Network Approach to Understanding Emotion Dynamics in Relation to Childhood Trauma and Genetic Liability to Psychopathology: Replication of a Prospective Experience Sampling Analysis

PubMed Central

Hasmi, Laila; Drukker, Marjan; Guloksuz, Sinan; Menne-Lothmann, Claudia; Decoster, Jeroen; van Winkel, Ruud; Collip, Dina; Delespaul, Philippe; De Hert, Marc; Derom, Catherine; Thiery, Evert; Jacobs, Nele; Rutten, Bart P. F.; Wichers, Marieke; van Os, Jim

2017-01-01

Background: The network analysis of intensive time series data collected using the Experience Sampling Method (ESM) may provide vital information in gaining insight into the link between emotion regulation and vulnerability to psychopathology. The aim of this study was to apply the network approach to investigate whether genetic liability (GL) to psychopathology and childhood trauma (CT) are associated with the network structure of the emotions “cheerful,” “insecure,” “relaxed,” “anxious,” “irritated,” and “down”—collected using the ESM method. Methods: Using data from a population-based sample of twin pairs and siblings (704 individuals), we examined whether momentary emotion network structures differed across strata of CT and GL. GL was determined empirically using the level of psychopathology in monozygotic and dizygotic co-twins. Network models were generated using multilevel time-lagged regression analysis and were compared across three strata (low, medium, and high) of CT and GL, respectively. Permutations were utilized to calculate p values and compare regressions coefficients, density, and centrality indices. Regression coefficients were presented as connections, while variables represented the nodes in the network. Results: In comparison to the low GL stratum, the high GL stratum had significantly denser overall (p = 0.018) and negative affect network density (p < 0.001). The medium GL stratum also showed a directionally similar (in-between high and low GL strata) but statistically inconclusive association with network density. In contrast to GL, the results of the CT analysis were less conclusive, with increased positive affect density (p = 0.021) and overall density (p = 0.042) in the high CT stratum compared to the medium CT stratum but not to the low CT stratum. The individual node comparisons across strata of GL and CT yielded only very few significant results, after adjusting for multiple testing. Conclusions: The present findings demonstrate that the network approach may have some value in understanding the relation between established risk factors for mental disorders (particularly GL) and the dynamic interplay between emotions. The present finding partially replicates an earlier analysis, suggesting it may be instructive to model negative emotional dynamics as a function of genetic influence. PMID:29163289

Effect of Cross-Linking on Free Volume Properties of PEG Based Thiol-Ene Networks

NASA Astrophysics Data System (ADS)

Ramakrishnan, Ramesh; Vasagar, Vivek; Nazarenko, Sergei

According to the Fox and Loshaek theory, in elastomeric networks, free volume decreases linearly with the cross-link density increase. The aim of this study is to show whether the poly(ethylene glycol) (PEG) based multicomponent thiol-ene elastomeric networks demonstrate this model behavior? Networks with a broad cross-link density range were prepared by changing the ratio of the trithiol crosslinker to PEG dithiol and then UV cured with PEG diene while maintaining 1:1 thiol:ene stoichiometry. Pressure-volume-temperature (PVT) data of the networks was generated from the high pressure dilatometry experiments which was fit using the Simha-Somcynsky Equation-of-State analysis to obtain the fractional free volume of the networks. Using Positron Annihilation Lifetime Spectroscopy (PALS) analysis, the average free volume hole size of the networks was also quantified. The fractional free volume and the average free volume hole size showed a linear change with the cross-link density confirming that the Fox and Loshaek theory can be applied to this multicomponent system. Gas diffusivities of the networks showed a good correlation with free volume. A free volume based model was developed to describe the gas diffusivity trends as a function of cross-link density.

Architectural and engineering issues for building an optical Internet

NASA Astrophysics Data System (ADS)

St. Arnaud, Bill

1998-10-01

Recent developments in high density Wave Division Multiplexing fiber systems allows for the deployment of a dedicated optical Internet network for large volume backbone pipes that does not require an underlying multi-service SONET/SDH and ATM transport protocol. Some intrinsic characteristics of Internet traffic such as its self similar nature, server bound congestion, routing and data asymmetry allow for highly optimized traffic engineered networks using individual wavelengths. By transmitting GigaBit Ethernet or SONET/SDH frames natively over WDM wavelengths that directly interconnect high performance routers the original concept of the Internet as an intrinsically survivable datagram network is possible. Traffic engineering, restoral, protection and bandwidth management of the network must now be carried out at the IP layer and so new routing or switching protocols such as MPLS that allow for uni- directional paths with fast restoral and protection at the IP layer become essential for a reliable production network. The deployment of high density WDM municipal and campus networks also gives carriers and ISPs the flexibility to offer customers as integrated and seamless set of optical Internet services.

Disrupted resting brain graph measures in individuals at high risk for alcoholism.

PubMed

Holla, Bharath; Panda, Rajanikant; Venkatasubramanian, Ganesan; Biswal, Bharat; Bharath, Rose Dawn; Benegal, Vivek

2017-07-30

Familial susceptibility to alcoholism is likely to be linked to the externalizing diathesis seen in high-risk offspring from high-density alcohol use disorder (AUD) families. The present study aimed at comparing resting brain functional connectivity and their association with externalizing symptoms and alcoholism familial density in 40 substance-naive high-risk (HR) male offspring from high-density AUD families and 30 matched healthy low-risk (LR) males without a family history of substance dependence using graph theory-based network analysis. The HR subjects from high-density AUD families compared with LR, showed significantly reduced clustering, small-worldness, and local network efficiency. The frontoparietal, cingulo-opercular, sensorimotor and cerebellar networks exhibited significantly reduced functional segregation. These disruptions exhibited independent incremental value in predicting the externalizing symptoms over and above the demographic variables. The reduction of functional segregation in HR subjects was significant across both the younger and older age groups and was proportional to the family loading of AUDs. Detection and estimation of these developmentally relevant disruptions in small-world architecture at critical brain regions sub-serving cognitive, affective, and sensorimotor processes are vital for understanding the familial risk for early onset alcoholism as well as for understanding the pathophysiological mechanism of externalizing behaviors. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Silicon-embedded copper nanostructure network for high energy storage

DOEpatents

Yu, Tianyue

2018-01-23

Provided herein are nanostructure networks having high energy storage, electrochemically active electrode materials including nanostructure networks having high energy storage, as well as electrodes and batteries including the nanostructure networks having high energy storage. According to various implementations, the nanostructure networks have high energy density as well as long cycle life. In some implementations, the nanostructure networks include a conductive network embedded with electrochemically active material. In some implementations, silicon is used as the electrochemically active material. The conductive network may be a metal network such as a copper nanostructure network. Methods of manufacturing the nanostructure networks and electrodes are provided. In some implementations, metal nanostructures can be synthesized in a solution that contains silicon powder to make a composite network structure that contains both. The metal nanostructure growth can nucleate in solution and on silicon nanostructure surfaces.

Silicon-embedded copper nanostructure network for high energy storage

DOEpatents

Yu, Tianyue

2016-03-15

Provided herein are nanostructure networks having high energy storage, electrochemically active electrode materials including nanostructure networks having high energy storage, as well as electrodes and batteries including the nanostructure networks having high energy storage. According to various implementations, the nanostructure networks have high energy density as well as long cycle life. In some implementations, the nanostructure networks include a conductive network embedded with electrochemically active material. In some implementations, silicon is used as the electrochemically active material. The conductive network may be a metal network such as a copper nanostructure network. Methods of manufacturing the nanostructure networks and electrodes are provided. In some implementations, metal nanostructures can be synthesized in a solution that contains silicon powder to make a composite network structure that contains both. The metal nanostructure growth can nucleate in solution and on silicon nanostructure surfaces.

Nonparametric Density Estimation Based on Self-Organizing Incremental Neural Network for Large Noisy Data.

PubMed

Nakamura, Yoshihiro; Hasegawa, Osamu

2017-01-01

With the ongoing development and expansion of communication networks and sensors, massive amounts of data are continuously generated in real time from real environments. Beforehand, prediction of a distribution underlying such data is difficult; furthermore, the data include substantial amounts of noise. These factors make it difficult to estimate probability densities. To handle these issues and massive amounts of data, we propose a nonparametric density estimator that rapidly learns data online and has high robustness. Our approach is an extension of both kernel density estimation (KDE) and a self-organizing incremental neural network (SOINN); therefore, we call our approach KDESOINN. An SOINN provides a clustering method that learns about the given data as networks of prototype of data; more specifically, an SOINN can learn the distribution underlying the given data. Using this information, KDESOINN estimates the probability density function. The results of our experiments show that KDESOINN outperforms or achieves performance comparable to the current state-of-the-art approaches in terms of robustness, learning time, and accuracy.

Network analysis of inter-organizational relationships and policy use among active living organizations in Alberta, Canada.

PubMed

Loitz, Christina C; Stearns, Jodie A; Fraser, Shawn N; Storey, Kate; Spence, John C

2017-08-09

Coordinated partnerships and collaborations can optimize the efficiency and effectiveness of service and program delivery in organizational networks. However, the extent to which organizations are working together to promote physical activity, and use physical activity policies in Canada, is unknown. This project sought to provide a snapshot of the funding, coordination and partnership relationships among provincial active living organizations (ALOs) in Alberta, Canada. Additionally, the awareness, and use of the provincial policy and national strategy by the organizations was examined. Provincial ALOs (N = 27) answered questions regarding their funding, coordination and partnership connections with other ALOs in the network. Social network analysis was employed to examine network structure and position of each ALO. Discriminant function analysis determined the extent to which degree centrality was associated with the use of the Active Alberta (AA) policy and Active Canada 20/20 (AC 20/20) strategy. The funding network had a low density level (density = .20) and was centralized around Alberta Tourism Parks and Recreation (ATPR; degree centralization = 48.77%, betweenness centralization = 32.43%). The coordination network had a moderate density level (density = .31), and was low-to-moderately centralized around a few organizations (degree centralization = 45.37%, betweenness centrality = 19.92%). The partnership network had a low density level (density = .15), and was moderate-to-highly centralized around ATPR. Most organizations were aware of AA (89%) and AC 20/20 (78%), however more were using AA (67%) compared to AC 20/20 (33%). Central ALOs in the funding network were more likely to use AA and AC 20/20. Central ALOs in the coordination network were more likely to use AC 20/20, but not AA. Increasing formal and informal relationships between organizations and integrating disconnected or peripheral organizations could increase the capacity of the network to promote active living across Alberta. Uptake of the AA policy within the network is high and appears to be facilitated by the most central ALO. Promoting policy use through a central organization appeared to be an effective strategy for disseminating the province-level physical activity policy and could be considered as a policy-uptake strategy by other regions.

Structure and mechanism of diet specialisation: testing models of individual variation in resource use with sea otters

USGS Publications Warehouse

Tinker, M. Tim; Guimarães, Paulo R.; Novak, Mark; Marquitti, Flavia Maria Darcie; Bodkin, James L.; Staedler, Michelle; Bentall, Gena B.; Estes, James A.

2012-01-01

Studies of consumer-resource interactions suggest that individual diet specialisation is empirically widespread and theoretically important to the organisation and dynamics of populations and communities. We used weighted networks to analyze the resource use by sea otters, testing three alternative models for how individual diet specialisation may arise. As expected, individual specialisation was absent when otter density was low, but increased at high-otter density. A high-density emergence of nested resource-use networks was consistent with the model assuming individuals share preference ranks. However, a density-dependent emergence of a non-nested modular network for ‘core’ resources was more consistent with the ‘competitive refuge’ model. Individuals from different diet modules showed predictable variation in rank-order prey preferences and handling times of core resources, further supporting the competitive refuge model. Our findings support a hierarchical organisation of diet specialisation and suggest individual use of core and marginal resources may be driven by different selective pressures.

The Influence of Neuronal Density and Maturation on Network Activity of Hippocampal Cell Cultures: A Methodological Study

PubMed Central

Menegon, Andrea; Ferrigno, Giancarlo; Pedrocchi, Alessandra

2013-01-01

It is known that cell density influences the maturation process of in vitro neuronal networks. Neuronal cultures plated with different cell densities differ in number of synapses per neuron and thus in single neuron synaptic transmission, which results in a density-dependent neuronal network activity. Although many authors provided detailed information about the effects of cell density on neuronal culture activity, a dedicated report of density and age influence on neuronal hippocampal culture activity has not yet been reported. Therefore, this work aims at providing reference data to researchers that set up an experimental study on hippocampal neuronal cultures, helping in planning and decoding the experiments. In this work, we analysed the effects of both neuronal density and culture age on functional attributes of maturing hippocampal cultures. We characterized the electrophysiological activity of neuronal cultures seeded at three different cell densities, recording their spontaneous electrical activity over maturation by means of MicroElectrode Arrays (MEAs). We had gather data from 86 independent hippocampal cultures to achieve solid statistic results, considering the high culture-to-culture variability. Network activity was evaluated in terms of simple spiking, burst and network burst features. We observed that electrical descriptors were characterized by a functional peak during maturation, followed by a stable phase (for sparse and medium density cultures) or by a decrease phase (for high dense neuronal cultures). Moreover, 900 cells/mm2 cultures showed characteristics suitable for long lasting experiments (e.g. chronic effect of drug treatments) while 1800 cells/mm2 cultures should be preferred for experiments that require intense electrical activity (e.g. to evaluate the effect of inhibitory molecules). Finally, cell cultures at 3600 cells/mm2 are more appropriate for experiments in which time saving is relevant (e.g. drug screenings). These results are intended to be a reference for the planning of in vitro neurophysiological and neuropharmacological experiments with MEAs. PMID:24386305

The influence of neuronal density and maturation on network activity of hippocampal cell cultures: a methodological study.

PubMed

Biffi, Emilia; Regalia, Giulia; Menegon, Andrea; Ferrigno, Giancarlo; Pedrocchi, Alessandra

2013-01-01

It is known that cell density influences the maturation process of in vitro neuronal networks. Neuronal cultures plated with different cell densities differ in number of synapses per neuron and thus in single neuron synaptic transmission, which results in a density-dependent neuronal network activity. Although many authors provided detailed information about the effects of cell density on neuronal culture activity, a dedicated report of density and age influence on neuronal hippocampal culture activity has not yet been reported. Therefore, this work aims at providing reference data to researchers that set up an experimental study on hippocampal neuronal cultures, helping in planning and decoding the experiments. In this work, we analysed the effects of both neuronal density and culture age on functional attributes of maturing hippocampal cultures. We characterized the electrophysiological activity of neuronal cultures seeded at three different cell densities, recording their spontaneous electrical activity over maturation by means of MicroElectrode Arrays (MEAs). We had gather data from 86 independent hippocampal cultures to achieve solid statistic results, considering the high culture-to-culture variability. Network activity was evaluated in terms of simple spiking, burst and network burst features. We observed that electrical descriptors were characterized by a functional peak during maturation, followed by a stable phase (for sparse and medium density cultures) or by a decrease phase (for high dense neuronal cultures). Moreover, 900 cells/mm(2) cultures showed characteristics suitable for long lasting experiments (e.g. chronic effect of drug treatments) while 1800 cells/mm(2) cultures should be preferred for experiments that require intense electrical activity (e.g. to evaluate the effect of inhibitory molecules). Finally, cell cultures at 3600 cells/mm(2) are more appropriate for experiments in which time saving is relevant (e.g. drug screenings). These results are intended to be a reference for the planning of in vitro neurophysiological and neuropharmacological experiments with MEAs.

A clustering algorithm for determining community structure in complex networks

NASA Astrophysics Data System (ADS)

Jin, Hong; Yu, Wei; Li, ShiJun

2018-02-01

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

High Energy Density All Solid State Asymmetric Pseudocapacitors Based on Free Standing Reduced Graphene Oxide-Co3O4 Composite Aerogel Electrodes.

PubMed

Ghosh, Debasis; Lim, Joonwon; Narayan, Rekha; Kim, Sang Ouk

2016-08-31

Modern flexible consumer electronics require efficient energy storage devices with flexible free-standing electrodes. We report a simple and cost-effective route to a graphene-based composite aerogel encapsulating metal oxide nanoparticles for high energy density, free-standing, binder-free flexible pseudocapacitive electrodes. Hydrothermally synthesized Co3O4 nanoparticles are successfully housed inside the microporous graphene aerogel network during the room temperature interfacial gelation at the Zn surface. The resultant three-dimensional (3D) rGO-Co3O4 composite aerogel shows mesoporous quasiparallel layer stack morphology with a high loading of Co3O4, which offers numerous channels for ion transport and a 3D interconnected network for high electrical conductivity. All solid state asymmetric pseudocapacitors employing the composite aerogel electrodes have demonstrated high areal energy density of 35.92 μWh/cm(2) and power density of 17.79 mW/cm(2) accompanied by excellent cycle life.

Epidemic spreading on dual-structure networks with mobile agents

NASA Astrophysics Data System (ADS)

Yao, Yiyang; Zhou, Yinzuo

2017-02-01

The rapid development of modern society continually transforms the social structure which leads to an increasingly distinct dual structure of higher population density in urban areas and lower density in rural areas. Such structure may induce distinctive spreading behavior of epidemics which does not happen in a single type structure. In this paper, we study the epidemic spreading of mobile agents on dual structure networks based on SIRS model. First, beyond the well known epidemic threshold for generic epidemic model that when the infection rate is below the threshold a pertinent infectious disease will die out, we find the other epidemic threshold which appears when the infection rate of a disease is relatively high. This feature of two thresholds for the SIRS model may lead to the elimination of infectious disease when social network has either high population density or low population density. Interestingly, however, we find that when a high density area is connected to a low density may cause persistent spreading of the infectious disease, even though the same disease will die out when it spreads in each single area. This phenomenon indicates the critical role of the connection between the two areas which could radically change the behavior of spreading dynamics. Our findings, therefore, provide new understanding of epidemiology pertinent to the characteristic modern social structure and have potential to develop controlling strategies accordingly.

Aligning Solution-Derived Carbon Nanotube Film with Full Surface Coverage for High-Performance Electronics Applications.

PubMed

Zhu, Ma-Guang; Si, Jia; Zhang, Zhiyong; Peng, Lian-Mao

2018-06-01

The main challenge for application of solution-derived carbon nanotubes (CNTs) in high performance field-effect transistor (FET) is how to align CNTs into an array with high density and full surface coverage. A directional shrinking transfer method is developed to realize high density aligned array based on randomly orientated CNT network film. Through transferring a solution-derived CNT network film onto a stretched retractable film followed by a shrinking process, alignment degree and density of CNT film increase with the shrinking multiple. The quadruply shrunk CNT films present well alignment, which is identified by the polarized Raman spectroscopy and electrical transport measurements. Based on the high quality and high density aligned CNT array, the fabricated FETs with channel length of 300 nm present ultrahigh performance including on-state current I on of 290 µA µm -1 (V ds = -1.5 V and V gs = -2 V) and peak transconductance g m of 150 µS µm -1 , which are, respectively, among the highest corresponding values in the reported CNT array FETs. High quality and high semiconducting purity CNT arrays with high density and full coverage obtained through this method promote the development of high performance CNT-based electronics. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Wireless sensor node for surface seawater density measurements.

PubMed

Baronti, Federico; Fantechi, Gabriele; Roncella, Roberto; Saletti, Roberto

2012-01-01

An electronic meter to measure surface seawater density is presented. It is based on the measurement of the difference in displacements of a surface level probe and a weighted float, which according to Archimedes' law depends on the density of the water. The displacements are simultaneously measured using a high-accuracy magnetostrictive sensor, to which a custom electronic board provides a wireless connection and power supply so that it can become part of a wireless sensor network. The electronics are designed so that different kinds of wireless networks can be used, by simply changing the wireless module and the relevant firmware of the microcontroller. Lastly, laboratory and at-sea tests are presented and discussed in order to highlight the functionality and the performance of a prototype of the wireless density meter node in a Bluetooth radio network. The experimental results show a good agreement of the values of the calculated density compared to reference hydrometer readings.

Wireless Sensor Node for Surface Seawater Density Measurements

PubMed Central

Baronti, Federico; Fantechi, Gabriele; Roncella, Roberto; Saletti, Roberto

2012-01-01

An electronic meter to measure surface seawater density is presented. It is based on the measurement of the difference in displacements of a surface level probe and a weighted float, which according to Archimedes’ law depends on the density of the water. The displacements are simultaneously measured using a high-accuracy magnetostrictive sensor, to which a custom electronic board provides a wireless connection and power supply so that it can become part of a wireless sensor network. The electronics are designed so that different kinds of wireless networks can be used, by simply changing the wireless module and the relevant firmware of the microcontroller. Lastly, laboratory and at-sea tests are presented and discussed in order to highlight the functionality and the performance of a prototype of the wireless density meter node in a Bluetooth radio network. The experimental results show a good agreement of the values of the calculated density compared to reference hydrometer readings. PMID:22736986

WSN-Based Space Charge Density Measurement System

PubMed Central

Deng, Dawei; Yuan, Haiwen; Lv, Jianxun; Ju, Yong

2017-01-01

It is generally acknowledged that high voltage direct current (HVDC) transmission line endures the drawback of large area, because of which the utilization of cable for space charge density monitoring system is of inconvenience. Compared with the traditional communication network, wireless sensor network (WSN) shows advantages in small volume, high flexibility and strong self-organization, thereby presenting great potential in solving the problem. Additionally, WSN is more suitable for the construction of distributed space charge density monitoring system as it has longer distance and higher mobility. A distributed wireless system is designed for collecting and monitoring the space charge density under HVDC transmission lines, which has been widely applied in both Chinese state grid HVDC test base and power transmission projects. Experimental results of the measuring system demonstrated its adaptability in the complex electromagnetic environment under the transmission lines and the ability in realizing accurate, flexible, and stable demands for the measurement of space charge density. PMID:28052105

WSN-Based Space Charge Density Measurement System.

PubMed

Deng, Dawei; Yuan, Haiwen; Lv, Jianxun; Ju, Yong

2017-01-01

It is generally acknowledged that high voltage direct current (HVDC) transmission line endures the drawback of large area, because of which the utilization of cable for space charge density monitoring system is of inconvenience. Compared with the traditional communication network, wireless sensor network (WSN) shows advantages in small volume, high flexibility and strong self-organization, thereby presenting great potential in solving the problem. Additionally, WSN is more suitable for the construction of distributed space charge density monitoring system as it has longer distance and higher mobility. A distributed wireless system is designed for collecting and monitoring the space charge density under HVDC transmission lines, which has been widely applied in both Chinese state grid HVDC test base and power transmission projects. Experimental results of the measuring system demonstrated its adaptability in the complex electromagnetic environment under the transmission lines and the ability in realizing accurate, flexible, and stable demands for the measurement of space charge density.

Spatiotemporal responses of dengue fever transmission to the road network in an urban area.

PubMed

Li, Qiaoxuan; Cao, Wei; Ren, Hongyan; Ji, Zhonglin; Jiang, Huixian

2018-07-01

Urbanization is one of the important factors leading to the spread of dengue fever. Recently, some studies found that the road network as an urbanization factor affects the distribution and spread of dengue epidemic, but the study of relationship between the distribution of dengue epidemic and road network is limited, especially in highly urbanized areas. This study explores the temporal and spatial spread characteristics of dengue fever in the distribution of road network by observing a dengue epidemic in the southern Chinese cities. Geographic information technology is used to extract the spatial location of cases and explore the temporal and spatial changes of dengue epidemic and its spatial relationship with road network. The results showed that there was a significant "severe" period in the temporal change of dengue epidemic situation, and the cases were mainly concentrated in the vicinity of narrow roads, the spread of the epidemic mainly along the high-density road network area. These results show that high-density road network is an important factor to the direction and scale of dengue epidemic. This information may be helpful to the development of related epidemic prevention and control strategies. Copyright © 2018. Published by Elsevier B.V.

High-resolution electron microscope observation of voids in amorphous Ge.

NASA Technical Reports Server (NTRS)

Donovan, T. M.; Heinemann, K.

1971-01-01

Electron micrographs have been obtained which clearly show the existence of a void network in amorphous Ge films formed at substrate temperatures of 25 and 150 C, and the absence of a void network in films formed at higher substrate temperatures of 200 and 250 C. These results correlate quite well with density measurements and predictions of void densities by indirect methods.

Simple gain probability functions for large reflector antennas of JPL/NASA

NASA Technical Reports Server (NTRS)

Jamnejad, V.

2003-01-01

Simple models for the patterns as well as their cumulative gain probability and probability density functions of the Deep Space Network antennas are developed. These are needed for the study and evaluation of interference from unwanted sources such as the emerging terrestrial system, High Density Fixed Service, with the Ka-band receiving antenna systems in Goldstone Station of the Deep Space Network.

Epidemics in interconnected small-world networks.

PubMed

Liu, Meng; Li, Daqing; Qin, Pengju; Liu, Chaoran; Wang, Huijuan; Wang, Feilong

2015-01-01

Networks can be used to describe the interconnections among individuals, which play an important role in the spread of disease. Although the small-world effect has been found to have a significant impact on epidemics in single networks, the small-world effect on epidemics in interconnected networks has rarely been considered. Here, we study the susceptible-infected-susceptible (SIS) model of epidemic spreading in a system comprising two interconnected small-world networks. We find that the epidemic threshold in such networks decreases when the rewiring probability of the component small-world networks increases. When the infection rate is low, the rewiring probability affects the global steady-state infection density, whereas when the infection rate is high, the infection density is insensitive to the rewiring probability. Moreover, epidemics in interconnected small-world networks are found to spread at different velocities that depend on the rewiring probability.

Feedforward, high density, programmable read only neural network based memory system

NASA Technical Reports Server (NTRS)

Daud, Taher; Moopenn, Alex; Lamb, James; Thakoor, Anil; Khanna, Satish

1988-01-01

Neural network-inspired, nonvolatile, programmable associative memory using thin-film technology is demonstrated. The details of the architecture, which uses programmable resistive connection matrices in synaptic arrays and current summing and thresholding amplifiers as neurons, are described. Several synapse configurations for a high-density array of a binary connection matrix are also described. Test circuits are evaluated for operational feasibility and to demonstrate the speed of the read operation. The results are discussed to highlight the potential for a read data rate exceeding 10 megabits/sec.

Convergence and divergence across construction methods for human brain white matter networks: an assessment based on individual differences.

PubMed

Zhong, Suyu; He, Yong; Gong, Gaolang

2015-05-01

Using diffusion MRI, a number of studies have investigated the properties of whole-brain white matter (WM) networks with differing network construction methods (node/edge definition). However, how the construction methods affect individual differences of WM networks and, particularly, if distinct methods can provide convergent or divergent patterns of individual differences remain largely unknown. Here, we applied 10 frequently used methods to construct whole-brain WM networks in a healthy young adult population (57 subjects), which involves two node definitions (low-resolution and high-resolution) and five edge definitions (binary, FA weighted, fiber-density weighted, length-corrected fiber-density weighted, and connectivity-probability weighted). For these WM networks, individual differences were systematically analyzed in three network aspects: (1) a spatial pattern of WM connections, (2) a spatial pattern of nodal efficiency, and (3) network global and local efficiencies. Intriguingly, we found that some of the network construction methods converged in terms of individual difference patterns, but diverged with other methods. Furthermore, the convergence/divergence between methods differed among network properties that were adopted to assess individual differences. Particularly, high-resolution WM networks with differing edge definitions showed convergent individual differences in the spatial pattern of both WM connections and nodal efficiency. For the network global and local efficiencies, low-resolution and high-resolution WM networks for most edge definitions consistently exhibited a highly convergent pattern in individual differences. Finally, the test-retest analysis revealed a decent temporal reproducibility for the patterns of between-method convergence/divergence. Together, the results of the present study demonstrated a measure-dependent effect of network construction methods on the individual difference of WM network properties. © 2015 Wiley Periodicals, Inc.

Supercapacitors based on 3D network of activated carbon nanowhiskers wrapped-on graphitized electrospun nanofibers

NASA Astrophysics Data System (ADS)

He, Shuijian; Chen, Linlin; Xie, Chencheng; Hu, Huan; Chen, Shuiliang; Hanif, Muddasir; Hou, Haoqing

2013-12-01

Due to their cycling stability and high power density, the supercapacitors bridge the power/energy gap between traditional dielectric capacitors and batteries/fuel cells. Electrode materials are key components for making high performance supercapacitors. An activated carbon nanowhiskers (ACNWs) wrapped-on graphitized electrospun nanofiber (GENF) network (ACNWs/GENFN) with 3D porous structure is prepared as a new type of binder-free electrode material for supercapacitors. The supercapacitor based on the ACNWs/GENFN composite material displays an excellent performance with a specific capacitance of 176.5 F g-1 at current density of 0.5 A g-1, an ultrahigh power density of 252.8 kW kg-1 at current density of 800 A g-1 and an outstanding cycling stability of no capacitance loss after 10,000 charge/discharge cycles.

Longitudinal development of cortical thickness, folding, and fiber density networks in the first 2 years of life.

PubMed

Nie, Jingxin; Li, Gang; Wang, Li; Shi, Feng; Lin, Weili; Gilmore, John H; Shen, Dinggang

2014-08-01

Quantitatively characterizing the development of cortical anatomical networks during the early stage of life plays an important role in revealing the relationship between cortical structural connection and high-level functional development. The development of correlation networks of cortical-thickness, cortical folding, and fiber-density is systematically analyzed in this article to study the relationship between different anatomical properties during the first 2 years of life. Specifically, longitudinal MR images of 73 healthy subjects from birth to 2 year old are used. For each subject at each time point, its measures of cortical thickness, cortical folding, and fiber density are projected to its cortical surface that has been partitioned into 78 cortical regions. Then, the correlation matrices for cortical thickness, cortical folding, and fiber density at each time point can be constructed, respectively, by computing the inter-regional Pearson correlation coefficient (of any pair of ROIs) across all 73 subjects. Finally, the presence/absence pattern (i.e., binary pattern) of the connection network is constructed from each inter-regional correlation matrix, and its statistical and anatomical properties are adopted to analyze the longitudinal development of anatomical networks. The results show that the development of anatomical network could be characterized differently by using different anatomical properties (i.e., using cortical thickness, cortical folding, or fiber density). Copyright © 2013 Wiley Periodicals, Inc.

Automated extraction of natural drainage density patterns for the conterminous United States through high performance computing

USGS Publications Warehouse

Stanislawski, Larry V.; Falgout, Jeff T.; Buttenfield, Barbara P.

2015-01-01

Hydrographic networks form an important data foundation for cartographic base mapping and for hydrologic analysis. Drainage density patterns for these networks can be derived to characterize local landscape, bedrock and climate conditions, and further inform hydrologic and geomorphological analysis by indicating areas where too few headwater channels have been extracted. But natural drainage density patterns are not consistently available in existing hydrographic data for the United States because compilation and capture criteria historically varied, along with climate, during the period of data collection over the various terrain types throughout the country. This paper demonstrates an automated workflow that is being tested in a high-performance computing environment by the U.S. Geological Survey (USGS) to map natural drainage density patterns at the 1:24,000-scale (24K) for the conterminous United States. Hydrographic network drainage patterns may be extracted from elevation data to guide corrections for existing hydrographic network data. The paper describes three stages in this workflow including data pre-processing, natural channel extraction, and generation of drainage density patterns from extracted channels. The workflow is concurrently implemented by executing procedures on multiple subbasin watersheds within the U.S. National Hydrography Dataset (NHD). Pre-processing defines parameters that are needed for the extraction process. Extraction proceeds in standard fashion: filling sinks, developing flow direction and weighted flow accumulation rasters. Drainage channels with assigned Strahler stream order are extracted within a subbasin and simplified. Drainage density patterns are then estimated with 100-meter resolution and subsequently smoothed with a low-pass filter. The extraction process is found to be of better quality in higher slope terrains. Concurrent processing through the high performance computing environment is shown to facilitate and refine the choice of drainage density extraction parameters and more readily improve extraction procedures than conventional processing.

Effects of the distribution density of a biomass combined heat and power plant network on heat utilisation efficiency in village-town systems.

PubMed

Zhang, Yifei; Kang, Jian

2017-11-01

The building of biomass combined heat and power (CHP) plants is an effective means of developing biomass energy because they can satisfy demands for winter heating and electricity consumption. The purpose of this study was to analyse the effect of the distribution density of a biomass CHP plant network on heat utilisation efficiency in a village-town system. The distribution density is determined based on the heat transmission threshold, and the heat utilisation efficiency is determined based on the heat demand distribution, heat output efficiency, and heat transmission loss. The objective of this study was to ascertain the optimal value for the heat transmission threshold using a multi-scheme comparison based on an analysis of these factors. To this end, a model of a biomass CHP plant network was built using geographic information system tools to simulate and generate three planning schemes with different heat transmission thresholds (6, 8, and 10 km) according to the heat demand distribution. The heat utilisation efficiencies of these planning schemes were then compared by calculating the gross power, heat output efficiency, and heat transmission loss of the biomass CHP plant for each scenario. This multi-scheme comparison yielded the following results: when the heat transmission threshold was low, the distribution density of the biomass CHP plant network was high and the biomass CHP plants tended to be relatively small. In contrast, when the heat transmission threshold was high, the distribution density of the network was low and the biomass CHP plants tended to be relatively large. When the heat transmission threshold was 8 km, the distribution density of the biomass CHP plant network was optimised for efficient heat utilisation. To promote the development of renewable energy sources, a planning scheme for a biomass CHP plant network that maximises heat utilisation efficiency can be obtained using the optimal heat transmission threshold and the nonlinearity coefficient for local roads. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

Feature extraction using convolutional neural network for classifying breast density in mammographic images

NASA Astrophysics Data System (ADS)

Thomaz, Ricardo L.; Carneiro, Pedro C.; Patrocinio, Ana C.

2017-03-01

Breast cancer is the leading cause of death for women in most countries. The high levels of mortality relate mostly to late diagnosis and to the direct proportionally relationship between breast density and breast cancer development. Therefore, the correct assessment of breast density is important to provide better screening for higher risk patients. However, in modern digital mammography the discrimination among breast densities is highly complex due to increased contrast and visual information for all densities. Thus, a computational system for classifying breast density might be a useful tool for aiding medical staff. Several machine-learning algorithms are already capable of classifying small number of classes with good accuracy. However, machinelearning algorithms main constraint relates to the set of features extracted and used for classification. Although well-known feature extraction techniques might provide a good set of features, it is a complex task to select an initial set during design of a classifier. Thus, we propose feature extraction using a Convolutional Neural Network (CNN) for classifying breast density by a usual machine-learning classifier. We used 307 mammographic images downsampled to 260x200 pixels to train a CNN and extract features from a deep layer. After training, the activation of 8 neurons from a deep fully connected layer are extracted and used as features. Then, these features are feedforward to a single hidden layer neural network that is cross-validated using 10-folds to classify among four classes of breast density. The global accuracy of this method is 98.4%, presenting only 1.6% of misclassification. However, the small set of samples and memory constraints required the reuse of data in both CNN and MLP-NN, therefore overfitting might have influenced the results even though we cross-validated the network. Thus, although we presented a promising method for extracting features and classifying breast density, a greater database is still required for evaluating the results.

Geographical Influences of an Emerging Network of Gang Rivalries

DTIC Science & Technology

2011-03-17

Hollenbeck in the N × M environment grid. The semi-permeable boundaries encoded in the model are displayed in the center image. The shades of gray of...intensity. Light shades of gray correspond to high density values near one and dark shades correspond to low densities near zero. The boundary crossing...Threshold Graphs ( GTG ) For comparison to the networks produced by our simulations, we constructed an instance of a Geograph- ical Threshold Graph ( GTG

Flowable Conducting Particle Networks in Redox-Active Electrolytes for Grid Energy Storage

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

Hatzell, K. B.; Boota, M.; Kumbur, E. C.

2015-01-01

This study reports a new hybrid approach toward achieving high volumetric energy and power densities in an electrochemical flow capacitor for grid energy storage. The electrochemical flow capacitor suffers from high self-discharge and low energy density because charge storage is limited to the available surface area (electric double layer charge storage). Here, we examine two carbon materials as conducting particles in a flow battery electrolyte containing the VO2+/VO2+ redox couple. Highly porous activated carbon spheres (CSs) and multi-walled carbon nanotubes (MWCNTs) are investigated as conducting particle networks that facilitate both faradaic and electric double layer charge storage. Charge storage contributionsmore » (electric double layer and faradaic) are distinguished for flow-electrodes composed of MWCNTs and activated CSs. A MWCNT flow-electrode based in a redox-active electrolyte containing the VO2+/VO2+ redox couple demonstrates 18% less self-discharge, 10 X more energy density, and 20 X greater power densities (at 20 mV s-1) than one based on a non-redox active electrolyte. Furthermore, a MWCNT redox-active flow electrode demonstrates 80% capacitance retention, and >95% coulombic efficiency over 100 cycles, indicating the feasibility of utilizing conducting networks with redox chemistries for grid energy storage.« less

Flowable conducting particle networks in redox-active electrolytes for grid energy storage

DOE PAGES

Hatzell, K. B.; Boota, M.; Kumbur, E. C.; ...

2015-01-09

This paper reports a new hybrid approach toward achieving high volumetric energy and power densities in an electrochemical flow capacitor for grid energy storage. The electrochemical flow capacitor suffers from high self-discharge and low energy density because charge storage is limited to the available surface area (electric double layer charge storage). Here, we examine two carbon materials as conducting particles in a flow battery electrolyte containing the VO 2+/VO 2 + redox couple. Highly porous activated carbon spheres (CSs) and multi-walled carbon nanotubes (MWCNTs) are investigated as conducting particle networks that facilitate both faradaic and electric double layer charge storage.more » Charge storage contributions (electric double layer and faradaic) are distinguished for flow-electrodes composed of MWCNTs and activated CSs. A MWCNT flow-electrode based in a redox-active electrolyte containing the VO 2+/VO 2 + redox couple demonstrates 18% less self-discharge, 10 X more energy density, and 20 X greater power densities (at 20 mV s -1) than one based on a non-redox active electrolyte. Additionally, a MWCNT redox-active flow electrode demonstrates 80% capacitance retention, and >95% coulombic efficiency over 100 cycles, indicating the feasibility of utilizing conducting networks with redox chemistries for grid energy storage.« less

Detection of protein complex from protein-protein interaction network using Markov clustering

NASA Astrophysics Data System (ADS)

Ochieng, P. J.; Kusuma, W. A.; Haryanto, T.

2017-05-01

Detection of complexes, or groups of functionally related proteins, is an important challenge while analysing biological networks. However, existing algorithms to identify protein complexes are insufficient when applied to dense networks of experimentally derived interaction data. Therefore, we introduced a graph clustering method based on Markov clustering algorithm to identify protein complex within highly interconnected protein-protein interaction networks. Protein-protein interaction network was first constructed to develop geometrical network, the network was then partitioned using Markov clustering to detect protein complexes. The interest of the proposed method was illustrated by its application to Human Proteins associated to type II diabetes mellitus. Flow simulation of MCL algorithm was initially performed and topological properties of the resultant network were analysed for detection of the protein complex. The results indicated the proposed method successfully detect an overall of 34 complexes with 11 complexes consisting of overlapping modules and 20 non-overlapping modules. The major complex consisted of 102 proteins and 521 interactions with cluster modularity and density of 0.745 and 0.101 respectively. The comparison analysis revealed MCL out perform AP, MCODE and SCPS algorithms with high clustering coefficient (0.751) network density and modularity index (0.630). This demonstrated MCL was the most reliable and efficient graph clustering algorithm for detection of protein complexes from PPI networks.

Pressure effects on collective density fluctuations in water and protein solutions

PubMed Central

Russo, Daniela; Laloni, Alessio; Filabozzi, Alessandra; Heyden, Matthias

2017-01-01

Neutron Brillouin scattering and molecular dynamics simulations have been used to investigate protein hydration water density fluctuations as a function of pressure. Our results show significant differences between the pressure and density dependence of collective dynamics in bulk water and in concentrated protein solutions. Pressure-induced changes in the tetrahedral order of the water HB network have direct consequences for the high-frequency sound velocity and damping coefficients, which we find to be a sensitive probe for changes in the HB network structure as well as the wetting of biomolecular surfaces. PMID:29073065

Toward the Limits of Uniformity of Mixed Metallicity SWCNT TFT Arrays with Spark-Synthesized and Surface-Density-Controlled Nanotube Networks.

PubMed

Kaskela, Antti; Mustonen, Kimmo; Laiho, Patrik; Ohno, Yutaka; Kauppinen, Esko I

2015-12-30

We report the fabrication of thin film transistors (TFTs) from networks of nonbundled single-walled carbon nanotubes with controlled surface densities. Individual nanotubes were synthesized by using a spark generator-based floating catalyst CVD process. High uniformity and the control of SWCNT surface density were realized by mixing of the SWCNT aerosol in a turbulent flow mixer and monitoring the online number concentration with a condensation particle counter at the reactor outlet in real time. The networks consist of predominantly nonbundled SWCNTs with diameters of 1.0-1.3 nm, mean length of 3.97 μm, and metallic to semiconducting tube ratio of 1:2. The ON/OFF ratio and charge carrier mobility of SWCNT TFTs were simultaneously optimized through fabrication of devices with SWCNT surface densities ranging from 0.36 to 1.8 μm(-2) and channel lengths and widths from 5 to 100 μm and from 100 to 500 μm, respectively. The density optimized TFTs exhibited excellent performance figures with charge carrier mobilities up to 100 cm(2) V(-1) s(-1) and ON/OFF current ratios exceeding 1 × 10(6), combined with high uniformity and more than 99% of devices working as theoretically expected.

Structural, electronic, and vibrational properties of high-density amorphous silicon: a first-principles molecular-dynamics study.

PubMed

Morishita, Tetsuya

2009-05-21

We report a first-principles study of the structural, electronic, and dynamical properties of high-density amorphous (HDA) silicon, which was found to be formed by pressurizing low-density amorphous (LDA) silicon (a normal amorphous Si) [T. Morishita, Phys. Rev. Lett. 93, 055503 (2004); P. F. McMillan, M. Wilson, D. Daisenberger, and D. Machon, Nature Mater. 4, 680 (2005)]. Striking structural differences between HDA and LDA are revealed. The LDA structure holds a tetrahedral network, while the HDA structure contains a highly distorted tetrahedral network. The fifth neighboring atom in HDA tends to be located at an interstitial position of a distorted tetrahedron composed of the first four neighboring atoms. Consequently, the coordination number of HDA is calculated to be approximately 5 unlike that of LDA. The electronic density of state (EDOS) shows that HDA is metallic, which is consistent with a recent experimental measurement of the electronic resistance of HDA Si. We find from local EDOS that highly distorted tetrahedral configurations enhance the metallic nature of HDA. The vibrational density of state (VDOS) also reflects the structural differences between HDA and LDA. Some of the characteristic vibrational modes of LDA are dematerialized in HDA, indicating the degradation of covalent bonds. The overall profile of the VDOS for HDA is found to be an intermediate between that for LDA and liquid Si under pressure (high-density liquid Si).

Networks for image acquisition, processing and display

NASA Technical Reports Server (NTRS)

Ahumada, Albert J., Jr.

1990-01-01

The human visual system comprises layers of networks which sample, process, and code images. Understanding these networks is a valuable means of understanding human vision and of designing autonomous vision systems based on network processing. Ames Research Center has an ongoing program to develop computational models of such networks. The models predict human performance in detection of targets and in discrimination of displayed information. In addition, the models are artificial vision systems sharing properties with biological vision that has been tuned by evolution for high performance. Properties include variable density sampling, noise immunity, multi-resolution coding, and fault-tolerance. The research stresses analysis of noise in visual networks, including sampling, photon, and processing unit noises. Specific accomplishments include: models of sampling array growth with variable density and irregularity comparable to that of the retinal cone mosaic; noise models of networks with signal-dependent and independent noise; models of network connection development for preserving spatial registration and interpolation; multi-resolution encoding models based on hexagonal arrays (HOP transform); and mathematical procedures for simplifying analysis of large networks.

3D Ta/TaO x /TiO2/Ti synaptic array and linearity tuning of weight update for hardware neural network applications

NASA Astrophysics Data System (ADS)

Wang, I.-Ting; Chang, Chih-Cheng; Chiu, Li-Wen; Chou, Teyuh; Hou, Tuo-Hung

2016-09-01

The implementation of highly anticipated hardware neural networks (HNNs) hinges largely on the successful development of a low-power, high-density, and reliable analog electronic synaptic array. In this study, we demonstrate a two-layer Ta/TaO x /TiO2/Ti cross-point synaptic array that emulates the high-density three-dimensional network architecture of human brains. Excellent uniformity and reproducibility among intralayer and interlayer cells were realized. Moreover, at least 50 analog synaptic weight states could be precisely controlled with minimal drifting during a cycling endurance test of 5000 training pulses at an operating voltage of 3 V. We also propose a new state-independent bipolar-pulse-training scheme to improve the linearity of weight updates. The improved linearity considerably enhances the fault tolerance of HNNs, thus improving the training accuracy.

Devices and circuits for nanoelectronic implementation of artificial neural networks

NASA Astrophysics Data System (ADS)

Turel, Ozgur

Biological neural networks perform complicated information processing tasks at speeds better than conventional computers based on conventional algorithms. This has inspired researchers to look into the way these networks function, and propose artificial networks that mimic their behavior. Unfortunately, most artificial neural networks, either software or hardware, do not provide either the speed or the complexity of a human brain. Nanoelectronics, with high density and low power dissipation that it provides, may be used in developing more efficient artificial neural networks. This work consists of two major contributions in this direction. First is the proposal of the CMOL concept, hybrid CMOS-molecular hardware [1-8]. CMOL may circumvent most of the problems in posed by molecular devices, such as low yield, vet provide high active device density, ˜1012/cm 2. The second contribution is CrossNets, artificial neural networks that are based on CMOL. We showed that CrossNets, with their fault tolerance, exceptional speed (˜ 4 to 6 orders of magnitude faster than biological neural networks) can perform any task any artificial neural network can perform. Moreover, there is a hope that if their integration scale is increased to that of human cerebral cortex (˜ 1010 neurons and ˜ 1014 synapses), they may be capable of performing more advanced tasks.

Efficient Supercapacitor Energy Storage Using Conjugated Microporous Polymer Networks Synthesized from Buchwald-Hartwig Coupling.

PubMed

Liao, Yaozu; Wang, Haige; Zhu, Meifang; Thomas, Arne

2018-03-01

Supercapacitors have received increasing interest as energy storage devices due to their rapid charge-discharge rates, high power densities, and high durability. In this work, novel conjugated microporous polymer (CMP) networks are presented for supercapacitor energy storage, namely 3D polyaminoanthraquinone (PAQ) networks synthesized via Buchwald-Hartwig coupling between 2,6-diaminoanthraquinone and aryl bromides. PAQs exhibit surface areas up to 600 m 2 g -1 , good dispersibility in polar solvents, and can be processed to flexible electrodes. The PAQs exhibit a three-electrode specific capacitance of 576 F g -1 in 0.5 m H 2 SO 4 at a current of 1 A g -1 retaining 80-85% capacitances and nearly 100% Coulombic efficiencies (95-98%) upon 6000 cycles at a current density of 2 A g -1 . Asymmetric two-electrode supercapacitors assembled by PAQs show a capacitance of 168 F g -1 of total electrode materials, an energy density of 60 Wh kg -1 at a power density of 1300 W kg -1 , and a wide working potential window (0-1.6 V). The asymmetric supercapacitors show Coulombic efficiencies up to 97% and can retain 95.5% of initial capacitance undergo 2000 cycles. This work thus presents novel promising CMP networks for charge energy storage. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Network survivability performance (computer diskette)

NASA Astrophysics Data System (ADS)

1993-11-01

File characteristics: Data file; 1 file. Physical description: 1 computer diskette; 3 1/2 in.; high density; 2.0MB. System requirements: Mac; Word. This technical report has been developed to address the survivability of telecommunications networks including services. It responds to the need for a common understanding of, and assessment techniques for network survivability, availability, integrity, and reliability. It provides a basis for designing and operating telecommunication networks to user expectations for network survivability.

Assessing Urban Streets Network Vulnerability against Earthquake Using GIS - Case Study: 6TH Zone of Tehran

NASA Astrophysics Data System (ADS)

Rastegar, A.

2017-09-01

Great earthquakes cause huge damages to human life. Street networks vulnerability makes the rescue operation to encounter serious difficulties especially at the first 72 hours after the incident. Today, physical expansion and high density of great cities, due to narrow access roads, large distance from medical care centers and location at areas with high seismic risk, will lead to a perilous and unpredictable situation in case of the earthquake. Zone # 6 of Tehran, with 229,980 population (3.6% of city population) and 20 km2 area (3.2% of city area), is one of the main municipal zones of Tehran (Iran center of statistics, 2006). Major land-uses, like ministries, embassies, universities, general hospitals and medical centers, big financial firms and so on, manifest the high importance of this region on local and national scale. In this paper, by employing indexes such as access to medical centers, street inclusion, building and population density, land-use, PGA and building quality, vulnerability degree of street networks in zone #6 against the earthquake is calculated through overlaying maps and data in combination with IHWP method and GIS. This article concludes that buildings alongside the streets with high population and building density, low building quality, far to rescue centers and high level of inclusion represent high rate of vulnerability, compared with other buildings. Also, by moving on from north to south of the zone, the vulnerability increases. Likewise, highways and streets with substantial width and low building and population density hold little values of vulnerability.

Consensus between Pipelines in Structural Brain Networks

PubMed Central

Parker, Christopher S.; Deligianni, Fani; Cardoso, M. Jorge; Daga, Pankaj; Modat, Marc; Dayan, Michael; Clark, Chris A.

2014-01-01

Structural brain networks may be reconstructed from diffusion MRI tractography data and have great potential to further our understanding of the topological organisation of brain structure in health and disease. Network reconstruction is complex and involves a series of processesing methods including anatomical parcellation, registration, fiber orientation estimation and whole-brain fiber tractography. Methodological choices at each stage can affect the anatomical accuracy and graph theoretical properties of the reconstructed networks, meaning applying different combinations in a network reconstruction pipeline may produce substantially different networks. Furthermore, the choice of which connections are considered important is unclear. In this study, we assessed the similarity between structural networks obtained using two independent state-of-the-art reconstruction pipelines. We aimed to quantify network similarity and identify the core connections emerging most robustly in both pipelines. Similarity of network connections was compared between pipelines employing different atlases by merging parcels to a common and equivalent node scale. We found a high agreement between the networks across a range of fiber density thresholds. In addition, we identified a robust core of highly connected regions coinciding with a peak in similarity across network density thresholds, and replicated these results with atlases at different node scales. The binary network properties of these core connections were similar between pipelines but showed some differences in atlases across node scales. This study demonstrates the utility of applying multiple structural network reconstrution pipelines to diffusion data in order to identify the most important connections for further study. PMID:25356977

Lipoprotein lipase S447X variant associated with VLDL, LDL and HDL diameter clustering in the MetS

USDA-ARS?s Scientific Manuscript database

Previous analysis clustered 1,238 individuals from the general population Genetics of Lipid Lowering Drugs Network (GOLDN) study by the size of their fasting very low-density, low-density and high-density lipoproteins (VLDL, LDL, HDL) using latent class analysis. From two of the eight identified gro...

High-density defects on PdAg nanowire networks as catalytic hot spots for efficient dehydrogenation of formic acid and reduction of nitrate.

PubMed

Liu, Hu; Yu, Yongsheng; Yang, Weiwei; Lei, Wenjuan; Gao, Manyi; Guo, Shaojun

2017-07-13

Controlling the surface defects of nanocrystals is a new way of tuning/boosting their catalytic properties. Herein, we report networked PdAg nanowires (NWs) with high-density defects as catalytic hot spots for efficient catalytic dehydrogenation of formic acid (FA) and catalytic reduction of nitrates. The networked PdAg NWs exhibit composition-dependent catalytic activity for the dehydrogenation reaction of FA without any additive, with Pd 5 Ag 5 NWs exhibiting the highest activity. They also show good durability, reflected by the retention of their initial activity during the dehydrogenation reaction of FA even after five cycles. Their initial TOF is 419 h -1 at 60 °C in water solution, much higher than those of the most Pd-based catalysts with a support. Moreover, they can efficiently reduce nitrates to alleviate nitrate pollution in water (conversion yield >99%). This strategy opens up a new green synthetic technique to design support-free heterogeneous catalysts with high-density defects as catalytic hot spots for efficient dehydrogenation catalysis of FA to meet the requirement of fuel cell applications and catalytic reduction of nitrates in water polluted with nitrates.

Prediction of the physical properties of barium titanates using an artificial neural network

NASA Astrophysics Data System (ADS)

Al-Jabar, Ahmed Jaafar Abed; Al-dujaili, Mohammed Assi Ahmed; Al-hydary, Imad Ali Disher

2017-04-01

Barium titanate is one of the most important ceramics amongst those that are widely used in the electronic industry because of their dielectric properties. These properties are related to the physical properties of the material, namely, the density and the porosity. Thus, the prediction of these properties is highly desirable. The aim of the current work is to develop models that can predict the density, porosity, firing shrinkage, and the green density of barium titanate BaTiO3. An artificial neural network was used to fulfill this aim. The modified pechini method was used to prepare barium titanate powders with five different particle size distributions. Eighty samples were prepared using different processing parameters including the pressing rate, pressing pressure, heating rate, sintering temperature, and soaking time. In the artificial neural network (ANN) model, the experimental data set consisted of these 80 samples, 70 samples were used for training the network and 10 samples were employed for testing. A comparison was made between the experimental and the predicted data. Good performance of the ANN model was achieved, in which the results showed that the mean error for the density, porosity, shrinkage, and green density are 0.02, 0.06, 0.04, and 0.002, respectively.

Developing a tissue-engineered neural-electrical relay using encapsulated neuronal constructs on conducting polymer fibers.

PubMed

Cullen, D Kacy; R Patel, Ankur; Doorish, John F; Smith, Douglas H; Pfister, Bryan J

2008-12-01

Neural-electrical interface platforms are being developed to extracellularly monitor neuronal population activity. Polyaniline-based electrically conducting polymer fibers are attractive substrates for sustained functional interfaces with neurons due to their flexibility, tailored geometry and controlled electro-conductive properties. In this study, we addressed the neurobiological considerations of utilizing small diameter (<400 microm) fibers consisting of a blend of electrically conductive polyaniline and polypropylene (PA-PP) as the backbone of encapsulated tissue-engineered neural-electrical relays. We devised new approaches to promote survival, adhesion and neurite outgrowth of primary dorsal root ganglion neurons on PA-PP fibers. We attained a greater than ten-fold increase in the density of viable neurons on fiber surfaces to approximately 700 neurons mm(-2) by manipulating surrounding surface charges to bias settling neuronal suspensions toward fibers coated with cell-adhesive ligands. This stark increase in neuronal density resulted in robust neuritic extension and network formation directly along the fibers. Additionally, we encapsulated these neuronal networks on PA-PP fibers using agarose to form a protective barrier while potentially facilitating network stability. Following encapsulation, the neuronal networks maintained integrity, high viability (>85%) and intimate adhesion to PA-PP fibers. These efforts accomplished key prerequisites for the establishment of functional electrical interfaces with neuronal populations using small diameter PA-PP fibers-specifically, improved neurocompatibility, high-density neuronal adhesion and neuritic network development directly on fiber surfaces.

Analysis of neuronal cells of dissociated primary culture on high-density CMOS electrode array

PubMed Central

Matsuda, Eiko; Mita, Takeshi; Hubert, Julien; Bakkum, Douglas; Frey, Urs; Hierlemann, Andreas; Takahashi, Hirokazu; Ikegami, Takashi

2017-01-01

Spontaneous development of neuronal cells was recorded around 4–34 days in vitro (DIV) with high-density CMOS array, which enables detailed study of the spatio-temporal activity of neuronal culture. We used the CMOS array to characterize the evolution of the inter-spike interval (ISI) distribution from putative single neurons, and estimate the network structure based on transfer entropy analysis, where each node corresponds to a single neuron. We observed that the ISI distributions gradually obeyed the power law with maturation of the network. The amount of information transferred between neurons increased at the early stage of development, but decreased as the network matured. These results suggest that both ISI and transfer entropy were very useful for characterizing the dynamic development of cultured neural cells over a few weeks. PMID:24109870

High-Density Liquid-State Machine Circuitry for Time-Series Forecasting.

PubMed

Rosselló, Josep L; Alomar, Miquel L; Morro, Antoni; Oliver, Antoni; Canals, Vincent

2016-08-01

Spiking neural networks (SNN) are the last neural network generation that try to mimic the real behavior of biological neurons. Although most research in this area is done through software applications, it is in hardware implementations in which the intrinsic parallelism of these computing systems are more efficiently exploited. Liquid state machines (LSM) have arisen as a strategic technique to implement recurrent designs of SNN with a simple learning methodology. In this work, we show a new low-cost methodology to implement high-density LSM by using Boolean gates. The proposed method is based on the use of probabilistic computing concepts to reduce hardware requirements, thus considerably increasing the neuron count per chip. The result is a highly functional system that is applied to high-speed time series forecasting.

Social networks and inference about unknown events: A case of the match between Google's AlphaGo and Sedol Lee.

PubMed

Bae, Jonghoon; Cha, Young-Jae; Lee, Hyungsuk; Lee, Boyun; Baek, Sojung; Choi, Semin; Jang, Dayk

2017-01-01

This study examines whether the way that a person makes inferences about unknown events is associated with his or her social relations, more precisely, those characterized by ego network density that reflects the structure of a person's immediate social relation. From the analysis of individual predictions over the Go match between AlphaGo and Sedol Lee in March 2016 in Seoul, Korea, this study shows that the low-density group scored higher than the high-density group in the accuracy of the prediction over a future state of a social event, i.e., the outcome of the first game. We corroborated this finding with three replication tests that asked the participants to predict the following: film awards, President Park's impeachment in Korea, and the counterfactual assessment of the US presidential election. Taken together, this study suggests that network density is negatively associated with vision advantage, i.e., the ability to discover and forecast an unknown aspect of a social event.

Inhibition delay increases neural network capacity through Stirling transform.

PubMed

Nogaret, Alain; King, Alastair

2018-03-01

Inhibitory neural networks are found to encode high volumes of information through delayed inhibition. We show that inhibition delay increases storage capacity through a Stirling transform of the minimum capacity which stabilizes locally coherent oscillations. We obtain both the exact and asymptotic formulas for the total number of dynamic attractors. Our results predict a (ln2)^{-N}-fold increase in capacity for an N-neuron network and demonstrate high-density associative memories which host a maximum number of oscillations in analog neural devices.

Inhibition delay increases neural network capacity through Stirling transform

NASA Astrophysics Data System (ADS)

Nogaret, Alain; King, Alastair

2018-03-01

Inhibitory neural networks are found to encode high volumes of information through delayed inhibition. We show that inhibition delay increases storage capacity through a Stirling transform of the minimum capacity which stabilizes locally coherent oscillations. We obtain both the exact and asymptotic formulas for the total number of dynamic attractors. Our results predict a (ln2) -N-fold increase in capacity for an N -neuron network and demonstrate high-density associative memories which host a maximum number of oscillations in analog neural devices.

Communication, advice exchange and job satisfaction of nursing staff: a social network analyses of 35 long-term care units.

PubMed

van Beek, Adriana P A; Wagner, Cordula; Spreeuwenberg, Peter P M; Frijters, Dinnus H M; Ribbe, Miel W; Groenewegen, Peter P

2011-06-01

The behaviour of individuals is affected by the social networks in which they are embedded. Networks are also important for the diffusion of information and the influence of employees in organisations. Yet, at the moment little is known about the social networks of nursing staff in healthcare settings. This is the first study that investigates informal communication and advice networks of nursing staff in long-term care. We examine the structure of the networks, how they are related to the size of units and characteristics of nursing staff, and their relationship with job satisfaction. We collected social network data of 380 nursing staff of 35 units in group projects and psychogeriatric units in nursing homes and residential homes in the Netherlands. Communication and advice networks were analyzed in a social network application (UCINET), focusing on the number of contacts (density) between nursing staff on the units. We then studied the correlation between the density of networks, size of the units and characteristics of nursing staff. We used multilevel analyses to investigate the relationship between social networks and job satisfaction of nursing staff, taking characteristics of units and nursing staff into account. Both communication and advice networks were negatively related to the number of residents and the number of nursing staff of the units. Communication and advice networks were more dense when more staff worked part-time. Furthermore, density of communication networks was positively related to the age of nursing staff of the units. Multilevel analyses showed that job satisfaction differed significantly between individual staff members and units and was influenced by the number of nursing staff of the units. However, this relationship disappeared when density of communication networks was added to the model. Overall, communication and advice networks of nursing staff in long-term care are relatively dense. This fits with the high level of cooperation that is needed to provide good care to residents. Social networks are more dense in small units and are also shaped by characteristics of staff members. The results furthermore show that communication networks are important for staff's job satisfaction.

Communication, advice exchange and job satisfaction of nursing staff: a social network analyses of 35 long-term care units

PubMed Central

2011-01-01

Background The behaviour of individuals is affected by the social networks in which they are embedded. Networks are also important for the diffusion of information and the influence of employees in organisations. Yet, at the moment little is known about the social networks of nursing staff in healthcare settings. This is the first study that investigates informal communication and advice networks of nursing staff in long-term care. We examine the structure of the networks, how they are related to the size of units and characteristics of nursing staff, and their relationship with job satisfaction. Methods We collected social network data of 380 nursing staff of 35 units in group projects and psychogeriatric units in nursing homes and residential homes in the Netherlands. Communication and advice networks were analyzed in a social network application (UCINET), focusing on the number of contacts (density) between nursing staff on the units. We then studied the correlation between the density of networks, size of the units and characteristics of nursing staff. We used multilevel analyses to investigate the relationship between social networks and job satisfaction of nursing staff, taking characteristics of units and nursing staff into account. Results Both communication and advice networks were negatively related to the number of residents and the number of nursing staff of the units. Communication and advice networks were more dense when more staff worked part-time. Furthermore, density of communication networks was positively related to the age of nursing staff of the units. Multilevel analyses showed that job satisfaction differed significantly between individual staff members and units and was influenced by the number of nursing staff of the units. However, this relationship disappeared when density of communication networks was added to the model. Conclusions Overall, communication and advice networks of nursing staff in long-term care are relatively dense. This fits with the high level of cooperation that is needed to provide good care to residents. Social networks are more dense in small units and are also shaped by characteristics of staff members. The results furthermore show that communication networks are important for staff's job satisfaction. PMID:21631936

Retinal Microvascular Network and Microcirculation Assessments in High Myopia.

PubMed

Li, Min; Yang, Ye; Jiang, Hong; Gregori, Giovanni; Roisman, Luiz; Zheng, Fang; Ke, Bilian; Qu, Dongyi; Wang, Jianhua

2017-02-01

To investigate the changes of the retinal microvascular network and microcirculation in high myopia. A cross-sectional, matched, comparative clinical study. Twenty eyes of 20 subjects with nonpathological high myopia (28 ± 5 years of age) with a refractive error of -6.31 ± 1.23 D (mean ± SD) and 20 eyes of 20 age- and sex-matched control subjects (30 ± 6 years of age) with a refractive error of -1.40 ± 1.00 D were recruited. Optical coherence tomography angiography (OCTA) was used to image the retinal microvascular network, which was later quantified by fractal analysis (box counting [D box ], representing vessel density) in both superficial and deep vascular plexuses. The Retinal Function Imager was used to image the retinal microvessel blood flow velocity (BFV). The BFV and microvascular density in the myopia group were corrected for ocular magnification using Bennett's formula. The density of both superficial and deep microvascular plexuses was significantly decreased in the myopia group in comparison to the controls (P < .05). The decrease of the microvessel density of the annular zone (0.6-2.5 mm), measured as D box , was 2.1% and 2.9% in the superficial and deep vascular plexuses, respectively. Microvessel density reached a plateau from 0.5 mm to 1.25 mm from the fovea in both groups, but that in the myopic group was about 3% lower than the control group. No significant differences were detected between the groups in retinal microvascular BFV in either arterioles or venules (P > .05). Microvascular densities in both superficial (r = -0.45, P = .047) and deep (r = -0.54, P = .01) vascular plexuses were negatively correlated with the axial lengths in the myopic eye. No correlations were observed between BFV and vessel density (P > .05). Retinal microvascular decrease was observed in the high myopia subjects, whereas the retinal microvessel BFV remained unchanged. The retinal microvascular network alteration may be attributed to ocular elongation that occurs with the progression of myopia. The novel quantitative analyses of the retinal microvasculature may help to characterize the underlying pathophysiology of myopia and enable early detection and prevention of myopic retinopathy. Copyright © 2016 Elsevier Inc. All rights reserved.

Rapid Anastomosis of Endothelial Progenitor Cell–Derived Vessels with Host Vasculature Is Promoted by a High Density of Cotransplanted Fibroblasts

PubMed Central

Chen, Xiaofang; Aledia, Anna S.; Popson, Stephanie A.; Him, Linda; Hughes, Christopher C.W.

2010-01-01

To ensure survival of engineered implantable tissues thicker than approximately 2–3 mm, convection of nutrients and waste products to enhance the rate of transport will be required. Creating a network of vessels in vitro, before implantation (prevascularization), is one potential strategy to achieve this aim. In this study, we developed three-dimensional engineered vessel networks in vitro by coculture of endothelial cells (ECs) and fibroblasts in a fibrin gel for 7 days. Vessels formed by cord blood endothelial progenitor cell–derived ECs (EPC-ECs) in the presence of a high density of fibroblasts created an interconnected tubular network within 4 days, compared with 5–7 days in the presence of a low density of fibroblasts. Vessels derived from human umbilical vein ECs (HUVECs) in vitro showed similar kinetics. Implantation of the prevascularized tissues into immune-compromised mice, however, revealed a dramatic difference in the ability of EPC-ECs and HUVECs to form anastomoses with the host vasculature. Vascular beds derived from EPC-ECs were perfused within 1 day of implantation, whereas no HUVEC vessels were perfused at day 1. Further, while almost 90% of EPC-EC–derived vascular beds were perfused at day 3, only one-third of HUVEC-derived vascular beds were perfused. In both cases, a high density of fibroblasts accelerated anastomosis by 2–3 days. We conclude that both EPC-ECs and a high density of fibroblasts significantly accelerate the rate of functional anastomosis, and that prevascularizing an engineered tissue may be an effective strategy to enhance convective transport of nutrients in vivo. PMID:19737050

An EBIC study of dislocation networks in unprocessed and unprocessed web silicon ribbon. [for solar cells

NASA Technical Reports Server (NTRS)

Fieldler, F. S.; Ast, D.

1982-01-01

Experimental techniques for the preparation of electron beam induced current samples of Web-dentritic silicon are described. Both as grown and processed material were investigated. High density dislocation networks were found close to twin planes in the bulk of the material. The electrical activity of these networks is reduced in processed material.

Noninvasive imaging of human foveal capillary network using dual-conjugate adaptive optics.

PubMed

Popovic, Zoran; Knutsson, Per; Thaung, Jörgen; Owner-Petersen, Mette; Sjöstrand, Johan

2011-04-22

To demonstrate noninvasive imaging of human foveal capillary networks with a high-resolution, wide-field, dual-conjugate adaptive optics (DCAO) imaging instrument. The foveal capillary networks of five healthy subjects with no previous history of ocular or neurologic disease or surgery were imaged with a novel high-resolution, wide-field DCAO instrument. The foveal avascular zone (FAZ) in each image was defined using a manual procedure. An automated algorithm based on publicly available and custom-written software was used to identify vessels and extract morphologic FAZ and vessel parameters. Capillary densities were calculated in two annular regions of interest (ROIs) outside the FAZ (500 μm and 750 μm outer radius from the foveal center) and in the superior, inferior, temporal, and nasal quadrants within the two ROIs. Mean FAZ area was 0.302 ± 0.100 mm(2), and mean capillary density (length/area) in the inner ROI was 38.0 ± 4.0 mm(-1) and 36.4 ± 4.0 mm(-1) in the outer ROI. The difference in ROI capillary density was not significant. There was no significant difference in quadrant capillary density within the two ROIs or between quadrants irrespective of ROI. The authors have demonstrated a technique for noninvasive imaging and semiautomated detection and analysis of foveal capillaries. In comparison with other studies, their method yielded lower capillary densities than histology but similar results to the current clinical gold standard, fluorescein angiography. The increased field of view of the DCAO instrument opens up new possibilities for high-resolution noninvasive clinical imaging of foveal capillaries.

Selective MBE growth of hexagonal networks of trapezoidal and triangular GaAs nanowires on patterned (1 1 1)B substrates

NASA Astrophysics Data System (ADS)

Tamai, Isao; Hasegawa, Hideki

2007-04-01

As a combination of novel hardware architecture and novel system architecture for future ultrahigh-density III-V nanodevice LSIs, the authors' group has recently proposed a hexagonal binary decision diagram (BDD) quantum circuit approach where gate-controlled path switching BDD node devices for a single or few electrons are laid out on a hexagonal nanowire network to realize a logic function. In this paper, attempts are made to establish a method to grow highly dense hexagonal nanowire networks for future BDD circuits by selective molecular beam epitaxy (MBE) on (1 1 1)B substrates. The (1 1 1)B orientation is suitable for BDD architecture because of the basic three-fold symmetry of the BDD node device. The growth experiments showed complex evolution of the cross-sectional structures, and it was explained in terms of kinetics determining facet boundaries. Straight arrays of triangular nanowires with 60 nm base width as well as hexagonal arrays of trapezoidal nanowires with a node density of 7.5×10 6 cm -2 were successfully grown with the aid of computer simulation. The result shows feasibility of growing high-density hexagonal networks of GaAs nanowires with precise control of the shape and size.

Determining Usability Versus Cost and Yields of a Regional Transport

NASA Technical Reports Server (NTRS)

Gvozdenovic, Slobodan

1999-01-01

Regional transports are designed to operate on air networks having the basic characteristics of short trip distances and low density passengers/cargo, i.e. small numbers of passengers per flight. Regional transports passenger capacity is from 10 to 100 seats and operate on routes from 350 to 1000 nautical miles (nm). An air network operated by regional transports has the following characteristics: (1) connecting regional centers; (2) operating on low density passengers/cargo flow services with minimum two frequencies per day; (3) operating on high density passengers/cargo flow with more than two frequencies per day; and (4) operating supplemental services whenever market demands in order to help bigger capacity aircraft already operating the same routes. In order to meet passenger requirements providing low fares and high or required number of frequencies, airlines must constantly monitor operational costs and keep them low. It is obvious that costs of operating aircraft must be lower than yield obtained by transporting passengers and cargo. The requirement to achieve favorable yield/cost ratio must provide the answer to the question of which aircraft will best meet a specific air network. An air network is defined by the number of services, the trip distance of each service, and the number of flights (frequencies) per day and week.

Urban-scale mapping of PM2.5 distribution via data fusion between high-density sensor network and MODIS Aerosol Optical Depth

NASA Astrophysics Data System (ADS)

Ba, Yu Tao; xian Liu, Bao; Sun, Feng; Wang, Li hua; Tang, Yu jia; Zhang, Da wei

2017-04-01

High-resolution mapping of PM2.5 is the prerequisite for precise analytics and subsequent anti-pollution interventions. Considering the large variances of particulate distribution, urban-scale mapping is challenging either with ground-based fixed stations, with satellites or via models. In this study, a dynamic fusion method between high-density sensor network and MODIS Aerosol Optical Depth (AOD) was introduced. The sensor network was deployed in Beijing ( > 1000 fixed monitors across 16000 km2 area) to provide raw observations with high temporal resolution (sampling interval < 1 hour), high spatial resolution in flat areas ( < 1 km), and low spatial resolution in mountainous areas ( > 5 km). The MODIS AOD was calibrated to provide distribution map with low temporal resolution (daily) and moderate spatial resolution ( = 3 km). By encoding the data quality and defects (e.g. could, reflectance, abnormal), a hybrid interpolation procedure with cross-validation generated PM2.5 distribution with both high temporal and spatial resolution. Several no-pollutant and high-pollution periods were tested to validate the proposed fusion method for capturing the instantaneous patterns of PM2.5 emission.

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.

Effects of the bipartite structure of a network on performance of recommenders

NASA Astrophysics Data System (ADS)

Wang, Qing-Xian; Li, Jian; Luo, Xin; Xu, Jian-Jun; Shang, Ming-Sheng

2018-02-01

Recommender systems aim to predict people's preferences for online items by analyzing their historical behaviors. A recommender can be modeled as a high-dimensional and sparse bipartite network, where the key issue is to understand the relation between the network structure and a recommender's performance. To address this issue, we choose three network characteristics, clustering coefficient, network density and user-item ratio, as the analyzing targets. For the cluster coefficient, we adopt the Degree-preserving rewiring algorithm to obtain a series of bipartite network with varying cluster coefficient, while the degree of user and item keep unchanged. Furthermore, five state-of-the-art recommenders are applied on two real datasets. The performances of recommenders are measured by both numerical and physical metrics. These results show that a recommender's performance is positively related to the clustering coefficient of a bipartite network. Meanwhile, higher density of a bipartite network can provide more accurate but less diverse or novel recommendations. Furthermore, the user-item ratio is positively correlated with the accuracy metrics but negatively correlated with the diverse and novel metrics.

Using NVMe Gen3 PCIe SSD Cards in High-density Servers for High-performance Big Data Transfer Over Multiple Network Channels

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

Fang, Chin

This Technical Note describes how the Zettar team came up with a data transfer cluster design that convincingly proved the feasibility of using high-density servers for high-performance Big Data transfers. It then outlines the tests, operations, and observations that address a potential over-heating concern regarding the use of Non-Volatile Memory Host Controller Interface Specification (NVMHCI aka NVM Express or NVMe) Gen 3 PCIe SSD cards in high-density servers. Finally, it points out the possibility of developing a new generation of high-performance Science DMZ data transfer system for the data-intensive research community and commercial enterprises.

Structure Analysis of Jungle-Gym-Type Gels by Brownian Dynamics Simulation

NASA Astrophysics Data System (ADS)

Ohta, Noriyoshi; Ono, Kohki; Takasu, Masako; Furukawa, Hidemitsu

2008-02-01

We investigated the structure and the formation process of two kinds of gels by Brownian dynamics simulation. The effect of flexibility of main chain oligomer was studied. From our results, hard gel with rigid main chain forms more homogeneous network structure than soft gel with flexible main chain. In soft gel, many small loops are formed, and clusters tend to shrink. This heterogeneous network structure may be caused by microgels. In the low density case, soft gel shows more heterogeneity than the high density case.

STAR FORMATION IN TURBULENT MOLECULAR CLOUDS WITH COLLIDING FLOW

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

Matsumoto, Tomoaki; Dobashi, Kazuhito; Shimoikura, Tomomi, E-mail: matsu@hosei.ac.jp

2015-03-10

Using self-gravitational hydrodynamical numerical simulations, we investigated the evolution of high-density turbulent molecular clouds swept by a colliding flow. The interaction of shock waves due to turbulence produces networks of thin filamentary clouds with a sub-parsec width. The colliding flow accumulates the filamentary clouds into a sheet cloud and promotes active star formation for initially high-density clouds. Clouds with a colliding flow exhibit a finer filamentary network than clouds without a colliding flow. The probability distribution functions (PDFs) for the density and column density can be fitted by lognormal functions for clouds without colliding flow. When the initial turbulence ismore » weak, the column density PDF has a power-law wing at high column densities. The colliding flow considerably deforms the PDF, such that the PDF exhibits a double peak. The stellar mass distributions reproduced here are consistent with the classical initial mass function with a power-law index of –1.35 when the initial clouds have a high density. The distribution of stellar velocities agrees with the gas velocity distribution, which can be fitted by Gaussian functions for clouds without colliding flow. For clouds with colliding flow, the velocity dispersion of gas tends to be larger than the stellar velocity dispersion. The signatures of colliding flows and turbulence appear in channel maps reconstructed from the simulation data. Clouds without colliding flow exhibit a cloud-scale velocity shear due to the turbulence. In contrast, clouds with colliding flow show a prominent anti-correlated distribution of thin filaments between the different velocity channels, suggesting collisions between the filamentary clouds.« less

Facile fabrication of network film electrodes with ultrathin Au nanowires for nonenzymatic glucose sensing and glucose/O2 fuel cell.

PubMed

Yang, Lu; Zhang, Yijia; Chu, Mi; Deng, Wenfang; Tan, Yueming; Ma, Ming; Su, Xiaoli; Xie, Qingji; Yao, Shuozhuo

2014-02-15

We report here on the facile fabrication of network film electrodes with ultrathin Au nanowires (AuNWs) and their electrochemical applications for high-performance nonenzymatic glucose sensing and glucose/O2 fuel cell under physiological conditions (pH 7.4, containing 0.15M Cl(-)). AuNWs with an average diameter of ~7 or 2 nm were prepared and can self-assemble into robust network films on common electrodes. The network film electrode fabricated with 2-nm AuNWs exhibits high sensitivity (56.0 μA cm(-2)mM(-1)), low detection limit (20 μM), short response time (within 10s), excellent selectivity, and good storage stability for nonenzymatic glucose sensing. Glucose/O2 fuel cells were constructed using network film electrodes as the anode and commercial Pt/C catalyst modified glassy carbon electrode as cathode. The glucose/O2 fuel cell using 2-nm AuNWs as anode catalyst output a maximum power density of is 126 μW cm(-2), an open-circuit cell voltage of 0.425 V, and a short-circuit current density of 1.34 mA cm(-2), respectively. Due to the higher specific electroactive surface area of 2-nm AuNWs, the network film electrode fabricated with 2-nm AuNWs exhibited higher electrocatalytic activity toward glucose oxidation than the network film electrode fabricated with 7-nm AuNWs. The network film electrode exhibits high electrocatalytic activity toward glucose oxidation under physiological conditions, which is helpful for constructing implantable electronic devices. © 2013 Elsevier B.V. All rights reserved.

Functional Organization of the Action Observation Network in Autism: A Graph Theory Approach.

PubMed

Alaerts, Kaat; Geerlings, Franca; Herremans, Lynn; Swinnen, Stephan P; Verhoeven, Judith; Sunaert, Stefan; Wenderoth, Nicole

2015-01-01

The ability to recognize, understand and interpret other's actions and emotions has been linked to the mirror system or action-observation-network (AON). Although variations in these abilities are prevalent in the neuro-typical population, persons diagnosed with autism spectrum disorders (ASD) have deficits in the social domain and exhibit alterations in this neural network. Here, we examined functional network properties of the AON using graph theory measures and region-to-region functional connectivity analyses of resting-state fMRI-data from adolescents and young adults with ASD and typical controls (TC). Overall, our graph theory analyses provided convergent evidence that the network integrity of the AON is altered in ASD, and that reductions in network efficiency relate to reductions in overall network density (i.e., decreased overall connection strength). Compared to TC, individuals with ASD showed significant reductions in network efficiency and increased shortest path lengths and centrality. Importantly, when adjusting for overall differences in network density between ASD and TC groups, participants with ASD continued to display reductions in network integrity, suggesting that also network-level organizational properties of the AON are altered in ASD. While differences in empirical connectivity contributed to reductions in network integrity, graph theoretical analyses provided indications that also changes in the high-level network organization reduced integrity of the AON.

Zinc oxide nanowire networks for macroelectronic devices

NASA Astrophysics Data System (ADS)

Unalan, Husnu Emrah; Zhang, Yan; Hiralal, Pritesh; Dalal, Sharvari; Chu, Daping; Eda, Goki; Teo, K. B. K.; Chhowalla, Manish; Milne, William I.; Amaratunga, Gehan A. J.

2009-04-01

Highly transparent zinc oxide (ZnO) nanowire networks have been used as the active material in thin film transistors (TFTs) and complementary inverter devices. A systematic study on a range of networks of variable density and TFT channel length was performed. ZnO nanowire networks provide a less lithographically intense alternative to individual nanowire devices, are always semiconducting, and yield significantly higher mobilites than those achieved from currently used amorphous Si and organic TFTs. These results suggest that ZnO nanowire networks could be ideal for inexpensive large area electronics.

Inferring Broad Regulatory Biology from Time Course Data: Have We Reached an Upper Bound under Constraints Typical of In Vivo Studies?

PubMed Central

Craddock, Travis J. A.; Fletcher, Mary Ann; Klimas, Nancy G.

2015-01-01

There is a growing appreciation for the network biology that regulates the coordinated expression of molecular and cellular markers however questions persist regarding the identifiability of these networks. Here we explore some of the issues relevant to recovering directed regulatory networks from time course data collected under experimental constraints typical of in vivo studies. NetSim simulations of sparsely connected biological networks were used to evaluate two simple feature selection techniques used in the construction of linear Ordinary Differential Equation (ODE) models, namely truncation of terms versus latent vector projection. Performance was compared with ODE-based Time Series Network Identification (TSNI) integral, and the information-theoretic Time-Delay ARACNE (TD-ARACNE). Projection-based techniques and TSNI integral outperformed truncation-based selection and TD-ARACNE on aggregate networks with edge densities of 10-30%, i.e. transcription factor, protein-protein cliques and immune signaling networks. All were more robust to noise than truncation-based feature selection. Performance was comparable on the in silico 10-node DREAM 3 network, a 5-node Yeast synthetic network designed for In vivo Reverse-engineering and Modeling Assessment (IRMA) and a 9-node human HeLa cell cycle network of similar size and edge density. Performance was more sensitive to the number of time courses than to sample frequency and extrapolated better to larger networks by grouping experiments. In all cases performance declined rapidly in larger networks with lower edge density. Limited recovery and high false positive rates obtained overall bring into question our ability to generate informative time course data rather than the design of any particular reverse engineering algorithm. PMID:25984725

Edge Density Imaging: Mapping the Anatomic Embedding of the Structural Connectome Within the White Matter of the Human Brain

PubMed Central

Owen, Julia P.; Chang, Yi-Shin; Mukherjee, Pratik

2015-01-01

The structural connectome has emerged as a powerful tool to characterize the network architecture of the human brain and shows great potential for generating important new biomarkers for neurologic and psychiatric disorders. The edges of the cerebral graph traverse white matter to interconnect cortical and subcortical nodes, although the anatomic embedding of these edges is generally overlooked in the literature. Mapping the paths of the connectome edges could elucidate the relative importance of individual white matter tracts to the overall network topology of the brain and also lead to a better understanding of the effect of regionally-specific white matter pathology on cognition and behavior. In this work, we introduce edge density imaging (EDI), which maps the number of network edges that pass through every white matter voxel. Test-retest analysis shows good to excellent reliability for edge density (ED) measurements, with consistent results using different cortical and subcortical parcellation schemes and different diffusion MR imaging acquisition parameters. We also demonstrate that ED yields complementary information to both traditional and emerging voxel-wise metrics of white matter microstructure and connectivity, including fractional anisotropy, track density, fiber orientation dispersion and neurite density. Our results demonstrate spatially ordered variations of ED throughout the white matter, notably including greater ED in posterior than anterior cerebral white matter. The EDI framework is employed to map the white matter regions that are enriched with pathways connecting rich club nodes and also those with high densities of intra-modular and inter-modular edges. We show that periventricular white matter has particularly high ED and high densities of rich club edges, which is significant for diseases in which these areas are selectively affected, ranging from white matter injury of prematurity in infants to leukoaraiosis in the elderly. Using edge betweenness centrality, we identify specific white matter regions involved in a large number of shortest paths, some containing highly connected rich club edges while others are relatively isolated within individual modules. Overall, these findings reveal an intricate relationship between white matter anatomy and the structural connectome, motivating further exploration of EDI for biomarkers of cognition and behavior. PMID:25592996

Importance of network density of nanotube: Effect on nitrogen dioxide gas sensing by solid state resistive sensor

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

Mishra, Prabhash; Grachyova, D. V.; Moskalenko, A. S.

2016-04-13

Dispersion of single-walled carbon nanotubes (SWCNTs) is an established fact, however, its effect on toxic gas sensing for the development of solid state resistive sensor was not well reported. In this report, the dispersion quality of SWCNTs has been investigated and improved, and this well-dispersed SWCNTs network was used for sensor fabrication to monitor nitrogen dioxide gas. Ultraviolet (UV)-visible spectroscopic studies shows the strength of SWNTs dispersion and scanning electron microscopy (SEM) imaging provides the morphological properties of the sensor device. In this gas sensor device, two sets of resistive type sensors were fabricated that consisting of a pair ofmore » interdigitated electrodes (IDEs) using dielectrophoresis technique with different SWCNTs network density. With low-density SWCNTs networks, this fabricated sensor exhibits a high response for nitrogen dioxide sensing. The sensing of nitrogen dioxide is mainly due to charge transfer from absorbed molecules to sidewalls of nanotube and tube-tube screening acting a major role for the transport properties of charge carriers.« less

How can we establish more successful knowledge networks in developing countries? Lessons learnt from knowledge networks in Iran.

PubMed

Yazdizadeh, Bahareh; Majdzadeh, Reza; Alami, Ali; Amrolalaei, Sima

2014-10-29

Formal knowledge networks are considered among the solutions for strengthening knowledge translation and one of the elements of innovative systems in developing and developed countries. In the year 2000, knowledge networks were established in Iran's health system to organize, lead, empower, and coordinate efforts made by health-related research centers in the country. Since the assessment of a knowledge network is one of the main requirements for its success, the current study was designed in two qualitative and quantitative sections to identify the strengths and weaknesses of the established knowledge networks and to assess their efficiency. In the qualitative section, semi-structured, in-depth interviews were held with network directors and secretaries. The interviews were analyzed through the framework approach. To analyze effectiveness, social network analysis approach was used. That is, by considering the networks' research council members as 'nodes', and the numbers of their joint articles--before and after the network establishments--as 'relations or ties', indices of density, clique, and centrality were calculated for each network. In the qualitative section, non-transparency of management, lack of goals, administrative problems were among the most prevalent issues observed. Currently, the most important challenges are the policies related to them and their management. In the quantitative section, we observed that density and clique indices had risen for some networks; however, the centrality index for the same networks was not as high. Consequently the attribution of density and clique indices to these networks was not possible. Therefore, consolidating and revising policies relevant to the networks and preparing a guide for establishing managing networks could prove helpful. To develop knowledge and technology in a country, networks need to solve the problems they face in management and governance. That is, the first step towards the realization of true knowledge networks in health system.

Social networks and inference about unknown events: A case of the match between Google’s AlphaGo and Sedol Lee

PubMed Central

Bae, Jonghoon; Cha, Young-Jae; Lee, Hyungsuk; Lee, Boyun; Baek, Sojung; Choi, Semin

2017-01-01

This study examines whether the way that a person makes inferences about unknown events is associated with his or her social relations, more precisely, those characterized by ego network density that reflects the structure of a person’s immediate social relation. From the analysis of individual predictions over the Go match between AlphaGo and Sedol Lee in March 2016 in Seoul, Korea, this study shows that the low-density group scored higher than the high-density group in the accuracy of the prediction over a future state of a social event, i.e., the outcome of the first game. We corroborated this finding with three replication tests that asked the participants to predict the following: film awards, President Park’s impeachment in Korea, and the counterfactual assessment of the US presidential election. Taken together, this study suggests that network density is negatively associated with vision advantage, i.e., the ability to discover and forecast an unknown aspect of a social event. PMID:28222114

On the Impact of Localization and Density Control Algorithms in Target Tracking Applications for Wireless Sensor Networks

PubMed Central

Campos, Andre N.; Souza, Efren L.; Nakamura, Fabiola G.; Nakamura, Eduardo F.; Rodrigues, Joel J. P. C.

2012-01-01

Target tracking is an important application of wireless sensor networks. The networks' ability to locate and track an object is directed linked to the nodes' ability to locate themselves. Consequently, localization systems are essential for target tracking applications. In addition, sensor networks are often deployed in remote or hostile environments. Therefore, density control algorithms are used to increase network lifetime while maintaining its sensing capabilities. In this work, we analyze the impact of localization algorithms (RPE and DPE) and density control algorithms (GAF, A3 and OGDC) on target tracking applications. We adapt the density control algorithms to address the k-coverage problem. In addition, we analyze the impact of network density, residual integration with density control, and k-coverage on both target tracking accuracy and network lifetime. Our results show that DPE is a better choice for target tracking applications than RPE. Moreover, among the evaluated density control algorithms, OGDC is the best option among the three. Although the choice of the density control algorithm has little impact on the tracking precision, OGDC outperforms GAF and A3 in terms of tracking time. PMID:22969329

Spatial-Temporal Dynamics of High-Resolution Animal Networks: What Can We Learn from Domestic Animals?

PubMed

Chen, Shi; Ilany, Amiyaal; White, Brad J; Sanderson, Michael W; Lanzas, Cristina

2015-01-01

Animal social network is the key to understand many ecological and epidemiological processes. We used real-time location system (RTLS) to accurately track cattle position, analyze their proximity networks, and tested the hypothesis of temporal stationarity and spatial homogeneity in these networks during different daily time periods and in different areas of the pen. The network structure was analyzed using global network characteristics (network density), subgroup clustering (modularity), triadic property (transitivity), and dyadic interactions (correlation coefficient from a quadratic assignment procedure) at hourly level. We demonstrated substantial spatial-temporal heterogeneity in these networks and potential link between indirect animal-environment contact and direct animal-animal contact. But such heterogeneity diminished if data were collected at lower spatial (aggregated at entire pen level) or temporal (aggregated at daily level) resolution. The network structure (described by the characteristics such as density, modularity, transitivity, etc.) also changed substantially at different time and locations. There were certain time (feeding) and location (hay) that the proximity network structures were more consistent based on the dyadic interaction analysis. These results reveal new insights for animal network structure and spatial-temporal dynamics, provide more accurate descriptions of animal social networks, and allow more accurate modeling of multiple (both direct and indirect) disease transmission pathways.

Asymmetric simple exclusion process on chains with a shortcut.

PubMed

Bunzarova, Nadezhda; Pesheva, Nina; Brankov, Jordan

2014-03-01

We consider the asymmetric simple exclusion process (TASEP) on an open network consisting of three consecutively coupled macroscopic chain segments with a shortcut between the tail of the first segment and the head of the third one. The model was introduced by Y.-M. Yuan et al. [J. Phys. A 40, 12351 (2007)] to describe directed motion of molecular motors along twisted filaments. We report here unexpected results which revise the previous findings in the case of maximum current through the network. Our theoretical analysis, based on the effective rates' approximation, shows that the second (shunted) segment can exist in both low- and high-density phases, as well as in the coexistence (shock) phase. Numerical simulations demonstrate that the last option takes place in finite-size networks with head and tail chains of equal length, provided the injection and ejection rates at their external ends are equal and greater than one-half. Then the local density distribution and the nearest-neighbor correlations in the middle chain correspond to a shock phase with completely delocalized domain wall. Upon moving the shortcut to the head or tail of the network, the density profile takes a shape typical of a high- or low-density phase, respectively. Surprisingly, the main quantitative parameters of that shock phase are governed by a positive root of a cubic equation, the coefficients of which linearly depend on the probability of choosing the shortcut. Alternatively, they can be expressed in a universal way through the shortcut current. The unexpected conclusion is that a shortcut in the bulk of a single lane may create traffic jams.

A density-based clustering model for community detection in complex networks

NASA Astrophysics Data System (ADS)

Zhao, Xiang; Li, Yantao; Qu, Zehui

2018-04-01

Network clustering (or graph partitioning) is an important technique for uncovering the underlying community structures in complex networks, which has been widely applied in various fields including astronomy, bioinformatics, sociology, and bibliometric. In this paper, we propose a density-based clustering model for community detection in complex networks (DCCN). The key idea is to find group centers with a higher density than their neighbors and a relatively large integrated-distance from nodes with higher density. The experimental results indicate that our approach is efficient and effective for community detection of complex networks.

Social Demand of New Generation Information Network: Introduction to High Spectral Density Optical Communication Technology

NASA Astrophysics Data System (ADS)

Kamiya, Takeshi; Miyazaki, Tetsuya; Kubota, Fumito

In this section, first, current situation of traffic growth and penetration of broadband services are described. Then social demand, technical issues, and research trend for future information network in the United States, Europe, and Japan are described. Finally, a detailed construction of this book is introduced.

Mandala Networks: ultra-small-world and highly sparse graphs

PubMed Central

Sampaio Filho, Cesar I. N.; Moreira, André A.; Andrade, Roberto F. S.; Herrmann, Hans J.; Andrade, José S.

2015-01-01

The increasing demands in security and reliability of infrastructures call for the optimal design of their embedded complex networks topologies. The following question then arises: what is the optimal layout to fulfill best all the demands? Here we present a general solution for this problem with scale-free networks, like the Internet and airline networks. Precisely, we disclose a way to systematically construct networks which are robust against random failures. Furthermore, as the size of the network increases, its shortest path becomes asymptotically invariant and the density of links goes to zero, making it ultra-small world and highly sparse, respectively. The first property is ideal for communication and navigation purposes, while the second is interesting economically. Finally, we show that some simple changes on the original network formulation can lead to an improved topology against malicious attacks. PMID:25765450

Immunization of complex networks

NASA Astrophysics Data System (ADS)

Pastor-Satorras, Romualdo; Vespignani, Alessandro

2002-03-01

Complex networks such as the sexual partnership web or the Internet often show a high degree of redundancy and heterogeneity in their connectivity properties. This peculiar connectivity provides an ideal environment for the spreading of infective agents. Here we show that the random uniform immunization of individuals does not lead to the eradication of infections in all complex networks. Namely, networks with scale-free properties do not acquire global immunity from major epidemic outbreaks even in the presence of unrealistically high densities of randomly immunized individuals. The absence of any critical immunization threshold is due to the unbounded connectivity fluctuations of scale-free networks. Successful immunization strategies can be developed only by taking into account the inhomogeneous connectivity properties of scale-free networks. In particular, targeted immunization schemes, based on the nodes' connectivity hierarchy, sharply lower the network's vulnerability to epidemic attacks.

Factors Underlying Bursting Behavior in a Network of Cultured Hippocampal Neurons Exposed to Zero Magnesium

PubMed Central

Mangan, Patrick S.; Kapur, Jaideep

2010-01-01

Factors contributing to reduced magnesium-induced neuronal action potential bursting were investigated in primary hippocampal cell culture at high and low culture density. In nominally zero external magnesium medium, pyramidal neurons from high-density cultures produced recurrent spontaneous action potential bursts superimposed on prolonged depolarizations. These bursts were partially attenuated by the NMDA receptor antagonist D-APV. Pharmacological analysis of miniature excitatory postsynaptic currents (EPSCs) revealed 2 components: one sensitive to D-APV and another to the AMPA receptor antagonist DNQX. The components were kinetically distinct. Participation of NMDA receptors in reduced magnesium-induced synaptic events was supported by the localization of the NR1 subunit of the NMDA receptor with the presynaptic vesicular protein synaptophysin. Presynaptically, zero magnesium induced a significant increase in EPSC frequency likely attributable to increased neuronal hyperexcitability induced by reduced membrane surface charge screening. Mean quantal content was significantly increased in zero magnesium. Cells from low-density cultures did not exhibit action potential bursting in zero magnesium but did show increased EPSC frequency. Low-density neurons had less synaptophysin immunofluorescence and fewer active synapses as determined by FM1-43 analysis. These results demonstrate that multiple factors are involved in network bursting. Increased probability of transmitter release presynaptically, enhanced NMDA receptor-mediated excitability postsynaptically, and extent of neuronal interconnectivity contribute to initiation and maintenance of elevated network excitability. PMID:14534286

Social Networks, Sexual Networks and HIV Risk in Men Who Have Sex with Men

PubMed Central

Amirkhanian, Yuri A.

2014-01-01

Worldwide, men who have sex with men (MSM) remain one of the most HIV-vulnerable community populations. A global public health priority is developing new methods of reaching MSM, understanding HIV transmission patterns, and intervening to reduce their risk. Increased attention is being given to the role that MSM networks play in HIV epidemiology. This review of MSM network research studies demonstrates that: (1) Members of the same social network often share similar norms, attitudes, and HIV risk behavior levels; (2) Network interventions are feasible and powerful for reducing unprotected sex and potentially for increasing HIV testing uptake; (3) HIV vulnerability among African American MSM increases when an individual enters a high-risk sexual network characterized by high density and racial homogeneity; and (4) Networks are primary sources of social support for MSM, particularly for those living with HIV, with greater support predicting higher care uptake and adherence. PMID:24384832

Ubiquitousness of link-density and link-pattern communities in real-world networks

NASA Astrophysics Data System (ADS)

Šubelj, L.; Bajec, M.

2012-01-01

Community structure appears to be an intrinsic property of many complex real-world networks. However, recent work shows that real-world networks reveal even more sophisticated modules than classical cohesive (link-density) communities. In particular, networks can also be naturally partitioned according to similar patterns of connectedness among the nodes, revealing link-pattern communities. We here propose a propagation based algorithm that can extract both link-density and link-pattern communities, without any prior knowledge of the true structure. The algorithm was first validated on different classes of synthetic benchmark networks with community structure, and also on random networks. We have further applied the algorithm to different social, information, technological and biological networks, where it indeed reveals meaningful (composites of) link-density and link-pattern communities. The results thus seem to imply that, similarly as link-density counterparts, link-pattern communities appear ubiquitous in nature and design.

Recognize PM2.5 sources and emission patterns via high-density sensor network: An application case in Beijing

NASA Astrophysics Data System (ADS)

Ba, Yu tao; xian Liu, Bao; Sun, Feng; Wang, Li hua; Zhang, Da wei; Yin, Wen jun

2017-04-01

Beijing suffered severe air pollution during wintertime, 2016, with the unprecedented high level pollutants monitored. As the most dominant pollutant, fine particulate matter (PM2.5) was measured via high-density sensor network (>1000 fixed monitors across 16000 km2 area). This campaign provided precise observations (spatial resolution ≈ 3 km, temporal resolution = 10 min, error of measure < 5 ug/m3) to track potential emission sources. In addition, these observations coupled with WRF-Chem model (Weather Research and Forecasting model coupled with Chemistry) were analyzed to elucidate the effects of atmospheric transportations across regions, both horizontal and vertical, on emission patterns during this haze period. The results quantified the main cause of regional transport and local emission, and highlighted the importance of cross-region cooperation in anti-pollution campaigns.

[International focuses in the studies of chronic pelvic pain syndrome: A social network analysis].

PubMed

Wen, Li-Jie; Pan, Xian-Wei; Yang, Bo

2016-10-01

To analyze the internationally published literature relevant to chronic pelvic pain syndrome (CPPS) using bibliometrics and social network analysis, and investigate the current status and focuses of CPPS studies. We identified 692 publications on CPPS by searching PubMed up to December 2015, extracted their subject headings, calculated the frequencies of the headings, and constructed a co-occurrence network of the high-frequency (≥10) subject headings. Then we studied the features and structure of the co-occurrence network by analyzing its attributes and topological structure. The density of the constructed co-occurrence network was 0.111, with an average distance of 2.886 and a clustering coefficient of 0.685. Its low density, long average distance and high clustering coefficient indicated that it was a sparse network, with a slow speed of information spreading among nodes but a strong potential coherence, which suggested that the current topics in the study of CPPS were scattered and weakly correlated, with a high possibility of being integrated. Based on the topological structure of the co-occurrence network, the topics in the study of CPPS were divided into six aspects: diagnosis and classification, drug therapy, treatment, etiology, microbiology, psychology, and epidemiology, the more important of which were diagnosis and classification, drug therapy, treatment and etiology. A system has been formed in the studies of CPPS, focusing on the diagnosis, drug therapy, and etiology of the disease. However, the research topics are relatively scattered and frequently repeated. Therefore, more attention should be paid to the macrocosmic guidance and rational coordination of the researches on CPPS.

JDINAC: joint density-based non-parametric differential interaction network analysis and classification using high-dimensional sparse omics data.

PubMed

Ji, Jiadong; He, Di; Feng, Yang; He, Yong; Xue, Fuzhong; Xie, Lei

2017-10-01

A complex disease is usually driven by a number of genes interwoven into networks, rather than a single gene product. Network comparison or differential network analysis has become an important means of revealing the underlying mechanism of pathogenesis and identifying clinical biomarkers for disease classification. Most studies, however, are limited to network correlations that mainly capture the linear relationship among genes, or rely on the assumption of a parametric probability distribution of gene measurements. They are restrictive in real application. We propose a new Joint density based non-parametric Differential Interaction Network Analysis and Classification (JDINAC) method to identify differential interaction patterns of network activation between two groups. At the same time, JDINAC uses the network biomarkers to build a classification model. The novelty of JDINAC lies in its potential to capture non-linear relations between molecular interactions using high-dimensional sparse data as well as to adjust confounding factors, without the need of the assumption of a parametric probability distribution of gene measurements. Simulation studies demonstrate that JDINAC provides more accurate differential network estimation and lower classification error than that achieved by other state-of-the-art methods. We apply JDINAC to a Breast Invasive Carcinoma dataset, which includes 114 patients who have both tumor and matched normal samples. The hub genes and differential interaction patterns identified were consistent with existing experimental studies. Furthermore, JDINAC discriminated the tumor and normal sample with high accuracy by virtue of the identified biomarkers. JDINAC provides a general framework for feature selection and classification using high-dimensional sparse omics data. R scripts available at https://github.com/jijiadong/JDINAC. lxie@iscb.org. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

English and Chinese languages as weighted complex networks

NASA Astrophysics Data System (ADS)

Sheng, Long; Li, Chunguang

2009-06-01

In this paper, we analyze statistical properties of English and Chinese written human language within the framework of weighted complex networks. The two language networks are based on an English novel and a Chinese biography, respectively, and both of the networks are constructed in the same way. By comparing the intensity and density of connections between the two networks, we find that high weight connections in Chinese language networks prevail more than those in English language networks. Furthermore, some of the topological and weighted quantities are compared. The results display some differences in the structural organizations between the two language networks. These observations indicate that the two languages may have different linguistic mechanisms and different combinatorial natures.

Network collaboration of organisations for homeless individuals in the Montreal region

PubMed Central

Fleury, Marie-Josée; Grenier, Guy; Lesage, Alain; Ma, Nan; Ngui, André Ngamini

2014-01-01

Introduction We know little about the intensity and determinants of interorganisational collaboration within the homeless network. This study describes the characteristics and relationships (along with the variables predicting their degree of interorganisational collaboration) of 68 organisations of such a network in Montreal (Quebec, Canada). Theory and methods Data were collected primarily through a self-administered questionnaire. Descriptive analyses were conducted followed by social network and multivariate analyses. Results The Montreal homeless network has a high density (50.5%) and a decentralised structure and maintains a mostly informal collaboration with the public and cross-sectorial sectors. The network density showed more frequent contacts among four types of organisations which could point to the existence of cliques. Four variables predicted interorganisational collaboration: organisation type, number of services offered, volume of referrals and satisfaction with the relationships with public organisations. Conclusions and discussion The Montreal homeless network seems adequate to address non-complex homelessness problems. Considering, however, that most homeless individuals present chronic and complex profiles, it appears necessary to have a more formal and better integrated network of homeless organisations, particularly in the health and social service sectors, in order to improve services. PMID:24520216

High-density interconnect substrates and device packaging using conductive composites

NASA Astrophysics Data System (ADS)

Gandhi, Pradeep; Gallagher, Catherine; Matijasevic, Goran

1998-02-01

High-end printed circuit board manufacturing technology is receiving increasing attention due to higher functionality in smaller form factors. This is evident from the industry efforts to produced reliable microvias and related trace features to pack as much circuit density as possible. Cost, density and performance requirements have prodded entry into a market that was mainly reserved for ceramic and molded packages for the last forty years. To successfully meet the demanding specifications of this market segment, a worldwide effort is underway for the development of new materials, processes and equipment. A novel base technology that is applicable to most of the major packaging and redistribution elements in an electronic module is presented.High density multilayer circuits with landless blind and buried vias can be fabricated by filling the conductor paste into photoimaged dielectrics and thermally processing it at a relatively lower temperature. Via layers are prepared directly on the inherently planarized circuit layer in an identical fashion. Because these composite materials are applied in an additive fabrication method, metal substrates can be employed for high thermal dissipation and excellent CTE control over a wide temperature range. The conductor material is based on interpenetrating polymer and metal networks that are formed in situ from metal particles and a thermosetting flux/binder. The metal network is formed when the alloy particles melt and react with adjacent high melting point metal particle. Interaction also occurs between the alloy particles and pad, lead or previous trace metallizations provided they are solderable by alloys of tin. The new alloy composition created by the interdiffusion process within the bulk material has a higher melting point than the original alloy and thus solidifies immediately upon formation. This metallurgical reaction, known as transient liquid phase sintering, is facilitated by the polymer mixture. INtegration of the polymer and metal networks is maintained by utilizing a thermosetting polymer system that cures simultaneously with the metallurgical reaction. Although similar in concept and performance to cermet inks, these compositions differ in that their process temperatures are compatible with conventional printed wiring board materials and that the polymeric binder remains to provide adhesion and fatigue resistance to the metallurgical network.

Growing Carbon Nanotubes

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

None

In situ transmission electron microscope (TEM) video (accelerated 10 times) of nucleation and self-organization of a high-density carbon nanotube network from catalytic iron nanoparticles, forming a vertically aligned forest.

Functional Organization of the Action Observation Network in Autism: A Graph Theory Approach

PubMed Central

Alaerts, Kaat; Geerlings, Franca; Herremans, Lynn; Swinnen, Stephan P.; Verhoeven, Judith; Sunaert, Stefan; Wenderoth, Nicole

2015-01-01

Background The ability to recognize, understand and interpret other’s actions and emotions has been linked to the mirror system or action-observation-network (AON). Although variations in these abilities are prevalent in the neuro-typical population, persons diagnosed with autism spectrum disorders (ASD) have deficits in the social domain and exhibit alterations in this neural network. Method Here, we examined functional network properties of the AON using graph theory measures and region-to-region functional connectivity analyses of resting-state fMRI-data from adolescents and young adults with ASD and typical controls (TC). Results Overall, our graph theory analyses provided convergent evidence that the network integrity of the AON is altered in ASD, and that reductions in network efficiency relate to reductions in overall network density (i.e., decreased overall connection strength). Compared to TC, individuals with ASD showed significant reductions in network efficiency and increased shortest path lengths and centrality. Importantly, when adjusting for overall differences in network density between ASD and TC groups, participants with ASD continued to display reductions in network integrity, suggesting that also network-level organizational properties of the AON are altered in ASD. Conclusion While differences in empirical connectivity contributed to reductions in network integrity, graph theoretical analyses provided indications that also changes in the high-level network organization reduced integrity of the AON. PMID:26317222

Social network effects on post-traumatic stress disorder (PTSD) in female North Korean immigrants.

PubMed

Lee, Byungkyu; Youm, Yoosik

2011-09-01

The goal of this paper is to examine the social network effects on post-traumatic sdress disorder (PTSD) in female North Korean immigrants who entered South Korea in 2007. Specifically, it attempts to verify if the density and composition of networks make a difference after controlling for the network size. A multivariate logistic regression is used to probe the effects of social networks using the North Korean Immigrant Panel data set. Because the data set had only completed its initial survey when this paper was written, the analysis was cross-sectional. The size of the support networks was systematically related to PTSD. Female North Korean immigrants with more supporting ties were less likely to develop PTSD, even after controlling for other risk factors (odds-ratio for one more tie was 0.8). However, once we control for the size of the network, neither the density nor the composition of the networks remains statistically significant. The prevalence of the PTSD among female North Korean immigrants is alarmingly high, and regardless of the characteristics of supporting network members, the size of the supporting networks provides substantial protection. This implies that a simple strategy that focuses on increasing the number of supporting ties will be effective among North Korean immigrants who entered South Korea in recent years.

Shortwave surface radiation network for observing small-scale cloud inhomogeneity fields

NASA Astrophysics Data System (ADS)

Lakshmi Madhavan, Bomidi; Kalisch, John; Macke, Andreas

2016-03-01

As part of the High Definition Clouds and Precipitation for advancing Climate Prediction Observational Prototype Experiment (HOPE), a high-density network of 99 silicon photodiode pyranometers was set up around Jülich (10 km × 12 km area) from April to July 2013 to capture the small-scale variability of cloud-induced radiation fields at the surface. In this paper, we provide the details of this unique setup of the pyranometer network, data processing, quality control, and uncertainty assessment under variable conditions. Some exemplary days with clear, broken cloudy, and overcast skies were explored to assess the spatiotemporal observations from the network along with other collocated radiation and sky imager measurements available during the HOPE period.

5G: rethink mobile communications for 2020+.

PubMed

Chih-Lin, I; Han, Shuangfeng; Xu, Zhikun; Sun, Qi; Pan, Zhengang

2016-03-06

The 5G network is anticipated to meet the challenging requirements of mobile traffic in the 2020s, which are characterized by super high data rate, low latency, high mobility, high energy efficiency and high traffic density. This paper provides an overview of China Mobile's 5G vision and potential solutions. Three key characteristics of 5G are analysed, i.e. super fast, soft and green. The main 5G R&D themes are further elaborated, which include five fundamental rethinkings of the traditional design methodologies. The 5G network design considerations are also discussed, with cloud radio access network, ultra-dense network, software defined network and network function virtualization examined as key potential solutions towards a green and soft 5G network. The paradigm shift to user-centric network operation from the traditional cell-centric operation is also investigated, where the decoupled downlink and uplink, control and data, and adaptive multiple connections provide sufficient means to achieve a user-centric 5G network with 'no more cells'. The software defined air interface is investigated under a uniform framework and can adaptively adapt the parameters to well satisfy various requirements in different 5G scenarios. © 2016 The Author(s).

Carbon nanotube dispersed conductive network for microbial fuel cells

NASA Astrophysics Data System (ADS)

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

2014-08-01

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

Rich club network analysis shows distinct patterns of disruption in frontotemporal dementia and Alzheimer’s disease

PubMed Central

Daianu, Madelaine; Jahanshad, Neda; Villalon-Reina, Julio E.; Mendez, Mario F.; Bartzokis, George; Jimenez, Elvira E.; Joshi, Aditi; Barsuglia, Joseph; Thompson, Paul M.

2015-01-01

Diffusion imaging and brain connectivity analyses can reveal the underlying organizational patterns of the human brain, described as complex networks of densely interlinked regions. Here, we analyzed 1.5-Tesla whole-brain diffusion-weighted images from 64 participants – 15 patients with behavioral variant frontotemporal (bvFTD) dementia, 19 with early-onset Alzheimer’s disease (EOAD), and 30 healthy elderly controls. Based on whole-brain tractography, we reconstructed structural brain connectivity networks to map connections between cortical regions. We examined how bvFTD and EOAD disrupt the weighted ‘rich club’ – a network property where high-degree network nodes are more interconnected than expected by chance. bvFTD disrupts both the nodal and global organization of the network in both low- and high-degree regions of the brain. EOAD targets the global connectivity of the brain, mainly affecting the fiber density of high-degree (highly connected) regions that form the rich club network. These rich club analyses suggest distinct patterns of disruptions among different forms of dementia. PMID:26161050

A high-resolution human contact network for infectious disease transmission

PubMed Central

Salathé, Marcel; Kazandjieva, Maria; Lee, Jung Woo; Levis, Philip; Feldman, Marcus W.; Jones, James H.

2010-01-01

The most frequent infectious diseases in humans—and those with the highest potential for rapid pandemic spread—are usually transmitted via droplets during close proximity interactions (CPIs). Despite the importance of this transmission route, very little is known about the dynamic patterns of CPIs. Using wireless sensor network technology, we obtained high-resolution data of CPIs during a typical day at an American high school, permitting the reconstruction of the social network relevant for infectious disease transmission. At 94% coverage, we collected 762,868 CPIs at a maximal distance of 3 m among 788 individuals. The data revealed a high-density network with typical small-world properties and a relatively homogeneous distribution of both interaction time and interaction partners among subjects. Computer simulations of the spread of an influenza-like disease on the weighted contact graph are in good agreement with absentee data during the most recent influenza season. Analysis of targeted immunization strategies suggested that contact network data are required to design strategies that are significantly more effective than random immunization. Immunization strategies based on contact network data were most effective at high vaccination coverage. PMID:21149721

Tailoring chain length and cross-link density in dielectric elastomer toward enhanced actuation strain

NASA Astrophysics Data System (ADS)

Zhang, Quan-Ping; Liu, Jun-Hua; Liu, Hai-Dong; Jia, Fei; Zhou, Yuan-Lin; Zheng, Jian

2017-10-01

Adding ceramic or conductive fillers into polymers for increasing permittivity is a direct and effective approach to enhance the actuation strain of dielectric elastomer actuators (DEAs). Unfortunately, the major dielectric loss caused by weak interfaces potentially harms the electro-mechanical stability and lifetime of DEAs. Here, we construct a desired macromolecular network with a long chain length and low cross-link density to reduce the elastic modulus of silicone elastomers. Selecting a high molecular weight of polymethylvinylsiloxane and a low dose of the cross-linker leads the soft but tough networks with rich entanglements, poor cross-links, and a low amount of defects. Then, a ductile material with low elastic modulus but high elongation at break is obtained. It accounts for much more excellent actuation strain of Hl in comparison to that of the other silicone elastomers. Importantly, without other fillers, the ultralow dielectric loss, conductivity, and firm networks possibly promote the electro-mechanical stability and lifetime for the DEA application.

Asymmetric simple exclusion process on chains with a shortcut

NASA Astrophysics Data System (ADS)

Bunzarova, Nadezhda; Pesheva, Nina; Brankov, Jordan

2014-03-01

We consider the asymmetric simple exclusion process (TASEP) on an open network consisting of three consecutively coupled macroscopic chain segments with a shortcut between the tail of the first segment and the head of the third one. The model was introduced by Y.-M. Yuan et al. [J. Phys. A 40, 12351 (2007), 10.1088/1751-8113/40/41/006] to describe directed motion of molecular motors along twisted filaments. We report here unexpected results which revise the previous findings in the case of maximum current through the network. Our theoretical analysis, based on the effective rates' approximation, shows that the second (shunted) segment can exist in both low- and high-density phases, as well as in the coexistence (shock) phase. Numerical simulations demonstrate that the last option takes place in finite-size networks with head and tail chains of equal length, provided the injection and ejection rates at their external ends are equal and greater than one-half. Then the local density distribution and the nearest-neighbor correlations in the middle chain correspond to a shock phase with completely delocalized domain wall. Upon moving the shortcut to the head or tail of the network, the density profile takes a shape typical of a high- or low-density phase, respectively. Surprisingly, the main quantitative parameters of that shock phase are governed by a positive root of a cubic equation, the coefficients of which linearly depend on the probability of choosing the shortcut. Alternatively, they can be expressed in a universal way through the shortcut current. The unexpected conclusion is that a shortcut in the bulk of a single lane may create traffic jams.

Differential network as an indicator of osteoporosis with network entropy.

PubMed

Ma, Lili; Du, Hongmei; Chen, Guangdong

2018-07-01

Osteoporosis is a common skeletal disorder characterized by a decrease in bone mass and density. The peak bone mass (PBM) is a significant determinant of osteoporosis. To gain insights into the indicating effect of PBM to osteoporosis, this study focused on characterizing the PBM networks and identifying key genes. One biological data set with 12 monocyte low PBM samples and 11 high PBM samples was derived to construct protein-protein interaction networks (PPINs). Based on clique-merging, module-identification algorithm was used to identify modules from PPINs. The systematic calculation and comparison were performed to test whether the network entropy can discriminate the low PBM network from high PBM network. We constructed 32 destination networks with 66 modules divided from monocyte low and high PBM networks. Among them, network 11 was the only significantly differential one (P<0.05) with 8 nodes and 28 edges. All genes belonged to precursors of osteoclasts, which were related to calcium transport as well as blood monocytes. In conclusion, based on the entropy in PBM PPINs, the differential network appears to be a novel therapeutic indicator for osteoporosis during the bone monocyte progression; these findings are helpful in disclosing the pathogenetic mechanisms of osteoporosis.

VEGF165 Stimulates Vessel Density and Vessel Diameter Differently in Angiogenesis and Lymphangiogenesis

NASA Technical Reports Server (NTRS)

Parsons-Wingerter, Patricia; Radhakrishnan, Krishnan; DiCorleto, Paul E.; Leontiev, Dmitry; Anand-Apte, Bela; Albarran, Brian; Farr, Andrew G.

2005-01-01

Vascular endothelial growth factor-165 (VEGF(sub 165)) stimulated angiogenesis in the quail chorioallantoic membrane (CAM) by vessel expansion from the capillary network. However, lymphangiogenesis was stimulated by the filopodial guidance of tip cells located on blind-ended lymphatic sprouts. As quantified by fractal/generational branching analysis using the computer code VESGEN, vascular density increased maximally at low VEGF concentrations, and vascular diameter increased most at high VEGF concentrations. Increased vascular density and diameter were statistically independent events (r(sub s), -0.06). By fluorescence immunohistochemistry of VEGF receptors VEGFR-1 and VEGFR-2, alpha smooth muscle actin ((alpha) SMA) and a vascular/lymphatic marker, VEGF(sub 165) increased the density and diameter of sprouting lymphatic vessels guided by tip cells (accompanied by the dissociation of lymphatics from blood vessels). Isolated migratory cells expressing (alpha)SMA were recruited to blood vessels, whereas isolated cells expressing VEGFR-2 were recruited primarily to lymphatics. In conclusion, VEGF(sub 165) increased lymphatic vessel density by lymphatic sprouting, but increased blood vessel density by vascular expansion from the capillary network.

Congestion relaxation due to density-dependent junction rules in TASEP network

NASA Astrophysics Data System (ADS)

Tannai, Takahiro; Nishinari, Katsuhiro

2017-09-01

We now consider a small network module of Totally Asymmetric Simple Exclusion Process with branching and aggregation points, and rules of junctions dependent on the densities of segments of the network module. We also focus on the interaction among junctions which are branching and aggregation. The interaction among junctions with density-dependent rules possesses more complexity than those with density-independent rules studied in the previous papers. In conclusion, we confirm the result that density-dependent rules enable vehicles to move more effectively than the density-independent rules.

N-Doped Porous Carbon Nanofibers/Porous Silver Network Hybrid for High-Rate Supercapacitor Electrode.

PubMed

Meng, Qingshi; Qin, Kaiqiang; Ma, Liying; He, Chunnian; Liu, Enzuo; He, Fang; Shi, Chunsheng; Li, Qunying; Li, Jiajun; Zhao, Naiqin

2017-09-13

A three-dimensional cross-linked porous silver network (PSN) is fabricated by silver mirror reaction using polymer foam as the template. The N-doped porous carbon nanofibers (N-PCNFs) are further prepared on PSN by chemical vapor deposition and treated by ammonia gas subsequently. The PSN substrate serving as the inner current collector will improve the electron transport efficiency significantly. The ammonia gas can not only introduce nitrogen doping into PCNFs but also increase the specific surface area of PCNFs at the same time. Because of its large surface area (801 m 2 /g), high electrical conductivity (211 S/cm), and robust structure, the as-constructed N-PCNFs/PSN demonstrates a specific capacitance of 222 F/g at the current density of 100 A/g with a superior rate capability of 90.8% of its initial capacitance ranging from 1 to 100 A/g while applied as the supercapacitor electrode. The symmetric supercapacitor device based on N-PCNFs/PSN displays an energy density of 8.5 W h/kg with power density of 250 W/kg and excellent cycling stability, which attains 103% capacitance retention after 10 000 charge-discharge cycles at a high current density of 20 A/g, which indicates that N-PCNFs/PSN is a promising candidate for supercapacitor electrode materials.

Neuron-Inspired Fe3O4/Conductive Carbon Filament Network for High-Speed and Stable Lithium Storage.

PubMed

Hao, Shu-Meng; Li, Qian-Jie; Qu, Jin; An, Fei; Zhang, Yu-Jiao; Yu, Zhong-Zhen

2018-05-17

Construction of a continuous conductance network with high electron-transfer rate is extremely important for high-performance energy storage. Owing to the highly efficient mass transport and information transmission, neurons are exactly a perfect model for electron transport, inspiring us to design a neuron-like reaction network for high-performance lithium-ion batteries (LIBs) with Fe 3 O 4 as an example. The reactive cores (Fe 3 O 4 ) are protected by carbon shells and linked by carbon filaments, constituting an integrated conductance network. Thus, once the reaction starts, the electrons released from every Fe 3 O 4 cores are capable of being transferred rapidly through the whole network directly to the external circuit, endowing the nanocomposite with tremendous rate performance and ultralong cycle life. After 1000 cycles at current densities as high as 1 and 2 A g -1 , charge capacities of the as-synthesized nanocomposite maintain 971 and 715 mA h g -1 , respectively, much higher than those of reported Fe 3 O 4 -based anode materials. The Fe 3 O 4 -based conductive network provides a new idea for future developments of high-rate-performance LIBs.

Optimal Base Station Density of Dense Network: From the Viewpoint of Interference and Load.

PubMed

Feng, Jianyuan; Feng, Zhiyong

2017-09-11

Network densification is attracting increasing attention recently due to its ability to improve network capacity by spatial reuse and relieve congestion by offloading. However, excessive densification and aggressive offloading can also cause the degradation of network performance due to problems of interference and load. In this paper, with consideration of load issues, we study the optimal base station density that maximizes the throughput of the network. The expected link rate and the utilization ratio of the contention-based channel are derived as the functions of base station density using the Poisson Point Process (PPP) and Markov Chain. They reveal the rules of deployment. Based on these results, we obtain the throughput of the network and indicate the optimal deployment density under different network conditions. Extensive simulations are conducted to validate our analysis and show the substantial performance gain obtained by the proposed deployment scheme. These results can provide guidance for the network densification.

Genetic dissection of seed oil and protein content and identification of networks associated with oil content in Brassica napus.

PubMed

Chao, Hongbo; Wang, Hao; Wang, Xiaodong; Guo, Liangxing; Gu, Jianwei; Zhao, Weiguo; Li, Baojun; Chen, Dengyan; Raboanatahiry, Nadia; Li, Maoteng

2017-04-10

High-density linkage maps can improve the precision of QTL localization. A high-density SNP-based linkage map containing 3207 markers covering 3072.7 cM of the Brassica napus genome was constructed in the KenC-8 × N53-2 (KNDH) population. A total of 67 and 38 QTLs for seed oil and protein content were identified with an average confidence interval of 5.26 and 4.38 cM, which could explain up to 22.24% and 27.48% of the phenotypic variation, respectively. Thirty-eight associated genomic regions from BSA overlapped with and/or narrowed the SOC-QTLs, further confirming the QTL mapping results based on the high-density linkage map. Potential candidates related to acyl-lipid and seed storage underlying SOC and SPC, respectively, were identified and analyzed, among which six were checked and showed expression differences between the two parents during different embryonic developmental periods. A large primary carbohydrate pathway based on potential candidates underlying SOC- and SPC-QTLs, and interaction networks based on potential candidates underlying SOC-QTLs, was constructed to dissect the complex mechanism based on metabolic and gene regulatory features, respectively. Accurate QTL mapping and potential candidates identified based on high-density linkage map and BSA analyses provide new insights into the complex genetic mechanism of oil and protein accumulation in the seeds of rapeseed.

How the initial level of visibility and limited resource affect the evolution of cooperation

NASA Astrophysics Data System (ADS)

Han, Dun; Li, Dandan; Sun, Mei

2016-06-01

This work sheds important light on how the initial level of visibility and limited resource might affect the evolution of the players’ strategies under different network structure. We perform the prisoner’s dilemma game in the lattice network and the scale-free network, the simulation results indicate that the average density of death in lattice network decreases with the increases of the initial proportion of visibility. However, the contrary phenomenon is observed in the scale-free network. Further results reflect that the individuals’ payoff in lattice network is significantly larger than the one in the scale-free network. In the lattice network, the visibility individuals could earn much more than the invisibility one. However, the difference is not apparent in the scale-free network. We also find that a high Successful-Defection-Payoff (SDB) and a rich natural environment have relatively larger deleterious cooperation effects. A high SDB is beneficial to raising the level of visibility in the heterogeneous network, however, that has adverse visibility consequences in homogeneous network. Our result reveals that players are more likely to cooperate voluntarily under homogeneous network structure.

The effects of working memory training on functional brain network efficiency.

PubMed

Langer, Nicolas; von Bastian, Claudia C; Wirz, Helen; Oberauer, Klaus; Jäncke, Lutz

2013-10-01

The human brain is a highly interconnected network. Recent studies have shown that the functional and anatomical features of this network are organized in an efficient small-world manner that confers high efficiency of information processing at relatively low connection cost. However, it has been unclear how the architecture of functional brain networks is related to performance in working memory (WM) tasks and if these networks can be modified by WM training. Therefore, we conducted a double-blind training study enrolling 66 young adults. Half of the subjects practiced three WM tasks and were compared to an active control group practicing three tasks with low WM demand. High-density resting-state electroencephalography (EEG) was recorded before and after training to analyze graph-theoretical functional network characteristics at an intracortical level. WM performance was uniquely correlated with power in the theta frequency, and theta power was increased by WM training. Moreover, the better a person's WM performance, the more their network exhibited small-world topology. WM training shifted network characteristics in the direction of high performers, showing increased small-worldness within a distributed fronto-parietal network. Taken together, this is the first longitudinal study that provides evidence for the plasticity of the functional brain network underlying WM. Copyright © 2013 Elsevier Ltd. All rights reserved.

Polymer-Based Dense Fluidic Networks for High Throughput Screening with Ultrasensitive Fluorescence Detection

PubMed Central

Okagbare, Paul I.; Soper, Steven A.

2011-01-01

Microfluidics represents a viable platform for performing High Throughput Screening (HTS) due to its ability to automate fluid handling and generate fluidic networks with high number densities over small footprints appropriate for the simultaneous optical interrogation of many screening assays. While most HTS campaigns depend on fluorescence, readers typically use point detection and serially address the assay results significantly lowering throughput or detection sensitivity due to a low duty cycle. To address this challenge, we present here the fabrication of a high density microfluidic network packed into the imaging area of a large field-of-view (FoV) ultrasensitive fluorescence detection system. The fluidic channels were 1, 5 or 10 μm (width), 1 μm (depth) with a pitch of 1–10 μm and each fluidic processor was individually addressable. The fluidic chip was produced from a molding tool using hot embossing and thermal fusion bonding to enclose the fluidic channels. A 40X microscope objective (numerical aperture = 0.75) created a FoV of 200 μm, providing the ability to interrogate ~25 channels using the current fluidic configuration. An ultrasensitive fluorescence detection system with a large FoV was used to transduce fluorescence signals simultaneously from each fluidic processor onto the active area of an electron multiplying charge-coupled device (EMCCD). The utility of these multichannel networks for HTS was demonstrated by carrying out the high throughput monitoring of the activity of an enzyme, APE1, used as a model screening assay. PMID:20872611

Neurobiological changes of schizotypy: evidence from both volume-based morphometric analysis and resting-state functional connectivity.

PubMed

Wang, Yi; Yan, Chao; Yin, Da-zhi; Fan, Ming-xia; Cheung, Eric F C; Pantelis, Christos; Chan, Raymond C K

2015-03-01

The current study sought to examine the underlying brain changes in individuals with high schizotypy by integrating networks derived from brain structural and functional imaging. Individuals with high schizotypy (n = 35) and low schizotypy (n = 34) controls were screened using the Schizotypal Personality Questionnaire and underwent brain structural and resting-state functional magnetic resonance imaging on a 3T scanner. Voxel-based morphometric analysis and graph theory-based functional network analysis were conducted. Individuals with high schizotypy showed reduced gray matter (GM) density in the insula and the dorsolateral prefrontal gyrus. The graph theoretical analysis showed that individuals with high schizotypy showed similar global properties in their functional networks as low schizotypy individuals. Several hubs of the functional network were identified in both groups, including the insula, the lingual gyrus, the postcentral gyrus, and the rolandic operculum. More hubs in the frontal lobe and fewer hubs in the occipital lobe were identified in individuals with high schizotypy. By comparing the functional connectivity between clusters with abnormal GM density and the whole brain, individuals with high schizotypy showed weaker functional connectivity between the left insula and the putamen, but stronger connectivity between the cerebellum and the medial frontal gyrus. Taken together, our findings suggest that individuals with high schizotypy present changes in terms of GM and resting-state functional connectivity, especially in the frontal lobe. © The Author 2014. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Encoding Hydrogel Mechanics via Network Cross-Linking Structure.

PubMed

Schweller, Ryan M; West, Jennifer L

2015-05-11

The effects of mechanical cues on cell behaviors in 3D remain difficult to characterize as the ability to tune hydrogel mechanics often requires changes in the polymer density, potentially altering the material's biochemical and physical characteristics. Additionally, with most PEG diacrylate (PEGDA) hydrogels, forming materials with compressive moduli less than ∼10 kPa has been virtually impossible. Here, we present a new method of controlling the mechanical properties of PEGDA hydrogels independent of polymer chain density through the incorporation of additional vinyl group moieties that interfere with the cross-linking of the network. This modification can tune hydrogel mechanics in a concentration dependent manner from <1 to 17 kPa, a more physiologically relevant range than previously possible with PEG-based hydrogels, without altering the hydrogel's degradation and permeability. Across this range of mechanical properties, endothelial cells (ECs) encapsulated within MMP-2/MMP-9 degradable hydrogels with RGDS adhesive peptides revealed increased cell spreading as hydrogel stiffness decreased in contrast to behavior typically observed for cells on 2D surfaces. EC-pericyte cocultures exhibited vessel-like networks within 3 days in highly compliant hydrogels as compared to a week in stiffer hydrogels. These vessel networks persisted for at least 4 weeks and deposited laminin and collagen IV perivascularly. These results indicate that EC morphogenesis can be regulated using mechanical cues in 3D. Furthermore, controlling hydrogel compliance independent of density allows for the attainment of highly compliant mechanical regimes in materials that can act as customizable cell microenvironments.

Nanoionics and Nanocatalysts: Conformal Mesoporous Surface Scaffold for Cathode of Solid Oxide Fuel Cells

PubMed Central

Chen, Yun; Gerdes, Kirk; Song, Xueyan

2016-01-01

Nanoionics has become increasingly important in devices and systems related to energy conversion and storage. Nevertheless, nanoionics and nanostructured electrodes development has been challenging for solid oxide fuel cells (SOFCs) owing to many reasons including poor stability of the nanocrystals during fabrication of SOFCs at elevated temperatures. In this study, a conformal mesoporous ZrO2 nanoionic network was formed on the surface of La1−xSrxMnO3/yttria-stabilized zirconia (LSM/YSZ) cathode backbone using Atomic Layer Deposition (ALD) and thermal treatment. The surface layer nanoionic network possesses open mesopores for gas penetration, and features a high density of grain boundaries for enhanced ion-transport. The mesoporous nanoionic network is remarkably stable and retains the same morphology after electrochemical operation at high temperatures of 650–800 °C for 400 hours. The stable mesoporous ZrO2 nanoionic network is further utilized to anchor catalytic Pt nanocrystals and create a nanocomposite that is stable at elevated temperatures. The power density of the ALD modified and inherently functional commercial cells exhibited enhancement by a factor of 1.5–1.7 operated at 0.8 V at 750 °C. PMID:27605121

Adaptive lyapunov control and artificial neural networks for spacecraft relative maneuvering using atmospheric differential drag

NASA Astrophysics Data System (ADS)

Perez Chaparro, David Andres

At low Earth orbits, a differential in the drag acceleration between spacecraft can be used to control their relative motion. This drag differential allows for a propellant-free alternative to thrusters for performing relative maneuvers in these orbits. The interest in autonomous propellant-less maneuvering comes from the desire to reduce the costs of spacecraft formations. Formation maneuvering opens up a wide variety of new applications for spacecraft missions, such as on-orbit maintenance and refueling. In this work atmospheric differential drag based nonlinear controllers are presented that can be used for virtually any planar relative maneuver of two spacecraft, provided that there is enough atmospheric density and that the spacecraft can change their ballistic coefficients by sufficient amounts to generate the necessary differential accelerations. The control techniques are successfully tested using high fidelity Satellite Tool Kit simulations for re-phase, fly-around, and rendezvous maneuvers, proving the feasibility of the proposed approach for a real flight. Furthermore, the atmospheric density varies in time and in space as the spacecraft travel along their orbits. The ability to accurately forecast the density allows for accurate onboard orbit propagation and for creating realistic guidance trajectories for maneuvers that rely on the differential drag. In this work a localized density predictor based on artificial neural networks is also presented. The predictor uses density measurements or estimates along the past orbits and can use a set of proxies for solar and geomagnetic activities to predict the value of the density along the future orbits of the spacecraft. The performance of the localized predictor is studied for different neural network structures, testing periods of high and low solar and geomagnetic activities and different prediction windows. Comparison with previously developed methods show substantial benefits in using neural networks, both in prediction accuracy and in the potential for spacecraft onboard implementation. The controllers and the predictor are designed for onboard implementation, and provide spacecraft with the tools necessary for performing propellant-less formation maneuvers using differential drag.

MINE: Module Identification in Networks

PubMed Central

2011-01-01

Background Graphical models of network associations are useful for both visualizing and integrating multiple types of association data. Identifying modules, or groups of functionally related gene products, is an important challenge in analyzing biological networks. However, existing tools to identify modules are insufficient when applied to dense networks of experimentally derived interaction data. To address this problem, we have developed an agglomerative clustering method that is able to identify highly modular sets of gene products within highly interconnected molecular interaction networks. Results MINE outperforms MCODE, CFinder, NEMO, SPICi, and MCL in identifying non-exclusive, high modularity clusters when applied to the C. elegans protein-protein interaction network. The algorithm generally achieves superior geometric accuracy and modularity for annotated functional categories. In comparison with the most closely related algorithm, MCODE, the top clusters identified by MINE are consistently of higher density and MINE is less likely to designate overlapping modules as a single unit. MINE offers a high level of granularity with a small number of adjustable parameters, enabling users to fine-tune cluster results for input networks with differing topological properties. Conclusions MINE was created in response to the challenge of discovering high quality modules of gene products within highly interconnected biological networks. The algorithm allows a high degree of flexibility and user-customisation of results with few adjustable parameters. MINE outperforms several popular clustering algorithms in identifying modules with high modularity and obtains good overall recall and precision of functional annotations in protein-protein interaction networks from both S. cerevisiae and C. elegans. PMID:21605434

Nitrogen-Superdoped 3D Graphene Networks for High-Performance Supercapacitors.

PubMed

Zhang, Weili; Xu, Chuan; Ma, Chaoqun; Li, Guoxian; Wang, Yuzuo; Zhang, Kaiyu; Li, Feng; Liu, Chang; Cheng, Hui-Ming; Du, Youwei; Tang, Nujiang; Ren, Wencai

2017-09-01

An N-superdoped 3D graphene network structure with an N-doping level up to 15.8 at% for high-performance supercapacitor is designed and synthesized, in which the graphene foam with high conductivity acts as skeleton and nested with N-superdoped reduced graphene oxide arogels. This material shows a highly conductive interconnected 3D porous structure (3.33 S cm -1 ), large surface area (583 m 2 g -1 ), low internal resistance (0.4 Ω), good wettability, and a great number of active sites. Because of the multiple synergistic effects of these features, the supercapacitors based on this material show a remarkably excellent electrochemical behavior with a high specific capacitance (of up to 380, 332, and 245 F g -1 in alkaline, acidic, and neutral electrolytes measured in three-electrode configuration, respectively, 297 F g -1 in alkaline electrolytes measured in two-electrode configuration), good rate capability, excellent cycling stability (93.5% retention after 4600 cycles), and low internal resistance (0.4 Ω), resulting in high power density with proper high energy density. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Facile synthesis of a mesoporous Co3O4 network for Li-storage via thermal decomposition of an amorphous metal complex.

PubMed

Wen, Wei; Wu, Jin-Ming; Cao, Min-Hua

2014-11-07

A facile strategy is developed for mass fabrication of porous Co3O4 networks via the thermal decomposition of an amorphous cobalt-based complex. At a low mass loading, the achieved porous Co3O4 network exhibits excellent performance for lithium storage, which has a high capacity of 587 mA h g(-1) after 500 cycles at a current density of 1000 mA g(-1).

Scaling properties of multitension domain wall networks

NASA Astrophysics Data System (ADS)

Oliveira, M. F.; Martins, C. J. A. P.

2015-02-01

We study the asymptotic scaling properties of domain wall networks with three different tensions in various cosmological epochs. We discuss the conditions under which a scale-invariant evolution of the network (which is well established for simpler walls) still applies and also consider the limiting case where defects are locally planar and the curvature is concentrated in the junctions. We present detailed quantitative predictions for scaling densities in various contexts, which should be testable by means of future high-resolution numerical simulations.

Cortical network architecture for context processing in primate brain

PubMed Central

Chao, Zenas C; Nagasaka, Yasuo; Fujii, Naotaka

2015-01-01

Context is information linked to a situation that can guide behavior. In the brain, context is encoded by sensory processing and can later be retrieved from memory. How context is communicated within the cortical network in sensory and mnemonic forms is unknown due to the lack of methods for high-resolution, brain-wide neuronal recording and analysis. Here, we report the comprehensive architecture of a cortical network for context processing. Using hemisphere-wide, high-density electrocorticography, we measured large-scale neuronal activity from monkeys observing videos of agents interacting in situations with different contexts. We extracted five context-related network structures including a bottom-up network during encoding and, seconds later, cue-dependent retrieval of the same network with the opposite top-down connectivity. These findings show that context is represented in the cortical network as distributed communication structures with dynamic information flows. This study provides a general methodology for recording and analyzing cortical network neuronal communication during cognition. DOI: http://dx.doi.org/10.7554/eLife.06121.001 PMID:26416139

The role of geographic and network factors in racial disparities in HIV among young men who have sex with men: An egocentric network study

PubMed Central

Mustanski, Brian; Birkett, Michelle; Kuhns, Lisa M.; Latkin, Carl A.; Muth, Stephen Q.

2014-01-01

The objective of this study was to characterize and compare individual and sexual network characteristics of Black, White, and Latino YMSM as potential drivers of racial disparities in HIV. Egocentric network interviews were conducted with 175 diverse YMSM who described 837 sex partners within 167 sexual-active egos. Sexual partner alter attributes were summarized by ego. Descriptives of ego demographics, sexual partner demographics, and network characteristics were calculated by race of the ego and compared. No racial differences were found in individual engagement in HIV risk behaviors or concurrent sexual partnership. Racial differences were found in partner characteristics, including female gender, non-gay sexual orientations, older age, and residence in a high HIV prevalence neighborhood. Racial differences in relationship characteristics included type of relationships (i.e., main partner) and strength of relationships. Network characteristics also showed differences, including sexual network density and assortativity by race. Most racial differences were in the direction of effects that would tend to increase HIV incidence among Black YMSM. These data suggest that racial disparities in HIV may be driven and/or maintained by a combination of racial differences in partner characteristics, assortativity by race, and increased sexual network density, rather than differences in individual’s HIV risk behaviors. PMID:25430501

Social Network Effects on Post-Traumatic Stress Disorder (PTSD) in Female North Korean Immigrants

PubMed Central

Lee, Byungkyu

2011-01-01

Objectives The goal of this paper is to examine the social network effects on post-traumatic sdress disorder (PTSD) in female North Korean immigrants who entered South Korea in 2007. Specifically, it attempts to verify if the density and composition of networks make a difference after controlling for the network size. Methods A multivariate logistic regression is used to probe the effects of social networks using the North Korean Immigrant Panel data set. Because the data set had only completed its initial survey when this paper was written, the analysis was cross-sectional. Results The size of the support networks was systematically related to PTSD. Female North Korean immigrants with more supporting ties were less likely to develop PTSD, even after controlling for other risk factors (odds-ratio for one more tie was 0.8). However, once we control for the size of the network, neither the density nor the composition of the networks remains statistically significant. Conclusions The prevalence of the PTSD among female North Korean immigrants is alarmingly high, and regardless of the characteristics of supporting network members, the size of the supporting networks provides substantial protection. This implies that a simple strategy that focuses on increasing the number of supporting ties will be effective among North Korean immigrants who entered South Korea in recent years. PMID:22020184

Large Scale Data Analysis and Knowledge Extraction in Communication Data

DTIC Science & Technology

2017-03-31

this purpose, we developed a novel method the " Correlation Density Ran!C’ which finds probability density distribution of related frequent event on all...which is called " Correlation Density Rank", is developed to derive the community tree from the network. As in the real world, where a network is...Community Structure in Dynamic Social Networks using the Correlation Density Rank," 2014 ASE BigData/SocialCom/Cybersecurity Conference, Stanford

High-Density, High-Resolution, Low-Cost Air Quality Sensor Networks for Urban Air Monitoring

NASA Astrophysics Data System (ADS)

Mead, M. I.; Popoola, O. A.; Stewart, G.; Bright, V.; Kaye, P.; Saffell, J.

2012-12-01

Monitoring air quality in highly granular environments such as urban areas which are spatially heterogeneous with variable emission sources, measurements need to be made at appropriate spatial and temporal scales. Current routine air quality monitoring networks generally are either composed of sparse expensive installations (incorporating e.g. chemiluminescence instruments) or higher density low time resolution systems (e.g. NO2 diffusion tubes). Either approach may not accurately capture important effects such as pollutant "hot spots" or adequately capture spatial (or temporal) variability. As a result, analysis based on data from traditional low spatial resolution networks, such as personal exposure, may be inaccurate. In this paper we present details of a sophisticated, low-cost, multi species (gas phase, speciated PM, meteorology) air quality measurement network methodology incorporating GPS and GPRS which has been developed for high resolution air quality measurements in urban areas. Sensor networks developed in the Centre for Atmospheric Science (University of Cambridge) incorporated electrochemical gas sensors configured for use in urban air quality studies operating at parts-per-billion (ppb) levels. It has been demonstrated that these sensors can be used to measure key air quality gases such as CO, NO and NO2 at the low ppb mixing ratios present in the urban environment (estimated detection limits <4ppb for CO and NO and <1ppb for NO2. Mead et al (submitted Aug., 2012)). Based on this work, a state of the art multi species instrument package for deployment in scalable sensor networks has been developed which has general applicability. This is currently being employed as part of a major 3 year UK program at London Heathrow airport (the Sensor Networks for Air Quality (SNAQ) Heathrow project). The main project outcome is the creation of a calibrated, high spatial and temporal resolution data set for O3, NO, NO2, SO2, CO, CO2, VOCstotal, size-speciated PM, temperature, relative humidity, wind speed and direction. The network incorporates existing GPRS infrastructures for real time sending of data with low overheads in terms of cost, effort and installation. In this paper we present data from the SNAQ Heathrow project as well as previous deployments showing measurement capability at the ppb level for NO, NO2 and CO. We show that variability can be observed and measured quantitatively using these sensor networks over widely differing time scales from individual emission events, diurnal variability associated with traffic and meteorological conditions, through to longer term synoptic weather conditions and seasonal behaviour. This work demonstrates a widely applicable generic capability to urban areas, airports as well as other complex emissions environments making this sensor system methodology valuable for scientific, policy and regulatory issues. We conclude that the low-cost high-density network philosophy has the potential to provide a more complete assessment of the high-granularity air quality structure generally observed in the environment. Further, when appropriately deployed, has the potential to offer a new paradigm in air quality quantification and monitoring.

Morphology and linear-elastic moduli of random network solids.

PubMed

Nachtrab, Susan; Kapfer, Sebastian C; Arns, Christoph H; Madadi, Mahyar; Mecke, Klaus; Schröder-Turk, Gerd E

2011-06-17

The effective linear-elastic moduli of disordered network solids are analyzed by voxel-based finite element calculations. We analyze network solids given by Poisson-Voronoi processes and by the structure of collagen fiber networks imaged by confocal microscopy. The solid volume fraction ϕ is varied by adjusting the fiber radius, while keeping the structural mesh or pore size of the underlying network fixed. For intermediate ϕ, the bulk and shear modulus are approximated by empirical power-laws K(phi)proptophin and G(phi)proptophim with n≈1.4 and m≈1.7. The exponents for the collagen and the Poisson-Voronoi network solids are similar, and are close to the values n=1.22 and m=2.11 found in a previous voxel-based finite element study of Poisson-Voronoi systems with different boundary conditions. However, the exponents of these empirical power-laws are at odds with the analytic values of n=1 and m=2, valid for low-density cellular structures in the limit of thin beams. We propose a functional form for K(ϕ) that models the cross-over from a power-law at low densities to a porous solid at high densities; a fit of the data to this functional form yields the asymptotic exponent n≈1.00, as expected. Further, both the intensity of the Poisson-Voronoi process and the collagen concentration in the samples, both of which alter the typical pore or mesh size, affect the effective moduli only by the resulting change of the solid volume fraction. These findings suggest that a network solid with the structure of the collagen networks can be modeled in quantitative agreement by a Poisson-Voronoi process. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Big data driven cycle time parallel prediction for production planning in wafer manufacturing

NASA Astrophysics Data System (ADS)

Wang, Junliang; Yang, Jungang; Zhang, Jie; Wang, Xiaoxi; Zhang, Wenjun Chris

2018-07-01

Cycle time forecasting (CTF) is one of the most crucial issues for production planning to keep high delivery reliability in semiconductor wafer fabrication systems (SWFS). This paper proposes a novel data-intensive cycle time (CT) prediction system with parallel computing to rapidly forecast the CT of wafer lots with large datasets. First, a density peak based radial basis function network (DP-RBFN) is designed to forecast the CT with the diverse and agglomerative CT data. Second, the network learning method based on a clustering technique is proposed to determine the density peak. Third, a parallel computing approach for network training is proposed in order to speed up the training process with large scaled CT data. Finally, an experiment with respect to SWFS is presented, which demonstrates that the proposed CTF system can not only speed up the training process of the model but also outperform the radial basis function network, the back-propagation-network and multivariate regression methodology based CTF methods in terms of the mean absolute deviation and standard deviation.

Coverage maximization under resource constraints using a nonuniform proliferating random walk.

PubMed

Saha, Sudipta; Ganguly, Niloy

2013-02-01

Information management services on networks, such as search and dissemination, play a key role in any large-scale distributed system. One of the most desirable features of these services is the maximization of the coverage, i.e., the number of distinctly visited nodes under constraints of network resources as well as time. However, redundant visits of nodes by different message packets (modeled, e.g., as walkers) initiated by the underlying algorithms for these services cause wastage of network resources. In this work, using results from analytical studies done in the past on a K-random-walk-based algorithm, we identify that redundancy quickly increases with an increase in the density of the walkers. Based on this postulate, we design a very simple distributed algorithm which dynamically estimates the density of the walkers and thereby carefully proliferates walkers in sparse regions. We use extensive computer simulations to test our algorithm in various kinds of network topologies whereby we find it to be performing particularly well in networks that are highly clustered as well as sparse.

Understanding network concepts in modules

PubMed Central

2007-01-01

Background Network concepts are increasingly used in biology and genetics. For example, the clustering coefficient has been used to understand network architecture; the connectivity (also known as degree) has been used to screen for cancer targets; and the topological overlap matrix has been used to define modules and to annotate genes. Dozens of potentially useful network concepts are known from graph theory. Results Here we study network concepts in special types of networks, which we refer to as approximately factorizable networks. In these networks, the pairwise connection strength (adjacency) between 2 network nodes can be factored into node specific contributions, named node 'conformity'. The node conformity turns out to be highly related to the connectivity. To provide a formalism for relating network concepts to each other, we define three types of network concepts: fundamental-, conformity-based-, and approximate conformity-based concepts. Fundamental concepts include the standard definitions of connectivity, density, centralization, heterogeneity, clustering coefficient, and topological overlap. The approximate conformity-based analogs of fundamental network concepts have several theoretical advantages. First, they allow one to derive simple relationships between seemingly disparate networks concepts. For example, we derive simple relationships between the clustering coefficient, the heterogeneity, the density, the centralization, and the topological overlap. The second advantage of approximate conformity-based network concepts is that they allow one to show that fundamental network concepts can be approximated by simple functions of the connectivity in module networks. Conclusion Using protein-protein interaction, gene co-expression, and simulated data, we show that a) many networks comprised of module nodes are approximately factorizable and b) in these types of networks, simple relationships exist between seemingly disparate network concepts. Our results are implemented in freely available R software code, which can be downloaded from the following webpage: http://www.genetics.ucla.edu/labs/horvath/ModuleConformity/ModuleNetworks PMID:17547772

Protocol Independent Adaptive Route Update for VANET

PubMed Central

Rasheed, Asim; Qayyum, Amir

2014-01-01

High relative node velocity and high active node density have presented challenges to existing routing approaches within highly scaled ad hoc wireless networks, such as Vehicular Ad hoc Networks (VANET). Efficient routing requires finding optimum route with minimum delay, updating it on availability of a better one, and repairing it on link breakages. Current routing protocols are generally focused on finding and maintaining an efficient route, with very less emphasis on route update. Adaptive route update usually becomes impractical for dense networks due to large routing overheads. This paper presents an adaptive route update approach which can provide solution for any baseline routing protocol. The proposed adaptation eliminates the classification of reactive and proactive by categorizing them as logical conditions to find and update the route. PMID:24723807

Interpenetrating polymer networks from acetylene terminated materials

NASA Technical Reports Server (NTRS)

Connell, J. W.; Hergenrother, P. M.

1989-01-01

As part of a program to develop high temperature/high performance structural resins for aerospace applications, the chemistry and properties of a novel class of interpenetrating polymer networks (IPNs) were investigated. These IPNs consist of a simple diacetylenic compound (aspartimide) blended with an acetylene terminated arylene ether oligomer. Various compositional blends were prepared and thermally cured to evaluate the effect of crosslink density on resin properties. The cured IPNs exhibited glass transition temperatures ranging from 197 to 254 C depending upon the composition and cure temperature. The solvent resistance, fracture toughness and coefficient of thermal expansion of the cured blends were related to the crosslink density. Isothermal aging of neat resin moldings, adhesive and composite specimens showed a postcure effect which resulted in improved elevated temperature properties. The chemistry, physical and mechanical properties of these materials will be discussed.

A Recurrent Probabilistic Neural Network with Dimensionality Reduction Based on Time-series Discriminant Component Analysis.

PubMed

Hayashi, Hideaki; Shibanoki, Taro; Shima, Keisuke; Kurita, Yuichi; Tsuji, Toshio

2015-12-01

This paper proposes a probabilistic neural network (NN) developed on the basis of time-series discriminant component analysis (TSDCA) that can be used to classify high-dimensional time-series patterns. TSDCA involves the compression of high-dimensional time series into a lower dimensional space using a set of orthogonal transformations and the calculation of posterior probabilities based on a continuous-density hidden Markov model with a Gaussian mixture model expressed in the reduced-dimensional space. The analysis can be incorporated into an NN, which is named a time-series discriminant component network (TSDCN), so that parameters of dimensionality reduction and classification can be obtained simultaneously as network coefficients according to a backpropagation through time-based learning algorithm with the Lagrange multiplier method. The TSDCN is considered to enable high-accuracy classification of high-dimensional time-series patterns and to reduce the computation time taken for network training. The validity of the TSDCN is demonstrated for high-dimensional artificial data and electroencephalogram signals in the experiments conducted during the study.

Development and Application of a Wireless Sensor for Space Charge Density Measurement in an Ultra-High-Voltage, Direct-Current Environment

PubMed Central

Xin, Encheng; Ju, Yong; Yuan, Haiwen

2016-01-01

A space charge density wireless measurement system based on the idea of distributed measurement is proposed for collecting and monitoring the space charge density in an ultra-high-voltage direct-current (UHVDC) environment. The proposed system architecture is composed of a number of wireless nodes connected with space charge density sensors and a base station. The space charge density sensor based on atmospheric ion counter method is elaborated and developed, and the ARM microprocessor and Zigbee radio frequency module are applied. The wireless network communication quality and the relationship between energy consumption and transmission distance in the complicated electromagnetic environment is tested. Based on the experimental results, the proposed measurement system demonstrates that it can adapt to the complex electromagnetic environment under the UHVDC transmission lines and can accurately measure the space charge density. PMID:27775627

Development and Application of a Wireless Sensor for Space Charge Density Measurement in an Ultra-High-Voltage, Direct-Current Environment.

PubMed

Xin, Encheng; Ju, Yong; Yuan, Haiwen

2016-10-20

A space charge density wireless measurement system based on the idea of distributed measurement is proposed for collecting and monitoring the space charge density in an ultra-high-voltage direct-current (UHVDC) environment. The proposed system architecture is composed of a number of wireless nodes connected with space charge density sensors and a base station. The space charge density sensor based on atmospheric ion counter method is elaborated and developed, and the ARM microprocessor and Zigbee radio frequency module are applied. The wireless network communication quality and the relationship between energy consumption and transmission distance in the complicated electromagnetic environment is tested. Based on the experimental results, the proposed measurement system demonstrates that it can adapt to the complex electromagnetic environment under the UHVDC transmission lines and can accurately measure the space charge density.

High-energy supercapacitors based on hierarchical porous carbon with an ultrahigh ion-accessible surface area in ionic liquid electrolytes

NASA Astrophysics Data System (ADS)

Zhong, Hui; Xu, Fei; Li, Zenghui; Fu, Ruowen; Wu, Dingcai

2013-05-01

A very important yet really challenging issue to address is how to greatly increase the energy density of supercapacitors to approach or even exceed those of batteries without sacrificing the power density. Herein we report the fabrication of a new class of ultrahigh surface area hierarchical porous carbon (UHSA-HPC) based on the pore formation and widening of polystyrene-derived HPC by KOH activation, and highlight its superior ability for energy storage in supercapacitors with ionic liquid (IL) as electrolyte. The UHSA-HPC with a surface area of more than 3000 m2 g-1 shows an extremely high energy density, i.e., 118 W h kg-1 at a power density of 100 W kg-1. This is ascribed to its unique hierarchical nanonetwork structure with a large number of small-sized nanopores for IL storage and an ideal meso-/macroporous network for IL transfer.A very important yet really challenging issue to address is how to greatly increase the energy density of supercapacitors to approach or even exceed those of batteries without sacrificing the power density. Herein we report the fabrication of a new class of ultrahigh surface area hierarchical porous carbon (UHSA-HPC) based on the pore formation and widening of polystyrene-derived HPC by KOH activation, and highlight its superior ability for energy storage in supercapacitors with ionic liquid (IL) as electrolyte. The UHSA-HPC with a surface area of more than 3000 m2 g-1 shows an extremely high energy density, i.e., 118 W h kg-1 at a power density of 100 W kg-1. This is ascribed to its unique hierarchical nanonetwork structure with a large number of small-sized nanopores for IL storage and an ideal meso-/macroporous network for IL transfer. Electronic supplementary information (ESI) available: Sample preparation, material characterization, electrochemical characterization and specific mass capacitance and energy density. See DOI: 10.1039/c3nr00738c

Estimating topological properties of weighted networks from limited information

NASA Astrophysics Data System (ADS)

Gabrielli, Andrea; Cimini, Giulio; Garlaschelli, Diego; Squartini, Angelo

A typical problem met when studying complex systems is the limited information available on their topology, which hinders our understanding of their structural and dynamical properties. A paramount example is provided by financial networks, whose data are privacy protected. Yet, the estimation of systemic risk strongly depends on the detailed structure of the interbank network. The resulting challenge is that of using aggregate information to statistically reconstruct a network and correctly predict its higher-order properties. Standard approaches either generate unrealistically dense networks, or fail to reproduce the observed topology by assigning homogeneous link weights. Here we develop a reconstruction method, based on statistical mechanics concepts, that exploits the empirical link density in a highly non-trivial way. Technically, our approach consists in the preliminary estimation of node degrees from empirical node strengths and link density, followed by a maximum-entropy inference based on a combination of empirical strengths and estimated degrees. Our method is successfully tested on the international trade network and the interbank money market, and represents a valuable tool for gaining insights on privacy-protected or partially accessible systems. Acknoweledgement to ``Growthcom'' ICT - EC project (Grant No: 611272) and ``Crisislab'' Italian Project.

Elastic properties and short-range structural order in mixed network former glasses.

PubMed

Wang, Weimin; Christensen, Randilynn; Curtis, Brittany; Hynek, David; Keizer, Sydney; Wang, James; Feller, Steve; Martin, Steve W; Kieffer, John

2017-06-21

Elastic properties of alkali containing glasses are of great interest not only because they provide information about overall structural integrity but also they are related to other properties such as thermal conductivity and ion mobility. In this study, we investigate two mixed-network former glass systems, sodium borosilicate 0.2Na 2 O + 0.8[xBO 1.5 + (1 - x)SiO 2 ] and sodium borogermanate 0.2Na 2 O + 0.8[xBO 1.5 + (1 - x)GeO 2 ] glasses. By mixing network formers, the network topology can be changed while keeping the network modifier concentration constant, which allows for the effect of network structure on elastic properties to be analyzed over a wide parametric range. In addition to non-linear, non-additive mixed-glass former effects, maxima are observed in longitudinal, shear and Young's moduli with increasing atomic number density. By combining results from NMR spectroscopy and Brillouin light scattering with a newly developed statistical thermodynamic reaction equilibrium model, it is possible to determine the relative proportions of all network structural units. This new analysis reveals that the structural characteristic predominantly responsible for effective mechanical load transmission in these glasses is a high density of network cations coordinated by four or more bridging oxygens, as it provides for establishing a network of covalent bonds among these cations with connectivity in three dimensions.

DEVELOPMENT OF THE “RICH CLUB” IN BRAIN CONNECTIVITY NETWORKS FROM 438 ADOLESCENTS & ADULTS AGED 12 TO 30

PubMed Central

Dennis, Emily L.; Jahanshad, Neda; Toga, Arthur W.; McMahon, Katie L.; de Zubicaray, Greig I.; Hickie, Ian; Wright, Margaret J.; Thompson, Paul M.

2014-01-01

The ‘rich club’ coefficient describes a phenomenon where a network's hubs (high-degree nodes) are on average more intensely interconnected than lower-degree nodes. Networks with rich clubs often have an efficient, higher-order organization, but we do not yet know how the rich club emerges in the living brain, or how it changes as our brain networks develop. Here we chart the developmental trajectory of the rich club in anatomical brain networks from 438 subjects aged 12-30. Cortical networks were constructed from 68×68 connectivity matrices of fiber density, using whole-brain tractography in 4-Tesla 105-gradient high angular resolution diffusion images (HARDI). The adult and younger cohorts had rich clubs that included different nodes; the rich club effect intensified with age. Rich-club organization is a sign of a network's efficiency and robustness. These concepts and findings may be advantageous for studying brain maturation and abnormal brain development. PMID:24827471

Spatial mismatch analysis among hotspots of alien plant species, road and railway networks in Germany and Austria

PubMed Central

Morelli, Federico

2017-01-01

Road and railway networks are pervasive elements of all environments, which have expanded intensively over the last century in all European countries. These transportation infrastructures have major impacts on the surrounding landscape, representing a threat to biodiversity. Roadsides and railways may function as corridors for dispersal of alien species in fragmented landscapes. However, only few studies have explored the spread of invasive species in relationship to transport network at large spatial scales. We performed a spatial mismatch analysis, based on a spatially explicit correlation test, to investigate whether alien plant species hotspots in Germany and Austria correspond to areas of high density of roads and railways. We tested this independently of the effects of dominant environments in each spatial unit, in order to focus just on the correlation between occurrence of alien species and density of linear transportation infrastructures. We found a significant spatial association between alien plant species hotspots distribution and roads and railways density in both countries. As expected, anthropogenic landscapes, such as urban areas, harbored more alien plant species, followed by water bodies. However, our findings suggested that the distribution of neobiota is strongest correlated to road/railways density than to land use composition. This study provides new evidence, from a transnational scale, that alien plants can use roadsides and rail networks as colonization corridors. Furthermore, our approach contributes to the understanding on alien plant species distribution at large spatial scale by the combination with spatial modeling procedures. PMID:28829818

Soft- to network hard-material for constructing both ion- and electron-conductive hierarchical porous structure to significantly boost energy density of a supercapacitor.

PubMed

Yang, Pingping; Xie, Jiale; Guo, Chunxian; Li, Chang Ming

2017-01-01

Soft-material PEDOT is used to network hard Co 3 O 4 nanowires for constructing both ion- and electron-conductive hierarchical porous structure Co 3 O 4 /PEDOT to greatly boost the capacitor energy density than sum of that of plain Co 3 O 4 nanowires and PEDOT film. Specifically, the networked hierarchical porous structure of Co 3 O 4 /PEDOT is synthesized and tailored through hydrothermal method and post-electrochemical polymerization method for the PEDOT coating onto Co 3 O 4 nanowires. Typically, Co 3 O 4 /PEDOT supercapacitor gets a highest areal capacitance of 160mFcm -2 at a current density of 0.2mAcm -2 , which is about 2.2 times larger than the sum of that of plain Co 3 O 4 NWs (0.92mFcm -2 ) and PEDOT film (69.88mFcm -2 ). Besides, if only PEDOT as active mass is counted, Co 3 O 4 /PEDOT cell can achieve a highest capacitance of 567.21Fg -1 , this is the highest capacitance value obtained by PEDOT-based supercapacitors. Furthermore, this soft-hard network porous structure also achieves a high cycling stability of 93% capacitance retention after the 20,000th cycle. This work demonstrates a new approach to constructing both ion and electron conductive hierarchical porous structure to significantly boost energy density of a supercapacitor. Copyright © 2016 Elsevier Inc. All rights reserved.

First results from comparison of rainfall estimations by GPM IMERG with rainfall measurements from the WegenerNet high density network

NASA Astrophysics Data System (ADS)

Oo, Sungmin; Foelsche, Ulrich; Kirchengast, Gottfried; Fuchsberger, Jürgen

2016-04-01

The research level products of the Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG "Final" run datasets) were compared with rainfall measurements from the WegenerNet high density network as part of ground validation (GV) projects of GPM missions. The WegenerNet network comprises 151 ground level weather stations in an area of 15 km × 20 km in south-eastern Austria (Feldbach region, ˜46.93° N, ˜15.90° E) designed to serve as a long-term monitoring and validation facility for weather and climate research and applications. While the IMERG provides rainfall estimations every half hour at 0.1° resolution, the WegenerNet network measures rainfall every 5 minutes at around 2 km2 resolution and produces 200 m × 200 m gridded datasets. The study was conducted on the domain of the WegenerNet network; eight IMERG grids are overlapped with the network, two of which are entirely covered by the WegenerNet (40 and 39 stations in each grid). We investigated data from April to September of the years 2014 to 2015; the date of first two years after the launch of the GPM Core Observatory. Since the network has a flexibility to work with various spatial and temporal scales, the comparison could be conducted on average-points to pixel basis at both sub-daily and daily timescales. This presentation will summarize the first results of the comparison and future plans to explore the characteristics of errors in the IMERG datasets.

Genetic dissection of seed oil and protein content and identification of networks associated with oil content in Brassica napus

PubMed Central

Chao, Hongbo; Wang, Hao; Wang, Xiaodong; Guo, Liangxing; Gu, Jianwei; Zhao, Weiguo; Li, Baojun; Chen, Dengyan; Raboanatahiry, Nadia; Li, Maoteng

2017-01-01

High-density linkage maps can improve the precision of QTL localization. A high-density SNP-based linkage map containing 3207 markers covering 3072.7 cM of the Brassica napus genome was constructed in the KenC-8 × N53-2 (KNDH) population. A total of 67 and 38 QTLs for seed oil and protein content were identified with an average confidence interval of 5.26 and 4.38 cM, which could explain up to 22.24% and 27.48% of the phenotypic variation, respectively. Thirty-eight associated genomic regions from BSA overlapped with and/or narrowed the SOC-QTLs, further confirming the QTL mapping results based on the high-density linkage map. Potential candidates related to acyl-lipid and seed storage underlying SOC and SPC, respectively, were identified and analyzed, among which six were checked and showed expression differences between the two parents during different embryonic developmental periods. A large primary carbohydrate pathway based on potential candidates underlying SOC- and SPC-QTLs, and interaction networks based on potential candidates underlying SOC-QTLs, was constructed to dissect the complex mechanism based on metabolic and gene regulatory features, respectively. Accurate QTL mapping and potential candidates identified based on high-density linkage map and BSA analyses provide new insights into the complex genetic mechanism of oil and protein accumulation in the seeds of rapeseed. PMID:28393910

Mapping transcription factor interactome networks using HaloTag protein arrays.

PubMed

Yazaki, Junshi; Galli, Mary; Kim, Alice Y; Nito, Kazumasa; Aleman, Fernando; Chang, Katherine N; Carvunis, Anne-Ruxandra; Quan, Rosa; Nguyen, Hien; Song, Liang; Alvarez, José M; Huang, Shao-Shan Carol; Chen, Huaming; Ramachandran, Niroshan; Altmann, Stefan; Gutiérrez, Rodrigo A; Hill, David E; Schroeder, Julian I; Chory, Joanne; LaBaer, Joshua; Vidal, Marc; Braun, Pascal; Ecker, Joseph R

2016-07-19

Protein microarrays enable investigation of diverse biochemical properties for thousands of proteins in a single experiment, an unparalleled capacity. Using a high-density system called HaloTag nucleic acid programmable protein array (HaloTag-NAPPA), we created high-density protein arrays comprising 12,000 Arabidopsis ORFs. We used these arrays to query protein-protein interactions for a set of 38 transcription factors and transcriptional regulators (TFs) that function in diverse plant hormone regulatory pathways. The resulting transcription factor interactome network, TF-NAPPA, contains thousands of novel interactions. Validation in a benchmarked in vitro pull-down assay revealed that a random subset of TF-NAPPA validated at the same rate of 64% as a positive reference set of literature-curated interactions. Moreover, using a bimolecular fluorescence complementation (BiFC) assay, we confirmed in planta several interactions of biological interest and determined the interaction localizations for seven pairs. The application of HaloTag-NAPPA technology to plant hormone signaling pathways allowed the identification of many novel transcription factor-protein interactions and led to the development of a proteome-wide plant hormone TF interactome network.

Using peptide array to identify binding motifs and interaction networks for modular domains.

PubMed

Li, Shawn S-C; Wu, Chenggang

2009-01-01

Specific protein-protein interactions underlie all essential biological processes and form the basis of cellular signal transduction. The recognition of a short, linear peptide sequence in one protein by a modular domain in another represents a common theme of macromolecular recognition in cells, and the importance of this mode of protein-protein interaction is highlighted by the large number of peptide-binding domains encoded by the human genome. This phenomenon also provides a unique opportunity to identify protein-protein binding events using peptide arrays and complementary biochemical assays. Accordingly, high-density peptide array has emerged as a useful tool by which to map domain-mediated protein-protein interaction networks at the proteome level. Using the Src-homology 2 (SH2) and 3 (SH3) domains as examples, we describe the application of oriented peptide array libraries in uncovering specific motifs recognized by an SH2 domain and the use of high-density peptide arrays in identifying interaction networks mediated by the SH3 domain. Methods reviewed here could also be applied to other modular domains, including catalytic domains, that recognize linear peptide sequences.

Absolute flux density calibrations of radio sources: 2.3 GHz

NASA Technical Reports Server (NTRS)

Freiley, A. J.; Batelaan, P. D.; Bathker, D. A.

1977-01-01

A detailed description of a NASA/JPL Deep Space Network program to improve S-band gain calibrations of large aperture antennas is reported. The program is considered unique in at least three ways; first, absolute gain calibrations of high quality suppressed-sidelobe dual mode horns first provide a high accuracy foundation to the foundation to the program. Second, a very careful transfer calibration technique using an artificial far-field coherent-wave source was used to accurately obtain the gain of one large (26 m) aperture. Third, using the calibrated large aperture directly, the absolute flux density of five selected galactic and extragalactic natural radio sources was determined with an absolute accuracy better than 2 percent, now quoted at the familiar 1 sigma confidence level. The follow-on considerations to apply these results to an operational network of ground antennas are discussed. It is concluded that absolute gain accuracies within + or - 0.30 to 0.40 db are possible, depending primarily on the repeatability (scatter) in the field data from Deep Space Network user stations.

Semiconducting carbon nanotube network thin-film transistors with enhanced inkjet-printed source and drain contact interfaces

NASA Astrophysics Data System (ADS)

Lee, Yongwoo; Yoon, Jinsu; Choi, Bongsik; Lee, Heesung; Park, Jinhee; Jeon, Minsu; Han, Jungmin; Lee, Jieun; Kim, Yeamin; Kim, Dae Hwan; Kim, Dong Myong; Choi, Sung-Jin

2017-10-01

Carbon nanotubes (CNTs) are emerging materials for semiconducting channels in high-performance thin-film transistor (TFT) technology. However, there are concerns regarding the contact resistance (Rcontact) in CNT-TFTs, which limits the ultimate performance, especially the CNT-TFTs with the inkjet-printed source/drain (S/D) electrodes. Thus, the contact interfaces comprising the overlap between CNTs and metal S/D electrodes play a particularly dominant role in determining the performances and degree of variability in the CNT-TFTs with inkjet-printed S/D electrodes. In this work, the CNT-TFTs with improved device performance are demonstrated to enhance contact interfaces by controlling the CNT density at the network channel and underneath the inkjet-printed S/D electrodes during the formation of a CNT network channel. The origin of the improved device performance was systematically investigated by extracting Rcontact in the CNT-TFTs with the enhanced contact interfaces by depositing a high density of CNTs underneath the S/D electrodes, resulting in a 59% reduction in Rcontact; hence, the key performance metrics were correspondingly improved without sacrificing any other device metrics.

Unified pipe network method for simulation of water flow in fractured porous rock

NASA Astrophysics Data System (ADS)

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

2017-04-01

Rock masses are often conceptualized as dual-permeability media containing fractures or fracture networks with high permeability and porous matrix that is less permeable. In order to overcome the difficulties in simulating fluid flow in a highly discontinuous dual-permeability medium, an effective unified pipe network method is developed, which discretizes the dual-permeability rock mass into a virtual pipe network system. It includes fracture pipe networks and matrix pipe networks. They are constructed separately based on equivalent flow models in a representative area or volume by taking the advantage of the orthogonality of the mesh partition. Numerical examples of fluid flow in 2-D and 3-D domain including porous media and fractured porous media are presented to demonstrate the accuracy, robustness, and effectiveness of the proposed unified pipe network method. Results show that the developed method has good performance even with highly distorted mesh. Water recharge into the fractured rock mass with complex fracture network is studied. It has been found in this case that the effect of aperture change on the water recharge rate is more significant in the early stage compared to the fracture density change.

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.

Multiplexed, High Density Electrophysiology with Nanofabricated Neural Probes

PubMed Central

Du, Jiangang; Blanche, Timothy J.; Harrison, Reid R.; Lester, Henry A.; Masmanidis, Sotiris C.

2011-01-01

Extracellular electrode arrays can reveal the neuronal network correlates of behavior with single-cell, single-spike, and sub-millisecond resolution. However, implantable electrodes are inherently invasive, and efforts to scale up the number and density of recording sites must compromise on device size in order to connect the electrodes. Here, we report on silicon-based neural probes employing nanofabricated, high-density electrical leads. Furthermore, we address the challenge of reading out multichannel data with an application-specific integrated circuit (ASIC) performing signal amplification, band-pass filtering, and multiplexing functions. We demonstrate high spatial resolution extracellular measurements with a fully integrated, low noise 64-channel system weighing just 330 mg. The on-chip multiplexers make possible recordings with substantially fewer external wires than the number of input channels. By combining nanofabricated probes with ASICs we have implemented a system for performing large-scale, high-density electrophysiology in small, freely behaving animals that is both minimally invasive and highly scalable. PMID:22022568

Using a geolocation social networking application to calculate the population density of sex-seeking gay men for research and prevention services.

PubMed

Delaney, Kevin P; Kramer, Michael R; Waller, Lance A; Flanders, W Dana; Sullivan, Patrick S

2014-11-18

In the United States, human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) continues to have a heavy impact on men who have sex with men (MSM). Among MSM, black men under the age of 30 are at the most risk for being diagnosed with HIV. The US National HIV/AIDS strategy recommends intensifying efforts in communities that are most heavily impacted; to do so requires new methods for identifying and targeting prevention resources to young MSM, especially young MSM of color. We piloted a methodology for using the geolocation features of social and sexual networking applications as a novel approach to calculating the local population density of sex-seeking MSM and to use self-reported age and race from profile postings to highlight areas with a high density of minority and young minority MSM in Atlanta, Georgia. We collected data from a geographically systematic sample of points in Atlanta. We used a sexual network mobile phone app and collected application profile data, including age, race, and distance from each point, for either the 50 closest users or for all users within a 2-mile radius of sampled points. From these data, we developed estimates of the spatial density of application users in the entire city, stratified by race. We then compared the ratios and differences between the spatial densities of black and white users and developed an indicator of areas with the highest density of users of each race. We collected data from 2666 profiles at 79 sampled points covering 883 square miles; overlapping circles of data included the entire 132.4 square miles in Atlanta. Of the 2666 men whose profiles were observed, 1563 (58.63%) were white, 810 (30.38%) were black, 146 (5.48%) were another race, and 147 (5.51%) did not report a race in their profile. The mean age was 31.5 years, with 591 (22.17%) between the ages of 18-25, and 496 (18.60%) between the ages of 26-30. The mean spatial density of observed profiles was 33 per square mile, but the distribution of profiles observed across the 79 sampled points was highly skewed (median 17, range 1-208). Ratio, difference, and distribution outlier measures all provided similar information, highlighting areas with higher densities of minority and young minority MSM. Using a limited number of sampled points, we developed a geospatial density map of MSM using a social-networking sex-seeking app. This approach provides a simple method to describe the density of specific MSM subpopulations (users of a particular app) for future HIV behavioral surveillance and allow targeting of prevention resources such as HIV testing to populations and areas of highest need.

Unconstrained Recovery Characterization of Shape-Memory Polymer Networks for Cardiovascular Applications

PubMed Central

Yakacki, Christopher M.; Shandas, Robin; Lanning, Craig; Rech, Bryan; Eckstein, Alex; Gall, Ken

2009-01-01

Shape-memory materials have been proposed in biomedical device design due to their ability to facilitate minimally invasive surgery and recover to a predetermined shape in-vivo. Use of the shape-memory effect in polymers is proposed for cardiovascular stent interventions to reduce the catheter size for delivery and offer highly controlled and tailored deployment at body temperature. Shape-memory polymer networks were synthesized via photopolymerization of tert-butyl acrylate and poly (ethylene glycol) dimethacrylate to provide precise control over the thermomechanical response of the system. The free recovery response of the polymer stents at body temperature was studied as a function of glass transition temperature (Tg), crosslink density, geometrical perforation, and deformation temperature, all of which can be independently controlled. Room temperature storage of the stents was shown to be highly dependent on Tg and crosslink density. The pressurized response of the stents is also demonstrated to depend on crosslink density. This polymer system exhibits a wide range of shape-memory and thermomechanical responses to adapt and meet specific needs of minimally invasive cardiovascular devices. PMID:17296222

Ionospheric signatures of Lightning

NASA Astrophysics Data System (ADS)

Hsu, M.; Liu, J.

2003-12-01

The geostationary metrology satellite (GMS) monitors motions of thunderstorm cloud, while the lightning detection network (LDN) in Taiwan and the very high Frequency (VHF) radar in Chung-Li (25.0›XN, 121.2›XE) observed occurrences of lightning during May and July, 1997. Measurements from the digisonde portable sounder (DPS) at National Central University shows that lightning results in occurrence of the sporadic E-layer (Es), as well as increase and decrease of plasma density at the F2-peak and E-peak in the ionosphere, respectively. A network of ground-based GPS receivers is further used to monitor the spatial distribution of the ionospheric TEC. To explain the plasma density variations, a model is proposed.

Poisson's ratio and the densification of glass under high pressure.

PubMed

Rouxel, T; Ji, H; Hammouda, T; Moréac, A

2008-06-06

Because of a relatively low atomic packing density, (Cg) glasses experience significant densification under high hydrostatic pressure. Poisson's ratio (nu) is correlated to Cg and typically varies from 0.15 for glasses with low Cg such as amorphous silica to 0.38 for close-packed atomic networks such as in bulk metallic glasses. Pressure experiments were conducted up to 25 GPa at 293 K on silica, soda-lime-silica, chalcogenide, and bulk metallic glasses. We show from these high-pressure data that there is a direct correlation between nu and the maximum post-decompression density change.

Biomass-Derived Nitrogen-Doped Carbon Nanofiber Network: A Facile Template for Decoration of Ultrathin Nickel-Cobalt Layered Double Hydroxide Nanosheets as High-Performance Asymmetric Supercapacitor Electrode.

PubMed

Lai, Feili; Miao, Yue-E; Zuo, Lizeng; Lu, Hengyi; Huang, Yunpeng; Liu, Tianxi

2016-06-01

The development of biomass-based energy storage devices is an emerging trend to reduce the ever-increasing consumption of non-renewable resources. Here, nitrogen-doped carbonized bacterial cellulose (CBC-N) nanofibers are obtained by one-step carbonization of polyaniline coated bacterial cellulose (BC) nanofibers, which not only display excellent capacitive performance as the supercapacitor electrode, but also act as 3D bio-template for further deposition of ultrathin nickel-cobalt layered double hydroxide (Ni-Co LDH) nanosheets. The as-obtained CBC-N@LDH composite electrodes exhibit significantly enhanced specific capacitance (1949.5 F g(-1) at a discharge current density of 1 A g(-1) , based on active materials), high capacitance retention of 54.7% even at a high discharge current density of 10 A g(-1) and excellent cycling stability of 74.4% retention after 5000 cycles. Furthermore, asymmetric supercapacitors (ASCs) are constructed using CBC-N@LDH composites as positive electrode materials and CBC-N nanofibers as negative electrode materials. By virtue of the intrinsic pseudocapacitive characteristics of CBC-N@LDH composites and 3D nitrogen-doped carbon nanofiber networks, the developed ASC exhibits high energy density of 36.3 Wh kg(-1) at the power density of 800.2 W kg(-1) . Therefore, this work presents a novel protocol for the large-scale production of biomass-derived high-performance electrode materials in practical supercapacitor applications. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Adjustable Trajectory Design Based on Node Density for Mobile Sink in WSNs

PubMed Central

Yang, Guisong; Liu, Shuai; He, Xingyu; Xiong, Naixue; Wu, Chunxue

2016-01-01

The design of movement trajectories for mobile sink plays an important role in data gathering for Wireless Sensor Networks (WSNs), as it affects the network coverage, and packet delivery ratio, as well as the network lifetime. In some scenarios, the whole network can be divided into subareas where the nodes are randomly deployed. The node densities of these subareas are quite different, which may result in a decreased packet delivery ratio and network lifetime if the movement trajectory of the mobile sink cannot adapt to these differences. To address these problems, we propose an adjustable trajectory design method based on node density for mobile sink in WSNs. The movement trajectory of the mobile sink in each subarea follows the Hilbert space-filling curve. Firstly, the trajectory is constructed based on network size. Secondly, the adjustable trajectory is established based on node density in specific subareas. Finally, the trajectories in each subarea are combined to acquire the whole network’s movement trajectory for the mobile sink. In addition, an adaptable power control scheme is designed to adjust nodes’ transmitting range dynamically according to the movement trajectory of the mobile sink in each subarea. The simulation results demonstrate that the proposed trajectories can adapt to network changes flexibly, thus outperform both in packet delivery ratio and in energy consumption the trajectories designed only based on the network size and the whole network node density. PMID:27941662

Interconnected V2O5 nanoporous network for high-performance supercapacitors.

PubMed

Saravanakumar, B; Purushothaman, Kamatchi K; Muralidharan, G

2012-09-26

Vanadium pentoxide (V(2)O(5)) has attracted attention for supercapcitor applications because of its extensive multifunctional properties. In the present study, V(2)O(5) nanoporous network was synthesized via simple capping-agent-assisted precipitation technique and it is further annealed at different temperatures. The effect of annealing temperature on the morphology, electrochemical and structural properties, and stability upon oxidation-reduction cycling has been analyzed for supercapacitor application. We achieved highest specific capacitance of 316 F g(-1) for interconnected V(2)O(5) nanoporous network. This interconnected nanoporous network creates facile nanochannels for ion diffusion and facilitates the easy accessibility of ions. Moreover, after six hundred consecutive cycling processes the specific capacitance has changed only by 24%. A simple cost-effective preparation technique of V(2)O(5) nanoporous network with excellent capacitive behavior, energy density, and stability encourages its possible commercial exploitation for the development of high-performance supercapacitors.

Friends, family, and foes: the influence of father's social networks.

PubMed

Murphy, Alexandrea Danielle; Gordon, Derrick; Sherrod, Hans; Dancy, Victoria; Kershaw, Trace

2013-05-01

Fathers can play an important role in child development and family functioning. However, little is known about the influence of paternal perceptions of fatherhood involvement or the influence of fathers' peer networks. We explored the network characteristics (density, closeness, and degree centrality) and peer norms regarding sex, fatherhood, and other risk behaviors of 52 urban adult males in New Haven, Connecticut. Results identify that engagement in high-risk sexual behavior was associated with fatherhood involvement, with 88% of less involved fathers engaging in high-risk sexual behavior (p = .004). Denser networks were positively correlated with unfavorable peer norms such as cheating on a partner or drinking or using drugs (p < .05). Our findings suggest that peer networks are important to father's health and behavior and that father's behaviors may be affected by peer norms. Interventions designed for men may be strengthened by including peers in programming and by addressing norms and norm changing.

sbv IMPROVER: Modern Approach to Systems Biology.

PubMed

Guryanova, Svetlana; Guryanova, Anna

2017-01-01

The increasing amount and variety of data in biosciences call for innovative methods of visualization, scientific verification, and pathway analysis. Novel approaches to biological networks and research quality control are important because of their role in development of new products, improvement, and acceleration of existing health policies and research for novel ways of solving scientific challenges. One such approach is sbv IMPROVER. It is a platform that uses crowdsourcing and verification to create biological networks with easy public access. It contains 120 networks built in Biological Expression Language (BEL) to interpret data from PubMed articles with high-quality verification available for free on the CBN database. Computable, human-readable biological networks with a structured syntax are a powerful way of representing biological information generated from high-density data. This article presents sbv IMPROVER, a crowd-verification approach for the visualization and expansion of biological networks.

Preparing high-density polymer brushes by mechanically assisted polymer assembly (MAPA)

NASA Astrophysics Data System (ADS)

Wu, Tao; Efimenko, Kirill; Genzer, Jan

2001-03-01

We introduce a novel method of modifying the surface properties of materials. This technique, called MAPA (="mechanically assisted polymer assembly"), is based on: 1) chemically attaching polymerization initiators to the surface of an elastomeric network that has been previously stretched by a certain length, Δx, and 2) growing end-anchored macromolecules using surface initiated ("grafting from") atom transfer living radical polymerization. After the polymerization, the strain is removed from the substrate, which returns to its original size causing the grafted macromolecules to stretch away from the substrate and form a dense polymer brush. We demonstrate the feasibility of the MAPA method by preparing high-density polymer brushes of poly(acryl amide), PAAm. We show that, as expected, the grafting density of the PAAm brushes can be increased by increasing Δx. We demonstrate that polymer brushes with extremely high grafting densities can be successfully prepared by MAPA.

Graph theory analysis of cortical thickness networks in adolescents with d-transposition of the great arteries.

PubMed

Watson, Christopher G; Stopp, Christian; Newburger, Jane W; Rivkin, Michael J

2018-02-01

Adolescents with d-transposition of the great arteries (d-TGA) who had the arterial switch operation in infancy have been found to have structural brain differences compared to healthy controls. We used cortical thickness measurements obtained from structural brain MRI to determine group differences in global brain organization using a graph theoretical approach. Ninety-two d-TGA subjects and 49 controls were scanned using one of two identical 1.5-Tesla MRI systems. Mean cortical thickness was obtained from 34 regions per hemisphere using Freesurfer. A linear model was used for each brain region to adjust for subject age, sex, and scanning location. Structural connectivity for each group was inferred based on the presence of high inter-regional correlations of the linear model residuals, and binary connectivity matrices were created by thresholding over a range of correlation values for each group. Graph theory analysis was performed using packages in R. Permutation tests were performed to determine significance of between-group differences in global network measures. Within-group connectivity patterns were qualitatively different between groups. At lower network densities, controls had significantly more long-range connections. The location and number of hub regions differed between groups: controls had a greater number of hubs at most network densities. The control network had a significant rightward asymmetry compared to the d-TGA group at all network densities. Using graph theory analysis of cortical thickness correlations, we found differences in brain structural network organization among d-TGA adolescents compared to controls. These may be related to the white matter and gray matter differences previously found in this cohort, and in turn may be related to the cognitive deficits this cohort presents.

High-density, fail-in-place switches for computer and data networks

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

Coteus, Paul W.; Doany, Fuad E.; Hall, Shawn A.

A structure for a network switch. The network switch may include a plurality of spine chips arranged on a plurality of spine cards, where one or more spine chips are located on each spine card; and a plurality of leaf chips arranged on a plurality of leaf cards, wherein one or more leaf chips are located on each leaf card, where each spine card is connected to every leaf chip and the plurality of spine chips are surrounded on at least two sides by leaf cards.

Ultrathin MnO2 nanoflakes deposited on carbon nanotube networks for symmetrical supercapacitors with enhanced performance

NASA Astrophysics Data System (ADS)

Sun, Peng; Yi, Huan; Peng, Tianquan; Jing, Yuting; Wang, Ruijing; Wang, Huanwen; Wang, Xuefeng

2017-02-01

Manganese dioxide is a promising electrode material for electrochemical supercapacitors, but its poor electronic conductivity (10-5∼10-6 S cm-1) limits the fast charge/discharge rate for practical applications. In the present work, we use the chemical vapor deposition (CVD) method to grow highly conductive carbon nanotube (CNT) networks on flexible Ni mesh, on which MnO2 nanoflake layers are deposited by a simple solution method, forming a hierarchical core-shell structure. Under the optimized mass loading, the as-fabricated MnO2 nanoflake@CNTs/Ni mesh electrode exhibits a high specific capacitance of 1072 F g-1 at 1 A g-1 in three-electrode configuration. Due to advantageous features of these core-shell electrodes (e.g., high conductivity, direct current path, structure stability), the as-assembled symmetric supercapacitor (SSC) based on MnO2@CNTs/Ni mesh has a wide working voltage (2.0 V) in 1 M Na2SO4 aqueous electrolyte. Finally an impressive energy density of 94.4 Wh kg-1 at 1000 W kg-1 and a high power density of 30.2 kW kg-1 at 33.6 Wh kg-1 have been achieved for the as-assembled SSC, which exhibits a great potential as a low-cost, high energy density and attractive wearable energy storage device.

Traffic signal synchronization in the saturated high-density grid road network.

PubMed

Hu, Xiaojian; Lu, Jian; Wang, Wei; Zhirui, Ye

2015-01-01

Most existing traffic signal synchronization strategies do not perform well in the saturated high-density grid road network (HGRN). Traffic congestion often occurs in the saturated HGRN, and the mobility of the network is difficult to restore. In order to alleviate traffic congestion and to improve traffic efficiency in the network, the study proposes a regional traffic signal synchronization strategy, named the long green and long red (LGLR) traffic signal synchronization strategy. The essence of the strategy is to control the formation and dissipation of queues and to maximize the efficiency of traffic flows at signalized intersections in the saturated HGRN. With this strategy, the same signal control timing plan is used at all signalized intersections in the HGRN, and the straight phase of the control timing plan has a long green time and a long red time. Therefore, continuous traffic flows can be maintained when vehicles travel, and traffic congestion can be alleviated when vehicles stop. Using the strategy, the LGLR traffic signal synchronization model is developed, with the objective of minimizing the number of stops. Finally, the simulation is executed to analyze the performance of the model by comparing it to other models, and the superiority of the LGLR model is evident in terms of delay, number of stops, queue length, and overall performance in the saturated HGRN.

The Role of Geographic and Network Factors in Racial Disparities in HIV Among Young Men Who have Sex with Men: An Egocentric Network Study.

PubMed

Mustanski, Brian; Birkett, Michelle; Kuhns, Lisa M; Latkin, Carl A; Muth, Stephen Q

2015-06-01

The objective of this study was to characterize and compare individual and sexual network characteristics of Black, White, and Latino young men who have sex with men (YMSM) as potential drivers of racial disparities in HIV. Egocentric network interviews were conducted with 175 diverse YMSM who described 837 sex partners within 167 sexual-active egos. Sexual partner alter attributes were summarized by ego. Descriptives of ego demographics, sexual partner demographics, and network characteristics were calculated by race of the ego and compared. No racial differences were found in individual engagement in HIV risk behaviors or concurrent sexual partnership. Racial differences were found in partner characteristics, including female gender, non-gay sexual orientations, older age, and residence in a high HIV prevalence neighborhood. Racial differences in relationship characteristics included type of relationships (i.e., main partner) and strength of relationships. Network characteristics also showed differences, including sexual network density and assortativity by race. Most racial differences were in the direction of effects that would tend to increase HIV incidence among Black YMSM. These data suggest that racial disparities in HIV may be driven and/or maintained by a combination of racial differences in partner characteristics, assortativity by race, and increased sexual network density, rather than differences in individual's HIV risk behaviors.

Direct laser written polymer waveguides with out of plane couplers for optical chips

NASA Astrophysics Data System (ADS)

Landowski, Alexander; Zepp, Dominik; Wingerter, Sebastian; von Freymann, Georg; Widera, Artur

2017-10-01

Optical technologies call for waveguide networks featuring high integration densities, low losses, and simple operation. Here, we present polymer waveguides fabricated from a negative tone photoresist via two-photon-lithography in direct laser writing, and show a detailed parameter study of their performance. Specifically, we produce waveguides featuring bend radii down to 40 μ m, insertion losses of the order of 10 dB, and loss coefficients smaller than 0.81 dB mm-1, facilitating high integration densities in writing fields of 300 μ m×300 μ m. A novel three-dimensional coupler design allows for coupling control as well as direct observation of outputs in a single field of view through a microscope objective. Finally, we present beam-splitting devices to construct larger optical networks, and we show that the waveguide material is compatible with the integration of quantum emitters.

The effect of volume exclusion on the formation of DNA minicircle networks: implications to kinetoplast DNA

NASA Astrophysics Data System (ADS)

Diao, Y.; Hinson, K.; Sun, Y.; Arsuaga, J.

2015-10-01

Kinetoplast DNA (kDNA) is the mitochondrial of DNA of disease causing organisms such as Trypanosoma Brucei (T. Brucei) and Trypanosoma Cruzi (T. Cruzi). In most organisms, KDNA is made of thousands of small circular DNA molecules that are highly condensed and topologically linked forming a gigantic planar network. In our previous work we have developed mathematical and computational models to test the confinement hypothesis, that is that the formation of kDNA minicircle networks is a product of the high DNA condensation achieved in the mitochondrion of these organisms. In these studies we studied three parameters that characterize the growth of the network topology upon confinement: the critical percolation density, the mean saturation density and the mean valence (i.e. the number of mini circles topologically linked to any chosen minicircle). Experimental results on insect-infecting organisms showed that the mean valence is equal to three, forming a structure similar to those found in medieval chain-mails. These same studies hypothesized that this value of the mean valence was driven by the DNA excluded volume. Here we extend our previous work on kDNA by characterizing the effects of DNA excluded volume on the three descriptive parameters. Using computer simulations of polymer swelling we found that (1) in agreement with previous studies the linking probability of two minicircles does not decrease linearly with the distance between the two minicircles, (2) the mean valence grows linearly with the density of minicircles and decreases with the thickness of the excluded volume, (3) the critical percolation and mean saturation densities grow linearly with the thickness of the excluded volume. Our results therefore suggest that the swelling of the DNA molecule, due to electrostatic interactions, has relatively mild implications on the overall topology of the network. Our results also validate our topological descriptors since they appear to reflect the changes in the physical properties of the polymeric chains and at the same time remain faithful to their description of kDNA.

Embedding Luminescent Nanocrystals in Silica Sol-Gel Matrices

DTIC Science & Technology

2006-01-01

procedure necessary to form low-density silica aerogels using supercritical drying procedures. The resulting aerogel networks show a high surface area...reactions. Recent research that just begins to delve into the subject of taking quantum dot semiconductors in silica aerogels was published in...surface of the QD is desirable. As such, ultra low-density silica aerogel materials are an excellent medium for sensor applications as they can be

Detecting Large-Scale Brain Networks Using EEG: Impact of Electrode Density, Head Modeling and Source Localization

PubMed Central

Liu, Quanying; Ganzetti, Marco; Wenderoth, Nicole; Mantini, Dante

2018-01-01

Resting state networks (RSNs) in the human brain were recently detected using high-density electroencephalography (hdEEG). This was done by using an advanced analysis workflow to estimate neural signals in the cortex and to assess functional connectivity (FC) between distant cortical regions. FC analyses were conducted either using temporal (tICA) or spatial independent component analysis (sICA). Notably, EEG-RSNs obtained with sICA were very similar to RSNs retrieved with sICA from functional magnetic resonance imaging data. It still remains to be clarified, however, what technological aspects of hdEEG acquisition and analysis primarily influence this correspondence. Here we examined to what extent the detection of EEG-RSN maps by sICA depends on the electrode density, the accuracy of the head model, and the source localization algorithm employed. Our analyses revealed that the collection of EEG data using a high-density montage is crucial for RSN detection by sICA, but also the use of appropriate methods for head modeling and source localization have a substantial effect on RSN reconstruction. Overall, our results confirm the potential of hdEEG for mapping the functional architecture of the human brain, and highlight at the same time the interplay between acquisition technology and innovative solutions in data analysis. PMID:29551969

Planning of Green Space Ecological Network in Urban Areas: An Example of Nanchang, China

PubMed Central

Li, Haifeng; Chen, Wenbo; He, Wei

2015-01-01

Green space plays an important role in sustainable urban development and ecology by virtue of multiple environmental, recreational, and economic benefits. Constructing an effective and harmonious urban ecological network and maintaining a sustainable living environment in response to rapid urbanization are the key issues required to be resolved by landscape planners. In this paper, Nanchang City, China was selected as a study area. Based on a series of landscape metrics, the landscape pattern analysis of the current (in 2005) and planned (in 2020) green space system were, respectively, conducted by using FRAGSTATS 3.3 software. Considering the actual situation of the Nanchang urban area, a “one river and two banks, north and south twin cities” ecological network was constructed by using network analysis. Moreover, the ecological network was assessed by using corridor structure analysis, and the improvement of an ecological network on the urban landscape was quantitatively assessed through a comparison between the ecological network and green space system planning. The results indicated that: (1) compared to the green space system in 2005, the planned green space system in 2020 of the Nanchang urban area will decline in both districts (Changnan and Changbei districts). Meanwhile, an increase in patch density and a decrease in mean patch size of green space patches at the landscape level implies the fragmentation of the urban green space landscape. In other words, the planned green space system does not necessarily improve the present green space system; (2) the ecological network of two districts has high corridor density, while Changnan’s ecological network has higher connectivity, but Changbei’s ecological network is more viable from an economic point of view, since it has relatively higher cost efficiency; (3) decrease in patch density, Euclidean nearest neighbor distance, and an increase in mean patch size and connectivity implied that the ecological network could improve landscape connectivity greatly, as compared with the planned green space system. That is to say, the planned ecological network would reduce landscape fragmentation, and increase the shape complexity of green space patches and landscape connectivity. As a result, the quality of the urban ecological environment would be improved. PMID:26501298

Planning of Green Space Ecological Network in Urban Areas: An Example of Nanchang, China.

PubMed

Li, Haifeng; Chen, Wenbo; He, Wei

2015-10-15

Green space plays an important role in sustainable urban development and ecology by virtue of multiple environmental, recreational, and economic benefits. Constructing an effective and harmonious urban ecological network and maintaining a sustainable living environment in response to rapid urbanization are the key issues required to be resolved by landscape planners. In this paper, Nanchang City, China was selected as a study area. Based on a series of landscape metrics, the landscape pattern analysis of the current (in 2005) and planned (in 2020) green space system were, respectively, conducted by using FRAGSTATS 3.3 software. Considering the actual situation of the Nanchang urban area, a "one river and two banks, north and south twin cities" ecological network was constructed by using network analysis. Moreover, the ecological network was assessed by using corridor structure analysis, and the improvement of an ecological network on the urban landscape was quantitatively assessed through a comparison between the ecological network and green space system planning. The results indicated that: (1) compared to the green space system in 2005, the planned green space system in 2020 of the Nanchang urban area will decline in both districts (Changnan and Changbei districts). Meanwhile, an increase in patch density and a decrease in mean patch size of green space patches at the landscape level implies the fragmentation of the urban green space landscape. In other words, the planned green space system does not necessarily improve the present green space system; (2) the ecological network of two districts has high corridor density, while Changnan's ecological network has higher connectivity, but Changbei's ecological network is more viable from an economic point of view, since it has relatively higher cost efficiency; (3) decrease in patch density, Euclidean nearest neighbor distance, and an increase in mean patch size and connectivity implied that the ecological network could improve landscape connectivity greatly, as compared with the planned green space system. That is to say, the planned ecological network would reduce landscape fragmentation, and increase the shape complexity of green space patches and landscape connectivity. As a result, the quality of the urban ecological environment would be improved.

Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints.

PubMed

Zilles, Karl; Bacha-Trams, Maraike; Palomero-Gallagher, Nicola; Amunts, Katrin; Friederici, Angela D

2015-02-01

The language network is a well-defined large-scale neural network of anatomically and functionally interacting cortical areas. The successful language process requires the transmission of information between these areas. Since neurotransmitter receptors are key molecules of information processing, we hypothesized that cortical areas which are part of the same functional language network may show highly similar multireceptor expression pattern ("receptor fingerprint"), whereas those that are not part of this network should have different fingerprints. Here we demonstrate that the relation between the densities of 15 different excitatory, inhibitory and modulatory receptors in eight language-related areas are highly similar and differ considerably from those of 18 other brain regions not directly involved in language processing. Thus, the fingerprints of all cortical areas underlying a large-scale cognitive domain such as language is a characteristic, functionally relevant feature of this network and an important prerequisite for the underlying neuronal processes of language functions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints

PubMed Central

Zilles, Karl; Bacha-Trams, Maraike; Palomero-Gallagher, Nicola; Amunts, Katrin; Friederici, Angela D.

2015-01-01

The language network is a well-defined large-scale neural network of anatomically and functionally interacting cortical areas. The successful language process requires the transmission of information between these areas. Since neurotransmitter receptors are key molecules of information processing, we hypothesized that cortical areas which are part of the same functional language network may show highly similar multireceptor expression pattern (“receptor fingerprint”), whereas those that are not part of this network should have different fingerprints. Here we demonstrate that the relation between the densities of 15 different excitatory, inhibitory and modulatory receptors in eight language-related areas are highly similar and differ considerably from those of 18 other brain regions not directly involved in language processing. Thus, the fingerprints of all cortical areas underlying a large-scale cognitive domain such as language is a characteristic, functionally relevant feature of this network and an important prerequisite for the underlying neuronal processes of language functions. PMID:25243991

Atypical water lattices and their possible relevance to the amorphous ices: A density functional study

NASA Astrophysics Data System (ADS)

Anick, David J.

2013-04-01

Of the fifteen known crystalline forms of ice, eleven consist of a single topologically connected hydrogen bond network with four H-bonds at every O. The other four, Ices VI-VIII and XV, consist of two topologically connected networks, each with four H-bonds at every O. The networks interpenetrate but do not share H-bonds. This article presents two new periodic water lattice families whose topological connectivity is "atypical": they consist of many two-dimensional layers that share no H-bonds. Layers are held together only by dispersion forces. Within each layer there are still four H-bonds at each O. Called "Hexagonal Bilayer Water" (HBW) and "Pleated Sheet Water" (PSW), they have computed densities of about 1.1 g/mL and 1.3 g/mL respectively, and nearest neighbor O-coordination is 4.5 to 5.5 and 6 to 8 respectively. Using density functional theory (BLYP-D/TZVP), various proton ordered forms of HBW and PSW are optimized and categorized. There are simple pathways connecting Ice-Ih to HBW and HBW to PSW. Their computed properties suggest similarities to the high density and very high density amorphous ices (HDA and VHDA) respectively. It is unknown whether HDA, VHDA, and Low Density Amorphous Ice (LDA) are fully disordered glasses down to the molecular level, or whether there is some short-range local order. Based on estimated radial distribution functions (RDFs), one proton ordered form of HBW matches HDA best. The idea is explored that HDA could contain islands with this underlying structure, and likewise, that VHDA could contain regions of PSW. A "microlattice model version 1" (MLM1) is presented as a device to compare key experimental data on the amorphous ices with these atypical structures and with a microlattice form of Ice-XI for LDA. Resemblances are found with the amorphs' RDFs, densities, Raman spectra, and transition behaviors. There is not enough information in the static models to assign either a microlattice structure or a partial microlattice structure to any amorphous ice phase.

Flexible, silver nanowire network nickel hydroxide core-shell electrodes for supercapacitors

NASA Astrophysics Data System (ADS)

Yuksel, Recep; Coskun, Sahin; Kalay, Yunus Eren; Unalan, Husnu Emrah

2016-10-01

We present a novel one-dimensional coaxial architecture composed of silver nanowire (Ag NW) network core and nickel hydroxide (Ni(OH)2) shell for the realization of coaxial nanocomposite electrode materials for supercapacitors. Ag NWs are formed conductive networks via spray coating onto polyethylene terephthalate (PET) substrates and Ni(OH)2 is gradually electrodeposited onto the Ag NW network to fabricate core-shell electrodes for supercapacitors. Synergy of highly conductive Ag NWs and high capacitive Ni(OH)2 facilitate ion and electron transport, enhance electrochemical properties and result in a specific capacitance of 1165.2 F g-1 at a current density of 3 A g-1. After 3000 cycles, fabricated nanocomposite electrodes show 93% capacity retention. The rational design explored in this study points out the potential of nanowire based coaxial energy storage devices.

Improved lithium-ion battery anode capacity with a network of easily fabricated spindle-like carbon nanofibers.

PubMed

Liu, Mengting; Xie, Wenhe; Gu, Lili; Qin, Tianfeng; Hou, Xiaoyi; He, Deyan

2016-01-01

A novel network of spindle-like carbon nanofibers was fabricated via a simplified synthesis involving electrospinning followed by preoxidation in air and postcarbonization in Ar. Not only was the as-obtained carbon network comprised of beads of spindle-like nanofibers but the cubic MnO phase and N elements were successfully anchored into the amorphous carbon matrix. When directly used as a binder-free anode for lithium-ion batteries, the network showed excellent electrochemical performance with high capacity, good rate capacity and reliable cycling stability. Under a current density of 0.2 A g -1 , it delivered a high reversible capacity of 875.5 mAh g -1 after 200 cycles and 1005.5 mAh g -1 after 250 cycles with a significant coulombic efficiency of 99.5%.

Walkability for Different Urban Granularities

NASA Astrophysics Data System (ADS)

Hollenstein, D.; Bleisch, S.

2016-06-01

The positive effects of low-intensity physical activity are widely acknowledged and in this context walking is often promoted as an active form of transport. Under the concept of walkability the role of the built environment in encouraging walking is investigated. For that purpose, walkability is quantified area-wise by measuring a varying set of built environment attributes. In purely GIS-based approaches to studying walkability, indices are generally built using existing and easily accessible data. These include street network design, population density, land use mix, and access to destinations. Access to destinations is usually estimated using either a fixed radius, or distances in the street network. In this paper, two approaches to approximate a footpath network are presented. The two footpath networks were built making different assumptions regarding the walkability of different street types with respect to more or less restrictive safety preferences. Information on sidewalk presence, pedestrian crossings, and traffic restrictions were used to build both networks. The first network comprises car traffic free areas only. The second network includes streets with low speed limits that have no sidewalks. Both networks are compared to the more commonly used street network in an access-to-distance analysis. The results suggest that for the generally highly walkable study area, access to destination mostly depends on destination density within the defined walkable distance. However, on single street segments access to destinations is diminished when only car traffic free spaces are assumed to be walkable.

Evaluation of Coordination of Emergency Response Team through the Social Network Analysis. Case Study: Oil and Gas Refinery.

PubMed

Mohammadfam, Iraj; Bastani, Susan; Esaghi, Mahbobeh; Golmohamadi, Rostam; Saee, Ali

2015-03-01

The purpose of this study was to examine the cohesions status of the coordination within response teams in the emergency response team (ERT) in a refinery. For this study, cohesion indicators of social network analysis (SNA; density, degree centrality, reciprocity, and transitivity) were utilized to examine the coordination of the response teams as a whole network. The ERT of this research, which was a case study, included seven teams consisting of 152 members. The required data were collected through structured interviews and were analyzed using the UCINET 6.0 Social Network Analysis Program. The results reported a relatively low number of triple connections, poor coordination with key members, and a high level of mutual relations in the network with low density, all implying that there were low cohesions of coordination in the ERT. The results showed that SNA provided a quantitative and logical approach for the examination of the coordination status among response teams and it also provided a main opportunity for managers and planners to have a clear understanding of the presented status. The research concluded that fundamental efforts were needed to improve the presented situations.

Transfer-Efficient Face Routing Using the Planar Graphs of Neighbors in High Density WSNs

PubMed Central

Kim, Sang-Ha

2017-01-01

Face routing has been adopted in wireless sensor networks (WSNs) where topological changes occur frequently or maintaining full network information is difficult. For message forwarding in networks, a planar graph is used to prevent looping, and because long edges are removed by planarization and the resulting planar graph is composed of short edges, and messages are forwarded along multiple nodes connected by them even though they can be forwarded directly. To solve this, face routing using information on all nodes within 2-hop range was adopted to forward messages directly to the farthest node within radio range. However, as the density of the nodes increases, network performance plunges because message transfer nodes receive and process increased node information. To deal with this problem, we propose a new face routing using the planar graphs of neighboring nodes to improve transfer efficiency. It forwards a message directly to the farthest neighbor and reduces loads and processing time by distributing network graph construction and planarization to the neighbors. It also decreases the amount of location information to be transmitted by sending information on the planar graph nodes rather than on all neighboring nodes. Simulation results show that it significantly improves transfer efficiency. PMID:29053623

The Quake Catcher Network: Cyberinfrastructure Bringing Seismology into Schools and Homes

NASA Astrophysics Data System (ADS)

Lawrence, J. F.; Cochran, E. S.

2007-12-01

We propose to implement a high density, low cost strong-motion network for rapid response and early warning by placing sensors in schools, homes, and offices. The Quake Catcher Network (QCN) will employ existing networked laptops and desktops to form the world's largest high-density, distributed computing seismic network. Costs for this network will be minimal because the QCN will use 1) strong motion sensors (accelerometers) already internal to many laptops and 2) nearly identical low-cost universal serial bus (USB) accelerometers for use with desktops. The Berkeley Open Infrastructure for Network Computing (BOINC!) provides a free, proven paradigm for involving the public in large-scale computational research projects. As evidenced by the SETI@home program and others, individuals are especially willing to donate their unused computing power to projects that they deem relevant, worthwhile, and educational. The client- and server-side software will rapidly monitor incoming seismic signals, detect the magnitudes and locations of significant earthquakes, and may even provide early warnings to other computers and users before they can feel the earthquake. The software will provide the client-user with a screen-saver displaying seismic data recorded on their laptop, recently detected earthquakes, and general information about earthquakes and the geosciences. Furthermore, this project will install USB sensors in K-12 classrooms as an educational tool for teaching science. Through a variety of interactive experiments students will learn about earthquakes and the hazards earthquakes pose. For example, students can learn how the vibrations of an earthquake decrease with distance by jumping up and down at increasing distances from the sensor and plotting the decreased amplitude of the seismic signal measured on their computer. We hope to include an audio component so that students can hear and better understand the difference between low and high frequency seismic signals. The QCN will provide a natural way to engage students and the public in earthquake detection and research.

Detecting large-scale networks in the human brain using high-density electroencephalography.

PubMed

Liu, Quanying; Farahibozorg, Seyedehrezvan; Porcaro, Camillo; Wenderoth, Nicole; Mantini, Dante

2017-09-01

High-density electroencephalography (hdEEG) is an emerging brain imaging technique that can be used to investigate fast dynamics of electrical activity in the healthy and the diseased human brain. Its applications are however currently limited by a number of methodological issues, among which the difficulty in obtaining accurate source localizations. In particular, these issues have so far prevented EEG studies from reporting brain networks similar to those previously detected by functional magnetic resonance imaging (fMRI). Here, we report for the first time a robust detection of brain networks from resting state (256-channel) hdEEG recordings. Specifically, we obtained 14 networks previously described in fMRI studies by means of realistic 12-layer head models and exact low-resolution brain electromagnetic tomography (eLORETA) source localization, together with independent component analysis (ICA) for functional connectivity analysis. Our analyses revealed three important methodological aspects. First, brain network reconstruction can be improved by performing source localization using the gray matter as source space, instead of the whole brain. Second, conducting EEG connectivity analyses in individual space rather than on concatenated datasets may be preferable, as it permits to incorporate realistic information on head modeling and electrode positioning. Third, the use of a wide frequency band leads to an unbiased and generally accurate reconstruction of several network maps, whereas filtering data in a narrow frequency band may enhance the detection of specific networks and penalize that of others. We hope that our methodological work will contribute to rise of hdEEG as a powerful tool for brain research. Hum Brain Mapp 38:4631-4643, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Background Noise of the Aldeia da Serra Region (Portugal) from a temporary broad band network

NASA Astrophysics Data System (ADS)

Wachilala, Piedade; Borges, José; Caldeira, Bento; Bezzeghoud, Mourad

2017-04-01

In this study, we analyse seismic background noise to assess the effect of noise based on the detectability of a temporary network constituted by DOCTAR (Deep Ocean Test Array), who have been deployed in a period between 2011 and 2012 in Portugal mainland, and the Évora permanent seismic station. This network is constituted by 14 digital broadband stations (14 CMG-3ESP and one STS2 sensors) with a flat response between the 60 sec to 50 Hz, 24-bit and 120s to 60Hz respectively. The temporary network was operated in continuous recording mode (three-components) in a region located in the north of the region of Évora, within a radius of about 30 km around the village of Aldeia da Serra, region in which there is an important seismic activity in the context of Portugal mainland. We calculated power spectral densities of background noise for each station/component and compare them with high-noise model and low-noise model of Peterson (1993). We consider different for day and night local and for different periods of the year. Power spectral density estimates show moderate noise levels with all stations falling within the high and low bounds of Peterson (1993). Considering the results of the noise, we estimate the detection limit of each station and consequently the detectability of the network. From this information and taking in attention the events recorded during the period of DOCTAR operation we analyse the improvement promoted by this temporary network regarding the existent seismic networks to the local seismicity study. This work was partially supported by COMPETE 2020 program (POCI-01-0145-FEDER-007690 project). We acknowledge GFZ Potsdam for providing part of the data used in this study.

The Community Collaborative Rain, Hail and Snow Network (CoCoRaHS): Timely Volunteer Precipitation Measurements to Supplement Existing Hydrometeorological Networks

NASA Astrophysics Data System (ADS)

Reges, H. W.; Doesken, N. J.; Cifelli, R. C.; Turner, J. S.

2005-12-01

The Community Collaborative Rain, Hail and Snow Network (CoCoRaHS) is a community-based, education-focused high density network of individual and family volunteers of all ages and backgrounds, who take daily measurements of rain, hail and snow at their homes, schools and businesses. Precipitation is measured using low-cost high capacity 4" diameter plastic rain gauges and Styrofoam wrapped in aluminum foil "hail pads". Thanks to the "low-tech/low-cost" approach, thousands of volunteers can afford to participate, giving the end user a large collection of data points that fill in gaps in many existing networks and data sets. Where feasible, CoCoRaHS is striving to achieve a station density approaching one observation per km-squared providing exceptional detail on cumulative storm precipitation over populated areas. These observations are collected and made available on the CoCoRaHS website: www.cocorahs.org in map and table format. The data are already being used daily by federal, state and community organizations and businesses for many resource management and hydrologic monitoring and predication applications. CoCoRaHS "Intense Rain Reports" and "Hail Reports" are used in "real time" by the National Weather Service in the issuing of flash flood warnings and severe thunderstorm warnings. While only providing once-daily and occasional event reports, CoCoRaHS does provide excellent observational consistency and accuracy including snowfall, depth and water content measurements, as well as the only comprehensive hail data currently being gathered in the U.S. The CoCoRaHS network currently engages over 2,000 volunteer observers in communities across six states, and the network continues to grow.

Retained executive abilities in mild cognitive impairment are associated with increased white matter network connectivity.

PubMed

Farrar, Danielle C; Mian, Asim Z; Budson, Andrew E; Moss, Mark B; Koo, Bang Bon; Killiany, Ronald J

2018-01-01

To describe structural network differences in individuals with mild cognitive impairment (MCI) with high versus low executive abilities, as reflected by measures of white matter connectivity using diffusion tensor imaging (DTI). This was a retrospective, cross-sectional study. Of the 128 participants from the Alzheimer's Disease Neuroimaging Initiative database who had both a DTI scan as well as a diagnosis of MCI, we used an executive function score to classify the top 15 scoring patients as high executive ability, and the bottom-scoring 16 patients as low executive ability. Using a regions-of-interest-based analysis, we constructed networks and calculated graph theory measures on the constructed networks. We used automated tractography in order to compare differences in major white matter tracts. The high executive ability group yielded greater network size, density and clustering coefficient. The high executive ability group reflected greater fractional anisotropy bilaterally in the inferior and superior longitudinal fasciculi. The network measures of the high executive ability group demonstrated greater white matter integrity. This suggests that white matter reserve may confer greater protection of executive abilities. Loss of this reserve may lead to greater impairment in the progression to Alzheimer's disease dementia. • The MCI high executive ability group yielded a larger network. • The MCI high executive ability group had greater FA in numerous tracts. • White matter reserve may confer greater protection of executive abilities. • Loss of executive reserve may lead to greater impairment in AD dementia.

Estimating topological properties of weighted networks from limited information.

PubMed

Cimini, Giulio; Squartini, Tiziano; Gabrielli, Andrea; Garlaschelli, Diego

2015-10-01

A problem typically encountered when studying complex systems is the limitedness of the information available on their topology, which hinders our understanding of their structure and of the dynamical processes taking place on them. A paramount example is provided by financial networks, whose data are privacy protected: Banks publicly disclose only their aggregate exposure towards other banks, keeping individual exposures towards each single bank secret. Yet, the estimation of systemic risk strongly depends on the detailed structure of the interbank network. The resulting challenge is that of using aggregate information to statistically reconstruct a network and correctly predict its higher-order properties. Standard approaches either generate unrealistically dense networks, or fail to reproduce the observed topology by assigning homogeneous link weights. Here, we develop a reconstruction method, based on statistical mechanics concepts, that makes use of the empirical link density in a highly nontrivial way. Technically, our approach consists in the preliminary estimation of node degrees from empirical node strengths and link density, followed by a maximum-entropy inference based on a combination of empirical strengths and estimated degrees. Our method is successfully tested on the international trade network and the interbank money market, and represents a valuable tool for gaining insights on privacy-protected or partially accessible systems.

Estimating topological properties of weighted networks from limited information

NASA Astrophysics Data System (ADS)

Cimini, Giulio; Squartini, Tiziano; Gabrielli, Andrea; Garlaschelli, Diego

2015-10-01

A problem typically encountered when studying complex systems is the limitedness of the information available on their topology, which hinders our understanding of their structure and of the dynamical processes taking place on them. A paramount example is provided by financial networks, whose data are privacy protected: Banks publicly disclose only their aggregate exposure towards other banks, keeping individual exposures towards each single bank secret. Yet, the estimation of systemic risk strongly depends on the detailed structure of the interbank network. The resulting challenge is that of using aggregate information to statistically reconstruct a network and correctly predict its higher-order properties. Standard approaches either generate unrealistically dense networks, or fail to reproduce the observed topology by assigning homogeneous link weights. Here, we develop a reconstruction method, based on statistical mechanics concepts, that makes use of the empirical link density in a highly nontrivial way. Technically, our approach consists in the preliminary estimation of node degrees from empirical node strengths and link density, followed by a maximum-entropy inference based on a combination of empirical strengths and estimated degrees. Our method is successfully tested on the international trade network and the interbank money market, and represents a valuable tool for gaining insights on privacy-protected or partially accessible systems.

Response of moose to a high‐density road network

USGS Publications Warehouse

Wattles, David W.; Zeller, Katherine A.; DeStefano, Stephen

2018-01-01

Road networks and the disturbance associated with vehicle traffic alter animal behavior, movements, and habitat selection. The response of moose (Alces americanus) to roads has been documented in relatively rural areas, but less is known about moose response to roads in more highly roaded landscapes. We examined road‐crossing frequencies and habitat use of global positioning system (GPS)‐collared moose in Massachusetts, USA, where moose home ranges have road densities approximately twice that of previous studies. We compared seasonal road‐crossing frequencies of moose with a null movement model. We estimated moose travel speeds during road‐crossing events and compared them with speeds during other home range movements. To estimate the extent of the road effect zone and determine how roads influenced moose habitat use, we fit a third‐order resource selection function. With the exception of the lowest use road class (<10 vehicles/day), we found moose crossed roads less than expected based on the null movement model and frequency decreased with increasing road size and traffic. Moose crossed roads faster than they traveled during other times. This effect increased with increasing road use intensity. Overall, roads were a major factor determining what portions of Massachusetts moose used and how they moved among habitat patches. Our results suggest that moose in Massachusetts can adapt to a high‐density road network, but the road effect is still strongly negative and, in some cases, is more pronounced than in study areas with lower road densities. Future road construction and the expansion of road networks may have a large effect on moose and other wildlife.

Kinetic Energy of Hydrocarbons as a Function of Electron Density and Convolutional Neural Networks.

PubMed

Yao, Kun; Parkhill, John

2016-03-08

We demonstrate a convolutional neural network trained to reproduce the Kohn-Sham kinetic energy of hydrocarbons from an input electron density. The output of the network is used as a nonlocal correction to conventional local and semilocal kinetic functionals. We show that this approximation qualitatively reproduces Kohn-Sham potential energy surfaces when used with conventional exchange correlation functionals. The density which minimizes the total energy given by the functional is examined in detail. We identify several avenues to improve on this exploratory work, by reducing numerical noise and changing the structure of our functional. Finally we examine the features in the density learned by the neural network to anticipate the prospects of generalizing these models.

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

Processing and Characterization of Mechanically Alloyed NiAl-Based Alloys

DTIC Science & Technology

1994-07-20

The ductility of the .MA material decreases at 800 K arranged in networks but many single dislocations are and again increases at higher temperatures...dislocation density increases significantly compared to the hot extruded material. Dislocations are often arranged in a network but many single...P. Deiavigette and S. Amelinckx, Phil. Mag., 5, 729 (1960). 10. K. Vedula and P.S. Khadkikar, High Te= nerone Ahi kides anwd Inmerti s, p.197, S.H

Polymeric Ionic Networks with High Charge Density: Solid-like Electrolytes in Lithium Metal Batteries

DOE PAGES

Zhang, Pengfei; Li, Mingtao; Jiang, Xueguang; ...

2015-11-02

Polymerized ionic networks (PINs) with six ion pairs per repeating unit are synthesized by nucleophilic-substitution-mediated polymerization or radical polymerization of monomers bearing six 1-vinylimidazolium cations. PIN-based solid-like electrolytes show good ionic conductivities (up to 5.32 × 10 -3 S cm -1 at 22 °C), wide electrochemical stability windows (up to 5.6 V), and good interfacial compatibility with the electrodes.

Estimation of Wheat Plant Density at Early Stages Using High Resolution Imagery

PubMed Central

Liu, Shouyang; Baret, Fred; Andrieu, Bruno; Burger, Philippe; Hemmerlé, Matthieu

2017-01-01

Crop density is a key agronomical trait used to manage wheat crops and estimate yield. Visual counting of plants in the field is currently the most common method used. However, it is tedious and time consuming. The main objective of this work is to develop a machine vision based method to automate the density survey of wheat at early stages. RGB images taken with a high resolution RGB camera are classified to identify the green pixels corresponding to the plants. Crop rows are extracted and the connected components (objects) are identified. A neural network is then trained to estimate the number of plants in the objects using the object features. The method was evaluated over three experiments showing contrasted conditions with sowing densities ranging from 100 to 600 seeds⋅m-2. Results demonstrate that the density is accurately estimated with an average relative error of 12%. The pipeline developed here provides an efficient and accurate estimate of wheat plant density at early stages. PMID:28559901

Anharmonic Damping of Terahertz Acoustic Waves in a Network Glass and Its Effect on the Density of Vibrational States

NASA Astrophysics Data System (ADS)

Baldi, G.; Giordano, V. M.; Ruta, B.; Dal Maschio, R.; Fontana, A.; Monaco, G.

2014-03-01

We report the observation, by means of high-resolution inelastic x-ray scattering, of an unusually large temperature dependence of the sound attenuation of a network glass at terahertz frequency, an unprecedentedly observed phenomenon. The anharmonicity can be ascribed to the interaction between the propagating acoustic wave and the bath of thermal vibrations. At low temperatures the sound attenuation follows a Rayleigh-Gans scattering law. As the temperature is increased the anharmonic process sets in, resulting in an almost quadratic frequency dependence of the damping in the entire frequency range. We show that the temperature variation of the sound damping accounts quantitatively for the temperature dependence of the density of vibrational states.

Detection of Atrial Fibrillation Using Artifical Neural Network with Power Spectrum Density of RR Interval of Electrocardiogram

NASA Astrophysics Data System (ADS)

Afdala, Adfal; Nuryani, Nuryani; Satrio Nugroho, Anto

2017-01-01

Atrial fibrillation (AF) is a disorder of the heart with fairly high mortality in adults. AF is a common heart arrythmia which is characterized by a missing or irregular contraction of atria. Therefore, finding a method to detect atrial fibrillation is necessary. In this article a system to detect atrial fibrillation has been proposed. Detection system utilized backpropagation artifical neural network. Data input in this method includes power spectrum density of R-peaks interval of electrocardiogram which is selected by wrapping method. This research uses parameter learning rate, momentum, epoch and hidden layer. System produces good performance with accuracy, sensitivity, and specificity of 83.55%, 86.72 % and 81.47 %, respectively.

Deployment Design of Wireless Sensor Network for Simple Multi-Point Surveillance of a Moving Target

PubMed Central

Tsukamoto, Kazuya; Ueda, Hirofumi; Tamura, Hitomi; Kawahara, Kenji; Oie, Yuji

2009-01-01

In this paper, we focus on the problem of tracking a moving target in a wireless sensor network (WSN), in which the capability of each sensor is relatively limited, to construct large-scale WSNs at a reasonable cost. We first propose two simple multi-point surveillance schemes for a moving target in a WSN and demonstrate that one of the schemes can achieve high tracking probability with low power consumption. In addition, we examine the relationship between tracking probability and sensor density through simulations, and then derive an approximate expression representing the relationship. As the results, we present guidelines for sensor density, tracking probability, and the number of monitoring sensors that satisfy a variety of application demands. PMID:22412326

Degradation behavior of, and tissue response to photo-crosslinked poly(trimethylene carbonate) networks.

PubMed

Rongen, Jan J; van Bochove, Bas; Hannink, Gerjon; Grijpma, Dirk W; Buma, Pieter

2016-11-01

Photo-crosslinked networks prepared from three-armed methacrylate functionalized PTMC oligomers (PTMC-tMA macromers) are attractive materials for developing an anatomically correct meniscus scaffold. In this study, we evaluated cell specific biocompatibility, in vitro and in vivo degradation behavior of, and tissue response to, such PTMC networks. By evaluating PTMC networks prepared from PTMC-tMA macromers of different molecular weights, we were able to assess the effect of macromer molecular weight on the degradation rate of the PTMC network obtained after photo-crosslinking. Three photo-crosslinked networks with different crosslinking densities were prepared using PTMC-tMA macromers with molecular weights 13.3, 17.8, and 26.7 kg/mol. Good cell biocompatibility was demonstrated in a proliferation assay with synovium derived cells. PTMC networks degraded slowly, but statistically significant, both in vitro as well as subcutaneously in rats. Networks prepared from macromers with higher molecular weights demonstrated increased degradation rates compared to networks prepared from initial macromers of lowest molecular weight. The degradation process took place via surface erosion. The PTMC networks showed good tissue tolerance during subcutaneous implantation, to which the tissue response was characterized by the presence of fibrous tissue and encapsulation of the implants. Concluding, we developed cell and tissue biocompatible, photo-crosslinked PTMC networks using PTMC-tMA macromers with relatively high molecular weights. These photo-crosslinked PTMC networks slowly degrade by a surface erosion process. Increasing the crosslinking density of these networks decreases the rate of surface degradation. © 2016 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 104A: 2823-2832, 2016. © 2016 Wiley Periodicals, Inc.

Co-altered functional networks and brain structure in unmedicated patients with bipolar and major depressive disorders.

PubMed

He, Hao; Sui, Jing; Du, Yuhui; Yu, Qingbao; Lin, Dongdong; Drevets, Wayne C; Savitz, Jonathan B; Yang, Jian; Victor, Teresa A; Calhoun, Vince D

2017-12-01

Bipolar disorder (BD) and major depressive disorder (MDD) share similar clinical characteristics that often obscure the diagnostic distinctions between their depressive conditions. Both functional and structural brain abnormalities have been reported in these two disorders. However, the direct link between altered functioning and structure in these two diseases is unknown. To elucidate this relationship, we conducted a multimodal fusion analysis on the functional network connectivity (FNC) and gray matter density from MRI data from 13 BD, 40 MDD, and 33 matched healthy controls (HC). A data-driven fusion method called mCCA+jICA was used to identify the co-altered FNC and gray matter components. Comparing to HC, BD exhibited reduced gray matter density in the parietal and occipital cortices, which correlated with attenuated functional connectivity within sensory and motor networks, as well as hyper-connectivity in regions that are putatively engaged in cognitive control. In addition, lower gray matter density was found in MDD in the amygdala and cerebellum. High accuracy in discriminating across groups was also achieved by trained classification models, implying that features extracted from the fusion analysis hold the potential to ultimately serve as diagnostic biomarkers for mood disorders.

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.

Poisson's Ratio and the Densification of Glass under High Pressure

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

Rouxel, T.; Ji, H.; Hammouda, T.

2008-06-06

Because of a relatively low atomic packing density, (C{sub g}) glasses experience significant densification under high hydrostatic pressure. Poisson's ratio ({nu}) is correlated to C{sub g} and typically varies from 0.15 for glasses with low C{sub g} such as amorphous silica to 0.38 for close-packed atomic networks such as in bulk metallic glasses. Pressure experiments were conducted up to 25 GPa at 293 K on silica, soda-lime-silica, chalcogenide, and bulk metallic glasses. We show from these high-pressure data that there is a direct correlation between {nu} and the maximum post-decompression density change.

Polymorphous Supercapacitors Constructed from Flexible Three-Dimensional Carbon Network/Polyaniline/MnO2 Composite Textiles.

PubMed

Wang, Jinjie; Dong, Liubing; Xu, Chengjun; Ren, Danyang; Ma, Xinpei; Kang, Feiyu

2018-04-04

Polymorphous supercapacitors were constructed from flexible three-dimensional carbon network/polyaniline (PANI)/MnO 2 composite textile electrodes. The flexible textile electrodes were fabricated through a layer-by-layer construction strategy: PANI, carbon nanotubes (CNTs), and MnO 2 were deposited on activated carbon fiber cloth (ACFC) in turn through an electropolymerization process, "dipping and drying" method, and in situ chemical reaction, respectively. In the fabricated ACFC/PANI/CNTs/MnO 2 textile electrodes, the ACFC/CNT hybrid framework serves as a porous and electrically conductive 3D network for the rapid transmission of electrons and electrolyte ions, where ACFC, PANI, and MnO 2 are high-performance supercapacitor electrode materials. In the electrolyte of H 2 SO 4 solution, the textile electrode-based symmetric supercapacitor delivers superior areal capacitance, energy density, and power density of 4615 mF cm -2 (for single electrode), 157 μW h cm -2 , and 10372 μW cm -2 , respectively, whereas asymmetric supercapacitor assembled with the prepared composite textile as the positive electrode and ACFC as the negative electrode exhibits an improved energy density of 413 μW h cm -2 and a power density of 16120 μW cm -2 . On the basis of the ACFC/PANI/CNTs/MnO 2 textile electrodes, symmetric and asymmetric solid-state textile supercapacitors with a PVA/H 2 SO 4 gel electrolyte were also produced. These solid-state textile supercapacitors exhibit good electrochemical performance and high flexibility. Furthermore, flexible solid-state fiber-like supercapacitors were prepared with fiber bundle electrodes dismantled from the above composite textiles. Overall, this work makes a meaningful exploration of the versatile applications of textile electrodes to produce polymorphous supercapacitors.

Nanomechanics of layer-by-layer polyelectrolyte complexes: a manifestation of ionic cross-links and fixed charges.

PubMed

Han, Biao; Chery, Daphney R; Yin, Jie; Lu, X Lucas; Lee, Daeyeon; Han, Lin

2016-01-28

This study investigates the roles of two distinct features of ionically cross-linked polyelectrolyte networks - ionic cross-links and fixed charges - in determining their nanomechanical properties. The layer-by-layer assembled poly(allylamine hydrochloride)/poly(acrylic acid) (PAH/PAA) network is used as the model material. The densities of ionic cross-links and fixed charges are modulated through solution pH and ionic strength (IS), and the swelling ratio, elastic and viscoelastic properties are quantified via an array of atomic force microscopy (AFM)-based nanomechanical tools. The roles of ionic cross-links are underscored by the distinctive elastic and viscoelastic nanomechanical characters observed here. First, as ionic cross-links are highly sensitive to solution conditions, the instantaneous modulus, E0, exhibits orders-of-magnitude changes upon pH- and IS-governed swelling, distinctive from the rubber elasticity prediction based on permanent covalent cross-links. Second, ionic cross-links can break and self-re-form, and this mechanism dominates force relaxation of PAH/PAA under a constant indentation depth. In most states, the degree of relaxation is >90%, independent of ionic cross-link density. The importance of fixed charges is highlighted by the unexpectedly more elastic nature of the network despite low ionic cross-link density at pH 2.0, IS 0.01 M. Here, the complex is a net charged, loosely cross-linked, where the degree of relaxation is attenuated to ≈50% due to increased elastic contribution arising from fixed charge-induced Donnan osmotic pressure. In addition, this study develops a new method for quantifying the thickness of highly swollen polymer hydrogel films. It also underscores important technical considerations when performing nanomechanical tests on highly rate-dependent polymer hydrogel networks. These results provide new insights into the nanomechanical characters of ionic polyelectrolyte complexes, and lay the ground for further investigation of their unique time-dependent properties.

Can nature's design be improved upon? High strength, transparent nacre-like nanocomposites with double network of sacrificial cross links.

PubMed

Podsiadlo, Paul; Kaushik, Amit K; Shim, Bong Sup; Agarwal, Ashish; Tang, Zhiyong; Waas, Anthony M; Arruda, Ellen M; Kotov, Nicholas A

2008-11-20

The preparation of a high-strength and highly transparent nacre-like nanocomposite via layer-by-layer assembly technique from poly(vinyl alcohol) (PVA) and Na+-montmorillonite clay nanosheets is reported in this article. We show that a high density of weak bonding interactions between the polymer and the clay particles: hydrogen, dipole-induced dipole, and van der Waals undergoing break-reform deformations, can lead to high strength nanocomposites: sigmaUTS approximately 150 MPa and E' approximately 13 GPa. Further introduction of ionic bonds into the polymeric matrix creates a double network of sacrificial bonds which dramatically increases the mechanical properties: sigmaUTS approximately 320 MPa and E' approximately 60 GPa.

Combined exposure to simulated microgravity and acute or chronic radiation reduces neuronal network integrity and cell survival

NASA Astrophysics Data System (ADS)

Benotmane, Rafi

During orbital or interplanetary space flights, astronauts are exposed to cosmic radiations and microgravity. This study aimed at assessing the effect of these combined conditions on neuronal network density, cell morphology and survival, using well-connected mouse cortical neuron cultures. To this end, neurons were exposed to acute low and high doses of low LET (X-rays) radiation or to chronic low dose-rate of high LET neutron irradiation (Californium-252), under the simulated microgravity generated by the Random Positioning Machine (RPM, Dutch space). High content image analysis of cortical neurons positive for the neuronal marker βIII-tubulin unveiled a reduced neuronal network integrity and connectivity, and an altered cell morphology after exposure to acute/chronic radiation or to simulated microgravity. Additionally, in both conditions, a defect in DNA-repair efficiency was revealed by an increased number of γH2AX-positive foci, as well as an increased number of Annexin V-positive apoptotic neurons. Of interest, when combining both simulated space conditions, we noted a synergistic effect on neuronal network density, neuronal morphology, cell survival and DNA repair. Furthermore, these observations are in agreement with preliminary gene expression data, revealing modulations in cytoskeletal and apoptosis-related genes after exposure to simulated microgravity. In conclusion, the observed in vitro changes in neuronal network integrity and cell survival induced by space simulated conditions provide us with mechanistic understanding to evaluate health risks and the development of countermeasures to prevent neurological disorders in astronauts over long-term space travels. Acknowledgements: This work is supported partly by the EU-FP7 projects CEREBRAD (n° 295552)

Using a Geolocation Social Networking Application to Calculate the Population Density of Sex-Seeking Gay Men for Research and Prevention Services

PubMed Central

Kramer, Michael R; Waller, Lance A; Flanders, W Dana; Sullivan, Patrick S

2014-01-01

Background In the United States, human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) continues to have a heavy impact on men who have sex with men (MSM). Among MSM, black men under the age of 30 are at the most risk for being diagnosed with HIV. The US National HIV/AIDS strategy recommends intensifying efforts in communities that are most heavily impacted; to do so requires new methods for identifying and targeting prevention resources to young MSM, especially young MSM of color. Objective We piloted a methodology for using the geolocation features of social and sexual networking applications as a novel approach to calculating the local population density of sex-seeking MSM and to use self-reported age and race from profile postings to highlight areas with a high density of minority and young minority MSM in Atlanta, Georgia. Methods We collected data from a geographically systematic sample of points in Atlanta. We used a sexual network mobile phone app and collected application profile data, including age, race, and distance from each point, for either the 50 closest users or for all users within a 2-mile radius of sampled points. From these data, we developed estimates of the spatial density of application users in the entire city, stratified by race. We then compared the ratios and differences between the spatial densities of black and white users and developed an indicator of areas with the highest density of users of each race. Results We collected data from 2666 profiles at 79 sampled points covering 883 square miles; overlapping circles of data included the entire 132.4 square miles in Atlanta. Of the 2666 men whose profiles were observed, 1563 (58.63%) were white, 810 (30.38%) were black, 146 (5.48%) were another race, and 147 (5.51%) did not report a race in their profile. The mean age was 31.5 years, with 591 (22.17%) between the ages of 18-25, and 496 (18.60%) between the ages of 26-30. The mean spatial density of observed profiles was 33 per square mile, but the distribution of profiles observed across the 79 sampled points was highly skewed (median 17, range 1-208). Ratio, difference, and distribution outlier measures all provided similar information, highlighting areas with higher densities of minority and young minority MSM. Conclusions Using a limited number of sampled points, we developed a geospatial density map of MSM using a social-networking sex-seeking app. This approach provides a simple method to describe the density of specific MSM subpopulations (users of a particular app) for future HIV behavioral surveillance and allow targeting of prevention resources such as HIV testing to populations and areas of highest need. PMID:25406722

The Effect of Angle Restriction on the Topological Characteristics of Minicircle Networks

NASA Astrophysics Data System (ADS)

Arsuaga, J.; Diao, Y.; Hinson, K.

2012-01-01

Networks of topologically linked minicircle polymers are found in diverse natural systems and are a subject of intense research in nanotechonology. In a recent report the authors introduced a new theoretical model to study the effects of polymer density on the formation and on the topological properties of minicircle networks. Three key topological characteristics were identified in the formation and characterization of a network: the critical percolation density, the average saturation density and the mean valence of the network. In this work we report how these characteristics change when an orientation bias is imposed on the minicircles forming the network. We observe that such restrictions have significant effects on the key topological characteristics of the network. In particular while the effects of restriction of the tilting angle can be predicted we find that those of the azimuthal angle can have somewhat unexpected results.

Symmetric transparent and flexible supercapacitor based on bio-inspired graphene-wrapped Fe2O3 nanowire networks

NASA Astrophysics Data System (ADS)

Huang, Xuankai; Zhang, Haiyan; Li, Na

2017-02-01

Transition metal oxides with high specific capacitance materials are ideal for a new generation of high-performance transparent supercapacitors but are rarely reported. Commonly, the synthesis of the required nanostructured materials is a crucial step required to achieve the transparency of the device. In this study, a Fe2O3 nanowire network transparent film is developed simply through air-solution interface reactions and wrapped in graphene shells for use as transparent electrodes. The Fe2O3 nanowire networks surrounded by the graphene layer exhibit an effective encapsulation structure, providing rapid three-dimensional electron and ion transport pathways. The specific areal capacitance (3.3 mF cm-2 at a scan rate of 10 mV s-1) was greatly improved, which is at least one hundred times higher than that for transparent devices based on planar chemical vapor deposition graphene. Furthermore, the films have a power density of 191.3 W cm-3, which is higher than that of electrolytic capacitors, an energy density of 8 mWh cm-3, which is comparable to that of lithium thin-film batteries, and superior cycling stability.

Experimental Evidence of Low Density Liquid Water under Decompression

NASA Astrophysics Data System (ADS)

Shen, G.; Lin, C.; Sinogeikin, S. V.; Smith, J.

2017-12-01

Water is not only the most important substance for life, but also plays important roles in liquid science for its anomalous properties. It has been widely accepted that water's anomalies are not a result of simple thermal fluctuation, but are connected to the formation of various structural aggregates in the hydrogen bonding network. Among several proposed scenarios, one model of fluctuations between two different liquids has gradually gained traction. These two liquids are referred to as a low-density liquid (LDL) and a high-density liquid (HDL) with a coexistence line in the deeply supercooled regime at elevated pressure. The LDL-HDL transition ends with decreasing pressure at a liquid-liquid critical point (LLCP) with its Widom line extending to low pressures. Above the Widom line lies mostly HDL which is favored by entropy, while LDL, mostly lying below the Widom line, is favored by enthalpy in the tetrahedral hydrogen bonding network. The origin of water's anomalies can then be explained by the increase in structural fluctuations, as water is cooled down to deeply supercooled temperatures approaching the Widom line. Because both the LLCP and the LDL-HDL transition line lie in water's "no man's land" between the homogeneous nucleation temperature (TH, 232 K) and the crystallization temperature (TX, 150 K), the success of experiments exploring this region has been limited thus far. Using a rapid decompression technique integrated with in situ x-ray diffraction, we observe that a high-pressure ice phase transforms to a low-density noncrystalline (LDN) form upon rapid release of pressure at temperatures of 140-165K. The LDN subsequently crystallizes into ice-Ic through a diffusion-controlled process. The change in crystallization rate with temperature indicates that the LDN is a LDL with its tetrahedrally-coordinated network fully developed and clearly linked to low-density amorphous ices. The observation of the tetrahedral LDL supports the two-liquid model for water including the existence of a LLCP.

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.

High-performance flexible supercapacitors based on electrochemically tailored three-dimensional reduced graphene oxide networks.

PubMed

Purkait, Taniya; Singh, Guneet; Kumar, Dinesh; Singh, Mandeep; Dey, Ramendra Sundar

2018-01-12

A simple approach for growing porous electrochemically reduced graphene oxide (pErGO) networks on copper wire, modified with galvanostatically deposited copper foam is demonstrated. The as-prepared pErGO networks on the copper wire are directly used to fabricate solid-state supercapacitor. The pErGO-based supercapacitor can deliver a specific capacitance (C sp ) as high as 81±3 F g -1 at 0.5 A g -1 with polyvinyl alcohol/H 3 PO 4 gel electrolyte. The C sp per unit length and area are calculated as 40.5 mF cm -1 and 283.5 mF cm -2 , respectively. The shape of the voltammogram retained up to high scan rate of 100 V s -1 . The pErGO-based supercapacitor device exhibits noticeably high charge-discharge cycling stability, with 94.5% C sp retained even after 5000 cycles at 5 A g -1 . Nominal change in the specific capacitance, as well as the shape of the voltammogram, is observed at different bending angles of the device even after 5000 cycles. The highest energy density of 11.25 W h kg -1 and the highest power density of 5 kW kg -1 are also achieved with this device. The wire-based supercapacitor is scalable and highly flexible, which can be assembled with/without a flexible substrate in different geometries and bending angles for illustrating promising use in smart textile and wearable device.

DCMDN: Deep Convolutional Mixture Density Network

NASA Astrophysics Data System (ADS)

D'Isanto, Antonio; Polsterer, Kai Lars

2017-09-01

Deep Convolutional Mixture Density Network (DCMDN) estimates probabilistic photometric redshift directly from multi-band imaging data by combining a version of a deep convolutional network with a mixture density network. The estimates are expressed as Gaussian mixture models representing the probability density functions (PDFs) in the redshift space. In addition to the traditional scores, the continuous ranked probability score (CRPS) and the probability integral transform (PIT) are applied as performance criteria. DCMDN is able to predict redshift PDFs independently from the type of source, e.g. galaxies, quasars or stars and renders pre-classification of objects and feature extraction unnecessary; the method is extremely general and allows the solving of any kind of probabilistic regression problems based on imaging data, such as estimating metallicity or star formation rate in galaxies.

Current distribution in conducting nanowire networks

NASA Astrophysics Data System (ADS)

Kumar, Ankush; Vidhyadhiraja, N. S.; Kulkarni, Giridhar U.

2017-07-01

Conducting nanowire networks find diverse applications in solar cells, touch-screens, transparent heaters, sensors, and various related transparent conducting electrode (TCE) devices. The performances of these devices depend on effective resistance, transmittance, and local current distribution in these networks. Although, there have been rigorous studies addressing resistance and transmittance in TCE, not much attention is paid on studying the distribution of current. Present work addresses this compelling issue of understanding current distribution in TCE networks using analytical as well as Monte-Carlo approaches. We quantified the current carrying backbone region against isolated and dangling regions as a function of wire density (ranging from percolation threshold to many multiples of threshold) and compared the wired connectivity with those obtained from template-based methods. Further, the current distribution in the obtained backbone is studied using Kirchhoff's law, which reveals that a significant fraction of the backbone (which is believed to be an active current component) may not be active for end-to-end current transport due to the formation of intervening circular loops. The study shows that conducting wire based networks possess hot spots (extremely high current carrying regions) which can be potential sources of failure. The fraction of these hot spots is found to decrease with increase in wire density, while they are completely absent in template based networks. Thus, the present work discusses unexplored issues related to current distribution in conducting networks, which are necessary to choose the optimum network for best TCE applications.

The energy balance and pressure in the solar transition zone for network and active region features

NASA Technical Reports Server (NTRS)

Nicolas, K. R.; Bartoe, J.-D. F.; Brueckner, G. E.; Vanhoosier, M. E.

1979-01-01

The electron pressure and energy balance in the solar transition zone are determined for about 125 network and active region features on the basis of high spectral and spatial resolution extreme ultraviolet spectra. Si III line intensity ratios obtained from the Naval Research Laboratory high-resolution telescope and spectrograph during a rocket flight are used as diagnostics of electron density and pressure for solar features near 3.5 x 10 to the 4th K. Observed ratios are compared with the calculated dependence of the 1301 A/1312 A and 1301 A/1296 A line intensity ratios on electron density, temperature and pressure. Electron densities ranging from 2 x 10 to the 10th/cu cm to 10 to the 12th/cu cm and active region pressures from 3 x 10 to the 15th to 10 to the 16th/cu cm K are obtained. Energy balance calculations reveal the balance of the divergence of the conductive flux and turbulent energy dissipation by radiative energy losses in a plane-parallel homogeneous transition zone (fill factor of 1), and an energy source requirement for a cylindrical zone geometry (fill factor less than 0.04).

High dose folic acid supplementation of rats alters synaptic transmission and seizure susceptibility in offspring

PubMed Central

Girotto, Fernando; Scott, Lucas; Avchalumov, Yosef; Harris, Jacqueline; Iannattone, Stephanie; Drummond-Main, Chris; Tobias, Rose; Bello-Espinosa, Luis; Rho, Jong M.; Davidsen, Jörn; Teskey, G. Campbell; Colicos, Michael A.

2013-01-01

Maternal folic acid supplementation is essential to reduce the risk of neural tube defects. We hypothesize that high levels of folic acid throughout gestation may produce neural networks more susceptible to seizure in offspring. We hence administered large doses of folic acid to rats before and during gestation and found their offspring had a 42% decrease in their seizure threshold. In vitro, acute application of folic acid or its metabolite 4Hfolate to neurons induced hyper-excitability and bursting. Cultured neuronal networks which develop in the presence of a low concentration (50 nM) of 4Hfolate had reduced capacity to stabilize their network dynamics after a burst of high-frequency activity, and an increase in the frequency of mEPSCs. Networks reared in the presence of the folic acid metabolite 5M4Hfolate developed a spontaneous, distinctive bursting pattern, and both metabolites produced an increase in synaptic density. PMID:23492951

Targeted Proteomics and Absolute Protein Quantification for the Construction of a Stoichiometric Host-Pathogen Surface Density Model*

PubMed Central

Sjöholm, Kristoffer; Kilsgård, Ola; Teleman, Johan; Happonen, Lotta; Malmström, Lars; Malmström, Johan

2017-01-01

Sepsis is a systemic immune response responsible for considerable morbidity and mortality. Molecular modeling of host-pathogen interactions in the disease state represents a promising strategy to define molecular events of importance for the transition from superficial to invasive infectious diseases. Here we used the Gram-positive bacterium Streptococcus pyogenes as a model system to establish a mass spectrometry based workflow for the construction of a stoichiometric surface density model between the S. pyogenes surface, the surface virulence factor M-protein, and adhered human blood plasma proteins. The workflow relies on stable isotope labeled reference peptides and selected reaction monitoring mass spectrometry analysis of a wild-type strain and an M-protein deficient mutant strain, to generate absolutely quantified protein stoichiometry ratios between S. pyogenes and interacting plasma proteins. The stoichiometry ratios in combination with a novel targeted mass spectrometry method to measure cell numbers enabled the construction of a stoichiometric surface density model using protein structures available from the protein data bank. The model outlines the topology and density of the host-pathogen protein interaction network on the S. pyogenes bacterial surface, revealing a dense and highly organized protein interaction network. Removal of the M-protein from S. pyogenes introduces a drastic change in the network topology, validated by electron microscopy. We propose that the stoichiometric surface density model of S. pyogenes in human blood plasma represents a scalable framework that can continuously be refined with the emergence of new results. Future integration of new results will improve the understanding of protein-protein interactions and their importance for bacterial virulence. Furthermore, we anticipate that the general properties of the developed workflow will facilitate the production of stoichiometric surface density models for other types of host-pathogen interactions. PMID:28183813

Computational modeling and molecular imprinting for the development of acrylic polymers with high affinity for bile salts.

PubMed

Yañez, Fernando; Chianella, Iva; Piletsky, Sergey A; Concheiro, Angel; Alvarez-Lorenzo, Carmen

2010-02-05

This work has focused on the rational development of polymers capable of acting as traps of bile salts. Computational modeling was combined with molecular imprinting technology to obtain networks with high affinity for cholate salts in aqueous medium. The screening of a virtual library of 18 monomers, which are commonly used for imprinted networks, identified N-(3-aminopropyl)-methacrylate hydrochloride (APMA.HCl), N,N-diethylamino ethyl methacrylate (DEAEM) and ethyleneglycol methacrylate phosphate (EGMP) as suitable functional monomers with medium-to-high affinity for cholic acid. The polymers were prepared with a fix cholic acid:functional monomer mole ratio of 1:4, but with various cross-linking densities. Compared to polymers prepared without functional monomer, both imprinted and non-imprinted microparticles showed a high capability to remove sodium cholate from aqueous medium. High affinity APMA-based particles even resembled the performance of commercially available cholesterol-lowering granules. The imprinting effect was evident in most of the networks prepared, showing that computational modeling and molecular imprinting can act synergistically to improve the performance of certain polymers. Nevertheless, both the imprinted and non-imprinted networks prepared with the best monomer (APMA.HCl) identified by the modeling demonstrated such high affinity for the template that the imprinting effect was less important. The fitting of adsorption isotherms to the Freundlich model indicated that, in general, imprinting increases the population of high affinity binding sites, except when the affinity of the functional monomer for the target molecule is already very high. The cross-linking density was confirmed as a key parameter that determines the accessibility of the binding points to sodium cholate. Materials prepared with 9% mol APMA and 91% mol cross-linker showed enough affinity to achieve binding levels of up to 0.4 mmol g(-1) (i.e., 170 mg g(-1)) under flow (1 mL min(-1)) of 0.2 mM sodium cholate solution. Copyright 2009 Elsevier B.V. All rights reserved.

An FPGA design of generalized low-density parity-check codes for rate-adaptive optical transport networks

NASA Astrophysics Data System (ADS)

Zou, Ding; Djordjevic, Ivan B.

2016-02-01

Forward error correction (FEC) is as one of the key technologies enabling the next-generation high-speed fiber optical communications. In this paper, we propose a rate-adaptive scheme using a class of generalized low-density parity-check (GLDPC) codes with a Hamming code as local code. We show that with the proposed unified GLDPC decoder architecture, a variable net coding gains (NCGs) can be achieved with no error floor at BER down to 10-15, making it a viable solution in the next-generation high-speed fiber optical communications.

Cellulose nanofiber-templated three-dimension TiO 2 hierarchical nanowire network for photoelectrochemical photoanode

Treesearch

Zhaodong Li; Chunhua Yao; Fei Wang; Zhiyong Cai; Xudong Wang

2014-01-01

Three dimensional (3D) nanostructures with extremely large porosity possess a great promise for the development of high-performance energy harvesting storage devices. In this paper, we developed a high-density 3D TiO2 fiber-nanorod (NR) heterostructure for photoelectrochemical (PEC) water splitting. The hierarchical structure was synthesized on a...

Damage Assessment for Disaster Relief Efforts in Urban Areas Using Optical Imagery and LiDAR Data

NASA Astrophysics Data System (ADS)

Bahr, Thomas

2014-05-01

Imagery combined with LiDAR data and LiDAR-derived products provides a significant source of geospatial data which is of use in disaster mitigation planning. Feature rich building inventories can be constructed from tools with 3D rooftop extraction capabilities, and two dimensional outputs such as DSMs and DTMs can be used to generate layers to support routing efforts in Spatial Analyst and Network Analyst workflows. This allows us to leverage imagery and LiDAR tools for disaster mitigation or other scenarios. Software such as ENVI, ENVI LiDAR, and ArcGIS® Spatial and Network Analyst can therefore be used in conjunction to help emergency responders route ground teams in support of disaster relief efforts. This is exemplified by a case study against the background of the magnitude 7.0 earthquake that struck Haiti's capital city of Port-au-Prince on January 12, 2010. Soon after, both LiDAR data and an 8-band WorldView-2 scene were collected to map the disaster zone. The WorldView-2 scene was orthorectified and atmospherically corrected in ENVI prior to use. ENVI LiDAR was used to extract the DSM, DTM, buildings, and debris from the LiDAR data point cloud. These datasets provide a foundation for the 2D portion of the analysis. As the data was acquired over an area of dense urbanization, the majority of ground surfaces are roads, and standing buildings and debris are actually largely separable on the basis of elevation classes. To extract the road network of Port-au-Prince, the LiDAR-based feature height information was fused with the WorldView-2 scene, using ENVI's object-based feature extraction approach. This road network was converted to a network dataset for further analysis by the ArcGIS Network Analyst. For the specific case of Haiti, the distribution of blue tarps, used as accommodations for refugees, provided a spectrally distinct target. Pure blue tarp pixel spectra were selected from the WorldView-2 scene and input as a reference into ENVI's Spectral Angle Mapper (SAM) classification routine, together with a water-shadow mask to prevent false positives. The resulting blue tarp shape file was input into the ArcGIS Point Density tool, a feature of the Spatial Analyst toolbox. The final distribution map shows the density of blue tarps in Port-au-Prince and can be used to roughly delineate camps of refugees. Analogous, a debris density map was generated after separating the debris elevation class. The combination of this debris density map with the road network allowed to construct an intact road network of Port-au-Prince within the ArcGIS Network Analyst. Moderate density debris was used as a cost-increase barrier feature of the network dataset, and high density debris was used as a total obstruction barrier feature. Based on this information, two hypothetical routing scenarios were analyzed. One involved routing a ground team between two different refugee concentration zones. For the other, potential helicopter landing zones were computed from the LiDAR-derived products and added as facility features to the Network Analyst. Routes from the helicopter landing zones to refugee concentration access points were solved using closest facility logic, again making use of the obstructed network.

Systems and methods for creation of conducting networks of magnetic particles through dynamic self-assembly process

DOEpatents

Snezhko, Oleksiy [Woodridge, IL; Aronson, Igor [Darien, IL; Kwok, Wai-Kwong [Downers Grove, IL

2011-01-25

Self-assembly of magnetic microparticles in AC magnetic fields. Excitation of the system by an AC magnetic field provides a variety of patterns that can be controlled by adjusting the frequency and the amplitude of the field. At low particle densities the low-frequency magnetic excitation favors cluster phase formation, while high frequency excitation favors chains and netlike structures. For denser configurations, an abrupt transition to the network phase was obtained.

Traffic Signal Synchronization in the Saturated High-Density Grid Road Network

PubMed Central

Hu, Xiaojian; Lu, Jian; Wang, Wei; Zhirui, Ye

2015-01-01

Most existing traffic signal synchronization strategies do not perform well in the saturated high-density grid road network (HGRN). Traffic congestion often occurs in the saturated HGRN, and the mobility of the network is difficult to restore. In order to alleviate traffic congestion and to improve traffic efficiency in the network, the study proposes a regional traffic signal synchronization strategy, named the long green and long red (LGLR) traffic signal synchronization strategy. The essence of the strategy is to control the formation and dissipation of queues and to maximize the efficiency of traffic flows at signalized intersections in the saturated HGRN. With this strategy, the same signal control timing plan is used at all signalized intersections in the HGRN, and the straight phase of the control timing plan has a long green time and a long red time. Therefore, continuous traffic flows can be maintained when vehicles travel, and traffic congestion can be alleviated when vehicles stop. Using the strategy, the LGLR traffic signal synchronization model is developed, with the objective of minimizing the number of stops. Finally, the simulation is executed to analyze the performance of the model by comparing it to other models, and the superiority of the LGLR model is evident in terms of delay, number of stops, queue length, and overall performance in the saturated HGRN. PMID:25663835

Periodic fluctuations in correlation-based connectivity density time series: Application to wind speed-monitoring network in Switzerland

NASA Astrophysics Data System (ADS)

Laib, Mohamed; Telesca, Luciano; Kanevski, Mikhail

2018-02-01

In this paper, we study the periodic fluctuations of connectivity density time series of a wind speed-monitoring network in Switzerland. By using the correlogram-based robust periodogram annual periodic oscillations were found in the correlation-based network. The intensity of such annual periodic oscillations is larger for lower correlation thresholds and smaller for higher. The annual periodicity in the connectivity density seems reasonably consistent with the seasonal meteo-climatic cycle.

High frequency sound propagation in a network of interconnecting streets

NASA Astrophysics Data System (ADS)

Hewett, D. P.

2012-12-01

We propose a new model for the propagation of acoustic energy from a time-harmonic point source through a network of interconnecting streets in the high frequency regime, in which the wavelength is small compared to typical macro-lengthscales such as street widths/lengths and building heights. Our model, which is based on geometrical acoustics (ray theory), represents the acoustic power flow from the source along any pathway through the network as the integral of a power density over the launch angle of a ray emanating from the source, and takes into account the key phenomena involved in the propagation, namely energy loss by wall absorption, energy redistribution at junctions, and, in 3D, energy loss to the atmosphere. The model predicts strongly anisotropic decay away from the source, with the power flow decaying exponentially in the number of junctions from the source, except along the axial directions of the network, where the decay is algebraic.

Accelerated reliability testing of highly aligned single-walled carbon nanotube networks subjected to DC electrical stressing.

PubMed

Strus, Mark C; Chiaramonti, Ann N; Kim, Young Lae; Jung, Yung Joon; Keller, Robert R

2011-07-01

We investigate the electrical reliability of nanoscale lines of highly aligned, networked, metallic/semiconducting single-walled carbon nanotubes (SWCNTs) fabricated through a template-based fluidic assembly process. We find that these SWCNT networks can withstand DC current densities larger than 10 MA cm(-2) for several hours and, in some cases, several days. We develop test methods that show that the degradation rate, failure predictability and total device lifetime can be linked to the initial resistance. Scanning electron and transmission electron microscopy suggest that fabrication variability plays a critical role in the rate of degradation, and we offer an empirical method of quickly determining the long-term performance of a network. We find that well-fabricated lines subject to constant electrical stress show a linear accumulation of damage reminiscent of electromigration in metallic interconnects, and we explore the underlying physical mechanisms that could cause such behavior.

Community coalitions as a system: effects of network change on adoption of evidence-based substance abuse prevention.

PubMed

Valente, Thomas W; Chou, Chich Ping; Pentz, Mary Ann

2007-05-01

We examined the effect of community coalition network structure on the effectiveness of an intervention designed to accelerate the adoption of evidence-based substance abuse prevention programs. At baseline, 24 cities were matched and randomly assigned to 3 conditions (control, satellite TV training, and training plus technical assistance). We surveyed 415 community leaders at baseline and 406 at 18-month follow-up about their attitudes and practices toward substance abuse prevention programs. Network structure was measured by asking leaders whom in their coalition they turned to for advice about prevention programs. The outcome was a scale with 4 subscales: coalition function, planning, achievement of benchmarks, and progress in prevention activities. We used multiple linear regression and path analysis to test hypotheses. Intervention had a significant effect on decreasing the density of coalition networks. The change in density subsequently increased adoption of evidence-based practices. Optimal community network structures for the adoption of public health programs are unknown, but it should not be assumed that increasing network density or centralization are appropriate goals. Lower-density networks may be more efficient for organizing evidence-based prevention programs in communities.

Hierarchical MoS2 nanowires/NiCo2O4 nanosheets supported on Ni foam for high-performance asymmetric supercapacitors

NASA Astrophysics Data System (ADS)

Wen, Shiyang; Liu, Yu; Zhu, Fangfang; Shao, Rong; Xu, Wei

2018-01-01

The hierarchical MoS2 nanowires/NiCo2O4 nanosheets (MS/NCO) supercapacitor electrode materials supported on Ni foam were synthesized by a two-step hydrothermal method. The capacitance was investigated by using various electrochemical methods including cyclic voltammetry, constant-current galvanostatic charge/discharge curves and electrochemical impedance spectroscopy. The MS/NCO networks show 7 times more capacitance (7.1 F cm-2) than pure NiCo2O4 nanosheets by CV at a scan rate of 2 mV s-1. The specific capacitance of the assembled MS/NCO//active carbon (AC) asymmetric supercapacitor could reach up to 51.7 F g-1 at a current density of 1.5 A g-1. Also, the maximum energy density of 18.4 W h kg-1 at a power density of 1200.2 W kg-1 was achieved, with 98.2% specific capacitance retention after 8000 cycles. These exciting results exhibit potential application in developing energy storage devices with high energy density and high power density.

Untangling Word Webs: Graph Theory and the Notion of Density in Second Language Word Association Networks.

ERIC Educational Resources Information Center

Wilks, Clarissa; Meara, Paul

2002-01-01

Examines the implications of the metaphor of the vocabulary network. Takes a formal approach to the exploration of this metaphor by applying the principles of graph theory to word association data to compare the relative densities of the first language and second language lexical networks. (Author/VWL)

Adaptive Dynamics, Control, and Extinction in Networked Populations

DTIC Science & Technology

2015-07-09

network geometries. From the pre-history of paths that go extinct, a density function is created from the prehistory of these paths, and a clear local...density plots of Fig. 3b. Using the IAMM to compute the most probable path and comparing it to the prehistory of extinction events on stochastic networks

Keypoint Density-Based Region Proposal for Fine-Grained Object Detection and Classification Using Regions with Convolutional Neural Network Features

DTIC Science & Technology

2015-12-15

Keypoint Density-based Region Proposal for Fine-Grained Object Detection and Classification using Regions with Convolutional Neural Network ... Convolutional Neural Networks (CNNs) enable them to outperform conventional techniques on standard object detection and classification tasks, their...detection accuracy and speed on the fine-grained Caltech UCSD bird dataset (Wah et al., 2011). Recently, Convolutional Neural Networks (CNNs), a deep

Chaotic evolution of prisoner's dilemma game with volunteering on interdependent networks

NASA Astrophysics Data System (ADS)

Luo, Chao; Zhang, Xiaolin; Zheng, YuanJie

2017-06-01

In this article, the evolution of prisoner's dilemma game with volunteering on interdependent networks is investigated. Different from the traditional two-strategy game, voluntary participation as an additional strategy is involved in repeated game, that can introduce more complex evolutionary dynamics. And, interdependent networks provide a more generalized network architecture to study the intricate variability of dynamics. We have showed that voluntary participation could effectively promote the density of co-operation, that is also greatly affected by interdependent strength between two coupled networks. We further discussed the influence of interdependent strength on the densities of different strategies and found that an intermediate interdependence would play a bigger role on the evolution of dynamics. Subsequently, the critical values of the defection temptation for phase transitions under different conditions have been studied. Moreover, the global oscillations induced by the circle of dominance of three strategies on interdependent networks have been quantitatively investigated. Counter-intuitively, the oscillations of strategy densities are not periodic or stochastic, but have rich dynamical behaviors. By means of various analysis tools, we have demonstrated the global oscillations of strategy densities possessed chaotic characteristics.

A single-walled carbon nanotubes/poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate)/copper hexacyanoferrate hybrid film for high-volumetric performance flexible supercapacitors

NASA Astrophysics Data System (ADS)

Li, Jianmin; Li, Haizeng; Li, Jiahui; Wu, Guiqing; Shao, Yuanlong; Li, Yaogang; Zhang, Qinghong; Wang, Hongzhi

2018-05-01

Volumetric energy density is generally considered to be detrimental to the actual application of supercapacitors, which has provoked a range of research work on increasing the packing density of electrodes. Herein, we fabricate a free-standing single-walled carbon nanotubes (SWCNTs)/poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS)/copper hexacyanoferrate (CuHCF) nanoparticles (NPs) composite supercapacitor electrode, with a high packing density of 2.67 g cm-3. The pseudocapacitive CuHCF NPs are decorated onto the SWCNTs/PEDOT:PSS networks and filled in interspace to increase both of packing density and specific capacitance. This hybrid electrode exhibits a series of outstanding performances, such as high electric conductivity, ultrahigh areal and volumetric capacitances (969.8 mF cm-2 and 775.2 F cm-3 at scan rate of 5 mV s-1), long cycle life and superior rate capability. The asymmetric supercapacitor built by using the SWCNTs/PEDOT:PSS/CuHCF film as positive electrode and Mo-doped WO3/SWCNTs film as negative electrode, can deliver a high energy density of 30.08 Wh L-1 with a power density of 4.25 kW L-1 based on the total volume of the device. The approach unveiled in this study could provide important insights to improving the volumetric performance of energy storage devices and help to reach the critical targets for high rate and high power density demand applications.

Fiber networks amplify active stress

PubMed Central

Ronceray, Pierre; Broedersz, Chase P.

2016-01-01

Large-scale force generation is essential for biological functions such as cell motility, embryonic development, and muscle contraction. In these processes, forces generated at the molecular level by motor proteins are transmitted by disordered fiber networks, resulting in large-scale active stresses. Although these fiber networks are well characterized macroscopically, this stress generation by microscopic active units is not well understood. Here we theoretically study force transmission in these networks. We find that collective fiber buckling in the vicinity of a local active unit results in a rectification of stress towards strongly amplified isotropic contraction. This stress amplification is reinforced by the networks’ disordered nature, but saturates for high densities of active units. Our predictions are quantitatively consistent with experiments on reconstituted tissues and actomyosin networks and shed light on the role of the network microstructure in shaping active stresses in cells and tissue. PMID:26921325

A high energy and power Li-ion capacitor based on a TiO2 nanobelt array anode and a graphene hydrogel cathode.

PubMed

Wang, Huanwen; Guan, Cao; Wang, Xuefeng; Fan, Hong Jin

2015-03-25

A novel hybrid Li-ion capacitor (LIC) with high energy and power densities is constructed by combining an electrochemical double layer capacitor type cathode (graphene hydrogels) with a Li-ion battery type anode (TiO(2) nanobelt arrays). The high power source is provided by the graphene hydrogel cathode, which has a 3D porous network structure and high electrical conductivity, and the counter anode is made of free-standing TiO(2) nanobelt arrays (NBA) grown directly on Ti foil without any ancillary materials. Such a subtle designed hybrid Li-ion capacitor allows rapid electron and ion transport in the non-aqueous electrolyte. Within a voltage range of 0.0-3.8 V, a high energy of 82 Wh kg(-1) is achieved at a power density of 570 W kg(-1). Even at an 8.4 s charge/discharge rate, an energy density as high as 21 Wh kg(-1) can be retained. These results demonstrate that the TiO(2) NBA//graphene hydrogel LIC exhibits higher energy density than supercapacitors and better power density than Li-ion batteries, which makes it a promising electrochemical power source. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Optimal interdependence between networks for the evolution of cooperation.

PubMed

Wang, Zhen; Szolnoki, Attila; Perc, Matjaž

2013-01-01

Recent research has identified interactions between networks as crucial for the outcome of evolutionary games taking place on them. While the consensus is that interdependence does promote cooperation by means of organizational complexity and enhanced reciprocity that is out of reach on isolated networks, we here address the question just how much interdependence there should be. Intuitively, one might assume the more the better. However, we show that in fact only an intermediate density of sufficiently strong interactions between networks warrants an optimal resolution of social dilemmas. This is due to an intricate interplay between the heterogeneity that causes an asymmetric strategy flow because of the additional links between the networks, and the independent formation of cooperative patterns on each individual network. Presented results are robust to variations of the strategy updating rule, the topology of interdependent networks, and the governing social dilemma, thus suggesting a high degree of universality.

Optimal interdependence between networks for the evolution of cooperation

PubMed Central

Wang, Zhen; Szolnoki, Attila; Perc, Matjaž

2013-01-01

Recent research has identified interactions between networks as crucial for the outcome of evolutionary games taking place on them. While the consensus is that interdependence does promote cooperation by means of organizational complexity and enhanced reciprocity that is out of reach on isolated networks, we here address the question just how much interdependence there should be. Intuitively, one might assume the more the better. However, we show that in fact only an intermediate density of sufficiently strong interactions between networks warrants an optimal resolution of social dilemmas. This is due to an intricate interplay between the heterogeneity that causes an asymmetric strategy flow because of the additional links between the networks, and the independent formation of cooperative patterns on each individual network. Presented results are robust to variations of the strategy updating rule, the topology of interdependent networks, and the governing social dilemma, thus suggesting a high degree of universality. PMID:23959086

Oxidizing and Scavenging Characteristics of April Rains - OSCAR data report

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

Benkovitz, C.M.; Evans, V.A.; Tichler, J.L.

The organization of this report is as follows: Chapter 1 presents a description of the OSCAR experiment, including its objectives, design, and field deployment. Chapter 2 presents the OSCAR Central Data Coordination function and summarizes the tasks needed to compile each data set. Chapters 3 through 6 address each of the four OSCAR events. A synoptic description of each event is presented in these chapters, followed by a summary of the data captured during the event. Chapter 3 and Appendices C-G then present detailed tabular and graphical displays of the data captured during this event by the intermediate-density precipitation chemistrymore » network, the BNL aircraft and the surface air chemistry measurements conducted by BNL and by state/province agency networks. Data from the high-density precipitation chemistry network are being presented in a separate series of reports by Pacific Northwest Laboratory. Detailed displays of the data for events 2 to 4 have not been included in this report; however, selected portions could be developed for interested parties.« less

Communication of brain network core connections altered in behavioral variant frontotemporal dementia but possibly preserved in early-onset Alzheimer's disease

NASA Astrophysics Data System (ADS)

Daianu, Madelaine; Jahanshad, Neda; Mendez, Mario F.; Bartzokis, George; Jimenez, Elvira E.; Thompson, Paul M.

2015-03-01

Diffusion imaging and brain connectivity analyses can assess white matter deterioration in the brain, revealing the underlying patterns of how brain structure declines. Fiber tractography methods can infer neural pathways and connectivity patterns, yielding sensitive mathematical metrics of network integrity. Here, we analyzed 1.5-Tesla wholebrain diffusion-weighted images from 64 participants - 15 patients with behavioral variant frontotemporal dementia (bvFTD), 19 with early-onset Alzheimer's disease (EOAD), and 30 healthy elderly controls. Using whole-brain tractography, we reconstructed structural brain connectivity networks to map connections between cortical regions. We evaluated the brain's networks focusing on the most highly central and connected regions, also known as hubs, in each diagnostic group - specifically the "high-cost" structural backbone used in global and regional communication. The high-cost backbone of the brain, predicted by fiber density and minimally short pathways between brain regions, accounted for 81-92% of the overall brain communication metric in all diagnostic groups. Furthermore, we found that the set of pathways interconnecting high-cost and high-capacity regions of the brain's communication network are globally and regionally altered in bvFTD, compared to healthy participants; however, the overall organization of the high-cost and high-capacity networks were relatively preserved in EOAD participants, relative to controls. Disruption of the major central hubs that transfer information between brain regions may impair neural communication and functional integrity in characteristic ways typical of each subtype of dementia.

High-performance solid state supercapacitors assembling graphene interconnected networks in porous silicon electrode by electrochemical methods using 2,6-dihydroxynaphthalen.

PubMed

Romanitan, Cosmin; Varasteanu, Pericle; Mihalache, Iuliana; Culita, Daniela; Somacescu, Simona; Pascu, Razvan; Tanasa, Eugenia; Eremia, Sandra A V; Boldeiu, Adina; Simion, Monica; Radoi, Antonio; Kusko, Mihaela

2018-06-25

The challenge for conformal modification of the ultra-high internal surface of nanoporous silicon was tackled by electrochemical polymerisation of 2,6-dihydroxynaphthalene using cyclic voltammetry or potentiometry and, notably, after the thermal treatment (800 °C, N 2 , 4 h) an assembly of interconnected networks of graphene strongly adhering to nanoporous silicon matrix resulted. Herein we demonstrate the achievement of an easy scalable technology for solid state supercapacitors on silicon, with excellent electrochemical properties. Accordingly, our symmetric supercapacitors (SSC) showed remarkable performance characteristics, comparable to many of the best high-power and/or high-energy carbon-based supercapacitors, their figures of merit matching under battery-like supercapacitor behaviour. Furthermore, the devices displayed high specific capacity values along with enhanced capacity retention even at ultra-high rates for voltage sweep, 5 V/s, or discharge current density, 100 A/g, respectively. The cycling stability tests performed at relatively high discharge current density of 10 A/g indicated good capacity retention, with a superior performance demonstrated for the electrodes obtained under cyclic voltammetry approach, which may be ascribed on the one hand to a better coverage of the porous silicon substrate and, on the other hand, to an improved resilience of the hybrid electrode to pore clogging.

High-energy supercapacitors based on hierarchical porous carbon with an ultrahigh ion-accessible surface area in ionic liquid electrolytes.

PubMed

Zhong, Hui; Xu, Fei; Li, Zenghui; Fu, Ruowen; Wu, Dingcai

2013-06-07

A very important yet really challenging issue to address is how to greatly increase the energy density of supercapacitors to approach or even exceed those of batteries without sacrificing the power density. Herein we report the fabrication of a new class of ultrahigh surface area hierarchical porous carbon (UHSA-HPC) based on the pore formation and widening of polystyrene-derived HPC by KOH activation, and highlight its superior ability for energy storage in supercapacitors with ionic liquid (IL) as electrolyte. The UHSA-HPC with a surface area of more than 3000 m(2) g(-1) shows an extremely high energy density, i.e., 118 W h kg(-1) at a power density of 100 W kg(-1). This is ascribed to its unique hierarchical nanonetwork structure with a large number of small-sized nanopores for IL storage and an ideal meso-/macroporous network for IL transfer.

Neural network hardware and software solutions for sorting of waste plastics for recycling

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

Stanton, S.L.; Alam, M.K.; Hebner, G.A.

1992-12-31

While plastic recycling efforts have expanded during the past several years, the cost of recovering plastics is still a major impediment for recyclers. Several factors contribute to the prohibitive cost of recycled resins, including the present low marketability of products made with mixed recycled materials, and costs of collecting, sorting and reprocessing plastic materials. A method for automatic sorting of post-consumer plastics into pure polymer streams is needed to overcome the inaccuracies and low product throughput of the currently used method of hand sorting of waste plastics for recycling. The Society of Plastics has designated seven categories as recyclable: Polyethylenemore » terephthalate (PET); High Density Polyethylene (HDPE); Polyvinyl Chloride (PVC); Low Density Polyethylene (LDPE); Polypropylene (PP); Polystyrene (PS); and Other (mixtures, layered items, etc.). With these categories in mind, a system for sorting of waste plastics using near-infrared reflectance spectra and a backpropagation neural network classifier has been developed. A solution has been demonstrated in the laboratory using a high resolution, and relatively slow instrument. A faster instrument is being developed at this time. Neural network hardware options have been evaluated for use in a real-time industrial system. In the lab, a Fourier transform Near Infrared (FT-NIR) scanning spectrometer was used to gather reflectance data from various locations on samples of actual waste plastics. Neural networks were trained off-line with this data using the NeuralWorks Professional II Plus software package on a SparcStation 2. One of the successfully trained networks was used to compare the neural accelerator hardware options available. The results of running this ``worst case`` network on the neural network hardware will be presented. The AT&T ANNA chip and the Intel 80170NX chip development system were used to determine the ease of implementation and accuracies for this network.« less

Neural network hardware and software solutions for sorting of waste plastics for recycling

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

Stanton, S.L.; Alam, M.K.; Hebner, G.A.

1992-01-01

While plastic recycling efforts have expanded during the past several years, the cost of recovering plastics is still a major impediment for recyclers. Several factors contribute to the prohibitive cost of recycled resins, including the present low marketability of products made with mixed recycled materials, and costs of collecting, sorting and reprocessing plastic materials. A method for automatic sorting of post-consumer plastics into pure polymer streams is needed to overcome the inaccuracies and low product throughput of the currently used method of hand sorting of waste plastics for recycling. The Society of Plastics has designated seven categories as recyclable: Polyethylenemore » terephthalate (PET); High Density Polyethylene (HDPE); Polyvinyl Chloride (PVC); Low Density Polyethylene (LDPE); Polypropylene (PP); Polystyrene (PS); and Other (mixtures, layered items, etc.). With these categories in mind, a system for sorting of waste plastics using near-infrared reflectance spectra and a backpropagation neural network classifier has been developed. A solution has been demonstrated in the laboratory using a high resolution, and relatively slow instrument. A faster instrument is being developed at this time. Neural network hardware options have been evaluated for use in a real-time industrial system. In the lab, a Fourier transform Near Infrared (FT-NIR) scanning spectrometer was used to gather reflectance data from various locations on samples of actual waste plastics. Neural networks were trained off-line with this data using the NeuralWorks Professional II Plus software package on a SparcStation 2. One of the successfully trained networks was used to compare the neural accelerator hardware options available. The results of running this worst case'' network on the neural network hardware will be presented. The AT T ANNA chip and the Intel 80170NX chip development system were used to determine the ease of implementation and accuracies for this network.« less

Sharing-based social capital associated with harvest production and wealth in the Canadian Arctic

PubMed Central

2018-01-01

Social institutions that facilitate sharing and redistribution may help mitigate the impact of resource shocks. In the North American Arctic, traditional food sharing may direct food to those who need it and provide a form of natural insurance against temporal variability in hunting returns within households. Here, network properties that facilitate resource flow (network size, quality, and density) are examined in a country food sharing network comprising 109 Inuit households from a village in Nunavik (Canada), using regressions to investigate the relationships between these network measures and household socioeconomic attributes. The results show that although single women and elders have larger networks, the sharing network is not structured to prioritize sharing towards households with low food availability. Rather, much food sharing appears to be driven by reciprocity between high-harvest households, meaning that poor, low-harvest households tend to have less sharing-based social capital than more affluent, high-harvest households. This suggests that poor, low-harvest households may be more vulnerable to disruptions in the availability of country food. PMID:29529040

Urban MEMS based seismic network for post-earthquakes rapid disaster assessment

NASA Astrophysics Data System (ADS)

D'Alessandro, A.; Luzio, D.; D'Anna, G.

2014-09-01

In this paper, we introduce a project for the realization of the first European real-time urban seismic network based on Micro Electro-Mechanical Systems (MEMS) technology. MEMS accelerometers are a highly enabling technology, and nowadays, the sensitivity and the dynamic range of these sensors are such as to allow the recording of earthquakes of moderate magnitude even at a distance of several tens of kilometers. Moreover, thanks to their low cost and smaller size, MEMS accelerometers can be easily installed in urban areas in order to achieve an urban seismic network constituted by high density of observation points. The network is being implemented in the Acireale Municipality (Sicily, Italy), an area among those with the highest hazard, vulnerability and exposure to the earthquake of the Italian territory. The main objective of the implemented urban network will be to achieve an effective system for post-earthquake rapid disaster assessment. The earthquake recorded, also that with moderate magnitude will be used for the effective seismic microzonation of the area covered by the network. The implemented system will be also used to realize a site-specific earthquakes early warning system.

Game-Theoretical Design of an Adaptive Distributed Dissemination Protocol for VANETs.

PubMed

Iza-Paredes, Cristhian; Mezher, Ahmad Mohamad; Aguilar Igartua, Mónica; Forné, Jordi

2018-01-19

Road safety applications envisaged for Vehicular Ad Hoc Networks (VANETs) depend largely on the dissemination of warning messages to deliver information to concerned vehicles. The intended applications, as well as some inherent VANET characteristics, make data dissemination an essential service and a challenging task in this kind of networks. This work lays out a decentralized stochastic solution for the data dissemination problem through two game-theoretical mechanisms. Given the non-stationarity induced by a highly dynamic topology, diverse network densities, and intermittent connectivity, a solution for the formulated game requires an adaptive procedure able to exploit the environment changes. Extensive simulations reveal that our proposal excels in terms of number of transmissions, lower end-to-end delay and reduced overhead while maintaining high delivery ratio, compared to other proposals.

Game-Theoretical Design of an Adaptive Distributed Dissemination Protocol for VANETs

PubMed Central

Mezher, Ahmad Mohamad; Aguilar Igartua, Mónica

2018-01-01

Road safety applications envisaged for Vehicular Ad Hoc Networks (VANETs) depend largely on the dissemination of warning messages to deliver information to concerned vehicles. The intended applications, as well as some inherent VANET characteristics, make data dissemination an essential service and a challenging task in this kind of networks. This work lays out a decentralized stochastic solution for the data dissemination problem through two game-theoretical mechanisms. Given the non-stationarity induced by a highly dynamic topology, diverse network densities, and intermittent connectivity, a solution for the formulated game requires an adaptive procedure able to exploit the environment changes. Extensive simulations reveal that our proposal excels in terms of number of transmissions, lower end-to-end delay and reduced overhead while maintaining high delivery ratio, compared to other proposals. PMID:29351255

Mercury sulphide dimorphism in glasses

DOE PAGES

Kassem, Mohammad; Sokolov, Anton; Cuisset, Arnault; ...

2016-05-23

Crystals usually exist in several polymorphic forms in different domains of the P,T-diagram. Glasses and liquids also reveal density- or entropy-driven polyamorphism when e.g. an amorphous molecular solid or liquid transforms into a network polymorph. Using pulsed neutron and high-energy X-ray diffraction, we show that mercury sulphide exists simultaneously in two polymorphic modifications in a glass network forming chain-like and tetrahedral motifs. DFT simulations of 4-fold coordinated mercury species and RMC modelling of high-resolution diffraction data provide additional details on local Hg environment and connectivity implying the (HgS2/2)m oligomeric chains (1 m 6) are acting as a network former whilemore » the HgS4/4-related mixed agglomerated units behave as a modifier« less

Foldable, High Energy Density Lithium Ion Batteries

NASA Astrophysics Data System (ADS)

Suresh, Shravan

Lithium Ion Batteries (LIBs) have become ubiquitous owing to its low cost, high energy density and, power density. Due to these advantages, LIBs have garnered a lot of attention as the primary energy storage devices in consumer electronics and electric vehicles. Recent advances in the consumer electronics research and, the drive to reduce greenhouse gases have created a demand for a shape conformable, high energy density batteries. This thesis focuses on the aforementioned two aspects of LIBs: (a) shape conformability (b) energy density and provides potential solutions to enhance them. This thesis is divided into two parts viz. (i) achieving foldability in batteries and, (ii) improving its energy density. Conventional LIBs are not shape conformable due to two limitations viz. inelasticity of metallic foils, and delamination of the active materials while bending. In the first part of the thesis (in Chapter 3), this problem is solved by replacing metallic current collector with Carbon Nanotube Macrofilms (CNMs). CNMs are superelastic films comprising of porous interconnected nanotube network. Using Molecular Dynamics (MD) simulation, we found that in the presence of an interconnected nanotube network CNMs can be fully folded. This is because the resultant stress due to bending and, the effective bending angle at the interface is reduced due to the network of nanotubes. Hence, unlike an isolated nanotube (which ruptures beyond 120 degrees of bending), a network of nanotubes can be completely folded. Thus, by replacing metallic current collector foils with CNMs, the flexibility limitation of a conventional LIB can be transcended. The second part of this thesis focusses on enhancing the energy density of LIBs. Two strategies adopted to achieve this goal are (a) removing the dead weight of the batteries, and (b) incorporating high energy density electrode materials. By incorporating CNMs, the weight of the batteries was reduced by 5-10 times due to low mass loading of CNMs (0.7 mg/cm2) as compared to metallic foils (5-10 mg/cm2). We show that the energy density of the fully foldable battery with CMF current collectors can be up to 2-fold higher than conventional LIBs at realistic mass loading (5mg/cm2) of the electrode materials. Therefore, not only does the CMF impart shape conformability, it also significantly boosts the energy density of the device by removing the dead weight of the batteries. Silicon (Si) shows enormous potential as the next generation anode material in Lithium-ion batteries due to its high energy denisty. However, Si is highly brittle, and in an effort to prevent Si from fracturing, the research community has migrated from the use of Si films to Si nanoparticle based electrodes. Such a strategy significantly reduces volumetric energy density due to the porosity of Si nanoparticle electrodes. In Chapters 4 and 5, we propose two solutions to incorporate Si films in foldable batteries. We show that contrary to conventional wisdom, Si films can be stabilized by two strategies: (a) anchoring the Si films to a carbon nanotube macrofilm (CNM) current-collector and (b) draping the films with a graphene monolayer. After electrochemical cycling, the graphene-coated Si films on CNM resembled a tough mud-cracked surface in which the graphene capping layer suppresses delamination and stabilizes the solid electrolyte interface by creating a slippery interface and reducing the stress transfer across the interface. The graphene-draped Si films on CNM exhibit long cycle life (> 1000 charge/discharge steps) with an average specific capacity of 806 mAh/g. The volumetric capacity averaged over 1000 cycles of charge/discharge is 2821 mAh/cm3 which is 2 to 5 times higher than what is reported in the literature for Si nanoparticle based electrodes. The graphene-draped Si anode could also be successfully cycled against commercial cathodes in a full-cell configuration. In Chapter 5, an alternate strategy has been explored to stabilize Si films by utilizing the role of a slippery interface in stabilizing Si. In this study, graphene films were used as a buffer layer on which Si films were deposited. Here, instead of a highly elastic matrix (as seen in Chapter 4), a slippery interface was used to stabilize Si. It was observed that due to the slippery interface, the Si films were stable and could retain a capacity of 900 mAh/g. These Si films also possessed a volumetric capacity of 5462 mAh/cm3. On the other hand, Si films with a rigid interface were completely eviscerated with a capacity retention of only 180 mAh/g. Thus, this thesis presents new ideas to achieve foldable high energy density Lithium Ion Battery. We also hope that this thesis serves as a platform for researchers to further explore this field.

A Low Cost High Density Sensor Network for Air Quality at London Heathrow Airport

NASA Astrophysics Data System (ADS)

Bright, V.; Mead, M. I.; Popoola, O. A.; Baron, R. P.; Saffell, J.; Stewart, G.; Kaye, P.; Jones, R.

2012-12-01

Atmospheric composition within urban areas has a direct effect on the air quality of an environment in which a large majority of people live and work. Atmospheric pollutants including ozone (O3), nitrogen dioxide (NO2), volatile organic compounds (VOCs) and particulate matter (PM) can have a significant effect on human health. As such it is important to determine the potential exposure of individuals to these atmospheric constituents and investigate the processes that lead to the degradation of air quality within the urban environment. Whilst modelled pollutant levels on the local scale often suggest high degrees of spatial and temporal variability, the relatively sparse fixed site automated urban networks only provide low spatial resolution data that do not appear adequate in detecting such small scale variability. In this paper we demonstrate that measurements can now be made using networks of low-cost sensors that utilise a variety of techniques, including electrochemical and optical, to measure concentrations of atmospheric species. Once equipped with GPS and GPRS to determine position and transmit data respectively, these networks have the potential to provide valuable insights into pollutant variability inherent on the local or micro-scale. The methodology has been demonstrated successfully in field campaigns carried out in cities including London and Valencia, and is now being deployed as part of the Sensor Networks for Air Quality currently deployed at London Heathrow airport (SNAQ-Heathrow) which is outlined in the partner paper presented by Mead et al. (this conference). The SNAQ-Heathrow network of 50 sensor nodes will provide an unprecedented data set that includes measurements of O3, NO, NO2, CO, CO2, SO2, total VOCs, size-speciated PM as well as meteorological variables that include temperature, relative humidity, wind speed and direction. This network will provide high temporal (20 second intervals) and spatial (50 sites within the airport area) resolution data over a 12 month period with data transmitted back to a server every 2 hours. In this paper we present the data capture and storage, data accessibility, data mining and visualisation techniques applied to the measurements of the SNAQ Heathrow high density sensor network, the preliminary results of which provide an insight into the potential use of such networks in characterising air quality, emissions and validating dispersion models on local scales. We also present a web based interface developed for the sensor network that allows users to access archived data and assess meteorological conditions, atmospheric dispersion, pollutant levels and emission rates.

Elastic properties of compressed emulsions

NASA Astrophysics Data System (ADS)

Jorjadze, Ivane; Brujic, Jasna

2012-02-01

Visualizing the packing of a dense emulsion in 3D as a function of the external pressure allows us to characterize the geometry and the local stress distribution inside this jammed system. We first test the scaling laws of the pressure and average coordination number over two orders of magnitude in density. We find deviations from theoretical exponents due to the non-affine motion of the particles. Second, we observe that the distribution of forces changes from a broad exponential at the jamming point to a narrower Gaussian-like distribution under high compression. Finally, we calculate the density of states from the measured force network in the approximation of a harmonic potential. Close to jamming, the number of low frequency modes is high, while the application of pressure shifts the distribution to higher frequencies, indicative of a rigid network. The confocal images reveal the structural features associated with the low frequency modes, as well as their localization within the packing. These data are then compared with published results from numerical simulations.

Thermal management methods for compact high power LED arrays

NASA Astrophysics Data System (ADS)

Christensen, Adam; Ha, Minseok; Graham, Samuel

2007-09-01

The package and system level temperature distributions of a high power (>1W) light emitting diode (LED) array has been investigated using numerical heat flow models. For this analysis, a thermal resistor network model was combined with a 3D finite element submodel of an LED structure to predict system and die level temperatures. The impact of LED array density, LED power density, and active versus passive cooling methods on device operation were calculated. In order to help understand the role of various thermal resistances in cooling such compact arrays, the thermal resistance network was analyzed in order to estimate the contributions from materials as well as active and passive cooling schemes. An analysis of thermal stresses and residual stresses in the die are also calculated based on power dissipation and convection heat transfer coefficients. Results show that the thermal stress in the GaN layer are compressive which can impact the band gap and performance of the LEDs.

Distributed learning automata-based algorithm for community detection in complex networks

NASA Astrophysics Data System (ADS)

Khomami, Mohammad Mehdi Daliri; Rezvanian, Alireza; Meybodi, Mohammad Reza

2016-03-01

Community structure is an important and universal topological property of many complex networks such as social and information networks. The detection of communities of a network is a significant technique for understanding the structure and function of networks. In this paper, we propose an algorithm based on distributed learning automata for community detection (DLACD) in complex networks. In the proposed algorithm, each vertex of network is equipped with a learning automation. According to the cooperation among network of learning automata and updating action probabilities of each automaton, the algorithm interactively tries to identify high-density local communities. The performance of the proposed algorithm is investigated through a number of simulations on popular synthetic and real networks. Experimental results in comparison with popular community detection algorithms such as walk trap, Danon greedy optimization, Fuzzy community detection, Multi-resolution community detection and label propagation demonstrated the superiority of DLACD in terms of modularity, NMI, performance, min-max-cut and coverage.

Association of Internalized and Social Network Level HIV Stigma With High-Risk Condomless Sex Among HIV-Positive African American Men.

PubMed

Wagner, Glenn J; Bogart, Laura M; Klein, David J; Green, Harold D; Mutchler, Matt G; McDavitt, Bryce; Hilliard, Charles

2016-08-01

We examined whether internalized HIV stigma and perceived HIV stigma from social network members (alters), including the most popular and most similar alter, predicted condomless intercourse with negative or unknown HIV status partners among 125 African American HIV-positive men. In a prospective, observational study, participants were administered surveys at baseline and months 6 and 12, with measures including sexual behavior, internalized HIV stigma, and an egocentric social network assessment that included several measures of perceived HIV stigma among alters. In longitudinal multivariable models comparing the relative predictive value of internalized stigma versus various measures of alter stigma, significant predictors of having had condomless intercourse included greater internalized HIV stigma (in all models), the perception that a popular (well-connected) alter or alter most like the participant agrees with an HIV stigma belief, and the interaction of network density with having any alter that agrees with a stigma belief. The interaction indicated that the protective effect of greater density (connectedness between alters) in terms of reduced risk behavior dissipated in the presence of perceived alter stigma. These findings call for interventions that help people living with HIV to cope with their diagnosis and reduce stigma, and inform the targets of social network-based and peer-driven HIV prevention interventions.

Association of Internalized and Social Network Level HIV Stigma With High-Risk Condomless Sex Among HIV-Positive African American Men

PubMed Central

Bogart, Laura M.; Klein, David J.; Green, Harold D.; Mutchler, Matt G.; McDavitt, Bryce; Hilliard, Charles

2016-01-01

We examined whether internalized HIV stigma and perceived HIV stigma from social network members (alters), including the most popular and most similar alter, predicted condomless intercourse with negative or unknown HIV status partners among 125 African American HIV-positive men. In a prospective, observational study, participants were administered surveys at baseline and months 6 and 12, with measures including sexual behavior, internalized HIV stigma, and an egocentric social network assessment that included several measures of perceived HIV stigma among alters. In longitudinal multivariable models comparing the relative predictive value of internalized stigma versus various measures of alter stigma, significant predictors of having had condomless intercourse included greater internalized HIV stigma (in all models), the perception that a popular (well-connected) alter or alter most like the participant agrees with an HIV stigma belief, and the interaction of network density with having any alter that agrees with a stigma belief. The interaction indicated that the protective effect of greater density (connectedness between alters) in terms of reduced risk behavior dissipated in the presence of perceived alter stigma. These findings call for interventions that help people living with HIV to cope with their diagnosis and reduce stigma, and inform the targets of social network-based and peer-driven HIV prevention interventions. PMID:26718361

Anisotropic Dye Adsorption and Anhydrous Proton Conductivity in Smectic Liquid Crystal Networks: The Role of Cross-Link Density, Order, and Orientation.

PubMed

Liang, Ting; van Kuringen, Huub P C; Mulder, Dirk J; Tan, Shuai; Wu, Yong; Borneman, Zandrie; Nijmeijer, Kitty; Schenning, Albertus P H J

2017-10-11

In this work, the decisive role of rigidity, orientation, and order in the smectic liquid crystalline network on the anisotropic proton and adsorbent properties is reported. The rigidity in the hydrogen-bonded polymer network has been altered by changing the cross-link density, the order by using different mesophases (smectic, nematic, and isotropic phases), whereas the orientation of the mesogens was controlled by alignment layers. Adding more cross-linkers improved the integrity of the polymer films. For the proton conduction, an optimum was found in the amount of cross-linker and the smectic organization results in the highest anhydrous proton conduction. The polymer films show anisotropic proton conductivity with a 54 times higher conductivity in the direction perpendicular to the molecular director. After a base treatment of the smectic liquid crystalline network, a nanoporous polymer film is obtained that also shows anisotropic adsorption of dye molecules and again straight smectic pores are favored over disordered pores in nematic and isotropic networks. The highly cross-linked films show size-selective adsorption of dyes. Low cross-linked materials do not show this difference due to swelling, which decreases the order and creates openings in the two-dimensional polymer layers. The latter is, however, beneficial for fast adsorption kinetics.

Automatic breast tissue density estimation scheme in digital mammography images

NASA Astrophysics Data System (ADS)

Menechelli, Renan C.; Pacheco, Ana Luisa V.; Schiabel, Homero

2017-03-01

Cases of breast cancer have increased substantially each year. However, radiologists are subject to subjectivity and failures of interpretation which may affect the final diagnosis in this examination. The high density features in breast tissue are important factors related to these failures. Thus, among many functions some CADx (Computer-Aided Diagnosis) schemes are classifying breasts according to the predominant density. In order to aid in such a procedure, this work attempts to describe automated software for classification and statistical information on the percentage change in breast tissue density, through analysis of sub regions (ROIs) from the whole mammography image. Once the breast is segmented, the image is divided into regions from which texture features are extracted. Then an artificial neural network MLP was used to categorize ROIs. Experienced radiologists have previously determined the ROIs density classification, which was the reference to the software evaluation. From tests results its average accuracy was 88.7% in ROIs classification, and 83.25% in the classification of the whole breast density in the 4 BI-RADS density classes - taking into account a set of 400 images. Furthermore, when considering only a simplified two classes division (high and low densities) the classifier accuracy reached 93.5%, with AUC = 0.95.

Synthesis of carbon core–shell pore structures and their performance as supercapacitors

DOE PAGES

Ariyanto, Teguh; Dyatkin, Boris; Zhang, Gui-Rong; ...

2015-07-15

High-power supercapacitors require excellent electrolyte mobility within the pore network and high electrical conductivity for maximum capacitance and efficiency. Achieving high power typically requires sacrificing energy densities, as the latter demands a high specific surface area and narrow porosity that impedes ion transport. Here, we present a novel solution for this optimization problem: a nanostructured core–shell carbonaceous material that exhibits a microporous carbon core surrounded by a mesoporous, graphitic shell. The tunable synthesis parameters yielded a structure that features either a sharp or a gradual transition between the core and shell sections. Electrochemical supercapacitor testing using organic electrolyte revealed thatmore » these novel core–shell materials outperform carbons with homogeneous pore structures. The hybrid core–shell materials showed a combination of good capacitance retention, typical for the carbon present in the shell and high specific capacitance, typical for the core material. These materials achieved power densities in excess of 40 kW kg -1 at energy densities reaching 27 Wh kg -1.« less

Experimental demonstration of the optical multi-mesh hypercube: scaleable interconnection network for multiprocessors and multicomputers.

PubMed

Louri, A; Furlonge, S; Neocleous, C

1996-12-10

A prototype of a novel topology for scaleable optical interconnection networks called the optical multi-mesh hypercube (OMMH) is experimentally demonstrated to as high as a 150-Mbit/s data rate (2(7) - 1 nonreturn-to-zero pseudo-random data pattern) at a bit error rate of 10(-13)/link by the use of commercially available devices. OMMH is a scaleable network [Appl. Opt. 33, 7558 (1994); J. Lightwave Technol. 12, 704 (1994)] architecture that combines the positive features of the hypercube (small diameter, connectivity, symmetry, simple routing, and fault tolerance) and the mesh (constant node degree and size scaleability). The optical implementation method is divided into two levels: high-density local connections for the hypercube modules, and high-bit-rate, low-density, long connections for the mesh links connecting the hypercube modules. Free-space imaging systems utilizing vertical-cavity surface-emitting laser (VCSEL) arrays, lenslet arrays, space-invariant holographic techniques, and photodiode arrays are demonstrated for the local connections. Optobus fiber interconnects from Motorola are used for the long-distance connections. The OMMH was optimized to operate at the data rate of Motorola's Optobus (10-bit-wide, VCSEL-based bidirectional data interconnects at 150 Mbits/s). Difficulties encountered included the varying fan-out efficiencies of the different orders of the hologram, misalignment sensitivity of the free-space links, low power (1 mW) of the individual VCSEL's, and noise.

Early warning model based on correlated networks in global crude oil markets

NASA Astrophysics Data System (ADS)

Yu, Jia-Wei; Xie, Wen-Jie; Jiang, Zhi-Qiang

2018-01-01

Applying network tools on predicting and warning the systemic risks provides a novel avenue to manage risks in financial markets. Here, we construct a series of global crude oil correlated networks based on the historical 57 oil prices covering a period from 1993 to 2012. Two systemic risk indicators are constructed based on the density and modularity of correlated networks. The local maximums of the risk indicators are found to have the ability to predict the trends of oil prices. In our sample periods, the indicator based on the network density sends five signals and the indicator based on the modularity index sends four signals. The four signals sent by both indicators are able to warn the drop of future oil prices and the signal only sent by the network density is followed by a huge rise of oil prices. Our results deepen the application of network measures on building early warning models of systemic risks and can be applied to predict the trends of future prices in financial markets.

High-density platinum nanoparticle-decorated titanium dioxide nanofiber networks for efficient capillary photocatalytic hydrogen generation

Treesearch

Zhaodong Li; Chunhua Yao; Yi-Cheng Wang; Solomon Mikael; Sundaram Gunasekaran; Zhenqiang Ma; Zhiyong Cai; Xudong Wang

2016-01-01

Aldehyde-functionalized cellulose nanofibers (CNFs) were applied to synthesize Pt nanoparticles (NPs) on CNF surfaces via on-site Pt ion reduction and achieve high concentration and uniform Pt NP loading. ALD could then selectively deposit TiO2 on CNFs and keep the Pt NPs uncovered due to their drastically different hydro-affinity properties. The...

Dynamics and diffusion mechanism of low-density liquid silicon

DOE PAGES

Shen, B.; Wang, Z. Y.; Dong, F.; ...

2015-11-05

A first-order phase transition from a high-density liquid to a low-density liquid has been proposed to explain the various thermodynamic anomies of water. It also has been proposed that such liquid–liquid phase transition would exist in supercooled silicon. Computer simulation studies show that, across the transition, the diffusivity drops roughly 2 orders of magnitude, and the structures exhibit considerable tetrahedral ordering. The resulting phase is a highly viscous, low-density liquid silicon. Investigations on the atomic diffusion of such a novel form of liquid silicon are of high interest. Here we report such diffusion results from molecular dynamics simulations using themore » classical Stillinger–Weber (SW) potential of silicon. We show that the atomic diffusion of the low-density liquid is highly correlated with local tetrahedral geometries. We also show that atoms diffuse through hopping processes within short ranges, which gradually accumulate to an overall random motion for long ranges as in normal liquids. There is a close relationship between dynamical heterogeneity and hopping process. We point out that the above diffusion mechanism is closely related to the strong directional bonding nature of the distorted tetrahedral network. Here, our work offers new insights into the complex behavior of the highly viscous low density liquid silicon, suggesting similar diffusion behaviors in other tetrahedral coordinated liquids that exhibit liquid–liquid phase transition such as carbon and germanium.« less

Bird migration flight altitudes studied by a network of operational weather radars.

PubMed

Dokter, Adriaan M; Liechti, Felix; Stark, Herbert; Delobbe, Laurent; Tabary, Pierre; Holleman, Iwan

2011-01-06

A fully automated method for the detection and quantification of bird migration was developed for operational C-band weather radar, measuring bird density, speed and direction as a function of altitude. These weather radar bird observations have been validated with data from a high-accuracy dedicated bird radar, which was stationed in the measurement volume of weather radar sites in The Netherlands, Belgium and France for a full migration season during autumn 2007 and spring 2008. We show that weather radar can extract near real-time bird density altitude profiles that closely correspond to the density profiles measured by dedicated bird radar. Doppler weather radar can thus be used as a reliable sensor for quantifying bird densities aloft in an operational setting, which--when extended to multiple radars--enables the mapping and continuous monitoring of bird migration flyways. By applying the automated method to a network of weather radars, we observed how mesoscale variability in weather conditions structured the timing and altitude profile of bird migration within single nights. Bird density altitude profiles were observed that consisted of multiple layers, which could be explained from the distinct wind conditions at different take-off sites. Consistently lower bird densities are recorded in The Netherlands compared with sites in France and eastern Belgium, which reveals some of the spatial extent of the dominant Scandinavian flyway over continental Europe.

Bird migration flight altitudes studied by a network of operational weather radars

PubMed Central

Dokter, Adriaan M.; Liechti, Felix; Stark, Herbert; Delobbe, Laurent; Tabary, Pierre; Holleman, Iwan

2011-01-01

A fully automated method for the detection and quantification of bird migration was developed for operational C-band weather radar, measuring bird density, speed and direction as a function of altitude. These weather radar bird observations have been validated with data from a high-accuracy dedicated bird radar, which was stationed in the measurement volume of weather radar sites in The Netherlands, Belgium and France for a full migration season during autumn 2007 and spring 2008. We show that weather radar can extract near real-time bird density altitude profiles that closely correspond to the density profiles measured by dedicated bird radar. Doppler weather radar can thus be used as a reliable sensor for quantifying bird densities aloft in an operational setting, which—when extended to multiple radars—enables the mapping and continuous monitoring of bird migration flyways. By applying the automated method to a network of weather radars, we observed how mesoscale variability in weather conditions structured the timing and altitude profile of bird migration within single nights. Bird density altitude profiles were observed that consisted of multiple layers, which could be explained from the distinct wind conditions at different take-off sites. Consistently lower bird densities are recorded in The Netherlands compared with sites in France and eastern Belgium, which reveals some of the spatial extent of the dominant Scandinavian flyway over continental Europe. PMID:20519212

Reciprocity in directed networks

NASA Astrophysics Data System (ADS)

Yin, Mei; Zhu, Lingjiong

2016-04-01

Reciprocity is an important characteristic of directed networks and has been widely used in the modeling of World Wide Web, email, social, and other complex networks. In this paper, we take a statistical physics point of view and study the limiting entropy and free energy densities from the microcanonical ensemble, the canonical ensemble, and the grand canonical ensemble whose sufficient statistics are given by edge and reciprocal densities. The sparse case is also studied for the grand canonical ensemble. Extensions to more general reciprocal models including reciprocal triangle and star densities will likewise be discussed.

In Situ Growth of Free-Standing All Metal Oxide Asymmetric Supercapacitor.

PubMed

Yin, Bo-Si; Wang, Zhen-Bo; Zhang, Si-Wen; Liu, Chang; Ren, Qing-Qing; Ke, Ke

2016-10-05

Metal oxides have attracted renewed interest in applications as energy storage and conversion devices. Here, a new design is reported to acquire an asymmetric supercapacitor assembled by all free-standing metal oxides. The positive electrode is made of 3D NiO open porous nanoribbons network on nickel foam and the negative electrode is composed of SnO 2 /MnO 2 nanoflakes grown on carbon cloth (CC) substrate. The combination of two metal oxide electrodes which replaced the traditional group of carbon materials together with metal oxide has achieved a higher energy density. The self-supported 3D NiO nanoribbons network demonstrates a high specific capacitance and better cycle performance without obvious mechanical deformation despite of undergoing harsh bulk redox reactions. The SnO 2 /MnO 2 nanoflakes as the pseudocapacitive electrode exhibit a wide range of voltage window (-1 to 1 V), which is conducive to electrochemical energy storage. The (CC/SnO 2 /MnO 2 )(-)//(NiO/Ni foam)(+) asymmetric supercapacitor device delivers an energy density of 64.4 Wh kg -1 (at a power density of 250 W kg -1 ) and two devices in series are applied to light up 24 red LEDs for about 60 s. The outstanding electrochemical properties of the device hold great promise for long-life, high-energy, and high-power energy storage/conversion applications.

Optical interconnect technologies for high-bandwidth ICT systems

NASA Astrophysics Data System (ADS)

Chujo, Norio; Takai, Toshiaki; Mizushima, Akiko; Arimoto, Hideo; Matsuoka, Yasunobu; Yamashita, Hiroki; Matsushima, Naoki

2016-03-01

The bandwidth of information and communication technology (ICT) systems is increasing and is predicted to reach more than 10 Tb/s. However, an electrical interconnect cannot achieve such bandwidth because of its density limits. To solve this problem, we propose two types of high-density optical fiber wiring for backplanes and circuit boards such as interface boards and switch boards. One type uses routed ribbon fiber in a circuit board because it has the ability to be formed into complex shapes to avoid interfering with the LSI and electrical components on the board. The backplane is required to exhibit high density and flexibility, so the second type uses loose fiber. We developed a 9.6-Tb/s optical interconnect demonstration system using embedded optical modules, optical backplane, and optical connector in a network apparatus chassis. We achieved 25-Gb/s transmission between FPGAs via the optical backplane.

Polarizability, optical basicity and optical properties of SiO2B2O3Bi2O3TeO2 glass system

NASA Astrophysics Data System (ADS)

Kashif, I.; Ratep, A.; Adel, Gh.

2018-07-01

Glasses having a composition xSiO2 xB2O3 (95-2 x) Bi2O35TeO2 where x = (5, 10, 15, 20, 25) prepared by the melt-quenching technique. Thermal stability, density, optical transmittance, and the refractive index of these glasses investigated. Glass samples were transparent in the visible to near-infrared (NIR) region and had a high refractive index. A number of glass samples have high glass-forming ability. This indicates that the quarterly glasses are suitable for optical applications in the visible to the NIR region. Bi2O3 substituted by B2O3 and SiO2 on optical properties discussed. It suggested that the substitution of Bi2O3 increased the density, molar volume, the molar polarizability, optical basicity and refractive index in addition to, the oxygen packing density, the optical energy gap, and metallization decrease. These results are helpful for designing new optical glasses controlled to have a higher refractive index. All studied glass presented high nonlinearities, and the addition of network modifiers made a little contribution. Results clarified the bandgap energy reduction, which associated with the growth within the non-bridging oxygen content with the addition of the network modifier. An increase in the refractive index nonlinearity explained by the optical basicity and the high electronic polarizability of the modifier ions.

Effect of the microscopic correlated-pinning landscape on the macroscopic critical current density in YBCO films

NASA Astrophysics Data System (ADS)

Ghigo, G.; Chiodoni, A.; Gerbaldo, R.; Gozzelino, L.; Laviano, F.; Mezzetti, E.; Minetti, B.; Camerlingo, C.

This paper deals with the mechanisms controlling the critical current density vs. field behavior in YBCO films. We base our analysis on a suitable model concerning the existence of a network of intergrain Josephson junctions whose length is modulated by defects. Irradiation with 0.25 GeV Au ions provide a useful tool to check the texture of the sample, in particular to give a gauge length reference to separate “weak” links and high- J c links.

Sustainability and collapse in a coevolutionary model of local resource stocks and behavioral patterns on a social network

NASA Astrophysics Data System (ADS)

Wiedermann, Marc; Donges, Jonathan F.; Heitzig, Jobst; Kurths, Jürgen

2014-05-01

When investigating the causes and consequences of global change, the collective behavior of human beings is considered as having a considerable impact on natural systems. In our work, we propose a conceptual coevolutionary model simulating the dynamics of local renewable resources in interaction with simplistic societal agents exploiting those resources. The society is represented by a social network on which social traits may be transmitted between agents. These traits themselves induce a certain rate of exploitation of the resource, leading either to its depletion or sustainable existence. Traits are exchanged probabilistically according to their instantaneous individual payoff, and hence this process depends on the status of the natural resource. At the same time agents may adaptively restructure their set of acquaintances. Connections with agents having a different trait may be broken while new connections with agents of the same trait are established. We investigate which choices of social parameters, like the frequency of social interaction, rationality and rate of social network adaptation, cause the system to end in a sustainable state and, hence, what can be done to avoid a collapse of the entire system. The importance and influence of the social network structure is analyzed by the variation of link-densities in the underlying network topology and shows significant influence on the expected outcome of the model. For a static network with no adaptation we find a robust phase transition between the two different regimes, sustainable and non-sustainable, which co-exist in parameter space. High connectivity within the social network, e.g., high link-densities, in combination with a fast rate of social learning lead to a likely collapse of the entire co-evolutionary system, whereas slow learning and small network connectivity very likely result in the sustainable existence of the natural resources. Collapse may be avoided by an intelligent rewiring, e.g. adaptation, of the social network that may also lead to the isolation of misbehaving parts of the society. Our results may suggest that with the current trend to faster imitation and ever increasing global network connectivity, societies are becoming more vulnerable to environmental collapse if they remain myopic at the same time.

Effects of Network Characteristics on Reaching the Payoff-Dominant Equilibrium in Coordination Games: A Simulation study.

PubMed

Buskens, Vincent; Snijders, Chris

2016-01-01

We study how payoffs and network structure affect reaching the payoff-dominant equilibrium in a [Formula: see text] coordination game that actors play with their neighbors in a network. Using an extensive simulation analysis of over 100,000 networks with 2-25 actors, we show that the importance of network characteristics is restricted to a limited part of the payoff space. In this part, we conclude that the payoff-dominant equilibrium is chosen more often if network density is larger, the network is more centralized, and segmentation of the network is smaller. Moreover, it is more likely that heterogeneity in behavior persists if the network is more segmented and less centralized. Persistence of heterogeneous behavior is not related to network density.

Central serotonin modulates neural responses to virtual violent actions in emotion regulation networks.

PubMed

Wolf, Dhana; Klasen, Martin; Eisner, Patrick; Zepf, Florian D; Zvyagintsev, Mikhail; Palomero-Gallagher, Nicola; Weber, René; Eisert, Albrecht; Mathiak, Klaus

2018-06-08

Disruptions in the cortico-limbic emotion regulation networks have been linked to depression, anxiety, impulsivity, and aggression. Altered transmission of the central nervous serotonin (5-HT) contributes to dysfunctions in the cognitive control of emotions. To date, studies relating to pharmaco-fMRI challenging of the 5-HT system have focused on emotion processing for facial expressions. We investigated effects of a single-dose selective 5-HT reuptake inhibitor (escitalopram) on emotion regulation during virtual violence. For this purpose, 38 male participants played a violent video game during fMRI scanning. The SSRI reduced neural responses to violent actions in right-hemispheric inferior frontal gyrus and medial prefrontal cortex encompassing the anterior cingulate cortex (ACC), but not to non-violent actions. Within the ACC, the drug effect differentiated areas with high inhibitory 5-HT1A receptor density (subgenual s25) from those with a lower density (pregenual p32, p24). This finding links functional responses during virtual violent actions with 5-HT neurotransmission in emotion regulation networks, underpinning the ecological validity of the 5-HT model in aggressive behavior. Available 5-HT receptor density data suggest that this SSRI effect is only observable when inhibitory and excitatory 5-HT receptors are balanced. The observed early functional changes may impact patient groups receiving SSRI treatment.

Carbon-based supercapacitors produced by activation of graphene.

PubMed

Zhu, Yanwu; Murali, Shanthi; Stoller, Meryl D; Ganesh, K J; Cai, Weiwei; Ferreira, Paulo J; Pirkle, Adam; Wallace, Robert M; Cychosz, Katie A; Thommes, Matthias; Su, Dong; Stach, Eric A; Ruoff, Rodney S

2011-06-24

Supercapacitors, also called ultracapacitors or electrochemical capacitors, store electrical charge on high-surface-area conducting materials. Their widespread use is limited by their low energy storage density and relatively high effective series resistance. Using chemical activation of exfoliated graphite oxide, we synthesized a porous carbon with a Brunauer-Emmett-Teller surface area of up to 3100 square meters per gram, a high electrical conductivity, and a low oxygen and hydrogen content. This sp(2)-bonded carbon has a continuous three-dimensional network of highly curved, atom-thick walls that form primarily 0.6- to 5-nanometer-width pores. Two-electrode supercapacitor cells constructed with this carbon yielded high values of gravimetric capacitance and energy density with organic and ionic liquid electrolytes. The processes used to make this carbon are readily scalable to industrial levels.

Carbon-Based Supercapacitors Produced by Activation of Graphene

NASA Astrophysics Data System (ADS)

Zhu, Yanwu; Murali, Shanthi; Stoller, Meryl D.; Ganesh, K. J.; Cai, Weiwei; Ferreira, Paulo J.; Pirkle, Adam; Wallace, Robert M.; Cychosz, Katie A.; Thommes, Matthias; Su, Dong; Stach, Eric A.; Ruoff, Rodney S.

2011-06-01

Supercapacitors, also called ultracapacitors or electrochemical capacitors, store electrical charge on high-surface-area conducting materials. Their widespread use is limited by their low energy storage density and relatively high effective series resistance. Using chemical activation of exfoliated graphite oxide, we synthesized a porous carbon with a Brunauer-Emmett-Teller surface area of up to 3100 square meters per gram, a high electrical conductivity, and a low oxygen and hydrogen content. This sp2-bonded carbon has a continuous three-dimensional network of highly curved, atom-thick walls that form primarily 0.6- to 5-nanometer-width pores. Two-electrode supercapacitor cells constructed with this carbon yielded high values of gravimetric capacitance and energy density with organic and ionic liquid electrolytes. The processes used to make this carbon are readily scalable to industrial levels.

A Hybrid Cellular Automaton Model of Clonal Evolution in Cancer: The Emergence of the Glycolytic Phenotype

PubMed Central

Gerlee, P.; Anderson, A.R.A.

2009-01-01

We present a cellular automaton model of clonal evolution in cancer aimed at investigating the emergence of the glycolytic phenotype. In the model each cell is equipped with a micro-environment response network that determines the behaviour or phenotype of the cell based on the local environment. The response network is modelled using a feed-forward neural network, which is subject to mutations when the cells divide. This implies that cells might react differently to the environment and when space and nutrients are limited only the fittest cells will survive. With this model we have investigated the impact of the environment on the growth dynamics of the tumour. In particular we have analysed the influence of the tissue oxygen concentration and extra-cellular matrix density on the dynamics of the model. We found that the environment influences both the growth and evolutionary dynamics of the tumour. For low oxygen concentration we observe tumours with a fingered morphology, while increasing the matrix density gives rise to more compact tumours with wider fingers. The distribution of phenotypes in the tumour is also affected, and we observe that the glycolytic phenotype is most likely to emerge in a poorly oxygenated tissue with a high matrix density. Our results suggest that it is the combined effect of the oxygen concentration and matrix density that creates an environment where the glycolytic phenotype has a growth advantage and consequently is most likely to appear. PMID:18068192

Quantifying Complexity in Quantum Phase Transitions via Mutual Information Complex Networks

NASA Astrophysics Data System (ADS)

Valdez, Marc Andrew; Jaschke, Daniel; Vargas, David L.; Carr, Lincoln D.

2017-12-01

We quantify the emergent complexity of quantum states near quantum critical points on regular 1D lattices, via complex network measures based on quantum mutual information as the adjacency matrix, in direct analogy to quantifying the complexity of electroencephalogram or functional magnetic resonance imaging measurements of the brain. Using matrix product state methods, we show that network density, clustering, disparity, and Pearson's correlation obtain the critical point for both quantum Ising and Bose-Hubbard models to a high degree of accuracy in finite-size scaling for three classes of quantum phase transitions, Z2, mean field superfluid to Mott insulator, and a Berzinskii-Kosterlitz-Thouless crossover.

Will HIV Vaccination Reshape HIV Risk Behavior Networks? A Social Network Analysis of Drug Users' Anticipated Risk Compensation

PubMed Central

Young, April M.; Halgin, Daniel S.; DiClemente, Ralph J.; Sterk, Claire E.; Havens, Jennifer R.

2014-01-01

Background An HIV vaccine could substantially impact the epidemic. However, risk compensation (RC), or post-vaccination increase in risk behavior, could present a major challenge. The methodology used in previous studies of risk compensation has been almost exclusively individual-level in focus, and has not explored how increased risk behavior could affect the connectivity of risk networks. This study examined the impact of anticipated HIV vaccine-related RC on the structure of high-risk drug users' sexual and injection risk network. Methods A sample of 433 rural drug users in the US provided data on their risk relationships (i.e., those involving recent unprotected sex and/or injection equipment sharing). Dyad-specific data were collected on likelihood of increasing/initiating risk behavior if they, their partner, or they and their partner received an HIV vaccine. Using these data and social network analysis, a "post-vaccination network" was constructed and compared to the current network on measures relevant to HIV transmission, including network size, cohesiveness (e.g., diameter, component structure, density), and centrality. Results Participants reported 488 risk relationships. Few reported an intention to decrease condom use or increase equipment sharing (4% and 1%, respectively). RC intent was reported in 30 existing risk relationships and vaccination was anticipated to elicit the formation of five new relationships. RC resulted in a 5% increase in risk network size (n = 142 to n = 149) and a significant increase in network density. The initiation of risk relationships resulted in the connection of otherwise disconnected network components, with the largest doubling in size from five to ten. Conclusions This study demonstrates a new methodological approach to studying RC and reveals that behavior change following HIV vaccination could potentially impact risk network connectivity. These data will be valuable in parameterizing future network models that can determine if network-level change precipitated by RC would appreciably impact the vaccine's population-level effectiveness. PMID:24992659

Formation of porous networks on polymeric surfaces by femtosecond laser micromachining

NASA Astrophysics Data System (ADS)

Assaf, Youssef; Kietzig, Anne-Marie

2017-02-01

In this study, porous network structures were successfully created on various polymer surfaces by femtosecond laser micromachining. Six different polymers (poly(tetrafluoroethylene) (PTFE), poly(methyl methacrylate) (PMMA), high density poly(ethylene) (HDPE), poly(lactic acid) (PLA), poly(carbonate) (PC), and poly(ethylene terephthalate) (PET)) were machined at different fluences and pulse numbers, and the resulting structures were identified and compared by lacunarity analysis. At low fluence and pulse numbers, porous networks were confirmed to form on all materials except PLA. Furthermore, all networks except for PMMA were shown to bundle up at high fluence and pulse numbers. In the case of PC, a complete breakdown of the structure at such conditions was observed. Operation slightly above threshold fluence and at low pulse numbers is therefore recommended for porous network formation. Finally, the thickness over which these structures formed was measured and compared to two intrinsic material dependent parameters: the single pulse threshold fluence and the incubation coefficient. Results indicate that a lower threshold fluence at operating conditions favors material removal over structure formation and is hence detrimental to porous network formation. Favorable machining conditions and material-dependent parameters for the formation of porous networks on polymer surfaces have thus been identified.

Diversity Performance Analysis on Multiple HAP Networks.

PubMed

Dong, Feihong; Li, Min; Gong, Xiangwu; Li, Hongjun; Gao, Fengyue

2015-06-30

One of the main design challenges in wireless sensor networks (WSNs) is achieving a high-data-rate transmission for individual sensor devices. The high altitude platform (HAP) is an important communication relay platform for WSNs and next-generation wireless networks. Multiple-input multiple-output (MIMO) techniques provide the diversity and multiplexing gain, which can improve the network performance effectively. In this paper, a virtual MIMO (V-MIMO) model is proposed by networking multiple HAPs with the concept of multiple assets in view (MAV). In a shadowed Rician fading channel, the diversity performance is investigated. The probability density function (PDF) and cumulative distribution function (CDF) of the received signal-to-noise ratio (SNR) are derived. In addition, the average symbol error rate (ASER) with BPSK and QPSK is given for the V-MIMO model. The system capacity is studied for both perfect channel state information (CSI) and unknown CSI individually. The ergodic capacity with various SNR and Rician factors for different network configurations is also analyzed. The simulation results validate the effectiveness of the performance analysis. It is shown that the performance of the HAPs network in WSNs can be significantly improved by utilizing the MAV to achieve overlapping coverage, with the help of the V-MIMO techniques.

Binary synaptic connections based on memory switching in a-Si:H for artificial neural networks

NASA Technical Reports Server (NTRS)

Thakoor, A. P.; Lamb, J. L.; Moopenn, A.; Khanna, S. K.

1987-01-01

A scheme for nonvolatile associative electronic memory storage with high information storage density is proposed which is based on neural network models and which uses a matrix of two-terminal passive interconnections (synapses). It is noted that the massive parallelism in the architecture would require the ON state of a synaptic connection to be unusually weak (highly resistive). Memory switching using a-Si:H along with ballast resistors patterned from amorphous Ge-metal alloys is investigated for a binary programmable read only memory matrix. The fabrication of a 1600 synapse test array of uniform connection strengths and a-Si:H switching elements is discussed.

Report of the panel on international programs

NASA Technical Reports Server (NTRS)

Anderson, Allen Joel; Fuchs, Karl W.; Ganeka, Yasuhiro; Gaur, Vinod; Green, Andrew A.; Siegfried, W.; Lambert, Anthony; Rais, Jacub; Reighber, Christopher; Seeger, Herman

1991-01-01

The panel recommends that NASA participate and take an active role in the continuous monitoring of existing regional networks, the realization of high resolution geopotential and topographic missions, the establishment of interconnection of the reference frames as defined by different space techniques, the development and implementation of automation for all ground-to-space observing systems, calibration and validation experiments for measuring techniques and data, the establishment of international space-based networks for real-time transmission of high density space data in standardized formats, tracking and support for non-NASA missions, and the extension of state-of-the art observing and analysis techniques to developing nations.

Water in the presence of inert Lennard-Jones obstacles

NASA Astrophysics Data System (ADS)

Kurtjak, Mario; Urbic, Tomaz

2014-04-01

Water confined by the presence of a 'sea' of inert obstacles was examined. In the article, freely mobile two-dimensional Mercedes-Benz (MB) water put to a disordered, but fixed, matrix of Lennard-Jones disks was studied by the Monte Carlo computer simulations. For the MB water molecules in the matrix of Lennard-Jones disks, we explored the structures, hydrogen-bond-network formation and thermodynamics as a function of temperature and size and density of matrix particles. We found that the structure of model water is perturbed by the presence of the obstacles. Density of confined water, which was in equilibrium with the bulk water, was smaller than the density of the bulk water and the temperature dependence of the density of absorbed water did not show the density anomaly in the studied temperature range. The behaviour observed as a consequence of confinement is similar to that of increasing temperature, which can for a matrix lead to a process similar to capillary evaporation. At the same occupancy of space, smaller matrix molecules cause higher destruction effect on the absorbed water molecules than the bigger ones. We have also tested the hypothesis that at low matrix densities the obstacles induce an increased ordering and 'hydrogen bonding' of the MB model molecules, relative to pure fluid, while at high densities the obstacles reduce MB water structuring, as they prevent the fluid to form good 'hydrogen-bonding' networks. However, for the size of matrix molecules similar to that of water, we did not observe this effect.

Heterogeneous network promotes species coexistence: metapopulation model for rock-paper-scissors game.

PubMed

Nagatani, Takashi; Ichinose, Genki; Tainaka, Kei-Ichi

2018-05-04

Understanding mechanisms of biodiversity has been a central question in ecology. The coexistence of three species in rock-paper-scissors (RPS) systems are discussed by many authors; however, the relation between coexistence and network structure is rarely discussed. Here we present a metapopulation model for RPS game. The total population is assumed to consist of three subpopulations (nodes). Each individual migrates by random walk; the destination of migration is randomly determined. From reaction-migration equations, we obtain the population dynamics. It is found that the dynamic highly depends on network structures. When a network is homogeneous, the dynamics are neutrally stable: each node has a periodic solution, and the oscillations synchronize in all nodes. However, when a network is heterogeneous, the dynamics approach stable focus and all nodes reach equilibriums with different densities. Hence, the heterogeneity of the network promotes biodiversity.

Automated identification of functional dynamic networks from X-ray crystallography

PubMed Central

van den Bedem, Henry; Bhabha, Gira; Yang, Kun; Wright, Peter E.; Fraser, James S.

2013-01-01

Protein function often depends on the exchange between conformational substates. Allosteric ligand binding or distal mutations can stabilize specific active site conformations and consequently alter protein function. In addition to comparing independently determined X-ray crystal structures, alternative conformations observed at low levels of electron density have the potential to provide mechanistic insights into conformational dynamics. Here, we report a new multi-conformer contact network algorithm (CONTACT) that identifies networks of conformationally heterogeneous residues directly from high-resolution X-ray crystallography data. Contact networks in Escherichia coli dihydrofolate reductase (ecDHFR) predict the long-range pattern of NMR chemical shift perturbations of an allosteric mutation. A comparison of contact networks in wild type and mutant ecDHFR suggests how mutations that alter optimized networks of coordinated motions can impair catalytic function. Thus, CONTACT-guided mutagenesis will allow the structure-dynamics-function relationship to be exploited in protein engineering and design. PMID:23913260

Seeing Eye to Eye: Predicting Teacher-Student Agreement on Classroom Social Networks

PubMed Central

Neal, Jennifer Watling; Cappella, Elise; Wagner, Caroline; Atkins, Marc S.

2010-01-01

This study examines the association between classroom characteristics and teacher-student agreement in perceptions of students’ classroom peer networks. Social network, peer nomination, and observational data were collected from a sample of second through fourth grade teachers (N=33) and students (N=669) in 33 classrooms across five high poverty urban schools. Results demonstrate that variation in teacher-student agreement on the structure of students’ peer networks can be explained, in part, by developmental factors and classroom characteristics. Developmental increases in network density partially mediated the positive relationship between grade level and teacher-student agreement. Larger class sizes and higher levels of normative aggressive behavior resulted in lower levels of teacher-student agreement. Teachers’ levels of classroom organization had mixed influences, with behavior management negatively predicting agreement, and productivity positively predicting agreement. These results underscore the importance of the classroom context in shaping teacher and student perceptions of peer networks. PMID:21666768

Korean VLBI Network Calibrator Survey (KVNCS). 1. Source Catalog of KVN Single-dish Flux Density Measurement in the K and Q Bands

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

Lee, Jeong Ae; Sohn, Bong Won; Jung, Taehyun

We present the catalog of the KVN Calibrator Survey (KVNCS). This first part of the KVNCS is a single-dish radio survey simultaneously conducted at 22 ( K band) and 43 GHz ( Q band) using the Korean VLBI Network (KVN) from 2009 to 2011. A total of 2045 sources are selected from the VLBA Calibrator Survey with an extrapolated flux density limit of 100 mJy at the K  band. The KVNCS contains 1533 sources in the K band with a flux density limit of 70 mJy and 553 sources in the Q band with a flux density limit of 120more » mJy; it covers the whole sky down to −32.°5 in decl. We detected 513 sources simultaneously in the K and Q bands; ∼76% of them are flat-spectrum sources (−0.5 ≤ α ≤ 0.5). From the flux–flux relationship, we anticipated that most of the radiation of many of the sources comes from the compact components. The sources listed in the KVNCS therefore are strong candidates for high-frequency VLBI calibrators.« less

Insight to the express transport network

NASA Astrophysics Data System (ADS)

Yang, Hua; Nie, Yuchao; Zhang, Hongbin; Di, Zengru; Fan, Ying

2009-09-01

The express delivery industry is developing rapidly in recent years and has attracted attention in many fields. Express shipment service requires that parcels be delivered in a limited time with a low operation cost, which requests a high level and efficient express transport network (ETN). The ETN is constructed based on the public transport networks, especially the airline network. It is similar to the airline network in some aspects, while it has its own feature. With the complex network theory, the topological properties of the ETN are analyzed deeply. We find that the ETN has the small-world property, with disassortative mixing behavior and rich club phenomenon. It also shows difference from the airline network in some features, such as edge density and average shortest path. Analysis on the corresponding distance-weighted network shows that the distance distribution displays a truncated power-law behavior. At last, an evolving model, which takes both geographical constraint and preference attachment into account, is proposed. The model shows similar properties with the empirical results.

Cereal phytochromes: targets of selection, targets for manipulation?

PubMed

Sawers, Ruairidh J H; Sheehan, Moira J; Brutnell, Thomas P

2005-03-01

Plants respond to shading through an adaptive syndrome termed shade avoidance. In high-density crop plantings, shade avoidance generally increases extension growth at the expense of yield and can be at odds with the agronomic performance of the crop as a whole. Studies in Arabidopsis are beginning to reveal the essential role phytochromes play in regulating this process and to identify genes underlying the response. In this article, we focus on how phytochrome signaling networks have been targeted in cereal breeding programs in the past and discuss the potential to alter these pathways through breeding and transgenic manipulation to develop crops that perform better under typical high density conditions.

Radial basis function network learns ceramic processing and predicts related strength and density

NASA Technical Reports Server (NTRS)

Cios, Krzysztof J.; Baaklini, George Y.; Vary, Alex; Tjia, Robert E.

1993-01-01

Radial basis function (RBF) neural networks were trained using the data from 273 Si3N4 modulus of rupture (MOR) bars which were tested at room temperature and 135 MOR bars which were tested at 1370 C. Milling time, sintering time, and sintering gas pressure were the processing parameters used as the input features. Flexural strength and density were the outputs by which the RBF networks were assessed. The 'nodes-at-data-points' method was used to set the hidden layer centers and output layer training used the gradient descent method. The RBF network predicted strength with an average error of less than 12 percent and density with an average error of less than 2 percent. Further, the RBF network demonstrated a potential for optimizing and accelerating the development and processing of ceramic materials.

A High Performance VLSI Computer Architecture For Computer Graphics

NASA Astrophysics Data System (ADS)

Chin, Chi-Yuan; Lin, Wen-Tai

1988-10-01

A VLSI computer architecture, consisting of multiple processors, is presented in this paper to satisfy the modern computer graphics demands, e.g. high resolution, realistic animation, real-time display etc.. All processors share a global memory which are partitioned into multiple banks. Through a crossbar network, data from one memory bank can be broadcasted to many processors. Processors are physically interconnected through a hyper-crossbar network (a crossbar-like network). By programming the network, the topology of communication links among processors can be reconfigurated to satisfy specific dataflows of different applications. Each processor consists of a controller, arithmetic operators, local memory, a local crossbar network, and I/O ports to communicate with other processors, memory banks, and a system controller. Operations in each processor are characterized into two modes, i.e. object domain and space domain, to fully utilize the data-independency characteristics of graphics processing. Special graphics features such as 3D-to-2D conversion, shadow generation, texturing, and reflection, can be easily handled. With the current high density interconnection (MI) technology, it is feasible to implement a 64-processor system to achieve 2.5 billion operations per second, a performance needed in most advanced graphics applications.

Structural characteristics of the online social networks of maltreated youth and offline sexual risk behavior.

PubMed

Negriff, Sonya; Valente, Thomas W

2018-02-07

Maltreated youth are at risk for exposure to online sexual content and high-risk sexual behavior, yet characteristics of their online social networks have not been examined as a potential source of vulnerability. The aims of the current study were: 1) to test indicators of size (number of friends) and fragmentation (number of connections between friends) of maltreated young adults' online networks as predictors of intentional and unintentional exposure to sexual content and offline high-risk sexual behavior and 2) to test maltreatment as a moderator of these associations. Participants were selected from a longitudinal study on the effects of child maltreatment (n = 152; Mean age 21.84 years). Data downloaded from Facebook were used to calculate network variables of size (number of friends), density (connections between friends), average degree (average number of connections for each friend), and percent isolates (those not connected to others in the network). Self-reports of intentional and unintentional exposure to online sexual content and offline high-risk sexual behavior were the outcome variables. Multiple-group path modeling showed that only for the maltreated group having a higher percent of isolates in the network predicted intentional exposure to online sexual content and offline high-risk sexual behavior. An implication of this finding is that the composition of the Facebook network may be used as a risk indicator for individuals with child-welfare documented maltreatment experiences. Copyright © 2018. Published by Elsevier Ltd.

A geostatistical state-space model of animal densities for stream networks.

PubMed

Hocking, Daniel J; Thorson, James T; O'Neil, Kyle; Letcher, Benjamin H

2018-06-21

Population dynamics are often correlated in space and time due to correlations in environmental drivers as well as synchrony induced by individual dispersal. Many statistical analyses of populations ignore potential autocorrelations and assume that survey methods (distance and time between samples) eliminate these correlations, allowing samples to be treated independently. If these assumptions are incorrect, results and therefore inference may be biased and uncertainty under-estimated. We developed a novel statistical method to account for spatio-temporal correlations within dendritic stream networks, while accounting for imperfect detection in the surveys. Through simulations, we found this model decreased predictive error relative to standard statistical methods when data were spatially correlated based on stream distance and performed similarly when data were not correlated. We found that increasing the number of years surveyed substantially improved the model accuracy when estimating spatial and temporal correlation coefficients, especially from 10 to 15 years. Increasing the number of survey sites within the network improved the performance of the non-spatial model but only marginally improved the density estimates in the spatio-temporal model. We applied this model to Brook Trout data from the West Susquehanna Watershed in Pennsylvania collected over 34 years from 1981 - 2014. We found the model including temporal and spatio-temporal autocorrelation best described young-of-the-year (YOY) and adult density patterns. YOY densities were positively related to forest cover and negatively related to spring temperatures with low temporal autocorrelation and moderately-high spatio-temporal correlation. Adult densities were less strongly affected by climatic conditions and less temporally variable than YOY but with similar spatio-temporal correlation and higher temporal autocorrelation. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Estimation of the hydraulic conductivity of a two-dimensional fracture network using effective medium theory and power-law averaging

NASA Astrophysics Data System (ADS)

Zimmerman, R. W.; Leung, C. T.

2009-12-01

Most oil and gas reservoirs, as well as most potential sites for nuclear waste disposal, are naturally fractured. In these sites, the network of fractures will provide the main path for fluid to flow through the rock mass. In many cases, the fracture density is so high as to make it impractical to model it with a discrete fracture network (DFN) approach. For such rock masses, it would be useful to have recourse to analytical, or semi-analytical, methods to estimate the macroscopic hydraulic conductivity of the fracture network. We have investigated single-phase fluid flow through generated stochastically two-dimensional fracture networks. The centers and orientations of the fractures are uniformly distributed, whereas their lengths follow a lognormal distribution. The aperture of each fracture is correlated with its length, either through direct proportionality, or through a nonlinear relationship. The discrete fracture network flow and transport simulator NAPSAC, developed by Serco (Didcot, UK), is used to establish the “true” macroscopic hydraulic conductivity of the network. We then attempt to match this value by starting with the individual fracture conductances, and using various upscaling methods. Kirkpatrick’s effective medium approximation, which works well for pore networks on a core scale, generally underestimates the conductivity of the fracture networks. We attribute this to the fact that the conductances of individual fracture segments (between adjacent intersections with other fractures) are correlated with each other, whereas Kirkpatrick’s approximation assumes no correlation. The power-law averaging approach proposed by Desbarats for porous media is able to match the numerical value, using power-law exponents that generally lie between 0 (geometric mean) and 1 (harmonic mean). The appropriate exponent can be correlated with statistical parameters that characterize the fracture density.

Adenine-functionalized Spongy Graphene for Green and High-Performance Supercapacitors

PubMed Central

El-Gendy, Dalia M.; Ghany, Nabil A. Abdel; El Sherbini, E. E. Foad; Allam, Nageh K.

2017-01-01

A simple method is demonstrated to prepare spongy adenine-functionalized graphene (SFG) as interconnected, porous 3-dimensional (3D) network crinkly sheets. Such 3D network structure provides better contact at the electrode/electrolyte interface and facilitates the charge transfer kinetics. The fabricated SFG was characterized by X-ray diffraction (XRD), FTIR, scanning electron microscopy (FESEM), Raman spectroscopy, thermogravimetric analysis (TGA), UV−vis absorption spectroscopy, and transmission electron microscopy (TEM). The synthesized materials have been evaluated as supercapacitor materials in 0.5 M H2SO4 using cyclic voltammetry (CV) at different potential scan rates, and galvanostatic charge/discharge tests at different current densities. The SFG electrodes showed a maximum specific capacitance of 333 F/g at scan rate of 1 mV/s and exhibited excellent cycling retention of 102% after 1000 cycles at 200 mV/s. The energy density was 64.42 Wh/kg with a power density of 599.8 W/kg at 1.0 A/g. Those figures of merit are much higher than those reported for graphene-based materials tested under similar conditions. The observed high performance can be related to the synergistic effects of the spongy structure and the adenine functionalization. PMID:28216668

Mesoporous NiCo2O4 nano-needles supported by 3D interconnected carbon network on Ni foam for electrochemical energy storage

NASA Astrophysics Data System (ADS)

Lu, Congxiang; Liu, Wen-wen; Pan, Hui; Tay, Beng Kang; Wang, Xingli; Liang, Kun; Wei, Xuezhe

2018-05-01

In this work, a three dimensional (3D) interconnected carbon network consisting of ultrathin graphite (UG) and carbon nanotubes (CNTs) on Ni foam is fabricated and employed as a novel type of substrate for mesoporous NiCo2O4 nano-needles. The successfully synthesized NiCo2O4 nano-needles/CNTs/UG on Ni foam has many advantages including facile electrolyte access and direct conducting pathways towards current collectors, which enable it to be a promising electrode material in battery-like electrochemical energy storage. Encouragingly, a high capacity of 135.1 mAh/g at the current density of 1 A/g, superior rate performance and also stable cycling for 1200 cycles at the current density of 5 A/g have been demonstrated in this novel material.

Generation of murine induced pluripotent stem cells by using high-density distributed electrodes network.

PubMed

Lu, Ming-Yu; Li, Zhihong; Hwang, Shiaw-Min; Linju Yen, B; Lee, Gwo-Bin

2015-09-01

This study reports a robust method of gene transfection in a murine primary cell model by using a high-density electrodes network (HDEN). By demonstrating high cell viability after gene transfection and successful expression of transgenes including fluorescent proteins, the HDEN device shows great promise as a solution in which reprogramming efficiency using non-viral induction for generation of murine induced pluripotent stem cells (iPSCs) is optimized. High and steady transgene expression levels in host cells of iPSCs can be demonstrated using this method. Moreover, the HDEN device achieved successful gene transfection with a low voltage of less than 180 V while requiring relatively low cell numbers (less than 1.5 × 10(4) cells). The results are comparable to current conventional methods, demonstrating a reasonable fluorescent-plasmid transfection rate (42.4% in single transfection and 24.5% in triple transfection) and high cell viability of over 95%. The gene expression levels of each iPSC factor was measured to be over 10-fold higher than that reported in previous studies using a single mouse embryonic fibroblast cell. Our results demonstrate that the generation of iPSCs using HDEN transfection of plasmid DNA may be a feasible and safe alternative to using viral transfection methods in the near future.

Process for preparing energetic materials

DOEpatents

Simpson, Randall L [Livermore, CA; Lee, Ronald S [Livermore, CA; Tillotson, Thomas M [Tracy, CA; Hrubesh, Lawrence W [Pleasanton, CA; Swansiger, Rosalind W [Livermore, CA; Fox, Glenn A [Livermore, CA

2011-12-13

Sol-gel chemistry is used for the preparation of energetic materials (explosives, propellants and pyrotechnics) with improved homogeneity, and/or which can be cast to near-net shape, and/or made into precision molding powders. The sol-gel method is a synthetic chemical process where reactive monomers are mixed into a solution, polymerization occurs leading to a highly cross-linked three dimensional solid network resulting in a gel. The energetic materials can be incorporated during the formation of the solution or during the gel stage of the process. The composition, pore, and primary particle sizes, gel time, surface areas, and density may be tailored and controlled by the solution chemistry. The gel is then dried using supercritical extraction to produce a highly porous low density aerogel or by controlled slow evaporation to produce a xerogel. Applying stress during the extraction phase can result in high density materials. Thus, the sol-gel method can be used for precision detonator explosive manufacturing as well as producing precision explosives, propellants, and pyrotechnics, along with high power composite energetic materials.

Sol-Gel Manufactured Energetic Materials

DOEpatents

Simpson, Randall L.; Lee, Ronald S.; Tillotson, Thomas M.; Hrubesh, Lawrence W.; Swansiger, Rosalind W.; Fox, Glenn A.

2005-05-17

Sol-gel chemistry is used for the preparation of energetic materials (explosives, propellants and pyrotechnics) with improved homogeneity, and/or which can be cast to near-net shape, and/or made into precision molding powders. The sol-gel method is a synthetic chemical process where reactive monomers are mixed into a solution, polymerization occurs leading to a highly cross-linked three dimensional solid network resulting in a gel. The energetic materials can be incorporated during the formation of the solution or during the gel stage of the process. The composition, pore, and primary particle sizes, gel time, surface areas, and density may be tailored and controlled by the solution chemistry. The gel is then dried using supercritical extraction to produce a highly porous low density aerogel or by controlled slow evaporation to produce a xerogel. Applying stress during the extraction phase can result in high density materials. Thus, the sol-gel method can be used for precision detonator explosive manufacturing as well as producing precision explosives, propellants, and pyrotechnics, along with high power composite energetic materials.

Sol-gel manufactured energetic materials

DOEpatents

Simpson, Randall L.; Lee, Ronald S.; Tillotson, Thomas M.; Hrubesh, Lawrence W.; Swansiger, Rosalind W.; Fox, Glenn A.

2003-12-23

Sol-gel chemistry is used for the preparation of energetic materials (explosives, propellants and pyrotechnics) with improved homogeneity, and/or which can be cast to near-net shape, and/or made into precision molding powders. The sol-gel method is a synthetic chemical process where reactive monomers are mixed into a solution, polymerization occurs leading to a highly cross-linked three dimensional solid network resulting in a gel. The energetic materials can be incorporated during the formation of the solution or during the gel stage of the process. The composition, pore, and primary particle sizes, gel time, surface areas, and density may be tailored and controlled by the solution chemistry. The gel is then dried using supercritical extraction to produce a highly porous low density aerogel or by controlled slow evaporation to produce a xerogel. Applying stress during the extraction phase can result in high density materials. Thus, the sol-gel method can be used for precision detonator explosive manufacturing as well as producing precision explosives, propellants, and pyrotechnics, along with high power composite energetic materials.

Anti-correlated cortical networks arise from spontaneous neuronal dynamics at slow timescales.

PubMed

Kodama, Nathan X; Feng, Tianyi; Ullett, James J; Chiel, Hillel J; Sivakumar, Siddharth S; Galán, Roberto F

2018-01-12

In the highly interconnected architectures of the cerebral cortex, recurrent intracortical loops disproportionately outnumber thalamo-cortical inputs. These networks are also capable of generating neuronal activity without feedforward sensory drive. It is unknown, however, what spatiotemporal patterns may be solely attributed to intrinsic connections of the local cortical network. Using high-density microelectrode arrays, here we show that in the isolated, primary somatosensory cortex of mice, neuronal firing fluctuates on timescales from milliseconds to tens of seconds. Slower firing fluctuations reveal two spatially distinct neuronal ensembles, which correspond to superficial and deeper layers. These ensembles are anti-correlated: when one fires more, the other fires less and vice versa. This interplay is clearest at timescales of several seconds and is therefore consistent with shifts between active sensing and anticipatory behavioral states in mice.

Food Web Topology in High Mountain Lakes

PubMed Central

Sánchez-Hernández, Javier; Cobo, Fernando; Amundsen, Per-Arne

2015-01-01

Although diversity and limnology of alpine lake systems are well studied, their food web structure and properties have rarely been addressed. Here, the topological food webs of three high mountain lakes in Central Spain were examined. We first addressed the pelagic networks of the lakes, and then we explored how food web topology changed when benthic biota was included to establish complete trophic networks. We conducted a literature search to compare our alpine lacustrine food webs and their structural metrics with those of 18 published lentic webs using a meta-analytic approach. The comparison revealed that the food webs in alpine lakes are relatively simple, in terms of structural network properties (linkage density and connectance), in comparison with lowland lakes, but no great differences were found among pelagic networks. The studied high mountain food webs were dominated by a high proportion of omnivores and species at intermediate trophic levels. Omnivores can exploit resources at multiple trophic levels, and this characteristic might reduce competition among interacting species. Accordingly, the trophic overlap, measured as trophic similarity, was very low in all three systems. Thus, these alpine networks are characterized by many omnivorous consumers with numerous prey species and few consumers with a single or few prey and with low competitive interactions among species. The present study emphasizes the ecological significance of omnivores in high mountain lakes as promoters of network stability and as central players in energy flow pathways via food partitioning and enabling energy mobility among trophic levels. PMID:26571235

Food Web Topology in High Mountain Lakes.

PubMed

Sánchez-Hernández, Javier; Cobo, Fernando; Amundsen, Per-Arne

2015-01-01

Although diversity and limnology of alpine lake systems are well studied, their food web structure and properties have rarely been addressed. Here, the topological food webs of three high mountain lakes in Central Spain were examined. We first addressed the pelagic networks of the lakes, and then we explored how food web topology changed when benthic biota was included to establish complete trophic networks. We conducted a literature search to compare our alpine lacustrine food webs and their structural metrics with those of 18 published lentic webs using a meta-analytic approach. The comparison revealed that the food webs in alpine lakes are relatively simple, in terms of structural network properties (linkage density and connectance), in comparison with lowland lakes, but no great differences were found among pelagic networks. The studied high mountain food webs were dominated by a high proportion of omnivores and species at intermediate trophic levels. Omnivores can exploit resources at multiple trophic levels, and this characteristic might reduce competition among interacting species. Accordingly, the trophic overlap, measured as trophic similarity, was very low in all three systems. Thus, these alpine networks are characterized by many omnivorous consumers with numerous prey species and few consumers with a single or few prey and with low competitive interactions among species. The present study emphasizes the ecological significance of omnivores in high mountain lakes as promoters of network stability and as central players in energy flow pathways via food partitioning and enabling energy mobility among trophic levels.

Coupling Mo2C@C core-shell nanocrystals on 3D graphene hybrid aerogel for high-performance lithium ion battery

NASA Astrophysics Data System (ADS)

Xin, Hailin; Hai, Yang; Li, Dongzhi; Qiu, Zhaozheng; Lin, Yemao; Yang, Bo; Fan, Haosen; Zhu, Caizhen

2018-05-01

Hybrid aerogel by dispersing Mo2C@C core-shell nanocrystals into three-dimensional (3D) graphene (Mo2C@C-GA) has been successfully prepared through two-step methods. Firstly, carbon-coated MoO2 nanocrystals uniformly anchor on 3D graphene aerogel (MoO2@C-GA) via hydrothermal reaction. Then the MoO2@C-GA precursor is transformed into Mo2C@C-GA after the following carbonization process. Furthermore, the freeze-drying step plays an important role in the resulting pore size distribution of the porous networks. Moreover, graphene aerogels exhibit extremely low densities and superior electrical properties. When evaluated as anode material for lithium ion battery, Mo2C@C-GA delivers excellent rate capability and stable cycle performance when compared with C-GA and Mo2C nanoparticles. Mo2C@C-GA exhibits the initial discharge capacity of 1461.4 mA h g-1 at the current density of 0.1 A g-1, and retains a reversible capacity of 1089.8 mA h g-1 after 100 cycles at a current density of 0.1 A g-1. Even at high current density of 5 A g-1, a discharge capacity of 623.5 mA h g-1 can be still achieved. The excellent performance of Mo2C@C-GA could be attributed to the synergistic effect of Mo2C@C nanocrystals and the 3D graphene conductive network.

Force feedback controls motor activity and mechanical properties of self-assembling branched actin networks

PubMed Central

Bieling, Peter; Li, Tai-De; Weichsel, Julian; McGorty, Ryan; Jreij, Pamela; Huang, Bo; Fletcher, Daniel A.; Mullins, R. Dyche

2016-01-01

Branched actin networks–created by the Arp2/3 complex, capping protein, and a nucleation promoting factor– generate and transmit forces required for many cellular processes, but their response to force is poorly understood. To address this, we assembled branched actin networks in vitro from purified components and used simultaneous fluorescence and atomic force microscopy to quantify their molecular composition and material properties under various forces. Remarkably, mechanical loading of these self-assembling materials increases their density, power, and efficiency. Microscopically, increased density reflects increased filament number and altered geometry, but no change in average length. Macroscopically, increased density enhances network stiffness and resistance to mechanical failure beyond those of isotropic actin networks. These effects endow branched actin networks with memory of their mechanical history that shapes their material properties and motor activity. This work reveals intrinsic force feedback mechanisms by which mechanical resistance makes self-assembling actin networks stiffer, stronger, and more powerful. PMID:26771487

High-Performance Li-Ion Capacitor Based on an Activated Carbon Cathode and Well-Dispersed Ultrafine TiO2 Nanoparticles Embedded in Mesoporous Carbon Nanofibers Anode.

PubMed

Yang, Cheng; Lan, Jin-Le; Liu, Wen-Xiao; Liu, Yuan; Yu, Yun-Hua; Yang, Xiao-Ping

2017-06-07

A novel Li-ion capacitor based on an activated carbon cathode and a well-dispersed ultrafine TiO 2 nanoparticles embedded in mesoporous carbon nanofibers (TiO 2 @PCNFs) anode was reported. A series of TiO 2 @PCNFs anode materials were prepared via a scalable electrospinning method followed by carbonization and a postetching method. The size of TiO 2 nanoparticles and the mesoporous structure of the TiO 2 @PCNFs were tuned by varying amounts of tetraethyl orthosilicate (TEOS) to increase the energy density and power density of the LIC significantly. Such a subtle designed LIC displayed a high energy density of 67.4 Wh kg -1 at a power density of 75 W kg -1 . Meanwhile, even when the power density was increased to 5 kW kg -1 , the energy density can still maintain 27.5 Wh kg -1 . Moreover, the LIC displayed a high capacitance retention of 80.5% after 10000 cycles at 10 A g -1 . The outstanding electrochemical performance can be contributed to the synergistic effect of the well-dispersed ultrafine TiO 2 nanoparticles, the abundant mesoporous structure, and the conductive carbon networks.

Two-dimensional network stability of nucleobases and amino acids on graphite under ambient conditions: adenine, L-serine and L-tyrosine.

PubMed

Bald, Ilko; Weigelt, Sigrid; Ma, Xiaojing; Xie, Pengyang; Subramani, Ramesh; Dong, Mingdong; Wang, Chen; Mamdouh, Wael; Wang, Jianguo; Besenbacher, Flemming

2010-04-14

We have investigated the stability of two-dimensional self-assembled molecular networks formed upon co-adsorption of the DNA base, adenine, with each of the amino acids, L-serine and L-tyrosine, on a highly oriented pyrolytic graphite (HOPG) surface by drop-casting from a water solution. L-serine and L-tyrosine were chosen as model systems due to their different interaction with the solvent molecules and the graphite substrate, which is reflected in a high and low solubility in water, respectively, compared with adenine. Combined scanning tunneling microscopy (STM) measurements and density functional theory (DFT) calculations show that the self-assembly process is mainly driven by the formation of strong adenine-adenine hydrogen bonds. We find that pure adenine networks are energetically more stable than networks built up of either pure L-serine, pure L-tyrosine or combinations of adenine with L-serine or L-tyrosine, and that only pure adenine networks are stable enough to be observable by STM under ambient conditions.

Topology-dependent density optima for efficient simultaneous network exploration

NASA Astrophysics Data System (ADS)

Wilson, Daniel B.; Baker, Ruth E.; Woodhouse, Francis G.

2018-06-01

A random search process in a networked environment is governed by the time it takes to visit every node, termed the cover time. Often, a networked process does not proceed in isolation but competes with many instances of itself within the same environment. A key unanswered question is how to optimize this process: How many concurrent searchers can a topology support before the benefits of parallelism are outweighed by competition for space? Here, we introduce the searcher-averaged parallel cover time (APCT) to quantify these economies of scale. We show that the APCT of the networked symmetric exclusion process is optimized at a searcher density that is well predicted by the spectral gap. Furthermore, we find that nonequilibrium processes, realized through the addition of bias, can support significantly increased density optima. Our results suggest alternative hybrid strategies of serial and parallel search for efficient information gathering in social interaction and biological transport networks.

Connecting macroscopic dynamics with microscopic properties in active microtubule network contraction

NASA Astrophysics Data System (ADS)

Foster, Peter J.; Yan, Wen; Fürthauer, Sebastian; Shelley, Michael J.; Needleman, Daniel J.

2017-12-01

The cellular cytoskeleton is an active material, driven out of equilibrium by molecular motor proteins. It is not understood how the collective behaviors of cytoskeletal networks emerge from the properties of the network’s constituent motor proteins and filaments. Here we present experimental results on networks of stabilized microtubules in Xenopus oocyte extracts, which undergo spontaneous bulk contraction driven by the motor protein dynein, and investigate the effects of varying the initial microtubule density and length distribution. We find that networks contract to a similar final density, irrespective of the length of microtubules or their initial density, but that the contraction timescale varies with the average microtubule length. To gain insight into why this microscopic property influences the macroscopic network contraction time, we developed simulations where microtubules and motors are explicitly represented. The simulations qualitatively recapitulate the variation of contraction timescale with microtubule length, and allowed stress contributions from different sources to be estimated and decoupled.

Effects of Cultural Tightness-Looseness and Social Network Density on Expression of Positive and Negative Emotions: A Large-Scale Study of Impression Management by Facebook Users.

PubMed

Liu, Pan; Chan, David; Qiu, Lin; Tov, William; Tong, Victor Joo Chuan

2018-05-01

Using data from 13,789 Facebook users across U.S. states, this study examined the main effects of societal-level cultural tightness-looseness and its interaction effects with individuals' social network density on impression management (IM) in terms of online emotional expression. Results showed that individuals from culturally tight (vs. loose) states were more likely to express positive emotions and less likely to express negative emotions. Meanwhile, for positive emotional expression, there was a tightness-looseness by social network density interaction effect. In culturally tight states, individuals with dense (vs. sparse) networks were more likely to express positive emotions, while in culturally loose states this pattern was reversed. For negative emotional expression, however, no such interaction was observed. Our findings highlight the influence of cultural norms and social network structure on emotional expressions as IM strategies.

Three-Dimensional Array of TiN@Pt3Cu Nanowires as an Efficient Porous Electrode for the Lithium-Oxygen Battery.

PubMed

Luo, Wen-Bin; Pham, Thien Viet; Guo, Hai-Peng; Liu, Hua-Kun; Dou, Shi-Xue

2017-02-28

The nonaqueous lithium-oxygen battery is a promising candidate as a next-generation energy storage system because of its potentially high energy density (up to 2-3 kW kg -1 ), exceeding that of any other existing energy storage system for storing sustainable and clean energy to reduce greenhouse gas emissions and the consumption of nonrenewable fossil fuels. To achieve high round-trip efficiency and satisfactory cycling stability, the air electrode structure and the electrocatalysts play important roles. Here, a 3D array composed of one-dimensional TiN@Pt 3 Cu nanowires was synthesized and employed as a whole porous air electrode in a lithium-oxygen battery. The TiN nanowire was primarily used as an air electrode frame and catalyst support to provide a high electronic conductivity network because of the high-orientation one-dimensional crystalline structure. Meanwhile, deposited icosahedral Pt 3 Cu nanocrystals exhibit highly efficient catalytic activity owing to the abundant {111} active lattice facets and multiple twin boundaries. This porous air electrode comprises a one-dimensional TiN@Pt 3 Cu nanowire array that demonstrates excellent energy conversion efficiency and rate performance in full discharge and charge modes. The discharge capacity is up to 4600 mAh g -1 along with an 84% conversion efficiency at a current density of 0.2 mA cm -2 , and when the current density increased to 0.8 mA cm -2 , the discharge capacity is still greater than 3500 mAh g -1 together with a nearly 70% efficiency. This designed array is a promising bifunctional porous air electrode for lithium-oxygen batteries, forming a continuous conductive and high catalytic activity network to facilitate rapid gas and electrolyte diffusion and catalytic reaction throughout the whole energy conversion process.

Trade-offs between lens complexity and real estate utilization in a free-space multichip global interconnection module.

PubMed

Milojkovic, Predrag; Christensen, Marc P; Haney, Michael W

2006-07-01

The FAST-Net (Free-space Accelerator for Switching Terabit Networks) concept uses an array of wide-field-of-view imaging lenses to realize a high-density shuffle interconnect pattern across an array of smart-pixel integrated circuits. To simplify the optics we evaluated the efficiency gained in replacing spherical surfaces with aspherical surfaces by exploiting the large disparity between narrow vertical cavity surface emitting laser (VCSEL) beams and the wide field of view of the imaging optics. We then analyzed trade-offs between lens complexity and chip real estate utilization and determined that there exists an optimal numerical aperture for VCSELs that maximizes their area density. The results provide a general framework for the design of wide-field-of-view free-space interconnection systems that incorporate high-density VCSEL arrays.

Three-dimensional graphene networks as a new substrate for immobilization of laccase and dopamine and its application in glucose/O2 biofuel cell.

PubMed

Zhang, Yijia; Chu, Mi; Yang, Lu; Tan, Yueming; Deng, Wenfang; Ma, Ming; Su, Xiaoli; Xie, Qingji

2014-08-13

We report here three-dimensional graphene networks (3D-GNs) as a novel substrate for the immobilization of laccase (Lac) and dopamine (DA) and its application in glucose/O2 biofuel cell. 3D-GNs were synthesized with an Ni(2+)-exchange/KOH activation combination method using a 732-type sulfonic acid ion-exchange resin as the carbon precursor. The 3D-GNs exhibited an interconnected network structure and a high specific surface area. DA was noncovalently functionalized on the surface of 3D-GNs with 3,4,9,10-perylene tetracarboxylic acid (PTCA) as a bridge and used as a novel immobilized mediating system for Lac-based bioelectrocatalytic reduction of oxygen. The 3D-GNs-PTCA-DA nanocomposite modified glassy carbon electrode (GCE) showed stable and well-defined redox current peaks for the catechol/o-quinone redox couple. Due to the mediated electron transfer by the 3D-GNs-PTCA-DA nanocomposite, the Nafion/Lac/3D-GNs-PTCA-DA/GCE exhibited high catalytic activity for oxygen reduction. The 3D-GNs are proven to be a better substrate for Lac and its mediator immobilization than 2D graphene nanosheets (2D-GNs) due to the interconnected network structure and high specific surface area of 3D-GNs. A glucose/O2 fuel cell using Nafion/Lac/3D-GNs-PTCA-DA/GCE as the cathode and Nafion/glucose oxidase/ferrocence/3D-GNs/GCE as the anode can output a maximum power density of 112 μW cm(-2) and a short-circuit current density of 0.96 mA cm(-2). This work may be helpful for exploiting the popular 3D-GNs as an efficient electrode material for many other biotechnology applications.

Associations between Aspects of Friendship Networks, Physical Activity, and Sedentary Behaviour among Adolescents

PubMed Central

McCormack, Gavin R.; Nettel-Aguirre, Alberto; Blackstaffe, Anita; Perry, Rosemary; Hawe, Penelope

2014-01-01

Background. Adolescent friendships have been linked to physical activity levels; however, network characteristics have not been broadly examined. Method. In a cross-sectional analysis of 1061 adolescents (11–15 years), achieving 60 minutes/day of moderate-to-vigorous physical activity (MVPA) and participating in over 2 hours/day of sedentary behaviour were determined based on friendship network characteristics (density; proportion of active/sedentary friends; betweenness centrality; popularity; clique membership) and perceived social support. Results. Adolescents with no friendship nominations participated in less MVPA. For boys and girls, a ten percent point increase in active friends was positively associated with achievement of 60 minutes/day of MVPA (OR 1.11; 95% CI 1.02–1.21, OR 1.14; 95% CI 1.02–1.27, resp.). For boys, higher social support from friends was negatively associated with achieving 60 minutes/day of MVPA (OR 0.63; 95% CI 0.42–0.96). Compared with low density networks, boys in higher density networks were more likely to participate in over 2 hours/day of sedentary behaviour (OR 2.93; 95% CI 1.32–6.49). Social support from friends also modified associations between network characteristics and MVPA and sedentary behaviour. Conclusion. Different network characteristics appeared to have different consequences. The proportion of active close friends was associated with MVPA, while network density was associated with sedentary behaviour. This poses challenges for intervention design. PMID:25328690

Network measures predict neuropsychological outcome after brain injury

PubMed Central

Warren, David E.; Power, Jonathan D.; Bruss, Joel; Denburg, Natalie L.; Waldron, Eric J.; Sun, Haoxin; Petersen, Steven E.; Tranel, Daniel

2014-01-01

Hubs are network components that hold positions of high importance for network function. Previous research has identified hubs in human brain networks derived from neuroimaging data; however, there is little consensus on the localization of such hubs. Moreover, direct evidence regarding the role of various proposed hubs in network function (e.g., cognition) is scarce. Regions of the default mode network (DMN) have been frequently identified as “cortical hubs” of brain networks. On theoretical grounds, we have argued against some of the methods used to identify these hubs and have advocated alternative approaches that identify different regions of cortex as hubs. Our framework predicts that our proposed hub locations may play influential roles in multiple aspects of cognition, and, in contrast, that hubs identified via other methods (including salient regions in the DMN) might not exert such broad influence. Here we used a neuropsychological approach to directly test these predictions by studying long-term cognitive and behavioral outcomes in 30 patients, 19 with focal lesions to six “target” hubs identified by our approaches (high system density and participation coefficient) and 11 with focal lesions to two “control” hubs (high degree centrality). In support of our predictions, we found that damage to target locations produced severe and widespread cognitive deficits, whereas damage to control locations produced more circumscribed deficits. These findings support our interpretation of how neuroimaging-derived network measures relate to cognition and augment classic neuroanatomically based predictions about cognitive and behavioral outcomes after focal brain injury. PMID:25225403

Quantifying climatic controls on river network topology across scales

NASA Astrophysics Data System (ADS)

Ranjbar Moshfeghi, S.; Hooshyar, M.; Wang, D.; Singh, A.

2017-12-01

Branching structure of river networks is an important topologic and geomorphologic feature that depends on several factors (e.g. climate, tectonic). However, mechanisms that cause these drainage patterns in river networks are poorly understood. In this study, we investigate the effects of varying climatic forcing on river network topology and geomorphology. For this, we select 20 catchments across the United States with different long-term climatic conditions quantified by climate aridity index (AI), defined here as the ratio of mean annual potential evaporation (Ep) to precipitation (P), capturing variation in runoff and vegetation cover. The river networks of these catchments are extracted, using a curvature-based method, from high-resolution (1 m) digital elevation models and several metrics such as drainage density, branching angle, and width functions are computed. We also use a multiscale-entropy-based approach to quantify the topologic irregularity and structural richness of these river networks. Our results reveal systematic impacts of climate forcing on the structure of river networks.

Spatial Distribution Characteristics of Healthcare Facilities in Nanjing: Network Point Pattern Analysis and Correlation Analysis.

PubMed

Ni, Jianhua; Qian, Tianlu; Xi, Changbai; Rui, Yikang; Wang, Jiechen

2016-08-18

The spatial distribution of urban service facilities is largely constrained by the road network. In this study, network point pattern analysis and correlation analysis were used to analyze the relationship between road network and healthcare facility distribution. The weighted network kernel density estimation method proposed in this study identifies significant differences between the outside and inside areas of the Ming city wall. The results of network K-function analysis show that private hospitals are more evenly distributed than public hospitals, and pharmacy stores tend to cluster around hospitals along the road network. After computing the correlation analysis between different categorized hospitals and street centrality, we find that the distribution of these hospitals correlates highly with the street centralities, and that the correlations are higher with private and small hospitals than with public and large hospitals. The comprehensive analysis results could help examine the reasonability of existing urban healthcare facility distribution and optimize the location of new healthcare facilities.

Identification of crucial genes related to postmenopausal osteoporosis using gene expression profiling.

PubMed

Ma, Min; Chen, Xiaofei; Lu, Liangyu; Yuan, Feng; Zeng, Wen; Luo, Shulin; Yin, Feng; Cai, Junfeng

2016-12-01

Postmenopausal osteoporosis is a common bone disease and characterized by low bone mineral density. This study aimed to reveal key genes associated with postmenopausal osteoporosis (PMO), and provide a theoretical basis for subsequent experiments. The dataset GSE7429 was obtained from Gene Expression Omnibus. A total of 20 B cell samples (ten ones, respectively from postmenopausal women with low or high bone mineral density (BMD) were included in this dataset. Following screening of differentially expressed genes (DEGs), coexpression analysis of all genes was performed, and key genes in the coexpression network were screened using the random walk algorithm. Afterwards, functional and pathway analyses were conducted. Additionally, protein-protein interactions (PPIs) between DEGs and key genes were analyzed. A set of 308 DEGs (170 up-regulated ones and 138 down-regulated ones) between low BMD and high BMD samples were identified, and 101 key genes in the coexpression network were screened out. In the coexpression network, some genes had a higher score and degree, such as CSTA. The key genes in the coexpression network were mainly enriched in GO terms of the defense response (e.g., SERPINA1 and CST3), immune response (e.g., IL32 and CLEC7A); while, the DEGs were mainly enriched in structural constituent of cytoskeleton (e.g., CYLC2 and TUBA1B) and membrane-enclosed lumen (e.g., CCNE1 and INTS5). In the PPI network, CCNE1 interacted with REL; and TUBA1B interacted with ESR1. A series of interactions, such as CSTA/TYROBP, CCNE1/REL and TUBA1B/ESR1 might play pivotal roles in the occurrence and development of PMO.

Using soft computing techniques to predict corrected air permeability using Thomeer parameters, air porosity and grain density

NASA Astrophysics Data System (ADS)

Nooruddin, Hasan A.; Anifowose, Fatai; Abdulraheem, Abdulazeez

2014-03-01

Soft computing techniques are recently becoming very popular in the oil industry. A number of computational intelligence-based predictive methods have been widely applied in the industry with high prediction capabilities. Some of the popular methods include feed-forward neural networks, radial basis function network, generalized regression neural network, functional networks, support vector regression and adaptive network fuzzy inference system. A comparative study among most popular soft computing techniques is presented using a large dataset published in literature describing multimodal pore systems in the Arab D formation. The inputs to the models are air porosity, grain density, and Thomeer parameters obtained using mercury injection capillary pressure profiles. Corrected air permeability is the target variable. Applying developed permeability models in recent reservoir characterization workflow ensures consistency between micro and macro scale information represented mainly by Thomeer parameters and absolute permeability. The dataset was divided into two parts with 80% of data used for training and 20% for testing. The target permeability variable was transformed to the logarithmic scale as a pre-processing step and to show better correlations with the input variables. Statistical and graphical analysis of the results including permeability cross-plots and detailed error measures were created. In general, the comparative study showed very close results among the developed models. The feed-forward neural network permeability model showed the lowest average relative error, average absolute relative error, standard deviations of error and root means squares making it the best model for such problems. Adaptive network fuzzy inference system also showed very good results.

Social-ecological network analysis of scale mismatches in estuary watershed restoration.

PubMed

Sayles, Jesse S; Baggio, Jacopo A

2017-03-07

Resource management boundaries seldom align with environmental systems, which can lead to social and ecological problems. Mapping and analyzing how resource management organizations in different areas collaborate can provide vital information to help overcome such misalignment. Few quantitative approaches exist, however, to analyze social collaborations alongside environmental patterns, especially among local and regional organizations (i.e., in multilevel governance settings). This paper develops and applies such an approach using social-ecological network analysis (SENA), which considers relationships among and between social and ecological units. The framework and methods are shown using an estuary restoration case from Puget Sound, United States. Collaboration patterns and quality are analyzed among local and regional organizations working in hydrologically connected areas. These patterns are correlated with restoration practitioners' assessments of the productivity of their collaborations to inform network theories for natural resource governance. The SENA is also combined with existing ecological data to jointly consider social and ecological restoration concerns. Results show potentially problematic areas in nearshore environments, where collaboration networks measured by density (percentage of possible network connections) and productivity are weakest. Many areas also have high centralization (a few nodes hold the network together), making network cohesion dependent on key organizations. Although centralization and productivity are inversely related, no clear relationship between density and productivity is observed. This research can help practitioners to identify where governance capacity needs strengthening and jointly consider social and ecological concerns. It advances SENA by developing a multilevel approach to assess social-ecological (or social-environmental) misalignments, also known as scale mismatches.

Social–ecological network analysis of scale mismatches in estuary watershed restoration

PubMed Central

Sayles, Jesse S.

2017-01-01

Resource management boundaries seldom align with environmental systems, which can lead to social and ecological problems. Mapping and analyzing how resource management organizations in different areas collaborate can provide vital information to help overcome such misalignment. Few quantitative approaches exist, however, to analyze social collaborations alongside environmental patterns, especially among local and regional organizations (i.e., in multilevel governance settings). This paper develops and applies such an approach using social–ecological network analysis (SENA), which considers relationships among and between social and ecological units. The framework and methods are shown using an estuary restoration case from Puget Sound, United States. Collaboration patterns and quality are analyzed among local and regional organizations working in hydrologically connected areas. These patterns are correlated with restoration practitioners’ assessments of the productivity of their collaborations to inform network theories for natural resource governance. The SENA is also combined with existing ecological data to jointly consider social and ecological restoration concerns. Results show potentially problematic areas in nearshore environments, where collaboration networks measured by density (percentage of possible network connections) and productivity are weakest. Many areas also have high centralization (a few nodes hold the network together), making network cohesion dependent on key organizations. Although centralization and productivity are inversely related, no clear relationship between density and productivity is observed. This research can help practitioners to identify where governance capacity needs strengthening and jointly consider social and ecological concerns. It advances SENA by developing a multilevel approach to assess social–ecological (or social–environmental) misalignments, also known as scale mismatches. PMID:28223529

Feature pruning by upstream drainage area to support automated generalization of the United States National Hydrography Dataset

USGS Publications Warehouse

Stanislawski, L.V.

2009-01-01

The United States Geological Survey has been researching generalization approaches to enable multiple-scale display and delivery of geographic data. This paper presents automated methods to prune network and polygon features of the United States high-resolution National Hydrography Dataset (NHD) to lower resolutions. Feature-pruning rules, data enrichment, and partitioning are derived from knowledge of surface water, the NHD model, and associated feature specification standards. Relative prominence of network features is estimated from upstream drainage area (UDA). Network and polygon features are pruned by UDA and NHD reach code to achieve a drainage density appropriate for any less detailed map scale. Data partitioning maintains local drainage density variations that characterize the terrain. For demonstration, a 48 subbasin area of 1:24 000-scale NHD was pruned to 1:100 000-scale (100 K) and compared to a benchmark, the 100 K NHD. The coefficient of line correspondence (CLC) is used to evaluate how well pruned network features match the benchmark network. CLC values of 0.82 and 0.77 result from pruning with and without partitioning, respectively. The number of polygons that remain after pruning is about seven times that of the benchmark, but the area covered by the polygons that remain after pruning is only about 10% greater than the area covered by benchmark polygons. ?? 2009.

A mixed SIR-SIS model to contain a virus spreading through networks with two degrees

NASA Astrophysics Data System (ADS)

Essouifi, Mohamed; Achahbar, Abdelfattah

Due to the fact that the “nodes” and “links” of real networks are heterogeneous, to model computer viruses prevalence throughout the Internet, we borrow the idea of the reduced scale free network which was introduced recently. The purpose of this paper is to extend the previous deterministic two subchains of Susceptible-Infected-Susceptible (SIS) model into a mixed Susceptible-Infected-Recovered and Susceptible-Infected-Susceptible (SIR-SIS) model to contain the computer virus spreading over networks with two degrees. Moreover, we develop its stochastic counterpart. Due to the high protection and security taken for hubs class, we suggest to treat it by using SIR epidemic model rather than the SIS one. The analytical study reveals that the proposed model admits a stable viral equilibrium. Thus, it is shown numerically that the mean dynamic behavior of the stochastic model is in agreement with the deterministic one. Unlike the infection densities i2 and i which both tend to a viral equilibrium for both approaches as in the previous study, i1 tends to the virus-free equilibrium. Furthermore, since a proportion of infectives are recovered, the global infection density i is minimized. Therefore, the permanent presence of viruses in the network due to the lower-degree nodes class. Many suggestions are put forward for containing viruses propagation and minimizing their damages.

CFS-SMO based classification of breast density using multiple texture models.

PubMed

Sharma, Vipul; Singh, Sukhwinder

2014-06-01

It is highly acknowledged in the medical profession that density of breast tissue is a major cause for the growth of breast cancer. Increased breast density was found to be linked with an increased risk of breast cancer growth, as high density makes it difficult for radiologists to see an abnormality which leads to false negative results. Therefore, there is need for the development of highly efficient techniques for breast tissue classification based on density. This paper presents a hybrid scheme for classification of fatty and dense mammograms using correlation-based feature selection (CFS) and sequential minimal optimization (SMO). In this work, texture analysis is done on a region of interest selected from the mammogram. Various texture models have been used to quantify the texture of parenchymal patterns of breast. To reduce the dimensionality and to identify the features which differentiate between breast tissue densities, CFS is used. Finally, classification is performed using SMO. The performance is evaluated using 322 images of mini-MIAS database. Highest accuracy of 96.46% is obtained for two-class problem (fatty and dense) using proposed approach. Performance of selected features by CFS is also evaluated by Naïve Bayes, Multilayer Perceptron, RBF Network, J48 and kNN classifier. The proposed CFS-SMO method outperforms all other classifiers giving a sensitivity of 100%. This makes it suitable to be taken as a second opinion in classifying breast tissue density.

OA20 The positioning of family, friends, community, and service providers in support networks for caring at end-of-life: a social network analysis.

PubMed

Leonard, Rosemary; Horsfall, Debbie; Rosenberg, John; Noonan, Kerrie

2015-04-01

Although there is ample evidence of the risk to carers from the burden of caring, there is also evidence that a caring network can relieve the burden on the principal carer, strengthen community relationships, and increase 'Death Literacy' in the community. There is often an assumption that, in caring networks, family and service providers are central and friends and community are marginal. We examined whether this is the case in practice using SNA. To identify the relative positioning of family, friends, community, and service providers in caring networks. In interviews with carers (N = 23) and focus groups with caring networks (N = 13) participants were asked to list the people in the caring network and rate the strength of their relationships to them (0 no relationship to 3 strong relationship). SNA in UCInet was used to map the networks, examine density (number and strength of relationships) across time (when caring began to the present) and across relationship types (family, friends, community, and service providers) supplemented by qualitative data. The analysis revealed significant increases in the density of the networks over time. The density of relationships with friends was similar to that other family. Community and service providers had significantly lower density. Qualitative analysis revealed that often service providers were not seen as part of the networks. To avoid carer burnout, it is important not to make assumptions about where carers obtain support but work with each carer to mobilise any support that is available. © 2015, 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.

Effect of crosslink torsional stiffness on elastic behavior of semiflexible polymer networks

NASA Astrophysics Data System (ADS)

Hatami-Marbini, H.

2018-02-01

Networks of semiflexible filaments are building blocks of different biological and structural materials such as cytoskeleton and extracellular matrix. The mechanical response of these systems when subjected to an applied strain at zero temperature is often investigated numerically using networks composed of filaments, which are either rigidly welded or pinned together at their crosslinks. In the latter, filaments during deformation are free to rotate about their crosslinks while the relative angles between filaments remain constant in the former. The behavior of crosslinks in actual semiflexible networks is different than these idealized models and there exists only partial constraint on torques at crosslinks. The present work develops a numerical model in which two intersecting filaments are connected to each other by torsional springs with arbitrary stiffness. We show that fiber networks composed of rigid and freely rotating crosslinks are the limiting case of the present model. Furthermore, we characterize the effects of stiffness of crosslinks on effective Young's modulus of semiflexible networks as a function of filament flexibility and crosslink density. The effective Young's modulus is determined as a function of the mechanical properties of crosslinks and is found to vanish for networks composed of very weak torsional springs. Independent of the stiffness of crosslinks, it is found that the effective Young's modulus is a function of fiber flexibility and crosslink density. In low density networks, filaments primarily bend and the effective Young's modulus is much lower than the affine estimate. With increasing filament bending stiffness and/or crosslink density, the mechanical behavior of the networks becomes more affine and the stretching of filaments depicts itself as the dominant mode of deformation. The torsional stiffness of the crosslinks significantly affects the effective Young's modulus of the semiflexible random fiber networks.

Impact of the intermixed phase and the channel network on the carrier mobility of nanostructured solar cells

NASA Astrophysics Data System (ADS)

Woellner, Cristiano F.; Freire, José A.

2016-02-01

We analyzed the impact of the complex channel network of donor and acceptor domains in nanostructured solar cells on the mobility of the charge carriers moving by thermally activated hopping. Particular attention was given to the so called intermixed phase, or interface roughness, that has recently been shown to promote an increase in the cell efficiency. The domains were obtained from a Monte Carlo simulation of a two-species lattice gas. We generated domain morphologies with controllable channel size and interface roughness. The field and density dependence of the carrier hopping mobility in different morphologies was obtained by solving a master equation. Our results show that the mobility decreases with roughness and increases with typical channel sizes. The deleterious effect of the roughness on the mobility is quite dramatic at low carrier densities and high fields. The complex channel network is shown to be directly responsible for two potentially harmful effects to the cell performance: a remarkable decrease of the mobility with increasing field and the accumulation of charge at the domains interface, which leads to recombination losses.

Multi-species genetic connectivity in a terrestrial habitat network.

PubMed

Marrotte, Robby R; Bowman, Jeff; Brown, Michael G C; Cordes, Chad; Morris, Kimberley Y; Prentice, Melanie B; Wilson, Paul J

2017-01-01

Habitat fragmentation reduces genetic connectivity for multiple species, yet conservation efforts tend to rely heavily on single-species connectivity estimates to inform land-use planning. Such conservation activities may benefit from multi-species connectivity estimates, which provide a simple and practical means to mitigate the effects of habitat fragmentation for a larger number of species. To test the validity of a multi-species connectivity model, we used neutral microsatellite genetic datasets of Canada lynx ( Lynx canadensis ), American marten ( Martes americana ), fisher ( Pekania pennanti ), and southern flying squirrel ( Glaucomys volans ) to evaluate multi-species genetic connectivity across Ontario, Canada. We used linear models to compare node-based estimates of genetic connectivity for each species to point-based estimates of landscape connectivity (current density) derived from circuit theory. To our knowledge, we are the first to evaluate current density as a measure of genetic connectivity. Our results depended on landscape context: habitat amount was more important than current density in explaining multi-species genetic connectivity in the northern part of our study area, where habitat was abundant and fragmentation was low. In the south however, where fragmentation was prevalent, genetic connectivity was correlated with current density. Contrary to our expectations however, locations with a high probability of movement as reflected by high current density were negatively associated with gene flow. Subsequent analyses of circuit theory outputs showed that high current density was also associated with high effective resistance, underscoring that the presence of pinch points is not necessarily indicative of gene flow. Overall, our study appears to provide support for the hypothesis that landscape pattern is important when habitat amount is low. We also conclude that while current density is proportional to the probability of movement per unit area, this does not imply increased gene flow, since high current density tends to be a result of neighbouring pixels with high cost of movement (e.g., low habitat amount). In other words, pinch points with high current density appear to constrict gene flow.

Scalable population estimates using spatial-stream-network (SSN) models, fish density surveys, and national geospatial database frameworks for streams

Treesearch

Daniel J. Isaak; Jay M. Ver Hoef; Erin E. Peterson; Dona L. Horan; David E. Nagel

2017-01-01

Population size estimates for stream fishes are important for conservation and management, but sampling costs limit the extent of most estimates to small portions of river networks that encompass 100s–10 000s of linear kilometres. However, the advent of large fish density data sets, spatial-stream-network (SSN) models that benefit from nonindependence among samples,...

Bacterial-cellulose-derived interconnected meso-microporous carbon nanofiber networks as binder-free electrodes for high-performance supercapacitors

NASA Astrophysics Data System (ADS)

Hao, Xiaodong; Wang, Jie; Ding, Bing; Wang, Ya; Chang, Zhi; Dou, Hui; Zhang, Xiaogang

2017-06-01

Bacterial cellulose (BC), a typical biomass prepared from the microbial fermentation process, has been proved that it can be an ideal platform for design of three-dimensional (3D) multifunctional nanomaterials in energy storage and conversion field. Here we developed a simple and general silica-assisted strategy for fabrication of interconnected 3D meso-microporous carbon nanofiber networks by confine nanospace pyrolysis of sustainable BC, which can be used as binder-free electrodes for high-performance supercapacitors. The synthesized carbon nanofibers exhibited the features of interconnected 3D networks architecture, large surface area (624 m2 g-1), mesopores-dominated hierarchical porosity, and high graphitization degree. The as-prepared electrode (CN-BC) displayed a maximum specific capacitance of 302 F g-1 at a current density of 0.5 A g-1, high-rate capability and good cyclicity in 6 M KOH electrolyte. This work, together with cost-effective preparation strategy to make high-value utilization of cheap biomass, should have significant implications in the green and mass-producible energy storage.

Online Network Influences on Emerging Adults’ Alcohol and Drug Use

PubMed Central

Cook, Stephanie H.; Gordon-Messer, Deborah; Zimmerman, Marc A.

2012-01-01

Researchers have reported that network characteristics are associated with substance use behavior. Considering that social interactions within online networks are increasingly common, we examined the relationship between online network characteristics and substance use in a sample of emerging adults (ages 18–24) from across the United States (N = 2,153; M = 21 years old; 47 % female; 70 % White). We used regression analyses to examine the relationship between online ego network characteristics (i.e., characteristics of individuals directly related to the focal participant plus the relationships shared among individuals within the online network) and alcohol use and substance use, respectively. Alcohol use was associated with network density (i.e., interconnectedness between individuals in a network), total number of peer ties, and a greater proportion of emotionally close ties. In sex-stratified models, density was related to alcohol use for males but not females. Drug use was associated with an increased number of peer ties, and the increased proportion of network members’ discussion and acceptance of drug use, respectively. We also found that online network density and total numbers of ties were associated with more personal drug use for males but not females. Conversely, we noted that social norms were related to increased drug use and this relationship was stronger for females than males. We discuss the implications of our findings for substance use and online network research. PMID:23212348

Land use change in the last century in the Veneto floodplain: effects on network drainage density, water storage, and related consequences on flood risk

NASA Astrophysics Data System (ADS)

Prosdocimi, Massimo; Sofia, Giulia; Dalla Fontana, Giancarlo; Tarolli, Paolo

2013-04-01

In a high-density populated country such as Italy, the anthropic pressure plays a fundamental role in the alteration and the modification of the landscape. Among the most evident anthropic alterations, the most important are the urbanization processes that have been occurring since the end of the second world war. Agricultural activities, housing and other land uses have shifted due to the progressive spreading of urban areas. These modifications affect the hydrologic regimes, but municipalities often are not aware of the real impact of land cover changes on such processes and, consequently, an increase of the elements at risk of flooding is generally registered. The main objective of this work is to evaluate the impact of land cover changes in the Veneto region (north-east Italy), from 1954 to 2006, on the minor drainage network system and on its capacity to attenuate the direct runoff. The major flood event occurred between October and November 2010. The study is a typical agrarian landscape and it has been chosen considering its involvement inthe major flood of 2010 and considering also the availability of high-resolution topographic data (LiDAR-derived DTMs) and historical aerial photographs. Aerial photographs dated back to 1954 and 1981, in particular, have been used either to classify the land cover in five categories according to the first level of the CORINE land cover classification and to identify the minor drainage network. A semi-automatic approach based on the high-resolution DTM (Cazorzi et al., 2012), was also considered to identify the minor drainage network and estimate its water storage capacity. The results underline how land cover variation over the last 50 years has strongly increased the propension of the soil to produce direct runoff (increase of the Curve Number value) and it has also reduced the extent of the minor network system. As a consequence, the capacity of the agrarian minor network to attenuate and laminate a flood event is decreased as well. These analysis can be considered useful tools for a suitable land use planning in flood prone areas. References Cazorzi, F., Dalla Fontana, G., De Luca, A., Sofia, G., Tarolli, P. (2012). Drainage network detection and assessment of network storage capacity in agrarian landscape, Hydrological Processes, ISSN: 0885-6087, doi:10.1002/hyp.9224

Analysis of beachgrass ecomorphodynamics and foredune morphology along US Pacific Northwest coastal sand dunes using a Bayesian network

NASA Astrophysics Data System (ADS)

Biel, R.; Hacker, S.; Ruggiero, P.

2016-12-01

Coastal dunes provide valuable infrastructure for mitigating flooding and erosion hazard exposure by dissipating wave energy. Although vegetation is essential for foredune establishment and growth by facilitating sand deposition and stabilization, few have examined how plant distribution and abundance relates to foredune morphology in the field. The US Pacific Northwest coastal dune system presents an excellent case study for examining ecomorphodynamic processes on sand dunes. It exhibits a diverse array of geomorphological conditions, including a range of dissipative to reflective beaches and highly varied foredune morphology. Ecologically, the region contains two invasive, dune-building beachgrasses of the same genus (Ammophila arenaria and A. breviligulata). To explore how geomorphological and ecological drivers alter foredune morphology, we used a Bayesian network to assess the role of nearshore bathymetry, sand supply (measured as shoreline change rate), and beachgrass species identity and density in determining foredune morphology. At a finer scale, we also examined whether beachgrass density and species identity altered sand accretion between 2012 and 2014 at multiple points across the foredune using a mixed model. Our Bayesian network analysis indicates that nearshore slope, shoreline change rate, beach width, and beachgrass density directly or indirectly affect foredune width, slope, and height. However, we observed no relationships between species identity and foredune morphology. When examining the finer-scale relationship between beachgrass density and sand accretion at points along the foredune, we found that sand accretion was correlated with beachgrass stem density in 2012, new stem growth between 2012 and 2014, beach width, and elevation. Moreover, A. arenaria accreted more sand than A. breviligulata on the foredune face, suggesting that subtle differences in beachgrass morphology or growth patterns may produce differing accretion patterns across the foredune. Both analyses indicate that beachgrass density alters foredune morphology. Although A. arenaria and A. breviligulata exhibit differing sand accretion patterns at points across the foredune face, it is unclear whether these fine-scale differences produce coarse-scale changes in foredune morphology.

Targeted Proteomics and Absolute Protein Quantification for the Construction of a Stoichiometric Host-Pathogen Surface Density Model.

PubMed

Sjöholm, Kristoffer; Kilsgård, Ola; Teleman, Johan; Happonen, Lotta; Malmström, Lars; Malmström, Johan

2017-04-01

Sepsis is a systemic immune response responsible for considerable morbidity and mortality. Molecular modeling of host-pathogen interactions in the disease state represents a promising strategy to define molecular events of importance for the transition from superficial to invasive infectious diseases. Here we used the Gram-positive bacterium Streptococcus pyogenes as a model system to establish a mass spectrometry based workflow for the construction of a stoichiometric surface density model between the S. pyogenes surface, the surface virulence factor M-protein, and adhered human blood plasma proteins. The workflow relies on stable isotope labeled reference peptides and selected reaction monitoring mass spectrometry analysis of a wild-type strain and an M-protein deficient mutant strain, to generate absolutely quantified protein stoichiometry ratios between S. pyogenes and interacting plasma proteins. The stoichiometry ratios in combination with a novel targeted mass spectrometry method to measure cell numbers enabled the construction of a stoichiometric surface density model using protein structures available from the protein data bank. The model outlines the topology and density of the host-pathogen protein interaction network on the S. pyogenes bacterial surface, revealing a dense and highly organized protein interaction network. Removal of the M-protein from S. pyogenes introduces a drastic change in the network topology, validated by electron microscopy. We propose that the stoichiometric surface density model of S. pyogenes in human blood plasma represents a scalable framework that can continuously be refined with the emergence of new results. Future integration of new results will improve the understanding of protein-protein interactions and their importance for bacterial virulence. Furthermore, we anticipate that the general properties of the developed workflow will facilitate the production of stoichiometric surface density models for other types of host-pathogen interactions. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Preliminary design work on a DSN VLBI correlator. [Deep Space Network

NASA Technical Reports Server (NTRS)

Lushbaugh, W. A.; Layland, J. W.

1978-01-01

The Deep Space Network is in the process of fielding high-density digital instrumentation recorders for support of the Pioneer Venus 1978 entry experiment and other related tasks. It has long been obvious that these recorders would also serve well as the recording medium for very long base interferometry (VLBI) experiments with relatively weak radio sources, provided that a suitable correlation processor for these tape recordings could be established. The overall design and current status of a VLBI correlator designed to mate with these tape recorders are described.

Percolation and epidemics in a two-dimensional small world

NASA Astrophysics Data System (ADS)

Newman, M. E.; Jensen, I.; Ziff, R. M.

2002-02-01

Percolation on two-dimensional small-world networks has been proposed as a model for the spread of plant diseases. In this paper we give an analytic solution of this model using a combination of generating function methods and high-order series expansion. Our solution gives accurate predictions for quantities such as the position of the percolation threshold and the typical size of disease outbreaks as a function of the density of ``shortcuts'' in the small-world network. Our results agree with scaling hypotheses and numerical simulations for the same model.

A study of physician collaborations through social network and exponential random graph

PubMed Central

2013-01-01

Background Physician collaboration, which evolves among physicians during the course of providing healthcare services to hospitalised patients, has been seen crucial to effective patient outcomes in healthcare organisations and hospitals. This study aims to explore physician collaborations using measures of social network analysis (SNA) and exponential random graph (ERG) model. Methods Based on the underlying assumption that collaborations evolve among physicians when they visit a common hospitalised patient, this study first proposes an approach to map collaboration network among physicians from the details of their visits to patients. This paper terms this network as physician collaboration network (PCN). Second, SNA measures of degree centralisation, betweenness centralisation and density are used to examine the impact of SNA measures on hospitalisation cost and readmission rate. As a control variable, the impact of patient age on the relation between network measures (i.e. degree centralisation, betweenness centralisation and density) and hospital outcome variables (i.e. hospitalisation cost and readmission rate) are also explored. Finally, ERG models are developed to identify micro-level structural properties of (i) high-cost versus low-cost PCN; and (ii) high-readmission rate versus low-readmission rate PCN. An electronic health insurance claim dataset of a very large Australian health insurance organisation is utilised to construct and explore PCN in this study. Results It is revealed that the density of PCN is positively correlated with hospitalisation cost and readmission rate. In contrast, betweenness centralisation is found negatively correlated with hospitalisation cost and readmission rate. Degree centralisation shows a negative correlation with readmission rate, but does not show any correlation with hospitalisation cost. Patient age does not have any impact for the relation of SNA measures with hospitalisation cost and hospital readmission rate. The 2-star parameter of ERG model has significant impact on hospitalisation cost. Furthermore, it is found that alternative-k-star and alternative-k-two-path parameters of ERG model have impact on readmission rate. Conclusions Collaboration structures among physicians affect hospitalisation cost and hospital readmission rate. The implications of the findings of this study in terms of their potentiality in developing guidelines to improve the performance of collaborative environments among healthcare professionals within healthcare organisations are discussed in this paper. PMID:23803165

Robust diamond-like Fe-Si network in the zero-strain Na xFeSiO 4 cathode

DOE PAGES

Ye, Zhuo; Zhao, Xin; Li, Shouding; ...

2016-07-14

Sodium orthosilicates Na 2 MSiO 4 ( M denotes transition metals) have attracted much attention due to the possibility of exchanging two electrons per formula unit. In this work, we report a group of sodium iron orthosilicates Na 2FeSiO 4. Their crystal structures are characterized by a diamond-like Fe-Si network. The Fe-Si network is quite robust against the charge/discharge process, which explains the high structural stability observed in experiment. Furthermore, using the density functional theory within the GGA + U framework and X-ray diffraction studies, the crystal structures and structural stabilities during the sodium extraction/re-insertion process are systematically investigated.

Faunal and vegetation monitoring in response to harbor dredging in the Port of Miami

USGS Publications Warehouse

Daniels, Andre; Stevenson, Rachael; Smith, Erin; Robblee, Michael

2018-04-11

Seagrasses are highly productive ecosystems. A before-after-control-impact (BACI) design was used to examine effects of dredging on seagrasses and the animals that inhabit them. The control site North Biscayne Bay and the affected site Port of Miami had seagrass densities decrease during both the before, Fish and Invertebrate Assessment Network 2006-2011, and after, Faunal Monitoring in Response to Harbor Dredging 2014-2016, studies. Turbidity levels increased at North Biscayne Bay and Port of Miami basins during the Faunal Monitoring in Response to Harbor Dredging study, especially in 2016. Animal populations decreased significantly in North Biscayne Bay and Port of Miami in the Faunal Monitoring in Response to Harbor Dredging study compared to the Fish and Invertebrate Assessment Network study. Predictive modeling shows that numbers of animal populations will likely continue to decrease if the negative trends in seagrass densities continue unabated. There could be effects on several fisheries vital to the south Florida economy. Additional research could determine if animal populations and seagrass densities have rebounded or continued to decrease.

Metal-Insulator-Semiconductor Nanowire Network Solar Cells.

PubMed

Oener, Sebastian Z; van de Groep, Jorik; Macco, Bart; Bronsveld, Paula C P; Kessels, W M M; Polman, Albert; Garnett, Erik C

2016-06-08

Metal-insulator-semiconductor (MIS) junctions provide the charge separating properties of Schottky junctions while circumventing the direct and detrimental contact of the metal with the semiconductor. A passivating and tunnel dielectric is used as a separation layer to reduce carrier recombination and remove Fermi level pinning. When applied to solar cells, these junctions result in two main advantages over traditional p-n-junction solar cells: a highly simplified fabrication process and excellent passivation properties and hence high open-circuit voltages. However, one major drawback of metal-insulator-semiconductor solar cells is that a continuous metal layer is needed to form a junction at the surface of the silicon, which decreases the optical transmittance and hence short-circuit current density. The decrease of transmittance with increasing metal coverage, however, can be overcome by nanoscale structures. Nanowire networks exhibit precisely the properties that are required for MIS solar cells: closely spaced and conductive metal wires to induce an inversion layer for homogeneous charge carrier extraction and simultaneously a high optical transparency. We experimentally demonstrate the nanowire MIS concept by using it to make silicon solar cells with a measured energy conversion efficiency of 7% (∼11% after correction), an effective open-circuit voltage (Voc) of 560 mV and estimated short-circuit current density (Jsc) of 33 mA/cm(2). Furthermore, we show that the metal nanowire network can serve additionally as an etch mask to pattern inverted nanopyramids, decreasing the reflectivity substantially from 36% to ∼4%. Our extensive analysis points out a path toward nanowire based MIS solar cells that exhibit both high Voc and Jsc values.

Regression of Lingual Lymphatic Vessels in Sodium-restricted Mice.

PubMed

He, Lianying; McCluskey, Lynnette Phillips

2018-05-01

Lymphatic vessel networks can expand and regress, with consequences for interstitial fluid drainage and nutrient supply to tissues, inflammation, and tumor spread. A diet high in sodium stimulates hyperplasia of cutaneous lymphatic capillaries. We hypothesized that dietary sodium restriction would have the opposite effect, shrinking lymphatic capillaries in the tongue. Lingual lymphatic capillary density and size was significantly reduced in mice fed a low-sodium diet (0.03%) for 3 weeks compared with control-fed mice. Blood vessel density was unchanged. Despite lymphatic capillary shrinkage, lingual edema was not observed. The effect on lymphatic capillaries was reversible, as lymphatic density and size in the tongue were restored by 3 weeks on a control diet. Lymphatic hyperplasia induced by a high-sodium diet is dependent on infiltrating macrophages. However, lingual CD68+ macrophage density was unchanged by sodium deficiency, indicating that distinct mechanisms may mediate lymphatic regression. Further studies are needed to test whether dietary sodium restriction is an effective, non-invasive co-therapy for oral cancer.

Evaluating conducting network based transparent electrodes from geometrical considerations

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

Kumar, Ankush; Kulkarni, G. U., E-mail: guk@cens.res.in

2016-01-07

Conducting nanowire networks have been developed as viable alternative to existing indium tin oxide based transparent electrode (TE). The nature of electrical conduction and process optimization for electrodes have gained much from the theoretical models based on percolation transport using Monte Carlo approach and applying Kirchhoff's law on individual junctions and loops. While most of the literature work pertaining to theoretical analysis is focussed on networks obtained from conducting rods (mostly considering only junction resistance), hardly any attention has been paid to those made using template based methods, wherein the structure of network is neither similar to network obtained frommore » conducting rods nor similar to well periodic geometry. Here, we have attempted an analytical treatment based on geometrical arguments and applied image analysis on practical networks to gain deeper insight into conducting networked structure particularly in relation to sheet resistance and transmittance. Many literature examples reporting networks with straight or curvilinear wires with distributions in wire width and length have been analysed by treating the networks as two dimensional graphs and evaluating the sheet resistance based on wire density and wire width. The sheet resistance values from our analysis compare well with the experimental values. Our analysis on various examples has revealed that low sheet resistance is achieved with high wire density and compactness with straight rather than curvilinear wires and with narrower wire width distribution. Similarly, higher transmittance for given sheet resistance is possible with narrower wire width but of higher thickness, minimal curvilinearity, and maximum connectivity. For the purpose of evaluating active fraction of the network, the algorithm was made to distinguish and quantify current carrying backbone regions as against regions containing only dangling or isolated wires. The treatment can be helpful in predicting the properties of a network simply from image analysis and will be helpful in improvisation and comparison of various TEs and better understanding of electrical percolation.« less

Evaluating conducting network based transparent electrodes from geometrical considerations

NASA Astrophysics Data System (ADS)

Kumar, Ankush; Kulkarni, G. U.

2016-01-01

Conducting nanowire networks have been developed as viable alternative to existing indium tin oxide based transparent electrode (TE). The nature of electrical conduction and process optimization for electrodes have gained much from the theoretical models based on percolation transport using Monte Carlo approach and applying Kirchhoff's law on individual junctions and loops. While most of the literature work pertaining to theoretical analysis is focussed on networks obtained from conducting rods (mostly considering only junction resistance), hardly any attention has been paid to those made using template based methods, wherein the structure of network is neither similar to network obtained from conducting rods nor similar to well periodic geometry. Here, we have attempted an analytical treatment based on geometrical arguments and applied image analysis on practical networks to gain deeper insight into conducting networked structure particularly in relation to sheet resistance and transmittance. Many literature examples reporting networks with straight or curvilinear wires with distributions in wire width and length have been analysed by treating the networks as two dimensional graphs and evaluating the sheet resistance based on wire density and wire width. The sheet resistance values from our analysis compare well with the experimental values. Our analysis on various examples has revealed that low sheet resistance is achieved with high wire density and compactness with straight rather than curvilinear wires and with narrower wire width distribution. Similarly, higher transmittance for given sheet resistance is possible with narrower wire width but of higher thickness, minimal curvilinearity, and maximum connectivity. For the purpose of evaluating active fraction of the network, the algorithm was made to distinguish and quantify current carrying backbone regions as against regions containing only dangling or isolated wires. The treatment can be helpful in predicting the properties of a network simply from image analysis and will be helpful in improvisation and comparison of various TEs and better understanding of electrical percolation.

Monitoring of stability of ASG-EUPOS network coordinates

NASA Astrophysics Data System (ADS)

Figurski, M.; Szafranek, K.; Wrona, M.

2009-04-01

ASG-EUPOS (Active Geodetic Network - European Position Determination System) is the national system of precise satellite positioning in Poland, which increases a density of regional and global GNSS networks and is widely used by public administration, national institutions, entrepreneurs and citizens (especially surveyors). In near future ASG-EUPOS is to take role of main national network. Control of proper activity of stations and realization of ETRS'89 is a necessity. User of the system needs to be sure that observations quality and coordinates accuracy are high enough. Coordinates of IGS (International GNSS Service) and EPN (European Permanent Network) stations are precisely determined and any changes are monitored all the time. Observations are verified before they are archived in regional and global databases. The same applies to ASG-EUPOS. This paper concerns standardization of GNSS observations from different stations (uniform adjustment), examination of solutions correctness according to IGS and EPN standards and stability of solutions and sites activity

Electronic system with memristive synapses for pattern recognition

PubMed Central

Park, Sangsu; Chu, Myonglae; Kim, Jongin; Noh, Jinwoo; Jeon, Moongu; Hun Lee, Byoung; Hwang, Hyunsang; Lee, Boreom; Lee, Byung-geun

2015-01-01

Memristive synapses, the most promising passive devices for synaptic interconnections in artificial neural networks, are the driving force behind recent research on hardware neural networks. Despite significant efforts to utilize memristive synapses, progress to date has only shown the possibility of building a neural network system that can classify simple image patterns. In this article, we report a high-density cross-point memristive synapse array with improved synaptic characteristics. The proposed PCMO-based memristive synapse exhibits the necessary gradual and symmetrical conductance changes, and has been successfully adapted to a neural network system. The system learns, and later recognizes, the human thought pattern corresponding to three vowels, i.e. /a /, /i /, and /u/, using electroencephalography signals generated while a subject imagines speaking vowels. Our successful demonstration of a neural network system for EEG pattern recognition is likely to intrigue many researchers and stimulate a new research direction. PMID:25941950

Urban MEMS based seismic network for post-earthquakes rapid disaster assessment

NASA Astrophysics Data System (ADS)

D'Alessandro, Antonino; Luzio, Dario; D'Anna, Giuseppe

2014-05-01

Life losses following disastrous earthquake depends mainly by the building vulnerability, intensity of shaking and timeliness of rescue operations. In recent decades, the increase in population and industrial density has significantly increased the exposure to earthquakes of urban areas. The potential impact of a strong earthquake on a town center can be reduced by timely and correct actions of the emergency management centers. A real time urban seismic network can drastically reduce casualties immediately following a strong earthquake, by timely providing information about the distribution of the ground shaking level. Emergency management centers, with functions in the immediate post-earthquake period, could be use this information to allocate and prioritize resources to minimize loss of human life. However, due to the high charges of the seismological instrumentation, the realization of an urban seismic network, which may allow reducing the rate of fatalities, has not been achieved. Recent technological developments in MEMS (Micro Electro-Mechanical Systems) technology could allow today the realization of a high-density urban seismic network for post-earthquakes rapid disaster assessment, suitable for the earthquake effects mitigation. In the 1990s, MEMS accelerometers revolutionized the automotive-airbag system industry and are today widely used in laptops, games controllers and mobile phones. Due to their great commercial successes, the research into and development of MEMS accelerometers are actively pursued around the world. Nowadays, the sensitivity and dynamics of these sensors are such to allow accurate recording of earthquakes with moderate to strong magnitude. Due to their low cost and small size, the MEMS accelerometers may be employed for the realization of high-density seismic networks. The MEMS accelerometers could be installed inside sensitive places (high vulnerability and exposure), such as schools, hospitals, public buildings and places of worship. The waveforms recorded could be promptly used to determine ground-shaking parameters, like peak ground acceleration/velocity/displacement, Arias and Housner intensity, that could be all used to create, few seconds after a strong earthquakes, shaking maps at urban scale. These shaking maps could allow to quickly identify areas of the town center that have had the greatest earthquake resentment. When a strong seismic event occur, the beginning of the ground motion observed at the site could be used to predict the ensuing ground motion at the same site and so to realize a short term earthquake early warning system. The data acquired after a moderate magnitude earthquake, would provide valuable information for the detail seismic microzonation of the area based on direct earthquake shaking observations rather than from a model-based or indirect methods. In this work, we evaluate the feasibility and effectiveness of such seismic network taking in to account both technological, scientific and economic issues. For this purpose, we have simulated the creation of a MEMS based urban seismic network in a medium size city. For the selected town, taking into account the instrumental specifics, the array geometry and the environmental noise, we investigated the ability of the planned network to detect and measure earthquakes of different magnitude generated from realistic near seismogentic sources.

Carbon nanotube network film directly grown on carbon cloth for high-performance solid-state flexible supercapacitors

NASA Astrophysics Data System (ADS)

Zhou, Cheng; Liu, Jinping

2014-01-01

Carbon nanotubes (CNTs) have received increasing attention as electrode materials for high-performance supercapacitors. We herein present a straightforward method to synthesize CNT films directly on carbon cloths as electrodes for all-solid-state flexible supercapacitors (AFSCs). The as-made highly conductive electrodes possess a three-dimensional (3D) network architecture for fast ion diffusion and good flexibility, leading to an AFSC with a specific capacitance of 106.1 F g-1, an areal capacitance of 38.75 mF cm-2, an ultralong cycle life of 100 000 times (capacitance retention: 99%), a good rate capability (can scan at 1000 mV s-1, at which the capacitance is still ˜37.8% of that at 5 mV s-1), a high energy density (2.4 μW h cm-2) and a high power density (19 mW cm-2). Moreover, our AFSC maintains excellent electrochemical attributes even with serious shape deformation (bending, folding, etc), high mechanical pressure (63 kPa) and a wide temperature window (up to 100 ° C). After charging for only 5 s, three such AFSC devices connected in series can efficiently power a red round LED for 60 s. Our work could pave the way for the design of practical AFSCs, which are expected to be used for various flexible portable/wearable electronic devices in the future.

Diversity Performance Analysis on Multiple HAP Networks

PubMed Central

Dong, Feihong; Li, Min; Gong, Xiangwu; Li, Hongjun; Gao, Fengyue

2015-01-01

One of the main design challenges in wireless sensor networks (WSNs) is achieving a high-data-rate transmission for individual sensor devices. The high altitude platform (HAP) is an important communication relay platform for WSNs and next-generation wireless networks. Multiple-input multiple-output (MIMO) techniques provide the diversity and multiplexing gain, which can improve the network performance effectively. In this paper, a virtual MIMO (V-MIMO) model is proposed by networking multiple HAPs with the concept of multiple assets in view (MAV). In a shadowed Rician fading channel, the diversity performance is investigated. The probability density function (PDF) and cumulative distribution function (CDF) of the received signal-to-noise ratio (SNR) are derived. In addition, the average symbol error rate (ASER) with BPSK and QPSK is given for the V-MIMO model. The system capacity is studied for both perfect channel state information (CSI) and unknown CSI individually. The ergodic capacity with various SNR and Rician factors for different network configurations is also analyzed. The simulation results validate the effectiveness of the performance analysis. It is shown that the performance of the HAPs network in WSNs can be significantly improved by utilizing the MAV to achieve overlapping coverage, with the help of the V-MIMO techniques. PMID:26134102

Spatio-Temporal Patterns of the International Merger and Acquisition Network.

PubMed

Dueñas, Marco; Mastrandrea, Rossana; Barigozzi, Matteo; Fagiolo, Giorgio

2017-09-07

This paper analyses the world web of mergers and acquisitions (M&As) using a complex network approach. We use data of M&As to build a temporal sequence of binary and weighted-directed networks for the period 1995-2010 and 224 countries (nodes) connected according to their M&As flows (links). We study different geographical and temporal aspects of the international M&A network (IMAN), building sequences of filtered sub-networks whose links belong to specific intervals of distance or time. Given that M&As and trade are complementary ways of reaching foreign markets, we perform our analysis using statistics employed for the study of the international trade network (ITN), highlighting the similarities and differences between the ITN and the IMAN. In contrast to the ITN, the IMAN is a low density network characterized by a persistent giant component with many external nodes and low reciprocity. Clustering patterns are very heterogeneous and dynamic. High-income economies are the main acquirers and are characterized by high connectivity, implying that most countries are targets of a few acquirers. Like in the ITN, geographical distance strongly impacts the structure of the IMAN: link-weights and node degrees have a non-linear relation with distance, and an assortative pattern is present at short distances.

Washington's "free" 300-station microscale weather network

Treesearch

Thomas Blackburn

1977-01-01

This article is intended to encourage those planning to conduct meso- or microscale weather studies to supplement their sophisticated observing techniques and equipment- with low-cost observations taken by volunteers. Such observations can often show high benefits per unit costs in expanding the geographical area of study, increasing the density of observations, or in...

Growing instead of confining

NASA Astrophysics Data System (ADS)

Sun, Yang-Kook; Yoon, Chong Seung

2017-10-01

Confining sulfur in high-surface-area carbon is a widely adapted approach in Li-S batteries, but it often results in low sulfur utilization and low energy density. Now, controlled nucleation of discrete Li2S particles on a network of low-surface-area carbon fibres provides a possible solution to the endemic problems of Li-S batteries.

Three-dimensional strutted graphene grown by substrate-free sugar blowing for high-power-density supercapacitors

PubMed Central

Wang, Xuebin; Zhang, Yuanjian; Zhi, Chunyi; Wang, Xi; Tang, Daiming; Xu, Yibin; Weng, Qunhong; Jiang, Xiangfen; Mitome, Masanori; Golberg, Dmitri; Bando, Yoshio

2013-01-01

Three-dimensional graphene architectures in the macroworld can in principle maintain all the extraordinary nanoscale properties of individual graphene flakes. However, current 3D graphene products suffer from poor electrical conductivity, low surface area and insufficient mechanical strength/elasticity; the interconnected self-supported reproducible 3D graphenes remain unavailable. Here we report a sugar-blowing approach based on a polymeric predecessor to synthesize a 3D graphene bubble network. The bubble network consists of mono- or few-layered graphitic membranes that are tightly glued, rigidly fixed and spatially scaffolded by micrometre-scale graphitic struts. Such a topological configuration provides intimate structural interconnectivities, freeway for electron/phonon transports, huge accessible surface area, as well as robust mechanical properties. The graphene network thus overcomes the drawbacks of presently available 3D graphene products and opens up a wide horizon for diverse practical usages, for example, high-power high-energy electrochemical capacitors, as highlighted in this work. PMID:24336225

Three-dimensional strutted graphene grown by substrate-free sugar blowing for high-power-density supercapacitors

NASA Astrophysics Data System (ADS)

Wang, Xuebin; Zhang, Yuanjian; Zhi, Chunyi; Wang, Xi; Tang, Daiming; Xu, Yibin; Weng, Qunhong; Jiang, Xiangfen; Mitome, Masanori; Golberg, Dmitri; Bando, Yoshio

2013-12-01

Three-dimensional graphene architectures in the macroworld can in principle maintain all the extraordinary nanoscale properties of individual graphene flakes. However, current 3D graphene products suffer from poor electrical conductivity, low surface area and insufficient mechanical strength/elasticity; the interconnected self-supported reproducible 3D graphenes remain unavailable. Here we report a sugar-blowing approach based on a polymeric predecessor to synthesize a 3D graphene bubble network. The bubble network consists of mono- or few-layered graphitic membranes that are tightly glued, rigidly fixed and spatially scaffolded by micrometre-scale graphitic struts. Such a topological configuration provides intimate structural interconnectivities, freeway for electron/phonon transports, huge accessible surface area, as well as robust mechanical properties. The graphene network thus overcomes the drawbacks of presently available 3D graphene products and opens up a wide horizon for diverse practical usages, for example, high-power high-energy electrochemical capacitors, as highlighted in this work.

Three-dimensional imaging for precise structural control of Si quantum dot networks for all-Si solar cells

NASA Astrophysics Data System (ADS)

Kourkoutis, Lena F.; Hao, Xiaojing; Huang, Shujuan; Puthen-Veettil, Binesh; Conibeer, Gavin; Green, Martin A.; Perez-Wurfl, Ivan

2013-07-01

All-Si tandem solar cells based on Si quantum dots (QDs) are a promising approach to future high-performance, thin film solar cells using abundant, stable and non-toxic materials. An important prerequisite to achieve a high conversion efficiency in such cells is the ability to control the geometry of the Si QD network. This includes the ability to control both, the size and arrangement of Si QDs embedded in a higher bandgap matrix. Using plasmon tomography we show the size, shape and density of Si QDs, that form in Si rich oxide (SRO)/SiO2 multilayers upon annealing, can be controlled by varying the SRO stoichiometry. Smaller, more spherical QDs of higher densities are obtained at lower Si concentrations. In richer SRO layers ellipsoidal QDs tend to form. Using electronic structure calculations within the effective mass approximation we show that ellipsoidal QDs give rise to reduced inter-QD coupling in the layer. Efficient carrier transport via mini-bands is in this case more likely across the multilayers provided the SiO2 spacer layer is thin enough to allow coupling in the vertical direction.All-Si tandem solar cells based on Si quantum dots (QDs) are a promising approach to future high-performance, thin film solar cells using abundant, stable and non-toxic materials. An important prerequisite to achieve a high conversion efficiency in such cells is the ability to control the geometry of the Si QD network. This includes the ability to control both, the size and arrangement of Si QDs embedded in a higher bandgap matrix. Using plasmon tomography we show the size, shape and density of Si QDs, that form in Si rich oxide (SRO)/SiO2 multilayers upon annealing, can be controlled by varying the SRO stoichiometry. Smaller, more spherical QDs of higher densities are obtained at lower Si concentrations. In richer SRO layers ellipsoidal QDs tend to form. Using electronic structure calculations within the effective mass approximation we show that ellipsoidal QDs give rise to reduced inter-QD coupling in the layer. Efficient carrier transport via mini-bands is in this case more likely across the multilayers provided the SiO2 spacer layer is thin enough to allow coupling in the vertical direction. Electronic supplementary information (ESI) available: Electron tomography reconstruction movies. See DOI: 10.1039/c3nr01998e

Dopamine D1 signaling organizes network dynamics underlying working memory.

PubMed

Roffman, Joshua L; Tanner, Alexandra S; Eryilmaz, Hamdi; Rodriguez-Thompson, Anais; Silverstein, Noah J; Ho, New Fei; Nitenson, Adam Z; Chonde, Daniel B; Greve, Douglas N; Abi-Dargham, Anissa; Buckner, Randy L; Manoach, Dara S; Rosen, Bruce R; Hooker, Jacob M; Catana, Ciprian

2016-06-01

Local prefrontal dopamine signaling supports working memory by tuning pyramidal neurons to task-relevant stimuli. Enabled by simultaneous positron emission tomography-magnetic resonance imaging (PET-MRI), we determined whether neuromodulatory effects of dopamine scale to the level of cortical networks and coordinate their interplay during working memory. Among network territories, mean cortical D1 receptor densities differed substantially but were strongly interrelated, suggesting cross-network regulation. Indeed, mean cortical D1 density predicted working memory-emergent decoupling of the frontoparietal and default networks, which respectively manage task-related and internal stimuli. In contrast, striatal D1 predicted opposing effects within these two networks but no between-network effects. These findings specifically link cortical dopamine signaling to network crosstalk that redirects cognitive resources to working memory, echoing neuromodulatory effects of D1 signaling on the level of cortical microcircuits.

Dopamine D1 signaling organizes network dynamics underlying working memory

PubMed Central

Roffman, Joshua L.; Tanner, Alexandra S.; Eryilmaz, Hamdi; Rodriguez-Thompson, Anais; Silverstein, Noah J.; Ho, New Fei; Nitenson, Adam Z.; Chonde, Daniel B.; Greve, Douglas N.; Abi-Dargham, Anissa; Buckner, Randy L.; Manoach, Dara S.; Rosen, Bruce R.; Hooker, Jacob M.; Catana, Ciprian

2016-01-01

Local prefrontal dopamine signaling supports working memory by tuning pyramidal neurons to task-relevant stimuli. Enabled by simultaneous positron emission tomography–magnetic resonance imaging (PET-MRI), we determined whether neuromodulatory effects of dopamine scale to the level of cortical networks and coordinate their interplay during working memory. Among network territories, mean cortical D1 receptor densities differed substantially but were strongly interrelated, suggesting cross-network regulation. Indeed, mean cortical D1 density predicted working memory–emergent decoupling of the frontoparietal and default networks, which respectively manage task-related and internal stimuli. In contrast, striatal D1 predicted opposing effects within these two networks but no between-network effects. These findings specifically link cortical dopamine signaling to network crosstalk that redirects cognitive resources to working memory, echoing neuromodulatory effects of D1 signaling on the level of cortical microcircuits. PMID:27386561

Inversion of Density Interfaces Using the Pseudo-Backpropagation Neural Network Method

NASA Astrophysics Data System (ADS)

Chen, Xiaohong; Du, Yukun; Liu, Zhan; Zhao, Wenju; Chen, Xiaocheng

2018-05-01

This paper presents a new pseudo-backpropagation (BP) neural network method that can invert multi-density interfaces at one time. The new method is based on the conventional forward modeling and inverse modeling theories in addition to conventional pseudo-BP neural network arithmetic. A 3D inversion model for gravity anomalies of multi-density interfaces using the pseudo-BP neural network method is constructed after analyzing the structure and function of the artificial neural network. The corresponding iterative inverse formula of the space field is presented at the same time. Based on trials of gravity anomalies and density noise, the influence of the two kinds of noise on the inverse result is discussed and the scale of noise requested for the stability of the arithmetic is analyzed. The effects of the initial model on the reduction of the ambiguity of the result and improvement of the precision of inversion are discussed. The correctness and validity of the method were verified by the 3D model of the three interfaces. 3D inversion was performed on the observed gravity anomaly data of the Okinawa trough using the program presented herein. The Tertiary basement and Moho depth were obtained from the inversion results, which also testify the adaptability of the method. This study has made a useful attempt for the inversion of gravity density interfaces.

Polymerization development of "low-shrink" resin composites: Reaction kinetics, polymerization stress and quality of network.

PubMed

Yamasaki, Lilyan C; De Vito Moraes, André G; Barros, Mathew; Lewis, Steven; Francci, Carlos; Stansbury, Jeffrey W; Pfeifer, Carmem S

2013-09-01

To evaluate "low-shrink" composites in terms of polymerization kinetics, stress development and mechanical properties. "Low-shrink" materials (Kalore/KAL, N'Durance/NDUR, and Filtek P90/P90) and one control (Esthet X HD/EHD) were tested. Polymerization stress (PS) was measured using the Instron 5565 tensometer. Volumetric shrinkage (VS) was determined by the ACTA linometer. Elastic modulus (E) and flexural strength (FS) were obtained by a three-point bending test. Degree of conversion (DC) and polymerization rate (Rp) were determined by NIR spectroscopy (6165cm(-1) for dimethacrylates; 4156 and 4071cm(-1) for P90). Photopolymerization was performed at 740mW/cm(2)×27s. Glass transition temperature (Tg), degree of heterogeneity and crosslink density were obtained in a DMA for the fully cured specimens. Analysis of extracts was done by (1)H NMR. Data were analyzed with one-way ANOVA/Tukey's test (α=0.05). The control presented the highest shrinkage and Tg. P90 showed the highest modulus, and NDUR demonstrated the highest conversion. The polymerization rates were comparable for all materials. NDUR and KAL had the highest and the lowest network homogeneity, respectively. The multifunctional P90 had the highest crosslink density, with no difference between other composites. The control had the greatest stress development, similar to NDUR. Crosslinking density and polymer network homogeneity were influenced by degree of conversion and monomer structure. Not all "low-shrink" composites reduced polymerization stress. P90 and NDUR had no leachable monomers, which was also a function of high crosslinking (P90) and high conversion (NDUR). Copyright © 2013 Academy of Dental Materials. All rights reserved.

A method for vibrational assessment of cortical bone

NASA Astrophysics Data System (ADS)

Song, Yan; Gunaratne, Gemunu H.

2006-09-01

Large bones from many anatomical locations of the human skeleton consist of an outer shaft (cortex) surrounding a highly porous internal region (trabecular bone) whose structure is reminiscent of a disordered cubic network. Age related degradation of cortical and trabecular bone takes different forms. Trabecular bone weakens primarily by loss of connectivity of the porous network, and recent studies have shown that vibrational response can be used to obtain reliable estimates for loss of its strength. In contrast, cortical bone degrades via the accumulation of long fractures and changes in the level of mineralization of the bone tissue. In this paper, we model cortical bone by an initially solid specimen with uniform density to which long fractures are introduced; we find that, as in the case of trabecular bone, vibrational assessment provides more reliable estimates of residual strength in cortical bone than is possible using measurements of density or porosity.

Epoxidized Natural Rubber/Chitosan Network Binder for Silicon Anode in Lithium-Ion Battery.

PubMed

Lee, Sang Ha; Lee, Jeong Hun; Nam, Dong Ho; Cho, Misuk; Kim, Jaehoon; Chanthad, Chalathorn; Lee, Youngkwan

2018-05-16

Polymeric binder is extremely important for Si-based anode in lithium-ion batteries due to large volume variation during charging/discharging process. Here, natural rubber-incorporated chitosan networks were designed as a binder material to obtain both adhesion and elasticity. Chitosan could strongly anchor Si particles through hydrogen bonding, while the natural rubber could stretch reversibly during the volume variation of Si particles, resulting in high cyclic performance. The prepared electrode exhibited the specific capacities of 1350 mAh/g after 1600 cycles at the current density of 8 A/g and 2310 mAh/g after 500 cycles at the current density of 1 A/g. Furthermore, the cycle test with limiting lithiation capacity was conducted to study the optimal binder properties at varying degree of the volume expansion of silicon, and it was found that the elastic property of binder material was strongly required when the large volume expansion of Si occurred.

Developing Mesoscale Model of Fibrin-Platelet Network Representing Blood Clotting =

NASA Astrophysics Data System (ADS)

Sun, Yueyi; Nikolov, Svetoslav; Bowie, Sam; Alexeev, Alexander; Lam, Wilbur; Myers, David

Blood clotting disorders which prevent the body's natural ability to achieve hemostasis can lead to a variety of life threatening conditions such as, excessive bleeding, stroke, or heart attack. Treatment of these disorders is highly dependent on understanding the underlying physics behind the clotting process. Since clotting is a highly complex multi scale mechanism developing a fully atomistic model is currently not possible. We develop a mesoscale model based on dissipative particle dynamics (DPD) to gain fundamental understanding of the underlying principles controlling the clotting process. In our study, we examine experimental data on clot contraction using stacks of confocal microscopy images to estimate the crosslink density in the fibrin networks and platelet location. Using this data we reconstruct the platelet rich fibrin network and study how platelet-fibrin interactions affect clotting. Furthermore, we probe how different system parameters affect clot contraction. ANSF CAREER Award DMR-1255288.

Mechanical metamaterials at the theoretical limit of isotropic elastic stiffness

NASA Astrophysics Data System (ADS)

Berger, J. B.; Wadley, H. N. G.; McMeeking, R. M.

2017-02-01

A wide variety of high-performance applications require materials for which shape control is maintained under substantial stress, and that have minimal density. Bio-inspired hexagonal and square honeycomb structures and lattice materials based on repeating unit cells composed of webs or trusses, when made from materials of high elastic stiffness and low density, represent some of the lightest, stiffest and strongest materials available today. Recent advances in 3D printing and automated assembly have enabled such complicated material geometries to be fabricated at low (and declining) cost. These mechanical metamaterials have properties that are a function of their mesoscale geometry as well as their constituents, leading to combinations of properties that are unobtainable in solid materials; however, a material geometry that achieves the theoretical upper bounds for isotropic elasticity and strain energy storage (the Hashin-Shtrikman upper bounds) has yet to be identified. Here we evaluate the manner in which strain energy distributes under load in a representative selection of material geometries, to identify the morphological features associated with high elastic performance. Using finite-element models, supported by analytical methods, and a heuristic optimization scheme, we identify a material geometry that achieves the Hashin-Shtrikman upper bounds on isotropic elastic stiffness. Previous work has focused on truss networks and anisotropic honeycombs, neither of which can achieve this theoretical limit. We find that stiff but well distributed networks of plates are required to transfer loads efficiently between neighbouring members. The resulting low-density mechanical metamaterials have many advantageous properties: their mesoscale geometry can facilitate large crushing strains with high energy absorption, optical bandgaps and mechanically tunable acoustic bandgaps, high thermal insulation, buoyancy, and fluid storage and transport. Our relatively simple design can be manufactured using origami-like sheet folding and bonding methods.

Mechanical metamaterials at the theoretical limit of isotropic elastic stiffness.

PubMed

Berger, J B; Wadley, H N G; McMeeking, R M

2017-03-23

A wide variety of high-performance applications require materials for which shape control is maintained under substantial stress, and that have minimal density. Bio-inspired hexagonal and square honeycomb structures and lattice materials based on repeating unit cells composed of webs or trusses, when made from materials of high elastic stiffness and low density, represent some of the lightest, stiffest and strongest materials available today. Recent advances in 3D printing and automated assembly have enabled such complicated material geometries to be fabricated at low (and declining) cost. These mechanical metamaterials have properties that are a function of their mesoscale geometry as well as their constituents, leading to combinations of properties that are unobtainable in solid materials; however, a material geometry that achieves the theoretical upper bounds for isotropic elasticity and strain energy storage (the Hashin-Shtrikman upper bounds) has yet to be identified. Here we evaluate the manner in which strain energy distributes under load in a representative selection of material geometries, to identify the morphological features associated with high elastic performance. Using finite-element models, supported by analytical methods, and a heuristic optimization scheme, we identify a material geometry that achieves the Hashin-Shtrikman upper bounds on isotropic elastic stiffness. Previous work has focused on truss networks and anisotropic honeycombs, neither of which can achieve this theoretical limit. We find that stiff but well distributed networks of plates are required to transfer loads efficiently between neighbouring members. The resulting low-density mechanical metamaterials have many advantageous properties: their mesoscale geometry can facilitate large crushing strains with high energy absorption, optical bandgaps and mechanically tunable acoustic bandgaps, high thermal insulation, buoyancy, and fluid storage and transport. Our relatively simple design can be manufactured using origami-like sheet folding and bonding methods.

Consistent individual differences and population plasticity in network-derived sociality: An experimental manipulation of density in a gregarious ungulate

PubMed Central

O’Brien, Paul P.; Vander Wal, Eric

2018-01-01

In many taxa, individual social traits appear to be consistent across time and context, thus meeting the criteria for animal personality. How these differences are maintained in response to changes in population density is unknown, particularly in large mammals, such as ungulates. Using a behavioral reaction norm (BRN) framework, we examined how among- and within-individual variation in social connectedness, measured using social network analyses, change as a function of population density. We studied a captive herd of elk (Cervus canadensis) separated into a group of male elk and a group of female elk. Males and females were exposed to three different density treatments and we recorded social associations between individuals with proximity-detecting radio-collars fitted to elk. We constructed social networks using dyadic association data and calculated three social network metrics reflective of social connectedness: eigenvector centrality, graph strength, and degree. Elk exhibited consistent individual differences in social connectedness across densities; however, they showed little individual variation in their response to changes in density, i.e., individuals oftentimes responded plastically, but in the same manner to changes in density. Female elk had highest connectedness at an intermediate density. In contrast, male elk increased connectedness with increasing density. Whereas this may suggest that the benefits of social connectedness outweigh the costs of increased competition at higher density for males, females appear to exhibit a threshold in social benefits (e.g. predator detection and forage information). Our study illustrates the importance of viewing social connectedness as a density-dependent trait, particularly in the context of plasticity. Moreover, we highlight the need to revisit our understanding of density dependence as a population-level phenomenon by accounting for consistent individual differences not only in social connectedness, but likely in other ecological processes (e.g., predator-prey dynamics, mate choice, disease transfer). PMID:29494640

Memory and neural networks on the basis of color centers in solids.

PubMed

Winnacker, Albrecht; Osvet, Andres

2009-11-01

Optical data recording is one of the most widely used and efficient systems of memory in the non-living world. The application of color centers in this context offers not only systems of high speed in writing and read-out due to a high degree of parallelism in data handling but also a possibility to set up models of neural networks. In this way, systems with a high potential for image processing, pattern recognition and logical operations can be constructed. A limitation to storage density is given by the diffraction limit of optical data recording. It is shown that this limitation can at least in principle be overcome by the principle of spectral hole burning, which results in systems of storage capacities close to the human brain system.

OTACT: ONU Turning with Adaptive Cycle Times in Long-Reach PONs

NASA Astrophysics Data System (ADS)

Zare, Sajjad; Ghaffarpour Rahbar, Akbar

2015-01-01

With the expansion of PON networks as Long-Reach PON (LR-PON) networks, the problem of degrading the efficiency of centralized bandwidth allocation algorithms threatens this network due to high propagation delay. This is because these algorithms are based on bandwidth negotiation messages frequently exchanged between the optical line terminal (OLT) in the Central Office and optical network units (ONUs) near the users, which become seriously delayed when the network is extended. To solve this problem, some decentralized algorithms are proposed based on bandwidth negotiation messages frequently exchanged between the Remote Node (RN)/Local Exchange (LX) and ONUs near the users. The network has a relatively high delay since there are relatively large distances between RN/LX and ONUs, and therefore, control messages should travel twice between ONUs and RN/LX in order to go from one ONU to another ONU. In this paper, we propose a novel framework, called ONU Turning with Adaptive Cycle Times (OTACT), that uses Power Line Communication (PLC) to connect two adjacent ONUs. Since there is a large population density in urban areas, ONUs are closer to each other. Thus, the efficiency of the proposed method is high. We investigate the performance of the proposed scheme in contrast with other decentralized schemes under the worst case conditions. Simulation results show that the average upstream packet delay can be decreased under the proposed scheme.

Comparative Study of Human and Mouse Postsynaptic Proteomes Finds High Compositional Conservation and Abundance Differences for Key Synaptic Proteins

PubMed Central

Bayés, Àlex; Collins, Mark O.; Croning, Mike D. R.; van de Lagemaat, Louie N.; Choudhary, Jyoti S.; Grant, Seth G. N.

2012-01-01

Direct comparison of protein components from human and mouse excitatory synapses is important for determining the suitability of mice as models of human brain disease and to understand the evolution of the mammalian brain. The postsynaptic density is a highly complex set of proteins organized into molecular networks that play a central role in behavior and disease. We report the first direct comparison of the proteome of triplicate isolates of mouse and human cortical postsynaptic densities. The mouse postsynaptic density comprised 1556 proteins and the human one 1461. A large compositional overlap was observed; more than 70% of human postsynaptic density proteins were also observed in the mouse postsynaptic density. Quantitative analysis of postsynaptic density components in both species indicates a broadly similar profile of abundance but also shows that there is higher abundance variation between species than within species. Well known components of this synaptic structure are generally more abundant in the mouse postsynaptic density. Significant inter-species abundance differences exist in some families of key postsynaptic density proteins including glutamatergic neurotransmitter receptors and adaptor proteins. Furthermore, we have identified a closely interacting set of molecules enriched in the human postsynaptic density that could be involved in dendrite and spine structural plasticity. Understanding synapse proteome diversity within and between species will be important to further our understanding of brain complexity and disease. PMID:23071613

Nanoscale X-Ray Microscopic Imaging of Mammalian Mineralized Tissue

PubMed Central

Andrews, Joy C.; Almeida, Eduardo; van der Meulen, Marjolein C.H.; Alwood, Joshua S.; Lee, Chialing; Liu, Yijin; Chen, Jie; Meirer, Florian; Feser, Michael; Gelb, Jeff; Rudati, Juana; Tkachuk, Andrei; Yun, Wenbing; Pianetta, Piero

2010-01-01

A novel hard transmission X-ray microscope (TXM) at the Stanford Synchrotron Radiation Light-source operating from 5 to 15 keV X-ray energy with 14 to 30 µm2 field of view has been used for high-resolution (30–40 nm) imaging and density quantification of mineralized tissue. TXM is uniquely suited for imaging of internal cellular structures and networks in mammalian mineralized tissues using relatively thick (50 µm), untreated samples that preserve tissue micro- and nanostructure. To test this method we performed Zernike phase contrast and absorption contrast imaging of mouse cancellous bone prepared under different conditions of in vivo loading, fixation, and contrast agents. In addition, the three-dimensional structure was examined using tomography. Individual osteocytic lacunae were observed embedded within trabeculae in cancellous bone. Extensive canalicular networks were evident and included processes with diameters near the 30–40 nm instrument resolution that have not been reported previously. Trabecular density was quantified relative to rod-like crystalline apatite, and rod-like trabecular struts were found to have 51–54% of pure crystal density and plate-like areas had 44–53% of crystal density. The nanometer resolution of TXM enables future studies for visualization and quantification of ultrastructural changes in bone tissue resulting from osteoporosis, dental disease, and other pathologies. PMID:20374681

Fiber networks amplify active stress

NASA Astrophysics Data System (ADS)

Lenz, Martin; Ronceray, Pierre; Broedersz, Chase

Large-scale force generation is essential for biological functions such as cell motility, embryonic development, and muscle contraction. In these processes, forces generated at the molecular level by motor proteins are transmitted by disordered fiber networks, resulting in large-scale active stresses. While fiber networks are well characterized macroscopically, this stress generation by microscopic active units is not well understood. I will present a comprehensive theoretical study of force transmission in these networks. I will show that the linear, small-force response of the networks is remarkably simple, as the macroscopic active stress depends only on the geometry of the force-exerting unit. In contrast, as non-linear buckling occurs around these units, local active forces are rectified towards isotropic contraction and strongly amplified. This stress amplification is reinforced by the networks' disordered nature, but saturates for high densities of active units. I will show that our predictions are quantitatively consistent with experiments on reconstituted tissues and actomyosin networks, and that they shed light on the role of the network microstructure in shaping active stresses in cells and tissue.

Foldable interpenetrated metal-organic frameworks/carbon nanotubes thin film for lithium-sulfur batteries

NASA Astrophysics Data System (ADS)

Mao, Yiyin; Li, Gaoran; Guo, Yi; Li, Zhoupeng; Liang, Chengdu; Peng, Xinsheng; Lin, Zhan

2017-03-01

Lithium-sulfur batteries are promising technologies for powering flexible devices due to their high energy density, low cost and environmental friendliness, when the insulating nature, shuttle effect and volume expansion of sulfur electrodes are well addressed. Here, we report a strategy of using foldable interpenetrated metal-organic frameworks/carbon nanotubes thin film for binder-free advanced lithium-sulfur batteries through a facile confinement conversion. The carbon nanotubes interpenetrate through the metal-organic frameworks crystal and interweave the electrode into a stratified structure to provide both conductivity and structural integrity, while the highly porous metal-organic frameworks endow the electrode with strong sulfur confinement to achieve good cyclability. These hierarchical porous interpenetrated three-dimensional conductive networks with well confined S8 lead to high sulfur loading and utilization, as well as high volumetric energy density.

Highly Nitrogen-Doped Three-Dimensional Carbon Fibers Network with Superior Sodium Storage Capacity.

PubMed

Lei, Wen; Xiao, Weiping; Li, Jingde; Li, Gaoran; Wu, Zexing; Xuan, Cuijuan; Luo, Dan; Deng, Ya-Ping; Wang, Deli; Chen, Zhongwei

2017-08-30

Inspired by the excellent absorption capability of spongelike bacterial cellulose (BC), three-dimensional hierarchical porous carbon fibers doped with an ultrahigh content of N (21.2 atom %) (i.e., nitrogen-doped carbon fibers, NDCFs) were synthesized by an adsorption-swelling strategy using BC as the carbonaceous material. When used as anode materials for sodium-ion batteries, the NDCFs deliver a high reversible capacity of 86.2 mAh g -1 even after 2000 cycles at a high current density of 10.0 A g -1 . It is proposed that the excellent Na + storage performance is mainly due to the defective surface of the NDCFs created by the high content of N dopant. Density functional theory (DFT) calculations show that the defect sites created by N doping can strongly "host" Na + and therefore contribute to the enhanced storage capacity.

Foldable interpenetrated metal-organic frameworks/carbon nanotubes thin film for lithium–sulfur batteries

PubMed Central

Mao, Yiyin; Li, Gaoran; Guo, Yi; Li, Zhoupeng; Liang, Chengdu; Peng, Xinsheng; Lin, Zhan

2017-01-01

Lithium–sulfur batteries are promising technologies for powering flexible devices due to their high energy density, low cost and environmental friendliness, when the insulating nature, shuttle effect and volume expansion of sulfur electrodes are well addressed. Here, we report a strategy of using foldable interpenetrated metal-organic frameworks/carbon nanotubes thin film for binder-free advanced lithium–sulfur batteries through a facile confinement conversion. The carbon nanotubes interpenetrate through the metal-organic frameworks crystal and interweave the electrode into a stratified structure to provide both conductivity and structural integrity, while the highly porous metal-organic frameworks endow the electrode with strong sulfur confinement to achieve good cyclability. These hierarchical porous interpenetrated three-dimensional conductive networks with well confined S8 lead to high sulfur loading and utilization, as well as high volumetric energy density. PMID:28262801

Forest structure in low-diversity tropical forests: a study of Hawaiian wet and dry forests.

PubMed

Ostertag, Rebecca; Inman-Narahari, Faith; Cordell, Susan; Giardina, Christian P; Sack, Lawren

2014-01-01

The potential influence of diversity on ecosystem structure and function remains a topic of significant debate, especially for tropical forests where diversity can range widely. We used Center for Tropical Forest Science (CTFS) methodology to establish forest dynamics plots in montane wet forest and lowland dry forest on Hawai'i Island. We compared the species diversity, tree density, basal area, biomass, and size class distributions between the two forest types. We then examined these variables across tropical forests within the CTFS network. Consistent with other island forests, the Hawai'i forests were characterized by low species richness and very high relative dominance. The two Hawai'i forests were floristically distinct, yet similar in species richness (15 vs. 21 species) and stem density (3078 vs. 3486/ha). While these forests were selected for their low invasive species cover relative to surrounding forests, both forests averaged 5->50% invasive species cover; ongoing removal will be necessary to reduce or prevent competitive impacts, especially from woody species. The montane wet forest had much larger trees, resulting in eightfold higher basal area and above-ground biomass. Across the CTFS network, the Hawaiian montane wet forest was similar to other tropical forests with respect to diameter distributions, density, and aboveground biomass, while the Hawai'i lowland dry forest was similar in density to tropical forests with much higher diversity. These findings suggest that forest structural variables can be similar across tropical forests independently of species richness. The inclusion of low-diversity Pacific Island forests in the CTFS network provides an ∼80-fold range in species richness (15-1182 species), six-fold variation in mean annual rainfall (835-5272 mm yr(-1)) and 1.8-fold variation in mean annual temperature (16.0-28.4°C). Thus, the Hawaiian forest plots expand the global forest plot network to enable testing of ecological theory for links among species diversity, environmental variation and ecosystem function.

Forest Structure in Low-Diversity Tropical Forests: A Study of Hawaiian Wet and Dry Forests

PubMed Central

Ostertag, Rebecca; Inman-Narahari, Faith; Cordell, Susan; Giardina, Christian P.; Sack, Lawren

2014-01-01

The potential influence of diversity on ecosystem structure and function remains a topic of significant debate, especially for tropical forests where diversity can range widely. We used Center for Tropical Forest Science (CTFS) methodology to establish forest dynamics plots in montane wet forest and lowland dry forest on Hawai‘i Island. We compared the species diversity, tree density, basal area, biomass, and size class distributions between the two forest types. We then examined these variables across tropical forests within the CTFS network. Consistent with other island forests, the Hawai‘i forests were characterized by low species richness and very high relative dominance. The two Hawai‘i forests were floristically distinct, yet similar in species richness (15 vs. 21 species) and stem density (3078 vs. 3486/ha). While these forests were selected for their low invasive species cover relative to surrounding forests, both forests averaged 5–>50% invasive species cover; ongoing removal will be necessary to reduce or prevent competitive impacts, especially from woody species. The montane wet forest had much larger trees, resulting in eightfold higher basal area and above-ground biomass. Across the CTFS network, the Hawaiian montane wet forest was similar to other tropical forests with respect to diameter distributions, density, and aboveground biomass, while the Hawai‘i lowland dry forest was similar in density to tropical forests with much higher diversity. These findings suggest that forest structural variables can be similar across tropical forests independently of species richness. The inclusion of low-diversity Pacific Island forests in the CTFS network provides an ∼80-fold range in species richness (15–1182 species), six-fold variation in mean annual rainfall (835–5272 mm yr−1) and 1.8-fold variation in mean annual temperature (16.0–28.4°C). Thus, the Hawaiian forest plots expand the global forest plot network to enable testing of ecological theory for links among species diversity, environmental variation and ecosystem function. PMID:25162731

Dissipation of ‘dark energy’ by cortex in knowledge retrieval

NASA Astrophysics Data System (ADS)

Capolupo, Antonio; Freeman, Walter J.; Vitiello, Giuseppe

2013-03-01

We have devised a thermodynamic model of cortical neurodynamics expressed at the classical level by neural networks and at the quantum level by dissipative quantum field theory. Our model is based on features in the spatial images of cortical activity newly revealed by high-density electrode arrays. We have incorporated the mechanism and necessity for so-called dark energy in knowledge retrieval. We have extended the model first using the Carnot cycle to define our measures for energy, entropy and temperature, and then using the Rankine cycle to incorporate criticality and phase transitions. We describe the dynamics of two interactive fields of neural activity that express knowledge, one at high and the other at low energy density, and the two operators that create and annihilate the fields. We postulate that the extremely high density of energy sequestered briefly in cortical activity patterns can account for the vividness, richness of associations, and emotional intensity of memories recalled by stimuli.

Dissipation of 'dark energy' by cortex in knowledge retrieval.

PubMed

Capolupo, Antonio; Freeman, Walter J; Vitiello, Giuseppe

2013-03-01

We have devised a thermodynamic model of cortical neurodynamics expressed at the classical level by neural networks and at the quantum level by dissipative quantum field theory. Our model is based on features in the spatial images of cortical activity newly revealed by high-density electrode arrays. We have incorporated the mechanism and necessity for so-called dark energy in knowledge retrieval. We have extended the model first using the Carnot cycle to define our measures for energy, entropy and temperature, and then using the Rankine cycle to incorporate criticality and phase transitions. We describe the dynamics of two interactive fields of neural activity that express knowledge, one at high and the other at low energy density, and the two operators that create and annihilate the fields. We postulate that the extremely high density of energy sequestered briefly in cortical activity patterns can account for the vividness, richness of associations, and emotional intensity of memories recalled by stimuli. Copyright © 2013 Elsevier B.V. All rights reserved.

Electrical Mapping of Silver Nanowire Networks: A Versatile Tool for Imaging Network Homogeneity and Degradation Dynamics during Failure.

PubMed

Sannicolo, Thomas; Charvin, Nicolas; Flandin, Lionel; Kraus, Silas; Papanastasiou, Dorina T; Celle, Caroline; Simonato, Jean-Pierre; Muñoz-Rojas, David; Jiménez, Carmen; Bellet, Daniel

2018-05-22

Electrical stability and homogeneity of silver nanowire (AgNW) networks are critical assets for increasing their robustness and reliability when integrated as transparent electrodes in devices. Our ability to distinguish defects, inhomogeneities, or inactive areas at the scale of the entire network is therefore a critical issue. We propose one-probe electrical mapping (1P-mapping) as a specific simple tool to study the electrical distribution in these discrete structures. 1P-mapping has allowed us to show that the tortuosity of the voltage equipotential lines of AgNW networks under bias decreases with increasing network density, leading to a better electrical homogeneity. The impact of the network fabrication technique on the electrical homogeneity of the resulting electrode has also been investigated. Then, by combining 1P-mapping with electrical resistance measurements and IR thermography, we propose a comprehensive analysis of the evolution of the electrical distribution in AgNW networks when subjected to increasing voltage stresses. We show that AgNW networks experience three distinctive stages: optimization, degradation, and breakdown. We also demonstrate that the failure dynamics of AgNW networks at high voltages occurs through a highly correlated and spatially localized mechanism. In particular the in situ formation of cracks could be clearly visualized. It consists of two steps: creation of a crack followed by propagation nearly parallel to the equipotential lines. Finally, we show that current can dynamically redistribute during failure, by following partially damaged secondary pathways through the crack.

Structures with high number density of carbon nanotubes and 3-dimensional distribution

NASA Technical Reports Server (NTRS)

Chen, Zheng (Inventor); Tzeng, Yonhua (Inventor)

2002-01-01

A composite is described having a three dimensional distribution of carbon nanotubes. The critical aspect of such composites is a nonwoven network of randomly oriented fibers connected at their junctions to afford macropores in the spaces between the fibers. A variety of fibers may be employed, including metallic fibers, and especially nickel fibers. The composite has quite desirable properties for cold field electron emission applications, such as a relatively low turn-on electric field, high electric field enhancement factors, and high current densities. The composites of this invention also show favorable properties for other an electrode applications. Several methods, which also have general application in carbon nanotube production, of preparing these composites are described and employ a liquid feedstock of oxyhydrocarbons as carbon nanotube precursors.

A novel end-to-end fault detection and localization protocol for wavelength-routed WDM networks

NASA Astrophysics Data System (ADS)

Zeng, Hongqing; Vukovic, Alex; Huang, Changcheng

2005-09-01

Recently the wavelength division multiplexing (WDM) networks are becoming prevalent for telecommunication networks. However, even a very short disruption of service caused by network faults may lead to high data loss in such networks due to the high date rates, increased wavelength numbers and density. Therefore, the network survivability is critical and has been intensively studied, where fault detection and localization is the vital part but has received disproportional attentions. In this paper we describe and analyze an end-to-end lightpath fault detection scheme in data plane with the fault notification in control plane. The endeavor is focused on reducing the fault detection time. In this protocol, the source node of each lightpath keeps sending hello packets to the destination node exactly following the path for data traffic. The destination node generates an alarm once a certain number of consecutive hello packets are missed within a given time period. Then the network management unit collects all alarms and locates the faulty source based on the network topology, as well as sends fault notification messages via control plane to either the source node or all upstream nodes along the lightpath. The performance evaluation shows such a protocol can achieve fast fault detection, and at the same time, the overhead brought to the user data by hello packets is negligible.

A distributed network of low-cost continuous reading sensors to measure spatiotemporal variations of PM2.5 in Xi'an, China.

PubMed

Gao, Meiling; Cao, Junji; Seto, Edmund

2015-04-01

Fine particulate matter (PM2.5) is a growing public health concern especially in industrializing countries but existing monitoring networks are unable to properly characterize human exposures due to low resolution spatiotemporal data. Low-cost portable monitors can supplement existing networks in both developed and industrializing regions to increase density of sites and data. This study tests the performance of a low-cost sensor in high concentration urban environments. Seven Portable University of Washington Particle (PUWP) monitors were calibrated with optical and gravimetric PM2.5 reference monitors in Xi'an, China in December 2013. Pairwise correlations between the raw PUWP and the reference monitors were high (R(2) = 0.86-0.89). PUWP monitors were also simultaneously deployed at eight sites across Xi'an alongside gravimetric PM2.5 monitors (R(2) = 0.53). The PUWP monitors were able to identify the High-technology Zone site as a potential PM2.5 hotspot with sustained high concentrations compared to the city average throughout the day. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Infrared spectroscopy of phenol-(H2O)(n>10): structural strains in hydrogen bond networks of neutral water clusters.

PubMed

Mizuse, Kenta; Hamashima, Toru; Fujii, Asuka

2009-11-05

To investigate hydrogen bond network structures of tens of water molecules, we report infrared spectra of moderately size (n)-selected phenol-(H2O)n (approximately 10 < or = n < or = approximately 50), which have essentially the same network structures as (H2O)(n+1). The phenyl group in phenol-(H2O)(n) allows us to apply photoionization-based size selection and infrared-ultraviolet double resonance spectroscopy. The spectra show a clear low-frequency shift of the free OH stretching band with increasing n. Detailed analyses with density functional theory calculations indicate that this shift is accounted for by the hydrogen bond network development from highly strained ones in the small (n < approximately 10) clusters to more relaxed ones in the larger clusters, in addition to the cooperativity of hydrogen bonds.

Food web topology and parasites in the pelagic zone of a subarctic lake

USGS Publications Warehouse

Amundsen, Per-Arne; Lafferty, K.D.; Knudsen, R.; Primicerio, R.; Klemetsen, A.; Kuris, A.M.

2009-01-01

Parasites permeate trophic webs with their often complex life cycles, but few studies have included parasitism in food web analyses. Here we provide a highly resolved food web from the pelagic zone of a subarctic lake and explore how the incorporation of parasites alters the topology of the web. 2. Parasites used hosts at all trophic levels and increased both food-chain lengths and the total number of trophic levels. Their inclusion in the network analyses more than doubled the number of links and resulted in an increase in important food-web characteristics such as linkage density and connectance. 3. More than half of the parasite taxa were trophically transmitted, exploiting hosts at multiple trophic levels and thus increasing the degree of omnivory in the trophic web. 4. For trophically transmitted parasites, the number of parasite-host links exhibited a positive correlation with the linkage density of the host species, whereas no such relationship was seen for nontrophically transmitted parasites. Our findings suggest that the linkage density of free-living species affects their exposure to trophically transmitted parasites, which may be more likely to adopt highly connected species as hosts during the evolution of complex life cycles. 5. The study supports a prominent role for parasites in ecological networks and demonstrates that their incorporation may substantially alter considerations of food-web structure and functioning. ?? 2009 British Ecological Society.

The relative efficiency of modular and non-modular networks of different size

PubMed Central

Tosh, Colin R.; McNally, Luke

2015-01-01

Most biological networks are modular but previous work with small model networks has indicated that modularity does not necessarily lead to increased functional efficiency. Most biological networks are large, however, and here we examine the relative functional efficiency of modular and non-modular neural networks at a range of sizes. We conduct a detailed analysis of efficiency in networks of two size classes: ‘small’ and ‘large’, and a less detailed analysis across a range of network sizes. The former analysis reveals that while the modular network is less efficient than one of the two non-modular networks considered when networks are small, it is usually equally or more efficient than both non-modular networks when networks are large. The latter analysis shows that in networks of small to intermediate size, modular networks are much more efficient that non-modular networks of the same (low) connective density. If connective density must be kept low to reduce energy needs for example, this could promote modularity. We have shown how relative functionality/performance scales with network size, but the precise nature of evolutionary relationship between network size and prevalence of modularity will depend on the costs of connectivity. PMID:25631996

Tough stimuli-responsive supramolecular hydrogels with hydrogen-bonding network junctions.

PubMed

Guo, Mingyu; Pitet, Louis M; Wyss, Hans M; Vos, Matthijn; Dankers, Patricia Y W; Meijer, E W

2014-05-14

Hydrogels were prepared with physical cross-links comprising 2-ureido-4[1H]-pyrimidinone (UPy) hydrogen-bonding units within the backbone of segmented amphiphilic macromolecules having hydrophilic poly(ethylene glycol) (PEG). The bulk materials adopt nanoscopic physical cross-links composed of UPy-UPy dimers embedded in segregated hydrophobic domains dispersed within the PEG matrix as comfirmed by cryo-electron microscopy. The amphiphilic network was swollen with high weight fractions of water (w(H2O) ≈ 0.8) owing to the high PEG weight fraction within the pristine polymers (w(PEG) ≈ 0.9). Two different PEG chain lengths were investigated and illustrate the corresponding consequences of cross-link density on mechanical properties. The resulting hydrogels exhibited high strength and resilience upon deformation, consistent with a microphase separated network, in which the UPy-UPy interactions were adequately shielded within hydrophobic nanoscale pockets that maintain the network despite extensive water content. The cumulative result is a series of tough hydrogels with tunable mechanical properties and tractable synthetic preparation and processing. Furthermore, the melting transition of PEG in the dry polymer was shown to be an effective stimulus for shape memory behavior.

Topology effects on nonaffine behavior of semiflexible fiber networks

NASA Astrophysics Data System (ADS)

Hatami-Marbini, H.; Shriyan, V.

2017-12-01

Filamentous semiflexible networks define the mechanical and physical properties of many materials such as cytoskeleton. In the absence of a distinct unit cell, the Mikado fiber network model is commonly used algorithm for representing the microstructure of these networks in numerical models. Nevertheless, certain types of filamentous structures such as collagenous tissues, at early stages of their development, are assembled by growth of individual fibers from random nucleation sites. In this work, we develop a computational model to investigate the mechanical response of such networks by characterizing their nonaffine behavior. We show that the deformation of these networks is nonaffine at all length scales. Furthermore, similar to Mikado networks, the degree of nonaffinity in these structures decreases with increasing the probing length scale, the network fiber density, and/or the bending stiffness of constituting filaments. Nevertheless, despite the lower coordination number of these networks, their deformation field is more affine than that of the Mikado networks with the same fiber density and fiber mechanical properties.

Measurement of electron density using reactance cutoff probe

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

You, K. H.; Seo, B. H.; Kim, J. H.

2016-05-15

This paper proposes a new measurement method of electron density using the reactance spectrum of the plasma in the cutoff probe system instead of the transmission spectrum. The highly accurate reactance spectrum of the plasma-cutoff probe system, as expected from previous circuit simulations [Kim et al., Appl. Phys. Lett. 99, 131502 (2011)], was measured using the full two-port error correction and automatic port extension methods of the network analyzer. The electron density can be obtained from the analysis of the measured reactance spectrum, based on circuit modeling. According to the circuit simulation results, the reactance cutoff probe can measure themore » electron density more precisely than the previous cutoff probe at low densities or at higher pressure. The obtained results for the electron density are presented and discussed for a wide range of experimental conditions, and this method is compared with previous methods (a cutoff probe using the transmission spectrum and a single Langmuir probe).« less

Path analysis of the energy density of wood in eucalyptus clones.

PubMed

Couto, A M; Teodoro, P E; Trugilho, P F

2017-03-16

Path analysis has been used for establishing selection criteria in genetic breeding programs for several crops. However, it has not been used in eucalyptus breeding programs yet. In the present study, we aimed to identify the wood technology traits that could be used as the criteria for direct and indirect selection of eucalyptus genotypes with high energy density of wood. Twenty-four eucalyptus clones were evaluated in a completely randomized design with five replications. The following traits were assessed: basic wood density, total extractives, lignin content, ash content, nitrogen content, carbon content, hydrogen content, sulfur content, oxygen content, higher calorific power, holocellulose, and energy density. After verifying the variability of all evaluated traits among the clones, a two-dimensional correlation network was used to determine the phenotypic patterns among them. The obtained coefficient of determination (0.94) presented a higher magnitude in relation to the effect of the residual variable, and it served as an excellent model for explaining the genetic effects related to the variations observed in the energy density of wood in all eucalyptus clones. However, for future studies, we recommend evaluating other traits, especially the morphological traits, because of the greater ease in their measurement. Selecting clones with high basic density is the most promising strategy for eucalyptus breeding programs that aim to increase the energy density of wood because of its high heritability and magnitude of the cause-and-effect relationship with this trait.

Fire danger rating network density

Treesearch

Rudy M. King; R. William Furman

1976-01-01

Conventional statistical techniques are used to answer the question, "What is the necessary station density for a fire danger network?" The Burning Index of the National Fire-Danger Rating System is used as an indicator of fire danger. Results are presented as station spacing in tabular form for each of six regions in the western United States.

Using regional bird density distribution models to evaluate protected area networks and inform conservation planning

Treesearch

John D. Alexander; Jaime L. Stephens; Sam Veloz; Leo Salas; Josée S. Rousseau; C. John Ralph; Daniel A. Sarr

2017-01-01

As data about populations of indicator species become available, proactive strategies that improve representation of biological diversity within protected area networks should consider finer-scaled evaluations, especially in regions identified as important through course-scale analyses. We use density distribution models derived from a robust regional bird...

Sodium citrate assisted facile synthesis of AuPd alloy networks for ethanol electrooxidation with high activity and durability

NASA Astrophysics Data System (ADS)

Zhai, Yanling; Zhu, Zhijun; Lu, Xiaolin; Zhou, H. Susan

2016-10-01

The direct ethanol fuel cell is an emerging energy conversion device for which palladium is considered as the one of the most effective components for anode catalyst, however, its widespread application has been still limited by the activity and durability of the anode catalyst. In this work, AuPd alloy networks (NWs) are synthesized using H2PdCl4 and HAuCl4 as precursors reduced by NaBH4 in the presence of sodium citrate (SC). The results reveal that SC plays significant role in network structure, resulting in the enhanced electrocatalytic activity of the catalyst. This self-supported AuPd NWs catalyst exhibits much higher electrochemical catalytic activity than commercial Pd/C catalyst toward ethanol electrooxidation in alkaline solution. Significantly, AuPd NWs catalyst shows extremely high durability at the beginning of the chronoamperometry test, and as high as 49% of the mass current density (1.41 A/mgPd) remains after 4000 s current-time test at -0.3 V (vs. Ag/AgCl) in N2-saturated KOH-ethanol solution. This strategy provides a facile method for the preparation of alloy networks with high electrochemical activity, and can be potentially expanded to a variety of electrochemical applications.

Thermochemical Stability and Friction Properties of Soft Organosilica Networks for Solid Lubrication.

PubMed

Gonzalez Rodriguez, Pablo; Dral, A Petra; van den Nieuwenhuijzen, Karin J H; Lette, Walter; Schipper, Dik J; Ten Elshof, Johan E

2018-01-24

In view of their possible application as high temperature solid lubricants, the tribological and thermochemical properties of several organosilica networks were investigated over a range of temperatures between 25 and 580 °C. Organosilica networks, obtained from monomers with terminal and bridging organic groups, were synthesized by a sol-gel process. The influence of carbon content, crosslink density, rotational freedom of incorporated hydrocarbon groups, and network connectivity on the high temperature friction properties of the polymer was studied for condensed materials from silicon alkoxide precursors with terminating organic groups, i.e., methyltrimethoxysilane, propyltrimethoxysilane, diisopropyldimethoxysilane, cyclohexyltrimethoxysilane, phenyltrimethoxysilane and 4-biphenylyltriethoxysilane networks, as well as precursors with organic bridging groups between Si centers, i.e., 1,4-bis(triethoxysilyl)benzene and 4,4'-bis(triethoxysilyl)-1,1'-biphenyl. Pin-on-disc measurements were performed using all selected solid lubricants. It was found that materials obtained from phenyltrimethoxysilane and cyclohexyltrimethoxysilane precursors showed softening above 120 °C and performed best in terms of friction reduction, reaching friction coefficients as low as 0.01. This value is lower than that of graphite films (0.050 ± 0.005), a common bench mark for solid lubricants.

Thermochemical Stability and Friction Properties of Soft Organosilica Networks for Solid Lubrication

PubMed Central

Gonzalez Rodriguez, Pablo; van den Nieuwenhuijzen, Karin J. H.; Lette, Walter; Schipper, Dik J.

2018-01-01

In view of their possible application as high temperature solid lubricants, the tribological and thermochemical properties of several organosilica networks were investigated over a range of temperatures between 25 and 580 °C. Organosilica networks, obtained from monomers with terminal and bridging organic groups, were synthesized by a sol-gel process. The influence of carbon content, crosslink density, rotational freedom of incorporated hydrocarbon groups, and network connectivity on the high temperature friction properties of the polymer was studied for condensed materials from silicon alkoxide precursors with terminating organic groups, i.e., methyltrimethoxysilane, propyltrimethoxysilane, diisopropyldimethoxysilane, cyclohexyltrimethoxysilane, phenyltrimethoxysilane and 4-biphenylyltriethoxysilane networks, as well as precursors with organic bridging groups between Si centers, i.e., 1,4-bis(triethoxysilyl)benzene and 4,4′-bis(triethoxysilyl)-1,1′-biphenyl. Pin-on-disc measurements were performed using all selected solid lubricants. It was found that materials obtained from phenyltrimethoxysilane and cyclohexyltrimethoxysilane precursors showed softening above 120 °C and performed best in terms of friction reduction, reaching friction coefficients as low as 0.01. This value is lower than that of graphite films (0.050 ± 0.005), a common bench mark for solid lubricants. PMID:29364164

Carbonaceous nanowire supports for polymer electrolyte membrane fuel cells

DOE PAGES

Garzon, Fernando H.; Wilson, Mahlon S.; Banham, Dustin; ...

2015-12-03

Here, carbohydrate-dye combinations were used to form ionically-linked soft templates for the formation of polypyrrole nanowire networks. High yields of nanostructured products were obtained using small amounts of low-cost carbohydrate and dye template materials, the majority of which remained encapsulated within the nanowires. Varying the concentration and the two-part ratio of the templates influenced the length and diameter of the nanofiber segments within the nanowire network. Pyrolysis of the nanowires yielded carbonaceous fibers containing nitrogen heteroatoms, as well as convoluted graphitic domains, well suited for supporting Pt nanoparticles. The resulting high density of nucleation sites enabled the formation of wellmore » dispersed, smaller Pt particles compared to commercial catalysts, despite significantly higher support surface loadings.« less

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.

Changes in the interaction of resting-state neural networks from adolescence to adulthood.

PubMed

Stevens, Michael C; Pearlson, Godfrey D; Calhoun, Vince D

2009-08-01

This study examined how the mutual interactions of functionally integrated neural networks during resting-state fMRI differed between adolescence and adulthood. Independent component analysis (ICA) was used to identify functionally connected neural networks in 100 healthy participants aged 12-30 years. Hemodynamic timecourses that represented integrated neural network activity were analyzed with tools that quantified system "causal density" estimates, which indexed the proportion of significant Granger causality relationships among system nodes. Mutual influences among networks decreased with age, likely reflecting stronger within-network connectivity and more efficient between-network influences with greater development. Supplemental tests showed that this normative age-related reduction in causal density was accompanied by fewer significant connections to and from each network, regional increases in the strength of functional integration within networks, and age-related reductions in the strength of numerous specific system interactions. The latter included paths between lateral prefrontal-parietal circuits and "default mode" networks. These results contribute to an emerging understanding that activity in widely distributed networks thought to underlie complex cognition influences activity in other networks. (c) 2009 Wiley-Liss, Inc.

Simple and Inexpensive Paper-Based Astrocyte Co-culture to Improve Survival of Low-Density Neuronal Networks

PubMed Central

Aebersold, Mathias J.; Thompson-Steckel, Greta; Joutang, Adriane; Schneider, Moritz; Burchert, Conrad; Forró, Csaba; Weydert, Serge; Han, Hana; Vörös, János

2018-01-01

Bottom-up neuroscience aims to engineer well-defined networks of neurons to investigate the functions of the brain. By reducing the complexity of the brain to achievable target questions, such in vitro bioassays better control experimental variables and can serve as a versatile tool for fundamental and pharmacological research. Astrocytes are a cell type critical to neuronal function, and the addition of astrocytes to neuron cultures can improve the quality of in vitro assays. Here, we present cellulose as an astrocyte culture substrate. Astrocytes cultured on the cellulose fiber matrix thrived and formed a dense 3D network. We devised a novel co-culture platform by suspending the easy-to-handle astrocytic paper cultures above neuronal networks of low densities typically needed for bottom-up neuroscience. There was significant improvement in neuronal viability after 5 days in vitro at densities ranging from 50,000 cells/cm2 down to isolated cells at 1,000 cells/cm2. Cultures exhibited spontaneous spiking even at the very low densities, with a significantly greater spike frequency per cell compared to control mono-cultures. Applying the co-culture platform to an engineered network of neurons on a patterned substrate resulted in significantly improved viability and almost doubled the density of live cells. Lastly, the shape of the cellulose substrate can easily be customized to a wide range of culture vessels, making the platform versatile for different applications that will further enable research in bottom-up neuroscience and drug development. PMID:29535595

Mineral-Templated 3D Graphene Architectures for Energy-Efficient Electrodes.

PubMed

Zhang, Mingchao; Chen, Ke; Wang, Chunya; Jian, Muqiang; Yin, Zhe; Liu, Zhenglian; Hong, Guo; Liu, Zhongfan; Zhang, Yingying

2018-05-01

3D graphene networks have shown extraordinary promise for high-performance electrochemical devices. Herein, the chemical vapor deposition synthesis of a highly porous 3D graphene foam (3D-GF) using naturally abundant calcined Iceland crystal as the template is reported. Intriguingly, the Iceland crystal transforms to CaO monolith with evenly distributed micro/meso/macropores through the releasing of CO 2 at high temperature. Meanwhile, the hierarchical structure of the calcined template could be easily tuned under different calcination conditions. By precisely inheriting fine structure from the templates, the as-prepared 3D-GF possesses a tunable hierarchical porosity and low density. Thus, the hierarchical pores offer space for guest hybridization and provide an efficient pathway for ion/charge transport in typical energy conversion/storage systems. The 3D-GF skeleton electrode hybridized with Ni(OH) 2 /Co(OH) 2 through an optimal electrodeposition condition exhibits a high specific capacitance of 2922.2 F g -1 at a scan rate of 10 mV s -1 , and 2138.4 F g -1 at a discharge current density of 3.1 A g -1 . The hybrid 3D-GF symmetry supercapacitor shows a high energy density of 83.0 Wh kg -1 at a power density of 1011.3 W kg -1 and 31.4 Wh kg -1 at a high power density of 18 845.2 W kg -1 . The facile fabrication process enables the mass production of hierarchical porous 3D-GF for high-performance supercapacitors. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Analysis of Near-field of Circular Aperture Antennas with Application to Study of High Intensity Radio Frequency (HIRF) Hazards to Aviation from JPL/NASA Deep Space Network Antennas

NASA Technical Reports Server (NTRS)

Jamnejad, Vahraz; Statman, Joseph

2013-01-01

This work includes a simplified analysis of the radiated near to mid-field from JPL/NASA Deep Space Network (DSN) reflector antennas and uses an averaging technique over the main beam region and beyond for complying with FAA regulations in specific aviation environments. The work identifies areas that require special attention, including the implications of the very narrow beam of the DSN transmitters. The paper derives the maximum averaged power densities allowed and identifies zones where mitigation measures are required.

Flow Correlated Percolation during Vascular Remodeling in Growing Tumors

NASA Astrophysics Data System (ADS)

Lee, D.-S.; Rieger, H.; Bartha, K.

2006-02-01

A theoretical model based on the molecular interactions between a growing tumor and a dynamically evolving blood vessel network describes the transformation of the regular vasculature in normal tissues into a highly inhomogeneous tumor specific capillary network. The emerging morphology, characterized by the compartmentalization of the tumor into several regions differing in vessel density, diameter, and necrosis, is in accordance with experimental data for human melanoma. Vessel collapse due to a combination of severely reduced blood flow and solid stress exerted by the tumor leads to a correlated percolation process that is driven towards criticality by the mechanism of hydrodynamic vessel stabilization.

Automated assessment of breast tissue density in non-contrast 3D CT images without image segmentation based on a deep CNN

NASA Astrophysics Data System (ADS)

Zhou, Xiangrong; Kano, Takuya; Koyasu, Hiromi; Li, Shuo; Zhou, Xinxin; Hara, Takeshi; Matsuo, Masayuki; Fujita, Hiroshi

2017-03-01

This paper describes a novel approach for the automatic assessment of breast density in non-contrast three-dimensional computed tomography (3D CT) images. The proposed approach trains and uses a deep convolutional neural network (CNN) from scratch to classify breast tissue density directly from CT images without segmenting the anatomical structures, which creates a bottleneck in conventional approaches. Our scheme determines breast density in a 3D breast region by decomposing the 3D region into several radial 2D-sections from the nipple, and measuring the distribution of breast tissue densities on each 2D section from different orientations. The whole scheme is designed as a compact network without the need for post-processing and provides high robustness and computational efficiency in clinical settings. We applied this scheme to a dataset of 463 non-contrast CT scans obtained from 30- to 45-year-old-women in Japan. The density of breast tissue in each CT scan was assigned to one of four categories (glandular tissue within the breast <25%, 25%-50%, 50%-75%, and >75%) by a radiologist as ground truth. We used 405 CT scans for training a deep CNN and the remaining 58 CT scans for testing the performance. The experimental results demonstrated that the findings of the proposed approach and those of the radiologist were the same in 72% of the CT scans among the training samples and 76% among the testing samples. These results demonstrate the potential use of deep CNN for assessing breast tissue density in non-contrast 3D CT images.

The maturation of cortical sleep rhythms and networks over early development.

PubMed

Chu, C J; Leahy, J; Pathmanathan, J; Kramer, M A; Cash, S S

2014-07-01

Although neuronal activity drives all aspects of cortical development, how human brain rhythms spontaneously mature remains an active area of research. We sought to systematically evaluate the emergence of human brain rhythms and functional cortical networks over early development. We examined cortical rhythms and coupling patterns from birth through adolescence in a large cohort of healthy children (n=384) using scalp electroencephalogram (EEG) in the sleep state. We found that the emergence of brain rhythms follows a stereotyped sequence over early development. In general, higher frequencies increase in prominence with striking regional specificity throughout development. The coordination of these rhythmic activities across brain regions follows a general pattern of maturation in which broadly distributed networks of low-frequency oscillations increase in density while networks of high frequency oscillations become sparser and more highly clustered. Our results indicate that a predictable program directs the development of key rhythmic components and physiological brain networks over early development. This work expands our knowledge of normal cortical development. The stereotyped neurophysiological processes observed at the level of rhythms and networks may provide a scaffolding to support critical periods of cognitive growth. Furthermore, these conserved patterns could provide a sensitive biomarker for cortical health across development. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

The maturation of cortical sleep rhythms and networks over early development

PubMed Central

Chu, CJ; Leahy, J; Pathmanathan, J; Kramer, MA; Cash, SS

2014-01-01

Objective Although neuronal activity drives all aspects of cortical development, how human brain rhythms spontaneously mature remains an active area of research. We sought to systematically evaluate the emergence of human brain rhythms and functional cortical networks over early development. Methods We examined cortical rhythms and coupling patterns from birth through adolescence in a large cohort of healthy children (n=384) using scalp electroencephalogram (EEG) in the sleep state. Results We found that the emergence of brain rhythms follows a stereotyped sequence over early development. In general, higher frequencies increase in prominence with striking regional specificity throughout development. The coordination of these rhythmic activities across brain regions follows a general pattern of maturation in which broadly distributed networks of low-frequency oscillations increase in density while networks of high frequency oscillations become sparser and more highly clustered. Conclusion Our results indicate that a predictable program directs the development of key rhythmic components and physiological brain networks over early development. Significance This work expands our knowledge of normal cortical development. The stereotyped neurophysiological processes observed at the level of rhythms and networks may provide a scaffolding to support critical periods of cognitive growth. Furthermore, these conserved patterns could provide a sensitive biomarker for cortical health across development. PMID:24418219

Grey matter networks in people at increased familial risk for schizophrenia.

PubMed

Tijms, Betty M; Sprooten, Emma; Job, Dominic; Johnstone, Eve C; Owens, David G C; Willshaw, David; Seriès, Peggy; Lawrie, Stephen M

2015-10-01

Grey matter brain networks are disrupted in schizophrenia, but it is still unclear at which point during the development of the illness these disruptions arise and whether these can be associated with behavioural predictors of schizophrenia. We investigated if single-subject grey matter networks were disrupted in a sample of people at familial risk of schizophrenia. Single-subject grey matter networks were extracted from structural MRI scans of 144 high risk subjects, 32 recent-onset patients and 36 healthy controls. The following network properties were calculated: size, connectivity density, degree, path length, clustering coefficient, betweenness centrality and small world properties. People at risk of schizophrenia showed decreased path length and clustering in mostly prefrontal and temporal areas. Within the high risk sample, the path length of the posterior cingulate cortex and the betweenness centrality of the left inferior frontal operculum explained 81% of the variance in schizotypal cognitions, which was previously shown to be the strongest behavioural predictor of schizophrenia in the study. In contrast, local grey matter volume measurements explained 48% of variance in schizotypy. The present results suggest that single-subject grey matter networks can quantify behaviourally relevant biological alterations in people at increased risk for schizophrenia before disease onset. Copyright © 2015 Elsevier B.V. All rights reserved.

Scaling an in situ network for high resolution modeling during SMAPVEX15

NASA Astrophysics Data System (ADS)

Coopersmith, E. J.; Cosh, M. H.; Jacobs, J. M.; Jackson, T. J.; Crow, W. T.; Holifield Collins, C.; Goodrich, D. C.; Colliander, A.

2015-12-01

Among the greatest challenges within the field of soil moisture estimation is that of scaling sparse point measurements within a network to produce higher resolution map products. Large-scale field experiments present an ideal opportunity to develop methodologies for this scaling, by coupling in situ networks, temporary networks, and aerial mapping of soil moisture. During the Soil Moisture Active Passive Validation Experiments in 2015 (SMAPVEX15) in and around the USDA-ARS Walnut Gulch Experimental Watershed and LTAR site in southeastern Arizona, USA, a high density network of soil moisture stations was deployed across a sparse, permanent in situ network in coordination with intensive soil moisture sampling and an aircraft campaign. This watershed is also densely instrumented with precipitation gages (one gauge/0.57 km2) to monitor the North American Monsoon System, which dominates the hydrologic cycle during the summer months in this region. Using the precipitation and soil moisture time series values provided, a physically-based model is calibrated that will provide estimates at the 3km, 9km, and 36km scales. The results from this model will be compared with the point-scale gravimetric samples, aircraft-based sensor, and the satellite-based products retrieved from NASA's Soil Moisture Active Passive mission.

Identification of neuronal network properties from the spectral analysis of calcium imaging signals in neuronal cultures.

PubMed

Tibau, Elisenda; Valencia, Miguel; Soriano, Jordi

2013-01-01

Neuronal networks in vitro are prominent systems to study the development of connections in living neuronal networks and the interplay between connectivity, activity and function. These cultured networks show a rich spontaneous activity that evolves concurrently with the connectivity of the underlying network. In this work we monitor the development of neuronal cultures, and record their activity using calcium fluorescence imaging. We use spectral analysis to characterize global dynamical and structural traits of the neuronal cultures. We first observe that the power spectrum can be used as a signature of the state of the network, for instance when inhibition is active or silent, as well as a measure of the network's connectivity strength. Second, the power spectrum identifies prominent developmental changes in the network such as GABAA switch. And third, the analysis of the spatial distribution of the spectral density, in experiments with a controlled disintegration of the network through CNQX, an AMPA-glutamate receptor antagonist in excitatory neurons, reveals the existence of communities of strongly connected, highly active neurons that display synchronous oscillations. Our work illustrates the interest of spectral analysis for the study of in vitro networks, and its potential use as a network-state indicator, for instance to compare healthy and diseased neuronal networks.

Relationships between cortical myeloarchitecture and electrophysiological networks

PubMed Central

Hunt, Benjamin A. E.; Tewarie, Prejaas K.; Mougin, Olivier E.; Geades, Nicolas; Singh, Krish D.; Morris, Peter G.; Gowland, Penny A.; Brookes, Matthew J.

2016-01-01

The human brain relies upon the dynamic formation and dissolution of a hierarchy of functional networks to support ongoing cognition. However, how functional connectivities underlying such networks are supported by cortical microstructure remains poorly understood. Recent animal work has demonstrated that electrical activity promotes myelination. Inspired by this, we test a hypothesis that gray-matter myelin is related to electrophysiological connectivity. Using ultra-high field MRI and the principle of structural covariance, we derive a structural network showing how myelin density differs across cortical regions and how separate regions can exhibit similar myeloarchitecture. Building upon recent evidence that neural oscillations mediate connectivity, we use magnetoencephalography to elucidate networks that represent the major electrophysiological pathways of communication in the brain. Finally, we show that a significant relationship exists between our functional and structural networks; this relationship differs as a function of neural oscillatory frequency and becomes stronger when integrating oscillations over frequency bands. Our study sheds light on the way in which cortical microstructure supports functional networks. Further, it paves the way for future investigations of the gray-matter structure/function relationship and its breakdown in pathology. PMID:27830650

Mobilizing homeless youth for HIV prevention: a social network analysis of the acceptability of a face-to-face and online social networking intervention.

PubMed

Rice, Eric; Tulbert, Eve; Cederbaum, Julie; Barman Adhikari, Anamika; Milburn, Norweeta G

2012-04-01

The objective of the study is to use social network analysis to examine the acceptability of a youth-led, hybrid face-to-face and online social networking HIV prevention program for homeless youth.Seven peer leaders (PLs) engaged face-to-face homeless youth (F2F) in the creation of digital media projects (e.g. You Tube videos). PL and F2F recruited online youth (OY) to participate in MySpace and Facebook communities where digital media was disseminated and discussed. The resulting social networks were assessed with respect to size, growth, density, relative centrality of positions and homophily of ties. Seven PL, 53 F2F and 103 OY created two large networks. After the first 50 F2F youth participated, online networks entered a rapid growth phase. OY were among the most central youth in these networks. Younger aged persons and females were disproportionately connected to like youth. The program appears highly acceptable to homeless youth. Social network analysis revealed which PL were the most critical to the program and which types of participants (younger youth and females) may require additional outreach efforts in the future.

Mobilizing homeless youth for HIV prevention: a social network analysis of the acceptability of a face-to-face and online social networking intervention

PubMed Central

Rice, Eric; Tulbert, Eve; Cederbaum, Julie; Barman Adhikari, Anamika; Milburn, Norweeta G.

2012-01-01

The objective of the study is to use social network analysis to examine the acceptability of a youth-led, hybrid face-to-face and online social networking HIV prevention program for homeless youth.Seven peer leaders (PLs) engaged face-to-face homeless youth (F2F) in the creation of digital media projects (e.g. You Tube videos). PL and F2F recruited online youth (OY) to participate in MySpace and Facebook communities where digital media was disseminated and discussed. The resulting social networks were assessed with respect to size, growth, density, relative centrality of positions and homophily of ties. Seven PL, 53 F2F and 103 OY created two large networks. After the first 50 F2F youth participated, online networks entered a rapid growth phase. OY were among the most central youth in these networks. Younger aged persons and females were disproportionately connected to like youth. The program appears highly acceptable to homeless youth. Social network analysis revealed which PL were the most critical to the program and which types of participants (younger youth and females) may require additional outreach efforts in the future. PMID:22247453

Geometric characterization and simulation of planar layered elastomeric fibrous biomaterials

PubMed Central

Carleton, James B.; D'Amore, Antonio; Feaver, Kristen R.; Rodin, Gregory J.; Sacks, Michael S.

2014-01-01

Many important biomaterials are composed of multiple layers of networked fibers. While there is a growing interest in modeling and simulation of the mechanical response of these biomaterials, a theoretical foundation for such simulations has yet to be firmly established. Moreover, correctly identifying and matching key geometric features is a critically important first step for performing reliable mechanical simulations. The present work addresses these issues in two ways. First, using methods of geometric probability we develop theoretical estimates for the mean linear and areal fiber intersection densities for two-dimensional fibrous networks. These densities are expressed in terms of the fiber density and the orientation distribution function, both of which are relatively easy-to-measure properties. Secondly, we develop a random walk algorithm for geometric simulation of two-dimensional fibrous networks which can accurately reproduce the prescribed fiber density and orientation distribution function. Furthermore, the linear and areal fiber intersection densities obtained with the algorithm are in agreement with the theoretical estimates. Both theoretical and computational results are compared with those obtained by post-processing of SEM images of actual scaffolds. These comparisons reveal difficulties inherent to resolving fine details of multilayered fibrous networks. The methods provided herein can provide a rational means to define and generate key geometric features from experimentally measured or prescribed scaffold structural data. PMID:25311685

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.

Mining and integration of pathway diagrams from imaging data.

PubMed

Kozhenkov, Sergey; Baitaluk, Michael

2012-03-01

Pathway diagrams from PubMed and World Wide Web (WWW) contain valuable highly curated information difficult to reach without tools specifically designed and customized for the biological semantics and high-content density of the images. There is currently no search engine or tool that can analyze pathway images, extract their pathway components (molecules, genes, proteins, organelles, cells, organs, etc.) and indicate their relationships. Here, we describe a resource of pathway diagrams retrieved from article and web-page images through optical character recognition, in conjunction with data mining and data integration methods. The recognized pathways are integrated into the BiologicalNetworks research environment linking them to a wealth of data available in the BiologicalNetworks' knowledgebase, which integrates data from >100 public data sources and the biomedical literature. Multiple search and analytical tools are available that allow the recognized cellular pathways, molecular networks and cell/tissue/organ diagrams to be studied in the context of integrated knowledge, experimental data and the literature. BiologicalNetworks software and the pathway repository are freely available at www.biologicalnetworks.org. Supplementary data are available at Bioinformatics online.

FM-UWB: Towards a Robust, Low-Power Radio for Body Area Networks

PubMed Central

Kopta, Vladimir; Farserotu, John; Enz, Christian

2017-01-01

The Frequency Modulated Ultra-Wideband (FM-UWB) is known as a low-power, low-complexity modulation scheme targeting low to moderate data rates in applications such as wireless body area networks. In this paper, a thorough review of all FM-UWB receivers and transmitters reported in literature is presented. The emphasis is on trends in power reduction that exhibit an improvement by a factor 20 over the past eight years, showing the high potential of FM-UWB. The main architectural and circuit techniques that have led to this improvement are highlighted. Seldom explored potential of using higher data rates and more complex modulations is demonstrated as a way to increase energy efficiency of FM-UWB. Multi-user communication over a single Radio Frequency (RF) channel is explored in more depth and multi-channel transmission is proposed as an extension of standard FM-UWB. The two techniques provide means of decreasing network latency, improving performance, and allow the FM-UWB to accommodate the increasing number of sensor nodes in the emerging applications such as High-Density Wireless Sensor Networks. PMID:28481248

Talking the talk, walking the walk: social network norms, communication patterns, and condom use among the male partners of female sex workers in La Romana, Dominican Republic.

PubMed

Barrington, Clare; Latkin, Carl; Sweat, Michael D; Moreno, Luis; Ellen, Jonathan; Kerrigan, Deanna

2009-06-01

Male partners of female sex workers are rarely targeted by HIV prevention interventions in the commercial sex industry, despite recognition of their central role and power in condom use negotiation. Social networks offer a naturally existing social structure to increase male participation in preventing HIV. The purpose of this study was to explore the relationship between social network norms and condom use among male partners of female sex workers in La Romana, Dominican Republic. Male partners (N =318) were recruited from 36 sex establishments to participate in a personal network survey. Measures of social network norms included 1) perceived condom use by male social network members and 2) encouragement to use condoms from social network members. Other social network characteristics included composition, density, social support, and communication. The primary behavioral outcome was consistent condom use by male partners with their most recent female sex worker partner during the last 3 months. In general, men reported small, dense networks with high levels of communication about condoms and consistent condom use. Multivariate logistic regression revealed consistent condom use was significantly more likely among male partners who perceived that some or all of their male social network members used condoms consistently. Perceived condom use was, in turn, significantly associated with dense networks, expressing dislike for condoms, and encouragement to use condoms from social network members. Findings suggest that the tight social networks of male partners may help to explain the high level of condom use and could provide an entry point for HIV prevention efforts with men. Such efforts should tap into existing social dynamics and patterns of communication to promote pro-condom norms and reduce HIV-related vulnerability among men and their sexual partners.

Improving referrals and integrating family planning and HIV services through organizational network strengthening.

PubMed

Thomas, James C; Reynolds, Heidi W; Alterescu, Xavier; Bevc, Christine; Tsegaye, Ademe

2016-04-01

The service needs of people with human immunodeficiency virus (HIV) in low-income settings are wide-ranging. Service provision in a community is often disjointed among a variety of providers. We sought to reduce unmet patient needs by increasing referral coordination for HIV and family planning, measured as network density, with an organizational network approach. We conducted organizational network analysis on two networks in sub-cities of Addis Ababa, Ethiopia. There were 25 organizations in one sub-city network and 26 in the other. In one of them we sought to increase referrals through three network strengthening meetings. We then conducted the network analysis again in both sub-cities to measure any changes since baseline. We also quantitatively measured reported client service needs in both sub-cities before and after the intervention with two cross-sectional samples of face-to-face interviews with clients (459 at baseline and 587 at follow-up). In the sub-city with the intervention, the number of referral connections between organizations, measured as network density, increased 55%. In the control community, the density decreased over the same period. Reported unmet client service needs declined more consistently across services in the intervention community. This quasi experiment demonstrated that (1) an organizational network analysis can inform an intervention, (2) a modest network strengthening intervention can enhance client referrals in the network, (3) improvement in client referrals was accompanied by a decrease in atient-reported unmet needs and (4) a series of network analyses can be a useful evaluation tool. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Nitrogen and phosphorus co-doped carbon hollow spheres derived from polypyrrole for high-performance supercapacitor electrodes

NASA Astrophysics Data System (ADS)

Lv, Bingjie; Li, Peipei; Liu, Yan; Lin, Shanshan; Gao, Bifen; Lin, Bizhou

2018-04-01

Nitrogen and phosphorus co-doped carbon hollow spheres (NPCHSs) have been prepared by a carbonization and subsequent chemical activation route using dehydrated polypyrrole hollow spheres as the precursor and KOH as the activating agent. NPCHSs are interconnected into a unique 3D porous network, which endows the as-prepared carbon to exhibit a large specific surface area of 1155 m2 g-1 and a high specific capacitance of 232 F g-1 at a current density of 1 A g-1. The as-obtained NPCHSs present a high-level heteroatom doping with N, O and P contents of 11.4, 6.7 and 3.5 wt%, respectively. The capacitance of NPCHSs has been retained at 89.1% after 5000 charge-discharge cycles at a relatively high current density of 5 A g-1. Such excellent performance suggests that NPCHSs are attractive electrode candidates for electrical double layer capacitors.

Mass transport enhancement in redox flow batteries with corrugated fluidic networks

NASA Astrophysics Data System (ADS)

Lisboa, Kleber Marques; Marschewski, Julian; Ebejer, Neil; Ruch, Patrick; Cotta, Renato Machado; Michel, Bruno; Poulikakos, Dimos

2017-08-01

We propose a facile, novel concept of mass transfer enhancement in flow batteries based on electrolyte guidance in rationally designed corrugated channel systems. The proposed fluidic networks employ periodic throttling of the flow to optimally deflect the electrolytes into the porous electrode, targeting enhancement of the electrolyte-electrode interaction. Theoretical analysis is conducted with channels in the form of trapezoidal waves, confirming and detailing the mass transport enhancement mechanism. In dilute concentration experiments with an alkaline quinone redox chemistry, a scaling of the limiting current with Re0.74 is identified, which compares favourably against the Re0.33 scaling typical of diffusion-limited laminar processes. Experimental IR-corrected polarization curves are presented for high concentration conditions, and a significant performance improvement is observed with the narrowing of the nozzles. The adverse effects of periodic throttling on the pumping power are compared with the benefits in terms of power density, and an improvement of up to 102% in net power density is obtained in comparison with the flow-by case employing straight parallel channels. The proposed novel concept of corrugated fluidic networks comes with facile fabrication and contributes to the improvement of the transport characteristics and overall performance of redox flow battery systems.

Bio-inspired spider-web-like membranes with a hierarchical structure for high performance lithium/sodium ion battery electrodes: the case of 3D freestanding and binder-free bismuth/CNF anodes.

PubMed

Jin, Yuqiang; Yuan, Haocheng; Lan, Jin-Le; Yu, Yunhua; Lin, Yuan-Hua; Yang, Xiaoping

2017-09-14

High gravimetric energy density and volumetric energy density energy storage devices are highly desirable due to the rapid development of electric vehicles, and portable and wearable electronic equipment. Electrospinning is a promising technology for preparing freestanding electrodes with high gravimetric and volumetric energy density. However, the energy density of the traditional electrospun electrodes is restricted by the low mass loading of active materials (e.g. 20%-30 wt%). Herein, a biomimetic strategy inspired by the phenomenon of the sticky spider web is demonstrated as a high performance anode, which simultaneously improves the gravimetric and volumetric energy density. Freestanding carbon nanofiber (CNF) membranes containing over 50 wt% of bismuth were prepared by electrospinning and subsequent thermal treatment. Membranes consisting of CNF network structures bonded tightly with active Bi cluster materials, resulting in excellent mechanical protection and a fast charge transport path, which are difficult to achieve simultaneously. The composite membrane delivers high reversible capacity (483 mA h g -1 at 100 mA g -1 after 200 cycles) and high rate performance (242 mA h g -1 at 1 A g -1 ) as a lithium-ion battery anode. For use as a sodium ion battery, the composite membrane also shows a high reversible specific capacity of 346 mA h g -1 and outstanding cycling performance (186 mA h g -1 at 50 mA g -1 after 100 cycles). This work offers a simple, low cost and eco-friendly method for fabricating free-standing and binder-free composite electrodes with high loading used in LIBs and SIBs.

Soil Bacterial Diversity Is Associated with Human Population Density in Urban Greenspaces.

PubMed

Wang, Haitao; Cheng, Minying; Dsouza, Melissa; Weisenhorn, Pamela; Zheng, Tianling; Gilbert, Jack A

2018-05-01

Urban greenspaces provide extensive ecosystem services, including pollutant remediation, water management, carbon maintenance, and nutrient cycling. However, while the urban soil microbiota underpin these services, we still have limited understanding of the factors that influence their distribution. We characterized soil bacterial communities from turf-grasses associated with urban parks, streets, and residential sites across a major urban environment, including a gradient of human population density. Bacterial diversity was significantly positively correlated with the population density; and species diversity was greater in park and street soils, compared to residential soils. Population density and greenspace type also led to significant differences in the microbial community composition that was also significantly correlated with soil pH, moisture, and texture. Co-occurrence network analysis revealed that microbial guilds in urban soils were well correlated. Abundant soil microbes in high density population areas had fewer interactions, while abundant bacteria in high moisture soils had more interactions. These results indicate the significant influence of changes in urban demographics and land-use on soil microbial communities. As urbanization is rapidly growing across the planet, it is important to improve our understanding of the consequences of urban zoning on the soil microbiota.

Porous, one-dimensional and high aspect ratio nanofibric network of cobalt manganese oxide as a high performance material for aqueous and solid-state supercapacitor (2 V)

NASA Astrophysics Data System (ADS)

Bhagwan, Jai; Sivasankaran, V.; Yadav, K. L.; Sharma, Yogesh

2016-09-01

Porous nanofibric network of spinel CoMn2O4 (CMO) are fabricated by facile electrospinning process and characterized by XRD, BET, TGA, FTIR, FESEM, TEM, XPS techniques. CMO nanofibers are employed as supercapacitor electrode for first time which exhibits high specific capacitance (Cs) of 320(±5) F g-1 and 270(±5) F g-1 at 1 A g-1 and 5 A g-1, respectively in 1 M H2SO4. CMO nanofibers exhibit excellent cyclability (till 10,000 cycles @ 5 A g-1). To examine practical performance, solid-state symmetric supercapacitor (SSSC) is also fabricated using PVA-H2SO4 as gel electrolyte. The SSSC evinces high energy density of 75 W h kg-1 (comparable to Pb-acid and Ni-MH battery) along with high power density of 2 kW kg-1. Furthermore, a red colored LED (1.8 V @ current 20 mA) was lit for 5 min using single SSSC device supporting its output voltage of 2 V. This high performance of CMO in both aqueous and SSSC is attributed to one dimensional nanofibers consisting of voids/gaps with minimum inter-particle resistance that facilitates smoother transportation of electrons/ions. These voids/gaps in CMO (structural as well as morphological) act as intercalation/de-intercalation sites for extra storage performance, and also works as buffering space to accommodate stress/strain produced while long term cyclings.

Complexity Optimization and High-Throughput Low-Latency Hardware Implementation of a Multi-Electrode Spike-Sorting Algorithm

PubMed Central

Dragas, Jelena; Jäckel, David; Hierlemann, Andreas; Franke, Felix

2017-01-01

Reliable real-time low-latency spike sorting with large data throughput is essential for studies of neural network dynamics and for brain-machine interfaces (BMIs), in which the stimulation of neural networks is based on the networks' most recent activity. However, the majority of existing multi-electrode spike-sorting algorithms are unsuited for processing high quantities of simultaneously recorded data. Recording from large neuronal networks using large high-density electrode sets (thousands of electrodes) imposes high demands on the data-processing hardware regarding computational complexity and data transmission bandwidth; this, in turn, entails demanding requirements in terms of chip area, memory resources and processing latency. This paper presents computational complexity optimization techniques, which facilitate the use of spike-sorting algorithms in large multi-electrode-based recording systems. The techniques are then applied to a previously published algorithm, on its own, unsuited for large electrode set recordings. Further, a real-time low-latency high-performance VLSI hardware architecture of the modified algorithm is presented, featuring a folded structure capable of processing the activity of hundreds of neurons simultaneously. The hardware is reconfigurable “on-the-fly” and adaptable to the nonstationarities of neuronal recordings. By transmitting exclusively spike time stamps and/or spike waveforms, its real-time processing offers the possibility of data bandwidth and data storage reduction. PMID:25415989

Complexity optimization and high-throughput low-latency hardware implementation of a multi-electrode spike-sorting algorithm.

PubMed

Dragas, Jelena; Jackel, David; Hierlemann, Andreas; Franke, Felix

2015-03-01

Reliable real-time low-latency spike sorting with large data throughput is essential for studies of neural network dynamics and for brain-machine interfaces (BMIs), in which the stimulation of neural networks is based on the networks' most recent activity. However, the majority of existing multi-electrode spike-sorting algorithms are unsuited for processing high quantities of simultaneously recorded data. Recording from large neuronal networks using large high-density electrode sets (thousands of electrodes) imposes high demands on the data-processing hardware regarding computational complexity and data transmission bandwidth; this, in turn, entails demanding requirements in terms of chip area, memory resources and processing latency. This paper presents computational complexity optimization techniques, which facilitate the use of spike-sorting algorithms in large multi-electrode-based recording systems. The techniques are then applied to a previously published algorithm, on its own, unsuited for large electrode set recordings. Further, a real-time low-latency high-performance VLSI hardware architecture of the modified algorithm is presented, featuring a folded structure capable of processing the activity of hundreds of neurons simultaneously. The hardware is reconfigurable “on-the-fly” and adaptable to the nonstationarities of neuronal recordings. By transmitting exclusively spike time stamps and/or spike waveforms, its real-time processing offers the possibility of data bandwidth and data storage reduction.

Estimating the hydraulic conductivity of two-dimensional fracture networks

NASA Astrophysics Data System (ADS)

Leung, C. T.; Zimmerman, R. W.

2010-12-01

Most oil and gas reservoirs, as well as most potential sites for nuclear waste disposal, are naturally fractured. In these sites, the network of fractures will provide the main path for fluid to flow through the rock mass. In many cases, the fracture density is so high as to make it impractical to model it with a discrete fracture network (DFN) approach. For such rock masses, it would be useful to have recourse to analytical, or semi-analytical, methods to estimate the macroscopic hydraulic conductivity of the fracture network. We have investigated single-phase fluid flow through stochastically generated two-dimensional fracture networks. The centres and orientations of the fractures are uniformly distributed, whereas their lengths follow either a lognormal distribution or a power law distribution. We have considered the case where the fractures in the network each have the same aperture, as well as the case where the aperture of each fracture is directly proportional to the fracture length. The discrete fracture network flow and transport simulator NAPSAC, developed by Serco (Didcot, UK), is used to establish the “true” macroscopic hydraulic conductivity of the network. We then attempt to match this conductivity using a simple estimation method that does not require extensive computation. For our calculations, fracture networks are represented as networks composed of conducting segments (bonds) between nodes. Each bond represents the region of a single fracture between two adjacent intersections with other fractures. We assume that the bonds are arranged on a kagome lattice, with some fraction of the bonds randomly missing. The conductance of each bond is then replaced with some effective conductance, Ceff, which we take to be the arithmetic mean of the individual conductances, averaged over each bond, rather than over each fracture. This is in contrast to the usual approximation used in effective medium theories, wherein the geometric mean is used. Our explanation is that the conductivities of the bonds that meet at a given node in a fracture network do not satisfy the usual assumption of being uncorrelated; rather, the conductances of at least two of these bonds are highly correlated, as they represent the incoming and outgoing branches of the same fracture. The effective conductance of our idealized “equivalent network” is then trivial to calculate. We find that this estimate of the hydraulic conductivity agrees very closely with the numerically computed value, essentially for all fracture densities that are not too close to the percolation threshold. Moreover, the same methodology applies regardless of whether the fracture lengths are distributed lognormally, or according to a power law.

Multipath Routing in Wireless Sensor Networks: Survey and Research Challenges

PubMed Central

Radi, Marjan; Dezfouli, Behnam; Bakar, Kamalrulnizam Abu; Lee, Malrey

2012-01-01

A wireless sensor network is a large collection of sensor nodes with limited power supply and constrained computational capability. Due to the restricted communication range and high density of sensor nodes, packet forwarding in sensor networks is usually performed through multi-hop data transmission. Therefore, routing in wireless sensor networks has been considered an important field of research over the past decade. Nowadays, multipath routing approach is widely used in wireless sensor networks to improve network performance through efficient utilization of available network resources. Accordingly, the main aim of this survey is to present the concept of the multipath routing approach and its fundamental challenges, as well as the basic motivations for utilizing this technique in wireless sensor networks. In addition, we present a comprehensive taxonomy on the existing multipath routing protocols, which are especially designed for wireless sensor networks. We highlight the primary motivation behind the development of each protocol category and explain the operation of different protocols in detail, with emphasis on their advantages and disadvantages. Furthermore, this paper compares and summarizes the state-of-the-art multipath routing techniques from the network application point of view. Finally, we identify open issues for further research in the development of multipath routing protocols for wireless sensor networks. PMID:22368490

Multipath routing in wireless sensor networks: survey and research challenges.

PubMed

Radi, Marjan; Dezfouli, Behnam; Abu Bakar, Kamalrulnizam; Lee, Malrey

2012-01-01

A wireless sensor network is a large collection of sensor nodes with limited power supply and constrained computational capability. Due to the restricted communication range and high density of sensor nodes, packet forwarding in sensor networks is usually performed through multi-hop data transmission. Therefore, routing in wireless sensor networks has been considered an important field of research over the past decade. Nowadays, multipath routing approach is widely used in wireless sensor networks to improve network performance through efficient utilization of available network resources. Accordingly, the main aim of this survey is to present the concept of the multipath routing approach and its fundamental challenges, as well as the basic motivations for utilizing this technique in wireless sensor networks. In addition, we present a comprehensive taxonomy on the existing multipath routing protocols, which are especially designed for wireless sensor networks. We highlight the primary motivation behind the development of each protocol category and explain the operation of different protocols in detail, with emphasis on their advantages and disadvantages. Furthermore, this paper compares and summarizes the state-of-the-art multipath routing techniques from the network application point of view. Finally, we identify open issues for further research in the development of multipath routing protocols for wireless sensor networks.

Right-side-stretched multifractal spectra indicate small-worldness in networks

NASA Astrophysics Data System (ADS)

Oświȩcimka, Paweł; Livi, Lorenzo; Drożdż, Stanisław

2018-04-01

Complex network formalism allows to explain the behavior of systems composed by interacting units. Several prototypical network models have been proposed thus far. The small-world model has been introduced to mimic two important features observed in real-world systems: i) local clustering and ii) the possibility to move across a network by means of long-range links that significantly reduce the characteristic path length. A natural question would be whether there exist several ;types; of small-world architectures, giving rise to a continuum of models with properties (partially) shared with other models belonging to different network families. Here, we take advantage of the interplay between network theory and time series analysis and propose to investigate small-world signatures in complex networks by analyzing multifractal characteristics of time series generated from such networks. In particular, we suggest that the degree of right-sided asymmetry of multifractal spectra is linked with the degree of small-worldness present in networks. This claim is supported by numerical simulations performed on several parametric models, including prototypical small-world networks, scale-free, fractal and also real-world networks describing protein molecules. Our results also indicate that right-sided asymmetry emerges with the presence of the following topological properties: low edge density, low average shortest path, and high clustering coefficient.

Networks of military alliances, wars, and international trade

PubMed Central

Jackson, Matthew O.; Nei, Stephen

2015-01-01

We investigate the role of networks of alliances in preventing (multilateral) interstate wars. We first show that, in the absence of international trade, no network of alliances is peaceful and stable. We then show that international trade induces peaceful and stable networks: Trade increases the density of alliances so that countries are less vulnerable to attack and also reduces countries’ incentives to attack an ally. We present historical data on wars and trade showing that the dramatic drop in interstate wars since 1950 is paralleled by a densification and stabilization of trading relationships and alliances. Based on the model we also examine some specific relationships, finding that countries with high levels of trade with their allies are less likely to be involved in wars with any other countries (including allies and nonallies), and that an increase in trade between two countries correlates with a lower chance that they will go to war with each other. PMID:26668370

Networks of military alliances, wars, and international trade.

PubMed

Jackson, Matthew O; Nei, Stephen

2015-12-15

We investigate the role of networks of alliances in preventing (multilateral) interstate wars. We first show that, in the absence of international trade, no network of alliances is peaceful and stable. We then show that international trade induces peaceful and stable networks: Trade increases the density of alliances so that countries are less vulnerable to attack and also reduces countries' incentives to attack an ally. We present historical data on wars and trade showing that the dramatic drop in interstate wars since 1950 is paralleled by a densification and stabilization of trading relationships and alliances. Based on the model we also examine some specific relationships, finding that countries with high levels of trade with their allies are less likely to be involved in wars with any other countries (including allies and nonallies), and that an increase in trade between two countries correlates with a lower chance that they will go to war with each other.

Implanted neural network potentials: Application to Li-Si alloys

NASA Astrophysics Data System (ADS)

Onat, Berk; Cubuk, Ekin D.; Malone, Brad D.; Kaxiras, Efthimios

2018-03-01

Modeling the behavior of materials composed of elements with different bonding and electronic structure character for large spatial and temporal scales and over a large compositional range is a challenging problem. Cases in point are amorphous alloys of Si, a prototypical covalent material, and Li, a prototypical metal, which are being considered as anodes for high-energy-density batteries. To address this challenge, we develop a methodology based on neural networks that extends the conventional training approach to incorporate pre-trained parts that capture the character of different components, into the overall network; we refer to this model as the "implanted neural network" method. We show that this approach works well for the Si-Li amorphous alloys for a wide range of compositions, giving good results for key quantities like the diffusion coefficients. The method is readily generalizable to more complicated situations that involve two or more different elements.

On Crowd-verification of Biological Networks

PubMed Central

Ansari, Sam; Binder, Jean; Boue, Stephanie; Di Fabio, Anselmo; Hayes, William; Hoeng, Julia; Iskandar, Anita; Kleiman, Robin; Norel, Raquel; O’Neel, Bruce; Peitsch, Manuel C.; Poussin, Carine; Pratt, Dexter; Rhrissorrakrai, Kahn; Schlage, Walter K.; Stolovitzky, Gustavo; Talikka, Marja

2013-01-01

Biological networks with a structured syntax are a powerful way of representing biological information generated from high density data; however, they can become unwieldy to manage as their size and complexity increase. This article presents a crowd-verification approach for the visualization and expansion of biological networks. Web-based graphical interfaces allow visualization of causal and correlative biological relationships represented using Biological Expression Language (BEL). Crowdsourcing principles enable participants to communally annotate these relationships based on literature evidences. Gamification principles are incorporated to further engage domain experts throughout biology to gather robust peer-reviewed information from which relationships can be identified and verified. The resulting network models will represent the current status of biological knowledge within the defined boundaries, here processes related to human lung disease. These models are amenable to computational analysis. For some period following conclusion of the challenge, the published models will remain available for continuous use and expansion by the scientific community. PMID:24151423

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

Jones, J.B.; Safinya, C.R.

Neurofilaments (NFs) are a major constituent of nerve cell axons that assemble from three subunit proteins of low (NF-L), medium (NF-M), and high (NF-H) molecular weight into a 10nm diameter rod with radiating sidearms to form a bottle-brush-like structure. Here, we reassemble NFs in vitro from varying weight ratios of the subunit proteins, purified from bovine spinal cord, to form homopolymers of NF-L or filaments composed of NF-L and NF-M (NF-LM), NF-L and NF-H (NF-LH), or all three subunits (NF-LMH). At high protein concentrations, NFs align to form a nematic liquid crystalline gel with a well-defined spacing determined with synchrotronmore » small angle x-ray scattering. Near physiological conditions (86mM monovalent salt and pH 6.8), NF-LM networks with a high NF-M grafting density favor nematic ordering whereas filaments composed of NF-LH transition to an isotropic gel at low protein concentrations as a function of increasing mole fraction of NF-H subunits. The interfilament distance decreases with NF-M grafting density, opposite the trend seen with NF-LH networks. This suggests a competition between the more attractive NF-M sidearms, forming a compact aligned nematic gel, and the repulsive NF-H sidearms, favoring a more expansive isotropic gel, at 86mM monovalent salt. These interactions are highly salt dependent and the nematic gel phase is stabilized with increasing monovalent salt.« less

Ni nanoparticles@Ni-Mo nitride nanorod arrays: a novel 3D-network hierarchical structure for high areal capacitance hybrid supercapacitors.

PubMed

Ruan, Yunjun; Lv, Lin; Li, Zhishan; Wang, Chundong; Jiang, Jianjun

2017-11-23

Because of the advanced nature of their high power density, fast charge/discharge time, excellent cycling stability, and safety, supercapacitors have attracted intensive attention for large-scale applications. Nevertheless, one of the obstacles for their further development is their low energy density caused by sluggish redox reaction kinetics, low electroactive electrode materials, and/or high internal resistance. Here, we develop a facile and simple nitridation process to successfully synthesize hierarchical Ni nanoparticle decorated Ni 0.2 Mo 0.8 N nanorod arrays on a nickel foam (Ni-Mo-N NRA/NF) from its NiMoO 4 precursor, which delivers a high areal capacity of 2446 mC cm -2 at a current density of 2 mA cm -2 and shows outstanding cycling stability. The superior performance of the Ni-Mo-N NRA/NF can be ascribed to the metallic conductive nature of the Ni-Mo nitride, the fast surface redox reactions for the electrolyte ions and electrode materials, and the low contacted resistance between the active materials and the current collectors. Furthermore, a hybrid supercapacitor (HSC) is assembled using the Ni-Mo-N NRA/NF as the positive electrode and reduced graphene oxide (RGO) as the negative electrode. The optimized HSC exhibits excellent electrochemical performance with a high energy density of 40.9 W h kg -1 at a power density of 773 W kg -1 and a retention of 80.1% specific capacitance after 6000 cycles. These results indicate that the Ni-Mo-N NRA/NF have a promising potential for use in high-performance supercapacitors.

Spectroscopy of metal "superatom" nanoclusters and high-Tc superconducting pairing

NASA Astrophysics Data System (ADS)

Halder, Avik; Kresin, Vitaly V.

2015-12-01

A unique property of metal nanoclusters is the "superatom" shell structure of their delocalized electrons. The electronic shell levels are highly degenerate and therefore represent sharp peaks in the density of states. This can enable exceptionally strong electron pairing in certain clusters composed of tens to hundreds of atoms. In a finite system, such as a free nanocluster or a nucleus, pairing is observed most clearly via its effect on the energy spectrum of the constituent fermions. Accordingly, we performed a photoionization spectroscopy study of size-resolved aluminum nanoclusters and observed a rapid rise in the near-threshold density of states of several clusters (A l37 ,44 ,66 ,68 ) with decreasing temperature. The characteristics of this behavior are consistent with compression of the density of states by a pairing transition into a high-temperature superconducting state with Tc≳100 K. This value exceeds that of bulk aluminum by two orders of magnitude. These results highlight the potential of novel pairing effects in size-quantized systems and the possibility to attain even higher critical temperatures by optimizing the particles' size and composition. As a new class of high-temperature superconductors, such metal nanocluster particles are promising building blocks for high-Tc materials, devices, and networks.

Network analysis of team communication in a busy emergency department

PubMed Central

2013-01-01

Background The Emergency Department (ED) is consistently described as a high-risk environment for patients and clinicians that demands colleagues quickly work together as a cohesive group. Communication between nurses, physicians, and other ED clinicians is complex and difficult to track. A clear understanding of communications in the ED is lacking, which has a potentially negative impact on the design and effectiveness of interventions to improve communications. We sought to use Social Network Analysis (SNA) to characterize communication between clinicians in the ED. Methods Over three-months, we surveyed to solicit the communication relationships between clinicians at one urban academic ED across all shifts. We abstracted survey responses into matrices, calculated three standard SNA measures (network density, network centralization, and in-degree centrality), and presented findings stratified by night/day shift and over time. Results We received surveys from 82% of eligible participants and identified wide variation in the magnitude of communication cohesion (density) and concentration of communication between clinicians (centralization) by day/night shift and over time. We also identified variation in in-degree centrality (a measure of power/influence) by day/night shift and over time. Conclusions We show that SNA measurement techniques provide a comprehensive view of ED communication patterns. Our use of SNA revealed that frequency of communication as a measure of interdependencies between ED clinicians varies by day/night shift and over time. PMID:23521890

Spatial overlap links seemingly unconnected genotype-matched TB cases in rural Uganda

PubMed Central

Kato-Maeda, Midori; Emperador, Devy M.; Wandera, Bonnie; Mugagga, Olive; Crandall, John; Janes, Michael; Marquez, Carina; Kamya, Moses R.; Charlebois, Edwin D.; Havlir, Diane V.

2018-01-01

Introduction Incomplete understanding of TB transmission dynamics in high HIV prevalence settings remains an obstacle for prevention. Understanding where transmission occurs could provide a platform for case finding and interrupting transmission. Methods From 2012–2015, we sought to recruit all adults starting TB treatment in a Ugandan community. Participants underwent household (HH) contact investigation, and provided names of social contacts, sites of work, healthcare and socializing, and two sputum samples. Mycobacterium tuberculosis culture-positive specimens underwent 24-loci MIRU-VNTR and spoligotyping. We sought to identify epidemiologic links between genotype-matched cases by analyzing social networks and mapping locations where cases reported spending ≥12 hours over the one-month pre-treatment. Sites of spatial overlap (≤100m) between genotype-matched cases were considered potential transmission sites. We analyzed social networks stratified by genotype clustering status, with cases linked by shared locations, and compared network density by location type between clustered vs. non-clustered cases. Results Of 173 adults with TB, 131 (76%) were enrolled, 108 provided sputum, and 84/131 (78%) were MTB culture-positive: 52% (66/131) tested HIV-positive. Of 118 adult HH contacts, 105 (89%) were screened and 3 (2.5%) diagnosed with active TB. Overall, 33 TB cases (39%) belonged to 15 distinct MTB genotype-matched clusters. Within each cluster, no cases shared a HH or reported shared non-HH contacts. In 6/15 (40%) clusters, potential epidemiologic links were identified by spatial overlap at specific locations: 5/6 involved health care settings. Genotype-clustered TB social networks had significantly greater network density based on shared clinics (p<0.001) and decreased density based on shared marketplaces (p<0.001), compared to non-clustered networks. Conclusions In this molecular epidemiologic study, links between MTB genotype-matched cases were only identifiable via shared locations, healthcare locations in particular, rather than named contacts. This suggests most transmission is occurring between casual contacts, and emphasizes the need for improved infection control in healthcare settings in rural Africa. PMID:29438413

Cross-border Portfolio Investment Networks and Indicators for Financial Crises

PubMed Central

Joseph, Andreas C.; Joseph, Stephan E.; Chen, Guanrong

2014-01-01

Cross-border equity and long-term debt securities portfolio investment networks are analysed from 2002 to 2012, covering the 2008 global financial crisis. They serve as network-proxies for measuring the robustness of the global financial system and the interdependence of financial markets, respectively. Two early-warning indicators for financial crises are identified: First, the algebraic connectivity of the equity securities network, as a measure for structural robustness, drops close to zero already in 2005, while there is an over-representation of high-degree off-shore financial centres among the countries most-related to this observation, suggesting an investigation of such nodes with respect to the structural stability of the global financial system. Second, using a phenomenological model, the edge density of the debt securities network is found to describe, and even forecast, the proliferation of several over-the-counter-traded financial derivatives, most prominently credit default swaps, enabling one to detect potentially dangerous levels of market interdependence and systemic risk. PMID:24510060

Cross-border Portfolio Investment Networks and Indicators for Financial Crises

NASA Astrophysics Data System (ADS)

Joseph, Andreas C.; Joseph, Stephan E.; Chen, Guanrong

2014-02-01

Cross-border equity and long-term debt securities portfolio investment networks are analysed from 2002 to 2012, covering the 2008 global financial crisis. They serve as network-proxies for measuring the robustness of the global financial system and the interdependence of financial markets, respectively. Two early-warning indicators for financial crises are identified: First, the algebraic connectivity of the equity securities network, as a measure for structural robustness, drops close to zero already in 2005, while there is an over-representation of high-degree off-shore financial centres among the countries most-related to this observation, suggesting an investigation of such nodes with respect to the structural stability of the global financial system. Second, using a phenomenological model, the edge density of the debt securities network is found to describe, and even forecast, the proliferation of several over-the-counter-traded financial derivatives, most prominently credit default swaps, enabling one to detect potentially dangerous levels of market interdependence and systemic risk.

Cross-border portfolio investment networks and indicators for financial crises.

PubMed

Joseph, Andreas C; Joseph, Stephan E; Chen, Guanrong

2014-02-10

Cross-border equity and long-term debt securities portfolio investment networks are analysed from 2002 to 2012, covering the 2008 global financial crisis. They serve as network-proxies for measuring the robustness of the global financial system and the interdependence of financial markets, respectively. Two early-warning indicators for financial crises are identified: First, the algebraic connectivity of the equity securities network, as a measure for structural robustness, drops close to zero already in 2005, while there is an over-representation of high-degree off-shore financial centres among the countries most-related to this observation, suggesting an investigation of such nodes with respect to the structural stability of the global financial system. Second, using a phenomenological model, the edge density of the debt securities network is found to describe, and even forecast, the proliferation of several over-the-counter-traded financial derivatives, most prominently credit default swaps, enabling one to detect potentially dangerous levels of market interdependence and systemic risk.

The social network-network: size is predicted by brain structure and function in the amygdala and paralimbic regions

PubMed Central

Von Der Heide, Rebecca; Vyas, Govinda

2014-01-01

The social brain hypothesis proposes that the large size of the primate neocortex evolved to support complex and demanding social interactions. Accordingly, recent studies have reported correlations between the size of an individual’s social network and the density of gray matter (GM) in regions of the brain implicated in social cognition. However, the reported relationships between GM density and social group size are somewhat inconsistent with studies reporting correlations in different brain regions. One factor that might account for these discrepancies is the use of different measures of social network size (SNS). This study used several measures of SNS to assess the relationships SNS and GM density. The second goal of this study was to test the relationship between social network measures and functional brain activity. Participants performed a social closeness task using photos of their friends and unknown people. Across the VBM and functional magnetic resonance imaging analyses, individual differences in SNS were consistently related to structural and functional differences in three regions: the left amygdala, right amygdala and the right entorhinal/ventral anterior temporal cortex. PMID:24493846

Social Network Analysis Identifies Key Participants in Conservation Development.

PubMed

Farr, Cooper M; Reed, Sarah E; Pejchar, Liba

2018-05-01

Understanding patterns of participation in private lands conservation, which is often implemented voluntarily by individual citizens and private organizations, could improve its effectiveness at combating biodiversity loss. We used social network analysis (SNA) to examine participation in conservation development (CD), a private land conservation strategy that clusters houses in a small portion of a property while preserving the remaining land as protected open space. Using data from public records for six counties in Colorado, USA, we compared CD participation patterns among counties and identified actors that most often work with others to implement CDs. We found that social network characteristics differed among counties. The network density, or proportion of connections in the network, varied from fewer than 2 to nearly 15%, and was higher in counties with smaller populations and fewer CDs. Centralization, or the degree to which connections are held disproportionately by a few key actors, was not correlated strongly with any county characteristics. Network characteristics were not correlated with the prevalence of wildlife-friendly design features in CDs. The most highly connected actors were biological and geological consultants, surveyors, and engineers. Our work demonstrates a new application of SNA to land-use planning, in which CD network patterns are examined and key actors are identified. For better conservation outcomes of CD, we recommend using network patterns to guide strategies for outreach and information dissemination, and engaging with highly connected actor types to encourage widespread adoption of best practices for CD design and stewardship.

Ethernet access network based on free-space optic deployment technology

NASA Astrophysics Data System (ADS)

Gebhart, Michael; Leitgeb, Erich; Birnbacher, Ulla; Schrotter, Peter

2004-06-01

The satisfaction of all communication needs from single households and business companies over a single access infrastructure is probably the most challenging topic in communications technology today. But even though the so-called "Last Mile Access Bottleneck" is well known since more than ten years and many distribution technologies have been tried out, the optimal solution has not yet been found and paying commercial access networks offering all service classes are still rare today. Conventional services like telephone, radio and TV, as well as new and emerging services like email, web browsing, online-gaming, video conferences, business data transfer or external data storage can all be transmitted over the well known and cost effective Ethernet networking protocol standard. Key requirements for the deployment technology driven by the different services are high data rates to the single customer, security, moderate deployment costs and good scalability to number and density of users, quick and flexible deployment without legal impediments and high availability, referring to the properties of optical and wireless communication. We demonstrate all elements of an Ethernet Access Network based on Free Space Optic distribution technology. Main physical parts are Central Office, Distribution Network and Customer Equipment. Transmission of different services, as well as configuration, service upgrades and remote control of the network are handled by networking features over one FSO connection. All parts of the network are proven, the latest commercially available technology. The set up is flexible and can be adapted to any more specific need if required.

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.

Construction of single-crystalline supramolecular networks of perchlorinated hexa-peri-hexabenzocoronene on Au(111)

NASA Astrophysics Data System (ADS)

Zhang, Yi; Zhang, Yanfang; Li, Geng; Lu, Jianchen; Lin, Xiao; Tan, Yuanzhi; Feng, Xinliang; Du, Shixuan; Müllen, Klaus; Gao, Hong-Jun

2015-03-01

The self-assembly of the perchlorinated hexa-peri-hexabenzocoronene (PCHBC) molecules on Au(111) has been studied by a low temperature scanning tunneling microscopy (STM) combining with density functional theory based first principle calculations. Highly ordered supramolecular networks with single domains limited by the terraces are formed on Au(111) substrate. High resolution images of the PCHBC molecules, confirmed by first principle simulations, are obtained. It reveals the close-packed arrangement of the PCHBC molecules on Au(111). The calculated charge distribution of PCHBC molecules shows the existence of attractive halogen-halogen interaction between neighboring molecules. Compared with the disordered adsorption of hexa-peri-hexabenzocoronene on Au(111), we conclude that the formation of attractive ClCl interactions between neighbors is the key factor to form the highly ordered, close-packed networks. Due to the steric hindrance resulted from the peripheral chlorine atoms, the PCHBC molecule is contorted and forms the doubly concave conformation, which is different from the hexa-peri-hexabenzocoronene with a planar structure. By using this supramolecular network as a template, we deposited C60 molecules on it at room temperature with low coverage. The STM images taken at low temperature show that the C60 molecules are mono-dispersed on the networks and adsorb on top of the PCHBC molecules, forming a typical concave-convex host-guest system.

Emergence of chirality in hexagonally packed monolayers of hexapentyloxytriphenylene on Au(111): a joint experimental and theoretical study.

PubMed

Sleczkowski, Piotr; Katsonis, Nathalie; Kapitanchuk, Oleksiy; Marchenko, Alexandr; Mathevet, Fabrice; Croset, Bernard; Lacaze, Emmanuelle

2014-11-11

We investigate the expression of chirality in a monolayer formed spontaneously by 2,3,6,7,10,11-pentyloxytriphenylene (H5T) on Au(111). We resolve its interface morphology by combining scanning tunneling microscopy (STM) with theoretical calculations of intermolecular and interfacial interaction potentials. We observe two commensurate structures. While both of them belong to a hexagonal space group, analogical to the triangular symmetry of the molecule and the hexagonal symmetry of the substrate surface, they surprisingly reveal a 2D chiral character. The corresponding breaking of symmetry arises for two reasons. First it is due to the establishment of a large molecular density on the substrate, which leads to a rotation of the molecules with respect to the molecular network crystallographic axes to avoid steric repulsion between neighboring alkoxy chains. Second it is due to the molecule-substrate interactions, leading to commensurable large crystallographic cells associated with the large size of the molecule. As a consequence, molecular networks disoriented with respect to the high symmetry directions of the substrate are induced. The high simplicity of the intermolecular and molecule-substrate van der Waals interactions leading to these observations suggests a generic character for this kind of symmetry breaking. We demonstrate that, for similar molecular densities, only two kinds of molecular networks are stabilized by the molecule-substrate interactions. The most stable network favors the interfacial interactions between terminal alkoxy tails and Au(111). The metastable one favors a specific orientation of the triphenylene core with its symmetry axes collinear to the Au⟨110⟩. This specific orientation of the triphenylene cores with respect to Au(111) appears associated with an energy advantage larger by at least 0.26 eV with respect to the disoriented core.

Spatial variation and sources of polycyclic aromatic hydrocarbons influenced by intensive land use in an urbanized river network of East China.

PubMed

Bi, Chunjuan; Wang, Xueping; Jia, Jinpu; Chen, Zhenlou

2018-06-15

The concentrations and distribution of polycyclic aromatic hydrocarbons (PAHs) in urbanized river networks are strongly influenced by intensive land use, industrial activities and population density. The spatial variations and their influencing factors of 16 priority PAHs were investigated in surface water, suspended particulate matter (SPM) and sediments among areas under different intensive land uses (industrial areas, agricultural areas, inner city, suburban towns and island areas) in the Shanghai river network, East China. Source apportionment was carried out using isomer ratios of PAHs and Positive Matrix Factorization (PMF). Total concentrations of 16 PAHs ranged from 105.2 to 400.5 ng/L, 108.1 to 1058.8 ng/L and 104.4 to 19,480.0 ng/g in water, SPM and sediments, respectively. The concentrations of PAHs in SPM and sediments varied significantly among areas (p < 0.05), with the highest concentrations in inner city characterized by highly intensive land use and high population density. The PAH concentrations in sediments were positively correlated with those in SPM and were more strongly correlated with black carbon than with total organic carbon, indicating a stronger influence of prolonged anthropogenic contamination than the recent surface input in sediments. Biomass and coal combustion contributed strongly to total PAHs, followed by natural gas combustion in water and SPM, and vehicular emissions in sediments. Vehicular emissions were the strongest contributors in SPM and sediments of the inner city, indicating the strong influence of vehicular transportation to PAHs pollution in the urbanized river network. Copyright © 2018 Elsevier B.V. All rights reserved.

Solution-Processable High-Purity Semiconducting SWCNTs for Large-Area Fabrication of High-Performance Thin-Film Transistors.

PubMed

Gu, Jianting; Han, Jie; Liu, Dan; Yu, Xiaoqin; Kang, Lixing; Qiu, Song; Jin, Hehua; Li, Hongbo; Li, Qingwen; Zhang, Jin

2016-09-01

For the large-area fabrication of thin-film transistors (TFTs), a new conjugated polymer poly[9-(1-octylonoyl)-9H-carbazole-2,7-diyl] is developed to harvest ultrahigh-purity semiconducting single-walled carbon nanotubes. Combined with spectral and nanodevice characterization, the purity is estimated up to 99.9%. High density and uniform network formed by dip-coating process is liable to fabricate high-performance TFTs on a wafer-scale and the as-fabricated TFTs exhibit a high degree of uniformity. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Extraction of Martian valley networks from digital topography

NASA Technical Reports Server (NTRS)

Stepinski, T. F.; Collier, M. L.

2004-01-01

We have developed a novel method for delineating valley networks on Mars. The valleys are inferred from digital topography by an autonomous computer algorithm as drainage networks, instead of being manually mapped from images. Individual drainage basins are precisely defined and reconstructed to restore flow continuity disrupted by craters. Drainage networks are extracted from their underlying basins using the contributing area threshold method. We demonstrate that such drainage networks coincide with mapped valley networks verifying that valley networks are indeed drainage systems. Our procedure is capable of delineating and analyzing valley networks with unparalleled speed and consistency. We have applied this method to 28 Noachian locations on Mars exhibiting prominent valley networks. All extracted networks have a planar morphology similar to that of terrestrial river networks. They are characterized by a drainage density of approx.0.1/km, low in comparison to the drainage density of terrestrial river networks. Slopes of "streams" in Martian valley networks decrease downstream at a slower rate than slopes of streams in terrestrial river networks. This analysis, based on a sizable data set of valley networks, reveals that although valley networks have some features pointing to their origin by precipitation-fed runoff erosion, their quantitative characteristics suggest that precipitation intensity and/or longevity of past pluvial climate were inadequate to develop mature drainage basins on Mars.

Modeling cytoskeletal traffic: an interplay between passive diffusion and active transport.

PubMed

Neri, Izaak; Kern, Norbert; Parmeggiani, Andrea

2013-03-01

We introduce the totally asymmetric simple exclusion process with Langmuir kinetics on a network as a microscopic model for active motor protein transport on the cytoskeleton, immersed in the diffusive cytoplasm. We discuss how the interplay between active transport along a network and infinite diffusion in a bulk reservoir leads to a heterogeneous matter distribution on various scales: we find three regimes for steady state transport, corresponding to the scale of the network, of individual segments, or local to sites. At low exchange rates strong density heterogeneities develop between different segments in the network. In this regime one has to consider the topological complexity of the whole network to describe transport. In contrast, at moderate exchange rates the transport through the network decouples, and the physics is determined by single segments and the local topology. At last, for very high exchange rates the homogeneous Langmuir process dominates the stationary state. We introduce effective rate diagrams for the network to identify these different regimes. Based on this method we develop an intuitive but generic picture of how the stationary state of excluded volume processes on complex networks can be understood in terms of the single-segment phase diagram.

Using Network Science Measures to Predict the Lexical Decision Performance of Adults Who Stutter.

PubMed

Castro, Nichol; Pelczarski, Kristin M; Vitevitch, Michael S

2017-07-12

Methods from network science have examined various aspects of language processing. Clinical populations may also benefit from these novel analyses. Phonological and lexical factors have been examined in adults who stutter (AWS) as potential contributing factors to stuttering, although differences reported are often subtle. We reexamined the performance of AWS and adults who do not stutter (AWNS) from a previously conducted lexical decision task in an attempt to determine if network science measures would provide additional insight into the phonological network of AWS beyond traditional psycholinguistic measures. Multiple regression was used to examine the influence of several traditional psycholinguistic measures as well as several new measures from network science on response times. AWS responded to low-frequency words more slowly than AWNS; responses for both groups were equivalent for high-frequency words. AWS responded to shorter words more slowly than AWNS, producing a reverse word-length effect. For the network measures, degree/neighborhood density and closeness centrality, but not whether a word was inside or outside the giant component, influenced response times similarly between groups. Network analyses suggest that multiple levels of the phonological network might influence phonological processing, not just the micro-level traditionally considered by mainstream psycholinguistics.

Advancing reversible shape memory by tuning the polymer network architecture

DOE PAGES

Li, Qiaoxi; Zhou, Jing; Vatankhah-Varnoosfaderani, Mohammad; ...

2016-02-02

Because of counteraction of a chemical network and a crystalline scaffold, semicrystalline polymer networks exhibit a peculiar behavior—reversible shape memory (RSM), which occurs naturally without applying any external force and particular structural design. There are three RSM properties: (i) range of reversible strain, (ii) rate of strain recovery, and (iii) decay of reversibility with time, which can be improved by tuning the architecture of the polymer network. Different types of poly(octylene adipate) networks were synthesized, allowing for control of cross-link density and network topology, including randomly cross-linked network by free-radical polymerization, thiol–ene clicked network with enhanced mesh uniformity, and loosemore » network with deliberately incorporated dangling chains. It is shown that the RSM properties are controlled by average cross-link density and crystal size, whereas topology of a network greatly affects its extensibility. In conclusion, we have achieved 80% maximum reversible range, 15% minimal decrease in reversibility, and fast strain recovery rate up to 0.05 K –1, i.e., ca. 5% per 10 s at a cooling rate of 5 K/min.« less

Opposite Latitudinal Dependence of the Premidnight and Postmidnight Oscillations in the Electron Density of Midlatitude F Layer

NASA Astrophysics Data System (ADS)

Chen, Gang; Wang, Jin; Zhang, Shaodong; Deng, Zhongxin; Zhong, Dingkun; Wu, Chen; Jin, Han; Li, Yaxian

2018-01-01

The dense observation points of the oblique-incidence ionosonde network in North China make it possible to discover the ionospheric regional variations with relatively high spatial resolution. The ionosonde network and the Beijing digisonde are used to investigate the ionospheric nighttime oscillations in January and February 2011. The electron density enhancements occurring before and after midnight present the obvious opposite latitudinal dependence in the time-latitude maps, which are composed by the differential critical frequency of F2 layer. The premidnight enhancements (PRMEs) appeared earlier in the north and then moved to south. The postmidnight enhancements (POMEs) did the opposite. The data analysis shows that the PRME was a part of the large-scale traveling ionospheric disturbance (LSTID), which may be produced by gravity waves. The southward propagation of the LSTIDs is considered to form the positive latitudinal dependence of the wave peaks and troughs. The postmidnight F layer oscillation was composed by a single enhancement and a single decline following it. The westward electric field-induced E × B drift, which pushed the F layer to lower altitudes with higher recombination loss, was most likely to compress the plasma and produce the POMEs. Along with the continuously dropping of the layer, the recombination loss exceeded the density increase due to the compression effect and then the electron density decline appeared.

The mechanical properties and cytotoxicity of cell-laden double-network hydrogels based on photocrosslinkable gelatin and gellan gum biomacromolecules.

PubMed

Shin, Hyeongho; Olsen, Bradley D; Khademhosseini, Ali

2012-04-01

A major goal in the application of hydrogels for tissue engineering scaffolds, especially for load-bearing tissues such as cartilage, is to develop hydrogels with high mechanical strength. In this study, a double-network (DN) strategy was used to engineer strong hydrogels that can encapsulate cells. We improved upon previously studied double-network (DN) hydrogels by using a processing condition compatible with cell survival. The DN hydrogels were created by a two-step photocrosslinking using gellan gum methacrylate (GGMA) for the rigid and brittle first network, and gelatin methacrylamide (GelMA) for the soft and ductile second network. We controlled the degree of methacrylation of each polymer so that they obtain relevant mechanical properties as each network. The DN was formed by photocrosslinking the GGMA, diffusing GelMA into the first network, and photocrosslinking the GelMA to form the second network. The formation of the DN was examined by diffusion tests of the large GelMA molecules into the GGMA network, the resulting enhancement in the mechanical properties, and the difference in mechanical properties between GGMA/GelMA single networks (SN) and DNs. The resulting DN hydrogels exhibited the compressive failure stress of up to 6.9 MPa, which approaches the strength of cartilage. It was found that there is an optimal range of the crosslink density of the second network for high strength of DN hydrogels. DN hydrogels with a higher mass ratio of GelMA to GGMA exhibited higher strength, which shows promise in developing even stronger DN hydrogels in the future. Three dimensional (3D) encapsulation of NIH-3T3 fibroblasts and the following viability test showed the cell-compatibility of the DN formation process. Given the high strength and the ability to encapsulate cells, the DN hydrogels made from photocrosslinkable macromolecules could be useful for the regeneration of load-bearing tissues. Copyright © 2012 Elsevier Ltd. All rights reserved.

The mechanical properties and cytotoxicity of cell-laden double-network hydrogels based on photocrosslinkable gelatin and gellan gum biomacromolecules

PubMed Central

Shin, Hyeongho; Olsen, Bradley D.; Khademhosseini, Ali

2012-01-01

A major goal in the application of hydrogels for tissue engineering scaffolds, especially for load-bearing tissues such as cartilage, is to develop hydrogels with high mechanical strength. In this study, a double-network (DN) strategy was used to engineer strong hydrogels that can encapsulate cells. We improved upon previously studied double-network (DN) hydrogels by using a processing condition compatible with cell survival. The DN hydrogels were created by a two-step photocrosslinking using gellan gum methacrylate (GGMA) for the rigid and brittle first network, and gelatin methacrylamide (GelMA) for the soft and ductile second network. We controlled the degree of methacrylation of each polymer so that they obtain relevant mechanical properties as each network. The DN was formed by photocrosslinking the GGMA, diffusing GelMA into the first network, and photocrosslinking the GelMA to form the second network. The formation of the DN was examined by diffusion tests of the large GelMA molecules into the GGMA network, the resulting enhancement in the mechanical properties, and the difference in mechanical properties between GGMA/GelMA single networks (SN) and DNs. The resulting DN hydrogels exhibited the compressive failure stress of up to 6.9 MPa, which approaches the strength of cartilage. It was found that there is an optimal range of the crosslink density of the second network for high strength of DN hydrogels. DN hydrogels with a higher mass ratio of GelMA to GGMA exhibited higher strength, which shows promise in developing even stronger DN hydrogels in the future. Three dimensional (3D) encapsulation of NIH-3T3 fibroblasts and the following viability test showed the cell-compatibility of the DN formation process. Given the high strength and the ability to encapsulate cells, the DN hydrogels made from photocrosslinkable macromolecules could be useful for the regeneration of load-bearing tissues. PMID:22265786

An efficient coordination protocol for wireless sensor networks

NASA Astrophysics Data System (ADS)

Paruchuri, Vamsi; Durresi, Arjan; Durresi, Mimoza; Barolli, Leonard

2005-10-01

Backbones infrastructures in wireless sensor networks reduce the communication overhead and energy consumption. In this paper, we present BackBone Routing (BBR), a fully distributed protocol for construction and rotation of backbone networks. BBR reduces energy consumption without significantly diminishing the capacity or connectivity of the network. Another key feature of BBR is its energy balancing nature by distributing the role of being Backbone Node among all the nodes. BBR builds on the observation that when a region of a shared-channel wireless network has a sufficient density of nodes, only a small number of them need be on at any time to forward traffic for active connections. Improvement in system lifetime due to BBR increases as the ratio of idle-to-sleep energy consumption increases, and increases as the density of the network increases. Our experiments show that BBR is more efficient in saving energy and extending network life without deteriorating network performance when compared with geographical shortest path routing.

Interconnected 3 D Network of Graphene-Oxide Nanosheets Decorated with Carbon Dots for High-Performance Supercapacitors.

PubMed

Zhao, Xiao; Li, Ming; Dong, Hanwu; Liu, Yingliang; Hu, Hang; Cai, Yijin; Liang, Yeru; Xiao, Yong; Zheng, Mingtao

2017-06-22

Interconnected 3 D nanosheet networks of reduced graphene oxide decorated with carbon dots (rGO/CDs) are successfully fabricated through a simple one-pot hydrothermal process. The as-prepared rGO/CDs present appropriate 3 D interconnectivity and abundant stable oxygen-containing functional groups, to which we can attribute the excellent electrochemical performance such as high specific capacitance, good rate capability, and great cycling stability. Employed as binder-free electrodes for supercapacitors, the resulting rGO/CDs exhibit excellent long-term cycling stability (ca. 92 % capacitance retention after 20 000 charge/discharge cycles at current density of 10 A g -1 ) as well as a maximum specific capacitance of about 308 F g -1 at current density of 0.5 A g -1 , which is much higher than that of rGO (200 F g -1 ) and CDs (2.2 F g -1 ). This work provides a promising strategy to fabricate graphene-based nanomaterials with greatly boosted electrochemical performances by decoration of with CDs. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Statistical mechanics of high-density bond percolation

NASA Astrophysics Data System (ADS)

Timonin, P. N.

2018-05-01

High-density (HD) percolation describes the percolation of specific κ -clusters, which are the compact sets of sites each connected to κ nearest filled sites at least. It takes place in the classical patterns of independently distributed sites or bonds in which the ordinary percolation transition also exists. Hence, the study of series of κ -type HD percolations amounts to the description of classical clusters' structure for which κ -clusters constitute κ -cores nested one into another. Such data are needed for description of a number of physical, biological, and information properties of complex systems on random lattices, graphs, and networks. They range from magnetic properties of semiconductor alloys to anomalies in supercooled water and clustering in biological and social networks. Here we present the statistical mechanics approach to study HD bond percolation on an arbitrary graph. It is shown that the generating function for κ -clusters' size distribution can be obtained from the partition function of the specific q -state Potts-Ising model in the q →1 limit. Using this approach we find exact κ -clusters' size distributions for the Bethe lattice and Erdos-Renyi graph. The application of the method to Euclidean lattices is also discussed.

Three-dimensional imaging for precise structural control of Si quantum dot networks for all-Si solar cells.

PubMed

Kourkoutis, Lena F; Hao, Xiaojing; Huang, Shujuan; Puthen-Veettil, Binesh; Conibeer, Gavin; Green, Martin A; Perez-Wurfl, Ivan

2013-08-21

All-Si tandem solar cells based on Si quantum dots (QDs) are a promising approach to future high-performance, thin film solar cells using abundant, stable and non-toxic materials. An important prerequisite to achieve a high conversion efficiency in such cells is the ability to control the geometry of the Si QD network. This includes the ability to control both, the size and arrangement of Si QDs embedded in a higher bandgap matrix. Using plasmon tomography we show the size, shape and density of Si QDs, that form in Si rich oxide (SRO)/SiO2 multilayers upon annealing, can be controlled by varying the SRO stoichiometry. Smaller, more spherical QDs of higher densities are obtained at lower Si concentrations. In richer SRO layers ellipsoidal QDs tend to form. Using electronic structure calculations within the effective mass approximation we show that ellipsoidal QDs give rise to reduced inter-QD coupling in the layer. Efficient carrier transport via mini-bands is in this case more likely across the multilayers provided the SiO2 spacer layer is thin enough to allow coupling in the vertical direction.

Kinetically Controlled Two-Step Amorphization and Amorphous-Amorphous Transition in Ice.

PubMed

Lin, Chuanlong; Yong, Xue; Tse, John S; Smith, Jesse S; Sinogeikin, Stanislav V; Kenney-Benson, Curtis; Shen, Guoyin

2017-09-29

We report the results of in situ structural characterization of the amorphization of crystalline ice Ih under compression and the relaxation of high-density amorphous (HDA) ice under decompression at temperatures between 96 and 160 K by synchrotron x-ray diffraction. The results show that ice Ih transforms to an intermediate crystalline phase at 100 K prior to complete amorphization, which is supported by molecular dynamics calculations. The phase transition pathways show clear temperature dependence: direct amorphization without an intermediate phase is observed at 133 K, while at 145 K a direct Ih-to-IX transformation is observed; decompression of HDA shows a transition to low-density amorphous ice at 96 K and ∼1  Pa, to ice Ic at 135 K and to ice IX at 145 K. These observations show that the amorphization of compressed ice Ih and the recrystallization of decompressed HDA are strongly dependent on temperature and controlled by kinetic barriers. Pressure-induced amorphous ice is an intermediate state in the phase transition from the connected H-bond water network in low pressure ices to the independent and interpenetrating H-bond network of high-pressure ices.

Degradation by water vapor of hydrogenated amorphous silicon oxynitride films grown at low temperature.

PubMed

Lee, Hyung-Ik; Park, Jong-Bong; Xianyu, Wenxu; Kim, Kihong; Chung, Jae Gwan; Kyoung, Yong Koo; Byun, Sunjung; Yang, Woo Young; Park, Yong Young; Kim, Seong Min; Cho, Eunae; Shin, Jai Kwang

2017-10-26

We report on the degradation process by water vapor of hydrogenated amorphous silicon oxynitride (SiON:H) films deposited by plasma-enhanced chemical vapor deposition at low temperature. The stability of the films was investigated as a function of the oxygen content and deposition temperature. Degradation by defects such as pinholes was not observed with transmission electron microscopy. However, we observed that SiON:H film degrades by reacting with water vapor through only interstitial paths and nano-defects. To monitor the degradation process, the atomic composition, mass density, and fully oxidized thickness were measured by using high-resolution Rutherford backscattering spectroscopy and X-ray reflectometry. The film rapidly degraded above an oxygen composition of ~27 at%, below a deposition temperature of ~150 °C, and below an mass density of ~2.15 g/cm 3 . This trend can be explained by the extents of porosity and percolation channel based on the ring model of the network structure. In the case of a high oxygen composition or low temperature, the SiON:H film becomes more porous because the film consists of network channels of rings with a low energy barrier.

Performance Improvement in Geographic Routing for Vehicular Ad Hoc Networks

PubMed Central

Kaiwartya, Omprakash; Kumar, Sushil; Lobiyal, D. K.; Abdullah, Abdul Hanan; Hassan, Ahmed Nazar

2014-01-01

Geographic routing is one of the most investigated themes by researchers for reliable and efficient dissemination of information in Vehicular Ad Hoc Networks (VANETs). Recently, different Geographic Distance Routing (GEDIR) protocols have been suggested in the literature. These protocols focus on reducing the forwarding region towards destination to select the Next Hop Vehicles (NHV). Most of these protocols suffer from the problem of elevated one-hop link disconnection, high end-to-end delay and low throughput even at normal vehicle speed in high vehicle density environment. This paper proposes a Geographic Distance Routing protocol based on Segment vehicle, Link quality and Degree of connectivity (SLD-GEDIR). The protocol selects a reliable NHV using the criteria segment vehicles, one-hop link quality and degree of connectivity. The proposed protocol has been simulated in NS-2 and its performance has been compared with the state-of-the-art protocols: P-GEDIR, J-GEDIR and V-GEDIR. The empirical results clearly reveal that SLD-GEDIR has lower link disconnection and end-to-end delay, and higher throughput as compared to the state-of-the-art protocols. It should be noted that the performance of the proposed protocol is preserved irrespective of vehicle density and speed. PMID:25429415

Performance improvement in geographic routing for Vehicular Ad Hoc Networks.

PubMed

Kaiwartya, Omprakash; Kumar, Sushil; Lobiyal, D K; Abdullah, Abdul Hanan; Hassan, Ahmed Nazar

2014-11-25

Geographic routing is one of the most investigated themes by researchers for reliable and efficient dissemination of information in Vehicular Ad Hoc Networks (VANETs). Recently, different Geographic Distance Routing (GEDIR) protocols have been suggested in the literature. These protocols focus on reducing the forwarding region towards destination to select the Next Hop Vehicles (NHV). Most of these protocols suffer from the problem of elevated one-hop link disconnection, high end-to-end delay and low throughput even at normal vehicle speed in high vehicle density environment. This paper proposes a Geographic Distance Routing protocol based on Segment vehicle, Link quality and Degree of connectivity (SLD-GEDIR). The protocol selects a reliable NHV using the criteria segment vehicles, one-hop link quality and degree of connectivity. The proposed protocol has been simulated in NS-2 and its performance has been compared with the state-of-the-art protocols: P-GEDIR, J-GEDIR and V-GEDIR. The empirical results clearly reveal that SLD-GEDIR has lower link disconnection and end-to-end delay, and higher throughput as compared to the state-of-the-art protocols. It should be noted that the performance of the proposed protocol is preserved irrespective of vehicle density and speed.

Kinetically Controlled Two-Step Amorphization and Amorphous-Amorphous Transition in Ice

NASA Astrophysics Data System (ADS)

Lin, Chuanlong; Yong, Xue; Tse, John S.; Smith, Jesse S.; Sinogeikin, Stanislav V.; Kenney-Benson, Curtis; Shen, Guoyin

2017-09-01

We report the results of in situ structural characterization of the amorphization of crystalline ice Ih under compression and the relaxation of high-density amorphous (HDA) ice under decompression at temperatures between 96 and 160 K by synchrotron x-ray diffraction. The results show that ice Ih transforms to an intermediate crystalline phase at 100 K prior to complete amorphization, which is supported by molecular dynamics calculations. The phase transition pathways show clear temperature dependence: direct amorphization without an intermediate phase is observed at 133 K, while at 145 K a direct Ih-to-IX transformation is observed; decompression of HDA shows a transition to low-density amorphous ice at 96 K and ˜1 Pa , to ice Ic at 135 K and to ice IX at 145 K. These observations show that the amorphization of compressed ice Ih and the recrystallization of decompressed HDA are strongly dependent on temperature and controlled by kinetic barriers. Pressure-induced amorphous ice is an intermediate state in the phase transition from the connected H-bond water network in low pressure ices to the independent and interpenetrating H-bond network of high-pressure ices.

Kinetically Controlled Two-Step Amorphization and Amorphous-Amorphous Transition in Ice

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

Lin, Chuanlong; Yong, Xue; Tse, John S.

We report the results of in situ structural characterization of the amorphization of crystalline ice Ih under compression and the relaxation of high-density amorphous (HDA) ice under decompression at temperatures between 96 and 160 K by synchrotron x-ray diffraction. The results show that ice Ih transforms to an intermediate crystalline phase at 100 K prior to complete amorphization, which is supported by molecular dynamics calculations. The phase transition pathways show clear temperature dependence: direct amorphization without an intermediate phase is observed at 133 K, while at 145 K a direct Ih-to-IX transformation is observed; decompression of HDA shows a transitionmore » to low-density amorphous ice at 96 K and ~ 1 Pa , to ice Ic at 135 K and to ice IX at 145 K. These observations show that the amorphization of compressed ice Ih and the recrystallization of decompressed HDA are strongly dependent on temperature and controlled by kinetic barriers. Pressure-induced amorphous ice is an intermediate state in the phase transition from the connected H-bond water network in low pressure ices to the independent and interpenetrating H-bond network of high-pressure ices.« less

Measuring interdependence in ambulatory care.

PubMed

Katerndahl, David; Wood, Robert; Jaen, Carlos R

2017-04-01

Complex systems differ from complicated systems in that they are nonlinear, unpredictable and lacking clear cause-and-effect relationships, largely due to the interdependence of their components (effects of interconnectedness on system behaviour and consequences). The purpose of this study was to demonstrate the potential for network density to serve as a measure of interdependence, assess its concurrent validity and test whether the use of valued or binary ties yields better results. This secondary analysis used the 2010 National Ambulatory Care Medical Survey to assess interdependence of 'top 20' diagnoses seen and medications prescribed for 14 specialties. The degree of interdependence was measured as the level of association between diagnoses and drug interactions among medications. Both valued and binary network densities were computed for each specialty. To assess concurrent validity, these measures were correlated with previously-derived valid measures of complexity of care using the same database, adjusting for diagnosis and medication diversity. Partial correlations between diagnosis density, and both diagnosis and total input complexity, were significant, as were those between medication density and both medication and total output complexity; for both diagnosis and medication densities, adjusted correlations were higher for binary rather than valued densities. This study demonstrated the feasibility and validity of using network density as a measure of interdependence. When adjusted for measure diversity, density-complexity correlations were significant and higher for binary than valued density. This approach complements other methods of estimating complexity of care and may be applicable to unique settings. © 2015 John Wiley & Sons, Ltd.

Terabit optical OFDM superchannel transmission via coherent carriers of a hybrid chip-scale soliton frequency comb

NASA Astrophysics Data System (ADS)

Geng, Yong; Huang, Xiatao; Cui, Wenwen; Ling, Yun; Xu, Bo; Zhang, Jin; Yi, Xingwen; Wu, Baojian; Huang, Shu-Wei; Qiu, Kun; Wong, Chee Wei; Zhou, Heng

2018-05-01

We demonstrate seamless channel multiplexing and high bitrate superchannel transmission of coherent optical orthogonal-frequency-division-multiplexing (CO-OFDM) data signals utilizing a dissipative Kerr soliton (DKS) frequency comb generated in an on-chip microcavity. Aided by comb line multiplication through Nyquist pulse modulation, the high stability and mutual coherence among mode-locked Kerr comb lines are exploited for the first time to eliminate the guard intervals between communication channels and achieve full spectral density bandwidth utilization. Spectral efficiency as high as 2.625 bit/Hz/s is obtained for 180 CO-OFDM bands encoded with 12.75 Gbaud 8-QAM data, adding up to total bitrate of 6.885 Tb/s within 2.295 THz frequency comb bandwidth. Our study confirms that high coherence is the key superiority of Kerr soliton frequency combs over independent laser diodes, as a multi-spectral coherent laser source for high-bandwidth high-spectral-density transmission networks.

Social network characteristics and cervical cancer screening among Quechua women in Andean Peru.

PubMed

Luque, John S; Opoku, Samuel; Ferris, Daron G; Guevara Condorhuaman, Wendy S

2016-02-24

Peru has high cervical cancer incidence and mortality rates compared to other Andean countries. Therefore, partnerships between governmental and international organizations have targeted rural areas of Peru to receive cervical cancer screening via outreach campaigns. Previous studies have found a relationship between a person's social networks and cancer screening behaviors. Screening outreach campaigns conducted by the nonprofit organization CerviCusco created an opportunity for a social network study to examine cervical cancer screening history and social network characteristics in a rural indigenous community that participated in these campaigns in 2012 and 2013. The aim of this study was to explore social network characteristics in this community related to receipt of cervical cancer screening following the campaigns. An egocentric social network questionnaire was used to collect cross-sectional network data on community participants. Each survey participant (ego) was asked to name six other women they knew (alters) and identify the nature of their relationship or tie (family, friend, neighbor, other), residential closeness (within 5 km), length of time known, frequency of communication, topics of conversation, and whether they lent money to the person, provided childcare or helped with transportation. In addition, each participant was asked to report the nature of the relationship between all alters identified (e.g., friend, family, or neighbor). Bivariate and multivariate analyses were used to explore the relationship between Pap test receipt at the CerviCusco outreach screening campaigns and social network characteristics. Bivariate results found significant differences in percentage of alter composition for neighbors and family, and for mean number of years known, mean density, and mean degree centrality between women who had received a Pap test (n = 19) compared to those who had not (n = 50) (p's < 0.05). The final logistic regression model was statistically significant (χ2 (2) = 20.911, p < .001). The model included the variables for percentage of family alter composition and mean density, and it explained 37.8% (Nagelkerke R(2)) of the variance in Pap test receipt, correctly classifying 78.3% of cases. Those women with higher percentages of family alter composition and higher mean density in their ego networks were less likely to have received a Pap test at the CerviCusco campaigns. According to this exploratory study, female neighbors more than family members may have provided an important source of social support for healthcare related decisions related to receipt of a Pap test. Future studies should collect longitudinal social network data on participants to measure the network effects of screening interventions in rural indigenous communities in Latin American countries experiencing the highest burden of cervical cancer.

Entanglement in a quantum neural network based on quantum dots

NASA Astrophysics Data System (ADS)

Altaisky, M. V.; Zolnikova, N. N.; Kaputkina, N. E.; Krylov, V. A.; Lozovik, Yu E.; Dattani, N. S.

2017-05-01

We studied the quantum correlations between the nodes in a quantum neural network built of an array of quantum dots with dipole-dipole interaction. By means of the quasiadiabatic path integral simulation of the density matrix evolution in a presence of the common phonon bath we have shown the coherence in such system can survive up to the liquid nitrogen temperature of 77 K and above. The quantum correlations between quantum dots are studied by means of calculation of the entanglement of formation in a pair of quantum dots with the typical dot size of a few nanometers and interdot distance of the same order. We have shown that the proposed quantum neural network can keep the mixture of entangled states of QD pairs up to the above mentioned high temperatures.

FPGA implementation of advanced FEC schemes for intelligent aggregation networks

NASA Astrophysics Data System (ADS)

Zou, Ding; Djordjevic, Ivan B.

2016-02-01

In state-of-the-art fiber-optics communication systems the fixed forward error correction (FEC) and constellation size are employed. While it is important to closely approach the Shannon limit by using turbo product codes (TPC) and low-density parity-check (LDPC) codes with soft-decision decoding (SDD) algorithm; rate-adaptive techniques, which enable increased information rates over short links and reliable transmission over long links, are likely to become more important with ever-increasing network traffic demands. In this invited paper, we describe a rate adaptive non-binary LDPC coding technique, and demonstrate its flexibility and good performance exhibiting no error floor at BER down to 10-15 in entire code rate range, by FPGA-based emulation, making it a viable solution in the next-generation high-speed intelligent aggregation networks.

Using Organizational Network Analysis to Plan Cancer Screening Programs for Vulnerable Populations

PubMed Central

Carothers, Bobbi J.; Lofters, Aisha K.

2014-01-01

Objectives. We examined relationships among organizations in a cancer screening network to inform the development of interventions to improve cancer screening for South Asians living in the Peel region of Ontario. Methods. From April to July 2012, we surveyed decision-makers, program managers, and program staff in 22 organizations in the South Asian cancer screening network in the Peel region. We used a network analytic approach to evaluate density (range = 0%–100%, number of ties among organizations in the network expressed as a percentage of all possible ties), centralization (range = 0–1, the extent of variability in centrality), and node characteristics for the communication, collaboration, and referral networks. Results. Density was similar across communication (15%), collaboration (17%), and referral (19%) networks. Centralization was greater in the collaboration network (0.30) than the communication network (0.24), and degree centralization was greater in the inbound (0.42) than the outbound (0.37) referral network. Diverse organizations were central to the networks. Conclusions. Certain organizations were unexpectedly important to the South Asian cancer screening network. Program planning was informed by identifying opportunities to strengthen linkages between key organizations and to leverage existing ties. PMID:24328613

Using organizational network analysis to plan cancer screening programs for vulnerable populations.

PubMed

Lobb, Rebecca; Carothers, Bobbi J; Lofters, Aisha K

2014-02-01

We examined relationships among organizations in a cancer screening network to inform the development of interventions to improve cancer screening for South Asians living in the Peel region of Ontario. From April to July 2012, we surveyed decision-makers, program managers, and program staff in 22 organizations in the South Asian cancer screening network in the Peel region. We used a network analytic approach to evaluate density (range = 0%-100%, number of ties among organizations in the network expressed as a percentage of all possible ties), centralization (range = 0-1, the extent of variability in centrality), and node characteristics for the communication, collaboration, and referral networks. Density was similar across communication (15%), collaboration (17%), and referral (19%) networks. Centralization was greater in the collaboration network (0.30) than the communication network (0.24), and degree centralization was greater in the inbound (0.42) than the outbound (0.37) referral network. Diverse organizations were central to the networks. Certain organizations were unexpectedly important to the South Asian cancer screening network. Program planning was informed by identifying opportunities to strengthen linkages between key organizations and to leverage existing ties.

Higher serum cholesterol is associated with intensified age-related neural network decoupling and cognitive decline in early- to mid-life.

PubMed

Spielberg, Jeffrey M; Sadeh, Naomi; Leritz, Elizabeth C; McGlinchey, Regina E; Milberg, William P; Hayes, Jasmeet P; Salat, David H

2017-06-01

Mounting evidence indicates that serum cholesterol and other risk factors for cardiovascular disease intensify normative trajectories of age-related cognitive decline. However, the neural mechanisms by which this occurs remain largely unknown. To understand the impact of cholesterol on brain networks, we applied graph theory to resting-state fMRI in a large sample of early- to mid-life Veterans (N = 206, Mean age  = 32). A network emerged (centered on the banks of the superior temporal sulcus) that evidenced age-related decoupling (i.e., decreased network connectivity with age), but only in participants with clinically-elevated total cholesterol (≥180 mg/dL). Crucially, decoupling in this network corresponded to greater day-to-day disability and mediated age-related declines in psychomotor speed. Finally, examination of network organization revealed a pattern of age-related dedifferentiation for the banks of the superior temporal sulcus, again present only with higher cholesterol. More specifically, age was related to decreasing within-module communication (indexed by Within-Module Degree Z-Score) and increasing between-module communication (indexed by Participation Coefficient), but only in participants with clinically-elevated cholesterol. Follow-up analyses indicated that all findings were driven by low-density lipoprotein (LDL) levels, rather than high-density lipoprotein (HDL) or triglycerides, which is interesting as LDL levels have been linked to increased risk for cardiovascular disease, whereas HDL levels appear inversely related to such disease. These findings provide novel insight into the deleterious effects of cholesterol on brain health and suggest that cholesterol accelerates the impact of age on neural trajectories by disrupting connectivity in circuits implicated in integrative processes and behavioral control. Hum Brain Mapp 38:3249-3261, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Short-range structure and cation bonding in calcium-aluminum metaphosphate glasses.

PubMed

Schneider, J; Oliveira, S L; Nunes, L A O; Bonk, F; Panepucci, H

2005-01-24

Comprehension of short- and medium-range order of phosphate glasses is a topic of interest, due to the close relation between network structure and mechanical, thermal, and optical properties. In this work, the short-range structure of glasses (1 - x)Ca(PO(3))(2).xAl(PO(3))(3) with 0 < or = x < or = 0.47 was studied using solid-state nuclear magnetic resonance spectroscopy, Raman spectroscopy, density measurements, and differential scanning calorimetry. The bonding between a network modifier species, Al, and the network forming phosphate groups was probed using high-resolution nuclear magnetic resonance spectroscopy of (27)Al and (31)P. Changes in the compositional behavior of the density, glass transition temperature, PO(2) symmetric vibrations, and Al coordination number were verified at around x = 0.30. (31)P NMR spectra show the presence of phosphorus in Q(2) sites with nonbridging oxygens (NBOs) coordinated by Ca ions and also Q(2) sites with one NBO coordinated by Al (namely, Q(2)(1Al)). The changes in the properties as a function of x can be understood by considering the mean coordination number measured for Al and the formation of only Q(2) and Q(2)(1Al) species. It is possible to calculate that a network formed only by Q(2)(1Al) phosphates can just exist up to the upper limit of x = 0.48. Above this value, Q(2)(2Al) species should appear, imposing a major reorganization of the network. Above x = 0.30 the network undergoes a progressive reorganization to incorporate Al ions, maintaining the condition that only Q(2)(1Al) species are formed. These observations support the idea that bonding principles for cationic species inferred originally in binary phosphate glasses can also be extended to ternary systems.

Empirical Modeling of the Plasmasphere Dynamics Using Neural Networks

NASA Astrophysics Data System (ADS)

Zhelavskaya, I. S.; Shprits, Y.; Spasojevic, M.

2017-12-01

We present a new empirical model for reconstructing the global dynamics of the cold plasma density distribution based only on solar wind data and geomagnetic indices. Utilizing the density database obtained using the NURD (Neural-network-based Upper hybrid Resonance Determination) algorithm for the period of October 1, 2012 - July 1, 2016, in conjunction with solar wind data and geomagnetic indices, we develop a neural network model that is capable of globally reconstructing the dynamics of the cold plasma density distribution for 2 ≤ L ≤ 6 and all local times. We validate and test the model by measuring its performance on independent datasets withheld from the training set and by comparing the model predicted global evolution with global images of He+ distribution in the Earth's plasmasphere from the IMAGE Extreme UltraViolet (EUV) instrument. We identify the parameters that best quantify the plasmasphere dynamics by training and comparing multiple neural networks with different combinations of input parameters (geomagnetic indices, solar wind data, and different durations of their time history). We demonstrate results of both local and global plasma density reconstruction. This study illustrates how global dynamics can be reconstructed from local in-situ observations by using machine learning techniques.

A survey on routing protocols for large-scale wireless sensor networks.

PubMed

Li, Changle; Zhang, Hanxiao; Hao, Binbin; Li, Jiandong

2011-01-01

With the advances in micro-electronics, wireless sensor devices have been made much smaller and more integrated, and large-scale wireless sensor networks (WSNs) based the cooperation among the significant amount of nodes have become a hot topic. "Large-scale" means mainly large area or high density of a network. Accordingly the routing protocols must scale well to the network scope extension and node density increases. A sensor node is normally energy-limited and cannot be recharged, and thus its energy consumption has a quite significant effect on the scalability of the protocol. To the best of our knowledge, currently the mainstream methods to solve the energy problem in large-scale WSNs are the hierarchical routing protocols. In a hierarchical routing protocol, all the nodes are divided into several groups with different assignment levels. The nodes within the high level are responsible for data aggregation and management work, and the low level nodes for sensing their surroundings and collecting information. The hierarchical routing protocols are proved to be more energy-efficient than flat ones in which all the nodes play the same role, especially in terms of the data aggregation and the flooding of the control packets. With focus on the hierarchical structure, in this paper we provide an insight into routing protocols designed specifically for large-scale WSNs. According to the different objectives, the protocols are generally classified based on different criteria such as control overhead reduction, energy consumption mitigation and energy balance. In order to gain a comprehensive understanding of each protocol, we highlight their innovative ideas, describe the underlying principles in detail and analyze their advantages and disadvantages. Moreover a comparison of each routing protocol is conducted to demonstrate the differences between the protocols in terms of message complexity, memory requirements, localization, data aggregation, clustering manner and other metrics. Finally some open issues in routing protocol design in large-scale wireless sensor networks and conclusions are proposed.

A Survey on Routing Protocols for Large-Scale Wireless Sensor Networks

PubMed Central

Li, Changle; Zhang, Hanxiao; Hao, Binbin; Li, Jiandong

2011-01-01

With the advances in micro-electronics, wireless sensor devices have been made much smaller and more integrated, and large-scale wireless sensor networks (WSNs) based the cooperation among the significant amount of nodes have become a hot topic. “Large-scale” means mainly large area or high density of a network. Accordingly the routing protocols must scale well to the network scope extension and node density increases. A sensor node is normally energy-limited and cannot be recharged, and thus its energy consumption has a quite significant effect on the scalability of the protocol. To the best of our knowledge, currently the mainstream methods to solve the energy problem in large-scale WSNs are the hierarchical routing protocols. In a hierarchical routing protocol, all the nodes are divided into several groups with different assignment levels. The nodes within the high level are responsible for data aggregation and management work, and the low level nodes for sensing their surroundings and collecting information. The hierarchical routing protocols are proved to be more energy-efficient than flat ones in which all the nodes play the same role, especially in terms of the data aggregation and the flooding of the control packets. With focus on the hierarchical structure, in this paper we provide an insight into routing protocols designed specifically for large-scale WSNs. According to the different objectives, the protocols are generally classified based on different criteria such as control overhead reduction, energy consumption mitigation and energy balance. In order to gain a comprehensive understanding of each protocol, we highlight their innovative ideas, describe the underlying principles in detail and analyze their advantages and disadvantages. Moreover a comparison of each routing protocol is conducted to demonstrate the differences between the protocols in terms of message complexity, memory requirements, localization, data aggregation, clustering manner and other metrics. Finally some open issues in routing protocol design in large-scale wireless sensor networks and conclusions are proposed. PMID:22163808

Putting the Capital 'A' in CoCoRAHS: A Pilot Program to Measure Albedo using the Community Collaborative Rain, Hail, and Snow (CoCoRaHS) Network

NASA Astrophysics Data System (ADS)

Burakowski, E. A.; Stampone, M. D.; Wake, C. P.; Dibb, J. E.

2012-12-01

The Community Collaborative Rain, Hail, and Snow (CoCoRaHS) Network, started in 1998 as a community-based network of volunteer weather observer in Colorado, is the single largest provider of daily precipitation observations in the United States. We embrace the CoCoRaHS mission to use low-cost measurement tools, provide training and education, and utilize an interactive website to collect high quality albedo data for research and education applications. We trained a select sub-set of CoCoRaHS's eighteen most enthusiastic, self-proclaimed 'weather nuts' in the state of New Hampshire to collect surface albedo, snow depth, and snow density measurements between 23-Nov-2011 and 15-Mar-2012. At less than 700 per observer, the low-cost albedo data falls within ±0.05 of albedo values collected from a First Class Kipp and Zonen Albedometer (CMA6) at local solar noon. CoCoRaHS albedo values range from 0.99 for fresh snow to 0.34 for shallow, aged snow. Snow-free albedo ranges from 0.09 to 0.39, depending on ground cover. Albedo is found to increase logarithmically with snow depth and decrease linearly with snow density. The latter relationship with snow density is inferred to be a proxy for increasing snow grain size as snowpack ages and compacts, supported by spectral albedo measurements collected with an ASD FieldSpec4 spectrometer. The newly established albedo network also serves as a development test bed for interactive online mapping and graphing applications for CoCoRaHS observers to investigate spatial and temporal patterns in albedo, snow depth, and snow density (www.cocorahs-albedo.org). The 2012-2013 field season will include low-cost infrared temperature guns (<40 each) to investigate the relationship between surface albedo and skin temperature. We have also recruited middle- and high-schools as volunteer observers and are working with the teachers to develop curriculum and lesson plans that utilize the low-cost measurement tools provided by CoCoRAHS. CoCoRAHS data will provide critical spatially distributed measurements of surface data that will be used to validate and improve land surface modeling of New Hampshire climate under different land cover scenarios. Building on the success of the first season, the newly established albedo network shows promise to put the capital 'A' in CoCoRAHS.Figure 1. (a) Map of Community Collaborative Rain, Hail, and Snow (CoCoRAHS) volunteers participating in the pilot albedo project, and (b) CoCoRAHS snow measurement kit.

Hip fracture in the elderly: a re-analysis of the EPIDOS study with causal Bayesian networks.

PubMed

Caillet, Pascal; Klemm, Sarah; Ducher, Michel; Aussem, Alexandre; Schott, Anne-Marie

2015-01-01

Hip fractures commonly result in permanent disability, institutionalization or death in elderly. Existing hip-fracture predicting tools are underused in clinical practice, partly due to their lack of intuitive interpretation. By use of a graphical layer, Bayesian network models could increase the attractiveness of fracture prediction tools. Our aim was to study the potential contribution of a causal Bayesian network in this clinical setting. A logistic regression was performed as a standard control approach to check the robustness of the causal Bayesian network approach. EPIDOS is a multicenter study, conducted in an ambulatory care setting in five French cities between 1992 and 1996 and updated in 2010. The study included 7598 women aged 75 years or older, in which fractures were assessed quarterly during 4 years. A causal Bayesian network and a logistic regression were performed on EPIDOS data to describe major variables involved in hip fractures occurrences. Both models had similar association estimations and predictive performances. They detected gait speed and mineral bone density as variables the most involved in the fracture process. The causal Bayesian network showed that gait speed and bone mineral density were directly connected to fracture and seem to mediate the influence of all the other variables included in our model. The logistic regression approach detected multiple interactions involving psychotropic drug use, age and bone mineral density. Both approaches retrieved similar variables as predictors of hip fractures. However, Bayesian network highlighted the whole web of relation between the variables involved in the analysis, suggesting a possible mechanism leading to hip fracture. According to the latter results, intervention focusing concomitantly on gait speed and bone mineral density may be necessary for an optimal prevention of hip fracture occurrence in elderly people.

Verifying Safety Messages Using Relative-Time and Zone Priority in Vehicular Ad Hoc Networks.

PubMed

Banani, Sam; Gordon, Steven; Thiemjarus, Surapa; Kittipiyakul, Somsak

2018-04-13

In high-density road networks, with each vehicle broadcasting multiple messages per second, the arrival rate of safety messages can easily exceed the rate at which digital signatures can be verified. Since not all messages can be verified, algorithms for selecting which messages to verify are required to ensure that each vehicle receives appropriate awareness about neighbouring vehicles. This paper presents a novel scheme to select important safety messages for verification in vehicular ad hoc networks (VANETs). The proposed scheme uses location and direction of the sender, as well as proximity and relative-time between vehicles, to reduce the number of irrelevant messages verified (i.e., messages from vehicles that are unlikely to cause an accident). Compared with other existing schemes, the analysis results show that the proposed scheme can verify messages from nearby vehicles with lower inter-message delay and reduced packet loss and thus provides high level of awareness of the nearby vehicles.

Polymer-free carbon nanotube thermoelectrics with improved charge carrier transport and power factor

DOE PAGES

Norton-Baker, Brenna; Ihly, Rachelle; Gould, Isaac E.; ...

2016-11-17

Here, semiconducting single-walled carbon nanotubes (s-SWCNTs) have recently attracted attention for their promise as active components in a variety of optical and electronic applications, including thermoelectricity generation. Here we demonstrate that removing the wrapping polymer from the highly enriched s-SWCNT network leads to substantial improvements in charge carrier transport and thermoelectric power factor. These improvements arise primarily from an increase in charge carrier mobility within the s-SWCNT networks because of removal of the insulating polymer and control of the level of nanotube bundling in the network, which enables higher thin-film conductivity for a given carrier density. Ultimately, these studies demonstratemore » that highly enriched s-SWCNT thin films, in the complete absence of any accompanying semiconducting polymer, can attain thermoelectric power factors in the range of approximately 400 μW m -1K -2, which is on par with that of some of the best single-component organic thermoelectrics demonstrated to date.« less

Verifying Safety Messages Using Relative-Time and Zone Priority in Vehicular Ad Hoc Networks

PubMed Central

Banani, Sam; Thiemjarus, Surapa; Kittipiyakul, Somsak

2018-01-01

In high-density road networks, with each vehicle broadcasting multiple messages per second, the arrival rate of safety messages can easily exceed the rate at which digital signatures can be verified. Since not all messages can be verified, algorithms for selecting which messages to verify are required to ensure that each vehicle receives appropriate awareness about neighbouring vehicles. This paper presents a novel scheme to select important safety messages for verification in vehicular ad hoc networks (VANETs). The proposed scheme uses location and direction of the sender, as well as proximity and relative-time between vehicles, to reduce the number of irrelevant messages verified (i.e., messages from vehicles that are unlikely to cause an accident). Compared with other existing schemes, the analysis results show that the proposed scheme can verify messages from nearby vehicles with lower inter-message delay and reduced packet loss and thus provides high level of awareness of the nearby vehicles. PMID:29652840

Both Intrinsic Substrate Preference and Network Context Contribute to Substrate Selection of Classical Tyrosine Phosphatases*

PubMed Central

Tinti, Michele; Paoluzi, Serena; Santonico, Elena; Masch, Antonia; Schutkowski, Mike

2017-01-01

Reversible tyrosine phosphorylation is a widespread post-translational modification mechanism underlying cell physiology. Thus, understanding the mechanisms responsible for substrate selection by kinases and phosphatases is central to our ability to model signal transduction at a system level. Classical protein-tyrosine phosphatases can exhibit substrate specificity in vivo by combining intrinsic enzymatic specificity with the network of protein-protein interactions, which positions the enzymes in close proximity to their substrates. Here we use a high throughput approach, based on high density phosphopeptide chips, to determine the in vitro substrate preference of 16 members of the protein-tyrosine phosphatase family. This approach helped identify one residue in the substrate binding pocket of the phosphatase domain that confers specificity for phosphopeptides in a specific sequence context. We also present a Bayesian model that combines intrinsic enzymatic specificity and interaction information in the context of the human protein interaction network to infer new phosphatase substrates at the proteome level. PMID:28159843

The Vehicular Information Space Framework

NASA Astrophysics Data System (ADS)

Prinz, Vivian; Schlichter, Johann; Schweiger, Benno

Vehicular networks are distributed, self-organizing and highly mobile ad hoc networks. They allow for providing drivers with up-to-the-minute information about their environment. Therefore, they are expected to be a decisive future enabler for enhancing driving comfort and safety. This article introduces the Vehicular Information Space framework (VIS). Vehicles running the VIS form a kind of distributed database. It enables them to provide information like existing hazards, parking spaces or traffic densities in a location aware and fully distributed manner. In addition, vehicles can retrieve, modify and delete these information items. The underlying algorithm is based on features derived from existing structured Peer-to-Peer algorithms and extended to suit the specific characteristics of highly mobile ad hoc networks. We present, implement and simulate the VIS using a motorway and an urban traffic environment. Simulation studies on VIS message occurrence show that the VIS implies reasonable traffic overhead. Also, overall VIS message traffic is independent from the number of information items provided.

Comparisons of topological properties in autism for the brain network construction methods

NASA Astrophysics Data System (ADS)

Lee, Min-Hee; Kim, Dong Youn; Lee, Sang Hyeon; Kim, Jin Uk; Chung, Moo K.

2015-03-01

Structural brain networks can be constructed from the white matter fiber tractography of diffusion tensor imaging (DTI), and the structural characteristics of the brain can be analyzed from its networks. When brain networks are constructed by the parcellation method, their network structures change according to the parcellation scale selection and arbitrary thresholding. To overcome these issues, we modified the Ɛ -neighbor construction method proposed by Chung et al. (2011). The purpose of this study was to construct brain networks for 14 control subjects and 16 subjects with autism using both the parcellation and the Ɛ-neighbor construction method and to compare their topological properties between two methods. As the number of nodes increased, connectedness decreased in the parcellation method. However in the Ɛ-neighbor construction method, connectedness remained at a high level even with the rising number of nodes. In addition, statistical analysis for the parcellation method showed significant difference only in the path length. However, statistical analysis for the Ɛ-neighbor construction method showed significant difference with the path length, the degree and the density.

The effect of hubs and shortcuts on fixation time in evolutionary graphs

NASA Astrophysics Data System (ADS)

Askari, Marziyeh; Moradi Miraghaei, Zeinab; Aghababaei Samani, Keivan

2017-07-01

How can a new species (like a gene, an idea, or a strategy) take over the whole of a population? This process, which is called fixation, is considerably affected by the structure of the population. There are two key quantities to quantify the fixation process, namely fixation probability and fixation time. Fixation probability has been vastly studied in recent years, but fixation time has not been completely explored, yet. This is because the discovery of a relationship between fixation time and network structure is quite challenging. In this paper we investigate this relationship for a number of well-known complex networks. We show that the existence of a few high-degree nodes (hubs) in the network results in a longer fixation time, while the existence of a few short-cuts decreases the fixation time. Furthermore we investigate the effect of network parameters, such as connection probability, on fixation time. We show that by increasing the density of edges, fixation time decreases for all types of studied networks. Finally, we survey the effect of rewiring probability in a Watts-Strogatz network on fixation time.