center (PC), and Stop Smoking Center (SSC)—were compared to power law distributions. To assist future researchers and managers, the 5-step methodology used to analyze and compare datasets is described. All four DHSNs were found to have right-skewed distributions, indicating the data were not normally distributed. When power trend lines were added to each frequency distribution, R(2) values indicated that, to a very high degree, the variance in post frequencies can be explained by actor rank (AHC .962, DC .975, PC .969, SSC .95). Spearman correlations provided further indication of the strength and statistical significance of the relationship (AHC .987. DC .967, PC .983, SSC .993, P<.001). This is the first study to investigate power distributions across multiple DHSNs, each addressing a unique condition. Results indicate that despite vast differences in theme, content, and length of existence, DHSNs follow properties of power laws. The structure of DHSNs is important as it gives insight to researchers and managers into the nature and mechanisms of network functionality. The 5-step process undertaken to compare actor contribution patterns can be replicated in networks that are managed by other organizations, and we conjecture that patterns observed in this study could be found in other DHSNs. Future research should analyze network growth over time and examine the characteristics and survival rates of superusers.
Managing uncertainty in metabolic network structure and improving predictions using EnsembleFBA

PubMed Central

2017-01-01

Genome-scale metabolic network reconstructions (GENREs) are repositories of knowledge about the metabolic processes that occur in an organism. GENREs have been used to discover and interpret metabolic functions, and to engineer novel network structures. A major barrier preventing more widespread use of GENREs, particularly to study non-model organisms, is the extensive time required to produce a high-quality GENRE. Many automated approaches have been developed which reduce this time requirement, but automatically-reconstructed draft GENREs still require curation before useful predictions can be made. We present a novel approach to the analysis of GENREs which improves the predictive capabilities of draft GENREs by representing many alternative network structures, all equally consistent with available data, and generating predictions from this ensemble. This ensemble approach is compatible with many reconstruction methods. We refer to this new approach as Ensemble Flux Balance Analysis (EnsembleFBA). We validate EnsembleFBA by predicting growth and gene essentiality in the model organism Pseudomonas aeruginosa UCBPP-PA14. We demonstrate how EnsembleFBA can be included in a systems biology workflow by predicting essential genes in six Streptococcus species and mapping the essential genes to small molecule ligands from DrugBank. We found that some metabolic subsystems contributed disproportionately to the set of predicted essential reactions in a way that was unique to each Streptococcus species, leading to species-specific outcomes from small molecule interactions. Through our analyses of P. aeruginosa and six Streptococci, we show that ensembles increase the quality of predictions without drastically increasing reconstruction time, thus making GENRE approaches more practical for applications which require predictions for many non-model organisms. All of our functions and accompanying example code are available in an open online repository. PMID:28263984
Managing uncertainty in metabolic network structure and improving predictions using EnsembleFBA.

PubMed

Biggs, Matthew B; Papin, Jason A

2017-03-01

Genome-scale metabolic network reconstructions (GENREs) are repositories of knowledge about the metabolic processes that occur in an organism. GENREs have been used to discover and interpret metabolic functions, and to engineer novel network structures. A major barrier preventing more widespread use of GENREs, particularly to study non-model organisms, is the extensive time required to produce a high-quality GENRE. Many automated approaches have been developed which reduce this time requirement, but automatically-reconstructed draft GENREs still require curation before useful predictions can be made. We present a novel approach to the analysis of GENREs which improves the predictive capabilities of draft GENREs by representing many alternative network structures, all equally consistent with available data, and generating predictions from this ensemble. This ensemble approach is compatible with many reconstruction methods. We refer to this new approach as Ensemble Flux Balance Analysis (EnsembleFBA). We validate EnsembleFBA by predicting growth and gene essentiality in the model organism Pseudomonas aeruginosa UCBPP-PA14. We demonstrate how EnsembleFBA can be included in a systems biology workflow by predicting essential genes in six Streptococcus species and mapping the essential genes to small molecule ligands from DrugBank. We found that some metabolic subsystems contributed disproportionately to the set of predicted essential reactions in a way that was unique to each Streptococcus species, leading to species-specific outcomes from small molecule interactions. Through our analyses of P. aeruginosa and six Streptococci, we show that ensembles increase the quality of predictions without drastically increasing reconstruction time, thus making GENRE approaches more practical for applications which require predictions for many non-model organisms. All of our functions and accompanying example code are available in an open online repository.
Achieving high strength and high ductility in metal matrix composites reinforced with a discontinuous three-dimensional graphene-like network.

PubMed

Zhang, Xiang; Shi, Chunsheng; Liu, Enzuo; He, Fang; Ma, Liying; Li, Qunying; Li, Jiajun; Bacsa, Wolfgang; Zhao, Naiqin; He, Chunnian

2017-08-24

Graphene or graphene-like nanosheets have been emerging as an attractive reinforcement for composites due to their unique mechanical and electrical properties as well as their fascinating two-dimensional structure. It is a great challenge to efficiently and homogeneously disperse them within a metal matrix for achieving metal matrix composites with excellent mechanical and physical performance. In this work, we have developed an innovative in situ processing strategy for the fabrication of metal matrix composites reinforced with a discontinuous 3D graphene-like network (3D GN). The processing route involves the in situ synthesis of the encapsulation structure of 3D GN powders tightly anchored with Cu nanoparticles (NPs) (3D GN@Cu) to ensure mixing at the molecular level between graphene-like nanosheets and metal, coating of Cu on the 3D GN@Cu (3D GN@Cu@Cu), and consolidation of the 3D GN@Cu@Cu powders. This process can produce GN/Cu composites on a large scale, in which the in situ synthesized 3D GN not only maintains the perfect 3D network structure within the composites, but also has robust interfacial bonding with the metal matrix. As a consequence, the as-obtained 3D GN/Cu composites exhibit exceptionally high strength and superior ductility (the uniform and total elongation to failure of the composite are even much higher than the unreinforced Cu matrix). To the best of our knowledge, this work is the first report validating that a discontinuous 3D graphene-like network can simultaneously remarkably enhance the strength and ductility of the metal matrix.
Regional shape-based feature space for segmenting biomedical images using neural networks

NASA Astrophysics Data System (ADS)

Sundaramoorthy, Gopal; Hoford, John D.; Hoffman, Eric A.

1993-07-01

In biomedical images, structure of interest, particularly the soft tissue structures, such as the heart, airways, bronchial and arterial trees often have grey-scale and textural characteristics similar to other structures in the image, making it difficult to segment them using only gray- scale and texture information. However, these objects can be visually recognized by their unique shapes and sizes. In this paper we discuss, what we believe to be, a novel, simple scheme for extracting features based on regional shapes. To test the effectiveness of these features for image segmentation (classification), we use an artificial neural network and a statistical cluster analysis technique. The proposed shape-based feature extraction algorithm computes regional shape vectors (RSVs) for all pixels that meet a certain threshold criteria. The distance from each such pixel to a boundary is computed in 8 directions (or in 26 directions for a 3-D image). Together, these 8 (or 26) values represent the pixel's (or voxel's) RSV. All RSVs from an image are used to train a multi-layered perceptron neural network which uses these features to 'learn' a suitable classification strategy. To clearly distinguish the desired object from other objects within an image, several examples from inside and outside the desired object are used for training. Several examples are presented to illustrate the strengths and weaknesses of our algorithm. Both synthetic and actual biomedical images are considered. Future extensions to this algorithm are also discussed.
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.
A systematic review of collaboration and network research in the public affairs literature: implications for public health practice and research.

PubMed

Varda, Danielle; Shoup, Jo Ann; Miller, Sara

2012-03-01

We explored and analyzed how findings from public affairs research can inform public health research and practice, specifically in the area of interorganizational collaboration, one of the most promising practice-based approaches in the public health field. We conducted a systematic review of the public affairs literature by following a grounded theory approach. We coded 151 articles for demographics and empirical findings (n = 258). Three primary findings stand out in the public affairs literature: network structure affects governance, management strategies exist for administrators, and collaboration can be linked to outcomes. These findings are linked to priorities in public health practice. Overall, we found that public affairs has a long and rich history of research in collaborations that offers unique organizational theory and management tools to public health practitioners.

Networks of connected Pt nanoparticles supported on carbon nanotubes as superior catalysts for methanol electrooxidation

NASA Astrophysics Data System (ADS)

Huang, Meihua; Zhang, Jianshuo; Wu, Chuxin; Guan, Lunhui

2017-02-01

The high cost and short lifetime of the Pt-based anode catalyst for methanol oxidation reaction (MOR) hamper the widespread commercialization of direct methanol fuel cell (DMFC). Therefore, improving the activity of Pt-based catalysts is necessary for their practical application. For the first time, we prepared networks of connected Pt nanoparticles supported on multi-walled carbon nanotubes with loading ratio as high as 91 wt% (Pt/MWCNTs). Thanks for the unique connected structure, the Pt mass activity of Pt/MWCNTs for methanol oxidation reaction is 4.4 times as active as that of the commercial Pt/C (20 wt%). When carbon support is considered, the total mass activity of Pt/MWCNTs is 20 times as active as that of the commercial Pt/C. The durability and anti-poisoning ability are also improved greatly.
Intermediate Filaments Play a Pivotal Role in Regulating Cell Architecture and Function*

PubMed Central

Lowery, Jason; Kuczmarski, Edward R.; Herrmann, Harald; Goldman, Robert D.

2015-01-01

Intermediate filaments (IFs) are composed of one or more members of a large family of cytoskeletal proteins, whose expression is cell- and tissue type-specific. Their importance in regulating the physiological properties of cells is becoming widely recognized in functions ranging from cell motility to signal transduction. IF proteins assemble into nanoscale biopolymers with unique strain-hardening properties that are related to their roles in regulating the mechanical integrity of cells. Furthermore, mutations in the genes encoding IF proteins cause a wide range of human diseases. Due to the number of different types of IF proteins, we have limited this short review to cover structure and function topics mainly related to the simpler homopolymeric IF networks composed of vimentin, and specifically for diseases, the related muscle-specific desmin IF networks. PMID:25957409
Structural insights into a secretory abundant heat-soluble protein from an anhydrobiotic tardigrade, Ramazzottius varieornatus.

PubMed

Fukuda, Yohta; Miura, Yoshimasa; Mizohata, Eiichi; Inoue, Tsuyoshi

2017-08-01

Upon stopping metabolic processes, some tardigrades can undergo anhydrobiosis. Secretory abundant heat-soluble (SAHS) proteins have been reported as candidates for anhydrobiosis-related proteins in tardigrades, which seem to protect extracellular components and/or secretory organelles. We determined structures of a SAHS protein from Ramazzottius varieornatus (RvSAHS1), which is one of the toughest tardigrades. RvSAHS1 shows a β-barrel structure similar to fatty acid-binding proteins (FABPs), in which hydrophilic residues form peculiar hydrogen bond networks, which would provide RvSAHS1 with better tolerance against dehydration. We identified two putative ligand-binding sites: one that superimposes on those of some FABPs and the other, unique to and conserved in SAHS proteins. These results indicate that SAHS proteins constitute a new FABP family. © 2017 Federation of European Biochemical Societies.
Assembly, Thermodynamics, and Structure of a Two-Wheeled Composite of a Dumbbell-Shaped Molecule and Cylindrical Molecules with Different Edges.

PubMed

Matsuno, Taisuke; Kamata, Sho; Sato, Sota; Yokoyama, Atsutoshi; Sarkar, Parantap; Isobe, Hiroyuki

2017-11-20

A carbonaceous dumbbell was able to spontaneously glue two tubular receptors to form a unique two-wheeled composite through van der Waals interactions, thus forcing the wheel components into contact with each other at the edges. In the present study, two tubular receptors with enantiomeric carbon networks were assembled on the dumbbell joint, and the handedness of the receptors was discriminated, thus leading to the self-sorting of homomeric receptors from a mixture of enantiomeric tubes. The crystal structures of the composites revealed the structural origins of the molecular recognition driven by van der Waals forces as well as the presence of a columnar array of C 120 molecules in a 1:1 composite. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Ion-water wires in imidazolium-based ionic liquid/water solutions induce unique trends in density.

PubMed

Ghoshdastidar, Debostuti; Senapati, Sanjib

2016-03-28

Ionic liquid/water binary mixtures are rapidly gaining popularity as solvents for dissolution of cellulose, nucleobases, and other poorly water-soluble biomolecules. Hence, several studies have focused on measuring the thermophysical properties of these versatile mixtures. Among these, 1-ethyl-3-methylimidazolium ([emim]) cation-based ILs containing different anions exhibit unique density behaviours upon addition of water. While [emim][acetate]/water binary mixtures display an unusual rise in density with the addition of low-to-moderate amounts of water, those containing the [trifluoroacetate] ([Tfa]) anion display a sluggish decrease in density. The density of [emim][tetrafluoroborate] ([emim][BF4])/water mixtures, on the other hand, declines rapidly in close accordance with the experimental reports. Here, we unravel the structural basis underlying this unique density behavior of [emim]-based IL/water mixtures using all-atom molecular dynamics (MD) simulations. The results revealed that the distinct nature of anion-water hydrogen bonded networks in the three systems was a key in modulating the observed unique density behaviour. Vast expanses of uninterrupted anion-water-anion H-bonded stretches, denoted here as anion-water wires, induced significant structuring in [emim][Ac]/water mixtures that resulted in the density rise. Conversely, the presence of intermittent large water clusters disintegrated the anion-water wires in [emim][Tfa]/water and [emim][BF4]/water mixtures to cause a monotonic density decrease. The differential nanostructuring affected the dynamics of the solutions proportionately, with the H-bond making and breaking dynamics found to be greatly retarded in [emim][Ac]/water mixtures, while it exhibited a faster relaxation in the other two binary solutions.
The network of Shanghai Stroke Service System (4S): A public health-care web-based database using automatic extraction of electronic medical records.

PubMed

Dong, Yi; Fang, Kun; Wang, Xin; Chen, Shengdi; Liu, Xueyuan; Zhao, Yuwu; Guan, Yangtai; Cai, Dingfang; Li, Gang; Liu, Jianmin; Liu, Jianren; Zhuang, Jianhua; Wang, Panshi; Chen, Xin; Shen, Haipeng; Wang, David Z; Xian, Ying; Feng, Wuwei; Campbell, Bruce Cv; Parsons, Mark; Dong, Qiang

2018-07-01

Background Several stroke outcome and quality control projects have demonstrated the success in stroke care quality improvement through structured process. However, Chinese health-care systems are challenged with its overwhelming numbers of patients, limited resources, and large regional disparities. Aim To improve quality of stroke care to address regional disparities through process improvement. Method and design The Shanghai Stroke Service System (4S) is established as a regional network for stroke care quality improvement in the Shanghai metropolitan area. The 4S registry uses a web-based database that automatically extracts data from structured electronic medical records. Site-specific education and training program will be designed and administrated according to their baseline characteristics. Both acute reperfusion therapies including thrombectomy and thrombolysis in the acute phase and subsequent care were measured and monitored with feedback. Primary outcome is to evaluate the differences in quality metrics between baseline characteristics (including rate of thrombolysis in acute stroke and key performance indicators in secondary prevention) and post-intervention. Conclusions The 4S system is a regional stroke network that monitors the ongoing stroke care quality in Shanghai. This project will provide the opportunity to evaluate the spectrum of acute stroke care and design quality improvement processes for better stroke care. A regional stroke network model for quality improvement will be explored and might be expanded to other large cities in China. Clinical Trial Registration-URL http://www.clinicaltrials.gov . Unique identifier: NCT02735226.
Partial covariance based functional connectivity computation using Ledoit-Wolf covariance regularization.

PubMed

Brier, Matthew R; Mitra, Anish; McCarthy, John E; Ances, Beau M; Snyder, Abraham Z

2015-11-01

Functional connectivity refers to shared signals among brain regions and is typically assessed in a task free state. Functional connectivity commonly is quantified between signal pairs using Pearson correlation. However, resting-state fMRI is a multivariate process exhibiting a complicated covariance structure. Partial covariance assesses the unique variance shared between two brain regions excluding any widely shared variance, hence is appropriate for the analysis of multivariate fMRI datasets. However, calculation of partial covariance requires inversion of the covariance matrix, which, in most functional connectivity studies, is not invertible owing to rank deficiency. Here we apply Ledoit-Wolf shrinkage (L2 regularization) to invert the high dimensional BOLD covariance matrix. We investigate the network organization and brain-state dependence of partial covariance-based functional connectivity. Although RSNs are conventionally defined in terms of shared variance, removal of widely shared variance, surprisingly, improved the separation of RSNs in a spring embedded graphical model. This result suggests that pair-wise unique shared variance plays a heretofore unrecognized role in RSN covariance organization. In addition, application of partial correlation to fMRI data acquired in the eyes open vs. eyes closed states revealed focal changes in uniquely shared variance between the thalamus and visual cortices. This result suggests that partial correlation of resting state BOLD time series reflect functional processes in addition to structural connectivity. Copyright © 2015 Elsevier Inc. All rights reserved.
Partial covariance based functional connectivity computation using Ledoit-Wolf covariance regularization

PubMed Central

Brier, Matthew R.; Mitra, Anish; McCarthy, John E.; Ances, Beau M.; Snyder, Abraham Z.

2015-01-01

Functional connectivity refers to shared signals among brain regions and is typically assessed in a task free state. Functional connectivity commonly is quantified between signal pairs using Pearson correlation. However, resting-state fMRI is a multivariate process exhibiting a complicated covariance structure. Partial covariance assesses the unique variance shared between two brain regions excluding any widely shared variance, hence is appropriate for the analysis of multivariate fMRI datasets. However, calculation of partial covariance requires inversion of the covariance matrix, which, in most functional connectivity studies, is not invertible owing to rank deficiency. Here we apply Ledoit-Wolf shrinkage (L2 regularization) to invert the high dimensional BOLD covariance matrix. We investigate the network organization and brain-state dependence of partial covariance-based functional connectivity. Although RSNs are conventionally defined in terms of shared variance, removal of widely shared variance, surprisingly, improved the separation of RSNs in a spring embedded graphical model. This result suggests that pair-wise unique shared variance plays a heretofore unrecognized role in RSN covariance organization. In addition, application of partial correlation to fMRI data acquired in the eyes open vs. eyes closed states revealed focal changes in uniquely shared variance between the thalamus and visual cortices. This result suggests that partial correlation of resting state BOLD time series reflect functional processes in addition to structural connectivity. PMID:26208872
Role of Unchannelized Flow in Determining Bifurcation Angle in Distributary Channel Networks

NASA Astrophysics Data System (ADS)

Coffey, T.

2016-12-01

Distributary channel bifurcations on river deltas are important features in both modern systems, where the channels control water, sediment, and nutrient routing, and in ancient deltas, where the channel networks can dictate large-scale stratigraphic heterogeneity. Geometric features of distributary channels, such as channel dimensions and network structure, have long been thought to be defined by factors such as flow velocity, grain size, or channel aspect ratio where the channel enters the basin. We use theory originally developed for tributary networks fed by groundwater seepage to understand the dynamics of distributary channel bifurcations. Interestingly, bifurcations in groundwater-fed tributary networks have been shown to evolve dependent on the diffusive flow patterns around the channel network. These networks possess a characteristic bifurcation angle of 72°, due to Laplacian flow (gradient2h2=0, where h is water surface elevation) in the groundwater flow field near tributary channel tips. We develop and test the hypothesis that bifurcation angles in distributary channel networks are likewise dictated by the external flow field, in this case the shallow surface water surrounding the subaqueous portion of distributary channel bifurcations in a deltaic setting. We measured 130 unique distributary channel bifurcations in a single experimental delta and in 10 natural deltas, yielding a mean angle of 70.35°±2.59° (95% confidence interval), in line with the theoretical prediction. This similarity implies that flow outside of the distributary channel network is also Laplacian, which we use scaling arguments to justify. We conclude that the dynamics of the unchannelized flow control bifurcation formation in distributary networks.
Nanoporous Metallic Networks: Fabrication, Optical Properties, and Applications.

PubMed

Ron, Racheli; Haleva, Emir; Salomon, Adi

2018-05-17

Nanoporous metallic networks are a group of porous materials made of solid metals with suboptical wavelength sizes of both particles and voids. They are characterized by unique optical properties, as well as high surface area and permeability of guest materials. As such, they attract a great focus as novel materials for photonics, catalysis, sensing, and renewable energy. Their properties together with the ability for scaling-up evoke an increased interest also in the industrial field. Here, fabrication techniques of large-scale metallic networks are discussed, and their interesting optical properties as well as their applications are considered. In particular, the focus is on disordered systems, which may facilitate the fabrication technique, yet, endow the three-dimensional (3D) network with distinct optical properties. These metallic networks bridge the nanoworld into the macroscopic world, and therefore pave the way to the fabrication of innovative materials with unique optoelectronic properties. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Fibrous hybrid of graphene and sulfur nanocrystals for high-performance lithium-sulfur batteries.

PubMed

Zhou, Guangmin; Yin, Li-Chang; Wang, Da-Wei; Li, Lu; Pei, Songfeng; Gentle, Ian Ross; Li, Feng; Cheng, Hui-Ming

2013-06-25

Graphene-sulfur (G-S) hybrid materials with sulfur nanocrystals anchored on interconnected fibrous graphene are obtained by a facile one-pot strategy using a sulfur/carbon disulfide/alcohol mixed solution. The reduction of graphene oxide and the formation/binding of sulfur nanocrystals were integrated. The G-S hybrids exhibit a highly porous network structure constructed by fibrous graphene, many electrically conducting pathways, and easily tunable sulfur content, which can be cut and pressed into pellets to be directly used as lithium-sulfur battery cathodes without using a metal current-collector, binder, and conductive additive. The porous network and sulfur nanocrystals enable rapid ion transport and short Li(+) diffusion distance, the interconnected fibrous graphene provides highly conductive electron transport pathways, and the oxygen-containing (mainly hydroxyl/epoxide) groups show strong binding with polysulfides, preventing their dissolution into the electrolyte based on first-principles calculations. As a result, the G-S hybrids show a high capacity, an excellent high-rate performance, and a long life over 100 cycles. These results demonstrate the great potential of this unique hybrid structure as cathodes for high-performance lithium-sulfur batteries.
Mapping the nomological network of employee self-determined safety motivation: A preliminary measure in China.

PubMed

Jiang, Li; Tetrick, Lois E

2016-09-01

The present study introduced a preliminary measure of employee safety motivation based on the definition of self-determination theory from Fleming (2012) research and validated the structure of self-determined safety motivation (SDSM) by surveying 375 employees in a Chinese high-risk organization. First, confirmatory factor analysis (CFA) was used to examine the factor structure of SDSM, and indices of five-factor model CFA met the requirements. Second, a nomological network was examined to provide evidence of the construct validity of SDSM. Beyond construct validity, the analysis also produced some interesting results concerning the relationship between leadership antecedents and safety motivation, and between safety motivation and safety behavior. Autonomous motivation was positively related to transformational leadership, negatively related to abusive supervision, and positively related to safety behavior. Controlled motivation with the exception of introjected regulation was negatively related to transformational leadership, positively related to abusive supervision, and negatively related to safety behavior. The unique role of introjected regulation and future research based on self-determination theory were discussed. Copyright © 2016 Elsevier Ltd. All rights reserved.
Analysis of the bacterial luciferase mobile loop by replica-exchange molecular dynamics.

PubMed

Campbell, Zachary T; Baldwin, Thomas O; Miyashita, Osamu

2010-12-15

Bacterial luciferase contains an extended 29-residue mobile loop. Movements of this loop are governed by binding of either flavin mononucleotide (FMNH2) or polyvalent anions. To understand this process, loop dynamics were investigated using replica-exchange molecular dynamics that yielded conformational ensembles in either the presence or absence of FMNH2. The resulting data were analyzed using clustering and network analysis. We observed the closed conformations that are visited only in the simulations with the ligand. Yet the mobile loop is intrinsically flexible, and FMNH2 binding modifies the relative populations of conformations. This model provides unique information regarding the function of a crystallographically disordered segment of the loop near the binding site. Structures at or near the fringe of this network were compatible with flavin binding or release. Finally, we demonstrate that the crystallographically observed conformation of the mobile loop bound to oxidized flavin was influenced by crystal packing. Thus, our study has revealed what we believe are novel conformations of the mobile loop and additional context for experimentally determined structures. Copyright © 2010 Biophysical Society. Published by Elsevier Inc. All rights reserved.
Transparency in Cooperative Online Education

ERIC Educational Resources Information Center

Dalsgaard, Christian; Paulsen, Morten Flate

2009-01-01

The purpose of this article is to discuss the following question: What is the potential of social networking within cooperative online education? Social networking does not necessarily involve communication, dialogue, or collaboration. Instead, the authors argue that "transparency" is a unique feature of social networking services.…
Teacher Networks Companion Piece

ERIC Educational Resources Information Center

Hopkins, Ami Patel; Rulli, Carolyn; Schiff, Daniel; Fradera, Marina

2015-01-01

Network building vitally impacts career development, but in few professions does it impact daily practice more than in teaching. Teacher networks, known as professional learning communities, communities of practice, peer learning circles, virtual professional communities, as well as other names, play a unique and powerful role in education. In…
Analysis of Traffic Signals on a Software-Defined Network for Detection and Classification of a Man-in-the-Middle Attack

DTIC Science & Technology

2017-09-01

unique characteristics of reported anomalies in the collected traffic signals to build a classification framework. Other cyber events, such as a...Furthermore, we identify unique characteristics of reported anomalies in the collected traffic signals to build a classification framework. Other cyber...2]. The applications build flow rules using network topology information provided by the control plane [1]. Since the control plane is able to
Mapping Extension's Networks: Using Social Network Analysis to Explore Extension's Outreach

ERIC Educational Resources Information Center

Bartholomay, Tom; Chazdon, Scott; Marczak, Mary S.; Walker, Kathrin C.

2011-01-01

The University of Minnesota Extension conducted a social network analysis (SNA) to examine its outreach to organizations external to the University of Minnesota. The study found that its outreach network was both broad in its reach and strong in its connections. The study found that SNA offers a unique method for describing and measuring Extension…
Advanced Mobility Handover for Mobile IPv6 Based Wireless Networks

PubMed Central

Safa Sadiq, Ali; Fisal, Norsheila Binti; Ghafoor, Kayhan Zrar; Lloret, Jaime

2014-01-01

We propose an Advanced Mobility Handover scheme (AMH) in this paper for seamless mobility in MIPv6-based wireless networks. In the proposed scheme, the mobile node utilizes a unique home IPv6 address developed to maintain communication with other corresponding nodes without a care-of-address during the roaming process. The IPv6 address for each MN during the first round of AMH process is uniquely identified by HA using the developed MN-ID field as a global permanent, which is identifying uniquely the IPv6 address of MN. Moreover, a temporary MN-ID is generated by access point each time an MN is associated with a particular AP and temporarily saved in a developed table inside the AP. When employing the AMH scheme, the handover process in the network layer is performed prior to its default time. That is, the mobility handover process in the network layer is tackled by a trigger developed AMH message to the next access point. Thus, a mobile node keeps communicating with the current access point while the network layer handover is executed by the next access point. The mathematical analyses and simulation results show that the proposed scheme performs better as compared with the existing approaches. PMID:25614890
Better sales networks.

PubMed

Ustüner, Tuba; Godes, David

2006-01-01

Anyone in sales will tell you that social networks are critical. The more contacts you have, the more leads you'll generate, and, ultimately, the more sales you'll make. But that's a vast oversimplification. Different configurations of networks produce different results, and the salesperson who develops a nuanced understanding of social networks will outshine competitors. The salesperson's job changes over the course of the selling process. Different abilities are required in each stage of the sale: identifying prospects, gaining buy-in from potential customers, creating solutions, and closing the deal. Success in the first stage, for instance, depends on the salesperson acquiring precise and timely information about opportunities from contacts in the marketplace. Closing the deal requires the salesperson to mobilize contacts from prior sales to act as references. Managers often view sales networks only in terms of direct contacts. But someone who knows lots of people doesn't necessarily have an effective network because networks often pay off most handsomely through indirect contacts. Moreover, the density of the connections in a network is important. Do a salesperson's contacts know all the same people, or are their associates widely dispersed? Sparse networks are better, for example, at generating unique information. Managers can use three levers--sales force structure, compensation, and skills development--to encourage salespeople to adopt a network-based view and make the best possible use of social webs. For example, the sales force can be restructured to decouple lead generation from other tasks because some people are very good at building diverse ties but not so good at maintaining other kinds of networks. Companies that take steps of this kind to help their sales teams build better networks will reap tremendous advantages.
Listing a Geological Rarity of ‘Stone Balls’ in Kysuce Among World Geotourism Destinations

NASA Astrophysics Data System (ADS)

Duraj, Miloš; Niemiec, Dominik; Marschalko, Marian; Yilmaz, Işik

2016-10-01

Kysuce, situated on the border with the Czech Republic and Poland, belongs among distinctive regions in the Slovak Republic. This region offers tourism many interesting sites. Few decades ago, Kysuce offered tourists and visitors well-preserved national architecture, which is nowadays concentrated in an open-air museum Vychylovka. Thanks to the rich afforestation and a sophisticated network of signs for hikers, hiking has been very popular. The ground relief and climatic conditions also encourage winter sports. The world-wide development of geotourism has also concerned this region. Despite a low-varied geological structure, there are unique geological formations that have attracted attention for years. For example, tourists visit the interesting mineralized springs and a remarkable crude oil seep in Korna. Geologically unique are also the occurrences of ‘stone balls’ from sandstone and conglomerates. This phenomenon has attracted attention of both geologists and esotericism supporters.

Non-equilibrium dissipative supramolecular materials with a tunable lifetime

NASA Astrophysics Data System (ADS)

Tena-Solsona, Marta; Rieß, Benedikt; Grötsch, Raphael K.; Löhrer, Franziska C.; Wanzke, Caren; Käsdorf, Benjamin; Bausch, Andreas R.; Müller-Buschbaum, Peter; Lieleg, Oliver; Boekhoven, Job

2017-07-01

Many biological materials exist in non-equilibrium states driven by the irreversible consumption of high-energy molecules like ATP or GTP. These energy-dissipating structures are governed by kinetics and are thus endowed with unique properties including spatiotemporal control over their presence. Here we show man-made equivalents of materials driven by the consumption of high-energy molecules and explore their unique properties. A chemical reaction network converts dicarboxylates into metastable anhydrides driven by the irreversible consumption of carbodiimide fuels. The anhydrides hydrolyse rapidly to the original dicarboxylates and are designed to assemble into hydrophobic colloids, hydrogels or inks. The spatiotemporal control over the formation and degradation of materials allows for the development of colloids that release hydrophobic contents in a predictable fashion, temporary self-erasing inks and transient hydrogels. Moreover, we show that each material can be re-used for several cycles.
Polysaccharide based nanogels in the drug delivery system: Application as the carrier of pharmaceutical agents.

PubMed

Debele, Tilahun Ayane; Mekuria, Shewaye Lakew; Tsai, Hsieh-Chih

2016-11-01

Polysaccharide-based nanoparticles have fascinated attention as a vesicle of different pharmaceutical agents due to their unique multi-functional groups in addition to their physicochemical properties, including biocompatibility and biodegradability. The existence of multi-functional groups on the polysaccharide backbone permits facile chemical or biochemical modification to synthesize polysaccharide based nanoparticles with miscellaneous structures. Polysaccharide-based nanogels have high water content, large surface area for multivalent bioconjugation, tunable size, and interior network for the incorporation of different pharmaceutical agents. These unique properties offer great potential for the utilization of polysaccharide-based nanogels in the drug delivery systems. Hence, this review describes chemistry of certain common polysaccharides, several methodologies used to synthesize polysaccharide nanoparticles and primarily focused on the polysaccharide (or polysaccharide derivative) based nanogels as the carrier of pharmaceutical agents. Copyright © 2016 Elsevier B.V. All rights reserved.
Pipeline including network and topology for identifying, locating and quantifying physical phenomena

DOEpatents

Richardson, John G.; Moore, Karen A.; Carrington, Robert A.

2006-02-14

A method and system for detecting, locating and quantifying a physical phenomena such as strain or a deformation in a structure. A plurality of laterally adjacent conductors may each include a plurality of segments. Each segment is constructed to exhibit a unit value representative of a defined energy transmission characteristic. A plurality of identity groups are defined with each identity group comprising a plurality of segments including at least one segment from each of the plurality of conductors. The segments contained within an identity group are configured and arranged such that each of their associated unit values may be represented by a concatenated digit string which is a unique number relative to the other identity groups. Additionally, the unit values of the segments within an identity group maintain unique ratios with respect to the other unit values in the identity group.
Network and topology for identifying, locating and quantifying physical phenomena, systems and methods for employing same

DOEpatents

Richardson, John G.; Moore, Karen A.; Carrington, Robert A.

2005-05-10

A method and system for detecting, locating and quantifying a physical phenomena such as strain or a deformation in a structure. A plurality of laterally adjacent conductors may each include a plurality of segments. Each segment is constructed to exhibit a unit value representative of a defined energy transmission characteristic. A plurality of identity groups are defined with each identity group comprising a plurality of segments including at least one segment from each of the plurality of conductors. The segments contained within an identity group are configured and arranged such that each of their associated unit values may be represented by a concatenated digit string which is a unique number relative to the other identity groups. Additionally, the unit values of the segments within an identity group maintain unique ratios with respect to the other unit values in the identity group.
Non-equilibrium dissipative supramolecular materials with a tunable lifetime

PubMed Central

Tena-Solsona, Marta; Rieß, Benedikt; Grötsch, Raphael K.; Löhrer, Franziska C.; Wanzke, Caren; Käsdorf, Benjamin; Bausch, Andreas R.; Müller-Buschbaum, Peter; Lieleg, Oliver; Boekhoven, Job

2017-01-01

Many biological materials exist in non-equilibrium states driven by the irreversible consumption of high-energy molecules like ATP or GTP. These energy-dissipating structures are governed by kinetics and are thus endowed with unique properties including spatiotemporal control over their presence. Here we show man-made equivalents of materials driven by the consumption of high-energy molecules and explore their unique properties. A chemical reaction network converts dicarboxylates into metastable anhydrides driven by the irreversible consumption of carbodiimide fuels. The anhydrides hydrolyse rapidly to the original dicarboxylates and are designed to assemble into hydrophobic colloids, hydrogels or inks. The spatiotemporal control over the formation and degradation of materials allows for the development of colloids that release hydrophobic contents in a predictable fashion, temporary self-erasing inks and transient hydrogels. Moreover, we show that each material can be re-used for several cycles. PMID:28719591
System identification of a tied arch bridge using reference-based wireless sensor networks

NASA Astrophysics Data System (ADS)

Hietbrink, Colby; Whelan, Matthew J.

2012-04-01

Vibration-based methods of structural health monitoring are generally founded on the principle that localized damage to a structure would exhibit changes within the global dynamic response. Upon this basis, accelerometers provide a unique health monitoring strategy in that a distributed network of sensors provides the technical feasibility to isolate the onset of damage without requiring that any sensor be located exactly on or in close proximity to the damage. While in theory this may be sufficient, practical experience has shown significant improvement in the application of damage diagnostic routines when mode shapes characterized by strongly localized behavior of specific elements are captured by the instrumentation array. In traditional applications, this presents a challenge since the cost and complexity of cable-based systems often effectively limits the number of instrumented locations thereby constraining the modal parameter extraction to only global modal responses. The advent of the low-cost RF chip transceiver with wireless networking capabilities has afforded a means by which a substantial number of output locations can be measured through referencebased testing using large-scale wireless sensor networks. In the current study, this approach was applied to the Prairie du Chien Bridge over the Mississippi River to extract operational mode shapes with high spatial reconstruction, including strongly localized modes. The tied arch bridge was instrumented at over 230 locations with single-axis accelerometers conditioned and acquired over a high-rate lossless wireless sensor network with simultaneous sampling capabilities. Acquisition of the dynamic response of the web plates of the arch rib was specifically targeted within the instrumentation array for diagnostic purposes. Reference-based operational modal analysis of the full structure through data-driven stochastic subspace identification is presented alongside finite element analysis results for confirmation of modal parameter plausibility. Particular emphasis is placed on the identification and reconstruction of modal response with large contribution from the arch rib web plates.
Unraveling the solvent induced welding of silver nanowires for high performance flexible transparent electrodes.

PubMed

Zhang, Kui; Li, Jia; Fang, Yunsheng; Luo, Beibei; Zhang, Yanli; Li, Yanqiu; Zhou, Jun; Hu, Bin

2018-04-25

A solution processed metal nanowire network is a promising flexible transparent electrode to replace brittle metal oxides for printable optoelectronics applications, but suffers from the issue of pseudo contact between nanowires. Herein, using volatile solvent mists as a powerful "zipper", we demonstrate a simple and rapid method to effectively weld silver nanowires, which dramatically improves the conductivity and robustness of the silver nanowire network based flexible transparent electrodes. We reveal that for a stacked network structure, the unique wedge-shaped nanogaps between the long nanowires and substrate provide a strong capillary force during solvent evaporation, which is much larger than that between zero-dimensional nanoparticles and gives a decisive contribution for nanowire junction welding, and this nanowire-substrate interplay force is positively related to the wettability of the substrate. At the same time, the dissolution-reprecipitation of the capping agent on the silver nanowire surface as the natural adhesive can fix the network on the substrate tightly, which enhances the robustness of the network. Our approach solves two key issues in solution-processed transparent electrodes in one simple step, and is compatible with various mild solution-processed optoelectronic devices, especially those containing heat-sensitive or chemical-sensitive materials. Moreover, a new type of invisible infrared encryption display is demonstrated based on this approach.
Engineering highly organized and aligned single walled carbon nanotube networks for electronic device applications: Interconnects, chemical sensor, and optoelectronics

NASA Astrophysics Data System (ADS)

Kim, Young Lae

For 20 years, single walled carbon nanotubes (SWNTs) have been studied actively due to their unique one-dimensional nanostructure and superior electrical, thermal, and mechanical properties. For these reasons, they offer the potential to serve as building blocks for future electronic devices such as field effect transistors (FETs), electromechanical devices, and various sensors. In order to realize these applications, it is crucial to develop a simple, scalable, and reliable nanomanufacturing process that controllably places aligned SWNTs in desired locations, orientations, and dimensions. Also electronic properties (semiconducting/metallic) of SWNTs and their organized networks must be controlled for the desired performance of devices and systems. These fundamental challenges are significantly limiting the use of SWNTs for future electronic device applications. Here, we demonstrate a strategy to fabricate highly controlled micro/nanoscale SWNT network structures and present the related assembly mechanism to engineer the SWNT network topology and its electrical transport properties. A method designed to evaluate the electrical reliability of such nano- and microscale SWNT networks is also presented. Moreover, we develop and investigate a robust SWNT based multifunctional selective chemical sensor and a range of multifunctional optoelectronic switches, photo-transistors, optoelectronic logic gates and complex optoelectronic digital circuits.
CytoViz: an artistic mapping of network measurements as living organisms in a VR application

NASA Astrophysics Data System (ADS)

López Silva, Brenda A.; Renambot, Luc

2007-02-01

CytoViz is an artistic, real-time information visualization driven by statistical information gathered during gigabit network transfers to the Scalable Adaptive Graphical Environment (SAGE) at various events. Data streams are mapped to cellular organisms defining their structure and behavior as autonomous agents. Network bandwidth drives the growth of each entity and the latency defines its physics-based independent movements. The collection of entity is bound within the 3D representation of the local venue. This visual and animated metaphor allows the public to experience the complexity of high-speed network streams that are used in the scientific community. Moreover, CytoViz displays the presence of discoverable Bluetooth devices carried by nearby persons. The concept is to generate an event-specific, real-time visualization that creates informational 3D patterns based on actual local presence. The observed Bluetooth traffic is put in opposition of the wide-area networking traffic by overlaying 2D animations on top of the 3D world. Each device is mapped to an animation fading over time while displaying the name of the detected device and its unique physical address. CytoViz was publicly presented at two major international conferences in 2005 (iGrid2005 in San Diego, CA and SC05 in Seattle, WA).
Bioinspired peptide nanotubes: deposition technology, basic physics and nanotechnology applications.

PubMed

Rosenman, G; Beker, P; Koren, I; Yevnin, M; Bank-Srour, B; Mishina, E; Semin, S

2011-02-01

Synthetic peptide monomers can self-assemble into PNM such as nanotubes, nanospheres, hydrogels, etc. which represent a novel class of nanomaterials. Molecular recognition processes lead to the formation of supramolecular PNM ensembles containing crystalline building blocks. Such low-dimensional highly ordered regions create a new physical situation and provide unique physical properties based on electron-hole QC phenomena. In the case of asymmetrical crystalline structure, basic physical phenomena such as linear electro-optic, piezoelectric, and nonlinear optical effects, described by tensors of the odd rank, should be explored. Some of the PNM crystalline structures permit the existence of spontaneous electrical polarization and observation of ferroelectricity. The PNM crystalline arrangement creates highly porous nanotubes when various residues are packed into structural network with specific wettability and electrochemical properties. We report in this review on a wide research of PNM intrinsic physical properties, their electronic and optical properties related to QC effect, unique SHG, piezoelectricity and ferroelectric spontaneous polarization observed in PNT due to their asymmetric structure. We also describe PNM wettability phenomenon based on their nanoporous structure and its influence on electrochemical properties in PNM. The new bottom-up large scale technology of PNT physical vapor deposition and patterning combined with found physical effects at nanoscale, developed by us, opens the avenue for emerging nanotechnology applications of PNM in novel fields of nanophotonics, nanopiezotronics and energy storage devices. Copyright © 2010 European Peptide Society and John Wiley & Sons, Ltd.
The HDAC complex and cytoskeleton.

PubMed

Kovacs, Jeffery J; Hubbert, Charlotte; Yao, Tso-Pang

2004-01-01

HDAC6 is a cytoplasmic deacetylase that dynamically associates with the microtubule and actin cytoskeletons. HDAC6 regulates growth factor-induced chemotaxis by its unique deacetylase activity towards microtubules or other substrates. Here we describe a non-catalytic structural domain that is essential for HDAC6 function and places HDAC6 as a critical mediator linking the acetylation and ubiquitination network. This evolutionarily conserved motif, termed the BUZ domain, has features of a zinc finger and binds both mono- and polyubiquitinated proteins. Furthermore, the BUZ domain promotes HDAC6 mono-ubiquitination. These results establish the BUZ domain, in addition to the UIM and CUE domains, as a novel motif that both binds ubiquitin and mediates mono-ubiquitination. Importantly, the BUZ domain is essential for HDAC6 to promote chemotaxis, indicating that communication with the ubiquitin network is critical for proper HDAC6 function. The unique presence of the UIM and CUE domains in proteins involved in endocytic trafficking suggests that HDAC6 might also regulate vesicle transport and protein degradation. Indeed, we have found that HDAC6 is actively transported and concentrated in vesicular compartments. We propose that an integration of reversible acetylation and ubiquitination by HDAC6 may be a novel component in regulating the cytoskeleton, vesicle transport and protein degradation.
Polyimide Aerogels with Three-Dimensional Cross-Linked Structure

NASA Technical Reports Server (NTRS)

Panek, John

2010-01-01

Polyimide aerogels with three-dimensional cross-linked structure are made using linear oligomeric segments of polyimide, and linked with one of the following into a 3D structure: trifunctional aliphatic or aromatic amines, latent reactive end caps such as nadic anhydride or phenylethynylphenyl amine, and silica or silsesquioxane cage structures decorated with amine. Drying the gels supercritically maintains the solid structure of the gel, creating a polyimide aerogel with improved mechanical properties over linear polyimide aerogels. Lightweight, low-density structures are desired for acoustic and thermal insulation for aerospace structures, habitats, astronaut equipment, and aeronautic applications. Aerogels are a unique material for providing such properties because of their extremely low density and small pore sizes. However, plain silica aerogels are brittle. Reinforcing the aerogel structure with a polymer (X-Aerogel) provides vast improvements in strength while maintaining low density and pore structure. However, degradation of polymers used in cross-linking tends to limit use temperatures to below 150 C. Organic aerogels made from linear polyimide have been demonstrated, but gels shrink substantially during supercritical fluid extraction and may have lower use temperature due to lower glass transition temperatures. The purpose of this innovation is to raise the glass transition temperature of all organic polyimide aerogel by use of tri-, tetra-, or poly-functional units in the structure to create a 3D covalently bonded network. Such cross-linked polyimides typically have higher glass transition temperatures in excess of 300 400 C. In addition, the reinforcement provided by a 3D network should improve mechanical stability, and prevent shrinkage on supercritical fluid extraction. The use of tri-functional aromatic or aliphatic amine groups in the polyimide backbone will provide such a 3D structure.
Structure-based manual screening and automatic networking for systematically exploring sansanmycin analogues using high performance liquid chromatography tandem mass spectroscopy.

PubMed

Jiang, Zhi-Bo; Ren, Wei-Cong; Shi, Yuan-Yuan; Li, Xing-Xing; Lei, Xuan; Fan, Jia-Hui; Zhang, Cong; Gu, Ren-Jie; Wang, Li-Fei; Xie, Yun-Ying; Hong, Bin

2018-05-18

Sansanmycins (SS), one of several known uridyl peptide antibiotics (UPAs) possessing a unique chemical scaffold, showed a good inhibitory effect on the highly refractory pathogens Pseudomonas aeruginosa and Mycobacterium tuberculosis, especially on the multi-drug resistant M. tuberculosis. This study employed high performance liquid chromatography-mass spectrometry detector (HPLC-MSD) ion trap and LTQ orbitrap tandem mass spectrometry (MS/MS) to explore sansanmycin analogues manually and automatically by re-analysis of the Streptomyces sp. SS fermentation broth. The structure-based manual screening method, based on analysis of the fragmentation pathway of known UPAs and on comparisons of the MS/MS spectra with that of sansanmycin A (SS-A), resulted in identifying twenty sansanmycin analogues, including twelve new structures (1-12). Furthermore, to deeply explore sansanmycin analogues, we utilized a GNPS based molecular networking workflow to re-analyze the HPLC-MS/MS data automatically. As a result, eight more new sansanmycins (13-20) were discovered. Compound 1 was discovered to lose two amino acids of residue 1 (AA 1 ) and (2S, 3S)-N 3 -methyl-2,3-diamino butyric acid (DABA) from the N-terminus, and compounds 6, 11 and 12 were found to contain a 2',3'-dehydrated 4',5'-enamine-3'-deoxyuridyl moiety, which have not been reported before. Interestingly, three trace components with novel 5,6-dihydro-5'-aminouridyl group (16-18) were detected for the first time in the sansanmycin-producing strain. Their structures were primarily determined by detail analysis of the data from MS/MS. Compounds 8 and 10 were further confirmed by nuclear magnetic resonance (NMR) data, which proved the efficiency and accuracy of the method of HPLC-MS/MS for exploration of novel UPAs. Comparing to manual screening, the networking method can provide systematic visualization results. Manual screening and networking method may complement with each other to facilitate the mining of novel UPAs. Copyright © 2018 Elsevier B.V. All rights reserved.
Invertebrate Metacommunity Structure and Dynamics in an Andean Glacial Stream Network Facing Climate Change

PubMed Central

Cauvy-Fraunié, Sophie; Espinosa, Rodrigo; Andino, Patricio; Jacobsen, Dean; Dangles, Olivier

2015-01-01

Under the ongoing climate change, understanding the mechanisms structuring the spatial distribution of aquatic species in glacial stream networks is of critical importance to predict the response of aquatic biodiversity in the face of glacier melting. In this study, we propose to use metacommunity theory as a conceptual framework to better understand how river network structure influences the spatial organization of aquatic communities in glacierized catchments. At 51 stream sites in an Andean glacierized catchment (Ecuador), we sampled benthic macroinvertebrates, measured physico-chemical and food resource conditions, and calculated geographical, altitudinal and glaciality distances among all sites. Using partial redundancy analysis, we partitioned community variation to evaluate the relative strength of environmental conditions (e.g., glaciality, food resource) vs. spatial processes (e.g., overland, watercourse, and downstream directional dispersal) in organizing the aquatic metacommunity. Results revealed that both environmental and spatial variables significantly explained community variation among sites. Among all environmental variables, the glacial influence component best explained community variation. Overland spatial variables based on geographical and altitudinal distances significantly affected community variation. Watercourse spatial variables based on glaciality distances had a unique significant effect on community variation. Within alpine catchment, glacial meltwater affects macroinvertebrate metacommunity structure in many ways. Indeed, the harsh environmental conditions characterizing glacial influence not only constitute the primary environmental filter but also, limit water-borne macroinvertebrate dispersal. Therefore, glacier runoff acts as an aquatic dispersal barrier, isolating species in headwater streams, and preventing non-adapted species to colonize throughout the entire stream network. Under a scenario of glacier runoff decrease, we expect a reduction in both environmental filtering and dispersal limitation, inducing a taxonomic homogenization of the aquatic fauna in glacierized catchments as well as the extinction of specialized species in headwater groundwater and glacier-fed streams, and consequently an irreversible reduction in regional diversity. PMID:26308853
Evidence for network evolution in an arabidopsis interactome map

USDA-ARS?s Scientific Manuscript database

Plants have unique features that evolved in response to their environments and ecosystems. A full account of the complex cellular networks that underlie plant-specific functions is still missing. We describe a proteome-wide binary protein-protein interaction map for the interactome network of the pl...
Dynamic facial expressions evoke distinct activation in the face perception network: a connectivity analysis study.

PubMed

Foley, Elaine; Rippon, Gina; Thai, Ngoc Jade; Longe, Olivia; Senior, Carl

2012-02-01

Very little is known about the neural structures involved in the perception of realistic dynamic facial expressions. In the present study, a unique set of naturalistic dynamic facial emotional expressions was created. Through fMRI and connectivity analysis, a dynamic face perception network was identified, which is demonstrated to extend Haxby et al.'s [Haxby, J. V., Hoffman, E. A., & Gobbini, M. I. The distributed human neural system for face perception. Trends in Cognitive Science, 4, 223-233, 2000] distributed neural system for face perception. This network includes early visual regions, such as the inferior occipital gyrus, which is identified as insensitive to motion or affect but sensitive to the visual stimulus, the STS, identified as specifically sensitive to motion, and the amygdala, recruited to process affect. Measures of effective connectivity between these regions revealed that dynamic facial stimuli were associated with specific increases in connectivity between early visual regions, such as the inferior occipital gyrus and the STS, along with coupling between the STS and the amygdala, as well as the inferior frontal gyrus. These findings support the presence of a distributed network of cortical regions that mediate the perception of different dynamic facial expressions.
The cell envelope stress response of Bacillus subtilis: from static signaling devices to dynamic regulatory network.

PubMed

Radeck, Jara; Fritz, Georg; Mascher, Thorsten

2017-02-01

The cell envelope stress response (CESR) encompasses all regulatory events that enable a cell to protect the integrity of its envelope, an essential structure of any bacterial cell. The underlying signaling network is particularly well understood in the Gram-positive model organism Bacillus subtilis. It consists of a number of two-component systems (2CS) and extracytoplasmic function σ factors that together regulate the production of both specific resistance determinants and general mechanisms to protect the envelope against antimicrobial peptides targeting the biogenesis of the cell wall. Here, we summarize the current picture of the B. subtilis CESR network, from the initial identification of the corresponding signaling devices to unraveling their interdependence and the underlying regulatory hierarchy within the network. In the course of detailed mechanistic studies, a number of novel signaling features could be described for the 2CSs involved in mediating CESR. This includes a novel class of so-called intramembrane-sensing histidine kinases (IM-HKs), which-instead of acting as stress sensors themselves-are activated via interprotein signal transfer. Some of these IM-HKs are involved in sensing the flux of antibiotic resistance transporters, a unique mechanism of responding to extracellular antibiotic challenge.
Quantum stochastic walks on networks for decision-making.

PubMed

Martínez-Martínez, Ismael; Sánchez-Burillo, Eduardo

2016-03-31

Recent experiments report violations of the classical law of total probability and incompatibility of certain mental representations when humans process and react to information. Evidence shows promise of a more general quantum theory providing a better explanation of the dynamics and structure of real decision-making processes than classical probability theory. Inspired by this, we show how the behavioral choice-probabilities can arise as the unique stationary distribution of quantum stochastic walkers on the classical network defined from Luce's response probabilities. This work is relevant because (i) we provide a very general framework integrating the positive characteristics of both quantum and classical approaches previously in confrontation, and (ii) we define a cognitive network which can be used to bring other connectivist approaches to decision-making into the quantum stochastic realm. We model the decision-maker as an open system in contact with her surrounding environment, and the time-length of the decision-making process reveals to be also a measure of the process' degree of interplay between the unitary and irreversible dynamics. Implementing quantum coherence on classical networks may be a door to better integrate human-like reasoning biases in stochastic models for decision-making.
Quantum stochastic walks on networks for decision-making

NASA Astrophysics Data System (ADS)

Martínez-Martínez, Ismael; Sánchez-Burillo, Eduardo

2016-03-01

Recent experiments report violations of the classical law of total probability and incompatibility of certain mental representations when humans process and react to information. Evidence shows promise of a more general quantum theory providing a better explanation of the dynamics and structure of real decision-making processes than classical probability theory. Inspired by this, we show how the behavioral choice-probabilities can arise as the unique stationary distribution of quantum stochastic walkers on the classical network defined from Luce’s response probabilities. This work is relevant because (i) we provide a very general framework integrating the positive characteristics of both quantum and classical approaches previously in confrontation, and (ii) we define a cognitive network which can be used to bring other connectivist approaches to decision-making into the quantum stochastic realm. We model the decision-maker as an open system in contact with her surrounding environment, and the time-length of the decision-making process reveals to be also a measure of the process’ degree of interplay between the unitary and irreversible dynamics. Implementing quantum coherence on classical networks may be a door to better integrate human-like reasoning biases in stochastic models for decision-making.
The role of stabilizing and communicating symptoms given overlapping communities in psychopathology networks.

PubMed

Blanken, Tessa F; Deserno, Marie K; Dalege, Jonas; Borsboom, Denny; Blanken, Peter; Kerkhof, Gerard A; Cramer, Angélique O J

2018-04-11

Network theory, as a theoretical and methodological framework, is energizing many research fields, among which clinical psychology and psychiatry. Fundamental to the network theory of psychopathology is the role of specific symptoms and their interactions. Current statistical tools, however, fail to fully capture this constitutional property. We propose community detection tools as a means to evaluate the complex network structure of psychopathology, free from its original boundaries of distinct disorders. Unique to this approach is that symptoms can belong to multiple communities. Using a large community sample and spanning a broad range of symptoms (Symptom Checklist-90-Revised), we identified 18 communities of interconnected symptoms. The differential role of symptoms within and between communities offers a framework to study the clinical concepts of comorbidity, heterogeneity and hallmark symptoms. Symptoms with many and strong connections within a community, defined as stabilizing symptoms, could be thought of as the core of a community, whereas symptoms that belong to multiple communities, defined as communicating symptoms, facilitate the communication between problem areas. We propose that defining symptoms on their stabilizing and/or communicating role within and across communities accelerates our understanding of these clinical phenomena, central to research and treatment of psychopathology.

Quantum stochastic walks on networks for decision-making

PubMed Central

Martínez-Martínez, Ismael; Sánchez-Burillo, Eduardo

2016-01-01

Recent experiments report violations of the classical law of total probability and incompatibility of certain mental representations when humans process and react to information. Evidence shows promise of a more general quantum theory providing a better explanation of the dynamics and structure of real decision-making processes than classical probability theory. Inspired by this, we show how the behavioral choice-probabilities can arise as the unique stationary distribution of quantum stochastic walkers on the classical network defined from Luce’s response probabilities. This work is relevant because (i) we provide a very general framework integrating the positive characteristics of both quantum and classical approaches previously in confrontation, and (ii) we define a cognitive network which can be used to bring other connectivist approaches to decision-making into the quantum stochastic realm. We model the decision-maker as an open system in contact with her surrounding environment, and the time-length of the decision-making process reveals to be also a measure of the process’ degree of interplay between the unitary and irreversible dynamics. Implementing quantum coherence on classical networks may be a door to better integrate human-like reasoning biases in stochastic models for decision-making. PMID:27030372
Pressure induced metallization with absence of structural transition in layered molybdenum diselenide

PubMed Central

Zhao, Zhao; Zhang, Haijun; Yuan, Hongtao; Wang, Shibing; Lin, Yu; Zeng, Qiaoshi; Xu, Gang; Liu, Zhenxian; Solanki, G. K.; Patel, K. D.; Cui, Yi; Hwang, Harold Y.; Mao, Wendy L.

2015-01-01

Layered transition-metal dichalcogenides have emerged as exciting material systems with atomically thin geometries and unique electronic properties. Pressure is a powerful tool for continuously tuning their crystal and electronic structures away from the pristine states. Here, we systematically investigated the pressurized behavior of MoSe2 up to ∼60 GPa using multiple experimental techniques and ab-initio calculations. MoSe2 evolves from an anisotropic two-dimensional layered network to a three-dimensional structure without a structural transition, which is a complete contrast to MoS2. The role of the chalcogenide anions in stabilizing different layered patterns is underscored by our layer sliding calculations. MoSe2 possesses highly tunable transport properties under pressure, determined by the gradual narrowing of its band-gap followed by metallization. The continuous tuning of its electronic structure and band-gap in the range of visible light to infrared suggest possible energy-variable optoelectronics applications in pressurized transition-metal dichalcogenides. PMID:26088416
Correlation Between Chain Architecture and Hydration Water Structure in Polysaccharides

NASA Astrophysics Data System (ADS)

Grossutti, Michael; Dutcher, John

The physical properties of confined water can differ dramatically from those of bulk water. Hydration water associated with polysaccharides provides a particularly important example of confined water, with differences in polysaccharide structure providing different spatially confined environments for water adsorption. We have used attenuated total reflection infrared (ATR-IR) spectroscopy to investigate the structure of hydration water in films of three different polysaccharides under controlled relative humidity (RH) conditions. We compare the results obtained for films of highly branched, monodisperse phytoglycogen nanoparticles to those obtained for two unbranched polysaccharides, hyaluronic acid (HA) and chitosan. We find similarities between water structuring in the two linear polysaccharides, and significant differences for phytoglycogen. In particular, the phytoglycogen nanoparticles exhibited high network water connectivity, and a large increase in the fraction of multimer water clusters with increasing RH, whereas the water structure for HA and chitosan was found to be insensitive to changes in RH. These measurements provide unique insight into the relationship between the chain architecture and hydration of polysaccharides.
Pressure induced metallization with absence of structural transition in layered molybdenum diselenide

DOE PAGES

Zhao, Zhao; Zhang, Haijun; Yuan, Hongtao; ...

2015-06-19

Layered transition-metal dichalcogenides have emerged as exciting material systems with atomically thin geometries and unique electronic properties. Pressure is a powerful tool for continuously tuning their crystal and electronic structures away from the pristine states. Here, we systematically investigated the pressurized behavior of MoSe 2 up to ~60 GPa using multiple experimental techniques and ab-initio calculations. MoSe 2 evolves from an anisotropic two-dimensional layered network to a three-dimensional structure without a structural transition, which is a complete contrast to MoS 2. The role of the chalcogenide anions in stabilizing different layered patterns is underscored by our layer sliding calculations. MoSemore » 2 possesses highly tunable transport properties under pressure, determined by the gradual narrowing of its band-gap followed by metallization. The continuous tuning of its electronic structure and band-gap in the range of visible light to infrared suggest possible energy-variable optoelectronics applications in pressurized transition-metal dichalcogenides.« less
Dynamic protein interaction networks and new structural paradigms in signaling

PubMed Central

Csizmok, Veronika; Follis, Ariele Viacava; Kriwacki, Richard W.; Forman-Kay, Julie D.

2017-01-01

Understanding signaling and other complex biological processes requires elucidating the critical roles of intrinsically disordered proteins and regions (IDPs/IDRs), which represent ~30% of the proteome and enable unique regulatory mechanisms. In this review we describe the structural heterogeneity of disordered proteins that underpins these mechanisms and the latest progress in obtaining structural descriptions of ensembles of disordered proteins that are needed for linking structure and dynamics to function. We describe the diverse interactions of IDPs that can have unusual characteristics such as “ultrasensitivity” and “regulated folding and unfolding”. We also summarize the mounting data showing that large-scale assembly and protein phase separation occurs within a variety of signaling complexes and cellular structures. In addition, we discuss efforts to therapeutically target disordered proteins with small molecules. Overall, we interpret the remodeling of disordered state ensembles due to binding and post-translational modifications within an expanded framework for allostery that provides significant insights into how disordered proteins transmit biological information. PMID:26922996
An exploratory comparison of name generator content: Data from rural India

PubMed Central

Shakya, Holly B.; Christakis, Nicholas A.; Fowler, James H.

2017-01-01

Since the 1970s sociologists have explored the best means for measuring social networks, although few name generator analyses have used sociocentric data or data from developing countries, partly because sociocentric studies in developing countries have been scant. Here, we analyze 12 different name generators used in a sociocentric network study conducted in 75 villages in rural Karnataka, India. Having unusual sociocentric data from a non-Western context allowed us to extend previous name generator research through the unique analyses of network structural measures, an extensive consideration of homophily, and investigation of status difference between egos and alters. We found that domestic interaction questions generated networks that were highly clustered and highly centralized. Similarity between respondents and their nominated contacts was strongest for gender, caste, and religion. We also found that domestic interaction name generators yielded the most homogeneous ties, while advice questions yielded the most heterogeneous. Participants were generally more likely to nominate those of higher social status, although certain questions, such as who participants talk to uncovered more egalitarian relationships, while other name generators elicited the names of social contacts distinctly higher or lower in status than the respondent. Some questions also seemed to uncover networks that were specific to the cultural context, suggesting that network researchers should balance local relevance with global generalizability when choosing name generators. PMID:28845086
A decomposition theory for phylogenetic networks and incompatible characters.

PubMed

Gusfield, Dan; Bansal, Vikas; Bafna, Vineet; Song, Yun S

2007-12-01

Phylogenetic networks are models of evolution that go beyond trees, incorporating non-tree-like biological events such as recombination (or more generally reticulation), which occur either in a single species (meiotic recombination) or between species (reticulation due to lateral gene transfer and hybrid speciation). The central algorithmic problems are to reconstruct a plausible history of mutations and non-tree-like events, or to determine the minimum number of such events needed to derive a given set of binary sequences, allowing one mutation per site. Meiotic recombination, reticulation and recurrent mutation can cause conflict or incompatibility between pairs of sites (or characters) of the input. Previously, we used "conflict graphs" and "incompatibility graphs" to compute lower bounds on the minimum number of recombination nodes needed, and to efficiently solve constrained cases of the minimization problem. Those results exposed the structural and algorithmic importance of the non-trivial connected components of those two graphs. In this paper, we more fully develop the structural importance of non-trivial connected components of the incompatibility and conflict graphs, proving a general decomposition theorem (Gusfield and Bansal, 2005) for phylogenetic networks. The decomposition theorem depends only on the incompatibilities in the input sequences, and hence applies to many types of phylogenetic networks, and to any biological phenomena that causes pairwise incompatibilities. More generally, the proof of the decomposition theorem exposes a maximal embedded tree structure that exists in the network when the sequences cannot be derived on a perfect phylogenetic tree. This extends the theory of perfect phylogeny in a natural and important way. The proof is constructive and leads to a polynomial-time algorithm to find the unique underlying maximal tree structure. We next examine and fully solve the major open question from Gusfield and Bansal (2005): Is it true that for every input there must be a fully decomposed phylogenetic network that minimizes the number of recombination nodes used, over all phylogenetic networks for the input. We previously conjectured that the answer is yes. In this paper, we show that the answer in is no, both for the case that only single-crossover recombination is allowed, and also for the case that unbounded multiple-crossover recombination is allowed. The latter case also resolves a conjecture recently stated in (Huson and Klopper, 2007) in the context of reticulation networks. Although the conjecture from Gusfield and Bansal (2005) is disproved in general, we show that the answer to the conjecture is yes in several natural special cases, and establish necessary combinatorial structure that counterexamples to the conjecture must possess. We also show that counterexamples to the conjecture are rare (for the case of single-crossover recombination) in simulated data.
Ensemble-based modeling and rigidity decomposition of allosteric interaction networks and communication pathways in cyclin-dependent kinases: Differentiating kinase clients of the Hsp90-Cdc37 chaperone

PubMed Central

Stetz, Gabrielle; Tse, Amanda

2017-01-01

The overarching goal of delineating molecular principles underlying differentiation of protein kinase clients and chaperone-based modulation of kinase activity is fundamental to understanding activity of many oncogenic kinases that require chaperoning of Hsp70 and Hsp90 systems to attain a functionally competent active form. Despite structural similarities and common activation mechanisms shared by cyclin-dependent kinase (CDK) proteins, members of this family can exhibit vastly different chaperone preferences. The molecular determinants underlying chaperone dependencies of protein kinases are not fully understood as structurally similar kinases may often elicit distinct regulatory responses to the chaperone. The regulatory divergences observed for members of CDK family are of particular interest as functional diversification among these kinases may be related to variations in chaperone dependencies and can be exploited in drug discovery of personalized therapeutic agents. In this work, we report the results of a computational investigation of several members of CDK family (CDK5, CDK6, CDK9) that represented a broad repertoire of chaperone dependencies—from nonclient CDK5, to weak client CDK6, and strong client CDK9. By using molecular simulations of multiple crystal structures we characterized conformational ensembles and collective dynamics of CDK proteins. We found that the elevated dynamics of CDK9 can trigger imbalances in cooperative collective motions and reduce stability of the active fold, thus creating a cascade of favorable conditions for chaperone intervention. The ensemble-based modeling of residue interaction networks and community analysis determined how differences in modularity of allosteric networks and topography of communication pathways can be linked with the client status of CDK proteins. This analysis unveiled depleted modularity of the allosteric network in CDK9 that alters distribution of communication pathways and leads to impaired signaling in the client kinase. According to our results, these network features may uniquely define chaperone dependencies of CDK clients. The perturbation response scanning and rigidity decomposition approaches identified regulatory hotspots that mediate differences in stability and cooperativity of allosteric interaction networks in the CDK structures. By combining these synergistic approaches, our study revealed dynamic and network signatures that can differentiate kinase clients and rationalize subtle divergences in the activation mechanisms of CDK family members. The therapeutic implications of these results are illustrated by identifying structural hotspots of pathogenic mutations that preferentially target regions of the increased flexibility to enable modulation of activation changes. Our study offers a network-based perspective on dynamic kinase mechanisms and drug design by unravelling relationships between protein kinase dynamics, allosteric communications and chaperone dependencies. PMID:29095844
Deep learning for computational chemistry

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

Goh, Garrett B.; Hodas, Nathan O.; Vishnu, Abhinav

The rise and fall of artificial neural networks is well documented in the scientific literature of both the fields of computer science and computational chemistry. Yet almost two decades later, we are now seeing a resurgence of interest in deep learning, a machine learning algorithm based on “deep” neural networks. Within the last few years, we have seen the transformative impact of deep learning the computer science domain, notably in speech recognition and computer vision, to the extent that the majority of practitioners in those field are now regularly eschewing prior established models in favor of deep learning models. Inmore » this review, we provide an introductory overview into the theory of deep neural networks and their unique properties as compared to traditional machine learning algorithms used in cheminformatics. By providing an overview of the variety of emerging applications of deep neural networks, we highlight its ubiquity and broad applicability to a wide range of challenges in the field, including QSAR, virtual screening, protein structure modeling, QM calculations, materials synthesis and property prediction. In reviewing the performance of deep neural networks, we observed a consistent outperformance against non neural networks state-of-the-art models across disparate research topics, and deep neural network based models often exceeded the “glass ceiling” expectations of their respective tasks. Coupled with the maturity of GPU-accelerated computing for training deep neural networks and the exponential growth of chemical data on which to train these networks on, we anticipate that deep learning algorithms will be a useful tool and may grow into a pivotal role for various challenges in the computational chemistry field.« less
Can SNMP be Used to Create a Silent SS in an 802.16 Implementation

DTIC Science & Technology

2008-09-01

wireless transmissions by using the Simple Network Management Protocol (SNMP). SNMP is a networking protocol that can be used by network ...802.16 as a unique networking technology. In a more familiar wireless networking environment like Wi-Fi, there is no central scheduler for access to...much a concern due to the scheduling algorithm , this power saving method provides good transmission security as a
Community-Based Research Networks: Development and Lessons Learned in an Emerging Field.

ERIC Educational Resources Information Center

Stoecker, Randy; Ambler, Susan H.; Cutforth, Nick; Donohue, Patrick; Dougherty, Dan; Marullo, Sam; Nelson, Kris S.; Stutts, Nancy B.

2003-01-01

Compares seven multi-institutional community-based research networks in Appalachia; Colorado; District of Columbia; Minneapolis-St. Paul; Philadelphia; Richmond, Virginia; and Trenton, New Jersey. After reviewing the histories of the networks, conducts a comparative SWOT analysis, showing their common and unique strengths, weaknesses,…
Facilitating and securing offline e-medicine service through image steganography.

PubMed

Kamal, A H M; Islam, M Mahfuzul

2014-06-01

E-medicine is a process to provide health care services to people using the Internet or any networking technology. In this Letter, a new idea is proposed to model the physical structure of the e-medicine system to better provide offline health care services. Smart cards are used to authenticate the user singly. A very unique technique is also suggested to verify the card owner's identity and to embed secret data to the card while providing patients' reports either at booths or at the e-medicine server system. The simulation results of card authentication and embedding procedure justify the proposed implementation.
Artificial Neural Network approach to develop unique Classification and Raga identification tools for Pattern Recognition in Carnatic Music

NASA Astrophysics Data System (ADS)

Srimani, P. K.; Parimala, Y. G.

2011-12-01

A unique approach has been developed to study patterns in ragas of Carnatic Classical music based on artificial neural networks. Ragas in Carnatic music which have found their roots in the Vedic period, have grown on a Scientific foundation over thousands of years. However owing to its vastness and complexities it has always been a challenge for scientists and musicologists to give an all encompassing perspective both qualitatively and quantitatively. Cognition, comprehension and perception of ragas in Indian classical music have always been the subject of intensive research, highly intriguing and many facets of these are hitherto not unravelled. This paper is an attempt to view the melakartha ragas with a cognitive perspective using artificial neural network based approach which has given raise to very interesting results. The 72 ragas of the melakartha system were defined through the combination of frequencies occurring in each of them. The data sets were trained using several neural networks. 100% accurate pattern recognition and classification was obtained using linear regression, TLRN, MLP and RBF networks. Performance of the different network topologies, by varying various network parameters, were compared. Linear regression was found to be the best performing network.
Combining cognitive engineering and information fusion architectures to build effective joint systems

NASA Astrophysics Data System (ADS)

Sliva, Amy L.; Gorman, Joe; Voshell, Martin; Tittle, James; Bowman, Christopher

2016-05-01

The Dual Node Decision Wheels (DNDW) architecture concept was previously described as a novel approach toward integrating analytic and decision-making processes in joint human/automation systems in highly complex sociotechnical settings. In this paper, we extend the DNDW construct with a description of components in this framework, combining structures of the Dual Node Network (DNN) for Information Fusion and Resource Management with extensions on Rasmussen's Decision Ladder (DL) to provide guidance on constructing information systems that better serve decision-making support requirements. The DNN takes a component-centered approach to system design, decomposing each asset in terms of data inputs and outputs according to their roles and interactions in a fusion network. However, to ensure relevancy to and organizational fitment within command and control (C2) processes, principles from cognitive systems engineering emphasize that system design must take a human-centered systems view, integrating information needs and decision making requirements to drive the architecture design and capabilities of network assets. In the current work, we present an approach for structuring and assessing DNDW systems that uses a unique hybrid DNN top-down system design with a human-centered process design, combining DNN node decomposition with artifacts from cognitive analysis (i.e., system abstraction decomposition models, decision ladders) to provide work domain and task-level insights at different levels in an example intelligence, surveillance, and reconnaissance (ISR) system setting. This DNDW structure will ensure not only that the information fusion technologies and processes are structured effectively, but that the resulting information products will align with the requirements of human decision makers and be adaptable to different work settings .
Boolean network inference from time series data incorporating prior biological knowledge.

PubMed

Haider, Saad; Pal, Ranadip

2012-01-01

Numerous approaches exist for modeling of genetic regulatory networks (GRNs) but the low sampling rates often employed in biological studies prevents the inference of detailed models from experimental data. In this paper, we analyze the issues involved in estimating a model of a GRN from single cell line time series data with limited time points. We present an inference approach for a Boolean Network (BN) model of a GRN from limited transcriptomic or proteomic time series data based on prior biological knowledge of connectivity, constraints on attractor structure and robust design. We applied our inference approach to 6 time point transcriptomic data on Human Mammary Epithelial Cell line (HMEC) after application of Epidermal Growth Factor (EGF) and generated a BN with a plausible biological structure satisfying the data. We further defined and applied a similarity measure to compare synthetic BNs and BNs generated through the proposed approach constructed from transitions of various paths of the synthetic BNs. We have also compared the performance of our algorithm with two existing BN inference algorithms. Through theoretical analysis and simulations, we showed the rarity of arriving at a BN from limited time series data with plausible biological structure using random connectivity and absence of structure in data. The framework when applied to experimental data and data generated from synthetic BNs were able to estimate BNs with high similarity scores. Comparison with existing BN inference algorithms showed the better performance of our proposed algorithm for limited time series data. The proposed framework can also be applied to optimize the connectivity of a GRN from experimental data when the prior biological knowledge on regulators is limited or not unique.
Inferring social structure and its drivers from refuge use in the desert tortoise, a relatively solitary species

USGS Publications Warehouse

Sah, Pratha; Nussear, Kenneth E.; Esque, Todd C.; Aiello, Christina M.; Hudson, Peter J.; Bansal, Shweta

2016-01-01

For several species, refuges (such as burrows, dens, roosts, nests) are an essential resource for protection from predators and extreme environmental conditions. Refuges also serve as focal sites for social interactions, including mating, courtship, and aggression. Knowledge of refuge use patterns can therefore provide information about social structure, mating, and foraging success, as well as the robustness and health of wildlife populations, especially for species considered to be relatively solitary. In this study, we construct networks of burrow use to infer social associations in a threatened wildlife species typically considered solitary—the desert tortoise. We show that tortoise social networks are significantly different than null networks of random associations, and have moderate spatial constraints. We next use statistical models to identify major mechanisms behind individual-level variation in tortoise burrow use, popularity of burrows in desert tortoise habitat, and test for stressor-driven changes in refuge use patterns. We show that seasonal variation has a strong impact on tortoise burrow switching behavior. On the other hand, burrow age and topographical condition influence the number of tortoises visiting a burrow in desert tortoise habitat. Of three major population stressors affecting this species (translocation, drought, disease), translocation alters tortoise burrow switching behavior, with translocated animals visiting fewer unique burrows than residents. In a species that is not social, our study highlights the importance of leveraging refuge use behavior to study the presence of and mechanisms behind non-random social structure and individual-level variation. Our analysis of the impact of stressors on refuge-based social structure further emphasizes the potential of this method to detect environmental or anthropogenic disturbances.
The biocontrol agent Pseudomonas chlororaphis PA23 primes Brassica napus defenses through distinct gene networks.

PubMed

Duke, Kelly A; Becker, Michael G; Girard, Ian J; Millar, Jenna L; Dilantha Fernando, W G; Belmonte, Mark F; de Kievit, Teresa R

2017-06-19

The biological control agent Pseudomonas chlororaphis PA23 is capable of protecting Brassica napus (canola) from the necrotrophic fungus Sclerotinia sclerotiorum via direct antagonism. While we have elucidated bacterial genes and gene products responsible biocontrol, little is known about how the host plant responds to bacterial priming on the leaf surface, including global changes in gene activity in the presence and absence of S. sclerotiorum. Application of PA23 to the aerial surfaces of canola plants reduced the number of S. sclerotiorum lesion-forming petals by 91.1%. RNA sequencing of the host pathogen interface showed that pretreatment with PA23 reduced the number of genes upregulated in response to S. sclerotiorum by 16-fold. By itself, PA23 activated unique defense networks indicative of defense priming. Genes encoding MAMP-triggered immunity receptors detecting flagellin and peptidoglycan were downregulated in PA23 only-treated plants, consistent with post-stimulus desensitization. Downstream, we observed reactive oxygen species (ROS) production involving low levels of H 2 O 2 and overexpression of genes associated with glycerol-3-phosphate (G3P)-mediated systemic acquired resistance (SAR). Leaf chloroplasts exhibited increased thylakoid membrane structures and chlorophyll content, while lipid metabolic processes were upregulated. In addition to directly antagonizing S. sclerotiorum, PA23 primes the plant defense response through induction of unique local and systemic defense networks. This study provides novel insight into the effects of biocontrol agents applied to the plant phyllosphere. Understanding these interactions will aid in the development of biocontrol systems as an alternative to chemical pesticides for protection of important crop systems.
Mapping human brain networks with cortico-cortical evoked potentials.

PubMed

Keller, Corey J; Honey, Christopher J; Mégevand, Pierre; Entz, Laszlo; Ulbert, Istvan; Mehta, Ashesh D

2014-10-05

The cerebral cortex forms a sheet of neurons organized into a network of interconnected modules that is highly expanded in humans and presumably enables our most refined sensory and cognitive abilities. The links of this network form a fundamental aspect of its organization, and a great deal of research is focusing on understanding how information flows within and between different regions. However, an often-overlooked element of this connectivity regards a causal, hierarchical structure of regions, whereby certain nodes of the cortical network may exert greater influence over the others. While this is difficult to ascertain non-invasively, patients undergoing invasive electrode monitoring for epilepsy provide a unique window into this aspect of cortical organization. In this review, we highlight the potential for cortico-cortical evoked potential (CCEP) mapping to directly measure neuronal propagation across large-scale brain networks with spatio-temporal resolution that is superior to traditional neuroimaging methods. We first introduce effective connectivity and discuss the mechanisms underlying CCEP generation. Next, we highlight how CCEP mapping has begun to provide insight into the neural basis of non-invasive imaging signals. Finally, we present a novel approach to perturbing and measuring brain network function during cognitive processing. The direct measurement of CCEPs in response to electrical stimulation represents a potentially powerful clinical and basic science tool for probing the large-scale networks of the human cerebral cortex. © 2014 The Author(s) Published by the Royal Society. All rights reserved.
Stochastic lumping analysis for linear kinetics and its application to the fluctuation relations between hierarchical kinetic networks.

PubMed

Deng, De-Ming; Chang, Cheng-Hung

2015-05-14

Conventional studies of biomolecular behaviors rely largely on the construction of kinetic schemes. Since the selection of these networks is not unique, a concern is raised whether and under which conditions hierarchical schemes can reveal the same experimentally measured fluctuating behaviors and unique fluctuation related physical properties. To clarify these questions, we introduce stochasticity into the traditional lumping analysis, generalize it from rate equations to chemical master equations and stochastic differential equations, and extract the fluctuation relations between kinetically and thermodynamically equivalent networks under intrinsic and extrinsic noises. The results provide a theoretical basis for the legitimate use of low-dimensional models in the studies of macromolecular fluctuations and, more generally, for exploring stochastic features in different levels of contracted networks in chemical and biological kinetic systems.
Development of Structural Covariance From Childhood to Adolescence: A Longitudinal Study in 22q11.2DS.

PubMed

Sandini, Corrado; Zöller, Daniela; Scariati, Elisa; Padula, Maria C; Schneider, Maude; Schaer, Marie; Van De Ville, Dimitri; Eliez, Stephan

2018-01-01

Background: Schizophrenia is currently considered a neurodevelopmental disorder of connectivity. Still few studies have investigated how brain networks develop in children and adolescents who are at risk for developing psychosis. 22q11.2 Deletion Syndrome (22q11DS) offers a unique opportunity to investigate the pathogenesis of schizophrenia from a neurodevelopmental perspective. Structural covariance (SC) is a powerful approach to explore morphometric relations between brain regions that can furthermore detect biomarkers of psychosis, both in 22q11DS and in the general population. Methods: Here we implement a state-of-the-art sliding-window approach to characterize maturation of SC network architecture in a large longitudinal cohort of patients with 22q11DS (110 with 221 visits) and healthy controls (117 with 211 visits). We furthermore propose a new clustering-based approach to group regions according to trajectories of structural connectivity maturation. We correlate measures of SC with development of working memory, a core executive function that is highly affected in both idiopathic psychosis and 22q11DS. Finally, in 22q11DS we explore correlations between SC dysconnectivity and severity of internalizing psychopathology. Results: In HCs network architecture underwent a quadratic developmental trajectory maturing up to mid-adolescence. Late-childhood maturation was particularly evident for fronto-parietal cortices, while Default-Mode-Network-related regions showed a more protracted linear development. Working memory performance was positively correlated with network segregation and fronto-parietal connectivity. In 22q11DS, we demonstrate aberrant maturation of SC with disturbed architecture selectively emerging during adolescence and correlating more severe internalizing psychopathology. Patients also presented a lack of typical network development during late-childhood, that was particularly prominent for frontal connectivity. Conclusions: Our results suggest that SC maturation may underlie critical cognitive development occurring during late-childhood in healthy controls. Aberrant trajectories of SC maturation may reflect core developmental features of 22q11DS, including disturbed cognitive maturation during childhood and predisposition to internalizing psychopathology and psychosis during adolescence.

Joint inversion of surface wave dispersion and receiver functions for crustal structure in Oklahoma

NASA Astrophysics Data System (ADS)

Guo, Hao

The surge in seismicity in Oklahoma starting in 2008 raises questions about the actual locations of the earthquakes in the upper crust. The key to answering this is an improved crustal model that explains as many observations as possible. Love and Rayleigh wave dispersion, teleseismic P-wave receiver functions and some unique transverse motions observed at distances less than 100 km that are characteristics of rays reverberating in a basin provide data to derive the crustal model. The surface wave dispersion data set consists of over 300,000 Love/Rayleigh phase/group values obtained from ambient noise cross-correlation of BH channels of the 133 Transportable Array (TA) stations of Earthscope to periods as short as 2 seconds. Station coverage is dense enough to perform the tomography on a 25*25 km grid that should be able to image shallow geological structures. In addition, receiver functions were obtained using teleseismic data recorded from 3 US Geological Survey Networks (GS) stations and 6 Oklahoma Seismic Network (OK) stations from 2011 to 2014. The 1-D S-wave velocity models derived by the joint inversion of surface wave dispersion and receiver functions with geological constraints are tested by fitting the independent transverse seismograms. This test also provides constraints on the earthquake depths in relation to the geological structure.
Early Cerebellar Network Shifting in Spinocerebellar Ataxia Type 6

PubMed Central

Falcon, M.I.; Gomez, C.M.; Chen, E.E.; Shereen, A.; Solodkin, A.

2016-01-01

Spinocerebellar ataxia 6 (SCA6), an autosomal dominant degenerative disease, is characterized by diplopia, gait ataxia, and incoordination due to severe progressive degeneration of Purkinje cells in the vestibulo- and spinocerebellum. Ocular motor deficits are common, including difficulty fixating on moving objects, nystagmus and disruption of smooth pursuit movements. In presymptomatic SCA6, there are alterations in saccades and smooth-pursuit movements. We sought to assess functional and structural changes in cerebellar connectivity associated with a visual task, hypothesizing that gradual changes would parallel disease progression. We acquired functional magnetic resonance imaging and diffusion tensor imaging data during a passive smooth-pursuit task in 14 SCA6 patients, representing a range of disease duration and severity, and performed a cross-sectional comparison of cerebellar networks compared with healthy controls. We identified a shift in activation from vermis in presymptomatic individuals to lateral cerebellum in moderate-to-severe cases. Concomitantly, effective connectivity between regions of cerebral cortex and cerebellum was at its highest in moderate cases, and disappeared in severe cases. Finally, we noted structural differences in the cerebral and cerebellar peduncles. These unique results, spanning both functional and structural domains, highlight widespread changes in SCA6 and compensatory mechanisms associated with cerebellar physiology that could be utilized in developing new therapies. PMID:26209844
Ultrafine nano-network structured bacterial cellulose as reductant and bridging ligands to fabricate ultrathin K-birnessite type MnO2 nanosheets for supercapacitors

NASA Astrophysics Data System (ADS)

Zhang, Xiaojuan; He, Mingqian; He, Ping; Li, Caixia; Liu, Huanhuan; Zhang, Xingquan; Ma, Yongjun

2018-03-01

In this work, nanostructured ultrathin K-birnessite type MnO2 nanosheets are successfully prepared by a rapid and environmently friendly hydrothermal method, which involves only a facile redox reaction between KMnO4 and nano-network structured bacterial cellulose with abundant hydroxyl groups. The results show that the unique three-dimensional interwoven structured bacterial cellulose acts as not only reductant but also bridging ligands for assembling nanoscaled building units to control the desired morphology of prepared MnO2. Furthermore, electrochemical performances of prepared MnO2 are investigated as electrode materials for supercapacitors by cyclic voltammetry, galvanostatic charge/discharge and electrochemical impedance spectrum in 1.0 M Na2SO4 electrolyte. The resulting ultrathin K-birnessite type MnO2 nanosheets based electrode exhibits higher capacitance (328.2 F g-1 at 0.2 A g-1), excellent rate capability (328.2 F g-1 and 200.4 F g-1 at 0.2 A g-1 and 2.0 A g-1, respectively) and satisfactory cyclic stability (91.6% of initial capacitance even after 2000 cycles at 3.0 A g-1). This work suggests that bacterial cellulose as reductant is a promising candidate in the development of nanostructures of metal oxides.
New understanding of the complex structure of knee menisci: implications for injury risk and repair potential for athletes.

PubMed

Rattner, J B; Matyas, J R; Barclay, L; Holowaychuk, S; Sciore, P; Lo, I K Y; Shrive, N G; Frank, C B; Achari, Y; Hart, D A

2011-08-01

Menisci help maintain the structural integrity of the knee. However, the poor healing potential of the meniscus following a knee injury can not only end a career in sports but lead to osteoarthritis later in life. Complete understanding of meniscal structure is essential for evaluating its risk for injury and subsequent successful repair. This study used novel approaches to elucidate meniscal architecture. The radial and circumferential collagen fibrils in the meniscus were investigated using novel tissue-preparative techniques for light and electron microscopic studies. The results demonstrate a unique architecture based on differences in the packaging of the fundamental collagen fibrils. For radial arrays, the collagen fibrils are arranged in parallel into ∼10 μm bundles, which associate laterally to form flat sheets of varying dimensions that bifurcate and come together to form a honeycomb network within the body of the meniscus. In contrast, the circumferential arrays display a complex network of collagen fibrils arranged into ∼5 μm bundles. Interestingly, both types of architectural organization of collagen fibrils in meniscus are conserved across mammalian species and are age and sex independent. These findings imply that disruptions in meniscal architecture following an injury contribute to poor prognosis for functional repair. © 2010 John Wiley & Sons A/S.
Correlation Between Chain Architecture and Hydration Water Structure in Polysaccharides.

PubMed

Grossutti, Michael; Dutcher, John R

2016-03-14

The physical properties of confined water can differ dramatically from those of bulk water. Hydration water associated with polysaccharides provides a particularly interesting example of confined water, because differences in polysaccharide structure provide different spatially confined environments for water sorption. We have used attenuated total reflection infrared (ATR-IR) spectroscopy to investigate the structure of hydration water in films of three different polysaccharides under controlled relative humidity (RH) conditions. We compare the results obtained for films of highly branched, dendrimer-like phytoglycogen nanoparticles to those obtained for two unbranched polysaccharides, hyaluronic acid (HA), and chitosan. We find similarities between the water structuring in the two linear polysaccharides and significant differences for phytoglycogen. In particular, the results suggest that the high degree of branching in phytoglycogen leads to a much more well-ordered water structure (low density, high connectivity network water), indicating the strong influence of chain architecture on the structuring of water. These measurements provide unique insight into the relationship between the structure and hydration of polysaccharides, which is important for understanding and exploiting these sustainable nanomaterials in a wide range of applications.
Diagnostics in the Extendable Integrated Support Environment (EISE)

NASA Technical Reports Server (NTRS)

Brink, James R.; Storey, Paul

1988-01-01

Extendable Integrated Support Environment (EISE) is a real-time computer network consisting of commercially available hardware and software components to support systems level integration, modifications, and enhancement to weapons systems. The EISE approach offers substantial potential savings by eliminating unique support environments in favor of sharing common modules for the support of operational weapon systems. An expert system is being developed that will help support diagnosing faults in this network. This is a multi-level, multi-expert diagnostic system that uses experiential knowledge relating symptoms to faults and also reasons from structural and functional models of the underlying physical model when experiential reasoning is inadequate. The individual expert systems are orchestrated by a supervisory reasoning controller, a meta-level reasoner which plans the sequence of reasoning steps to solve the given specific problem. The overall system, termed the Diagnostic Executive, accesses systems level performance checks and error reports, and issues remote test procedures to formulate and confirm fault hypotheses.
Printing Highly Controlled Suspended Carbon Nanotube Network on Micro-patterned Superhydrophobic Flexible Surface

PubMed Central

Li, Bo; Wang, Xin; Jung, Hyun Young; Kim, Young Lae; Robinson, Jeremy T.; Zalalutdinov, Maxim; Hong, Sanghyun; Hao, Ji; Ajayan, Pulickel M.; Wan, Kai-Tak; Jung, Yung Joon

2015-01-01

Suspended single-walled carbon nanotubes (SWCNTs) offer unique functionalities for electronic and electromechanical systems. Due to their outstanding flexible nature, suspended SWCNT architectures have great potential for integration into flexible electronic systems. However, current techniques for integrating SWCNT architectures with flexible substrates are largely absent, especially in a manner that is both scalable and well controlled. Here, we present a new nanostructured transfer paradigm to print scalable and well-defined suspended nano/microscale SWCNT networks on 3D patterned flexible substrates with micro- to nanoscale precision. The underlying printing/transfer mechanism, as well as the mechanical, electromechanical, and mechanical resonance properties of the suspended SWCNTs are characterized, including identifying metrics relevant for reliable and sensitive device structures. Our approach represents a fast, scalable and general method for building suspended nano/micro SWCNT architectures suitable for flexible sensing and actuation systems. PMID:26511284
Printing Highly Controlled Suspended Carbon Nanotube Network on Micro-patterned Superhydrophobic Flexible Surface.

PubMed

Li, Bo; Wang, Xin; Jung, Hyun Young; Kim, Young Lae; Robinson, Jeremy T; Zalalutdinov, Maxim; Hong, Sanghyun; Hao, Ji; Ajayan, Pulickel M; Wan, Kai-Tak; Jung, Yung Joon

2015-10-29

Suspended single-walled carbon nanotubes (SWCNTs) offer unique functionalities for electronic and electromechanical systems. Due to their outstanding flexible nature, suspended SWCNT architectures have great potential for integration into flexible electronic systems. However, current techniques for integrating SWCNT architectures with flexible substrates are largely absent, especially in a manner that is both scalable and well controlled. Here, we present a new nanostructured transfer paradigm to print scalable and well-defined suspended nano/microscale SWCNT networks on 3D patterned flexible substrates with micro- to nanoscale precision. The underlying printing/transfer mechanism, as well as the mechanical, electromechanical, and mechanical resonance properties of the suspended SWCNTs are characterized, including identifying metrics relevant for reliable and sensitive device structures. Our approach represents a fast, scalable and general method for building suspended nano/micro SWCNT architectures suitable for flexible sensing and actuation systems.
Practice-based research networks (PBRNs) are promising laboratories for conducting dissemination and implementation research.

PubMed

Heintzman, John; Gold, Rachel; Krist, Alexander; Crosson, Jay; Likumahuwa, Sonja; DeVoe, Jennifer E

2014-01-01

Dissemination and implementation science addresses the application of research findings in varied health care settings. Despite the potential benefit of dissemination and implementation work to primary care, ideal laboratories for this science have been elusive. Practice-based research networks (PBRNs) have a long history of conducting research in community clinical settings, demonstrating an approach that could be used to execute multiple research projects over time in broad and varied settings. PBRNs also are uniquely structured and increasingly involved in pragmatic trials, a research design central to dissemination and implementation science. We argue that PBRNs and dissemination and implementation scientists are ideally suited to work together and that the collaboration of these 2 groups will yield great value for the future of primary care and the delivery of evidence-based health care. © Copyright 2014 by the American Board of Family Medicine.
Intermediate Filaments Play a Pivotal Role in Regulating Cell Architecture and Function.

PubMed

Lowery, Jason; Kuczmarski, Edward R; Herrmann, Harald; Goldman, Robert D

2015-07-10

Intermediate filaments (IFs) are composed of one or more members of a large family of cytoskeletal proteins, whose expression is cell- and tissue type-specific. Their importance in regulating the physiological properties of cells is becoming widely recognized in functions ranging from cell motility to signal transduction. IF proteins assemble into nanoscale biopolymers with unique strain-hardening properties that are related to their roles in regulating the mechanical integrity of cells. Furthermore, mutations in the genes encoding IF proteins cause a wide range of human diseases. Due to the number of different types of IF proteins, we have limited this short review to cover structure and function topics mainly related to the simpler homopolymeric IF networks composed of vimentin, and specifically for diseases, the related muscle-specific desmin IF networks. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.
Fabricating Ir/C Nanofiber Networks as Free-Standing Air Cathodes for Rechargeable Li-CO2 Batteries.

PubMed

Wang, Chengyi; Zhang, Qinming; Zhang, Xin; Wang, Xin-Gai; Xie, Zhaojun; Zhou, Zhen

2018-06-07

Li-CO 2 batteries are promising energy storage systems by utilizing CO 2 at the same time, though there are still some critical barriers before its practical applications such as high charging overpotential and poor cycling stability. In this work, iridium/carbon nanofibers (Ir/CNFs) are prepared via electrospinning and subsequent heat treatment, and are used as cathode catalysts for rechargeable Li-CO 2 batteries. Benefitting from the unique porous network structure and the high activity of ultrasmall Ir nanoparticles, Ir/CNFs exhibit excellent CO 2 reduction and evolution activities. The Li-CO 2 batteries present extremely large discharge capacity, high coulombic efficiency, and long cycling life. Moreover, free-standing Ir/CNF films are used directly as air cathodes to assemble Li-CO 2 batteries, which show high energy density and ultralong operation time, demonstrating great potential for practical applications. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
A Systematic Review of Collaboration and Network Research in the Public Affairs Literature: Implications for Public Health Practice and Research

PubMed Central

Shoup, Jo Ann; Miller, Sara

2012-01-01

Objectives. We explored and analyzed how findings from public affairs research can inform public health research and practice, specifically in the area of interorganizational collaboration, one of the most promising practice-based approaches in the public health field. Methods. We conducted a systematic review of the public affairs literature by following a grounded theory approach. We coded 151 articles for demographics and empirical findings (n = 258). Results. Three primary findings stand out in the public affairs literature: network structure affects governance, management strategies exist for administrators, and collaboration can be linked to outcomes. These findings are linked to priorities in public health practice. Conclusions. Overall, we found that public affairs has a long and rich history of research in collaborations that offers unique organizational theory and management tools to public health practitioners. PMID:22021311
Giant hub Src and Syk tyrosine kinase thermodynamic profiles recapitulate evolution

NASA Astrophysics Data System (ADS)

Phillips, J. C.

2017-10-01

Thermodynamic scaling theory, previously applied mainly to small proteins, here analyzes quantitative evolution of the titled functional network giant hub enzymes. The broad domain structure identified homologically is confirmed hydropathically using amino acid sequences only. The most surprising results concern the evolution of the tyrosine kinase globular surface roughness from avians to mammals, which is first order, compared to the evolution within mammals from rodents to humans, which is second order. The mystery of the unique amide terminal region of proto oncogene tyrosine protein kinase is resolved by the discovery there of a rare hydroneutral septad targeting cluster, which is paralleled by an equally rare octad catalytic cluster in tyrosine kinase in humans and a few other species (cat and dog). These results, which go far towards explaining why these proteins are among the largest giant hubs in protein interaction networks, use no adjustable parameters.
In Situ Synthesis of Vertical Standing Nanosized NiO Encapsulated in Graphene as Electrodes for High-Performance Supercapacitors.

PubMed

Lin, Jinghuang; Jia, Henan; Liang, Haoyan; Chen, Shulin; Cai, Yifei; Qi, Junlei; Qu, Chaoqun; Cao, Jian; Fei, Weidong; Feng, Jicai

2018-03-01

NiO is a promising electrode material for supercapacitors. Herein, the novel vertically standing nanosized NiO encapsulated in graphene layers (G@NiO) are rationally designed and synthesized as nanosheet arrays. This unique vertical standing structure of G@NiO nanosheet arrays can enlarge the accessible surface area with electrolytes, and has the benefits of short ion diffusion path and good charge transport. Further, an interconnected graphene conductive network acts as binder to encapsulate the nanosized NiO particles as core-shell structure, which can promote the charge transport and maintain the structural stability. Consequently, the optimized G@NiO hybrid electrodes exhibit a remarkably enhanced specific capacity up to 1073 C g -1 and excellent cycling stability. This study provides a facial strategy to design and construct high-performance metal oxides for energy storage.
Controlling Hydrogel Mechanics via Bio-Inspired Polymer-Nanoparticle Bond Dynamics.

PubMed

Li, Qiaochu; Barrett, Devin G; Messersmith, Phillip B; Holten-Andersen, Niels

2016-01-26

Interactions between polymer molecules and inorganic nanoparticles can play a dominant role in nanocomposite material mechanics, yet control of such interfacial interaction dynamics remains a significant challenge particularly in water. This study presents insights on how to engineer hydrogel material mechanics via nanoparticle interface-controlled cross-link dynamics. Inspired by the adhesive chemistry in mussel threads, we have incorporated iron oxide nanoparticles (Fe3O4 NPs) into a catechol-modified polymer network to obtain hydrogels cross-linked via reversible metal-coordination bonds at Fe3O4 NP surfaces. Unique material mechanics result from the supra-molecular cross-link structure dynamics in the gels; in contrast to the previously reported fluid-like dynamics of transient catechol-Fe(3+) cross-links, the catechol-Fe3O4 NP structures provide solid-like yet reversible hydrogel mechanics. The structurally controlled hierarchical mechanics presented here suggest how to develop hydrogels with remote-controlled self-healing dynamics.
Accommodation of structural rearrangements in the huntingtin-interacting protein 1 coiled-coil domain.

PubMed

Wilbur, Jeremy D; Hwang, Peter K; Brodsky, Frances M; Fletterick, Robert J

2010-03-01

Huntingtin-interacting protein 1 (HIP1) is an important link between the actin cytoskeleton and clathrin-mediated endocytosis machinery. HIP1 has also been implicated in the pathogenesis of Huntington's disease. The binding of HIP1 to actin is regulated through an interaction with clathrin light chain. Clathrin light chain binds to a flexible coiled-coil domain in HIP1 and induces a compact state that is refractory to actin binding. To understand the mechanism of this conformational regulation, a high-resolution crystal structure of a stable fragment from the HIP1 coiled-coil domain was determined. The flexibility of the HIP1 coiled-coil region was evident from its variation from a previously determined structure of a similar region. A hydrogen-bond network and changes in coiled-coil monomer interaction suggest that the HIP1 coiled-coil domain is uniquely suited to allow conformational flexibility.
Structure and function of APH(4)-Ia, a hygromycin B resistance enzyme.

PubMed

Stogios, Peter J; Shakya, Tushar; Evdokimova, Elena; Savchenko, Alexei; Wright, Gerard D

2011-01-21

The aminoglycoside phosphotransferase (APH) APH(4)-Ia is one of two enzymes responsible for bacterial resistance to the atypical aminoglycoside antibiotic hygromycin B (hygB). The crystal structure of APH(4)-Ia enzyme was solved in complex with hygB at 1.95 Å resolution. The APH(4)-Ia structure adapts a general two-lobe architecture shared by other APH enzymes and eukaryotic kinases, with the active site located at the interdomain cavity. The enzyme forms an extended hydrogen bond network with hygB primarily through polar and acidic side chain groups. Individual alanine substitutions of seven residues involved in hygB binding did not have significant effect on APH(4)-Ia enzymatic activity, indicating that the binding affinity is spread across a distributed network. hygB appeared as the only substrate recognized by APH(4)-Ia among the panel of 14 aminoglycoside compounds. Analysis of the active site architecture and the interaction with the hygB molecule demonstrated several unique features supporting such restricted substrate specificity. Primarily the APH(4)-Ia substrate-binding site contains a cluster of hydrophobic residues that provides a complementary surface to the twisted structure of the substrate. Similar to APH(2″) enzymes, the APH(4)-Ia is able to utilize either ATP or GTP for phosphoryl transfer. The defined structural features of APH(4)-Ia interactions with hygB and the promiscuity in regard to ATP or GTP binding could be exploited for the design of novel aminoglycoside antibiotics or inhibitors of this enzyme.
Hierarchical auto-configuration addressing in mobile ad hoc networks (HAAM)

NASA Astrophysics Data System (ADS)

Ram Srikumar, P.; Sumathy, S.

2017-11-01

Addressing plays a vital role in networking to identify devices uniquely. A device must be assigned with a unique address in order to participate in the data communication in any network. Different protocols defining different types of addressing are proposed in literature. Address auto-configuration is a key requirement for self organizing networks. Existing auto-configuration based addressing protocols require broadcasting probes to all the nodes in the network before assigning a proper address to a new node. This needs further broadcasts to reflect the status of the acquired address in the network. Such methods incur high communication overheads due to repetitive flooding. To address this overhead, a new partially stateful address allocation scheme, namely Hierarchical Auto-configuration Addressing (HAAM) scheme is extended and proposed. Hierarchical addressing basically reduces latency and overhead caused during address configuration. Partially stateful addressing algorithm assigns addresses without the need for flooding and global state awareness, which in turn reduces the communication overhead and space complexity respectively. Nodes are assigned addresses hierarchically to maintain the graph of the network as a spanning tree which helps in effectively avoiding the broadcast storm problem. Proposed algorithm for HAAM handles network splits and merges efficiently in large scale mobile ad hoc networks incurring low communication overheads.
The Structure and Evolution of Buyer-Supplier Networks

PubMed Central

Mizuno, Takayuki; Souma, Wataru; Watanabe, Tsutomu

2014-01-01

In this paper, we investigate the structure and evolution of customer-supplier networks in Japan using a unique dataset that contains information on customer and supplier linkages for more than 500,000 incorporated non-financial firms for the five years from 2008 to 2012. We find, first, that the number of customer links is unequal across firms; the customer link distribution has a power-law tail with an exponent of unity (i.e., it follows Zipf's law). We interpret this as implying that competition among firms to acquire new customers yields winners with a large number of customers, as well as losers with fewer customers. We also show that the shortest path length for any pair of firms is, on average, 4.3 links. Second, we find that link switching is relatively rare. Our estimates indicate that the survival rate per year for customer links is 92 percent and for supplier links 93 percent. Third and finally, we find that firm growth rates tend to be more highly correlated the closer two firms are to each other in a customer-supplier network (i.e., the smaller is the shortest path length for the two firms). This suggests that a non-negligible portion of fluctuations in firm growth stems from the propagation of microeconomic shocks – shocks affecting only a particular firm – through customer-supplier chains. PMID:25000368
The structure and evolution of buyer-supplier networks.

PubMed

Mizuno, Takayuki; Souma, Wataru; Watanabe, Tsutomu

2014-01-01

In this paper, we investigate the structure and evolution of customer-supplier networks in Japan using a unique dataset that contains information on customer and supplier linkages for more than 500,000 incorporated non-financial firms for the five years from 2008 to 2012. We find, first, that the number of customer links is unequal across firms; the customer link distribution has a power-law tail with an exponent of unity (i.e., it follows Zipf's law). We interpret this as implying that competition among firms to acquire new customers yields winners with a large number of customers, as well as losers with fewer customers. We also show that the shortest path length for any pair of firms is, on average, 4.3 links. Second, we find that link switching is relatively rare. Our estimates indicate that the survival rate per year for customer links is 92 percent and for supplier links 93 percent. Third and finally, we find that firm growth rates tend to be more highly correlated the closer two firms are to each other in a customer-supplier network (i.e., the smaller is the shortest path length for the two firms). This suggests that a non-negligible portion of fluctuations in firm growth stems from the propagation of microeconomic shocks - shocks affecting only a particular firm - through customer-supplier chains.

Reduced frontal cortex thickness and cortical volume associated with pathological narcissism.

PubMed

Mao, Yu; Sang, Na; Wang, Yongchao; Hou, Xin; Huang, Hui; Wei, Dongtao; Zhang, Jinfu; Qiu, Jiang

2016-07-22

Pathological narcissism is often characterized by arrogant behavior, a lack of empathy, and willingness to exploit other individuals. Generally, individuals with high levels of narcissism are more likely to suffer mental disorders. However, the brain structural basis of individual pathological narcissism trait among healthy people has not yet been investigated with surface-based morphometry. Thus, in this study, we investigated the relationship between cortical thickness (CT), cortical volume (CV), and individual pathological narcissism in a large healthy sample of 176 college students. Multiple regression was used to analyze the correlation between regional CT, CV, and the total Pathological Narcissism Inventory (PNI) score, adjusting for age, sex, and total intracranial volume. The results showed that the PNI score was significantly negatively associated with CT and CV in the right dorsolateral prefrontal cortex (DLPFC, key region of the central executive network, CEN), which might be associated with impaired emotion regulation processes. Furthermore, the PNI score showed significant negative associations with CV in the right postcentral gyrus, left medial prefrontal cortex (MPFC), and the CT in the right inferior frontal cortex (IFG, overlap with social brain network), which may be related to impairments in social cognition. Together, these findings suggest a unique structural basis for individual differences in pathological narcissism, distributed across different gray matter regions of the social brain network and CEN. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.
Unimodal primary sensory cortices are directly connected by long-range horizontal projections in the rat sensory cortex.

PubMed

Stehberg, Jimmy; Dang, Phat T; Frostig, Ron D

2014-01-01

Research based on functional imaging and neuronal recordings in the barrel cortex subdivision of primary somatosensory cortex (SI) of the adult rat has revealed novel aspects of structure-function relationships in this cortex. Specifically, it has demonstrated that single whisker stimulation evokes subthreshold neuronal activity that spreads symmetrically within gray matter from the appropriate barrel area, crosses cytoarchitectural borders of SI and reaches deeply into other unimodal primary cortices such as primary auditory (AI) and primary visual (VI). It was further demonstrated that this spread is supported by a spatially matching underlying diffuse network of border-crossing, long-range projections that could also reach deeply into AI and VI. Here we seek to determine whether such a network of border-crossing, long-range projections is unique to barrel cortex or characterizes also other primary, unimodal sensory cortices and therefore could directly connect them. Using anterograde (BDA) and retrograde (CTb) tract-tracing techniques, we demonstrate that such diffuse horizontal networks directly and mutually connect VI, AI and SI. These findings suggest that diffuse, border-crossing axonal projections connecting directly primary cortices are an important organizational motif common to all major primary sensory cortices in the rat. Potential implications of these findings for topics including cortical structure-function relationships, multisensory integration, functional imaging, and cortical parcellation are discussed.
Unimodal primary sensory cortices are directly connected by long-range horizontal projections in the rat sensory cortex

PubMed Central

Stehberg, Jimmy; Dang, Phat T.; Frostig, Ron D.

2014-01-01

Research based on functional imaging and neuronal recordings in the barrel cortex subdivision of primary somatosensory cortex (SI) of the adult rat has revealed novel aspects of structure-function relationships in this cortex. Specifically, it has demonstrated that single whisker stimulation evokes subthreshold neuronal activity that spreads symmetrically within gray matter from the appropriate barrel area, crosses cytoarchitectural borders of SI and reaches deeply into other unimodal primary cortices such as primary auditory (AI) and primary visual (VI). It was further demonstrated that this spread is supported by a spatially matching underlying diffuse network of border-crossing, long-range projections that could also reach deeply into AI and VI. Here we seek to determine whether such a network of border-crossing, long-range projections is unique to barrel cortex or characterizes also other primary, unimodal sensory cortices and therefore could directly connect them. Using anterograde (BDA) and retrograde (CTb) tract-tracing techniques, we demonstrate that such diffuse horizontal networks directly and mutually connect VI, AI and SI. These findings suggest that diffuse, border-crossing axonal projections connecting directly primary cortices are an important organizational motif common to all major primary sensory cortices in the rat. Potential implications of these findings for topics including cortical structure-function relationships, multisensory integration, functional imaging, and cortical parcellation are discussed. PMID:25309339
Advanced lesion symptom mapping analyses and implementation as BCBtoolkit

PubMed Central

Foulon, Chris; Cerliani, Leonardo; Kinkingnéhun, Serge; Levy, Richard; Rosso, Charlotte; Urbanski, Marika

2018-01-01

Abstract Background Patients with brain lesions provide a unique opportunity to understand the functioning of the human mind. However, even when focal, brain lesions have local and remote effects that impact functionally and structurally connected circuits. Similarly, function emerges from the interaction between brain areas rather than their sole activity. For instance, category fluency requires the associations between executive, semantic, and language production functions. Findings Here, we provide, for the first time, a set of complementary solutions for measuring the impact of a given lesion on the neuronal circuits. Our methods, which were applied to 37 patients with a focal frontal brain lesions, revealed a large set of directly and indirectly disconnected brain regions that had significantly impacted category fluency performance. The directly disconnected regions corresponded to areas that are classically considered as functionally engaged in verbal fluency and categorization tasks. These regions were also organized into larger directly and indirectly disconnected functional networks, including the left ventral fronto-parietal network, whose cortical thickness correlated with performance on category fluency. Conclusions The combination of structural and functional connectivity together with cortical thickness estimates reveal the remote effects of brain lesions, provide for the identification of the affected networks, and strengthen our understanding of their relationship with cognitive and behavioral measures. The methods presented are available and freely accessible in the BCBtoolkit as supplementary software [1]. PMID:29432527
Phylogenetic trends in respiratory rhythmogenesis: insights from ectothermic vertebrates.

PubMed

Kinkead, Richard

2009-08-31

Understanding the neural substrate driving breathing has puzzled physiologists for more than a century. The discovery of the pre-Bötzinger complex (preBötC) in newborn rodents as a structure with a unique physiological function in respiratory rhythm generation was an important progress in respiratory neurobiology that stimulated much research. Owing to the extensive literature describing the location, organisation, and function of the preBötC mainly in newborn rodents, this structure has become the point of reference in studies addressing respiratory rhythm generation in other mammals and various classes of vertebrates. This paper reviews recent progress made in non-mammalian vertebrates in our understanding of the location and function of the neural networks driving respiratory activity. As in newborn rodents, data from lampreys, air breathing fish, and amphibians show that the production of eupnea is the result of interactions between multiple (at least two) rhythmogenic networks. These networks are located in anatomically distinct areas and show different functional properties in terms of their ability to produce (or not) bursting activity in the absence of synaptic inputs (e.g. pacemaker neurons) and their sensitivity to specific neuromodulators such as substance P, somatostatin, and opioids. Current data indicate that respiratory rhythmogenesis is a phylogenetically ancient function that was highly conserved throughout evolution and that a comparative approach remains important to derive broader biological principles and a more comprehensive view.
Vascular tissue engineering by computer-aided laser micromachining.

PubMed

Doraiswamy, Anand; Narayan, Roger J

2010-04-28

Many conventional technologies for fabricating tissue engineering scaffolds are not suitable for fabricating scaffolds with patient-specific attributes. For example, many conventional technologies for fabricating tissue engineering scaffolds do not provide control over overall scaffold geometry or over cell position within the scaffold. In this study, the use of computer-aided laser micromachining to create scaffolds for vascular tissue networks was investigated. Computer-aided laser micromachining was used to construct patterned surfaces in agarose or in silicon, which were used for differential adherence and growth of cells into vascular tissue networks. Concentric three-ring structures were fabricated on agarose hydrogel substrates, in which the inner ring contained human aortic endothelial cells, the middle ring contained HA587 human elastin and the outer ring contained human aortic vascular smooth muscle cells. Basement membrane matrix containing vascular endothelial growth factor and heparin was to promote proliferation of human aortic endothelial cells within the vascular tissue networks. Computer-aided laser micromachining provides a unique approach to fabricate small-diameter blood vessels for bypass surgery as well as other artificial tissues with complex geometries.
Communication about childhood obesity on Twitter.

PubMed

Harris, Jenine K; Moreland-Russell, Sarah; Tabak, Rachel G; Ruhr, Lindsay R; Maier, Ryan C

2014-07-01

Little is known about the use of social media as a tool for health communication. We used a mixed-methods design to examine communication about childhood obesity on Twitter. NodeXL was used to collect tweets sent in June 2013 containing the hashtag #childhoodobesity. Tweets were coded for content; tweeters were classified by sector and health focus. Data were also collected on the network of follower connections among the tweeters. We used descriptive statistics and exponential random graph modeling to examine tweet content, characteristics of tweeters, and the composition and structure of the network of connections facilitating communication among tweeters. We collected 1110 tweets originating from 576 unique Twitter users. More individuals (65.6%) than organizations (32.9%) tweeted. More tweets focused on individual behavior than environment or policy. Few government and educational tweeters were in the network, but they were more likely than private individuals to be followed by others. There is an opportunity to better disseminate evidence-based information to a broad audience through Twitter by increasing the presence of credible sources in the #childhoodobesity conversation and focusing the content of tweets on scientific evidence.
Hippocampal maturity promotes memory distinctiveness in childhood and adolescence

PubMed Central

Keresztes, Attila; Bender, Andrew R.; Bodammer, Nils C.; Shing, Yee Lee

2017-01-01

Adaptive learning systems need to meet two complementary and partially conflicting goals: detecting regularities in the world versus remembering specific events. The hippocampus (HC) keeps a fine balance between computations that extract commonalities of incoming information (i.e., pattern completion) and computations that enable encoding of highly similar events into unique representations (i.e., pattern separation). Histological evidence from young rhesus monkeys suggests that HC development is characterized by the differential development of intrahippocampal subfields and associated networks. However, due to challenges in the in vivo investigation of such developmental organization, the ontogenetic timing of HC subfield maturation remains controversial. Delineating its course is important, as it directly influences the fine balance between pattern separation and pattern completion operations and, thus, developmental changes in learning and memory. Here, we relate in vivo, high-resolution structural magnetic resonance imaging data of HC subfields to behavioral memory performance in children aged 6–14 y and in young adults. We identify a multivariate profile of age-related differences in intrahippocampal structures and show that HC maturity as captured by this pattern is associated with age differences in the differential encoding of unique memory representations. PMID:28784801
TiO2 quantum dots embedded in bamboo-like porous carbon nanotubes as ultra high power and long life anodes for lithium ion batteries

NASA Astrophysics Data System (ADS)

Tang, Yakun; Liu, Lang; Wang, Xingchao; Jia, Dianzeng; Xia, Wei; Zhao, Zongbin; Qiu, Jieshan

2016-07-01

TiO2 quantum dots embedded in bamboo-like porous carbon nanotubes have been constructed through the pyrolysis of sulfonated polymer nanotubes and TiO2 hybrids. The TiO2 quantum dots are formed during the pyrolysis, due to the space confinement within the highly cross-linked copolymer networks. The sulfonation degree of the polymer nanotubes is a critical factor to ensure the formation of the unique interpenetrating structure. The nanocomposites exhibit high reversible capacity of 523 mAh g-1 at 100 mA g-1 after 200 cycles, excellent rate capability and superior long-term cycling stability at high current density, which could attain a high discharge capacity of 189 mAh g-1 at 2000 mA g-1 for up to 2000 cycles. The enhanced electrochemical performance of the nanocomposites benefit from the uniform distribution of TiO2 quantum dots, high electronic conductivity of porous carbons and unique interpenetrating structure, which simultaneously solved the major problems of TiO2 anode facing the pulverization, loss of electrical contact and particle aggregation.
Calibration of microsimulation models for multimodal freight networks.

DOT National Transportation Integrated Search

2012-06-01

This research presents a framework for incorporating the unique operating characteristics of multi-modal freight networks : into the calibration process for microscopic traffic simulation models. Because of the nature of heavy freight movements : in ...
EHD proteins: Key conductors of endocytic transport

PubMed Central

Naslavsky, Naava; Caplan, Steve

2010-01-01

Regulation of endocytic transport is controlled by an elaborate network of proteins. Rab GTP-binding proteins and their effectors have well-defined roles in mediating specific endocytic transport steps, but until recently, less was known about the four mammalian dynamin-like C-terminal Eps15 Homology Domain (EHD) proteins that also regulate endocytic events. In recent years, however, great strides have been made in understanding the structure and function of these unique proteins. Indeed, a growing body of literature addresses EHD protein structure, interactions with binding partners, functions in mammalian cells, and the generation of various new model systems. Accordingly, this is now an opportune time to pause and review the function and mechanisms of action of EHD proteins, and to highlight some of the challenges and future directions for the field. PMID:21067929
Understanding the mind of a worm: hierarchical network structure underlying nervous system function in C. elegans.

PubMed

Chatterjee, Nivedita; Sinha, Sitabhra

2008-01-01

The nervous system of the nematode C. elegans provides a unique opportunity to understand how behavior ('mind') emerges from activity in the nervous system ('brain') of an organism. The hermaphrodite worm has only 302 neurons, all of whose connections (synaptic and gap junctional) are known. Recently, many of the functional circuits that make up its behavioral repertoire have begun to be identified. In this paper, we investigate the hierarchical structure of the nervous system through k-core decomposition and find it to be intimately related to the set of all known functional circuits. Our analysis also suggests a vital role for the lateral ganglion in processing information, providing an essential connection between the sensory and motor components of the C. elegans nervous system.
Lesion network localization of criminal behavior

PubMed Central

Darby, R. Ryan; Horn, Andreas; Fox, Michael D.

2018-01-01

Following brain lesions, previously normal patients sometimes exhibit criminal behavior. Although rare, these cases can lend unique insight into the neurobiological substrate of criminality. Here we present a systematic mapping of lesions with known temporal association to criminal behavior, identifying 17 lesion cases. The lesion sites were spatially heterogeneous, including the medial prefrontal cortex, orbitofrontal cortex, and different locations within the bilateral temporal lobes. No single brain region was damaged in all cases. Because lesion-induced symptoms can come from sites connected to the lesion location and not just the lesion location itself, we also identified brain regions functionally connected to each lesion location. This technique, termed lesion network mapping, has recently identified regions involved in symptom generation across a variety of lesion-induced disorders. All lesions were functionally connected to the same network of brain regions. This criminality-associated connectivity pattern was unique compared with lesions causing four other neuropsychiatric syndromes. This network includes regions involved in morality, value-based decision making, and theory of mind, but not regions involved in cognitive control or empathy. Finally, we replicated our results in a separate cohort of 23 cases in which a temporal relationship between brain lesions and criminal behavior was implied but not definitive. Our results suggest that lesions in criminals occur in different brain locations but localize to a unique resting state network, providing insight into the neurobiology of criminal behavior. PMID:29255017
Cellulose as an Architectural Element in Spatially Structured Escherichia coli Biofilms

PubMed Central

Serra, Diego O.; Richter, Anja M.

2013-01-01

Morphological form in multicellular aggregates emerges from the interplay of genetic constitution and environmental signals. Bacterial macrocolony biofilms, which form intricate three-dimensional structures, such as large and often radially oriented ridges, concentric rings, and elaborate wrinkles, provide a unique opportunity to understand this interplay of “nature and nurture” in morphogenesis at the molecular level. Macrocolony morphology depends on self-produced extracellular matrix components. In Escherichia coli, these are stationary phase-induced amyloid curli fibers and cellulose. While the widely used “domesticated” E. coli K-12 laboratory strains are unable to generate cellulose, we could restore cellulose production and macrocolony morphology of E. coli K-12 strain W3110 by “repairing” a single chromosomal SNP in the bcs operon. Using scanning electron and fluorescence microscopy, cellulose filaments, sheets and nanocomposites with curli fibers were localized in situ at cellular resolution within the physiologically two-layered macrocolony biofilms of this “de-domesticated” strain. As an architectural element, cellulose confers cohesion and elasticity, i.e., tissue-like properties that—together with the cell-encasing curli fiber network and geometrical constraints in a growing colony—explain the formation of long and high ridges and elaborate wrinkles of wild-type macrocolonies. In contrast, a biofilm matrix consisting of the curli fiber network only is brittle and breaks into a pattern of concentric dome-shaped rings separated by deep crevices. These studies now set the stage for clarifying how regulatory networks and in particular c-di-GMP signaling operate in the three-dimensional space of highly structured and “tissue-like” bacterial biofilms. PMID:24097954
Cellulose as an architectural element in spatially structured Escherichia coli biofilms.

PubMed

Serra, Diego O; Richter, Anja M; Hengge, Regine

2013-12-01

Morphological form in multicellular aggregates emerges from the interplay of genetic constitution and environmental signals. Bacterial macrocolony biofilms, which form intricate three-dimensional structures, such as large and often radially oriented ridges, concentric rings, and elaborate wrinkles, provide a unique opportunity to understand this interplay of "nature and nurture" in morphogenesis at the molecular level. Macrocolony morphology depends on self-produced extracellular matrix components. In Escherichia coli, these are stationary phase-induced amyloid curli fibers and cellulose. While the widely used "domesticated" E. coli K-12 laboratory strains are unable to generate cellulose, we could restore cellulose production and macrocolony morphology of E. coli K-12 strain W3110 by "repairing" a single chromosomal SNP in the bcs operon. Using scanning electron and fluorescence microscopy, cellulose filaments, sheets and nanocomposites with curli fibers were localized in situ at cellular resolution within the physiologically two-layered macrocolony biofilms of this "de-domesticated" strain. As an architectural element, cellulose confers cohesion and elasticity, i.e., tissue-like properties that-together with the cell-encasing curli fiber network and geometrical constraints in a growing colony-explain the formation of long and high ridges and elaborate wrinkles of wild-type macrocolonies. In contrast, a biofilm matrix consisting of the curli fiber network only is brittle and breaks into a pattern of concentric dome-shaped rings separated by deep crevices. These studies now set the stage for clarifying how regulatory networks and in particular c-di-GMP signaling operate in the three-dimensional space of highly structured and "tissue-like" bacterial biofilms.
File Server-Based CD-ROM Networking: Using SCSI Express.

ERIC Educational Resources Information Center

McQueen, Howard

1992-01-01

Provides guidelines for evaluating SCSI Express Novell 386, a new product allowing CD-ROM drives to be attached to a Netware 3.11 file server, increasing CD-ROM networking capability. Specific limitations concerning software, hardware, and human resources are outlined, as well as its unique features and potential for future networking uses. (EA)
Understanding Classrooms through Social Network Analysis: A Primer for Social Network Analysis in Education Research

ERIC Educational Resources Information Center

Grunspan, Daniel Z.; Wiggins, Benjamin L.; Goodreau, Steven M.

2014-01-01

Social interactions between students are a major and underexplored part of undergraduate education. Understanding how learning relationships form in undergraduate classrooms, as well as the impacts these relationships have on learning outcomes, can inform educators in unique ways and improve educational reform. Social network analysis (SNA)…
Enriching Professional Learning Networks: A Framework for Identification, Reflection, and Intention

ERIC Educational Resources Information Center

Krutka, Daniel G.; Carpenter, Jeffrey Paul; Trust, Torrey

2017-01-01

Many educators in the 21st century utilize social media platforms to enrich professional learning networks (PLNs). PLNs are uniquely personalized networks that can support participatory and continuous learning. Social media services can mediate professional engagements with a wide variety of people, spaces and tools that might not otherwise be…
Crystal Structure of Hyperthermophilic Endo-β-1,4-glucanase

PubMed Central

Zheng, Baisong; Yang, Wen; Zhao, Xinyu; Wang, Yuguo; Lou, Zhiyong; Rao, Zihe; Feng, Yan

2012-01-01

Endo-β-1,4-glucanase from thermophilic Fervidobacterium nodosum Rt17-B1 (FnCel5A), a new member of glycosyl hydrolase family 5, is highly thermostable and exhibits the highest activity on carboxymethylcellulose among the reported homologues. To understand the structural basis for the thermostability and catalytic mechanism, we report here the crystal structures of FnCel5A and the complex with glucose at atomic resolution. FnCel5A exhibited a (β/α)8-barrel structure typical of clan GH-A of the glycoside hydrolase families with a large and deep catalytic pocket located in the C-terminal end of the β-strands that may permit substrate access. A comparison of the structure of FnCel5A with related structures from thermopile Clostridium thermocellum, mesophile Clostridium cellulolyticum, and psychrophile Pseudoalteromonas haloplanktis showed significant differences in intramolecular interactions (salt bridges and hydrogen bonds) that may account for the difference in their thermostabilities. The substrate complex structure in combination with a mutagenesis analysis of the catalytic residues implicates a distinctive catalytic module Glu167-His226-Glu283, which suggests that the histidine may function as an intermediate for the electron transfer network between the typical Glu-Glu catalytic module. Further investigation suggested that the aromatic residues Trp61, Trp204, Phe231, and Trp240 as well as polar residues Asn51, His127, Tyr228, and His235 in the active site not only participated in substrate binding but also provided a unique microenvironment suitable for catalysis. These results provide substantial insight into the unique characteristics of FnCel5A for catalysis and adaptation to extreme temperature. PMID:22128157
An Adaptive Resonance Theory account of the implicit learning of orthographic word forms.

PubMed

Glotin, H; Warnier, P; Dandurand, F; Dufau, S; Lété, B; Touzet, C; Ziegler, J C; Grainger, J

2010-01-01

An Adaptive Resonance Theory (ART) network was trained to identify unique orthographic word forms. Each word input to the model was represented as an unordered set of ordered letter pairs (open bigrams) that implement a flexible prelexical orthographic code. The network learned to map this prelexical orthographic code onto unique word representations (orthographic word forms). The network was trained on a realistic corpus of reading textbooks used in French primary schools. The amount of training was strictly identical to children's exposure to reading material from grade 1 to grade 5. Network performance was examined at each grade level. Adjustment of the learning and vigilance parameters of the network allowed us to reproduce the developmental growth of word identification performance seen in children. The network exhibited a word frequency effect and was found to be sensitive to the order of presentation of word inputs, particularly with low frequency words. These words were better learned with a randomized presentation order compared with the order of presentation in the school books. These results open up interesting perspectives for the application of ART networks in the study of the dynamics of learning to read. 2009 Elsevier Ltd. All rights reserved.

Physical Heterogeneity and Aquatic Community Function in River Networks

EPA Science Inventory

The geomorphological character of a river network provides the template upon which evolution acts to create unique biological communities. Deciphering commonly observed patterns and processes within riverine landscapes resulting from the interplay between physical and biological...
A Functionally Conserved Gene Regulatory Network Module Governing Olfactory Neuron Diversity.

PubMed

Li, Qingyun; Barish, Scott; Okuwa, Sumie; Maciejewski, Abigail; Brandt, Alicia T; Reinhold, Dominik; Jones, Corbin D; Volkan, Pelin Cayirlioglu

2016-01-01

Sensory neuron diversity is required for organisms to decipher complex environmental cues. In Drosophila, the olfactory environment is detected by 50 different olfactory receptor neuron (ORN) classes that are clustered in combinations within distinct sensilla subtypes. Each sensilla subtype houses stereotypically clustered 1-4 ORN identities that arise through asymmetric divisions from a single multipotent sensory organ precursor (SOP). How each class of SOPs acquires a unique differentiation potential that accounts for ORN diversity is unknown. Previously, we reported a critical component of SOP diversification program, Rotund (Rn), increases ORN diversity by generating novel developmental trajectories from existing precursors within each independent sensilla type lineages. Here, we show that Rn, along with BarH1/H2 (Bar), Bric-à-brac (Bab), Apterous (Ap) and Dachshund (Dac), constitutes a transcription factor (TF) network that patterns the developing olfactory tissue. This network was previously shown to pattern the segmentation of the leg, which suggests that this network is functionally conserved. In antennal imaginal discs, precursors with diverse ORN differentiation potentials are selected from concentric rings defined by unique combinations of these TFs along the proximodistal axis of the developing antennal disc. The combinatorial code that demarcates each precursor field is set up by cross-regulatory interactions among different factors within the network. Modifications of this network lead to predictable changes in the diversity of sensilla subtypes and ORN pools. In light of our data, we propose a molecular map that defines each unique SOP fate. Our results highlight the importance of the early prepatterning gene regulatory network as a modulator of SOP and terminally differentiated ORN diversity. Finally, our model illustrates how conserved developmental strategies are used to generate neuronal diversity.
Origin and evolution of the deep thermochemical structure beneath Eurasia.

PubMed

Flament, N; Williams, S; Müller, R D; Gurnis, M; Bower, D J

2017-01-18

A unique structure in the Earth's lowermost mantle, the Perm Anomaly, was recently identified beneath Eurasia. It seismologically resembles the large low-shear velocity provinces (LLSVPs) under Africa and the Pacific, but is much smaller. This challenges the current understanding of the evolution of the plate-mantle system in which plumes rise from the edges of the two LLSVPs, spatially fixed in time. New models of mantle flow over the last 230 million years reproduce the present-day structure of the lower mantle, and show a Perm-like anomaly. The anomaly formed in isolation within a closed subduction network ∼22,000 km in circumference prior to 150 million years ago before migrating ∼1,500 km westward at an average rate of 1 cm year -1 , indicating a greater mobility of deep mantle structures than previously recognized. We hypothesize that the mobile Perm Anomaly could be linked to the Emeishan volcanics, in contrast to the previously proposed Siberian Traps.
Human NOD2 Recognizes Structurally Unique Muramyl Dipeptides from Mycobacterium leprae

PubMed Central

Schenk, Mirjam; Mahapatra, Sebabrata; Le, Phuonganh; Kim, Hee Jin; Choi, Aaron W.; Brennan, Patrick J.; Belisle, John T.

2016-01-01

The innate immune system recognizes microbial pathogens via pattern recognition receptors. One such receptor, NOD2, via recognition of muramyl dipeptide (MDP), triggers a distinct network of innate immune responses, including the production of interleukin-32 (IL-32), which leads to the differentiation of monocytes into dendritic cells (DC). NOD2 has been implicated in the pathogenesis of human leprosy, yet it is not clear whether Mycobacterium leprae, which has a distinct MDP structure, can activate this pathway. We investigated the effect of MDP structure on the innate immune response, finding that infection of monocytes with M. leprae induces IL-32 and DC differentiation in a NOD2-dependent manner. The presence of the proximal l-Ala instead of Gly in the common configuration of the peptide side chain of M. leprae did not affect recognition by NOD2 or cytokine production. Furthermore, amidation of the d-Glu residue did not alter NOD2 activation. These data provide experimental evidence that NOD2 recognizes naturally occurring structural variants of MDP. PMID:27297389
Design of a minimal protein oligomerization domain by a structural approach.

PubMed

Burkhard, P; Meier, M; Lustig, A

2000-12-01

Because of the simplicity and regularity of the alpha-helical coiled coil relative to other structural motifs, it can be conveniently used to clarify the molecular interactions responsible for protein folding and stability. Here we describe the de novo design and characterization of a two heptad-repeat peptide stabilized by a complex network of inter- and intrahelical salt bridges. Circular dichroism spectroscopy and analytical ultracentrifugation show that this peptide is highly alpha-helical and 100% dimeric tinder physiological buffer conditions. Interestingly, the peptide was shown to switch its oligomerization state from a dimer to a trimer upon increasing ionic strength. The correctness of the rational design principles used here is supported by details of the atomic structure of the peptide deduced from X-ray crystallography. The structure of the peptide shows that it is not a molten globule but assumes a unique, native-like conformation. This de novo peptide thus represents an attractive model system for the design of a molecular recognition system.
Design of a minimal protein oligomerization domain by a structural approach.

PubMed Central

Burkhard, P.; Meier, M.; Lustig, A.

2000-01-01

Because of the simplicity and regularity of the alpha-helical coiled coil relative to other structural motifs, it can be conveniently used to clarify the molecular interactions responsible for protein folding and stability. Here we describe the de novo design and characterization of a two heptad-repeat peptide stabilized by a complex network of inter- and intrahelical salt bridges. Circular dichroism spectroscopy and analytical ultracentrifugation show that this peptide is highly alpha-helical and 100% dimeric tinder physiological buffer conditions. Interestingly, the peptide was shown to switch its oligomerization state from a dimer to a trimer upon increasing ionic strength. The correctness of the rational design principles used here is supported by details of the atomic structure of the peptide deduced from X-ray crystallography. The structure of the peptide shows that it is not a molten globule but assumes a unique, native-like conformation. This de novo peptide thus represents an attractive model system for the design of a molecular recognition system. PMID:11206050
Band Structure Engineering and Thermoelectric Properties of Charge-Compensated Filled Skutterudites

PubMed Central

Shi, Xiaoya; Yang, Jiong; Wu, Lijun; Salvador, James R.; Zhang, Cheng; Villaire, William L.; Haddad, Daad; Yang, Jihui; Zhu, Yimei; Li, Qiang

2015-01-01

Thermoelectric properties of semiconductors are intimately related to their electronic band structure, which can be engineered via chemical doping. Dopant Ga in the cage-structured skutterudite Co4Sb12 substitutes Sb sites while occupying the void sites. Combining quantitative scanning transmission electron microscopy and first-principles calculations, we show that Ga dual-site occupancy breaks the symmetry of the Sb-Sb network, splits the deep triply-degenerate conduction bands, and drives them downward to the band edge. The charge-compensating nature of the dual occupancy Ga increases overall filling fraction limit. By imparting this unique band structure feature, and judiciously doping the materials by increasing the Yb content, we promote the Fermi level to a point where carriers are in energetic proximity to these features. Increased participation of these heavier bands in electronic transport leads to increased thermopower and effective mass. Further, the localized distortion from Ga/Sb substitution enhances the phonon scattering to reduce the thermal conductivity effectively. PMID:26456013
Band structure engineering and thermoelectric properties of charge-compensated filled skutterudites

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

Shi, Xiaoya; Yang, Jiong; Wu, Lijun

2015-10-12

Thermoelectric properties of semiconductors are intimately related to their electronic band structure, which can be engineered via chemical doping. Dopant Ga in the cage-structured skutterudite Co 4Sb 12 substitutes Sb sites while occupying the void sites. Combining quantitative scanning transmission electron microscopy and first-principles calculations, we show that Ga dual-site occupancy breaks the symmetry of the Sb-Sb network, splits the deep triply-degenerate conduction bands, and drives them downward to the band edge. The charge-compensating nature of the dual occupancy Ga increases overall filling fraction limit. By imparting this unique band structure feature, and judiciously doping the materials by increasing themore » Yb content, we promote the Fermi level to a point where carriers are in energetic proximity to these features. Increased participation of these heavier bands in electronic transport leads to increased thermopower and effective mass. Further, the localized distortion from Ga/Sb substitution enhances the phonon scattering to reduce the thermal conductivity effectively.« less
Band Structure Engineering and Thermoelectric Properties of Charge-Compensated Filled Skutterudites

NASA Astrophysics Data System (ADS)

Shi, Xiaoya; Yang, Jiong; Wu, Lijun; Salvador, James R.; Zhang, Cheng; Villaire, William L.; Haddad, Daad; Yang, Jihui; Zhu, Yimei; Li, Qiang

2015-10-01

Thermoelectric properties of semiconductors are intimately related to their electronic band structure, which can be engineered via chemical doping. Dopant Ga in the cage-structured skutterudite Co4Sb12 substitutes Sb sites while occupying the void sites. Combining quantitative scanning transmission electron microscopy and first-principles calculations, we show that Ga dual-site occupancy breaks the symmetry of the Sb-Sb network, splits the deep triply-degenerate conduction bands, and drives them downward to the band edge. The charge-compensating nature of the dual occupancy Ga increases overall filling fraction limit. By imparting this unique band structure feature, and judiciously doping the materials by increasing the Yb content, we promote the Fermi level to a point where carriers are in energetic proximity to these features. Increased participation of these heavier bands in electronic transport leads to increased thermopower and effective mass. Further, the localized distortion from Ga/Sb substitution enhances the phonon scattering to reduce the thermal conductivity effectively.
Non-coding RNA networks in cancer.

PubMed

Anastasiadou, Eleni; Jacob, Leni S; Slack, Frank J

2018-01-01

Thousands of unique non-coding RNA (ncRNA) sequences exist within cells. Work from the past decade has altered our perception of ncRNAs from 'junk' transcriptional products to functional regulatory molecules that mediate cellular processes including chromatin remodelling, transcription, post-transcriptional modifications and signal transduction. The networks in which ncRNAs engage can influence numerous molecular targets to drive specific cell biological responses and fates. Consequently, ncRNAs act as key regulators of physiological programmes in developmental and disease contexts. Particularly relevant in cancer, ncRNAs have been identified as oncogenic drivers and tumour suppressors in every major cancer type. Thus, a deeper understanding of the complex networks of interactions that ncRNAs coordinate would provide a unique opportunity to design better therapeutic interventions.
Predicting new drug indications from network analysis

NASA Astrophysics Data System (ADS)

Mohd Ali, Yousoff Effendy; Kwa, Kiam Heong; Ratnavelu, Kurunathan

This work adapts centrality measures commonly used in social network analysis to identify drugs with better positions in drug-side effect network and drug-indication network for the purpose of drug repositioning. Our basic hypothesis is that drugs having similar phenotypic profiles such as side effects may also share similar therapeutic properties based on related mechanism of action and vice versa. The networks were constructed from Side Effect Resource (SIDER) 4.1 which contains 1430 unique drugs with side effects and 1437 unique drugs with indications. Within the giant components of these networks, drugs were ranked based on their centrality scores whereby 18 prominent drugs from the drug-side effect network and 15 prominent drugs from the drug-indication network were identified. Indications and side effects of prominent drugs were deduced from the profiles of their neighbors in the networks and compared to existing clinical studies while an optimum threshold of similarity among drugs was sought for. The threshold can then be utilized for predicting indications and side effects of all drugs. Similarities of drugs were measured by the extent to which they share phenotypic profiles and neighbors. To improve the likelihood of accurate predictions, only profiles such as side effects of common or very common frequencies were considered. In summary, our work is an attempt to offer an alternative approach to drug repositioning using centrality measures commonly used for analyzing social networks.
Networks of Interacting Processes: Relationships Between Drivers and Deltaic Variables to Understand Water and Sediment Transport in Wax Lake Delta, Coastal Louisiana

NASA Astrophysics Data System (ADS)

Sendrowski, A.; Passalacqua, P.; Wagner, W.; Mohrig, D. C.; Meselhe, E. A.; Sadid, K. M.; Castañeda-Moya, E.; Twilley, R.

2017-12-01

Studying distributary channel networks in river deltaic systems provides important insight into deltaic functioning and evolution. This view of networks highlights the physical connection along channels and can also encompass the structural link between channels and deltaic islands (termed structural connectivity). An alternate view of the deltaic network is one composed of interacting processes, such as relationships between external drivers (e.g., river discharge, tides, and wind) and internal deltaic response variables (e.g., water level and sediment concentration). This network, also referred to as process connectivity, is dynamic across space and time, often comprises nonlinear relationships, and contributes to the development of complex channel networks and ecologically rich island platforms. The importance of process connectivity has been acknowledged, however, few studies have directly quantified these network interactions. In this work, we quantify process connections in Wax Lake Delta (WLD), coastal Louisiana. WLD is a naturally prograding delta that serves as an analogue for river diversion projects, thus it provides an excellent setting for understanding the influence of river discharge, tides, and wind on water and sediment in a delta. Time series of water level and sediment concentration were collected in three channels from November 2013 to February 2014, while water level and turbidity were collected on an island from April 2014 to August 2015. Additionally, a model run on WLD bathymetry generated two years of sediment concentration time series in multiple channels. River discharge, tide, and wind measurements were collected from the USGS and NOAA, respectively. We analyze this data with information theory (IT), a set of statistics that measure uncertainty in signals and communication between signals. Using IT, the timescale, strength, and direction of network links are quantified by measuring the synchronization and direct influence from one variable to another. We compare channel and island process connections, which show distinct differences. Our study captures the temporal evolution of variable transport at multiple locations. While WLD is river dominated, tides and wind show unique transport signatures related to tidal spring and neap transitions and wind events.
Genetic networking of the Bemisia tabaci cryptic species complex reveals pattern of biological invasions.

PubMed

De Barro, Paul; Ahmed, Muhammad Z

2011-01-01

A challenge within the context of cryptic species is the delimitation of individual species within the complex. Statistical parsimony network analytics offers the opportunity to explore limits in situations where there are insufficient species-specific morphological characters to separate taxa. The results also enable us to explore the spread in taxa that have invaded globally. Using a 657 bp portion of mitochondrial cytochrome oxidase 1 from 352 unique haplotypes belonging to the Bemisia tabaci cryptic species complex, the analysis revealed 28 networks plus 7 unconnected individual haplotypes. Of the networks, 24 corresponded to the putative species identified using the rule set devised by Dinsdale et al. (2010). Only two species proposed in Dinsdale et al. (2010) departed substantially from the structure suggested by the analysis. The analysis of the two invasive members of the complex, Mediterranean (MED) and Middle East - Asia Minor 1 (MEAM1), showed that in both cases only a small number of haplotypes represent the majority that have spread beyond the home range; one MEAM1 and three MED haplotypes account for >80% of the GenBank records. Israel is a possible source of the globally invasive MEAM1 whereas MED has two possible sources. The first is the eastern Mediterranean which has invaded only the USA, primarily Florida and to a lesser extent California. The second are western Mediterranean haplotypes that have spread to the USA, Asia and South America. The structure for MED supports two home range distributions, a Sub-Saharan range and a Mediterranean range. The MEAM1 network supports the Middle East - Asia Minor region. The network analyses show a high level of congruence with the species identified in a previous phylogenetic analysis. The analysis of the two globally invasive members of the complex support the view that global invasion often involve very small portions of the available genetic diversity.
Two-Dimensional Lead Halide Perovskites Templated by a Conjugated Asymmetric Diammonium.

PubMed

Hautzinger, Matthew P; Dai, Jun; Ji, Yujin; Fu, Yongping; Chen, Jie; Guzei, Ilia A; Wright, John C; Li, Youyong; Jin, Song

2017-12-18

We report novel two-dimensional lead halide perovskite structures templated by a unique conjugated aromatic dication, N,N-dimethylphenylene-p-diammonium (DPDA). The asymmetrically substituted primary and tertiary ammoniums in DPDA facilitate the formation of two-dimensional network (2DN) perovskite structures incorporating a conjugated dication between the PbX 4 2- (X = Br, I) layers. These 2DN structures of (DPDA)PbI 4 and (DPDA)PbBr 4 were characterized by single-crystal X-ray diffraction, showing uniquely low distortions in the Pb-X-Pb bond angle for 2D perovskites. The Pb-I-Pb bond angle is very close to ideal (180°) for a 2DN lead iodide perovskite, which can be attributed to the ability of the rigid diammonium DPDA to insert into the PbX 6 2- octahedral pockets. Optical characterization of (DPDA)PbI 4 shows an excitonic absorption peak at 2.29 eV (541 nm), which is red-shifted in comparison to similar 2DN lead iodide structures. Temperature-dependent photoluminescence of both compounds reveals both a self-trapped exciton and free exciton emission feature. The reduced exciton absorption energy and emission properties are attributed to the dication-induced structural order of the inorganic PbX 4 2- layers. DFT calculation results suggest mixing of the conjugated organic orbital component in the valence band of these 2DN perovskites. These results demonstrate a rational new strategy to incorporate conjugated organic dications into hybrid perovskites and will spur spectroscopic investigations of these compounds as well as optoelectronic applications.
Altered affective, executive and sensorimotor resting state networks in patients with pediatric mania

PubMed Central

Wu, Minjie; Lu, Lisa H.; Passarotti, Alessandra M.; Wegbreit, Ezra; Fitzgerald, Jacklynn; Pavuluri, Mani N.

2013-01-01

Background The aim of the present study was to map the pathophysiology of resting state functional connectivity accompanying structural and functional abnormalities in children with bipolar disorder. Methods Children with bipolar disorder and demographically matched healthy controls underwent resting-state functional magnetic resonance imaging. A model-free independent component analysis was performed to identify intrinsically interconnected networks. Results We included 34 children with bipolar disorder and 40 controls in our analysis. Three distinct resting state networks corresponding to affective, executive and sensorimotor functions emerged as being significantly different between the pediatric bipolar disorder (PBD) and control groups. All 3 networks showed hyperconnectivity in the PBD relative to the control group. Specifically, the connectivity of the dorsal anterior cingulate cortex (ACC) differentiated the PBD from the control group in both the affective and the executive networks. Exploratory analysis suggests that greater connectivity of the right amygdala within the affective network is associated with better executive function in children with bipolar disorder, but not in controls. Limitations Unique clinical characteristics of the study sample allowed us to evaluate the pathophysiology of resting state connectivity at an early state of PBD, which led to the lack of generalizability in terms of comorbid disorders existing in a typical PBD population. Conclusion Abnormally engaged resting state affective, executive and sensorimotor networks observed in children with bipolar disorder may reflect a biological context in which abnormal task-based brain activity can occur. Dual engagement of the dorsal ACC in affective and executive networks supports the neuroanatomical interface of these networks, and the amygdala’s engagement in moderating executive function illustrates the intricate interplay of these neural operations at rest. PMID:23735583
The Military Applications of Cloud Computing Technologies

DTIC Science & Technology

2013-05-23

tactical networks will potentially cause some unique issues when implementing the JIE. Tactical networks are temporary in nature , and are utilized...connected ABCS clients will receive software updates and security patches as they are published over the network , rather than catching up after an extended...approach from the previous JNN network model, in that it introduces a limited, wireless capability to a unit’s LAN that will enable limited, on-the
Power allocation for target detection in radar networks based on low probability of intercept: A cooperative game theoretical strategy

NASA Astrophysics Data System (ADS)

Shi, Chenguang; Salous, Sana; Wang, Fei; Zhou, Jianjiang

2017-08-01

Distributed radar network systems have been shown to have many unique features. Due to their advantage of signal and spatial diversities, radar networks are attractive for target detection. In practice, the netted radars in radar networks are supposed to maximize their transmit power to achieve better detection performance, which may be in contradiction with low probability of intercept (LPI). Therefore, this paper investigates the problem of adaptive power allocation for radar networks in a cooperative game-theoretic framework such that the LPI performance can be improved. Taking into consideration both the transmit power constraints and the minimum signal to interference plus noise ratio (SINR) requirement of each radar, a cooperative Nash bargaining power allocation game based on LPI is formulated, whose objective is to minimize the total transmit power by optimizing the power allocation in radar networks. First, a novel SINR-based network utility function is defined and utilized as a metric to evaluate power allocation. Then, with the well-designed network utility function, the existence and uniqueness of the Nash bargaining solution are proved analytically. Finally, an iterative Nash bargaining algorithm is developed that converges quickly to a Pareto optimal equilibrium for the cooperative game. Numerical simulations and theoretic analysis are provided to evaluate the effectiveness of the proposed algorithm.
Adversarial Threshold Neural Computer for Molecular de Novo Design.

PubMed

Putin, Evgeny; Asadulaev, Arip; Vanhaelen, Quentin; Ivanenkov, Yan; Aladinskaya, Anastasia V; Aliper, Alex; Zhavoronkov, Alex

2018-03-30

In this article, we propose the deep neural network Adversarial Threshold Neural Computer (ATNC). The ATNC model is intended for the de novo design of novel small-molecule organic structures. The model is based on generative adversarial network architecture and reinforcement learning. ATNC uses a Differentiable Neural Computer as a generator and has a new specific block, called adversarial threshold (AT). AT acts as a filter between the agent (generator) and the environment (discriminator + objective reward functions). Furthermore, to generate more diverse molecules we introduce a new objective reward function named Internal Diversity Clustering (IDC). In this work, ATNC is tested and compared with the ORGANIC model. Both models were trained on the SMILES string representation of the molecules, using four objective functions (internal similarity, Muegge druglikeness filter, presence or absence of sp 3 -rich fragments, and IDC). The SMILES representations of 15K druglike molecules from the ChemDiv collection were used as a training data set. For the different functions, ATNC outperforms ORGANIC. Combined with the IDC, ATNC generates 72% of valid and 77% of unique SMILES strings, while ORGANIC generates only 7% of valid and 86% of unique SMILES strings. For each set of molecules generated by ATNC and ORGANIC, we analyzed distributions of four molecular descriptors (number of atoms, molecular weight, logP, and tpsa) and calculated five chemical statistical features (internal diversity, number of unique heterocycles, number of clusters, number of singletons, and number of compounds that have not been passed through medicinal chemistry filters). Analysis of key molecular descriptors and chemical statistical features demonstrated that the molecules generated by ATNC elicited better druglikeness properties. We also performed in vitro validation of the molecules generated by ATNC; results indicated that ATNC is an effective method for producing hit compounds.
Analysis of structure-function network decoupling in the brain systems of spastic diplegic cerebral palsy.

PubMed

Lee, Dongha; Pae, Chongwon; Lee, Jong Doo; Park, Eun Sook; Cho, Sung-Rae; Um, Min-Hee; Lee, Seung-Koo; Oh, Maeng-Keun; Park, Hae-Jeong

2017-10-01

Manifestation of the functionalities from the structural brain network is becoming increasingly important to understand a brain disease. With the aim of investigating the differential structure-function couplings according to network systems, we investigated the structural and functional brain networks of patients with spastic diplegic cerebral palsy with periventricular leukomalacia compared to healthy controls. The structural and functional networks of the whole brain and motor system, constructed using deterministic and probabilistic tractography of diffusion tensor magnetic resonance images and Pearson and partial correlation analyses of resting-state functional magnetic resonance images, showed differential embedding of functional networks in the structural networks in patients. In the whole-brain network of patients, significantly reduced global network efficiency compared to healthy controls were found in the structural networks but not in the functional networks, resulting in reduced structural-functional coupling. On the contrary, the motor network of patients had a significantly lower functional network efficiency over the intact structural network and a lower structure-function coupling than the control group. This reduced coupling but reverse directionality in the whole-brain and motor networks of patients was prominent particularly between the probabilistic structural and partial correlation-based functional networks. Intact (or less deficient) functional network over impaired structural networks of the whole brain and highly impaired functional network topology over the intact structural motor network might subserve relatively preserved cognitions and impaired motor functions in cerebral palsy. This study suggests that the structure-function relationship, evaluated specifically using sparse functional connectivity, may reveal important clues to functional reorganization in cerebral palsy. Hum Brain Mapp 38:5292-5306, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Theta rhythm-like bidirectional cycling dynamics of living neuronal networks in vitro.

PubMed

Gladkov, Arseniy; Grinchuk, Oleg; Pigareva, Yana; Mukhina, Irina; Kazantsev, Victor; Pimashkin, Alexey

2018-01-01

The phenomena of synchronization, rhythmogenesis and coherence observed in brain networks are believed to be a dynamic substrate for cognitive functions such as learning and memory. However, researchers are still debating whether the rhythmic activity emerges from the network morphology that developed during neurogenesis or as a result of neuronal dynamics achieved under certain conditions. In the present study, we observed self-organized spiking activity that converged to long, complex and rhythmically repeated superbursts in neural networks formed by mature hippocampal cultures with a high cellular density. The superburst lasted for tens of seconds and consisted of hundreds of short (50-100 ms) small bursts with a high spiking rate of 139.0 ± 78.6 Hz that is associated with high-frequency oscillations in the hippocampus. In turn, the bursting frequency represents a theta rhythm (11.2 ± 1.5 Hz). The distribution of spikes within the bursts was non-random, representing a set of well-defined spatio-temporal base patterns or motifs. The long superburst was classified into two types. Each type was associated with a unique direction of spike propagation and, hence, was encoded by a binary sequence with random switching between the two "functional" states. The precisely structured bidirectional rhythmic activity that developed in self-organizing cultured networks was quite similar to the activity observed in the in vivo experiments.

Periodic Hydraulic Testing for Discerning Fracture Network Connections

NASA Astrophysics Data System (ADS)

Becker, M.; Le Borgne, T.; Bour, O.; Guihéneuf, N.; Cole, M.

2015-12-01

Discrete fracture network (DFN) models often predict highly variable hydraulic connections between injection and pumping wells used for enhanced oil recovery, geothermal energy extraction, and groundwater remediation. Such connections can be difficult to verify in fractured rock systems because standard pumping or pulse interference tests interrogate too large a volume to pinpoint specific connections. Three field examples are presented in which periodic hydraulic tests were used to obtain information about hydraulic connectivity in fractured bedrock. The first site, a sandstone in New York State, involves only a single fracture at a scale of about 10 m. The second site, a granite in Brittany, France, involves a fracture network at about the same scale. The third site, a granite/schist in the U.S. State of New Hampshire, involves a complex network at scale of 30-60 m. In each case periodic testing provided an enhanced view of hydraulic connectivity over previous constant rate tests. Periodic testing is particularly adept at measuring hydraulic diffusivity, which is a more effective parameter than permeability for identify the complexity of flow pathways between measurement locations. Periodic tests were also conducted at multiple frequencies which provides a range in the radius of hydraulic penetration away from the oscillating well. By varying the radius of penetration, we attempt to interrogate the structure of the fracture network. Periodic tests, therefore, may be uniquely suited for verifying and/or calibrating DFN models.
Disrupted small world topology and modular organisation of functional networks in late-life depression with and without amnestic mild cognitive impairment.

PubMed

Li, Wenjun; Douglas Ward, B; Liu, Xiaolin; Chen, Gang; Jones, Jennifer L; Antuono, Piero G; Li, Shi-Jiang; Goveas, Joseph S

2015-10-01

The topological architecture of the whole-brain functional networks in those with and without late-life depression (LLD) and amnestic mild cognitive impairment (aMCI) are unknown. To investigate the differences in the small-world measures and the modular community structure of the functional networks between patients with LLD and aMCI when occurring alone or in combination and cognitively healthy non-depressed controls. 79 elderly participants (LLD (n=23), aMCI (n=18), comorbid LLD and aMCI (n=13), and controls (n=25)) completed neuropsychiatric assessments. Graph theoretical methods were employed on resting-state functional connectivity MRI data. LLD and aMCI comorbidity was associated with the greatest disruptions in functional integration measures (decreased global efficiency and increased path length); both LLD groups showed abnormal functional segregation (reduced local efficiency). The modular network organisation was most variable in the comorbid group, followed by patients with LLD-only. Decreased mean global, local and nodal efficiency metrics were associated with greater depressive symptom severity but not memory performance. Considering the whole brain as a complex network may provide unique insights on the neurobiological underpinnings of LLD with and without cognitive impairment. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Global exponential stability of BAM neural networks with time-varying delays and diffusion terms

NASA Astrophysics Data System (ADS)

Wan, Li; Zhou, Qinghua

2007-11-01

The stability property of bidirectional associate memory (BAM) neural networks with time-varying delays and diffusion terms are considered. By using the method of variation parameter and inequality technique, the delay-independent sufficient conditions to guarantee the uniqueness and global exponential stability of the equilibrium solution of such networks are established.
A Visually Attractive "Interconnected Network of Ideas" for Organizing the Teaching and Learning of Descriptive Inorganic Chemistry

ERIC Educational Resources Information Center

Rodgers, Glen E.

2014-01-01

A visually attractive interconnected network of ideas that helps general and second-year inorganic chemistry students make sense of the descriptive inorganic chemistry of the main-group elements is presented. The eight network components include the periodic law, the uniqueness principle, the diagonal effect, the inert-pair effect, the…
Examining the Presence of Social Media on University Web Sites

ERIC Educational Resources Information Center

Greenwood, Grant

2012-01-01

Over the past few years, social networking has exploded into a massive medium that has captured the attention of a large portion of the American population. The ever-growing social networking site(s) (SNS) movement has filled a networking gap and thus, has presented higher education institutions with unique opportunities (Reid 2009) to further…
Productive Tensions in a Cross-Cultural Peer Mentoring Women's Network: A Social Capital Perspective

ERIC Educational Resources Information Center

Esnard, Talia; Cobb-Roberts, Deirdre; Agosto, Vonzell; Karanxha, Zorka; Beck, Makini; Wu, Ke; Unterreiner, Ann

2015-01-01

A growing body of researchers documents the unique barriers women face in their academic career progression and the significance of mentoring networks for advancement of their academic trajectories as faculty. However, few researchers explore the embedded tensions and conflicts in the social processes and relations of mentoring networks, and the…
A new mechanism for selective adsorption of rubber on carbon black surface caused by nano-confinement in SBR/NBR solution

NASA Astrophysics Data System (ADS)

Kawazoe, Masayuki

A novel mechanism of selective adsorption of rubber molecules onto carbon black surface in a binary immiscible rubber blend solution has been proposed in this dissertation. The phenomenon leads to uneven distribution of carbon black to the specific polymer in the blend and the obtained electrically conductive composite showed drastic reduction of percolation threshold concentration (PTC). The mechanism and the feature of conductive network formation have much potential concerning both fundamental understanding and industrial application to improve conductive polymer composites. In chapter I, carbon black filled conductive polymer composites are briefly reviewed. Then, in chapter II, a mechanism of rubber molecular confinement into carbon black aggregate structure is introduced to explain the selective adsorption of a specific rubber onto carbon black surface in an immiscible rubber solution blend (styrene butadiene rubber (SBR) and acrylonitrile butadiene rubber (NBR) with toluene or chloroform). Next, in chapters III and IV, polymers with various radius of gyration (Rg) and carbon blacks with various aggregate structure are examined to verify the selective adsorption mechanism. Finally, in chapter V, the novel mechanism was applied to create unique meso-/micro-unit conductive network in carbon black dispersed SBR/NBR composites.
Edge enhanced growth induced shape transition in the formation of GaN nanowall network

NASA Astrophysics Data System (ADS)

Nayak, Sanjay; Kumar, Rajendra; Shivaprasad, S. M.

2018-01-01

We address the mechanism of early stages of growth and shape transition of the unique nanowall network (NwN) of GaN by experimentally monitoring its morphological evolution and complementing it by first-principles calculations. Using atomic force and scanning electron microscopy, we observe the formation of oval shaped islands at very early stages of the growth which later transformed into tetrahedron shaped (3 faced pyramid) islands. These tetrahedron shaped islands further grow anisotropically along their edges of the (20 2 ¯ 1) facets to form the wall-like structure as the growth proceeds. The mechanism of this crystal growth is discussed in light of surface free energies of the different surfaces, adsorption energy, and diffusion barrier of Ga ad-atoms on the (20 2 ¯ 1) facets. By first-principles calculations, we find that the diffusion barrier of ad-atoms reduces with decreasing width of facets and is responsible for the anisotropic growth leading to the formation of NwN. This study suggests that formation of NwN is an archetype example of structure dependent attachment kinetic instability induced shape transition in thin film growth.
Zinc(II) and lead(II) metal-organic networks driven by a multifunctional pyridine-carboxylate building block: Hydrothermal synthesis, structural and topological features, and luminescence properties

NASA Astrophysics Data System (ADS)

Yang, Ling; Li, Yu; You, Ao; Jiang, Juan; Zou, Xun-Zhong; Chen, Jin-Wei; Gu, Jin-Zhong; Kirillov, Alexander M.

2016-09-01

4-(5-Carboxypyridin-2-yl)isophthalic acid (H3L) was applied as a flexible, multifunctional N,O-building block for the hydrothermal self-assembly synthesis of two novel coordination compounds, namely 2D [Zn(μ3-HL)(H2O)]n·nH2O (1) and 3D [Pb2(μ5-HL)(μ6-HL)]n (2) coordination polymers (CPs). These compounds were obtained in aqueous medium from a mixture containing zinc(II) or lead(II) nitrate, H3L, and sodium hydroxide. The products were isolated as stable crystalline solids and were characterized by IR spectroscopy, elemental, thermogravimetric (TGA), powder (PXRD) and single-crystal X-ray diffraction analyses. Compound 1 possesses a 2D metal-organic layer with the fes topology, which is further extended into a 3D supramolecular framework via hydrogen bonds. In contrast, compound 2 features a very complex network structure, which was topologically classified as a binodal 5,6-connected net with the unique topology defined by the point symbol of (47.63)(49.66). Compounds 1 and 2 disclose an intense blue or green luminescent emission at room temperature.
Facile Synthesis of SiO2@C Nanoparticles Anchored on MWNT as High-Performance Anode Materials for Li-ion Batteries.

PubMed

Zhao, Yan; Liu, Zhengjun; Zhang, Yongguang; Mentbayeva, Almagul; Wang, Xin; Maximov, M Yu; Liu, Baoxi; Bakenov, Zhumabay; Yin, Fuxing

2017-12-01

Carbon-coated silica nanoparticles anchored on multi-walled carbon nanotubes (SiO 2 @C/MWNT composite) were synthesized via a simple and facile sol-gel method followed by heat treatment. Scanning and transmission electron microscopy (SEM and TEM) studies confirmed densely anchoring the carbon-coated SiO 2 nanoparticles onto a flexible MWNT conductive network, which facilitated fast electron and lithium-ion transport and improved structural stability of the composite. As prepared, ternary composite anode showed superior cyclability and rate capability compared to a carbon-coated silica counterpart without MWNT (SiO 2 @C). The SiO 2 @C/MWNT composite exhibited a high reversible discharge capacity of 744 mAh g -1 at the second discharge cycle conducted at a current density of 100 mA g -1 as well as an excellent rate capability, delivering a capacity of 475 mAh g -1 even at 1000 mA g -1 . This enhanced electrochemical performance of SiO 2 @C/MWNT ternary composite anode was associated with its unique core-shell and networking structure and a strong mutual synergistic effect among the individual components.
A Network-Based Algorithm for Clustering Multivariate Repeated Measures Data

NASA Technical Reports Server (NTRS)

Koslovsky, Matthew; Arellano, John; Schaefer, Caroline; Feiveson, Alan; Young, Millennia; Lee, Stuart

2017-01-01

The National Aeronautics and Space Administration (NASA) Astronaut Corps is a unique occupational cohort for which vast amounts of measures data have been collected repeatedly in research or operational studies pre-, in-, and post-flight, as well as during multiple clinical care visits. In exploratory analyses aimed at generating hypotheses regarding physiological changes associated with spaceflight exposure, such as impaired vision, it is of interest to identify anomalies and trends across these expansive datasets. Multivariate clustering algorithms for repeated measures data may help parse the data to identify homogeneous groups of astronauts that have higher risks for a particular physiological change. However, available clustering methods may not be able to accommodate the complex data structures found in NASA data, since the methods often rely on strict model assumptions, require equally-spaced and balanced assessment times, cannot accommodate missing data or differing time scales across variables, and cannot process continuous and discrete data simultaneously. To fill this gap, we propose a network-based, multivariate clustering algorithm for repeated measures data that can be tailored to fit various research settings. Using simulated data, we demonstrate how our method can be used to identify patterns in complex data structures found in practice.
Advancing medical device innovation through collaboration and coordination of structured data capture pilots: Report from the Medical Device Epidemiology Network (MDEpiNet) Specific, Measurable, Achievable, Results-Oriented, Time Bound (SMART) Think Tank.

PubMed

Reed, Terrie L; Drozda, Joseph P; Baskin, Kevin M; Tcheng, James; Conway, Karen; Wilson, Natalia; Marinac-Dabic, Danica; Heise, Theodore; Krucoff, Mitchell W

2017-12-01

The Medical Device Epidemiology Network (MDEpiNet) is a public private partnership (PPP) that provides a platform for collaboration on medical device evaluation and depth of expertise for supporting pilots to capture, exchange and use device information for improving device safety and protecting public health. The MDEpiNet SMART Think Tank, held in February, 2013, sought to engage expert stakeholders who were committed to improving the capture of device data, including Unique Device Identification (UDI), in key electronic health information. Prior to the Think Tank there was limited collaboration among stakeholders beyond a few single health care organizations engaged in electronic capture and exchange of device data. The Think Tank resulted in what has become two sustainable multi-stakeholder device data capture initiatives, BUILD and VANGUARD. These initiatives continue to mature within the MDEpiNet PPP structure and are well aligned with the goals outlined in recent FDA-initiated National Medical Device Planning Board and Medical Device Registry Task Force white papers as well as the vision for the National Evaluation System for health Technology.%. Published by Elsevier Inc.
Facile Synthesis of SiO2@C Nanoparticles Anchored on MWNT as High-Performance Anode Materials for Li-ion Batteries

NASA Astrophysics Data System (ADS)

Zhao, Yan; Liu, Zhengjun; Zhang, Yongguang; Mentbayeva, Almagul; Wang, Xin; Maximov, M. Yu.; Liu, Baoxi; Bakenov, Zhumabay; Yin, Fuxing

2017-07-01

Carbon-coated silica nanoparticles anchored on multi-walled carbon nanotubes (SiO2@C/MWNT composite) were synthesized via a simple and facile sol-gel method followed by heat treatment. Scanning and transmission electron microscopy (SEM and TEM) studies confirmed densely anchoring the carbon-coated SiO2 nanoparticles onto a flexible MWNT conductive network, which facilitated fast electron and lithium-ion transport and improved structural stability of the composite. As prepared, ternary composite anode showed superior cyclability and rate capability compared to a carbon-coated silica counterpart without MWNT (SiO2@C). The SiO2@C/MWNT composite exhibited a high reversible discharge capacity of 744 mAh g-1 at the second discharge cycle conducted at a current density of 100 mA g-1 as well as an excellent rate capability, delivering a capacity of 475 mAh g-1 even at 1000 mA g-1. This enhanced electrochemical performance of SiO2@C/MWNT ternary composite anode was associated with its unique core-shell and networking structure and a strong mutual synergistic effect among the individual components.
MONGKIE: an integrated tool for network analysis and visualization for multi-omics data.

PubMed

Jang, Yeongjun; Yu, Namhee; Seo, Jihae; Kim, Sun; Lee, Sanghyuk

2016-03-18

Network-based integrative analysis is a powerful technique for extracting biological insights from multilayered omics data such as somatic mutations, copy number variations, and gene expression data. However, integrated analysis of multi-omics data is quite complicated and can hardly be done in an automated way. Thus, a powerful interactive visual mining tool supporting diverse analysis algorithms for identification of driver genes and regulatory modules is much needed. Here, we present a software platform that integrates network visualization with omics data analysis tools seamlessly. The visualization unit supports various options for displaying multi-omics data as well as unique network models for describing sophisticated biological networks such as complex biomolecular reactions. In addition, we implemented diverse in-house algorithms for network analysis including network clustering and over-representation analysis. Novel functions include facile definition and optimized visualization of subgroups, comparison of a series of data sets in an identical network by data-to-visual mapping and subsequent overlaying function, and management of custom interaction networks. Utility of MONGKIE for network-based visual data mining of multi-omics data was demonstrated by analysis of the TCGA glioblastoma data. MONGKIE was developed in Java based on the NetBeans plugin architecture, thus being OS-independent with intrinsic support of module extension by third-party developers. We believe that MONGKIE would be a valuable addition to network analysis software by supporting many unique features and visualization options, especially for analysing multi-omics data sets in cancer and other diseases. .
Bounded noise induced first-order phase transitions in a baseline non-spatial model of gene transcription

NASA Astrophysics Data System (ADS)

d'Onofrio, Alberto; Caravagna, Giulio; de Franciscis, Sebastiano

2018-02-01

In this work we consider, from a statistical mechanics point of view, the effects of bounded stochastic perturbations of the protein decay rate for a bistable biomolecular network module. Namely, we consider the perturbations of the protein decay/binding rate constant (DBRC) in a circuit modeling the positive feedback of a transcription factor (TF) on its own synthesis. The DBRC models both the spontaneous degradation of the TF and its linking to other unknown biomolecular factors or drugs. We show that bounded perturbations of the DBRC preserve the positivity of the parameter value (and also its limited variation), and induce effects of interest. First, the noise amplitude induces a first-order phase transition. This is of interest since the system in study has neither spatial components nor it is composed by multiple interacting networks. In particular, we observe that the system passes from two to a unique stochastic attractor, and vice-versa. This behavior is different from noise-induced transitions (also termed phenomenological bifurcations), where a unique stochastic attractor changes its shape depending on the values of a parameter. Moreover, we observe irreversible jumps as a consequence of the above-mentioned phase transition. We show that the illustrated mechanism holds for general models with the same deterministic hysteresis bifurcation structure. Finally, we illustrate the possible implications of our findings to the intracellular pharmacodynamics of drugs delivered in continuous infusion.
Synthesis of bacteria promoted reduced graphene oxide-nickel sulfide networks for advanced supercapacitors.

PubMed

Zhang, Haiming; Yu, Xinzhi; Guo, Di; Qu, Baihua; Zhang, Ming; Li, Qiuhong; Wang, Taihong

2013-08-14

Supercapacitors with potential high power are useful and have attracted much attention recently. Graphene-based composites have been demonstrated to be promising electrode materials for supercapacitors with enhanced properties. To improve the performance of graphene-based composites further and realize their synthesis with large scale, we report a green approach to synthesize bacteria-reduced graphene oxide-nickel sulfide (BGNS) networks. By using Bacillus subtilis as spacers, we deposited reduced graphene oxide/Ni3S2 nanoparticle composites with submillimeter pores directly onto substrate by a binder-free electrostatic spray approach to form BGNS networks. Their electrochemical capacitor performance was evaluated. Compared with stacked reduced graphene oxide-nickel sulfide (GNS) prepared without the aid of bacteria, BGNS with unique nm-μm structure exhibited a higher specific capacitance of about 1424 F g(-1) at a current density of 0.75 A g(-1). About 67.5% of the capacitance was retained as the current density increased from 0.75 to 15 A g(-1). At a current density of 75 A g(-1), a specific capacitance of 406 F g(-1) could still remain. The results indicate that the reduced graphene oxide-nickel sulfide network promoted by bacteria is a promising electrode material for supercapacitors.
The gravitational law of social interaction

NASA Astrophysics Data System (ADS)

Levy, Moshe; Goldenberg, Jacob

2014-01-01

While a great deal is known about the topology of social networks, there is much less agreement about the geographical structure of these networks. The fundamental question in this context is: how does the probability of a social link between two individuals depend on the physical distance between them? While it is clear that the probability decreases with the distance, various studies have found different functional forms for this dependence. The exact form of the distance dependence has crucial implications for network searchability and dynamics: Kleinberg (2000) [15] shows that the small-world property holds if the probability of a social link is a power-law function of the distance with power -2, but not with any other power. We investigate the distance dependence of link probability empirically by analyzing four very different sets of data: Facebook links, data from the electronic version of the Small-World experiment, email messages, and data from detailed personal interviews. All four datasets reveal the same empirical regularity: the probability of a social link is proportional to the inverse of the square of the distance between the two individuals, analogously to the distance dependence of the gravitational force. Thus, it seems that social networks spontaneously converge to the exact unique distance dependence that ensures the Small-World property.
Spinal Cord Injury Disrupts Resting-State Networks in the Human Brain.

PubMed

Hawasli, Ammar H; Rutlin, Jerrel; Roland, Jarod L; Murphy, Rory K J; Song, Sheng-Kwei; Leuthardt, Eric C; Shimony, Joshua S; Ray, Wilson Z

2018-03-15

Despite 253,000 spinal cord injury (SCI) patients in the United States, little is known about how SCI affects brain networks. Spinal MRI provides only structural information with no insight into functional connectivity. Resting-state functional MRI (RS-fMRI) quantifies network connectivity through the identification of resting-state networks (RSNs) and allows detection of functionally relevant changes during disease. Given the robust network of spinal cord afferents to the brain, we hypothesized that SCI produces meaningful changes in brain RSNs. RS-fMRIs and functional assessments were performed on 10 SCI subjects. Blood oxygen-dependent RS-fMRI sequences were acquired. Seed-based correlation mapping was performed using five RSNs: default-mode (DMN), dorsal-attention (DAN), salience (SAL), control (CON), and somatomotor (SMN). RSNs were compared with normal control subjects using false-discovery rate-corrected two way t tests. SCI reduced brain network connectivity within the SAL, SMN, and DMN and disrupted anti-correlated connectivity between CON and SMN. When divided into separate cohorts, complete but not incomplete SCI disrupted connectivity within SAL, DAN, SMN and DMN and between CON and SMN. Finally, connectivity changed over time after SCI: the primary motor cortex decreased connectivity with the primary somatosensory cortex, the visual cortex decreased connectivity with the primary motor cortex, and the visual cortex decreased connectivity with the sensory parietal cortex. These unique findings demonstrate the functional network plasticity that occurs in the brain as a result of injury to the spinal cord. Connectivity changes after SCI may serve as biomarkers to predict functional recovery following an SCI and guide future therapy.
Phase-space networks of geometrically frustrated systems.

PubMed

Han, Yilong

2009-11-01

We illustrate a network approach to the phase-space study by using two geometrical frustration models: antiferromagnet on triangular lattice and square ice. Their highly degenerated ground states are mapped as discrete networks such that the quantitative network analysis can be applied to phase-space studies. The resulting phase spaces share some comon features and establish a class of complex networks with unique Gaussian spectral densities. Although phase-space networks are heterogeneously connected, the systems are still ergodic due to the random Poisson processes. This network approach can be generalized to phase spaces of some other complex systems.
Trespassing cancer cells: ‘fingerprinting’ invasive protrusions reveals metastatic culprits

PubMed Central

Klemke, Richard L.

2012-01-01

Metastatic cancer cells produce invasive membrane protrusions called invadopodia and pseudopodia, which play a central role in driving cancer cell dissemination in the body. Malignant cells use these structures to attach to and degrade extracellular matrix proteins, generate force for cell locomotion, and to penetrate the vasculature. Recent work using unique subcellular fractionation methodologies combined with spatial genomic, proteomic, and phosphoproteomic profiling has provided insight into the invadopodiome and pseudopodiome signaling networks that control the protrusion of invasive membranes. Here I highlight how these powerful spatial “omics” approaches reveal important signatures of metastatic cancer cells and possible new therapeutic targets aimed at treating metastatic disease. PMID:22980730

Some links on this page may take you to non-federal websites. Their policies may differ from this site.