Dynamic Network Model for Smart City Data-Loss Resilience Case Study: City-to-City Network for Crime Analytics

Science.gov (United States)

Kotevska, Olivera; Kusne, A. Gilad; Samarov, Daniel V.; Lbath, Ahmed; Battou, Abdella

2017-01-01

Today’s cities generate tremendous amounts of data, thanks to a boom in affordable smart devices and sensors. The resulting big data creates opportunities to develop diverse sets of context-aware services and systems, ensuring smart city services are optimized to the dynamic city environment. Critical resources in these smart cities will be more rapidly deployed to regions in need, and those regions predicted to have an imminent or prospective need. For example, crime data analytics may be used to optimize the distribution of police, medical, and emergency services. However, as smart city services become dependent on data, they also become susceptible to disruptions in data streams, such as data loss due to signal quality reduction or due to power loss during data collection. This paper presents a dynamic network model for improving service resilience to data loss. The network model identifies statistically significant shared temporal trends across multivariate spatiotemporal data streams and utilizes these trends to improve data prediction performance in the case of data loss. Dynamics also allow the system to respond to changes in the data streams such as the loss or addition of new information flows. The network model is demonstrated by city-based crime rates reported in Montgomery County, MD, USA. A resilient network is developed utilizing shared temporal trends between cities to provide improved crime rate prediction and robustness to data loss, compared with the use of single city-based auto-regression. A maximum improvement in performance of 7.8% for Silver Spring is found and an average improvement of 5.6% among cities with high crime rates. The model also correctly identifies all the optimal network connections, according to prediction error minimization. City-to-city distance is designated as a predictor of shared temporal trends in crime and weather is shown to be a strong predictor of crime in Montgomery County. PMID:29250476

H-Infinity Control Design Considering Packet Loss as a Disturbance for Networked Control Systems

OpenAIRE

OGURA, Takashi; KOBAYASHI, Kentaro; OKADA, Hiraku; KATAYAMA, Masaaki

2017-01-01

This paper studies H∞ control for networked control systems with packet loss. In networked control systems, packet loss is one of major weakness because the control performance deteriorates due to packet loss. H∞ control, which is one of robust control, can design a controller to reduce the influence of disturbances acting on the controlled object. This paper proposes an H∞ control design that considers packet loss as a disturbance. Numerical examples show that the proposed H∞ control design ...

Toward economic flood loss characterization via hazard simulation

Science.gov (United States)

Czajkowski, Jeffrey; Cunha, Luciana K.; Michel-Kerjan, Erwann; Smith, James A.

2016-08-01

Among all natural disasters, floods have historically been the primary cause of human and economic losses around the world. Improving flood risk management requires a multi-scale characterization of the hazard and associated losses—the flood loss footprint. But this is typically not available in a precise and timely manner, yet. To overcome this challenge, we propose a novel and multidisciplinary approach which relies on a computationally efficient hydrological model that simulates streamflow for scales ranging from small creeks to large rivers. We adopt a normalized index, the flood peak ratio (FPR), to characterize flood magnitude across multiple spatial scales. The simulated FPR is then shown to be a key statistical driver for associated economic flood losses represented by the number of insurance claims. Importantly, because it is based on a simulation procedure that utilizes generally readily available physically-based data, our flood simulation approach has the potential to be broadly utilized, even for ungauged and poorly gauged basins, thus providing the necessary information for public and private sector actors to effectively reduce flood losses and save lives.

Dynamical Networks Characterization of Space Weather Events

Science.gov (United States)

Orr, L.; Chapman, S. C.; Dods, J.; Gjerloev, J. W.

2017-12-01

Space weather can cause disturbances to satellite systems, impacting navigation technology and telecommunications; it can cause power loss and aviation disruption. A central aspect of the earth's magnetospheric response to space weather events are large scale and rapid changes in ionospheric current patterns. Space weather is highly dynamic and there are still many controversies about how the current system evolves in time. The recent SuperMAG initiative, collates ground-based vector magnetic field time series from over 200 magnetometers with 1-minute temporal resolution. In principle this combined dataset is an ideal candidate for quantification using dynamical networks. Network properties and parameters allow us to characterize the time dynamics of the full spatiotemporal pattern of the ionospheric current system. However, applying network methodologies to physical data presents new challenges. We establish whether a given pair of magnetometers are connected in the network by calculating their canonical cross correlation. The magnetometers are connected if their cross correlation exceeds a threshold. In our physical time series this threshold needs to be both station specific, as it varies with (non-linear) individual station sensitivity and location, and able to vary with season, which affects ground conductivity. Additionally, the earth rotates and therefore the ground stations move significantly on the timescales of geomagnetic disturbances. The magnetometers are non-uniformly spatially distributed. We will present new methodology which addresses these problems and in particular achieves dynamic normalization of the physical time series in order to form the network. Correlated disturbances across the magnetometers capture transient currents. Once the dynamical network has been obtained [1][2] from the full magnetometer data set it can be used to directly identify detailed inferred transient ionospheric current patterns and track their dynamics. We will show

Individual Hearing Loss: Characterization, Modelling, Compensation Strategies

DEFF Research Database (Denmark)

Santurette, Sébastien; Dau, Torsten; Christensen-Dalsgaard, Jakob

2016-01-01

account for such individual differences, which make it challenging to find adequate compensation strategies in hearing devices. How to characterize, model, and compensate for individual hearing loss were the main topics of the fifth International Symposium on Auditory and Audiological Research (ISAAR...

Leakage Detection and Estimation Algorithm for Loss Reduction in Water Piping Networks

Directory of Open Access Journals (Sweden)

Kazeem B. Adedeji

2017-10-01

Full Text Available Water loss through leaking pipes constitutes a major challenge to the operational service of water utilities. In recent years, increasing concern about the financial loss and environmental pollution caused by leaking pipes has been driving the development of efficient algorithms for detecting leakage in water piping networks. Water distribution networks (WDNs are disperse in nature with numerous number of nodes and branches. Consequently, identifying the segment(s of the network and the exact leaking pipelines connected to this segment(s where higher background leakage outflow occurs is a challenging task. Background leakage concerns the outflow from small cracks or deteriorated joints. In addition, because they are diffuse flow, they are not characterised by quick pressure drop and are not detectable by measuring instruments. Consequently, they go unreported for a long period of time posing a threat to water loss volume. Most of the existing research focuses on the detection and localisation of burst type leakages which are characterised by a sudden pressure drop. In this work, an algorithm for detecting and estimating background leakage in water distribution networks is presented. The algorithm integrates a leakage model into a classical WDN hydraulic model for solving the network leakage flows. The applicability of the developed algorithm is demonstrated on two different water networks. The results of the tested networks are discussed and the solutions obtained show the benefits of the proposed algorithm. A noteworthy evidence is that the algorithm permits the detection of critical segments or pipes of the network experiencing higher leakage outflow and indicates the probable pipes of the network where pressure control can be performed. However, the possible position of pressure control elements along such critical pipes will be addressed in future work.

Loss Performance Modeling for Hierarchical Heterogeneous Wireless Networks With Speed-Sensitive Call Admission Control

DEFF Research Database (Denmark)

Huang, Qian; Huang, Yue-Cai; Ko, King-Tim

2011-01-01

. This approach avoids unnecessary and frequent handoff between cells and reduces signaling overheads. An approximation model with guaranteed accuracy and low computational complexity is presented for the loss performance of multiservice traffic. The accuracy of numerical results is validated by comparing......A hierarchical overlay structure is an alternative solution that integrates existing and future heterogeneous wireless networks to provide subscribers with better mobile broadband services. Traffic loss performance in such integrated heterogeneous networks is necessary for an operator's network...

Network reconfiguration for loss reduction in electrical distribution system using genetic algorithm

International Nuclear Information System (INIS)

Adail, A.S.A.A.

2012-01-01

Distribution system is a critical links between the utility and the nuclear installation. During feeding electricity to that installation there are power losses. The quality of the network depends on the reduction of these losses. Distribution system which feeds the nuclear installation must have a higher quality power. For example, in Inshas site, electrical power is supplied to it from two incoming feeders (one from new abu-zabal substation and the other from old abu-zabal substation). Each feeder is designed to carry the full load, while the operator preferred to connect with a new abu-zabal substation, which has a good power quality. Bad power quality affects directly the nuclear reactor and has a negative impact on the installed sensitive equipment's of the operation. The thesis is Studying the electrical losses in a distribution system (causes and effected factors), feeder reconfiguration methods, and applying of genetic algorithm in an electric distribution power system. In the end, this study proposes an optimization technique based on genetic algorithms for distribution network reconfiguration to reduce the network losses to minimum. The proposed method is applied to IEEE test network; that contain 3 feeders and 16 nodes. The technique is applied through two groups, distribution have general loads, and nuclear loads. In the groups the technique applied to seven cases at normal operation state, system fault condition as well as different loads conditions. Simulated results are drawn to show the accuracy of the technique.

Prediction of thermal hydraulic parameters in the loss of coolant accident by using artificial neural networks

International Nuclear Information System (INIS)

Vaziri, N.; Erfani, A.; Monsefi, M.; Hajabri, A.

2008-01-01

In a reactor accident like loss of coolant accident , one or more signals may not be monitored by control panel for some reasons such as interruptions and so on. Therefore a fast alternative method could guarantee the safe and reliable exploration of nuclear power planets. In this study, we used artificial neural network with Elman recurrent structure to predict six thermal hydraulic signals in a loss of coolant accident after upper plenum break. In the prediction procedure, a few previous samples are fed to the artificial neural network and the output value or next time step is estimated by the network output. The Elman recurrent network is trained with the data obtained from the benchmark simulation of loss of coolant accident in VVER. The results reveal that the predicted values follow the real trends well and artificial neural network can be used as a fast alternative prediction tool in loss of coolant accident

Studying influence of two effective parameters on network losses in transmission expansion planning using DCGA

International Nuclear Information System (INIS)

Shayeghi, H.; Jalilzadeh, S.; Mahdavi, M.; Hadadian, H.

2008-01-01

Transmission network expansion planning (TNEP) is a basic part of power network planning that determines where, when and how many new transmission lines should be added to the network. Its task is to minimize the network construction and operational cost, while meeting imposed technical, economic and reliability constraints. Up till now, various methods have been proposed for solution of the static transmission network expansion planning (STNEP) problem. But, in all of them, the effect of two important parameters i.e., inflation rate and load growth factor on network losses has not been investigated. Thus, in this paper, STNEP is being studied considering the effect of inflation rate and load growth factor on the network losses in a transmission network with different voltage levels using a decimal codification genetic algorithm (DCGA). The effectiveness of the proposed idea is tested on the Garver's six-bus network. The results evaluation reveals that the inflation rate and load growth factor have important effect on the network losses and subsequent network arrangement. In addition, considering the effect of two above-mentioned parameters (inflation rate and load growth factor) in expansion planning of transmission networks with various line voltage levels is caused that the total expansion cost of the network (expansion costs and the operational cost) is calculated more exactly and therefore the network satisfies the requirements of delivering electric power more safely and reliably to load centers

Economic networks: Heterogeneity-induced vulnerability and loss of synchronization

Science.gov (United States)

Colon, Célian; Ghil, Michael

2017-12-01

Interconnected systems are prone to propagation of disturbances, which can undermine their resilience to external perturbations. Propagation dynamics can clearly be affected by potential time delays in the underlying processes. We investigate how such delays influence the resilience of production networks facing disruption of supply. Interdependencies between economic agents are modeled using systems of Boolean delay equations (BDEs); doing so allows us to introduce heterogeneity in production delays and in inventories. Complex network topologies are considered that reproduce realistic economic features, including a network of networks. Perturbations that would otherwise vanish can, because of delay heterogeneity, amplify and lead to permanent disruptions. This phenomenon is enabled by the interactions between short cyclic structures. Difference in delays between two interacting, and otherwise resilient, structures can in turn lead to loss of synchronization in damage propagation and thus prevent recovery. Finally, this study also shows that BDEs on complex networks can lead to metastable relaxation oscillations, which are damped out in one part of a network while moving on to another part.

Analysis of naming game over networks in the presence of memory loss

Science.gov (United States)

Fu, Guiyuan; Cai, Yunze; Zhang, Weidong

2017-08-01

In this paper, we study the dynamics of naming game where individuals are under the influence of memory loss. An extended naming game incorporating memory loss is proposed. Different from the existing naming game models, the individual in the proposed model would forget some words with a probability in his memory during interaction and keep his conveyed word unchanged until he reaches a local agreement. We analyze the dynamics of the proposed model through extensive and comprehensive simulations, where four typical networks with different configuration are employed. The influence of memory loss as well as the population size on the performance of the proposed model is investigated. The simulation results show that (i) the stronger memory loss, the larger convergence time; (ii) as the strength of memory loss becomes stronger, maximum number of total words will decrease, while the maximum number of different words among the population remains almost unchanged; (iii) the maximum number of different words increases linearly with the increase of the population size and coincides with each other under different strength of memory loss. The findings in the proposed model may give an insight to understand better the influence of memory loss on the transient dynamics of language evolution and opinion formation over networks.

Impact of stand-by energy losses in electronic devices on smart network performance

Directory of Open Access Journals (Sweden)

Mandić-Lukić Jasmina S.

2012-01-01

Full Text Available Limited energy resources and environmental concerns due to ever increasing energy consumption, more and more emphasis is being put on energy savings. Smart networks are promoted worldwide as a powerful tool used to improve the energy efficiency through consumption management, as well as to enable the distributed power generation, primarily based on renewable energy sources, to be optimally explored. To make it possible for the smart networks to function, a large number of electronic devices is needed to operate or to be in their stand-by mode. The consumption of these devices is added to the consumption of many other electronic devices already in use in households and offices, thus giving rise to the overall power consumption and threatening to counteract the primary function of smart networks. This paper addresses the consumption of particular electronic devices, with an emphasis placed on their thermal losses when in stand-by mode and their total share in the overall power consumption in certain countries. The thermal losses of electronic devices in their stand-by mode are usually neglected, but it seems theoretically possible that a massive increase in their number can impact net performance of the future smart networks considerably so that above an optimum level of energy savings achieved by their penetration, total consumption begins to increase. Based on the current stand-by energy losses from the existing electronic devices, we propose that the future penetration of smart networks be optimized taking also into account losses from their own electronic devices, required to operate in stand-by mode.

Impact of Loss Synchronization on Reliable High Speed Networks: A Model Based Simulation

Directory of Open Access Journals (Sweden)

Suman Kumar

2014-01-01

Full Text Available Contemporary nature of network evolution demands for simulation models which are flexible, scalable, and easily implementable. In this paper, we propose a fluid based model for performance analysis of reliable high speed networks. In particular, this paper aims to study the dynamic relationship between congestion control algorithms and queue management schemes, in order to develop a better understanding of the causal linkages between the two. We propose a loss synchronization module which is user configurable. We validate our model through simulations under controlled settings. Also, we present a performance analysis to provide insights into two important issues concerning 10 Gbps high speed networks: (i impact of bottleneck buffer size on the performance of 10 Gbps high speed network and (ii impact of level of loss synchronization on link utilization-fairness tradeoffs. The practical impact of the proposed work is to provide design guidelines along with a powerful simulation tool to protocol designers and network developers.

Effect of placement of droop based generators in distribution network on small signal stability margin and network loss

DEFF Research Database (Denmark)

Dheer, D.K.; Doolla, S.; Bandyopadhyay, S.

2017-01-01

, small signal stability margin is on the fore. The present research studied the effect of location of droop-controlled DGs on small signal stability margin and network loss on a modified IEEE 13 bus system, an IEEE 33-bus distribution system and a practical 22-bus radial distribution network. A complete...... loss and stability margin is further investigated by identifying the Pareto fronts for modified IEEE 13 bus, IEEE 33 and practical 22-bus radial distribution network with application of Reference point based Non-dominated Sorting Genetic Algorithm (R-NSGA). Results were validated by time domain......For a utility-connected system, issues related to small signal stability with Distributed Generators (DGs) are insignificant due to the presence of a very strong grid. Optimally placed sources in utility connected microgrid system may not be optimal/stable in islanded condition. Among others issues...

Loss of inhibition in sensorimotor networks in focal hand dystonia

Directory of Open Access Journals (Sweden)

Cecile Gallea

2018-01-01

Interpretation: Impairments of GABAergic neurotransmission in the cerebellum and the sensorimotor cortical areas could explain different aspects of loss of inhibitory control in FHD, the former being involved in maladaptive plasticity, the latter in surround inhibition. Reorganization of the inferior prefrontal cortices, part of the associative network, might be compensatory for the loss of inhibitory control in sensorimotor circuits. These findings suggest that cerebellar and cerebral GABAergic abnormalities could play a role in the functional imbalance of striato-cerebello-cortical loops in dystonia.

Characterization of a Fiber-Coupled 36-Core 3-Mode Photonic Lantern Spatial Multiplexer

DEFF Research Database (Denmark)

Rommel, Simon; Mendinueta, José Manuel Delgado; Klaus, Werner

2017-01-01

A fiber-coupled 108-port photonic lantern spatial-MUX is characterized with a spatially-diverse optical vector network analyzer. Insertion loss, mode-dependent losses, and time response are measured, showing significant mode mixing at a fiber splice.......A fiber-coupled 108-port photonic lantern spatial-MUX is characterized with a spatially-diverse optical vector network analyzer. Insertion loss, mode-dependent losses, and time response are measured, showing significant mode mixing at a fiber splice....

110 kV NETWORK TECHNICAL LOSSES ASSESSMENT. REAL DISTRIBUTION SYSTEM CASE STUDY

Directory of Open Access Journals (Sweden)

BARBULESCU C.

2015-06-01

Full Text Available The paper is focusing on evaluating the technical losses within a real distribution network. The study was conducted for a distribution system operator within the Romanian Power System. The analysed area is represented by a real part of the Romanian Power System. It is modelled in a computer aided power system analysis tool. Several power system operating conditions are analysed. Power system optimization measures are provided having as a goal to reduce the technical losses' value. Values obtained based on the field measurement are compared to the ones provided by computer simulations. These conclusions are very useful for the distribution network operator.

Characterizing Peptide Neutral Losses Induced by Negative Electron-Transfer Dissociation (NETD)

Science.gov (United States)

Rumachik, Neil G.; McAlister, Graeme C.; Russell, Jason D.; Bailey, Derek J.; Wenger, Craig D.; Coon, Joshua J.

2012-01-01

We implemented negative electron-transfer dissociation (NETD) on a hybrid ion trap/Orbitrap mass spectrometer to conduct ion/ion reactions using peptide anions and radical reagent cations. In addition to sequence-informative ladders of a•- and x-type fragment ions, NETD generated intense neutral loss peaks corresponding to the entire or partial side-chain cleavage from amino acids constituting a given peptide. Thus, a critical step towards the characterization of this recently introduced fragmentation technique is a systematic study of synthetic peptides to identify common neutral losses and preferential fragmentation pathways. Examining 46 synthetic peptides with high mass accuracy and high resolution analysis permitted facile determination of the chemical composition of each neutral loss. We identified 19 unique neutral losses from 14 amino acids and three modified amino acids, and assessed the specificity and sensitivity of each neutral loss using a database of 1542 confidently identified peptides generated from NETD shotgun experiments employing high-pH separations and negative electrospray ionization. As residue-specific neutral losses indicate the presence of certain amino acids, we determined that many neutral losses have potential diagnostic utility. We envision this catalogue of neutral losses being incorporated into database search algorithms to improve peptide identification specificity and to further advance characterization of the acidic proteome. PMID:22290482

Dynamic Data-Driven UAV Network for Plume Characterization

Science.gov (United States)

2016-05-23

AFRL-AFOSR-VA-TR-2016-0203 Dynamic Data-Driven UAV Network for Plume Characterization Kamran Mohseni UNIVERSITY OF FLORIDA Final Report 05/23/2016...AND SUBTITLE Dynamic Data-Driven UAV Network for Plume Characterization 5a.  CONTRACT NUMBER 5b.  GRANT NUMBER FA9550-13-1-0090 5c.  PROGRAM ELEMENT...studied a dynamic data driven (DDD) approach to operation of a heterogeneous team of unmanned aerial vehicles ( UAVs ) or micro/miniature aerial

Parameter-free Network Sparsification and Data Reduction by Minimal Algorithmic Information Loss

KAUST Repository

Zenil, Hector

2018-02-16

The study of large and complex datasets, or big data, organized as networks has emerged as one of the central challenges in most areas of science and technology. Cellular and molecular networks in biology is one of the prime examples. Henceforth, a number of techniques for data dimensionality reduction, especially in the context of networks, have been developed. Yet, current techniques require a predefined metric upon which to minimize the data size. Here we introduce a family of parameter-free algorithms based on (algorithmic) information theory that are designed to minimize the loss of any (enumerable computable) property contributing to the object\\'s algorithmic content and thus important to preserve in a process of data dimension reduction when forcing the algorithm to delete first the least important features. Being independent of any particular criterion, they are universal in a fundamental mathematical sense. Using suboptimal approximations of efficient (polynomial) estimations we demonstrate how to preserve network properties outperforming other (leading) algorithms for network dimension reduction. Our method preserves all graph-theoretic indices measured, ranging from degree distribution, clustering-coefficient, edge betweenness, and degree and eigenvector centralities. We conclude and demonstrate numerically that our parameter-free, Minimal Information Loss Sparsification (MILS) method is robust, has the potential to maximize the preservation of all recursively enumerable features in data and networks, and achieves equal to significantly better results than other data reduction and network sparsification methods.

Role of vision loss, functional limitations and the supporting network in depression in a general population.

Science.gov (United States)

van Nispen, Ruth M A; Vreeken, Hilde L; Comijs, Hannie C; Deeg, Dorly J H; van Rens, Ger H M B

2016-02-01

Although the prevalence of depression in visually impaired older persons is high, the association between vision loss and depression seems to be influenced by factors other than visual impairment. In this study, the role of vision loss, functional limitations and social network characteristics in relation to depressive symptoms was investigated. Cross-sectional data (N = 1237) from the Longitudinal Aging Study Amsterdam were used to investigate the prevalence of depression (Center of Epidemiological Studies-Depression scale) within subgroups with increasing vision loss. In linear regression models, functional limitations and social network characteristics were examined as possible mediators in the association between vision loss and depression. Having a partner was considered to be a potential moderator. Although a significant linear trend was found in the presence of depressive symptoms with 14% in normally sighted, 23% in mild and 37% in severe vision loss (χ(2)(1) = 14.9; p depression. Mediators were functional limitations (p depression, a trend was found with increasing severity of vision loss, indicating the need for more attention in (mental) health care and low-vision rehabilitation. In the general older population, vision loss was not an independent determinant of depression but was mediated by functional limitations and social network size. Rather than receiving actual social support, the idea of having a social network to rely on when needed seemed to be associated with lower levels of depression. © 2015 Acta Ophthalmologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.

DISTRIBUTION NETWORK RECONFIGURATION FOR POWER LOSS MINIMIZATION AND VOLTAGE PROFILE ENHANCEMENT USING ANT LION ALGORITHM

Directory of Open Access Journals (Sweden)

Maryam Shokouhi

2017-06-01

Full Text Available Distribution networks are designed as a ring and operated as a radial form. Therefore, the reconfiguration is a simple and cost-effective way to use existing facilities without the need for any new equipment in distribution networks to achieve various objectives such as: power loss reduction, feeder overload reduction, load balancing, voltage profile improvement, reducing the number of switching considering constraints that ultimately result in the power loss reduction. In this paper, a new method based on the Ant Lion algorithm (a modern meta-heuristic algorithm is provided for the reconfiguration of distribution networks. Considering the extension of the distribution networks and complexity of their communications networks, and the various parameters, using smart techniques is inevitable. The proposed approach is tested on the IEEE 33 & 69-bus radial standard distribution networks. The Evaluation of results in MATLAB software shows the effectiveness of the Ant Lion algorithm in the distribution network reconfiguration.

ANALYSIS OF THE HARMONIC LOSSES WITH ARTIFICIAL NEURAL NETWORKS IN UNBALANCED SYSTEM LOSSES USING BALANCED ELECTRIC POWER SYSTEM DATA

Directory of Open Access Journals (Sweden)

Aslan İNAN

2005-01-01

Full Text Available The losses in the power systems should be low as possible as. Saving energy instead of loses (kWh in power utilities can supply much more energy to the consumers. The lower losses the more energy is saved and thus the power system becomes more economical. In recent years, the increasing number of applications and power ratings of the devices which have nonlinear voltage-current characteristics cause voltage waveform distortion and additional losses. While evaluating losses considering harmonics will provide more contribution to obtain more accurate results. In this study, Artificial Neural Networks (ANN method has been presented to predict the harmonic losses in unbalanced power systems by using the data from balanced power system with nonlinear loads.

SegAN: Adversarial Network with Multi-scale L1 Loss for Medical Image Segmentation.

Science.gov (United States)

Xue, Yuan; Xu, Tao; Zhang, Han; Long, L Rodney; Huang, Xiaolei

2018-05-03

Inspired by classic Generative Adversarial Networks (GANs), we propose a novel end-to-end adversarial neural network, called SegAN, for the task of medical image segmentation. Since image segmentation requires dense, pixel-level labeling, the single scalar real/fake output of a classic GAN's discriminator may be ineffective in producing stable and sufficient gradient feedback to the networks. Instead, we use a fully convolutional neural network as the segmentor to generate segmentation label maps, and propose a novel adversarial critic network with a multi-scale L 1 loss function to force the critic and segmentor to learn both global and local features that capture long- and short-range spatial relationships between pixels. In our SegAN framework, the segmentor and critic networks are trained in an alternating fashion in a min-max game: The critic is trained by maximizing a multi-scale loss function, while the segmentor is trained with only gradients passed along by the critic, with the aim to minimize the multi-scale loss function. We show that such a SegAN framework is more effective and stable for the segmentation task, and it leads to better performance than the state-of-the-art U-net segmentation method. We tested our SegAN method using datasets from the MICCAI BRATS brain tumor segmentation challenge. Extensive experimental results demonstrate the effectiveness of the proposed SegAN with multi-scale loss: on BRATS 2013 SegAN gives performance comparable to the state-of-the-art for whole tumor and tumor core segmentation while achieves better precision and sensitivity for Gd-enhance tumor core segmentation; on BRATS 2015 SegAN achieves better performance than the state-of-the-art in both dice score and precision.

Impact of Next Generation District Heating Systems on Distribution Network Heat Losses: A Case Study Approach

Science.gov (United States)

Li, Yu; Rezgui, Yacine

2018-01-01

District heating (DH) is a promising energy pathway to alleviate environmental negative impacts induced by fossil fuels. Improving the performance of DH systems is one of the major challenges facing its wide adoption. This paper discusses the heat losses of the next generation DH based on the constructed Simulink model. Results show that lower distribution temperature and advanced insulation technology greatly reduce network heat losses. Also, the network heat loss can be further minimized by a reduction of heat demand in buildings.

Network-based H.264/AVC whole frame loss visibility model and frame dropping methods.

Science.gov (United States)

Chang, Yueh-Lun; Lin, Ting-Lan; Cosman, Pamela C

2012-08-01

We examine the visual effect of whole frame loss by different decoders. Whole frame losses are introduced in H.264/AVC compressed videos which are then decoded by two different decoders with different common concealment effects: frame copy and frame interpolation. The videos are seen by human observers who respond to each glitch they spot. We found that about 39% of whole frame losses of B frames are not observed by any of the subjects, and over 58% of the B frame losses are observed by 20% or fewer of the subjects. Using simple predictive features which can be calculated inside a network node with no access to the original video and no pixel level reconstruction of the frame, we developed models which can predict the visibility of whole B frame losses. The models are then used in a router to predict the visual impact of a frame loss and perform intelligent frame dropping to relieve network congestion. Dropping frames based on their visual scores proves superior to random dropping of B frames.

Impact of distributed generators on the power loss and voltage profile of sub-transmission network

Directory of Open Access Journals (Sweden)

A.S.O. Ogunjuyigbe

2016-05-01

Full Text Available This paper presents the impact of distributed generator (DG on the power loss and voltage profile of sub-transmission network at different penetration levels (PLs. The various DG technologies are modeled based on their electrical output characteristics. Voltage profile index which allows a single value to represent how well the voltage matches the ideal value is developed. The index allows a fair comparison of the voltage profile obtained from different scenarios. The extent to which DGs affect power losses and voltage profile depend on the type of DG technology, PL and the location in which the DG is connected to the grid. The integration of DGs reduces power losses on the network, however, as the PL increases, the power losses begin to increase. A PL of 50–75% is achieved on 69 kV voltage level and 25–50% penetration on 13.8 kV voltage level without an increase in the power loss. Also more DG can be integrated into the network at point of common connection of higher voltage level compared to the low voltage level.

Effects of neuronal loss in the dynamic model of neural networks

International Nuclear Information System (INIS)

Yoon, B-G; Choi, J; Choi, M Y

2008-01-01

We study the phase transitions and dynamic behavior of the dynamic model of neural networks, with an emphasis on the effects of neuronal loss due to external stress. In the absence of loss the overall results obtained numerically are found to agree excellently with the theoretical ones. When the external stress is turned on, some neurons may deteriorate and die; such loss of neurons, in general, weakens the memory in the system. As the loss increases beyond a critical value, the order parameter measuring the strength of memory decreases to zero either continuously or discontinuously, namely, the system loses its memory via a second- or a first-order transition, depending on the ratio of the refractory period to the duration of action potential

Characterization of complex networks : Application to robustness analysis

NARCIS (Netherlands)

Jamakovic, A.

2008-01-01

This thesis focuses on the topological characterization of complex networks. It specifically focuses on those elementary graph measures that are of interest when quantifying topology-related aspects of the robustness of complex networks. This thesis makes the following contributions to the field of

Characterizing time series: when Granger causality triggers complex networks

Science.gov (United States)

Ge, Tian; Cui, Yindong; Lin, Wei; Kurths, Jürgen; Liu, Chong

2012-08-01

In this paper, we propose a new approach to characterize time series with noise perturbations in both the time and frequency domains by combining Granger causality and complex networks. We construct directed and weighted complex networks from time series and use representative network measures to describe their physical and topological properties. Through analyzing the typical dynamical behaviors of some physical models and the MIT-BIHMassachusetts Institute of Technology-Beth Israel Hospital. human electrocardiogram data sets, we show that the proposed approach is able to capture and characterize various dynamics and has much potential for analyzing real-world time series of rather short length.

Characterizing time series: when Granger causality triggers complex networks

International Nuclear Information System (INIS)

Ge Tian; Cui Yindong; Lin Wei; Liu Chong; Kurths, Jürgen

2012-01-01

In this paper, we propose a new approach to characterize time series with noise perturbations in both the time and frequency domains by combining Granger causality and complex networks. We construct directed and weighted complex networks from time series and use representative network measures to describe their physical and topological properties. Through analyzing the typical dynamical behaviors of some physical models and the MIT-BIH human electrocardiogram data sets, we show that the proposed approach is able to capture and characterize various dynamics and has much potential for analyzing real-world time series of rather short length. (paper)

Characterizing English Poetic Style Using Complex Networks

Science.gov (United States)

Roxas-Villanueva, Ranzivelle Marianne; Nambatac, Maelori Krista; Tapang, Giovanni

Complex networks have been proven useful in characterizing written texts. Here, we use networks to probe if there exist a similarity within, and difference across, era as reflected within the poem's structure. In literary history, boundary lines are set to distinguish the change in writing styles through time. We obtain the network parameters and motif frequencies of 845 poems published from 1522 to 1931 and relate this to the writing of the Elizabethan, 17th Century, Augustan, Romantic and Victorian eras. Analysis of the different network parameters shows a significant difference of the Augustan era (1667-1780) with the rest. The network parameters and the convex hull and centroids of the motif frequencies reflect the adjectival sequence pattern of the poems of the Augustan era.

Characterization of subgraph relationships and distribution in complex networks

International Nuclear Information System (INIS)

Antiqueira, Lucas; Fontoura Costa, Luciano da

2009-01-01

A network can be analyzed at different topological scales, ranging from single nodes to motifs, communities, up to the complete structure. We propose a novel approach which extends from single nodes to the whole network level by considering non-overlapping subgraphs (i.e. connected components) and their interrelationships and distribution through the network. Though such subgraphs can be completely general, our methodology focuses on the cases in which the nodes of these subgraphs share some special feature, such as being critical for the proper operation of the network. The methodology of subgraph characterization involves two main aspects: (i) the generation of histograms of subgraph sizes and distances between subgraphs and (ii) a merging algorithm, developed to assess the relevance of nodes outside subgraphs by progressively merging subgraphs until the whole network is covered. The latter procedure complements the histograms by taking into account the nodes lying between subgraphs, as well as the relevance of these nodes to the overall subgraph interconnectivity. Experiments were carried out using four types of network models and five instances of real-world networks, in order to illustrate how subgraph characterization can help complementing complex network-based studies.

Verifying cell loss requirements in high-speed communication networks

Directory of Open Access Journals (Sweden)

Kerry W. Fendick

1998-01-01

Full Text Available In high-speed communication networks it is common to have requirements of very small cell loss probabilities due to buffer overflow. Losses are measured to verify that the cell loss requirements are being met, but it is not clear how to interpret such measurements. We propose methods for determining whether or not cell loss requirements are being met. A key idea is to look at the stream of losses as successive clusters of losses. Often clusters of losses, rather than individual losses, should be regarded as the important “loss events”. Thus we propose modeling the cell loss process by a batch Poisson stochastic process. Successive clusters of losses are assumed to arrive according to a Poisson process. Within each cluster, cell losses do not occur at a single time, but the distance between losses within a cluster should be negligible compared to the distance between clusters. Thus, for the purpose of estimating the cell loss probability, we ignore the spaces between successive cell losses in a cluster of losses. Asymptotic theory suggests that the counting process of losses initiating clusters often should be approximately a Poisson process even though the cell arrival process is not nearly Poisson. The batch Poisson model is relatively easy to test statistically and fit; e.g., the batch-size distribution and the batch arrival rate can readily be estimated from cell loss data. Since batch (cluster sizes may be highly variable, it may be useful to focus on the number of batches instead of the number of cells in a measurement interval. We also propose a method for approximately determining the parameters of a special batch Poisson cell loss with geometric batch-size distribution from a queueing model of the buffer content. For this step, we use a reflected Brownian motion (RBM approximation of a G/D/1/C queueing model. We also use the RBM model to estimate the input burstiness given the cell loss rate. In addition, we use the RBM model to

Quadratic head loss approximations for optimisation problems in water supply networks

NARCIS (Netherlands)

Pecci, Filippo; Abraham, E.; I, Stoianov

2017-01-01

This paper presents a novel analysis of the accuracy of quadratic approximations for the Hazen–Williams (HW) head loss formula, which enables the control of constraint violations in optimisation problems for water supply networks. The two smooth polynomial approximations considered here minimise the

Dynamic fMRI networks predict success in a behavioral weight loss program among older adults.

Science.gov (United States)

Mokhtari, Fatemeh; Rejeski, W Jack; Zhu, Yingying; Wu, Guorong; Simpson, Sean L; Burdette, Jonathan H; Laurienti, Paul J

2018-06-01

More than one-third of adults in the United States are obese, with a higher prevalence among older adults. Obesity among older adults is a major cause of physical dysfunction, hypertension, diabetes, and coronary heart diseases. Many people who engage in lifestyle weight loss interventions fail to reach targeted goals for weight loss, and most will regain what was lost within 1-2 years following cessation of treatment. This variability in treatment efficacy suggests that there are important phenotypes predictive of success with intentional weight loss that could lead to tailored treatment regimen, an idea that is consistent with the concept of precision-based medicine. Although the identification of biochemical and metabolic phenotypes are one potential direction of research, neurobiological measures may prove useful as substantial behavioral change is necessary to achieve success in a lifestyle intervention. In the present study, we use dynamic brain networks from functional magnetic resonance imaging (fMRI) data to prospectively identify individuals most likely to succeed in a behavioral weight loss intervention. Brain imaging was performed in overweight or obese older adults (age: 65-79 years) who participated in an 18-month lifestyle weight loss intervention. Machine learning and functional brain networks were combined to produce multivariate prediction models. The prediction accuracy exceeded 95%, suggesting that there exists a consistent pattern of connectivity which correctly predicts success with weight loss at the individual level. Connectivity patterns that contributed to the prediction consisted of complex multivariate network components that substantially overlapped with known brain networks that are associated with behavior emergence, self-regulation, body awareness, and the sensory features of food. Future work on independent datasets and diverse populations is needed to corroborate our findings. Additionally, we believe that efforts can begin to

Characterizing Topology of Probabilistic Biological Networks.

Science.gov (United States)

Todor, Andrei; Dobra, Alin; Kahveci, Tamer

2013-09-06

Biological interactions are often uncertain events, that may or may not take place with some probability. Existing studies analyze the degree distribution of biological networks by assuming that all the given interactions take place under all circumstances. This strong and often incorrect assumption can lead to misleading results. Here, we address this problem and develop a sound mathematical basis to characterize networks in the presence of uncertain interactions. We develop a method that accurately describes the degree distribution of such networks. We also extend our method to accurately compute the joint degree distributions of node pairs connected by edges. The number of possible network topologies grows exponentially with the number of uncertain interactions. However, the mathematical model we develop allows us to compute these degree distributions in polynomial time in the number of interactions. It also helps us find an adequate mathematical model using maximum likelihood estimation. Our results demonstrate that power law and log-normal models best describe degree distributions for probabilistic networks. The inverse correlation of degrees of neighboring nodes shows that, in probabilistic networks, nodes with large number of interactions prefer to interact with those with small number of interactions more frequently than expected.

Pricing of embedded generation: Incorporation of externalities and avoided network losses

International Nuclear Information System (INIS)

Rodrigo, Asanka S.; Wijayatunga, Priyantha D.C.

2007-01-01

Traditionally, the electricity purchase tariff of embedded generators reflected only the cost of production and delivery of electricity to the consumers, which includes the costs of labor, capital, operation, taxes and insurance. However, the production of electricity causes adverse impacts on the environment. At present, this issue has not been widely addressed by the existing pricing methodologies. This paper proposes a pricing methodology for renewable energy based embedded electricity generation, incorporating the cost of externalities with a case study on the Sri Lanka power system. It recommends that the embedded generation tariff be based on the principle of 'avoided cost', considering the cost of energy production, cost of externalities and the cost of network losses. While the 'impact path way' approach is proposed for calculation of the cost of externalities of energy, the nodal-based cost calculation is proposed for the avoided cost of network losses calculation. The pricing methodology proposed in the paper provides important information for investors when choosing the most economical site for their development. It can also be used to optimize the network use. These will allow the developers of embedded generation facilities and the utilities operating the national grid to maximize the potential of embedded generation. (author)

Abnormal neural activities of directional brain networks in patients with long-term bilateral hearing loss.

Science.gov (United States)

Xu, Long-Chun; Zhang, Gang; Zou, Yue; Zhang, Min-Feng; Zhang, Dong-Sheng; Ma, Hua; Zhao, Wen-Bo; Zhang, Guang-Yu

2017-10-13

The objective of the study is to provide some implications for rehabilitation of hearing impairment by investigating changes of neural activities of directional brain networks in patients with long-term bilateral hearing loss. Firstly, we implemented neuropsychological tests of 21 subjects (11 patients with long-term bilateral hearing loss, and 10 subjects with normal hearing), and these tests revealed significant differences between the deaf group and the controls. Then we constructed the individual specific virtual brain based on functional magnetic resonance data of participants by utilizing effective connectivity and multivariate regression methods. We exerted the stimulating signal to the primary auditory cortices of the virtual brain and observed the brain region activations. We found that patients with long-term bilateral hearing loss presented weaker brain region activations in the auditory and language networks, but enhanced neural activities in the default mode network as compared with normally hearing subjects. Especially, the right cerebral hemisphere presented more changes than the left. Additionally, weaker neural activities in the primary auditor cortices were also strongly associated with poorer cognitive performance. Finally, causal analysis revealed several interactional circuits among activated brain regions, and these interregional causal interactions implied that abnormal neural activities of the directional brain networks in the deaf patients impacted cognitive function.

Radiation synthesis and characterization of network structure of natural/synthetic double-network superabsorbent polymers

International Nuclear Information System (INIS)

Sen, M.; Hayrabolulu, H.

2011-01-01

Complete text of publication follows. Superabsorbent polymers (SAPs) are moderately cross linked, 3-D, hydrophilic network polymers that can absorb and conserve considerable amounts of aqueous fluids even under certain heat or pressure. Because of the unique properties superior to conventional absorbents, SAPs have found potential application in many fields such as hygienic products, disposable diapers, horticulture, gel actuators, drug-delivery systems, as well as water-blocking tapes coal dewatering, water managing materials for the renewal of arid and desert environment, etc. In recent years, naturally available resources, such as polysaccharides have drawn considerable attention for the preparation of SAPs. Since the mechanical properties of polysaccharide based natural polymers are low, researchers have mostly focused on natural/synthetic polymer/monomer mixtures to obtain novel SAPs. The aim of this study is to synthesize and characterization of network structure of novel double-network (DN) hydrogels as a SAP. Hydrogels with high mechanical strength have been prepared by radiation induced polymerization and crosslink of acrylic acid sodium salt in the presence of natural polymer locust bean gum. Liquid retention capacities and absorbency under load (AUL) analysis of synthesized SAPs was performed at different temperatures in water and synthetic urine solution, in order to determine their SAP character. For the characterization of network structure of the semi-IPN hydrogels, the average molecular weight between cross links (M c ) were evaluated by using uniaxial compression and oscillatory dynamical mechanical analyses and the advantage and disadvantage of these two technique for the characterization of network structures were compared.

The loss of efficiency caused by agents' uncoordinated routing in transport networks.

Science.gov (United States)

Xu, Zhongzhi; Sun, Li; Wang, Junjie; Wang, Pu

2014-01-01

Large-scale daily commuting data were combined with detailed geographical information system (GIS) data to analyze the loss of transport efficiency caused by drivers' uncoordinated routing in urban road networks. We used Price of Anarchy (POA) to quantify the loss of transport efficiency and found that both volume and distribution of human mobility demand determine the POA. In order to reduce POA, a small number of highways require considerable decreases in traffic, and their neighboring arterial roads need to attract more traffic. The magnitude of the adjustment in traffic flow can be estimated using the fundamental measure traffic flow only, which is widely available and easy to collect. Surprisingly, the most congested roads or the roads with largest traffic flow were not those requiring the most reduction of traffic. This study can offer guidance for the optimal control of urban traffic and facilitate improvements in the efficiency of transport networks.

Functional Connectivity with Distinct Neural Networks Tracks Fluctuations in Gain/Loss Framing Susceptibility

Science.gov (United States)

Smith, David V.; Sip, Kamila E.; Delgado, Mauricio R.

2016-01-01

Multiple large-scale neural networks orchestrate a wide range of cognitive processes. For example, interoceptive processes related to self-referential thinking have been linked to the default-mode network (DMN); whereas exteroceptive processes related to cognitive control have been linked to the executive-control network (ECN). Although the DMN and ECN have been postulated to exert opposing effects on cognition, it remains unclear how connectivity with these spatially overlapping networks contribute to fluctuations in behavior. While previous work has suggested the medial prefrontal cortex (MPFC) is involved in behavioral change following feedback, these observations could be linked to interoceptive processes tied to DMN or exteroceptive processes tied to ECN because MPFC is positioned in both networks. To address this problem, we employed independent component analysis combined with dual-regression functional connectivity analysis. Participants made a series of financial decisions framed as monetary gains or losses. In some sessions, participants received feedback from a peer observing their choices; in other sessions, feedback was not provided. Following feedback, framing susceptibility—indexed as the increase in gambling behavior in loss frames compared to gain frames—was heightened in some participants and diminished in others. We examined whether these individual differences were linked to differences in connectivity by contrasting sessions containing feedback against those that did not contain feedback. We found two key results. As framing susceptibility increased, the MPFC increased connectivity with DMN; in contrast, temporal-parietal junction decreased connectivity with the ECN. Our results highlight how functional connectivity patterns with distinct neural networks contribute to idiosyncratic behavioral changes. PMID:25858445

Stochastic Characterization of Communication Network Latency for Wide Area Grid Control Applications.

Energy Technology Data Exchange (ETDEWEB)

Ameme, Dan Selorm Kwami [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Guttromson, Ross [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-10-01

This report characterizes communications network latency under various network topologies and qualities of service (QoS). The characterizations are probabilistic in nature, allowing deeper analysis of stability for Internet Protocol (IP) based feedback control systems used in grid applications. The work involves the use of Raspberry Pi computers as a proxy for a controlled resource, and an ns-3 network simulator on a Linux server to create an experimental platform (testbed) that can be used to model wide-area grid control network communications in smart grid. Modbus protocol is used for information transport, and Routing Information Protocol is used for dynamic route selection within the simulated network.

Microstructural characterization of stone wool fibre network

DEFF Research Database (Denmark)

Chapelle, Lucie; Brøndsted, Povl; Kusano, Yukihiro

2014-01-01

Understanding the mechanical properties of fibrous network as complex as stone wool materials requires a relevant description of their microstructure and architecture. In this study, different methods have been proposed to characterize the fibre orientation, diameter and length of fibres as well...

The loss of efficiency caused by agents' uncoordinated routing in transport networks.

Directory of Open Access Journals (Sweden)

Zhongzhi Xu

Full Text Available Large-scale daily commuting data were combined with detailed geographical information system (GIS data to analyze the loss of transport efficiency caused by drivers' uncoordinated routing in urban road networks. We used Price of Anarchy (POA to quantify the loss of transport efficiency and found that both volume and distribution of human mobility demand determine the POA. In order to reduce POA, a small number of highways require considerable decreases in traffic, and their neighboring arterial roads need to attract more traffic. The magnitude of the adjustment in traffic flow can be estimated using the fundamental measure traffic flow only, which is widely available and easy to collect. Surprisingly, the most congested roads or the roads with largest traffic flow were not those requiring the most reduction of traffic. This study can offer guidance for the optimal control of urban traffic and facilitate improvements in the efficiency of transport networks.

Characterizing auditory processing and perception in individual listeners with sensorineural hearing loss

DEFF Research Database (Denmark)

Jepsen, Morten Løve; Dau, Torsten

2011-01-01

–438 (2008)] was used as a framework. The parameters of the cochlear processing stage of the model were adjusted to account for behaviorally estimated individual basilar-membrane inputoutput functions and the audiogram, from which the amounts of inner hair-cell and outer hair-cell losses were estimated......This study considered consequences of sensorineural hearing loss in ten listeners. The characterization of individual hearing loss was based on psychoacoustic data addressing audiometric pure-tone sensitivity, cochlear compression, frequency selectivity, temporal resolution, and intensity...

Damper-to-damper path loss characterization for intra-vehicular wireless sensor networks

NARCIS (Netherlands)

Mendes da Costa Jr., C.A.; Gao, H.; Le Polain, T.; van Dommele, A.R.; Smolders, A.B.; Dheans, M.; Baltus, P.G.M.

2017-01-01

Intra-Vehicular Wireless Sensor Networks (IVWSNs) is one of the major advances in electrical smart cars. It could extend the driving distance of E-cars by reducing the weight of bulky cables. It can also bring more sensing functions, turning the car into smart units for Intelligent Transportation

Damper-to-damper path loss characterization for intra-vehicular wireless sensor networks

NARCIS (Netherlands)

Costa, Carlos A.M.; Gao, Hao; Le Polain, Thibault; Van Dommele, Rainier; Smolders, Bart; Dheans, Miguel; Baltus, Peter

2018-01-01

Intra-Vehicular Wireless Sensor Networks (IVWSNs) is one of the major advances in electrical smart cars. It could extend the driving distance of E-cars by reducing the weight of bulky cables. It can also bring more sensing functions, turning the car into smart units for Intelligent Transportation

Characterizing contract-based multiagent resource allocation in networks.

Science.gov (United States)

An, Bo; Lesser, Victor

2010-06-01

We consider a multiagent resource allocation problem where individual users intend to route traffic by requesting the help of entities across a network, and a cost is incurred at each network node that depends on the amount of traffic to be routed. We propose to study contract-based network resource allocation. In our model, users and nodes in the network make contracts before nodes route traffic for the users. The problem is an interesting self-interested negotiation problem because it requires the complete assembly of a set of distinct resources, and there are multiple combinations of distinct resources that could satisfy the goal of negotiation. First, we characterize the network allocation problem and show that finding optimal allocations is NP-complete and is inapproximable. We take both Nash equilibrium and pairwise Nash equilibrium as the solution concepts to characterize the equilibrium allocations. We find that, for any resource allocation game, Nash equilibrium and pairwise Nash equilibrium always exist. In addition, socially optimal allocations are always supported by Nash equilibrium and pairwise Nash equilibrium. We introduce best-response dynamics in which each agent takes a myopic best-response strategy and interacts with each other to dynamically form contracts. We analyze the convergence of the dynamics in some special cases. We also experimentally study the convergence rate of the dynamics and how efficient the evolved allocation is as compared with the optimal allocation in a variety of environments.

Associations between sensory loss and social networks, participation, support, and loneliness: Analysis of the Canadian Longitudinal Study on Aging.

Science.gov (United States)

Mick, Paul; Parfyonov, Maksim; Wittich, Walter; Phillips, Natalie; Kathleen Pichora-Fuller, M

2018-01-01

To determine if hearing loss, vision loss, and dual sensory loss were associated with social network diversity, social participation, availability of social support, and loneliness, respectively, in a population-based sample of older Canadians and to determine whether age or sex modified the associations. Cross-sectional population-based study. Canada. The sample included 21 241 participants in the Canadian Longitudinal Study on Aging tracking cohort. The sample was nationally representative of English- and French-speaking, non-institutionalized 45- to 89-year-old Canadians who did not live on First Nations reserves and who had normal cognition. Participants with missing data for any of the variables in the multivariable regression models were excluded from analysis. Hearing and vision loss were determined by self-report. Dual sensory loss was defined as reporting both hearing and vision loss. Univariate analyses were performed to assess cross-sectional associations between hearing, vision, and dual sensory loss, and social, demographic, and medical variables. Multivariable regression models were used to analyze cross-sectional associations between each type of sensory loss and social network diversity, social participation, availability of social support, and loneliness. Vision loss (in men) and dual sensory loss (in 65- to 85-year-olds) were independently associated with reduced social network diversity. Vision loss and dual sensory loss (in 65- to 85-year-olds) were each independently associated with reduced social participation. All forms of sensory loss were associated with both low availability of social support and loneliness. Sensory impairment is associated with reduced social function in older Canadians. Interventions and research that address the social needs of older individuals with sensory loss are needed. Copyright© the College of Family Physicians of Canada.

An Optimal Domestic Electric Vehicle Charging Strategy for Reducing Network Transmission Loss While Taking Seasonal Factors into Consideration

Directory of Open Access Journals (Sweden)

Yuancheng Zhao

2018-01-01

Full Text Available With the rapid growth of domestic electric vehicle charging loads, the peak-valley gap and power fluctuation rate of power systems increase sharply, which can lead to the increase of network losses and energy efficiency reduction. This paper tries to regulate network loads and reduce power system transmission loss by optimizing domestic electric vehicle charging loads. In this paper, a domestic electric vehicle charging loads model is first developed by analyzing the key factors that can affect users’ charging behavior. Subsequently, the Monte Carlo method is proposed to simulate the power consumption of a cluster of domestic electric vehicles. After that, an optimal electric vehicle charging strategy based on the 0-1 integer programming is presented to regulate network daily loads. Finally, by taking the IEEE33 distributed power system as an example, this paper tries to verify the efficacy of the proposed optimal charging strategy and the necessity for considering seasonal factors when scheduling electric vehicle charging loads. Simulation results show that the proposed 0-1 integer programming method does have good performance in reducing the network peak-valley gap, voltage fluctuation rate, and transmission loss. Moreover, it has some potential to further reduce power system transmission loss when seasonal factors are considered.

A novel analytical characterization for short-term plasticity parameters in spiking neural networks.

Science.gov (United States)

O'Brien, Michael J; Thibeault, Corey M; Srinivasa, Narayan

2014-01-01

Short-term plasticity (STP) is a phenomenon that widely occurs in the neocortex with implications for learning and memory. Based on a widely used STP model, we develop an analytical characterization of the STP parameter space to determine the nature of each synapse (facilitating, depressing, or both) in a spiking neural network based on presynaptic firing rate and the corresponding STP parameters. We demonstrate consistency with previous work by leveraging the power of our characterization to replicate the functional volumes that are integral for the previous network stabilization results. We then use our characterization to predict the precise transitional point from the facilitating regime to the depressing regime in a simulated synapse, suggesting in vitro experiments to verify the underlying STP model. We conclude the work by integrating our characterization into a framework for finding suitable STP parameters for self-sustaining random, asynchronous activity in a prescribed recurrent spiking neural network. The systematic process resulting from our analytical characterization improves the success rate of finding the requisite parameters for such networks by three orders of magnitude over a random search.

Quantitative phosphoproteomics to characterize signaling networks

DEFF Research Database (Denmark)

Rigbolt, Kristoffer T G; Blagoev, Blagoy

2012-01-01

for analyzing protein phosphorylation at a system-wide scale and has become the intuitive strategy for comprehensive characterization of signaling networks. Contemporary phosphoproteomics use highly optimized procedures for sample preparation, mass spectrometry and data analysis algorithms to identify......Reversible protein phosphorylation is involved in the regulation of most, if not all, major cellular processes via dynamic signal transduction pathways. During the last decade quantitative phosphoproteomics have evolved from a highly specialized area to a powerful and versatile platform...... and quantify thousands of phosphorylations, thus providing extensive overviews of the cellular signaling networks. As a result of these developments quantitative phosphoproteomics have been applied to study processes as diverse as immunology, stem cell biology and DNA damage. Here we review the developments...

DRINKING WATER CONSUMPTION AND LOSS IN ALGERIA THE CASE OF NETWORKS WITH LOW LEVEL COUNTING

Directory of Open Access Journals (Sweden)

Rachid Masmoudi

2016-01-01

Full Text Available Demand for drinking domestic water is continuously increasing specially in urban centres which experience high demographic expansion. The decrease of water losses in water supply networks can help preserve such a rare resource. Low number of water meters and intermittent supply make it difficult to quantify the leaking volumes of water. This article presents an analysis of the consumption for drinking water based on an extrapolation from a sample of consumers on whom data are available. Comparison of the volumes of water produced allows a determination of the losses in the water supply system. This analysis is completed by measurements of night flows. The results obtained may be relied on for an evaluation of the needs for drinking water in the South of Algeria, and for future regional development. The study indicates a high rate of water losses in the distribution network, reaching about 40%, and over-consumption due to an insufficient number of water meters and discontinuous supply. It is recommended that water meters come into general use and defective parts of the network are rehabilitated. We will try then to make the necessary recommendations in order to better functioning of the water supply systems in Algeria.

Characterizing the topology of probabilistic biological networks.

Science.gov (United States)

Todor, Andrei; Dobra, Alin; Kahveci, Tamer

2013-01-01

Biological interactions are often uncertain events, that may or may not take place with some probability. This uncertainty leads to a massive number of alternative interaction topologies for each such network. The existing studies analyze the degree distribution of biological networks by assuming that all the given interactions take place under all circumstances. This strong and often incorrect assumption can lead to misleading results. In this paper, we address this problem and develop a sound mathematical basis to characterize networks in the presence of uncertain interactions. Using our mathematical representation, we develop a method that can accurately describe the degree distribution of such networks. We also take one more step and extend our method to accurately compute the joint-degree distributions of node pairs connected by edges. The number of possible network topologies grows exponentially with the number of uncertain interactions. However, the mathematical model we develop allows us to compute these degree distributions in polynomial time in the number of interactions. Our method works quickly even for entire protein-protein interaction (PPI) networks. It also helps us find an adequate mathematical model using MLE. We perform a comparative study of node-degree and joint-degree distributions in two types of biological networks: the classical deterministic networks and the more flexible probabilistic networks. Our results confirm that power-law and log-normal models best describe degree distributions for both probabilistic and deterministic networks. Moreover, the inverse correlation of degrees of neighboring nodes shows that, in probabilistic networks, nodes with large number of interactions prefer to interact with those with small number of interactions more frequently than expected. We also show that probabilistic networks are more robust for node-degree distribution computation than the deterministic ones. all the data sets used, the software

Eddy Current Flaw Characterization Using Neural Networks

International Nuclear Information System (INIS)

Song, S. J.; Park, H. J.; Shin, Y. K.

1998-01-01

Determination of location, shape and size of a flaw from its eddy current testing signal is one of the fundamental issues in eddy current nondestructive evaluation of steam generator tubes. Here, we propose an approach to this problem; an inversion of eddy current flaw signal using neural networks trained by finite element model-based synthetic signatures. Total 216 eddy current signals from four different types of axisymmetric flaws in tubes are generated by finite element models of which the accuracy is experimentally validated. From each simulated signature, total 24 eddy current features are extracted and among them 13 features are finally selected for flaw characterization. Based on these features, probabilistic neural networks discriminate flaws into four different types according to the location and the shape, and successively back propagation neural networks determine the size parameters of the discriminated flaw

Practical characterization of large networks using neighborhood information

KAUST Repository

Wang, Pinghui

2018-02-14

Characterizing large complex networks such as online social networks through node querying is a challenging task. Network service providers often impose severe constraints on the query rate, hence limiting the sample size to a small fraction of the total network of interest. Various ad hoc subgraph sampling methods have been proposed, but many of them give biased estimates and no theoretical basis on the accuracy. In this work, we focus on developing sampling methods for large networks where querying a node also reveals partial structural information about its neighbors. Our methods are optimized for NoSQL graph databases (if the database can be accessed directly), or utilize Web APIs available on most major large networks for graph sampling. We show that our sampling method has provable convergence guarantees on being an unbiased estimator, and it is more accurate than state-of-the-art methods. We also explore methods to uncover shortest paths between a subset of nodes and detect high degree nodes by sampling only a small fraction of the network of interest. Our results demonstrate that utilizing neighborhood information yields methods that are two orders of magnitude faster than state-of-the-art methods.

Characterization of Volatiles Loss from Soil Samples at Lunar Environments

Science.gov (United States)

Kleinhenz, Julie; Smith, Jim; Roush, Ted; Colaprete, Anthony; Zacny, Kris; Paulsen, Gale; Wang, Alex; Paz, Aaron

2017-01-01

Resource Prospector Integrated Thermal Vacuum Test Program A series of ground based dirty thermal vacuum tests are being conducted to better understand the subsurface sampling operations for RP Volatiles loss during sampling operations Hardware performance Sample removal and transfer Concept of operationsInstrumentation5 test campaigns over 5 years have been conducted with RP hardware with advancing hardware designs and additional RP subsystems Volatiles sampling 4 years Using flight-forward regolith sampling hardware, empirically determine volatile retention at lunar-relevant conditions Use data to improve theoretical predictions Determine driving variables for retention Bound water loss potential to define measurement uncertainties. The main goal of this talk is to introduce you to our approach to characterizing volatiles loss for RP. Introduce the facility and its capabilities Overview of the RP hardware used in integrated testing (most recent iteration) Summarize the test variables used thus farReview a sample of the results.

Risk seeking for losses modulates the functional connectivity of the default mode and left frontoparietal networks in young males.

Science.gov (United States)

Deza Araujo, Yacila I; Nebe, Stephan; Neukam, Philipp T; Pooseh, Shakoor; Sebold, Miriam; Garbusow, Maria; Heinz, Andreas; Smolka, Michael N

2018-06-01

Value-based decision making (VBDM) is a principle that states that humans and other species adapt their behavior according to the dynamic subjective values of the chosen or unchosen options. The neural bases of this process have been extensively investigated using task-based fMRI and lesion studies. However, the growing field of resting-state functional connectivity (RSFC) may shed light on the organization and function of brain connections across different decision-making domains. With this aim, we used independent component analysis to study the brain network dynamics in a large cohort of young males (N = 145) and the relationship of these dynamics with VBDM. Participants completed a battery of behavioral tests that evaluated delay aversion, risk seeking for losses, risk aversion for gains, and loss aversion, followed by an RSFC scan session. We identified a set of large-scale brain networks and conducted our analysis only on the default mode network (DMN) and networks comprising cognitive control, appetitive-driven, and reward-processing regions. Higher risk seeking for losses was associated with increased connectivity between medial temporal regions, frontal regions, and the DMN. Higher risk seeking for losses was also associated with increased coupling between the left frontoparietal network and occipital cortices. These associations illustrate the participation of brain regions involved in prospective thinking, affective decision making, and visual processing in participants who are greater risk-seekers, and they demonstrate the sensitivity of RSFC to detect brain connectivity differences associated with distinct VBDM parameters.

Application of Network Analysis for Characterizing Service Modularity

DEFF Research Database (Denmark)

Frandsen, Thomas

2012-01-01

The purpose of this paper is to explore the potential of the application of network analytical techniques to identify and characterize modularity of service processes. Services can be conceptualized as systems of interrelated components which can be decomposed in order to achieve a modular design...

Chromatic characterization of a three-channel colorimeter using back-propagation neural networks

Science.gov (United States)

Pardo, P. J.; Pérez, A. L.; Suero, M. I.

2004-09-01

This work describes a method for the chromatic characterization of a three-channel colorimeter of recent design and construction dedicated to color vision research. The colorimeter consists of two fixed monochromators and a third monochromator interchangeable with a cathode ray tube or any other external light source. Back-propagation neural networks were used for the chromatic characterization to establish the relationship between each monochromator's input parameters and the tristimulus values of each chromatic stimulus generated. The results showed the effectiveness of this type of neural-network-based system for the chromatic characterization of the stimuli produced by any monochromator.

A network model for characterizing brine channels in sea ice

Science.gov (United States)

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

2018-03-01

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

Event-Driven Control for Networked Control Systems With Quantization and Markov Packet Losses.

Science.gov (United States)

Yang, Hongjiu; Xu, Yang; Zhang, Jinhui

2016-05-23

In this paper, event-driven is used in a networked control system (NCS) which is subjected to the effect of quantization and packet losses. A discrete event-detector is used to monitor specific events in the NCS. Both an arbitrary region quantizer and Markov jump packet losses are also considered for the NCS. Based on zoom strategy and Lyapunov theory, a complete proof is given to guarantee mean square stability of the closed-loop system. Stabilization of the NCS is ensured by designing a feedback controller. Lastly, an inverted pendulum model is given to show the advantages and effectiveness of the proposed results.

Characterizing short-term stability for Boolean networks over any distribution of transfer functions

International Nuclear Information System (INIS)

Seshadhri, C.; Smith, Andrew M.; Vorobeychik, Yevgeniy; Mayo, Jackson R.; Armstrong, Robert C.

2016-01-01

Here we present a characterization of short-term stability of random Boolean networks under arbitrary distributions of transfer functions. Given any distribution of transfer functions for a random Boolean network, we present a formula that decides whether short-term chaos (damage spreading) will happen. We provide a formal proof for this formula, and empirically show that its predictions are accurate. Previous work only works for special cases of balanced families. Finally, it has been observed that these characterizations fail for unbalanced families, yet such families are widespread in real biological networks.

Characterizing multistationarity regimes in biochemical reaction networks.

Directory of Open Access Journals (Sweden)

Irene Otero-Muras

Full Text Available Switch like responses appear as common strategies in the regulation of cellular systems. Here we present a method to characterize bistable regimes in biochemical reaction networks that can be of use to both direct and reverse engineering of biological switches. In the design of a synthetic biological switch, it is important to study the capability for bistability of the underlying biochemical network structure. Chemical Reaction Network Theory (CRNT may help at this level to decide whether a given network has the capacity for multiple positive equilibria, based on their structural properties. However, in order to build a working switch, we also need to ensure that the bistability property is robust, by studying the conditions leading to the existence of two different steady states. In the reverse engineering of biological switches, knowledge collected about the bistable regimes of the underlying potential model structures can contribute at the model identification stage to a drastic reduction of the feasible region in the parameter space of search. In this work, we make use and extend previous results of the CRNT, aiming not only to discriminate whether a biochemical reaction network can exhibit multiple steady states, but also to determine the regions within the whole space of parameters capable of producing multistationarity. To that purpose we present and justify a condition on the parameters of biochemical networks for the appearance of multistationarity, and propose an efficient and reliable computational method to check its satisfaction through the parameter space.

Characterizing system dynamics with a weighted and directed network constructed from time series data

International Nuclear Information System (INIS)

Sun, Xiaoran; Small, Michael; Zhao, Yi; Xue, Xiaoping

2014-01-01

In this work, we propose a novel method to transform a time series into a weighted and directed network. For a given time series, we first generate a set of segments via a sliding window, and then use a doubly symbolic scheme to characterize every windowed segment by combining absolute amplitude information with an ordinal pattern characterization. Based on this construction, a network can be directly constructed from the given time series: segments corresponding to different symbol-pairs are mapped to network nodes and the temporal succession between nodes is represented by directed links. With this conversion, dynamics underlying the time series has been encoded into the network structure. We illustrate the potential of our networks with a well-studied dynamical model as a benchmark example. Results show that network measures for characterizing global properties can detect the dynamical transitions in the underlying system. Moreover, we employ a random walk algorithm to sample loops in our networks, and find that time series with different dynamics exhibits distinct cycle structure. That is, the relative prevalence of loops with different lengths can be used to identify the underlying dynamics

Characterizing system dynamics with a weighted and directed network constructed from time series data

Energy Technology Data Exchange (ETDEWEB)

Sun, Xiaoran, E-mail: sxr0806@gmail.com [Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen 518055 (China); School of Mathematics and Statistics, The University of Western Australia, Crawley WA 6009 (Australia); Small, Michael, E-mail: michael.small@uwa.edu.au [School of Mathematics and Statistics, The University of Western Australia, Crawley WA 6009 (Australia); Zhao, Yi [Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen 518055 (China); Xue, Xiaoping [Department of Mathematics, Harbin Institute of Technology, Harbin 150025 (China)

2014-06-15

In this work, we propose a novel method to transform a time series into a weighted and directed network. For a given time series, we first generate a set of segments via a sliding window, and then use a doubly symbolic scheme to characterize every windowed segment by combining absolute amplitude information with an ordinal pattern characterization. Based on this construction, a network can be directly constructed from the given time series: segments corresponding to different symbol-pairs are mapped to network nodes and the temporal succession between nodes is represented by directed links. With this conversion, dynamics underlying the time series has been encoded into the network structure. We illustrate the potential of our networks with a well-studied dynamical model as a benchmark example. Results show that network measures for characterizing global properties can detect the dynamical transitions in the underlying system. Moreover, we employ a random walk algorithm to sample loops in our networks, and find that time series with different dynamics exhibits distinct cycle structure. That is, the relative prevalence of loops with different lengths can be used to identify the underlying dynamics.

Optimizing the District Heating Primary Network from the Perspective of Economic-Specific Pressure Loss

Directory of Open Access Journals (Sweden)

Haichao Wang

2017-07-01

Full Text Available A district heating (DH system is one of the most important components of infrastructures in cold areas. Proper DH network design should balance the initial investment and the heat distribution cost of the DH network. Currently, this design is often based on a recommended value for specific pressure loss (R = ∆P/L in the main lines. This will result in a feasible network design, but probably not be optimal in most cases. The paper develops a novel optimization model to facilitate the design by considering the initial investment in the pipes and the heat distribution costs. The model will generate all possible network scenarios consisting of different series of diameters for each pipe in the flow direction of the network. Then, the annuity on the initial investment, the heat distribution cost, and the total annual cost will be calculated for each network scenario, taking into account the uncertainties of the material prices and the yearly operating time levels. The model is applied to a sample DH network and the results indicate that the model works quite well, clearly identifying the optimal network design and demonstrating that the heat distribution cost is more important than the initial investment in DH network design.

Stabilization of a Wireless Networked Control System with Packet Loss and Time Delay: An ADS Approach

Directory of Open Access Journals (Sweden)

Jing Wang

2012-01-01

Full Text Available The stabilization problem of a wireless networked control system is considered in this paper. Both time delay and packet loss exist simultaneously in the wireless network. The system is modeled as an asynchronous dynamic system (ADS with unstable subsystems. A sufficient condition for the system to be stable is presented. A numerical example is given to demonstrate the effectiveness of the proposed approach.

Case Library Construction Technology of Energy Loss in Distribution Networks Considering Regional Differentiation Theory

Directory of Open Access Journals (Sweden)

Ze Yuan

2017-11-01

Full Text Available The grid structures, load levels, and running states of distribution networks in different supply regions are known as the influencing factors of energy loss. In this paper, the case library of energy loss is constructed to differentiate the crucial factors of energy loss in the different supply regions. First of all, the characteristic state values are selected as the representation of the cases based on the analysis of energy loss under various voltage classes and in different types of regions. Then, the methods of Grey Relational Analysis and the K-Nearest Neighbor are utilized to implement the critical technologies of case library construction, including case representation, processing, analysis, and retrieval. Moreover, the analysis software of the case library is designed based on the case library construction technology. Some case studies show that there are many differences and similarities concerning the factors that influence the energy loss in different types of regions. In addition, the most relevant sample case can be retrieved from the case library. Compared with the traditional techniques, constructing a case library provides a new way to find out the characteristics of energy loss in different supply regions and constitutes differentiated loss-reducing programs.

Low loss power splitter for antenna beam forming networks using probes in a waveguide

DEFF Research Database (Denmark)

Dich, Mikael; Mortensen, Mette Dahl

1994-01-01

The design of a low loss one-to-four power splitter suitable for beam forming networks in antenna arrays is presented. The power splitter is constructed of a shorted waveguide in which five coaxial probes are inserted. Methods for the design of the power splitter are presented together...

Initial Characterization of Optical Communications with Disruption-Tolerant Network Protocols

Science.gov (United States)

Schoolcraft, Joshua; Wilson, Keith

2011-01-01

Disruption-tolerant networks (DTNs) are groups of network assets connected with a suite of communication protocol technologies designed to mitigate the effects of link delay and disruption. Application of DTN protocols to diverse groups of network resources in multiple sub-networks results in an overlay network-of-networks with autonomous data routing capability. In space environments where delay or disruption is expected, performance of this type of architecture (such as an interplanetary internet) can increase with the inclusion of new communications mediums and techniques. Space-based optical communication links are therefore an excellent building block of space DTN architectures. When compared to traditional radio frequency (RF) communications, optical systems can provide extremely power-efficient and high bandwidth links bridging sub-networks. Because optical links are more susceptible to link disruption and experience the same light-speed delays as RF, optical-enabled DTN architectures can lessen potential drawbacks and maintain the benefits of autonomous optical communications over deep space distances. These environment-driven expectations - link delay and interruption, along with asymmetric data rates - are the purpose of the proof-of-concept experiment outlined herein. In recognizing the potential of these two technologies, we report an initial experiment and characterization of the performance of a DTN-enabled space optical link. The experiment design employs a point-to-point free-space optical link configured to have asymmetric bandwidth. This link connects two networked systems running a DTN protocol implementation designed and written at JPL for use on spacecraft, and further configured for higher bandwidth performance. Comparing baseline data transmission metrics with and without periodic optical link interruptions, the experiment confirmed the DTN protocols' ability to handle real-world unexpected link outages while maintaining capability of

Optimal reconfiguration-based dynamic tariff for congestion management and line loss reduction in distribution networks

DEFF Research Database (Denmark)

Huang, Shaojun; Wu, Qiuwei; Cheng, Lin

2016-01-01

This paper presents an optimal reconfiguration-based dynamic tariff (DT) method for congestion management and line loss reduction in distribution networks with high penetration of electric vehicles. In the proposed DT concept, feeder reconfiguration (FR) is employed through mixed integer programm...

Epidemic Survivability: Characterizing Networks Under Epidemic-like Failure Propagation Scenarios

DEFF Research Database (Denmark)

Manzano, Marc; Calle, Eusebi; Ripoll, Jordi

2013-01-01

Epidemics theory has been used in different contexts in order to describe the propagation of diseases, human interactions or natural phenomena. In computer science, virus spreading has been also characterized using epidemic models. Although in the past the use of epidemic models...... in telecommunication networks has not been extensively considered, nowadays, with the increasing computation capacity and complexity of operating systems of modern network devices (routers, switches, etc.), the study of possible epidemic-like failure scenarios must be taken into account. When epidemics occur......, such as in other multiple failure scenarios, identifying the level of vulnerability offered by a network is one of the main challenges. In this paper, we present epidemic survivability, a new network measure that describes the vulnerability of each node of a network under a specific epidemic intensity. Moreover...

A Formal Approach to the Selection by Minimum Error and Pattern Method for Sensor Data Loss Reduction in Unstable Wireless Sensor Network Communications.

Science.gov (United States)

Kim, Changhwa; Shin, DongHyun

2017-05-12

There are wireless networks in which typically communications are unsafe. Most terrestrial wireless sensor networks belong to this category of networks. Another example of an unsafe communication network is an underwater acoustic sensor network (UWASN). In UWASNs in particular, communication failures occur frequently and the failure durations can range from seconds up to a few hours, days, or even weeks. These communication failures can cause data losses significant enough to seriously damage human life or property, depending on their application areas. In this paper, we propose a framework to reduce sensor data loss during communication failures and we present a formal approach to the Selection by Minimum Error and Pattern (SMEP) method that plays the most important role for the reduction in sensor data loss under the proposed framework. The SMEP method is compared with other methods to validate its effectiveness through experiments using real-field sensor data sets. Moreover, based on our experimental results and performance comparisons, the SMEP method has been validated to be better than others in terms of the average sensor data value error rate caused by sensor data loss.

THE EVALUATION OF THE EFFECT OF REACTIVE POWER COMPENSATION IN ELECTRIC POWER LOSSES IN ELECTRIC NETWORK OF RAILWAY JUNCTION

OpenAIRE

O. I. Bondar; I. L. Bondar

2009-01-01

In this work the generalized mathematical model of an electrical network of the electrified railway junction is proposed. An estimation of influence of static var compensators installation on electric power losses in a network is executed on the basis of given model.

Low loss power splitter for antenna beam forming networks using probes in a waveguide

OpenAIRE

Dich, Mikael; Mortensen, Mette Dahl

1994-01-01

The design of a low loss one-to-four power splitter suitable for beam forming networks in antenna arrays is presented. The power splitter is constructed of a shorted waveguide in which five coaxial probes are inserted. Methods for the design of the power splitter are presented together with an experimental verification

Investigation of extra power loss sharing among photovoltaic inverters caused by reactive power management in distribution networks

DEFF Research Database (Denmark)

Demirok, Erhan; Sera, Dezso; Teodorescu, Remus

2014-01-01

load and power loss on the feeders and individual inverters. Simplified energy loss evaluation is carried out here by using analytical average loss modeling of 2-level full bridge inverter coupled with network load flow analysis simulating one month period. The study shows that whatever Q control......Grid-connected photovoltaic (PV) inverters tailored with reactive power management feature can support the grid voltage especially when the voltage fluctuates near its admissible limits. Although Q control allows reducing the grid voltage elevation along the distribution feeder, it brings extra...... is selected, extra power loss is not a substantial amount to take into consideration. Similarly, loss difference among the inverters located at the various points is negligible....

Estimation of break location and size for loss of coolant accidents using neural networks

International Nuclear Information System (INIS)

Na, Man Gyun; Shin, Sun Ho; Jung, Dong Won; Kim, Soong Pyung; Jeong, Ji Hwan; Lee, Byung Chul

2004-01-01

In this work, a probabilistic neural network (PNN) that has been applied well to the classification problems is used in order to identify the break locations of loss of coolant accidents (LOCA) such as hot-leg, cold-leg and steam generator tubes. Also, a fuzzy neural network (FNN) is designed to estimate the break size. The inputs to PNN and FNN are time-integrated values obtained by integrating measurement signals during a short time interval after reactor scram. An automatic structure constructor for the fuzzy neural network automatically selects the input variables from the time-integrated values of many measured signals, and optimizes the number of rules and its related parameters. It is verified that the proposed algorithm identifies very well the break locations of LOCAs and also, estimate their break size accurately

Characterization and metabolic synthetic lethal testing in a new model of SDH-loss familial pheochromocytoma and paraganglioma.

Science.gov (United States)

Smestad, John; Hamidi, Oksana; Wang, Lin; Holte, Molly Nelson; Khazal, Fatimah Al; Erber, Luke; Chen, Yue; Maher, L James

2018-01-19

Succinate dehydrogenase (SDH)-loss pheochromocytoma and paraganglioma (PPGL) are tumors driven by metabolic derangement. SDH loss leads to accumulation of intracellular succinate, which competitively inhibits dioxygenase enzymes, causing activation of pseudohypoxic signaling and hypermethylation of histones and DNA. The mechanisms by which these alterations lead to tumorigenesis are unclear, however. In an effort to fundamentally understand how SDH loss reprograms cell biology, we developed an immortalized mouse embryonic fibroblast cell line with conditional disruption of Sdhc and characterize the kinetics of Sdhc gene rearrangement, SDHC protein loss, succinate accumulation, and the resultant hypoproliferative phenotype. We further perform global transcriptomic, epigenomic, and proteomic characterization of changes resulting from SDHC loss, identifying specific perturbations at each biological level. We compare the observed patterns of epigenomic derangement to another previously-described immortalized mouse chromaffin cell model of SDHB loss, and compare both models to human SDH-loss tumors. Finally, we perform analysis of SDHC synthetic lethality with lactate dehydrogenase A (LDHA) and pyruvate carboxylase (PCX), which are important for regeneration of NAD+ and aspartate biosynthesis, respectively. Our data show that SDH-loss cells are selectively vulnerable to LDH genetic knock-down or chemical inhibition, suggesting that LDH inhibition may be an effective therapeutic strategy for SDH-loss PPGL.

Mechanical and swelling behaviour of well characterized polybutadiene networks

Science.gov (United States)

Mckenna, Gregory B.; Hinkley, Jeffrey A.

1986-01-01

Endlinking of hydroxyl-terminated polybutadiene with the appropriate isocyanate has been used to prepare well characterized networks. Two networks have been studied with molecular weights of the prepolymers being 6100 and 2400 g/mole by g.p.c. Cylindrical specimens were prepared and the derivatives of the stored energy function with respect to the stretch invariants were determined by torque and normal force measurements in torsion. From these data the Valanis-Landel (1967) stored energy function derivatives w-prime(lambda) were determined for both networks. The stored energy function for the junction constraint model of Flory (1953, 1977, 1979, 1985) which is a special form of the Valanis-Landel function, has been fitted to that determined from the experiments. The contributions to the stored energy function from the phantom network and from the junction constraints respectively do not agree with predictions from the topologies of the networks. In spite of this, the form of w-prime(lambda) for the junction constraint model gives an excellent 'curve fit' to the data. Comparison is also made with equilibrium swelling.

Ammonia and greenhouse gases losses from mechanically turned cattle manure windrows: A regional composting network.

Science.gov (United States)

Arriaga, Haritz; Viguria, Maialen; López, Diana M; Merino, Pilar

2017-12-01

An on-farm composting network operates in the Basque Country (northern Spain), in which solid manure produced in livestock farms (mostly dairy and beef cattle) is composted through windrow turning. This network aims to produce a valuable resource (compost) for the farmers whereas the volume of the solid manure was reduced at farm level The objective of the study was to assess the gaseous losses (NH 3 and GHG) from 6 on-farm composting windrows (either deep litter systems or solid fraction after slurry separation) after turning operations. Monitored turning events occurred 1 to 4 months after establishing the heaps on the field. Ammonia and greenhouse gas (GHG) losses were estimated by the open and close chamber techniques, respectively. Results showed overall low emission rates related to the long degradation period of the windrows. Maximum NH 3 release was at 2.0 mg m -2 d -1 after the second/third turning events. Baseline N 2 O losses were below 50 mg m -2 d -1 , with maximum rates close to 500 mg m -2 d -1 some days after turning works. Methane emissions were mostly below 100 mg m -2 d -1 , while CO 2 losses were lower than 25 g m -2 d -1 . Carbon dioxide peaks (≈250 g m -2 d -1 ) were reached after the second/third turnings. Overall, gaseous N and C losses accounted for 0.1 and 1% of the initial N and C content of the windrows, respectively. The present study concluded that two/three turning operations in aged solid manure-derived compost windrows do not have significant effects on NH 3 and GHG losses. The magnitude of the gaseous losses from on-farm composting systems is dependent on the manure management practices at farm level (e.g. moment of windrow stacking). Copyright © 2017 Elsevier Ltd. All rights reserved.

Loss of integrity and atrophy in cingulate structural covariance networks in Parkinson's disease.

Science.gov (United States)

de Schipper, Laura J; van der Grond, Jeroen; Marinus, Johan; Henselmans, Johanna M L; van Hilten, Jacobus J

2017-01-01

In Parkinson's disease (PD), the relation between cortical brain atrophy on MRI and clinical progression is not straightforward. Determination of changes in structural covariance networks - patterns of covariance in grey matter density - has shown to be a valuable technique to detect subtle grey matter variations. We evaluated how structural network integrity in PD is related to clinical data. 3 Tesla MRI was performed in 159 PD patients. We used nine standardized structural covariance networks identified in 370 healthy subjects as a template in the analysis of the PD data. Clinical assessment comprised motor features (Movement Disorder Society-Unified Parkinson's Disease Rating Scale; MDS-UPDRS motor scale) and predominantly non-dopaminergic features (SEverity of Non-dopaminergic Symptoms in Parkinson's Disease; SENS-PD scale: postural instability and gait difficulty, psychotic symptoms, excessive daytime sleepiness, autonomic dysfunction, cognitive impairment and depressive symptoms). Voxel-based analyses were performed within networks significantly associated with PD. The anterior and posterior cingulate network showed decreased integrity, associated with the SENS-PD score, p = 0.001 (β = - 0.265, η p 2  = 0.070) and p = 0.001 (β = - 0.264, η p 2  = 0.074), respectively. Of the components of the SENS-PD score, cognitive impairment and excessive daytime sleepiness were associated with atrophy within both networks. We identified loss of integrity and atrophy in the anterior and posterior cingulate networks in PD patients. Abnormalities of both networks were associated with predominantly non-dopaminergic features, specifically cognition and excessive daytime sleepiness. Our findings suggest that (components of) the cingulate networks display a specific vulnerability to the pathobiology of PD and may operate as interfaces between networks involved in cognition and alertness.

Geospatial Analysis of the Building Heat Demand and Distribution Losses in a District Heating Network

Directory of Open Access Journals (Sweden)

Tobias Törnros

2016-11-01

Full Text Available The district heating (DH demand of various systems has been simulated in several studies. Most studies focus on the temporal aspects rather than the spatial component. In this study, the DH demand for a medium-sized DH network in a city in southern Germany is simulated and analyzed in a spatially explicit approach. Initially, buildings are geo-located and attributes obtained from various sources including building type, ground area, and number of stories are merged. Thereafter, the annual primary energy demand for heating and domestic hot water is calculated for individual buildings. Subsequently, the energy demand is aggregated on the segment level of an existing DH network and the water flow is routed through the system. The simulation results show that the distribution losses are overall the highest at the end segments (given in percentage terms. However, centrally located pipes with a low throughflow are also simulated to have high losses. The spatial analyses are not only useful when addressing the current demand. Based on a scenario taking into account the refurbishment of buildings and a decentralization of energy production, the future demand was also addressed. Due to lower demand, the distribution losses given in percentage increase under such conditions.

Is Social Network Diversity Associated with Tooth Loss among Older Japanese Adults?

Science.gov (United States)

Aida, Jun; Kondo, Katsunori; Yamamoto, Tatsuo; Saito, Masashige; Ito, Kanade; Suzuki, Kayo; Osaka, Ken; Kawachi, Ichiro

2016-01-01

We sought to examine social network diversity as a potential determinant of oral health, considering size and contact frequency of the social network and oral health behaviors. Our cross-sectional study was based on data from the 2010 Japan Gerontological Evaluation Study. Data from 19,756 community-dwelling individuals aged 65 years or older were analyzed. We inquired about diversity of friendships based on seven types of friends. Ordered logistic regression models were developed to determine the association between the diversity of social networks and number of teeth (categorized as ≥20, 10-19, 1-9, and 0). Of the participants, 54.1% were women (mean age, 73.9 years; standard deviation, 6.2). The proportion of respondents with ≥20 teeth was 34.1%. After adjusting for age, sex, socioeconomic status (income, education, and occupation), marital status, health status (diabetes and mental health), and size and contact frequency of the social network, an increase in the diversity of social networks was significantly associated with having more teeth (odds ratio = 1.08; 95% confidence interval, 1.04-1.11). Even adjusted for oral health behaviors (smoking, curative/preventive dental care access, use of dental floss/fluoride toothpaste), significant association was still observed (odds ratio = 1.05 (95% confidence interval, 1.02-1.08)). Social connectedness among people from diverse backgrounds may increase information channels and promote the diffusion of oral health behaviors and prevent tooth loss.

Is Social Network Diversity Associated with Tooth Loss among Older Japanese Adults?

Directory of Open Access Journals (Sweden)

Jun Aida

Full Text Available We sought to examine social network diversity as a potential determinant of oral health, considering size and contact frequency of the social network and oral health behaviors.Our cross-sectional study was based on data from the 2010 Japan Gerontological Evaluation Study. Data from 19,756 community-dwelling individuals aged 65 years or older were analyzed. We inquired about diversity of friendships based on seven types of friends. Ordered logistic regression models were developed to determine the association between the diversity of social networks and number of teeth (categorized as ≥20, 10-19, 1-9, and 0.Of the participants, 54.1% were women (mean age, 73.9 years; standard deviation, 6.2. The proportion of respondents with ≥20 teeth was 34.1%. After adjusting for age, sex, socioeconomic status (income, education, and occupation, marital status, health status (diabetes and mental health, and size and contact frequency of the social network, an increase in the diversity of social networks was significantly associated with having more teeth (odds ratio = 1.08; 95% confidence interval, 1.04-1.11. Even adjusted for oral health behaviors (smoking, curative/preventive dental care access, use of dental floss/fluoride toothpaste, significant association was still observed (odds ratio = 1.05 (95% confidence interval, 1.02-1.08.Social connectedness among people from diverse backgrounds may increase information channels and promote the diffusion of oral health behaviors and prevent tooth loss.

Validation of Tilt Gain under Realistic Path Loss Model and Network Scenario

DEFF Research Database (Denmark)

Nguyen, Huan Cong; Rodriguez, Ignacio; Sørensen, Troels Bundgaard

2013-01-01

Despite being a simple and commonly-applied radio optimization technique, the impact on practical network performance from base station antenna downtilt is not well understood. Most published studies based on empirical path loss models report tilt angles and performance gains that are far higher...... than practical experience suggests. We motivate in this paper, based on a practical LTE scenario, that the discrepancy partly lies in the path loss model, and shows that a more detailed semi-deterministic model leads to both lower gains in terms of SINR, outage probability and downlink throughput...... settings, including the use of electrical and/or mechanical antenna downtilt, and therefore it is possible to find multiple optimum tilt profiles in a practical case. A broader implication of this study is that care must be taken when using the 3GPP model to evaluate advanced adaptive antenna techniques...

Reconfiguration of distribution networks to minimize loss and disruption costs using genetic algorithms

Energy Technology Data Exchange (ETDEWEB)

Cebrian, Juan Carlos; Kagan, Nelson [Department of Electrical Engineering, University of Sao Paulo, Escola Politecnica, Av. Prof. Luciano Gualberto, travessa 3 n 380 - CEP - 05508-970 - Sao Paulo (Brazil)

2010-01-15

In this paper a computational implementation of an evolutionary algorithm (EA) is shown in order to tackle the problem of reconfiguring radial distribution systems. The developed module considers power quality indices such as long duration interruptions and customer process disruptions due to voltage sags, by using the Monte Carlo simulation method. Power quality costs are modeled into the mathematical problem formulation, which are added to the cost of network losses. As for the EA codification proposed, a decimal representation is used. The EA operators, namely selection, recombination and mutation, which are considered for the reconfiguration algorithm, are herein analyzed. A number of selection procedures are analyzed, namely tournament, elitism and a mixed technique using both elitism and tournament. The recombination operator was developed by considering a chromosome structure representation that maps the network branches and system radiality, and another structure that takes into account the network topology and feasibility of network operation to exchange genetic material. The topologies regarding the initial population are randomly produced so as radial configurations are produced through the Prim and Kruskal algorithms that rapidly build minimum spanning trees. (author)

Loss of variation of state detected in soybean metabolic and human myelomonocytic leukaemia cell transcriptional networks under external stimuli

KAUST Repository

Sakata, Katsumi

2016-10-24

Soybean (Glycine max) is sensitive to flooding stress, and flood damage at the seedling stage is a barrier to growth. We constructed two mathematical models of the soybean metabolic network, a control model and a flooded model, from metabolic profiles in soybean plants. We simulated the metabolic profiles with perturbations before and after the flooding stimulus using the two models. We measured the variation of state that the system could maintain from a state–space description of the simulated profiles. The results showed a loss of variation of state during the flooding response in the soybean plants. Loss of variation of state was also observed in a human myelomonocytic leukaemia cell transcriptional network in response to a phorbol-ester stimulus. Thus, we detected a loss of variation of state under external stimuli in two biological systems, regardless of the regulation and stimulus types. Our results suggest that a loss of robustness may occur concurrently with the loss of variation of state in biological systems. We describe the possible applications of the quantity of variation of state in plant genetic engineering and cell biology. Finally, we present a hypothetical “external stimulus-induced information loss” model of biological systems.

Loss of variation of state detected in soybean metabolic and human myelomonocytic leukaemia cell transcriptional networks under external stimuli

KAUST Repository

Sakata, Katsumi; Saito, Toshiyuki; Ohyanagi, Hajime; Okumura, Jun; Ishige, Kentaro; Suzuki, Harukazu; Nakamura, Takuji; Komatsu, Setsuko

2016-01-01

Soybean (Glycine max) is sensitive to flooding stress, and flood damage at the seedling stage is a barrier to growth. We constructed two mathematical models of the soybean metabolic network, a control model and a flooded model, from metabolic profiles in soybean plants. We simulated the metabolic profiles with perturbations before and after the flooding stimulus using the two models. We measured the variation of state that the system could maintain from a state–space description of the simulated profiles. The results showed a loss of variation of state during the flooding response in the soybean plants. Loss of variation of state was also observed in a human myelomonocytic leukaemia cell transcriptional network in response to a phorbol-ester stimulus. Thus, we detected a loss of variation of state under external stimuli in two biological systems, regardless of the regulation and stimulus types. Our results suggest that a loss of robustness may occur concurrently with the loss of variation of state in biological systems. We describe the possible applications of the quantity of variation of state in plant genetic engineering and cell biology. Finally, we present a hypothetical “external stimulus-induced information loss” model of biological systems.

Tweet for health: using an online social network to examine temporal trends in weight loss-related posts.

Science.gov (United States)

Turner-McGrievy, Gabrielle M; Beets, Michael W

2015-06-01

Few studies have used social networking sites to track temporal trends in health-related posts, particularly around weight loss. To examine the temporal relationship of Twitter messages about weight loss over 1 year (2012). Temporal trends in #weightloss mentions and #fitness, #diet, and #health tweets which also had the word "weight" in them were examined using three a priori time periods: (1) holidays: pre-winter holidays, holidays, and post-holidays; (2) Season: winter and summer; and (3) New Year's: pre-New Year's and post-New Year's. Regarding #weightloss, there were 145 (95 % CI 79, 211) more posts/day during holidays and 143 (95 % CI 76, 209) more posts/day after holidays as compared to 480 pre-holiday posts/day; 232 (95 % CI 178, 286) more posts/day during the winter versus summer (441 posts/day); there was no difference in posts around New Year's. Examining social networks for trends in health-related posts may aid in timing interventions when individuals are more likely to be discussing weight loss.

Comprehensive Power Losses Model for Electronic Power Transformer

DEFF Research Database (Denmark)

Yue, Quanyou; Li, Canbing; Cao, Yijia

2018-01-01

and considering the impact of the non-unity power factor and the three-phase unbalanced current, the overall power losses in the distribution network when using the EPT to replace the conventional transformer is analyzed, and the conditions in which the application of the EPT can cause less power losses...... reduced power losses in the distribution network require a comprehensive consideration when comparing the power losses of theEPT and conventional transformer. In this paper, a comprehensive power losses analysis model for the EPT in distribution networks is proposed. By analyzing the EPT self-losses......The electronic power transformer (EPT) has highe rpower losses than the conventional transformer. However, the EPT can correct the power factor, compensate the unbalanced current and reduce the line power losses in the distribution network.Therefore, the higher losses of the EPT and the consequent...

Comprehensive Power Losses Model for Electronic Power Transformer

DEFF Research Database (Denmark)

Yue, Quanyou; Li, Canbing; Cao, Yijia

2018-01-01

The electronic power transformer (EPT) has highe rpower losses than the conventional transformer. However, the EPT can correct the power factor, compensate the unbalanced current and reduce the line power losses in the distribution network.Therefore, the higher losses of the EPT and the consequent...... reduced power losses in the distribution network require a comprehensive consideration when comparing the power losses of theEPT and conventional transformer. In this paper, a comprehensive power losses analysis model for the EPT in distribution networks is proposed. By analyzing the EPT self......-losses and considering the impact of the non-unity power factor and the three-phase unbalanced current, the overall power losses in the distribution network when using the EPT to replace the conventional transformer is analyzed, and the conditions in which the application of the EPT can cause less power losses...

Assuring SS7 dependability: A robustness characterization of signaling network elements

Science.gov (United States)

Karmarkar, Vikram V.

1994-04-01

Current and evolving telecommunication services will rely on signaling network performance and reliability properties to build competitive call and connection control mechanisms under increasing demands on flexibility without compromising on quality. The dimensions of signaling dependability most often evaluated are the Rate of Call Loss and End-to-End Route Unavailability. A third dimension of dependability that captures the concern about large or catastrophic failures can be termed Network Robustness. This paper is concerned with the dependability aspects of the evolving Signaling System No. 7 (SS7) networks and attempts to strike a balance between the probabilistic and deterministic measures that must be evaluated to accomplish a risk-trend assessment to drive architecture decisions. Starting with high-level network dependability objectives and field experience with SS7 in the U.S., potential areas of growing stringency in network element (NE) dependability are identified to improve against current measures of SS7 network quality, as per-call signaling interactions increase. A sensitivity analysis is presented to highlight the impact due to imperfect coverage of duplex network component or element failures (i.e., correlated failures), to assist in the setting of requirements on NE robustness. A benefit analysis, covering several dimensions of dependability, is used to generate the domain of solutions available to the network architect in terms of network and network element fault tolerance that may be specified to meet the desired signaling quality goals.

Characterization of low-temperature microwave loss of thin aluminum oxide formed by plasma oxidation

Energy Technology Data Exchange (ETDEWEB)

Deng, Chunqing, E-mail: cdeng@uwaterloo.ca; Otto, M.; Lupascu, A., E-mail: alupascu@uwaterloo.ca [Institute for Quantum Computing, Department of Physics and Astronomy, and Waterloo Institute for Nanotechnology, University of Waterloo, Waterloo, Ontario N2L 3G1 (Canada)

2014-01-27

We report on the characterization of microwave loss of thin aluminum oxide films at low temperatures using superconducting lumped resonators. The oxide films are fabricated using plasma oxidation of aluminum and have a thickness of 5 nm. We measure the dielectric loss versus microwave power for resonators with frequencies in the GHz range at temperatures from 54 to 303 mK. The power and temperature dependence of the loss are consistent with the tunneling two-level system theory. These results are relevant to understanding decoherence in superconducting quantum devices. The obtained oxide films are thin and robust, making them suitable for capacitors in compact microwave resonators.

Multivariate recurrence network analysis for characterizing horizontal oil-water two-phase flow.

Science.gov (United States)

Gao, Zhong-Ke; Zhang, Xin-Wang; Jin, Ning-De; Marwan, Norbert; Kurths, Jürgen

2013-09-01

Characterizing complex patterns arising from horizontal oil-water two-phase flows is a contemporary and challenging problem of paramount importance. We design a new multisector conductance sensor and systematically carry out horizontal oil-water two-phase flow experiments for measuring multivariate signals of different flow patterns. We then infer multivariate recurrence networks from these experimental data and investigate local cross-network properties for each constructed network. Our results demonstrate that a cross-clustering coefficient from a multivariate recurrence network is very sensitive to transitions among different flow patterns and recovers quantitative insights into the flow behavior underlying horizontal oil-water flows. These properties render multivariate recurrence networks particularly powerful for investigating a horizontal oil-water two-phase flow system and its complex interacting components from a network perspective.

Characterizing root response phenotypes by neural network analysis

OpenAIRE

Hatzig, Sarah V.; Schiessl, Sarah; Stahl, Andreas; Snowdon, Rod J.

2015-01-01

Roots play an immediate role as the interface for water acquisition. To improve sustainability in low-water environments, breeders of major crops must therefore pay closer attention to advantageous root phenotypes; however, the complexity of root architecture in response to stress can be difficult to quantify. Here, the Sholl method, an established technique from neurobiology used for the characterization of neural network anatomy, was adapted to more adequately describe root responses to osm...

Theoretical characterization of the topology of connected carbon nanotubes in random networks

International Nuclear Information System (INIS)

Heitz, Jerome; Leroy, Yann; Hebrard, Luc; Lallement, Christophe

2011-01-01

In recent years, a lot of attention has been paid to carbon nanotube (CNT) networks and their applications to electronic devices. Many studies concentrate on the percolation threshold and the characterization of the conduction in such materials. Nevertheless, no theoretical study has yet attempted to characterize the CNT features inside finite size CNT networks. We present a theoretical approach based on geometrical and statistical considerations. We demonstrate the possibility of explicitly determining some relations existing between two neighbor CNTs and their contact efficiency in random networks of identical CNTs. We calculate the contact probability of rigid identical CNTs and we obtain a probability of 0.2027, which turns out to be independent of the CNT density. Based on this probability, we establish also the dependence of the number of contacts per CNT as a function of the CNT density. All the theoretical results are validated by very good agreement with Monte Carlo simulations.

A Case Study of IPv6 Network Performance: Packet Delay, Loss, and Reordering

Directory of Open Access Journals (Sweden)

Fuliang Li

2017-01-01

Full Text Available Internet Protocol (IP is used to identify and locate computers on the Internet. Currently, IPv4 still routes most Internet traffic. However, with the exhausting of IPv4 addresses, the transition to IPv6 is imminent, because, as the successor of IPv4, IPv6 can provide a larger available address space. Existing studies have addressed the notion that IPv6-centric next generation networks are widely deployed and applied. In order to gain a deep understanding of IPv6, this paper revisits several critical IPv6 performance metrics. Our extensive measurement shows that packet delay and loss rate of IPv6 are similar to IPv4 when the AS-level paths are roughly the same. Specifically, when the link utilization exceeds a threshold, for example, 0.83 in our study, variation of packet delay presents a similar pattern with the variation of link utilization. If packet delay of a path is large, packet-loss rate of that path is more likely to fluctuate. In addition, we conduct a first-ever analysis of packet reordering in IPv6 world. Few IPv6 probe packets are out-of-order and the reordering rate is 2.3⁎10-6, which is much lower than that of 0.79% in IPv4 world. Our analysis consolidates an experimental basis for operators and researchers of IPv6 networks.

Loss Factor Characterization Methodology for Piezoelectric Ceramics

International Nuclear Information System (INIS)

Zhuang Yuan; Ural, Seyit O; Uchino, Kenji

2011-01-01

The key factor for the miniaturization of piezoelectric devices is power density, which is limited by the heat generation or loss mechanisms. There are three loss components for piezoelectric vibrators, i.e., dielectric, elastic and piezoelectric losses. The mechanical quality factor, determined by these three factors, is the figure of merit in the sense of loss or heat generation. In this paper, quality factors of resonance and antiresonance for k 31 , k 33 , and k 15 vibration modes are derived, and the methodology to determine loss factors in various directions is provided. For simplicity, we focus on materials with ∞mm (equivalent to 6mm) crystal symmetry for deriving the loss factors of polycrystalline ceramics, and 16 different loss factors among total 20 can be obtained from the admittance/ impedance measurements.

[Aberrant topological properties of whole-brain functional network in chronic right-sided sensorineural hearing loss: a resting-state functional MRI study].

Science.gov (United States)

Zhang, Lingling; Liu, Bin; Xu, Yangwen; Yang, Ming; Feng, Yuan; Huang, Yaqing; Huan, Zhichun; Hou, Zhaorui

2015-02-03

To investigate the topological properties of the functional brain network in unilateral sensorineural hearing loss patients. In this study, we acquired resting-state BOLD- fMRI data from 19 right-sided SNHL patients and 31 healthy controls with normal hearing and constructed their whole brain functional networks. Two-sample two-tailed t-tests were performed to investigate group differences in topological parameters between the USNHL patients and the controls. Partial correlation analysis was conducted to determine the relationships between the network metrics and USNHL-related variables. Both USNHL patients and controls exhibited small-word architecture in their brain functional networks within the range 0. 1 - 0. 2 of sparsity. Compared to the controls, USNHL patients showed significant increase in characteristic path length and normalized characteristic path length, but significant decrease in global efficiency. Clustering coefficient, local efficiency and normalized clustering coefficient demonstrated no significant difference. Furthermore, USNHL patients exhibited no significant association between the altered network metrics and the duration of USNHL or the severity of hearing loss. Our results indicated the altered topological properties of whole brain functional networks in USNHL patients, which may help us to understand pathophysiologic mechanism of USNHL patients.

Thin film metrology and microwave loss characterization of indium and aluminum/indium superconducting planar resonators

Science.gov (United States)

McRae, C. R. H.; Béjanin, J. H.; Earnest, C. T.; McConkey, T. G.; Rinehart, J. R.; Deimert, C.; Thomas, J. P.; Wasilewski, Z. R.; Mariantoni, M.

2018-05-01

Scalable architectures characterized by quantum bits (qubits) with low error rates are essential to the development of a practical quantum computer. In the superconducting quantum computing implementation, understanding and minimizing material losses are crucial to the improvement of qubit performance. A new material that has recently received particular attention is indium, a low-temperature superconductor that can be used to bond pairs of chips containing standard aluminum-based qubit circuitry. In this work, we characterize microwave loss in indium and aluminum/indium thin films on silicon substrates by measuring superconducting coplanar waveguide resonators and estimating the main loss parameters at powers down to the sub-photon regime and at temperatures between 10 and 450 mK. We compare films deposited by thermal evaporation, sputtering, and molecular beam epitaxy. We study the effects of heating in a vacuum and ambient atmospheric pressure as well as the effects of pre-deposition wafer cleaning using hydrofluoric acid. The microwave measurements are supported by thin film metrology including secondary-ion mass spectrometry. For thermally evaporated and sputtered films, we find that two-level state are the dominant loss mechanism at low photon number and temperature, with a loss tangent due to native indium oxide of ˜ 5 × 10 - 5 . The molecular beam epitaxial films show evidence of the formation of a substantial indium-silicon eutectic layer, which leads to a drastic degradation in resonator performance.

On characterizing population commonalities and subject variations in brain networks.

Science.gov (United States)

Ghanbari, Yasser; Bloy, Luke; Tunc, Birkan; Shankar, Varsha; Roberts, Timothy P L; Edgar, J Christopher; Schultz, Robert T; Verma, Ragini

2017-05-01

Brain networks based on resting state connectivity as well as inter-regional anatomical pathways obtained using diffusion imaging have provided insight into pathology and development. Such work has underscored the need for methods that can extract sub-networks that can accurately capture the connectivity patterns of the underlying population while simultaneously describing the variation of sub-networks at the subject level. We have designed a multi-layer graph clustering method that extracts clusters of nodes, called 'network hubs', which display higher levels of connectivity within the cluster than to the rest of the brain. The method determines an atlas of network hubs that describes the population, as well as weights that characterize subject-wise variation in terms of within- and between-hub connectivity. This lowers the dimensionality of brain networks, thereby providing a representation amenable to statistical analyses. The applicability of the proposed technique is demonstrated by extracting an atlas of network hubs for a population of typically developing controls (TDCs) as well as children with autism spectrum disorder (ASD), and using the structural and functional networks of a population to determine the subject-level variation of these hubs and their inter-connectivity. These hubs are then used to compare ASD and TDCs. Our method is generalizable to any population whose connectivity (structural or functional) can be captured via non-negative network graphs. Copyright © 2015 Elsevier B.V. All rights reserved.

A method for building low loss multi-layer wiring for superconducting microwave devices

Science.gov (United States)

Dunsworth, A.; Barends, R.; Chen, Yu; Chen, Zijun; Chiaro, B.; Fowler, A.; Foxen, B.; Jeffrey, E.; Kelly, J.; Klimov, P. V.; Lucero, E.; Mutus, J. Y.; Neeley, M.; Neill, C.; Quintana, C.; Roushan, P.; Sank, D.; Vainsencher, A.; Wenner, J.; White, T. C.; Neven, H.; Martinis, John M.; Megrant, A.

2018-02-01

Complex integrated circuits require multiple wiring layers. In complementary metal-oxide-semiconductor processing, these layers are robustly separated by amorphous dielectrics. These dielectrics would dominate energy loss in superconducting integrated circuits. Here, we describe a procedure that capitalizes on the structural benefits of inter-layer dielectrics during fabrication and mitigates the added loss. We use a deposited inter-layer dielectric throughout fabrication and then etch it away post-fabrication. This technique is compatible with foundry level processing and can be generalized to make many different forms of low-loss wiring. We use this technique to create freestanding aluminum vacuum gap crossovers (airbridges). We characterize the added capacitive loss of these airbridges by connecting ground planes over microwave frequency λ/4 coplanar waveguide resonators and measuring resonator loss. We measure a low power resonator loss of ˜3.9 × 10-8 per bridge, which is 100 times lower than that of dielectric supported bridges. We further characterize these airbridges as crossovers, control line jumpers, and as part of a coupling network in gmon and fluxmon qubits. We measure qubit characteristic lifetimes (T1s) in excess of 30 μs in gmon devices.

Hearing loss on social media: Who is winning hearts and minds?

Science.gov (United States)

Crowson, Matthew G; Tucci, Debara L; Kaylie, David

2018-06-01

To analyze specific patterns of Twitter usage using common references to hearing loss, and characterize the virtual public that comprises the hearing loss community to inform hearing loss stakeholders for opportunities for engagement and outreach. Social media network analysis. Twitter tweets were sampled from July 2016 to September 2016 using #hearing, #hearingloss, #deaf, #hearingimpairment, #hardofhearing, #deafness, #hearingmatters, #hearinghealth, and #hearingimpaired tags. User and Twitter social community metrics were examined including temporal trends, tweet content, user activity, tweet reach, and an analysis of the tweets' social network. We identified and analyzed 49,208 tweets from July 2016 to September 2016 with tags relevant to hearing loss. Of the 100 most active Twitter accounts, organizations owned 67% compared to 33% owned by individuals. Commercial/for profit and informational organizations were the most common organization account owners (26% and 16%, respectively). Five unique tweets were identified as each having a reach of over 100,000 Twitter users, with the greatest reach exceeding 250,000 users. Temporal analysis identified marked retweet outliers (>300 retweets per hour) that corresponded with a widely publicized event involving the dismissal of a deaf employee from a fast-food chain store. Twitter accounts owned by organizations outnumbered individual accounts, and commercial/for profit user accounts were the most frequently active organization account type. Tweets pertaining to hearing loss may have a broad reach to a large community base. Analyses of social media use can be helpful in discovering issues of interest to the hearing loss community, as well as determining which users and organizations are dominating social network conversations. NA. Laryngoscope, 128:1453-1461, 2018. © 2017 The American Laryngological, Rhinological and Otological Society, Inc.

IP, ethernet and MPLS networks resource and fault management

CERN Document Server

Perez, André

2013-01-01

This book summarizes the key Quality of Service technologies deployed in telecommunications networks: Ethernet, IP, and MPLS. The QoS of the network is made up of two parts: fault and resource management. Network operation quality is among the functions to be fulfilled in order to offer QoS to the end user. It is characterized by four parameters: packet loss, delay, jitter or the variation of delay over time, and availability. Resource management employs mechanisms that enable the first three parameters to be guaranteed or optimized. Fault management aims to ensure continuity of service.

X-ray Spectroscopic Characterization of Plasma for a Charged-Particle Energy-Loss Experiment

Science.gov (United States)

Hoffman, Nm; Lee, Cl; Wilson, Dc; Barnes, Cris W.; Petrasso, Rd; Li, C.; Hicks, D.

2000-10-01

We are pursuing an approach to a charged-particle energy-loss experiment in which charged fusion products from an imploded ICF capsule travel through a well characterized, spatially separate plasma. For this purpose, a fully ionized, uniform, nearly steady-state carbon-hydrogen plasma will be created by laser irradiation of a plastic foil. The temperature and density structure of this plasma must be determined accurately in order to relate observed energy losses to predictions of theory. Various methods for diagnosing the plasma are possible, including Thomson scattering. Alternatively, if a small admixture of higher-Z material such as chlorine is included in the plastic, x-ray spectroscopic techniques will allow the plasma's temperature and density to be determined. Electron temperature is inferred from the ratios of line strengths of various chlorine ion stages, while electron density is determined from the spectra of lithium-like satellite lines near the He beta line of helium-like chlorine. We present results from detailed-configuration accounting (DCA) models of line emission from C+H+Cl plasmas, and estimate the accuracy with which such plasmas can be characterized.

Design and characterization of low-loss 2D grating couplers for silicon photonics integrated circuits

Science.gov (United States)

Lacava, C.; Carrol, L.; Bozzola, A.; Marchetti, R.; Minzioni, P.; Cristiani, I.; Fournier, M.; Bernabe, S.; Gerace, D.; Andreani, L. C.

2016-03-01

We present the characterization of Silicon-on-insulator (SOI) photonic-crystal based 2D grating-couplers (2D-GCs) fabricated by CEA-Leti in the frame of the FP7 Fabulous project, which is dedicated to the realization of devices and systems for low-cost and high-performance passives-optical-networks. On the analyzed samples different test structures are present, including 2D-GC connected to another 2D-GC by different waveguides (in a Mach-Zehnder like configuration), and 2D-GC connected to two separate 2D-GCs, so as to allow a complete assessment of different parameters. Measurements were carried out using a tunable laser source operating in the extended telecom bandwidth and a fiber-based polarization controlling system at the input of device-under-test. The measured data yielded an overall fiber-to-fiber loss of 7.5 dB for the structure composed by an input 2D-GC connected to two identical 2D-GCs. This value was obtained at the peak wavelength of the grating, and the 3-dB bandwidth of the 2D-GC was assessed to be 43 nm. Assuming that the waveguide losses are negligible, so as to make a worst-case analysis, the coupling efficiency of the single 2D-GC results to be equal to -3.75 dB, constituting, to the best of our knowledge, the lowest value ever reported for a fully CMOS compatible 2D-GC. It is worth noting that both the obtained values are in good agreement with those expected by the numerical simulations performed using full 3D analysis by Lumerical FDTD-solutions.

Templated synthesis, characterization, and sensing application of macroscopic platinum nanowire network electrodes

DEFF Research Database (Denmark)

Wang, D. H.; Kou, R.; Gil, M. P.

2005-01-01

properties of the electrodes, such as electrochemical active area and methanol oxidation, have also been studied. Compared with conventional polycrystalline Pt electrodes, these novel nanowire network electrodes possess high electrochemical active areas and demonstrate higher current densities and a lower...... onset potential for methanol electro-oxidation. Enzymatic Pt nanowire-network-based sensors show higher sensitivity for glucose detection than that using conventional polycrystalline Pt electrode. Such macroscopic nanowire network electrodes provide ideal platforms for sensing and other device......Abstract: Novel platinum nanowire network electrodes have been fabricated through electrodeposition using mesoporous silica thin films as templates. These electrodes were characterized by X-ray diffraction, transmission electron microscope, and scanning electron microscope. The electrochemical...

Mobility Network and Safety

Directory of Open Access Journals (Sweden)

Adriana Galderisi

2010-04-01

Full Text Available Mobility network is crucial for ensuring territorial safety with respect to natural and technological hazards. They represent a basic support to community’s everyday life although being exposed elements often characterized by high vulnerability to different hazards and, in the meanwhile, strategic equipments for emergency management. Physical damages or the lack in functioning of those networks may greatly increase the loss of human lives caused by hazardous events as well as produce relevant economic damages at medium and long term. Although the relevance of the mobility networks in assuring territorial safety is at present largely recognized, risk analyses have been long focused on buildings’ vulnerability or, even where they have paid attention to mobility network, they have been mainly focused on the physical damages that a given hazard could may induce on individual elements of such network. It is recent the awareness that mobility network represents a system, characterized by relevant interdependences both among its elements and among network infrastructures and urban systems. Based on these assumptions, this paper points out the heterogeneous aspects of the mobility network vulnerability and their relevance in increasing the overall territorial or urban vulnerability to hazardous events. Therefore, an in-depth investigation of the concept of mobility network vulnerability is provided, in order to highlight the aspects mostly investigated and more recent research perspectives. Finally, a case study in the Campania Region is presented in order to point out how traditional risk analyses, generally referred to individual hazards, can sometimes led to invest in the mobility network improvement or development which, targeted to increase the security of a territory result, on the opposite, in an increase of the territorial vulnerability.

A Formal Approach to the Selection by Minimum Error and Pattern Method for Sensor Data Loss Reduction in Unstable Wireless Sensor Network Communications

OpenAIRE

Kim, Changhwa; Shin, DongHyun

2017-01-01

There are wireless networks in which typically communications are unsafe. Most terrestrial wireless sensor networks belong to this category of networks. Another example of an unsafe communication network is an underwater acoustic sensor network (UWASN). In UWASNs in particular, communication failures occur frequently and the failure durations can range from seconds up to a few hours, days, or even weeks. These communication failures can cause data losses significant enough to seriously damage...

Characterization of leadership styles by analyzing social networks

Directory of Open Access Journals (Sweden)

Enrique Saravia Vergara

2015-12-01

Full Text Available The study presents an analysis of networks to characterize the leadership styles in an institution volunteer, complementary or alternative to classic questionnaires to measure leadership. The study raises test questions to identify friendly relations and prominent leaders in the leadership dimensions of transformational, transactional and passive / avoidant and analyzes, for each of them, the metrics of the network structure as a whole and the role each individual actor. The study exploratory level, based on the opinion of 9 members of a specific project, allowed to show the benefits of network analysis applied to the subject of leadership: (i identified that the climate of "respect and trust", "enthusiasm" and "concern for the welfare of the people" dominate the organization; and (ii the individual role of each leader was identified. Three leaders who are considered as the best friends and care about the welfare of others were identified, but one of them stands for broadcasting "greater respect and trust" and is "an example to follow"; while the other two leaders stand out as being more "enthusiastic and optimistic" and "promote innovation and creativity," among other findings.

Characterization of differentially expressed genes using high-dimensional co-expression networks

DEFF Research Database (Denmark)

Coelho Goncalves de Abreu, Gabriel; Labouriau, Rodrigo S.

2010-01-01

We present a technique to characterize differentially expressed genes in terms of their position in a high-dimensional co-expression network. The set-up of Gaussian graphical models is used to construct representations of the co-expression network in such a way that redundancy and the propagation...... that allow to make effective inference in problems with high degree of complexity (e.g. several thousands of genes) and small number of observations (e.g. 10-100) as typically occurs in high throughput gene expression studies. Taking advantage of the internal structure of decomposable graphical models, we...... construct a compact representation of the co-expression network that allows to identify the regions with high concentration of differentially expressed genes. It is argued that differentially expressed genes located in highly interconnected regions of the co-expression network are less informative than...

Characterization of hearing loss in aged type II diabetics

Science.gov (United States)

Frisina, Susan T.; Mapes, Frances; Kim, SungHee; Frisina, D. Robert; Frisina, Robert D.

2009-01-01

Presbycusis – age-related hearing loss – is the number one communicative disorder and a significant chronic medical condition of the aged. Little is known about how type II diabetes, another prevalent age-related medical condition, and presbycusis interact. The present investigation aimed to comprehensively characterize the nature of hearing impairment in aged type II diabetics. Hearing tests measuring both peripheral (cochlea) and central (brainstem and cortex) auditory processing were utilized. The majority of differences between the hearing abilities of the aged diabetics and their age-matched controls were found in measures of inner ear function. For example, large differences were found in pure-tone audiograms, wideband noise and speech reception thresholds, and otoacoustic emissions. The greatest deficits tended to be at low frequencies. In addition, there was a strong tendency for diabetes to affect the right ear more than the left. One possible interpretation is that as one develops presbycusis, the right ear advantage is lost, and this decline is accelerated by diabetes. In contrast, auditory processing tests that measure both peripheral and central processing showed fewer declines between the elderly diabetics and the control group. Consequences of elevated blood sugar levels as possible underlying physiological mechanisms for the hearing loss are discussed. PMID:16309862

Cumulative exergy losses associated with the production of lead metal

Energy Technology Data Exchange (ETDEWEB)

Szargut, J [Technical Univ. of Silesia, Gliwice (PL). Inst. of Thermal-Engineering; Morris, D R [New Brunswick Univ., Fredericton, NB (Canada). Dept. of Chemical Engineering

1990-08-01

Cumulative exergy losses result from the irreversibility of the links of a technological network leading from raw materials and fuels extracted from nature to the product under consideration. The sum of these losses can be apportioned into partial exergy losses (associated with particular links of the technological network) or into constituent exergy losses (associated with constituent subprocesses of the network). The methods of calculation of the partial and constituent exergy losses are presented, taking into account the useful byproducts substituting the major products of other processes. Analyses of partial and constituent exergy losses are made for the technological network of lead metal production. (author).

Multi-port network and 3D finite-element models for accurate transformer calculations: Single-phase load-loss test

Energy Technology Data Exchange (ETDEWEB)

Escarela-Perez, R. [Departamento de Energia, Universidad Autonoma Metropolitana, Av. San Pablo 180, Col. Reynosa, C.P. 02200, Mexico D.F. (Mexico); Kulkarni, S.V. [Electrical Engineering Department, Indian Institute of Technology, Bombay (India); Melgoza, E. [Instituto Tecnologico de Morelia, Av. Tecnologico 1500, Morelia, Mich., C.P. 58120 (Mexico)

2008-11-15

A six-port impedance network for a three-phase transformer is obtained from a 3D time-harmonic finite-element (FE) model. The network model properly captures the eddy current effects of the transformer tank and frame. All theorems and tools of passive linear networks can be used with the multi-port model to simulate several important operating conditions without resorting anymore to computationally expensive 3D FE simulations. The results of the network model are of the same quality as those produced by the FE program. Although the passive network may seem limited by the assumption of linearity, many important transformer operating conditions imply unsaturated states. Single-phase load-loss measurements are employed to demonstrate the effectiveness of the network model and to understand phenomena that could not be explained with conventional equivalent circuits. In addition, formal deduction of novel closed-form formulae is presented for the calculation of the leakage impedance measured at the high and low voltage sides of the transformer. (author)

Integrated workflow for characterizing and modeling fracture network in unconventional reservoirs using microseismic data

Science.gov (United States)

Ayatollahy Tafti, Tayeb

We develop a new method for integrating information and data from different sources. We also construct a comprehensive workflow for characterizing and modeling a fracture network in unconventional reservoirs, using microseismic data. The methodology is based on combination of several mathematical and artificial intelligent techniques, including geostatistics, fractal analysis, fuzzy logic, and neural networks. The study contributes to scholarly knowledge base on the characterization and modeling fractured reservoirs in several ways; including a versatile workflow with a novel objective functions. Some the characteristics of the methods are listed below: 1. The new method is an effective fracture characterization procedure estimates different fracture properties. Unlike the existing methods, the new approach is not dependent on the location of events. It is able to integrate all multi-scaled and diverse fracture information from different methodologies. 2. It offers an improved procedure to create compressional and shear velocity models as a preamble for delineating anomalies and map structures of interest and to correlate velocity anomalies with fracture swarms and other reservoir properties of interest. 3. It offers an effective way to obtain the fractal dimension of microseismic events and identify the pattern complexity, connectivity, and mechanism of the created fracture network. 4. It offers an innovative method for monitoring the fracture movement in different stages of stimulation that can be used to optimize the process. 5. Our newly developed MDFN approach allows to create a discrete fracture network model using only microseismic data with potential cost reduction. It also imposes fractal dimension as a constraint on other fracture modeling approaches, which increases the visual similarity between the modeled networks and the real network over the simulated volume.

Multi-Point Measurements to Characterize Radiation Belt Electron Precipitation Loss

Science.gov (United States)

Blum, L. W.

2017-12-01

Multipoint measurements in the inner magnetosphere allow the spatial and temporal evolution of various particle populations and wave modes to be disentangled. To better characterize and quantify radiation belt precipitation loss, we utilize multi-point measurements both to study precipitating electrons directly as well as the potential drivers of this loss process. Magnetically conjugate CubeSat and balloon measurements are combined to estimate of the temporal and spatial characteristics of dusk-side precipitation features and quantify loss due to these events. To then understand the drivers of precipitation events, and what determines their spatial structure, we utilize measurements from the dual Van Allen Probes to estimate spatial and temporal scales of various wave modes in the inner magnetosphere, and compare these to precipitation characteristics. The structure, timing, and spatial extent of waves are compared to those of MeV electron precipitation during a few individual events to determine when and where EMIC waves cause radiation belt electron precipitation. Magnetically conjugate measurements provide observational support of the theoretical picture of duskside interaction of EMIC waves and MeV electrons leading to radiation belt loss. Finally, understanding the drivers controlling the spatial scales of wave activity in the inner magnetosphere is critical for uncovering the underlying physics behind the wave generation as well as for better predicting where and when waves will be present. Again using multipoint measurements from the Van Allen Probes, we estimate the spatial and temporal extents and evolution of plasma structures and their gradients in the inner magnetosphere, to better understand the drivers of magnetospheric wave characteristic scales. In particular, we focus on EMIC waves and the plasma parameters important for their growth, namely cold plasma density and cool and warm ion density, anisotropy, and composition.

Revisiting the Characterization of the Losses in Piezoelectric Materials from Impedance Spectroscopy at Resonance

Directory of Open Access Journals (Sweden)

Amador M. González

2016-01-01

Full Text Available Electronic devices using the piezoelectric effect contain piezoelectric materials: often crystals, but in many cases poled ferroelectric ceramics (piezoceramics, polymers or composites. On the one hand, these materials exhibit non-negligible losses, not only dielectric, but also mechanical and piezoelectric. In this work, we made simulations of the effect of the three types of losses in piezoelectric materials on the impedance spectrum at the resonance. We analyze independently each type of loss and show the differences among them. On the other hand, electrical and electronic engineers include piezoelectric sensors in electrical circuits to build devices and need electrical models of the sensor element. Frequently, material scientists and engineers use different languages, and the characteristic material coefficients do not have a straightforward translation to those specific electrical circuit components. To connect both fields of study, we propose the use of accurate methods of characterization from impedance measurements at electromechanical resonance that lead to determination of all types of losses, as an alternative to current standards. We introduce a simplified equivalent circuit model with electrical parameters that account for piezoceramic losses needed for the modeling and design of industrial applications.

Revisiting the Characterization of the Losses in Piezoelectric Materials from Impedance Spectroscopy at Resonance.

Science.gov (United States)

González, Amador M; García, Álvaro; Benavente-Peces, César; Pardo, Lorena

2016-01-26

Electronic devices using the piezoelectric effect contain piezoelectric materials: often crystals, but in many cases poled ferroelectric ceramics (piezoceramics), polymers or composites. On the one hand, these materials exhibit non-negligible losses, not only dielectric, but also mechanical and piezoelectric. In this work, we made simulations of the effect of the three types of losses in piezoelectric materials on the impedance spectrum at the resonance. We analyze independently each type of loss and show the differences among them. On the other hand, electrical and electronic engineers include piezoelectric sensors in electrical circuits to build devices and need electrical models of the sensor element. Frequently, material scientists and engineers use different languages, and the characteristic material coefficients do not have a straightforward translation to those specific electrical circuit components. To connect both fields of study, we propose the use of accurate methods of characterization from impedance measurements at electromechanical resonance that lead to determination of all types of losses, as an alternative to current standards. We introduce a simplified equivalent circuit model with electrical parameters that account for piezoceramic losses needed for the modeling and design of industrial applications.

Multi-Relational Characterization of Dynamic Social Network Communities

Science.gov (United States)

Lin, Yu-Ru; Sundaram, Hari; Kelliher, Aisling

The emergence of the mediated social web - a distributed network of participants creating rich media content and engaging in interactive conversations through Internet-based communication technologies - has contributed to the evolution of powerful social, economic and cultural change. Online social network sites and blogs, such as Facebook, Twitter, Flickr and LiveJournal, thrive due to their fundamental sense of "community". The growth of online communities offers both opportunities and challenges for researchers and practitioners. Participation in online communities has been observed to influence people's behavior in diverse ways ranging from financial decision-making to political choices, suggesting the rich potential for diverse applications. However, although studies on the social web have been extensive, discovering communities from online social media remains challenging, due to the interdisciplinary nature of this subject. In this article, we present our recent work on characterization of communities in online social media using computational approaches grounded on the observations from social science.

Artificial Neural Networks-Based Software for Measuring Heat Collection Rate and Heat Loss Coefficient of Water-in-Glass Evacuated Tube Solar Water Heaters.

Science.gov (United States)

Liu, Zhijian; Liu, Kejun; Li, Hao; Zhang, Xinyu; Jin, Guangya; Cheng, Kewei

2015-01-01

Measurements of heat collection rate and heat loss coefficient are crucial for the evaluation of in service water-in-glass evacuated tube solar water heaters. However, conventional measurement requires expensive detection devices and undergoes a series of complicated procedures. To simplify the measurement and reduce the cost, software based on artificial neural networks for measuring heat collection rate and heat loss coefficient of water-in-glass evacuated tube solar water heaters was developed. Using multilayer feed-forward neural networks with back-propagation algorithm, we developed and tested our program on the basis of 915 measured samples of water-in-glass evacuated tube solar water heaters. This artificial neural networks-based software program automatically obtained accurate heat collection rate and heat loss coefficient using simply "portable test instruments" acquired parameters, including tube length, number of tubes, tube center distance, heat water mass in tank, collector area, angle between tubes and ground and final temperature. Our results show that this software (on both personal computer and Android platforms) is efficient and convenient to predict the heat collection rate and heat loss coefficient due to it slow root mean square errors in prediction. The software now can be downloaded from http://t.cn/RLPKF08.

Artificial Neural Networks-Based Software for Measuring Heat Collection Rate and Heat Loss Coefficient of Water-in-Glass Evacuated Tube Solar Water Heaters

Science.gov (United States)

Liu, Zhijian; Liu, Kejun; Li, Hao; Zhang, Xinyu; Jin, Guangya; Cheng, Kewei

2015-01-01

Measurements of heat collection rate and heat loss coefficient are crucial for the evaluation of in service water-in-glass evacuated tube solar water heaters. However, conventional measurement requires expensive detection devices and undergoes a series of complicated procedures. To simplify the measurement and reduce the cost, software based on artificial neural networks for measuring heat collection rate and heat loss coefficient of water-in-glass evacuated tube solar water heaters was developed. Using multilayer feed-forward neural networks with back-propagation algorithm, we developed and tested our program on the basis of 915measuredsamples of water-in-glass evacuated tube solar water heaters. This artificial neural networks-based software program automatically obtained accurate heat collection rateand heat loss coefficient using simply "portable test instruments" acquired parameters, including tube length, number of tubes, tube center distance, heat water mass in tank, collector area, angle between tubes and ground and final temperature. Our results show that this software (on both personal computer and Android platforms) is efficient and convenient to predict the heat collection rate and heat loss coefficient due to it slow root mean square errors in prediction. The software now can be downloaded from http://t.cn/RLPKF08. PMID:26624613

Engineering equations for characterizing non-linear laser intensity propagation in air with loss.

Science.gov (United States)

Karr, Thomas; Stotts, Larry B; Tellez, Jason A; Schmidt, Jason D; Mansell, Justin D

2018-02-19

The propagation of high peak-power laser beams in real atmospheres will be affected at long range by both linear and nonlinear effects contained therein. Arguably, J. H. Marburger is associated with the mathematical characterization of this phenomenon. This paper provides a validated set of engineering equations for characterizing the self-focusing distance from a laser beam propagating through non-turbulent air with, and without, loss as well as three source configurations: (1) no lens, (2) converging lens and (3) diverging lens. The validation was done against wave-optics simulation results. Some validated equations follow Marburger completely, but others do not, requiring modification of the original theory. Our results can provide a guide for numerical simulations and field experiments.

Measurement based analysis of active and reactive power losses in a distribution network with wind farms and CHPs

DEFF Research Database (Denmark)

Lund, Torsten

2007-01-01

The paper presents an investigation of the active and reactive power losses in a distribution network with wind turbines and combined heat and power plants. The investigation is based on 15 min average power measurements and load flow calculations in the power system simulation tool PowerFactory...

Improvement of defect characterization in ultrasonic testing by adaptative learning network

International Nuclear Information System (INIS)

Bieth, M.; Adamonis, D.C.; Jusino, A.

1982-01-01

Numerous methods exist now for signal analysis in ultrasonic testing. These methods give more or less accurate information for defects characterization. In this paper is presented the development of a particular system based on a computer Signal processing: the Adaptative Learning Network (ALN) allowing the discrimination of defects in function of their nature. The ultrasonic signal is sampled and characterized by parameters amplitude-time and amplitude-frequency. The method was tested on stainless steel tubes welds showing fatigue cracks. The ALN model developed allows, under certain conditions, the discrimination of cracks from other defects [fr

Characterization of a patch-clamp microchannel array towards neuronal networks analysis

DEFF Research Database (Denmark)

Alberti, Massimo; Snakenborg, Detlef; Lopacinska, Joanna M.

2010-01-01

for simultaneous patch clamping of cultured cells or neurons in the same network. A disposable silicon/silicon dioxide (Si/SiO2) chip with a microhole array was integrated in a microfluidic system for cell handling, perfusion and electrical recording. Fluidic characterization showed that our PC mu CA can work...

Improved Safety Margin Characterization of Risk from Loss of Offsite Power

International Nuclear Information System (INIS)

Nelson, Paul

2017-01-01

Original intent: The original intent of this task was ''support of the Risk-Informed Safety Margin Characteristic (RISMC) methodology in order'' ''to address ... efficiency of computation so that more accurate and cost-effective techniques can be used to address safety margin characterizations'' (S. M. Hess et al., ''Risk-Informed Safety Margin Characterization,'' Procs. ICONE17, Brussels, July 2009, CD format). It was intended that ''in Task 1 itself this improvement will be directed toward upon the very important issue of Loss of Offsite Power (LOOP) events,'' more specifically toward the challenge of efficient computation of the multidimensional nonrecovery integral that has been discussed by many previous contributors to the theory of nuclear safety. It was further envisioned that ''three different computational approaches will be explored,'' corresponding to the three subtasks listed below; deliverables were tied to the individual subtasks.

Markov transition probability-based network from time series for characterizing experimental two-phase flow

International Nuclear Information System (INIS)

Gao Zhong-Ke; Hu Li-Dan; Jin Ning-De

2013-01-01

We generate a directed weighted complex network by a method based on Markov transition probability to represent an experimental two-phase flow. We first systematically carry out gas—liquid two-phase flow experiments for measuring the time series of flow signals. Then we construct directed weighted complex networks from various time series in terms of a network generation method based on Markov transition probability. We find that the generated network inherits the main features of the time series in the network structure. In particular, the networks from time series with different dynamics exhibit distinct topological properties. Finally, we construct two-phase flow directed weighted networks from experimental signals and associate the dynamic behavior of gas-liquid two-phase flow with the topological statistics of the generated networks. The results suggest that the topological statistics of two-phase flow networks allow quantitative characterization of the dynamic flow behavior in the transitions among different gas—liquid flow patterns. (general)

Enhancing Sensor Network Data Quality via Collaborated Circuit and Network Operations

Directory of Open Access Journals (Sweden)

Lucas Vespa

2013-04-01

Full Text Available In many applications, the quality of data gathered by sensor networks is directly related to the signal-to-noise ratio (SNR of the sensor data being transmitted in the networks. Different from the SNR that is often used in measuring the quality of communication links, the SNR used in this work measures how accurately the data in the network packets represent the physical parameters being sensed. Hence, the signal here refers to the physical parameters that are being monitored by sensor networks; the noise is due to environmental interference and circuit noises at sensor nodes, and packet loss during network transmission. While issues affecting SNR at sensor nodes have been intensively investigated, the impact of network packet loss on data SNR has not attracted significant attention in sensor network design. This paper investigates the impact of packet loss on sensor network data SNR and shows that data SNR is dramatically affected by network packet loss. A data quality metric, based on data SNR, is developed and a cross-layer adaptive scheme is presented to minimize data quality degradation in congested sensor networks. The proposed scheme consists of adaptive downsampling and bit truncation at sensor nodes and intelligent traffic management techniques at the network level. Simulation results are presented to demonstrate the validity and effectiveness of the proposed techniques.

Fracture network topology and characterization of structural permeability

Science.gov (United States)

Hansberry, Rowan; King, Rosalind; Holford, Simon

2017-04-01

other permeability indicators such as drilling fluid losses, and pore pressure measurements. Initial work with these techniques has led to new developments in our ability to image subsurface faults and fractures at a variety of scales from independent datasets. We establish a strong relationship between features identified using seismic attribute analysis and interpreted natural fractures. However, care must be taken to use these methods in a case-by-case basis, as controls on fracture distribution and orientation can vary significantly with both regional and local influences. These results outline and effective method by which structural permeability can be assessed with existing petroleum datasets. However, unlike the broad stress field, mapping fracture orientation and characteristics within the Australian Continent is complicated as the distribution, geometry, areal extent and connectivity of fracture networks can vary significantly.

An X-band waveguide measurement technique for the accurate characterization of materials with low dielectric loss permittivity

Energy Technology Data Exchange (ETDEWEB)

Allen, Kenneth W., E-mail: kenneth.allen@gtri.gatech.edu; Scott, Mark M.; Reid, David R.; Bean, Jeffrey A.; Ellis, Jeremy D.; Morris, Andrew P.; Marsh, Jeramy M. [Advanced Concepts Laboratory, Georgia Tech Research Institute, Atlanta, Georgia 30318 (United States)

2016-05-15

In this work, we present a new X-band waveguide (WR90) measurement method that permits the broadband characterization of the complex permittivity for low dielectric loss tangent material specimens with improved accuracy. An electrically long polypropylene specimen that partially fills the cross-section is inserted into the waveguide and the transmitted scattering parameter (S{sub 21}) is measured. The extraction method relies on computational electromagnetic simulations, coupled with a genetic algorithm, to match the experimental S{sub 21} measurement. The sensitivity of the technique to sample length was explored by simulating specimen lengths from 2.54 to 15.24 cm, in 2.54 cm increments. Analysis of our simulated data predicts the technique will have the sensitivity to measure loss tangent values on the order of 10{sup −3} for materials such as polymers with relatively low real permittivity values. The ability to accurately characterize low-loss dielectric material specimens of polypropylene is demonstrated experimentally. The method was validated by excellent agreement with a free-space focused-beam system measurement of a polypropylene sheet. This technique provides the material measurement community with the ability to accurately extract material properties of low-loss material specimen over the entire X-band range. This technique could easily be extended to other frequency bands.

Statistical Modeling of Large-Scale Signal Path Loss in Underwater Acoustic Networks

Directory of Open Access Journals (Sweden)

Manuel Perez Malumbres

2013-02-01

Full Text Available In an underwater acoustic channel, the propagation conditions are known to vary in time, causing the deviation of the received signal strength from the nominal value predicted by a deterministic propagation model. To facilitate a large-scale system design in such conditions (e.g., power allocation, we have developed a statistical propagation model in which the transmission loss is treated as a random variable. By applying repetitive computation to the acoustic field, using ray tracing for a set of varying environmental conditions (surface height, wave activity, small node displacements around nominal locations, etc., an ensemble of transmission losses is compiled and later used to infer the statistical model parameters. A reasonable agreement is found with log-normal distribution, whose mean obeys a log-distance increases, and whose variance appears to be constant for a certain range of inter-node distances in a given deployment location. The statistical model is deemed useful for higher-level system planning, where simulation is needed to assess the performance of candidate network protocols under various resource allocation policies, i.e., to determine the transmit power and bandwidth allocation necessary to achieve a desired level of performance (connectivity, throughput, reliability, etc..

Innovations in workplace accessibility and accommodation for persons with hearing loss: using social networking and community of practice theory to promote knowledge exchange and change.

Science.gov (United States)

Shaw, Lynn; Jennings, Mary Beth; Poost-Foroosh, Laya; Hodgins, Heather; Kuchar, Ashley

2013-01-01

Despite widespread availability of assistive technology and the role of occupational therapists and audiologists in workplace health, little is known about how these groups influence the health of workers with hearing loss. Based on a previously conducted study, this paper explores the need for networking and community of practice theory to promote knowledge sharing and use between occupational therapists, audiologists, educators, regulators, workers, and employers. Five occupational therapists and five audiologists participated in in-depth interviews. Grounded theory was used to investigate the processes that hinder or support these professionals in addressing the accommodation needs of and workplace accessibility for workers with hearing loss. Constraints to addressing the needs of workers with hearing loss included: lack of knowledge about professional practice processes, lack of networking, lack of knowledge on current research, and lack of knowledge on the realm of expertise of audiologists by occupational therapists and of occupational therapists by audiologists. Innovations in workplace practice in hearing loss require engagement of occupational therapists, audiologists, and employers in knowledge transfer, networking, and learning. This column introduces two theories that may guide the use and development of evidence, knowledge, and expertise toward innovations in hearing work practice.

Dynamic robustness of knowledge collaboration network of open source product development community

Science.gov (United States)

Zhou, Hong-Li; Zhang, Xiao-Dong

2018-01-01

As an emergent innovative design style, open source product development communities are characterized by a self-organizing, mass collaborative, networked structure. The robustness of the community is critical to its performance. Using the complex network modeling method, the knowledge collaboration network of the community is formulated, and the robustness of the network is systematically and dynamically studied. The characteristics of the network along the development period determine that its robustness should be studied from three time stages: the start-up, development and mature stages of the network. Five kinds of user-loss pattern are designed, to assess the network's robustness under different situations in each of these three time stages. Two indexes - the largest connected component and the network efficiency - are used to evaluate the robustness of the community. The proposed approach is applied in an existing open source car design community. The results indicate that the knowledge collaboration networks show different levels of robustness in different stages and different user loss patterns. Such analysis can be applied to provide protection strategies for the key users involved in knowledge dissemination and knowledge contribution at different stages of the network, thereby promoting the sustainable and stable development of the open source community.

Directed weighted network structure analysis of complex impedance measurements for characterizing oil-in-water bubbly flow.

Science.gov (United States)

Gao, Zhong-Ke; Dang, Wei-Dong; Xue, Le; Zhang, Shan-Shan

2017-03-01

Characterizing the flow structure underlying the evolution of oil-in-water bubbly flow remains a contemporary challenge of great interests and complexity. In particular, the oil droplets dispersing in a water continuum with diverse size make the study of oil-in-water bubbly flow really difficult. To study this issue, we first design a novel complex impedance sensor and systematically conduct vertical oil-water flow experiments. Based on the multivariate complex impedance measurements, we define modalities associated with the spatial transient flow structures and construct modality transition-based network for each flow condition to study the evolution of flow structures. In order to reveal the unique flow structures underlying the oil-in-water bubbly flow, we filter the inferred modality transition-based network by removing the edges with small weight and resulting isolated nodes. Then, the weighted clustering coefficient entropy and weighted average path length are employed for quantitatively assessing the original network and filtered network. The differences in network measures enable to efficiently characterize the evolution of the oil-in-water bubbly flow structures.

Selective logging in tropical forests decreases the robustness of liana-tree interaction networks to the loss of host tree species.

Science.gov (United States)

Magrach, Ainhoa; Senior, Rebecca A; Rogers, Andrew; Nurdin, Deddy; Benedick, Suzan; Laurance, William F; Santamaria, Luis; Edwards, David P

2016-03-16

Selective logging is one of the major drivers of tropical forest degradation, causing important shifts in species composition. Whether such changes modify interactions between species and the networks in which they are embedded remain fundamental questions to assess the 'health' and ecosystem functionality of logged forests. We focus on interactions between lianas and their tree hosts within primary and selectively logged forests in the biodiversity hotspot of Malaysian Borneo. We found that lianas were more abundant, had higher species richness, and different species compositions in logged than in primary forests. Logged forests showed heavier liana loads disparately affecting slow-growing tree species, which could exacerbate the loss of timber value and carbon storage already associated with logging. Moreover, simulation scenarios of host tree local species loss indicated that logging might decrease the robustness of liana-tree interaction networks if heavily infested trees (i.e. the most connected ones) were more likely to disappear. This effect is partially mitigated in the short term by the colonization of host trees by a greater diversity of liana species within logged forests, yet this might not compensate for the loss of preferred tree hosts in the long term. As a consequence, species interaction networks may show a lagged response to disturbance, which may trigger sudden collapses in species richness and ecosystem function in response to additional disturbances, representing a new type of 'extinction debt'. © 2016 The Author(s).

Selective logging in tropical forests decreases the robustness of liana–tree interaction networks to the loss of host tree species

Science.gov (United States)

Magrach, Ainhoa; Senior, Rebecca A.; Rogers, Andrew; Nurdin, Deddy; Benedick, Suzan; Laurance, William F.; Santamaria, Luis; Edwards, David P.

2016-01-01

Selective logging is one of the major drivers of tropical forest degradation, causing important shifts in species composition. Whether such changes modify interactions between species and the networks in which they are embedded remain fundamental questions to assess the ‘health’ and ecosystem functionality of logged forests. We focus on interactions between lianas and their tree hosts within primary and selectively logged forests in the biodiversity hotspot of Malaysian Borneo. We found that lianas were more abundant, had higher species richness, and different species compositions in logged than in primary forests. Logged forests showed heavier liana loads disparately affecting slow-growing tree species, which could exacerbate the loss of timber value and carbon storage already associated with logging. Moreover, simulation scenarios of host tree local species loss indicated that logging might decrease the robustness of liana–tree interaction networks if heavily infested trees (i.e. the most connected ones) were more likely to disappear. This effect is partially mitigated in the short term by the colonization of host trees by a greater diversity of liana species within logged forests, yet this might not compensate for the loss of preferred tree hosts in the long term. As a consequence, species interaction networks may show a lagged response to disturbance, which may trigger sudden collapses in species richness and ecosystem function in response to additional disturbances, representing a new type of ‘extinction debt’. PMID:26936241

Corona helps curb losses

Energy Technology Data Exchange (ETDEWEB)

Laasonen, M.; Lahtinen, M.; Lustre, L.

1996-11-01

The greatest power losses in electricity transmission arise through a phenomenon called load losses. Corona losses caused by the surface discharge of electricity also constitute a considerable cost item. IVS, the nationwide network company, is investigating corona- induced losses, and has also commissioned similar research from IVO International, the Technical Research Centre of Finland (VTT) and from Tampere University of Technology. The research work strives to gain more in-depth knowledge on the phenomenon of frosting and its impact on corona losses. The correct prediction of frost helps reduce corona losses, while also cutting costs considerably. (orig.)

Simultaneous characterization of elemental segregation and cementite networks in high carbon steel products by spatially-resolved laser-induced breakdown spectroscopy

Energy Technology Data Exchange (ETDEWEB)

Boué-Bigne, Fabienne, E-mail: fabienne.boue-bigne@tatasteel.com

2014-06-01

The reliable characterization of the level of elemental segregation and of the extent of grain-boundary cementite networks in high carbon steel products is a prerequisite for checking product quality, for the purpose of product release to customers, and to investigate the presence of defects that may have led to mechanical property failure of the product. Current methods for the characterization of segregation and cementite networks rely on two different methods of sample etching followed by visual observation, where quality scores are given based on human perception and judgment. With the continuous demand on increasing quality, some of the conventional characterization methods and their associated scoring boards have lost relevance for the precision of characterization that is required today to distinguish between a product that will perform well and one that will not. In order to move away from a qualitative, human perception based situation for the scoring of the severity of segregation and cementite networks, a new method of data evaluation based on spatially-resolved LIBS measurements was developed to provide quantitative and simultaneous characterization of both types of defects. The quantitative assessment of segregation and cementite networks is based on the acquisition of carbon concentration maps. The ability to produce rapid scanning measurements of micro and macro-scale features with adequate spatial resolution makes LIBS the measurement method of preference for this purpose. The characterization of both different defects is extracted simultaneously and from the same carbon concentration map following a series of statistical treatment and data extraction rules. LIBS results were validated against recognized methods and were applied to a significant number of routine samples. The new LIBS method offers a step change improvement in reliability for the characterization of segregation and cementite networks in steel products over the conventional methods

A hybrid framework for reservoir characterization using fuzzy ranking and an artificial neural network

Science.gov (United States)

Wang, Baijie; Wang, Xin; Chen, Zhangxin

2013-08-01

Reservoir characterization refers to the process of quantitatively assigning reservoir properties using all available field data. Artificial neural networks (ANN) have recently been introduced to solve reservoir characterization problems dealing with the complex underlying relationships inherent in well log data. Despite the utility of ANNs, the current limitation is that most existing applications simply focus on directly implementing existing ANN models instead of improving/customizing them to fit the specific reservoir characterization tasks at hand. In this paper, we propose a novel intelligent framework that integrates fuzzy ranking (FR) and multilayer perceptron (MLP) neural networks for reservoir characterization. FR can automatically identify a minimum subset of well log data as neural inputs, and the MLP is trained to learn the complex correlations from the selected well log data to a target reservoir property. FR guarantees the selection of the optimal subset of representative data from the overall well log data set for the characterization of a specific reservoir property; and, this implicitly improves the modeling and predication accuracy of the MLP. In addition, a growing number of industrial agencies are implementing geographic information systems (GIS) in field data management; and, we have designed the GFAR solution (GIS-based FR ANN Reservoir characterization solution) system, which integrates the proposed framework into a GIS system that provides an efficient characterization solution. Three separate petroleum wells from southwestern Alberta, Canada, were used in the presented case study of reservoir porosity characterization. Our experiments demonstrate that our method can generate reliable results.

The LCO Follow-up and Characterization Network and AgentNEO Citizen Science Project

Science.gov (United States)

Lister, Tim; Greenstreet, Sarah; Gomez, Edward; Christensen, Eric J.; Larson, Stephen M.

2017-10-01

The LCO NEO Follow-up Network is using the telescopes of the Las Cumbres Observatory (LCO) and a web-based target selection, scheduling and data reduction system to confirm NEO candidates and characterize radar-targeted known NEOs. Starting in July 2014, the LCO NEO Follow-up Network has observed over 4,500 targets and reported more than 25,000 astrometric and photometric measurements to the Minor Planet Center.The LCO NEO Follow-up Network's main aims are to perform confirming follow-up of the large number of NEO candidates and to perform characterization measurements of radar targets to obtain light curves and rotation rates. The NEO candidates come from the NEO surveys such as Catalina, PanSTARRS, ATLAS, NEOWISE and others. In particular, we are targeting objects in the Southern Hemisphere, where the LCO NEO Follow-up Network is the largest resource for NEO observations.The first phase of the LCO Network comprises nine 1-meter and seven 0.4-meter telescopes at site at McDonald Observatory (Texas), Cerro Tololo (Chile), SAAO (South Africa) and Siding Spring Observatory (Australia). The network has been fully operational since 2014 May, and observations are being executed remotely and robotically. Additional 0.4-meter telescopes will be deployed in 2017 and 2x1-meter telescopes for a site at Ali Observatory, Tibet are planned for 2018-2019.We have developed web-based software called NEOexchange which automatically downloads and aggregates NEO candidates from the Minor Planet Center's NEO Confirmation Page, the Arecibo and Goldstone radar target lists and the NASA lists. NEOexchange allows the planning and scheduling of observations on the LCO Telescope Network and the tracking of the resulting blocks and generated data. We have extended the NEOexchange software to include automated scheduling and moving object detection, with the results presented to the user via the website.We will present results from the LCO NEO Follow-up Network and from the development of the

Improvements in the computation of balances and localization of commercial losses of electric energy in 0.38-kV networks

International Nuclear Information System (INIS)

Vorotnitskii, V. Z.; Zaslonov, S. V.; Lysyuk, S. S.

2006-01-01

An example of four 0.38-kV overhead distribution lines fed from a 10/0.4-kV transformer substation of the Grodno Electrical Networks (Belarus') and supplying electricity to a cottage area is used for analyzing energy balances and commercial losses in the networks. It is shown that the reliability of such analysis can be ensured by the use of modern software and electronic energy meters recording a retrospective of half-hourly intervals of active and reactive electric energy

Characterizing Social Interaction in Tobacco-Oriented Social Networks: An Empirical Analysis.

Science.gov (United States)

Liang, Yunji; Zheng, Xiaolong; Zeng, Daniel Dajun; Zhou, Xingshe; Leischow, Scott James; Chung, Wingyan

2015-06-19

Social media is becoming a new battlefield for tobacco "wars". Evaluating the current situation is very crucial for the advocacy of tobacco control in the age of social media. To reveal the impact of tobacco-related user-generated content, this paper characterizes user interaction and social influence utilizing social network analysis and information theoretic approaches. Our empirical studies demonstrate that the exploding pro-tobacco content has long-lasting effects with more active users and broader influence, and reveal the shortage of social media resources in global tobacco control. It is found that the user interaction in the pro-tobacco group is more active, and user-generated content for tobacco promotion is more successful in obtaining user attention. Furthermore, we construct three tobacco-related social networks and investigate the topological patterns of these tobacco-related social networks. We find that the size of the pro-tobacco network overwhelms the others, which suggests a huge number of users are exposed to the pro-tobacco content. These results indicate that the gap between tobacco promotion and tobacco control is widening and tobacco control may be losing ground to tobacco promotion in social media.

Dynamical Networks Characterization of Geomagnetic Substorms and Transient Response to the Solar Wind State.

Science.gov (United States)

Chapman, S. C.; Dods, J.; Gjerloev, J. W.

2017-12-01

Observations of how the solar wind interacts with earth's magnetosphere, and its dynamical response, are increasingly becoming a data analytics challenge. Constellations of satellites observe the solar corona, the upstream solar wind and throughout earth's magnetosphere. These data are multipoint in space and extended in time, so in principle are ideal for study using dynamical networks to characterize the full time evolving spatial pattern. We focus here on analysis of data from the full set of 100+ auroral ground based magnetometer stations that have been collated by SuperMAG. Spatio-temporal patterns of correlation between the magnetometer time series can be used to form a dynamical network [1]. The properties of the network can then be captured by (time dependent) network parameters. This offers the possibility of characterizing detailed spatio-temporal pattern by a few parameters, so that many events can then be compared [2] with each other. Whilst networks are in widespread use in the data analytics of societal and commercial data, there are additional challenges in their application to physical timeseries. Determining whether two nodes (here, ground based magnetometer stations) are connected in a network (seeing the same dynamics) requires normalization w.r.t. the detailed sensitivities and dynamical responses of specific observing stations and seasonal conductivity variations and we have developed methods to achieve this dynamical normalization. The detailed properties of the network capture time dependent spatial correlation in the magnetometer responses and we will show how this can be used to infer a transient current system response to magnetospheric activity. [l] Dods et al, J. Geophys. Res 120, doi:10.1002/2015JA02 (2015). [2] Dods et al, J. Geophys. Res. 122, doi:10.1002/2016JA02 (2017).

Complex network approach to characterize the statistical features of the sunspot series

International Nuclear Information System (INIS)

Zou, Yong; Liu, Zonghua; Small, Michael; Kurths, Jürgen

2014-01-01

Complex network approaches have been recently developed as an alternative framework to study the statistical features of time-series data. We perform a visibility-graph analysis on both the daily and monthly sunspot series. Based on the data, we propose two ways to construct the network: one is from the original observable measurements and the other is from a negative-inverse-transformed series. The degree distribution of the derived networks for the strong maxima has clear non-Gaussian properties, while the degree distribution for minima is bimodal. The long-term variation of the cycles is reflected by hubs in the network that span relatively large time intervals. Based on standard network structural measures, we propose to characterize the long-term correlations by waiting times between two subsequent events. The persistence range of the solar cycles has been identified over 15–1000 days by a power-law regime with scaling exponent γ = 2.04 of the occurrence time of two subsequent strong minima. In contrast, a persistent trend is not present in the maximal numbers, although maxima do have significant deviations from an exponential form. Our results suggest some new insights for evaluating existing models. (paper)

P2P Network Lending, Loss Given Default and Credit Risks

Directory of Open Access Journals (Sweden)

Guangyou Zhou

2018-03-01

Full Text Available Peer-to-peer (P2P network lending is a new mode of internet finance that still holds credit risk as its main risk. According to the internal rating method of the New Basel Accord, in addition to the probability of default, loss given default is also one of the important indicators of evaluation credit risks. Proceeding from the perspective of loss given default (LGD, this paper conducts an empirical study on the probability distribution of LGDs of P2P as well as its influencing factors with the transaction data of Lending Club. The results show that: (1 the LGDs of P2P loans presents an obvious unimodal distribution, the peak value is relatively high and tends to concentrate with the decrease of the borrower’s credit rating, indicating that the distribution of LGDs of P2P lending is similar to that of unsecured bonds; (2 The total asset of the borrower has no significant impact on LGD, the credit rating and the debt-to-income ratio exert a significant negative impact, while the term and amount of the loan produce a relatively strong positive impact. Therefore, when evaluating the borrower’s repayment ability, it is required to pay more attention to its assets structure rather than the size of its total assets. When carrying out risk control for the P2P platform, it is necessary to give priority to the control of default rate.

Definition and characterization of an extended social-affective default network.

Science.gov (United States)

Amft, Maren; Bzdok, Danilo; Laird, Angela R; Fox, Peter T; Schilbach, Leonhard; Eickhoff, Simon B

2015-03-01

Recent evidence suggests considerable overlap between the default mode network (DMN) and regions involved in social, affective and introspective processes. We considered these overlapping regions as the social-affective part of the DMN. In this study, we established a robust mapping of the underlying brain network formed by these regions and those strongly connected to them (the extended social-affective default network). We first seeded meta-analytic connectivity modeling and resting-state analyses in the meta-analytically defined DMN regions that showed statistical overlap with regions associated with social and affective processing. Consensus connectivity of each seed was subsequently delineated by a conjunction across both connectivity analyses. We then functionally characterized the ensuing regions and performed several cluster analyses. Among the identified regions, the amygdala/hippocampus formed a cluster associated with emotional processes and memory functions. The ventral striatum, anterior cingulum, subgenual cingulum and ventromedial prefrontal cortex formed a heterogeneous subgroup associated with motivation, reward and cognitive modulation of affect. Posterior cingulum/precuneus and dorsomedial prefrontal cortex were associated with mentalizing, self-reference and autobiographic information. The cluster formed by the temporo-parietal junction and anterior middle temporal sulcus/gyrus was associated with language and social cognition. Taken together, the current work highlights a robustly interconnected network that may be central to introspective, socio-affective, that is, self- and other-related mental processes.

Combined effect of CVR and penetration of DG in the voltage profile and losses of lowvoltage secondary distribution networks

Science.gov (United States)

Bokhari, Abdullah

Demarcations between traditional distribution power systems and distributed generation (DG) architectures are increasingly evolving as higher DG penetration is introduced in the system. The concerns in existing electric power systems (EPSs) to accommodate less restrictive interconnection policies while maintaining reliability and performance of power delivery have been the major challenge for DG growth. In this dissertation, the work is aimed to study power quality, energy saving and losses in a low voltage distributed network under various DG penetration cases. Simulation platform suite that includes electric power system, distributed generation and ZIP load models is implemented to determine the impact of DGs on power system steady state performance and the voltage profile of the customers/loads in the network under the voltage reduction events. The investigation designed to test the DG impact on power system starting with one type of DG, then moves on multiple DG types distributed in a random case and realistic/balanced case. The functionality of the proposed DG interconnection is designed to meet the basic requirements imposed by the various interconnection standards, most notably IEEE 1547, public service commission, and local utility regulation. It is found that implementation of DGs on the low voltage secondary network would improve customer's voltage profile, system losses and significantly provide energy savings and economics for utilities. In a network populated with DGs, utility would have a uniform voltage profile at the customers end as the voltage profile becomes more concentrated around targeted voltage level. The study further reinforced the concept that the behavior of DG in distributed network would improve voltage regulation as certain percentage reduction on utility side would ensure uniform percentage reduction seen by all customers and reduce number of voltage violations.

Losses compensation; Compensation des pertes

Energy Technology Data Exchange (ETDEWEB)

NONE

2001-07-01

One mission of RTE (Electric Power Transportation), is to watch over the losses compensation resulting from the power transport on the electric power network. Since january 2001, RTE makes good the electric losses by the purchase of energy. To choose the marketers, a consultation has been realized by RTE. This document presents the rules concerning these losses compensation. (A.L.B.)

MPO-type single-mode multi-fiber connector: Low-loss and high-return-loss intermateability of APC-MPO connectors

Science.gov (United States)

Satake, Toshiaki; Nagasawa, Shinji; Hughes, Mike; Lutz, Sharon

2011-01-01

The electrical communication laboratory of NTT started the research of MT (Mechanically Transferable) connector in early 1980s. The initial goal was to realize a multi-fiber connector which can repeat low loss, stable, reliable and low-cost connections of subscriber optical fiber cable networks for more than 20 years period in the field. We review the multi-fiber alignment design with two guide pins, and following several technical improvements toward the final MT connector used in the commercial telecommunication networks. And then, we review development histories to reach to the low-loss, high-return-loss and reliable APC-MPO (Angled Physical Contact Multi-fiber Push On) connectors introduced in NTT COs and in Verizon's FTTH (Fiber To The Home) networks. In the latter half, we propose the low-loss intermateability design for connectors made by different suppliers in order to enable mass introductions into large scale systems. In addition we also describe an accurate connector loss presumption method for different lots' ferrules based on the MT ferrule dimension data before assembling the connectors. We believe with a wide intermateability of APC-MPO connector will increase its use in the fields. The APC-MPO connector manufactured based on the proposed design had low insertion losses of less than 0.25 dB at the same level of simplex connectors and the higher level of return losses higher than 65 dB.

Communication Network Architectures Based on Ethernet Passive Optical Network for Offshore Wind Power Farms

Directory of Open Access Journals (Sweden)

Mohamed A. Ahmed

2016-03-01

Full Text Available Nowadays, with large-scale offshore wind power farms (WPFs becoming a reality, more efforts are needed to maintain a reliable communication network for WPF monitoring. Deployment topologies, redundancy, and network availability are the main items to enhance the communication reliability between wind turbines (WTs and control centers. Traditional communication networks for monitoring and control (i.e., supervisory control and data acquisition (SCADA systems using switched gigabit Ethernet will not be sufficient for the huge amount of data passing through the network. In this paper, the optical power budget, optical path loss, reliability, and network cost of the proposed Ethernet Passive Optical Network (EPON-based communication network for small-size offshore WPFs have been evaluated for five different network architectures. The proposed network model consists of an optical network unit device (ONU deployed on the WT side for collecting data from different internal networks. All ONUs from different WTs are connected to a central optical line terminal (OLT, placed in the control center. There are no active electronic elements used between the ONUs and the OLT, which reduces the costs and complexity of maintenance and deployment. As fiber access networks without any protection are characterized by poor reliability, three different protection schemes have been configured, explained, and discussed. Considering the cost of network components, the total implementation expense of different architectures with, or without, protection have been calculated and compared. The proposed network model can significantly contribute to the communication network architecture for next generation WPFs.

Brain network characterization of high-risk preterm-born school-age children

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Elda Fischi-Gomez

2016-01-01

Full Text Available Higher risk for long-term cognitive and behavioral impairments is one of the hallmarks of extreme prematurity (EP and pregnancy-associated fetal adverse conditions such as intrauterine growth restriction (IUGR. While neurodevelopmental delay and abnormal brain function occur in the absence of overt brain lesions, these conditions have been recently associated with changes in microstructural brain development. Recent imaging studies indicate changes in brain connectivity, in particular involving the white matter fibers belonging to the cortico-basal ganglia-thalamic loop. Furthermore, EP and IUGR have been related to altered brain network architecture in childhood, with reduced network global capacity, global efficiency and average nodal strength. In this study, we used a connectome analysis to characterize the structural brain networks of these children, with a special focus on their topological organization. On one hand, we confirm the reduced averaged network node degree and strength due to EP and IUGR. On the other, the decomposition of the brain networks in an optimal set of clusters remained substantially different among groups, talking in favor of a different network community structure. However, and despite the different community structure, the brain networks of these high-risk school-age children maintained the typical small-world, rich-club and modularity characteristics in all cases. Thus, our results suggest that brain reorganizes after EP and IUGR, prioritizing a tight modular structure, to maintain the small-world, rich-club and modularity characteristics. By themselves, both extreme prematurity and IUGR bear a similar risk for neurocognitive and behavioral impairment, and the here defined modular network alterations confirm similar structural changes both by IUGR and EP at school age compared to control. Interestingly, the combination of both conditions (IUGR + EP does not result in a worse outcome. In such cases, the alteration

Multivariate correlation analysis technique based on euclidean distance map for network traffic characterization

NARCIS (Netherlands)

Tan, Zhiyuan; Jamdagni, Aruna; He, Xiangjian; Nanda, Priyadarsi; Liu, Ren Ping; Qing, Sihan; Susilo, Willy; Wang, Guilin; Liu, Dongmei

2011-01-01

The quality of feature has significant impact on the performance of detection techniques used for Denial-of-Service (DoS) attack. The features that fail to provide accurate characterization for network traffic records make the techniques suffer from low accuracy in detection. Although researches

Characterization of Schizophrenia Adverse Drug Interactions through a Network Approach and Drug Classification

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Jingchun Sun

2013-01-01

Full Text Available Antipsychotic drugs are medications commonly for schizophrenia (SCZ treatment, which include two groups: typical and atypical. SCZ patients have multiple comorbidities, and the coadministration of drugs is quite common. This may result in adverse drug-drug interactions, which are events that occur when the effect of a drug is altered by the coadministration of another drug. Therefore, it is important to provide a comprehensive view of these interactions for further coadministration improvement. Here, we extracted SCZ drugs and their adverse drug interactions from the DrugBank and compiled a SCZ-specific adverse drug interaction network. This network included 28 SCZ drugs, 241 non-SCZs, and 991 interactions. By integrating the Anatomical Therapeutic Chemical (ATC classification with the network analysis, we characterized those interactions. Our results indicated that SCZ drugs tended to have more adverse drug interactions than other drugs. Furthermore, SCZ typical drugs had significant interactions with drugs of the “alimentary tract and metabolism” category while SCZ atypical drugs had significant interactions with drugs of the categories “nervous system” and “antiinfectives for systemic uses.” This study is the first to characterize the adverse drug interactions in the course of SCZ treatment and might provide useful information for the future SCZ treatment.

Temporal Information Partitioning Networks (TIPNets): Characterizing emergent behavior in complex ecohydrologic systems

Science.gov (United States)

Goodwell, Allison; Kumar, Praveen

2017-04-01

Within an ecosystem, components of the atmosphere, vegetation, and the root-soil system participate in forcing and feedback reactions at varying time scales and intensities. These interactions constitute a complex network that exhibits behavioral shifts due to perturbations ranging from weather events to long-term drought or land use change. However, it is challenging to characterize this shifting network due to multiple drivers, non-linear interactions, and synchronization due to feedback. To overcome these issues, we implement a process network approach where eco-hydrologic time-series variables are nodes and information measures are links. We introduce a Temporal Information Partition Network (TIPNet) framework in which multivariate lagged mutual information between source and target nodes is decomposed into synergistic, redundant, and unique components, each of which reveals different aspects of interactions within the network. We use methods to compute information measures given as few as 200 data points to construct TIPNets based on 1-minute weather station data (radiation Rg, air temperature Ta, wind speed WS, relative humidity RH, precipitation PPT, and leaf wetness LWet) from Central Illinois during the growing season of 2015. We assess temporal shifts in network behavior for various weather conditions and over the growing season. We find that wet time periods are associated with complex and synergistic network structures compared to dry conditions, and that seasonal network patterns reveal responses to vegetation growth and rainfall trends. This framework is applicable to study a broad range of complex systems composed of multiple interacting components, and may aid process understanding, model improvement, and resilience and vulnerability assessments.

Synthesis and characterization of p and n dopable interpenetrating polymer networks for organic photovoltaic devices

International Nuclear Information System (INIS)

Lav, T.X.; Tran-Van, F.; Vidal, F.; Peralta, S.; Chevrot, C.; Teyssie, D.; Grazulevicius, J.V.; Getautis, V.; Derbal, H.; Nunzi, J.-M.

2008-01-01

Interpenetrating polymer networks (IPN) based on carbazole derivatives and diacrylate perylene are synthesized in two steps via an in-situ process. From a spin-coated thin film of a mixture of the two precursors, the diacrylate perylene is first photopolymerized to form a network in the presence of the carbazole derivative which is then electropolymerized to elaborate the IPN. Electrochemical characterizations show that the carbazole and perylene are electroactive inside the film which confirm the p and n dopable properties of the IPN. AFM images of the IPNs show a homogenous and smooth surface, compared to single network, which indicate a high quality of association of each network which should allow an efficient p/n bulk heterojunction

Synthesis and characterization of p and n dopable interpenetrating polymer networks for organic photovoltaic devices

Energy Technology Data Exchange (ETDEWEB)

Lav, T.X. [Laboratoire de Physicochimie des Polymeres et des Interfaces, EA 2528 Universite de Cergy-Pontoise, 5 mail Gay-Lussac, 95031 Cergy-Pontoise Cedex (France); Tran-Van, F. [Laboratoire de Physicochimie des Polymeres et des Interfaces, EA 2528 Universite de Cergy-Pontoise, 5 mail Gay-Lussac, 95031 Cergy-Pontoise Cedex (France)], E-mail: francois.tran-van@u-cergy.fr; Vidal, F.; Peralta, S.; Chevrot, C.; Teyssie, D. [Laboratoire de Physicochimie des Polymeres et des Interfaces, EA 2528 Universite de Cergy-Pontoise, 5 mail Gay-Lussac, 95031 Cergy-Pontoise Cedex (France); Grazulevicius, J.V.; Getautis, V. [Faculty of Chemical Technology, Kaunas University of Technology, Radvilenu Plentas 19, LT 50254 (Lithuania); Derbal, H.; Nunzi, J.-M. [PPF Cellules Solaires Photovoltaiques Plastiques - Laboratoire POMA, UMR-CNRS 6136, Universite d' Angers, 2 bd Lavoisier, 49045 Angers (France)

2008-08-30

Interpenetrating polymer networks (IPN) based on carbazole derivatives and diacrylate perylene are synthesized in two steps via an in-situ process. From a spin-coated thin film of a mixture of the two precursors, the diacrylate perylene is first photopolymerized to form a network in the presence of the carbazole derivative which is then electropolymerized to elaborate the IPN. Electrochemical characterizations show that the carbazole and perylene are electroactive inside the film which confirm the p and n dopable properties of the IPN. AFM images of the IPNs show a homogenous and smooth surface, compared to single network, which indicate a high quality of association of each network which should allow an efficient p/n bulk heterojunction.

Variable Scheduling to Mitigate Channel Losses in Energy-Efficient Body Area Networks

Directory of Open Access Journals (Sweden)

Lavy Libman

2012-11-01

Full Text Available We consider a typical body area network (BAN setting in which sensor nodes send data to a common hub regularly on a TDMA basis, as defined by the emerging IEEE 802.15.6 BAN standard. To reduce transmission losses caused by the highly dynamic nature of the wireless channel around the human body, we explore variable TDMA scheduling techniques that allow the order of transmissions within each TDMA round to be decided on the fly, rather than being fixed in advance. Using a simple Markov model of the wireless links, we devise a number of scheduling algorithms that can be performed by the hub, which aim to maximize the expected number of successful transmissions in a TDMA round, and thereby significantly reduce transmission losses as compared with a static TDMA schedule. Importantly, these algorithms do not require a priori knowledge of the statistical properties of the wireless channels, and the reliability improvement is achieved entirely via shuffling the order of transmissions among devices, and does not involve any additional energy consumption (e.g., retransmissions. We evaluate these algorithms directly on an experimental set of traces obtained from devices strapped to human subjects performing regular daily activities, and confirm that the benefits of the proposed variable scheduling algorithms extend to this practical setup as well.

An efficient approach to characterizing and calculating carrier loss due to heating and barrier height variation in vertical-cavity surface-emitting lasers

International Nuclear Information System (INIS)

Jian, Wu; Summers, H. D.

2010-01-01

It is important to determine quantitatively the internal carrier loss arising from heating and barrier height variation in a vertical-cavity surface-emitting quantum well laser (VCSEL). However, it is generally difficult to realize this goal using purely theoretical formulas due to difficulty in deriving the parameters relating to the quantum well structure. In this paper, we describe an efficient approach to characterizing and calculating the carrier loss due to the heating and the barrier height change in the VCSEL. In the method, the thermal carrier loss mechanism is combined with gain measurement and calculation. The carrier loss is re-characterized in a calculable form by constructing the threshold current and gain detuning-related loss current using the measured gain data and then substituting them for the quantum well-related parameters in the formula. The result can be expressed as a product of an exponential weight factor linked to the barrier height change and the difference between the threshold current and gain detuning-related loss current. The gain variation at cavity frequency due to thermal carrier loss and gain detuning processes is measured by using an AlInGaAs–AlGaAs VCSEL structure. This work provides a useful approach to analysing threshold and loss properties of the VCSEL, particularly, gain offset design for high temperature operation of VCSELs. (classical areas of phenomenology)

Effects of wireless packet loss in industrial process control systems.

Science.gov (United States)

Liu, Yongkang; Candell, Richard; Moayeri, Nader

2017-05-01

Timely and reliable sensing and actuation control are essential in networked control. This depends on not only the precision/quality of the sensors and actuators used but also on how well the communications links between the field instruments and the controller have been designed. Wireless networking offers simple deployment, reconfigurability, scalability, and reduced operational expenditure, and is easier to upgrade than wired solutions. However, the adoption of wireless networking has been slow in industrial process control due to the stochastic and less than 100% reliable nature of wireless communications and lack of a model to evaluate the effects of such communications imperfections on the overall control performance. In this paper, we study how control performance is affected by wireless link quality, which in turn is adversely affected by severe propagation loss in harsh industrial environments, co-channel interference, and unintended interference from other devices. We select the Tennessee Eastman Challenge Model (TE) for our study. A decentralized process control system, first proposed by N. Ricker, is adopted that employs 41 sensors and 12 actuators to manage the production process in the TE plant. We consider the scenario where wireless links are used to periodically transmit essential sensor measurement data, such as pressure, temperature and chemical composition to the controller as well as control commands to manipulate the actuators according to predetermined setpoints. We consider two models for packet loss in the wireless links, namely, an independent and identically distributed (IID) packet loss model and the two-state Gilbert-Elliot (GE) channel model. While the former is a random loss model, the latter can model bursty losses. With each channel model, the performance of the simulated decentralized controller using wireless links is compared with the one using wired links providing instant and 100% reliable communications. The sensitivity of the

Complex Network Analysis for Characterizing Global Value Chains in Equipment Manufacturing

Science.gov (United States)

Meng, Bo; Cheng, Lihong

2017-01-01

The rise of global value chains (GVCs) characterized by the so-called “outsourcing”, “fragmentation production”, and “trade in tasks” has been considered one of the most important phenomena for the 21st century trade. GVCs also can play a decisive role in trade policy making. However, due to the increasing complexity and sophistication of international production networks, especially in the equipment manufacturing industry, conventional trade statistics and the corresponding trade indicators may give us a distorted picture of trade. This paper applies various network analysis tools to the new GVC accounting system proposed by Koopman et al. (2014) and Wang et al. (2013) in which gross exports can be decomposed into value-added terms through various routes along GVCs. This helps to divide the equipment manufacturing-related GVCs into some sub-networks with clear visualization. The empirical results of this paper significantly improve our understanding of the topology of equipment manufacturing-related GVCs as well as the interdependency of countries in these GVCs that is generally invisible from the traditional trade statistics. PMID:28081201

Complex Network Analysis for Characterizing Global Value Chains in Equipment Manufacturing.

Directory of Open Access Journals (Sweden)

Hao Xiao

Full Text Available The rise of global value chains (GVCs characterized by the so-called "outsourcing", "fragmentation production", and "trade in tasks" has been considered one of the most important phenomena for the 21st century trade. GVCs also can play a decisive role in trade policy making. However, due to the increasing complexity and sophistication of international production networks, especially in the equipment manufacturing industry, conventional trade statistics and the corresponding trade indicators may give us a distorted picture of trade. This paper applies various network analysis tools to the new GVC accounting system proposed by Koopman et al. (2014 and Wang et al. (2013 in which gross exports can be decomposed into value-added terms through various routes along GVCs. This helps to divide the equipment manufacturing-related GVCs into some sub-networks with clear visualization. The empirical results of this paper significantly improve our understanding of the topology of equipment manufacturing-related GVCs as well as the interdependency of countries in these GVCs that is generally invisible from the traditional trade statistics.

Complex Network Analysis for Characterizing Global Value Chains in Equipment Manufacturing.

Science.gov (United States)

Xiao, Hao; Sun, Tianyang; Meng, Bo; Cheng, Lihong

2017-01-01

The rise of global value chains (GVCs) characterized by the so-called "outsourcing", "fragmentation production", and "trade in tasks" has been considered one of the most important phenomena for the 21st century trade. GVCs also can play a decisive role in trade policy making. However, due to the increasing complexity and sophistication of international production networks, especially in the equipment manufacturing industry, conventional trade statistics and the corresponding trade indicators may give us a distorted picture of trade. This paper applies various network analysis tools to the new GVC accounting system proposed by Koopman et al. (2014) and Wang et al. (2013) in which gross exports can be decomposed into value-added terms through various routes along GVCs. This helps to divide the equipment manufacturing-related GVCs into some sub-networks with clear visualization. The empirical results of this paper significantly improve our understanding of the topology of equipment manufacturing-related GVCs as well as the interdependency of countries in these GVCs that is generally invisible from the traditional trade statistics.

A Performance Evaluation Model for Mobile Ad Hoc Networks and Sensor Networks

Directory of Open Access Journals (Sweden)

Heng LUO

2014-03-01

Full Text Available Potential applications in areas such as military sites and disaster relief fields that are characterized by absence of prefixed infrastructure justify the development of mobile ad hoc networks (MANETs and wireless sensor networks (WSNs. However, unfavorable wireless links and dynamic topology are still challenging, leading to the proposal of a collection of routing protocols for MANETs and WSNs. Nevertheless the performance of algorithms may vary with deployment scenario due to the application dependent philosophy behind algorithms. In this paper, the performance evaluation problem for MANETs and WSNs is investigated and a novel performance ranking model, termed AHP-SAW, is proposed. For simplicity but without loss of generality, the performance of two routing protocols DSDV and DSR are studies based on which ranking results are provided. Extensive simulations show that an overall 37.2 %, at most, gain may be achieved based on the AHP-SAW model.

Endogenous network states predict gain or loss of functions for genetic mutations in hepatocellular carcinoma.

Science.gov (United States)

Wang, Gaowei; Su, Hang; Yu, Helin; Yuan, Ruoshi; Zhu, Xiaomei; Ao, Ping

2016-02-01

Cancers have been typically characterized by genetic mutations. Patterns of such mutations have traditionally been analysed by posteriori statistical association approaches. One may ponder the possibility of a priori determination of any mutation regularity. Here by exploring biological processes implied in a mechanistic theory recently developed (the endogenous molecular-cellular network theory), we found that the features of genetic mutations in cancers may be predicted without any prior knowledge of mutation propensities. With hepatocellular carcinoma (HCC) as an example, we found that the normal hepatocyte and cancerous hepatocyte can be represented by robust stable states of one single endogenous network. These stable states, specified by distinct patterns of expressions or activities of proteins in the network, provide means to directly identify a set of most probable genetic mutations and their effects in HCC. As the key proteins and main interactions in the network are conserved through cell types in an organism, similar mutational features may also be found in other cancers. This analysis yielded straightforward and testable predictions on accumulated and preferred mutation spectra in normal tissue. The validation of predicted cancer state mutation patterns demonstrates the usefulness and potential of a causal dynamical framework to understand and predict genetic mutations in cancer. © 2016 The Author(s).

Characterizing Social Interaction in Tobacco-Oriented Social Networks: An Empirical Analysis

OpenAIRE

Liang, Yunji; Zheng, Xiaolong; Zeng, Daniel Dajun; Zhou, Xingshe; Leischow, Scott James; Chung, Wingyan

2015-01-01

Social media is becoming a new battlefield for tobacco ?wars?. Evaluating the current situation is very crucial for the advocacy of tobacco control in the age of social media. To reveal the impact of tobacco-related user-generated content, this paper characterizes user interaction and social influence utilizing social network analysis and information theoretic approaches. Our empirical studies demonstrate that the exploding pro-tobacco content has long-lasting effects with more active users a...

The Localized Discovery and Recovery for Query Packet Losses in Wireless Sensor Networks with Distributed Detector Clusters

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Ryu Miura

2013-06-01

Full Text Available An essential application of wireless sensor networks is to successfully respond to user queries. Query packet losses occur in the query dissemination due to wireless communication problems such as interference, multipath fading, packet collisions, etc. The losses of query messages at sensor nodes result in the failure of sensor nodes reporting the requested data. Hence, the reliable and successful dissemination of query messages to sensor nodes is a non-trivial problem. The target of this paper is to enable highly successful query delivery to sensor nodes by localized and energy-efficient discovery, and recovery of query losses. We adopt local and collective cooperation among sensor nodes to increase the success rate of distributed discoveries and recoveries. To enable the scalability in the operations of discoveries and recoveries, we employ a distributed name resolution mechanism at each sensor node to allow sensor nodes to self-detect the correlated queries and query losses, and then efficiently locally respond to the query losses. We prove that the collective discovery of query losses has a high impact on the success of query dissemination and reveal that scalability can be achieved by using the proposed approach. We further study the novel features of the cooperation and competition in the collective recovery at PHY and MAC layers, and show that the appropriate number of detectors can achieve optimal successful recovery rate. We evaluate the proposed approach with both mathematical analyses and computer simulations. The proposed approach enables a high rate of successful delivery of query messages and it results in short route lengths to recover from query losses. The proposed approach is scalable and operates in a fully distributed manner.

Characterization of Genes for Beef Marbling Based on Applying Gene Coexpression Network

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Dajeong Lim

2014-01-01

Full Text Available Marbling is an important trait in characterization beef quality and a major factor for determining the price of beef in the Korean beef market. In particular, marbling is a complex trait and needs a system-level approach for identifying candidate genes related to the trait. To find the candidate gene associated with marbling, we used a weighted gene coexpression network analysis from the expression value of bovine genes. Hub genes were identified; they were topologically centered with large degree and BC values in the global network. We performed gene expression analysis to detect candidate genes in M. longissimus with divergent marbling phenotype (marbling scores 2 to 7 using qRT-PCR. The results demonstrate that transmembrane protein 60 (TMEM60 and dihydropyrimidine dehydrogenase (DPYD are associated with increasing marbling fat. We suggest that the network-based approach in livestock may be an important method for analyzing the complex effects of candidate genes associated with complex traits like marbling or tenderness.

Characterization of the Usage of the Serine Metabolic Network in Human Cancer

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Mahya Mehrmohamadi

2014-11-01

Full Text Available The serine, glycine, one-carbon (SGOC metabolic network is implicated in cancer pathogenesis, but its general functions are unknown. We carried out a computational reconstruction of the SGOC network and then characterized its expression across thousands of cancer tissues. Pathways including methylation and redox metabolism exhibited heterogeneous expression indicating a strong context dependency of their usage in tumors. From an analysis of coexpression, simultaneous up- or downregulation of nucleotide synthesis, NADPH, and glutathione synthesis was found to be a common occurrence in all cancers. Finally, we developed a method to trace the metabolic fate of serine using stable isotopes, high-resolution mass spectrometry, and a mathematical model. Although the expression of single genes didn’t appear indicative of flux, the collective expression of several genes in a given pathway allowed for successful flux prediction. Altogether, these findings identify expansive and heterogeneous functions for the SGOC metabolic network in human cancer.

Statistical Modelling and Characterization of Experimental mm-Wave Indoor Channels for Future 5G Wireless Communication Networks.

Science.gov (United States)

Al-Samman, A M; Rahman, T A; Azmi, M H; Hindia, M N; Khan, I; Hanafi, E

This paper presents an experimental characterization of millimeter-wave (mm-wave) channels in the 6.5 GHz, 10.5 GHz, 15 GHz, 19 GHz, 28 GHz and 38 GHz frequency bands in an indoor corridor environment. More than 4,000 power delay profiles were measured across the bands using an omnidirectional transmitter antenna and a highly directional horn receiver antenna for both co- and cross-polarized antenna configurations. This paper develops a new path-loss model to account for the frequency attenuation with distance, which we term the frequency attenuation (FA) path-loss model and introduce a frequency-dependent attenuation factor. The large-scale path loss was characterized based on both new and well-known path-loss models. A general and less complex method is also proposed to estimate the cross-polarization discrimination (XPD) factor of close-in reference distance with the XPD (CIX) and ABG with the XPD (ABGX) path-loss models to avoid the computational complexity of minimum mean square error (MMSE) approach. Moreover, small-scale parameters such as root mean square (RMS) delay spread, mean excess (MN-EX) delay, dispersion factors and maximum excess (MAX-EX) delay parameters were used to characterize the multipath channel dispersion. Multiple statistical distributions for RMS delay spread were also investigated. The results show that our proposed models are simpler and more physically-based than other well-known models. The path-loss exponents for all studied models are smaller than that of the free-space model by values in the range of 0.1 to 1.4 for all measured frequencies. The RMS delay spread values varied between 0.2 ns and 13.8 ns, and the dispersion factor values were less than 1 for all measured frequencies. The exponential and Weibull probability distribution models best fit the RMS delay spread empirical distribution for all of the measured frequencies in all scenarios.

Sensitivity of the brain to loss aversion during risky gambles.

Science.gov (United States)

Dreher, Jean-Claude

2007-07-01

Little is known about the neural systems that subserve human loss aversion. A recent neuroimaging study by Tom, Poldrack and colleagues reports that this pattern of behaviour is directly tied to the greater sensitivity of the brain to potential losses compared with potential gains and uncovers a brain network whose activity increases with potential gains and decreases with potential losses. These results challenge the common view that loss aversion engages a distinct emotion-related brain network (e.g. amygdala and insula).

Identification and network-enabled characterization of auxin response factor genes in Medicago truncatula

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David J. Burks

2016-12-01

Full Text Available The Auxin Response Factor (ARF family of transcription factors is an important regulator of environmental response and symbiotic nodulation in the legume Medicago truncatula. While previous studies have identified members of this family, a recent spurt in gene expression data coupled with genome update and reannotation calls for a reassessment of the prevalence of ARF genes and their interaction networks in M. truncatula. We performed a comprehensive analysis of the M. truncatula genome and transcriptome that entailed search for novel ARF genes and the co-expression networks. Our investigation revealed 8 novel M. truncatula ARF (MtARF genes, of the total 22 identified, and uncovered novel gene co-expression networks as well. Furthermore, the topological clustering and single enrichment analysis of several network models revealed the roles of individual members of the MtARF family in nitrogen regulation, nodule initiation, and post-embryonic development through a specialized protein packaging and secretory pathway. In summary, this study not just shines new light on an important gene family, but also provides a guideline for identification of new members of gene families and their functional characterization through network analyses.

INTEGRAL INDEX OF OPERATION QUALITY FOR EVALUATION OF IMPACT OF DISTRIBUTIVE GENERATION SOURCES ON ELECTRIC NETWORK MODES

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Petro D. Lezhniuk

2017-06-01

Full Text Available Method of operation quality evaluation of electric network, comprising renewable sources of energy (RSE is considered. Integral index that enables to evaluate the impact of RSE on energy losses and its quality as well as balance reliability in electric network is suggested. Mathematical model is constructed, taking into account the assumption that electric network with RSE may be in various operation modes, characterized by different technical economic indices. To determine the integral index of operation quality of electric network with RSE in all possible states tools of Markov processes theory and criterial method are used.

The effect of mild-to-moderate hearing loss on auditory and emotion processing networks

Science.gov (United States)

Husain, Fatima T.; Carpenter-Thompson, Jake R.; Schmidt, Sara A.

2014-01-01

We investigated the impact of hearing loss (HL) on emotional processing using task- and rest-based functional magnetic resonance imaging. Two age-matched groups of middle-aged participants were recruited: one with bilateral high-frequency HL and a control group with normal hearing (NH). During the task-based portion of the experiment, participants were instructed to rate affective stimuli from the International Affective Digital Sounds (IADS) database as pleasant, unpleasant, or neutral. In the resting state experiment, participants were told to fixate on a “+” sign on a screen for 5 min. The results of both the task-based and resting state studies suggest that NH and HL patients differ in their emotional response. Specifically, in the task-based study, we found slower response to affective but not neutral sounds by the HL group compared to the NH group. This was reflected in the brain activation patterns, with the NH group employing the expected limbic and auditory regions including the left amygdala, left parahippocampus, right middle temporal gyrus and left superior temporal gyrus to a greater extent in processing affective stimuli when compared to the HL group. In the resting state study, we observed no significant differences in connectivity of the auditory network between the groups. In the dorsal attention network (DAN), HL patients exhibited decreased connectivity between seed regions and left insula and left postcentral gyrus compared to controls. The default mode network (DMN) was also altered, showing increased connectivity between seeds and left middle frontal gyrus in the HL group. Further targeted analysis revealed increased intrinsic connectivity between the right middle temporal gyrus and the right precentral gyrus. The results from both studies suggest neuronal reorganization as a consequence of HL, most notably in networks responding to emotional sounds. PMID:24550791

Cell-to-module optical loss/gain analysis for various photovoltaic module materials through systematic characterization

Science.gov (United States)

Hsian Saw, Min; Khoo, Yong Sheng; Singh, Jai Prakash; Wang, Yan

2017-08-01

Reducing levelized cost of electricity (LCOE) is important for solar photovoltaics to compete against other energy sources. Thus, the focus should not only be on improving the solar cell efficiency, but also on continuously reducing the losses (or achieving gain) in the cell-to-module process. This can be achieved by choosing the appropriate module material and design. This paper presents a detailed and systematic characterization of various photovoltaic (PV) module materials (encapsulants, tabbing ribbons, and backsheets) and an evaluation of their impact on the output power of silicon wafer-based PV modules. Various characterization tools/techniques, such as UV-vis (reflectance) measurement, external quantum efficiency (EQE) measurement and EQE line-scan are used. Based on the characterization results, we use module materials with the best-evaluated optical performance to build “optimized modules”. Compared to the standard mini-module, an optical gain of more than 5% is achievable for the “optimized module” with selected module materials.

Allocation of losses in distribution system with dispersed generation of electricity

International Nuclear Information System (INIS)

Atanasovski, Metodija B.

2005-01-01

The problem of allocation of losses in distribution systems with dispersed generation (DG) of electricity is considered in this work. Definition of category DG, overview of technologies which belongs to this category and main features of each technology are given. Modeling of DG in steady state analysis of distribution networks is completely elaborated. Requirements for ideal allocation of losses are summarized. Methods from the literature, for allocation of losses in distribution systems with DG, are elaborated, as: classical distribution pricing method, substitution method, marginal loss coefficients method and nodal factors pricing method. In this work a new method for allocation of losses in distribution systems with DG is also presented. The new method is based on branches and resolves the problems of implementation of branch based methods for transmission networks to distribution networks. The method establishes direct relationship between losses in each branch of the network and injected active and reactive power in the nodes on which path to the root node the branch is placed. Reactive power is considered in the loss allocation process in this method and allocation of crossed terms of active and reactive power is performed using quadratic allocation of crossed terms. DG in this method is treated as negative power injection. It is assumed that the network is radial and the power flow in each branch of the, distribution network is constant and equal to the sum of injected active and reactive power in each node on which path to the root node, the branch is placed. The network is considered loss less. The new proposed method is applied and tested on real distribution network which is a part of Distribution company-Bitola. One distribution feeder of power station 110/10 kV/kV Bitola 4 is considered. Different types of consumers and two small hydro power plants in property of JP Strezevo as typical representatives of DG are connected to the feeder. Results

Reason's Enemy Is Not Emotion: Engagement of Cognitive Control Networks Explains Biases in Gain/Loss Framing

Science.gov (United States)

2017-01-01

In the classic gain/loss framing effect, describing a gamble as a potential gain or loss biases people to make risk-averse or risk-seeking decisions, respectively. The canonical explanation for this effect is that frames differentially modulate emotional processes, which in turn leads to irrational choice behavior. Here, we evaluate the source of framing biases by integrating functional magnetic resonance imaging data from 143 human participants performing a gain/loss framing task with meta-analytic data from >8000 neuroimaging studies. We found that activation during choices consistent with the framing effect were most correlated with activation associated with the resting or default brain, while activation during choices inconsistent with the framing effect was most correlated with the task-engaged brain. Our findings argue against the common interpretation of gain/loss framing as a competition between emotion and control. Instead, our study indicates that this effect results from differential cognitive engagement across decision frames. SIGNIFICANCE STATEMENT The biases frequently exhibited by human decision makers have often been attributed to the presence of emotion. Using a large fMRI sample and analysis of whole-brain networks defined with the meta-analytic tool Neurosynth, we find that neural activity during frame-biased decisions was more significantly associated with default behaviors (and the absence of executive control) than with emotion. These findings point to a role for neuroscience in shaping long-standing psychological theories in decision science. PMID:28264981

Reason's Enemy Is Not Emotion: Engagement of Cognitive Control Networks Explains Biases in Gain/Loss Framing.

Science.gov (United States)

Li, Rosa; Smith, David V; Clithero, John A; Venkatraman, Vinod; Carter, R McKell; Huettel, Scott A

2017-03-29

In the classic gain/loss framing effect, describing a gamble as a potential gain or loss biases people to make risk-averse or risk-seeking decisions, respectively. The canonical explanation for this effect is that frames differentially modulate emotional processes, which in turn leads to irrational choice behavior. Here, we evaluate the source of framing biases by integrating functional magnetic resonance imaging data from 143 human participants performing a gain/loss framing task with meta-analytic data from >8000 neuroimaging studies. We found that activation during choices consistent with the framing effect were most correlated with activation associated with the resting or default brain, while activation during choices inconsistent with the framing effect was most correlated with the task-engaged brain. Our findings argue against the common interpretation of gain/loss framing as a competition between emotion and control. Instead, our study indicates that this effect results from differential cognitive engagement across decision frames. SIGNIFICANCE STATEMENT The biases frequently exhibited by human decision makers have often been attributed to the presence of emotion. Using a large fMRI sample and analysis of whole-brain networks defined with the meta-analytic tool Neurosynth, we find that neural activity during frame-biased decisions was more significantly associated with default behaviors (and the absence of executive control) than with emotion. These findings point to a role for neuroscience in shaping long-standing psychological theories in decision science. Copyright © 2017 the authors 0270-6474/17/373588-11$15.00/0.

Efficient Characterization of Parametric Uncertainty of Complex (Biochemical Networks.

Directory of Open Access Journals (Sweden)

Claudia Schillings

2015-08-01

Full Text Available Parametric uncertainty is a particularly challenging and relevant aspect of systems analysis in domains such as systems biology where, both for inference and for assessing prediction uncertainties, it is essential to characterize the system behavior globally in the parameter space. However, current methods based on local approximations or on Monte-Carlo sampling cope only insufficiently with high-dimensional parameter spaces associated with complex network models. Here, we propose an alternative deterministic methodology that relies on sparse polynomial approximations. We propose a deterministic computational interpolation scheme which identifies most significant expansion coefficients adaptively. We present its performance in kinetic model equations from computational systems biology with several hundred parameters and state variables, leading to numerical approximations of the parametric solution on the entire parameter space. The scheme is based on adaptive Smolyak interpolation of the parametric solution at judiciously and adaptively chosen points in parameter space. As Monte-Carlo sampling, it is "non-intrusive" and well-suited for massively parallel implementation, but affords higher convergence rates. This opens up new avenues for large-scale dynamic network analysis by enabling scaling for many applications, including parameter estimation, uncertainty quantification, and systems design.

Characterization of Energy Availability in RF Energy Harvesting Networks

Directory of Open Access Journals (Sweden)

Daniela Oliveira

2016-01-01

Full Text Available The multiple nodes forming a Radio Frequency (RF Energy Harvesting Network (RF-EHN have the capability of converting received electromagnetic RF signals in energy that can be used to power a network device (the energy harvester. Traditionally the RF signals are provided by high power transmitters (e.g., base stations operating in the neighborhood of the harvesters. Admitting that the transmitters are spatially distributed according to a spatial Poisson process, we start by characterizing the distribution of the RF power received by an energy harvester node. Considering Gamma shadowing and Rayleigh fading, we show that the received RF power can be approximated by the sum of multiple Gamma distributions with different scale and shape parameters. Using the distribution of the received RF power, we derive the probability of a node having enough energy to transmit a packet after a given amount of charging time. The RF power distribution and the probability of a harvester having enough energy to transmit a packet are validated through simulation. The numerical results obtained with the proposed analysis are close to the ones obtained through simulation, which confirms the accuracy of the proposed analysis.

Network Coordinator Report

Science.gov (United States)

Himwich, Ed; Strand, Richard

2013-01-01

This report includes an assessment of the network performance in terms of lost observing time for the 2012 calendar year. Overall, the observing time loss was about 12.3%, which is in-line with previous years. A table of relative incidence of problems with various subsystems is presented. The most significant identified causes of loss were electronics rack problems (accounting for about 21.8% of losses), antenna reliability (18.1%), RFI (11.8%), and receiver problems (11.7%). About 14.2% of the losses occurred for unknown reasons. New antennas are under development in the USA, Germany, and Spain. There are plans for new telescopes in Norway and Sweden. Other activities of the Network Coordinator are summarized.

Cognitive Network Modeling as a Basis for Characterizing Human Communication Dynamics and Belief Contagion in Technology Adoption

Science.gov (United States)

Hutto, Clayton; Briscoe, Erica; Trewhitt, Ethan

2012-01-01

Societal level macro models of social behavior do not sufficiently capture nuances needed to adequately represent the dynamics of person-to-person interactions. Likewise, individual agent level micro models have limited scalability - even minute parameter changes can drastically affect a model's response characteristics. This work presents an approach that uses agent-based modeling to represent detailed intra- and inter-personal interactions, as well as a system dynamics model to integrate societal-level influences via reciprocating functions. A Cognitive Network Model (CNM) is proposed as a method of quantitatively characterizing cognitive mechanisms at the intra-individual level. To capture the rich dynamics of interpersonal communication for the propagation of beliefs and attitudes, a Socio-Cognitive Network Model (SCNM) is presented. The SCNM uses socio-cognitive tie strength to regulate how agents influence--and are influenced by--one another's beliefs during social interactions. We then present experimental results which support the use of this network analytical approach, and we discuss its applicability towards characterizing and understanding human information processing.

Motivation by potential gains and losses affects control processes via different mechanisms in the attentional network.

Science.gov (United States)

Paschke, Lena M; Walter, Henrik; Steimke, Rosa; Ludwig, Vera U; Gaschler, Robert; Schubert, Torsten; Stelzel, Christine

2015-05-01

Attentional control in demanding cognitive tasks can be improved by manipulating the motivational state. Motivation to obtain gains and motivation to avoid losses both usually result in faster reaction times and stronger activation in relevant brain areas such as the prefrontal cortex, but little is known about differences in the underlying neurocognitive mechanisms of these types of motivation in an attentional control context. In the present functional magnetic resonance imaging (fMRI) study, we tested whether potential gain and loss as motivating incentives lead to overlapping or distinct neural effects in the attentional network, and whether one of these conditions is more effective than the other. A Flanker task with word stimuli as targets and distracters was performed by 115 healthy participants. Using a mixed blocked and event-related design allowed us to investigate transient and sustained motivation-related effects. Participants could either gain money (potential gain) or avoid losing money (potential loss) in different task blocks. Participants showed a congruency effect with increased reaction times for incongruent compared to congruent trials. Potential gain led to generally faster responses compared to the neutral condition and to stronger improvements than potential loss. Potential loss also led to shorter response times compared to the neutral condition, but participants improved mainly during incongruent and not during congruent trials. The event-related fMRI data revealed a main effect of congruency with increased activity in the left inferior frontal gyrus (IFG) and inferior frontal junction area (IFJ), the pre-supplementary motor area (pre-SMA), bilateral insula, intraparietal sulcus (IPS) and visual word form area (VWFA). While potential gain led to increased activity in a cluster of the IFJ and the VWFA only during incongruent trials, potential loss was linked to activity increases in these regions during incongruent and congruent trials. The

Transmission Loss Calculation using A and B Loss Coefficients in Dynamic Economic Dispatch Problem

Science.gov (United States)

Jethmalani, C. H. Ram; Dumpa, Poornima; Simon, Sishaj P.; Sundareswaran, K.

2016-04-01

This paper analyzes the performance of A-loss coefficients while evaluating transmission losses in a Dynamic Economic Dispatch (DED) Problem. The performance analysis is carried out by comparing the losses computed using nominal A loss coefficients and nominal B loss coefficients in reference with load flow solution obtained by standard Newton-Raphson (NR) method. Density based clustering method based on connected regions with sufficiently high density (DBSCAN) is employed in identifying the best regions of A and B loss coefficients. Based on the results obtained through cluster analysis, a novel approach in improving the accuracy of network loss calculation is proposed. Here, based on the change in per unit load values between the load intervals, loss coefficients are updated for calculating the transmission losses. The proposed algorithm is tested and validated on IEEE 6 bus system, IEEE 14 bus, system IEEE 30 bus system and IEEE 118 bus system. All simulations are carried out using SCILAB 5.4 (www.scilab.org) which is an open source software.

A Comparative Study of Theoretical Graph Models for Characterizing Structural Networks of Human Brain

Directory of Open Access Journals (Sweden)

Xiaojin Li

2013-01-01

Full Text Available Previous studies have investigated both structural and functional brain networks via graph-theoretical methods. However, there is an important issue that has not been adequately discussed before: what is the optimal theoretical graph model for describing the structural networks of human brain? In this paper, we perform a comparative study to address this problem. Firstly, large-scale cortical regions of interest (ROIs are localized by recently developed and validated brain reference system named Dense Individualized Common Connectivity-based Cortical Landmarks (DICCCOL to address the limitations in the identification of the brain network ROIs in previous studies. Then, we construct structural brain networks based on diffusion tensor imaging (DTI data. Afterwards, the global and local graph properties of the constructed structural brain networks are measured using the state-of-the-art graph analysis algorithms and tools and are further compared with seven popular theoretical graph models. In addition, we compare the topological properties between two graph models, namely, stickiness-index-based model (STICKY and scale-free gene duplication model (SF-GD, that have higher similarity with the real structural brain networks in terms of global and local graph properties. Our experimental results suggest that among the seven theoretical graph models compared in this study, STICKY and SF-GD models have better performances in characterizing the structural human brain network.

Preservation of knowledge through networking with retirees

International Nuclear Information System (INIS)

Barroso, A.C.O.; Reis-Junior, J.S.B.; Monteiro, C.A.; Seary, A

2009-01-01

Loss of emphasis or phasing down of nuclear programs has reduced substantially the hiring of new employees as a result nuclear organizations, in most countries, are experiencing reduction in the workforce and the average age of their technical professionals are around mid fifties. Knowledge management activities with emphasis on knowledge preservation have become a crucial issue for such organizations. This work studied a spontaneous knowledge preservation mechanism at IPEN that could be leveraged and may be replicated in other organizations. Crossing examining publications and human resources data base, with some alias detecting algorithm a large collaboration network involving retirees and current workers of IPEN was unveiled. Using simple indicators and advance techniques of social network analysis the following studies were performed: assessment of the network performance; characterization of its key global properties and detailed structure; characterization and assessment of the role of its key actors; analysis of groups and subgroups patterns; and longitudinal (time evolution) of the network and assessment of its robustness. Rich insights came from this study concerning the value of this mechanism for IPEN and also about the essence of the common interest that constitutes the 'glue' for such mechanism. While more detailed network analysis will still go on for a couple of months, a new phase has already been started with a formulated conceptual model, consisting of four latent variables and thirty six observable ones, to 'explain' at the actor level, in this particular setting what matters when engaging in collaboration. Upon finishing this new phase network data and actors' survey data will be cross correlate to provide a more fully understanding of this amazing mechanism. (author)

Preservation of knowledge through networking with retirees

Energy Technology Data Exchange (ETDEWEB)

Barroso, A.C.O.; Reis-Junior, J.S.B.; Monteiro, C.A. [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)], e-mail: barroso@ipen.br, e-mail: jose.sergio.junior@googlemail.com, e-mail: monteiro@ipen.br; Seary, A [Simon Fraser University School of Comunication, Burnaby, BC (Canada)], e-mail: seary@sfu.ca

2009-07-01

Loss of emphasis or phasing down of nuclear programs has reduced substantially the hiring of new employees as a result nuclear organizations, in most countries, are experiencing reduction in the workforce and the average age of their technical professionals are around mid fifties. Knowledge management activities with emphasis on knowledge preservation have become a crucial issue for such organizations. This work studied a spontaneous knowledge preservation mechanism at IPEN that could be leveraged and may be replicated in other organizations. Crossing examining publications and human resources data base, with some alias detecting algorithm a large collaboration network involving retirees and current workers of IPEN was unveiled. Using simple indicators and advance techniques of social network analysis the following studies were performed: assessment of the network performance; characterization of its key global properties and detailed structure; characterization and assessment of the role of its key actors; analysis of groups and subgroups patterns; and longitudinal (time evolution) of the network and assessment of its robustness. Rich insights came from this study concerning the value of this mechanism for IPEN and also about the essence of the common interest that constitutes the 'glue' for such mechanism. While more detailed network analysis will still go on for a couple of months, a new phase has already been started with a formulated conceptual model, consisting of four latent variables and thirty six observable ones, to 'explain' at the actor level, in this particular setting what matters when engaging in collaboration. Upon finishing this new phase network data and actors' survey data will be cross correlate to provide a more fully understanding of this amazing mechanism. (author)

Improved Safety Margin Characterization of Risk from Loss of Offsite Power

Energy Technology Data Exchange (ETDEWEB)

Nelson, Paul [Texas A & M Univ., College Station, TX (United States)

2017-11-07

Original intent: The original intent of this task was “support of the Risk-Informed Safety Margin Characteristic (RISMC) methodology in order” “to address … efficiency of computation so that more accurate and cost-effective techniques can be used to address safety margin characterizations” (S. M. Hess et al., “Risk-Informed Safety Margin Characterization,” Procs. ICONE17, Brussels, July 2009, CD format). It was intended that “in Task 1 itself this improvement will be directed toward upon the very important issue of Loss of Offsite Power (LOOP) events,” more specifically toward the challenge of efficient computation of the multidimensional nonrecovery integral that has been discussed by many previous contributors to the theory of nuclear safety. It was further envisioned that “three different computational approaches will be explored,” corresponding to the three subtasks listed below; deliverables were tied to the individual subtasks.

Characterizing hydrophobicity of amino acid side chains in a protein environment via measuring contact angle of a water nanodroplet on planar peptide network.

Science.gov (United States)

Zhu, Chongqin; Gao, Yurui; Li, Hui; Meng, Sheng; Li, Lei; Francisco, Joseph S; Zeng, Xiao Cheng

2016-11-15

Hydrophobicity of macroscopic planar surface is conventionally characterized by the contact angle of water droplets. However, this engineering measurement cannot be directly extended to surfaces of proteins, due to the nanometer scale of amino acids and inherent nonplanar structures. To measure the hydrophobicity of side chains of proteins quantitatively, numerous parameters were developed to characterize behavior of hydrophobic solvation. However, consistency among these parameters is not always apparent. Herein, we demonstrate an alternative way of characterizing hydrophobicity of amino acid side chains in a protein environment by constructing a monolayer of amino acids (i.e., artificial planar peptide network) according to the primary and the β-sheet secondary structures of protein so that the conventional engineering measurement of the contact angle of a water droplet can be brought to bear. Using molecular dynamics simulations, contact angles θ of a water nanodroplet on the planar peptide network, together with excess chemical potentials of purely repulsive methane-sized Weeks-Chandler-Andersen solute, are computed. All of the 20 types of amino acids and the corresponding planar peptide networks are studied. Expectedly, all of the planar peptide networks with nonpolar amino acids are hydrophobic due to θ [Formula: see text] 90°, whereas all of the planar peptide networks of the polar and charged amino acids are hydrophilic due to θ [Formula: see text] 90°. Planar peptide networks of the charged amino acids exhibit complete-wetting behavior due to θ [Formula: see text] 0°. This computational approach for characterization of hydrophobicity can be extended to artificial planar networks of other soft matter.

Robustness of weighted networks

Science.gov (United States)

Bellingeri, Michele; Cassi, Davide

2018-01-01

Complex network response to node loss is a central question in different fields of network science because node failure can cause the fragmentation of the network, thus compromising the system functioning. Previous studies considered binary networks where the intensity (weight) of the links is not accounted for, i.e. a link is either present or absent. However, in real-world networks the weights of connections, and thus their importance for network functioning, can be widely different. Here, we analyzed the response of real-world and model networks to node loss accounting for link intensity and the weighted structure of the network. We used both classic binary node properties and network functioning measure, introduced a weighted rank for node importance (node strength), and used a measure for network functioning that accounts for the weight of the links (weighted efficiency). We find that: (i) the efficiency of the attack strategies changed using binary or weighted network functioning measures, both for real-world or model networks; (ii) in some cases, removing nodes according to weighted rank produced the highest damage when functioning was measured by the weighted efficiency; (iii) adopting weighted measure for the network damage changed the efficacy of the attack strategy with respect the binary analyses. Our results show that if the weighted structure of complex networks is not taken into account, this may produce misleading models to forecast the system response to node failure, i.e. consider binary links may not unveil the real damage induced in the system. Last, once weighted measures are introduced, in order to discover the best attack strategy, it is important to analyze the network response to node loss using nodes rank accounting the intensity of the links to the node.

Efficiency Loss of Mixed Equilibrium Associated with Altruistic Users and Logit-based Stochastic Users in Transportation Network

Directory of Open Access Journals (Sweden)

Xiao-Jun Yu

2014-02-01

Full Text Available The efficiency loss of mixed equilibrium associated with two categories of users is investigated in this paper. The first category of users are altruistic users (AU who have the same altruism coefficient and try to minimize their own perceived cost that assumed to be a linear combination of selfish com­ponent and altruistic component. The second category of us­ers are Logit-based stochastic users (LSU who choose the route according to the Logit-based stochastic user equilib­rium (SUE principle. The variational inequality (VI model is used to formulate the mixed route choice behaviours associ­ated with AU and LSU. The efficiency loss caused by the two categories of users is analytically derived and the relations to some network parameters are discussed. The numerical tests validate our analytical results. Our result takes the re­sults in the existing literature as its special cases.

Networking our science to characterize the state, vulnerabilities, and management opportunities of soil organic matter

Science.gov (United States)

Harden, Jennifer W.; Hugelius, Gustaf; Ahlström, Anders; Blankinship, Joseph C.; Bond-Lamberty, Ben; Lawrence, Corey; Loisel, Julie; Malhotra, Avni; Jackson, Robert B.; Ogle, Stephen M.; Phillips, Claire; Ryals, Rebecca; Todd-Brown, Katherine; Vargas, Rodrigo; Vergara, Sintana E.; Cotrufo, M. Francesca; Keiluweit, Marco; Heckman, Katherine; Crow, Susan E.; Silver, Whendee L.; DeLonge, Marcia; Nave, Lucas E.

2018-01-01

Soil organic matter (SOM) supports the Earth's ability to sustain terrestrial ecosystems, provide food and fiber, and retains the largest pool of actively cycling carbon. Over 75% of the soil organic carbon (SOC) in the top meter of soil is directly affected by human land use. Large land areas have lost SOC as a result of land use practices, yet there are compensatory opportunities to enhance productivity and SOC storage in degraded lands through improved management practices. Large areas with and without intentional management are also being subjected to rapid changes in climate, making many SOC stocks vulnerable to losses by decomposition or disturbance. In order to quantify potential SOC losses or sequestration at field, regional, and global scales, measurements for detecting changes in SOC are needed. Such measurements and soil-management best practices should be based on well established and emerging scientific understanding of processes of C stabilization and destabilization over various timescales, soil types, and spatial scales. As newly engaged members of the International Soil Carbon Network, we have identified gaps in data, modeling, and communication that underscore the need for an open, shared network to frame and guide the study of SOM and SOC and their management for sustained production and climate regulation.

Networking our science to characterize the state, vulnerabilities, and management opportunities of soil organic matter

Energy Technology Data Exchange (ETDEWEB)

Harden, Jennifer W. [Stanford Univ., Stanford, CA (United States); U.S. Geological Survey, Menlo Park, CA (United States); Hugelius, Gustaf [Stanford Univ., Stanford, CA (United States); Stockholm Univ., Stockholm (Sweden); Ahlstrom, Anders [Stanford Univ., Stanford, CA (United States); Department of Physical Geography and Ecosystem Science, Lund (Sweden); Blankinship, Joseph C. [Univ. of Arizona, Tucson, AZ (United States); Bond-Lamberty, Ben [Univ. of Maryland, College Park, MD (United States); Lawrence, Corey R. [U.S. Geological Survey, Denver, CO (United States); Loisel, Julie [Texas A & M Univ., College Station, TX (United States); Malhotra, Avni [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Jackson, Robert B. [Stanford Univ., Stanford, CA (United States); Ogle, Stephen [Colorado State Univ., Fort Collins, CO (United States); Phillips, Claire [USDA-ARS Forage Seed and Cereal Research Unit, Corvallis, OR (United States); Ryals, Rebecca [Univ. of Hawai' i at Manoa, Honolulu, HI (United States); Todd-Brown, Katherine [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Vargas, Rodrigo [Univ. of Delaware, Newark, DE (United States); Vergara, Sintana E. [Univ. of California, Berkeley, CA (United States); Cotrufo, M. Francesca [Colorado State Univ., Fort Collins, CO (United States); Keiluweit, Marco [Univ. of Massachusetts, Amherst, MA (United States); Heckman, Katherine A. [USDA Forest Service, Houghton, MI (United States); Crow, Susan E. [Univ. of Hawai' i at Manoa, Honolulu, HI (United States); Silver, Whendee L. [Univ. of California, Berkeley, CA (United States); DeLonge, Marcia [Union of Concerned Scientists, Washington, D.C. (United States); Nave, Lucas E. [Univ. of Michigan, Pellston, MI (United States)

2017-10-05

Here, soil organic matter supports the Earth’s ability to sustain terrestrial ecosystems, provide food and fiber, and retain the largest pool of actively cycling carbon (C). Over 75% of the soil organic carbon (SOC) in the top meter of soil is directly affected by human land use. Large land areas have lost SOC as a result of land use practices, yet there are compensatory opportunities to enhance land productivity and SOC storage in degraded lands through improved management practices. Large areas with and without intentional management are also being subjected to rapid changes in climate, making many SOC stocks vulnerable to losses by decomposition or disturbance. In order to quantify potential SOC losses or sequestration at field, regional, and global scales, measurements for detecting changes in SOC are needed. Such measurements and soil-management best practices should be based on well-established and emerging scientific understanding of processes of C stabilization and destabilization over various timescales, soil types, and spatial scales. As newly engaged members of the International Soil Carbon Network, we have identified gaps in data, modeling, and communication that underscore the need for an open, shared network to frame and guide the study of soil organic matter and C and their management for sustained production and climate regulation.

Improving a Radioisotope Monitoring Network for the Hydrodynamic Characterization of a Karstic Basin

Energy Technology Data Exchange (ETDEWEB)

Peralta Vital, J. L.; Gil Castillo, R.; Fleitas Esteveza, G. [Center of Radiation Protection and Hygiene (CPHR) (Cuba); Moleiro Leon, L. [Environmental Commercial Division (GAMMA) (Cuba); Dapena, C. [Institute of Isotope Geochronology and Geology (INGEIS) (Argentina); Olivera Acosta, J. [Institute of Geodesy and Astronomy (IGA) (Cuba)

2013-07-15

The paper shows the application of geomathematical tools for the design of a radioisotope monitoring network in order to characterize groundwater dynamics in a karstic basin, a very difficult task to acccomplish due to the complex physical, geographical, geologic and hydrogeological characteristics of karstic basins. The sampling frequency of the network has been optimized according to the analysis of the spectrum of variances. In order to evaluate this optimization, the geomathematical model is compared to the results of the mathematical model AQUIMPE. This model solves the flow equation of groundwater using the finite element method. The results validate the design in order to assess aquifer recharge, residence time of groundwater, vulnerability to pollution and groundwater-surface water interaction in this complex water resource. (author)

Wireless Interconnect in Multilayer Chip-Area-Networks for Future Multimaterial High-Speed Systems Design

Directory of Open Access Journals (Sweden)

Oluwole John Famoriji

2017-01-01

Full Text Available Wireless chip area network which enables wireless communication among chips fosters development in wireless communication and it is envisioned that future hardware system and developmental functionality will require multimaterial. However, the traditional system architecture is limited by channel bandwidth-limited interfaces, throughput, delay, and power consumption and as a result limits the efficiency and system performance. Wireless interconnect has been proposed to overcome scalability and performance limitations of multihop wired architectures. Characterization and modeling of channel become more important for specification of choice of modulation or demodulation techniques, channel bandwidths, and other mitigation techniques for channel distortion and interference such as equalization. This paper presents an analytical channel model for characterization, modeling, and analysis of wireless chip-to-chip or interchip interconnects in wireless chip area network with a particular focus on large-scale analysis. The proposed model accounts for both static and dynamic channel losses/attenuation in high-speed systems. Simulation and evaluation of the model with experimental data conducted in a computer desktop casing depict that proposed model matched measurement data very closely. The transmission of EM waves via a medium introduces molecular absorption due to various molecules within the material substance. This model is a representative of channel loss profile in wireless chip-area-network communication and good for future electronic circuits and high-speed systems design.

Evolutionary conservation and network structure characterize genes of phenotypic relevance for mitosis in human.

Directory of Open Access Journals (Sweden)

Marek Ostaszewski

Full Text Available The impact of gene silencing on cellular phenotypes is difficult to establish due to the complexity of interactions in the associated biological processes and pathways. A recent genome-wide RNA knock-down study both identified and phenotypically characterized a set of important genes for the cell cycle in HeLa cells. Here, we combine a molecular interaction network analysis, based on physical and functional protein interactions, in conjunction with evolutionary information, to elucidate the common biological and topological properties of these key genes. Our results show that these genes tend to be conserved with their corresponding protein interactions across several species and are key constituents of the evolutionary conserved molecular interaction network. Moreover, a group of bistable network motifs is found to be conserved within this network, which are likely to influence the network stability and therefore the robustness of cellular functioning. They form a cluster, which displays functional homogeneity and is significantly enriched in genes phenotypically relevant for mitosis. Additional results reveal a relationship between specific cellular processes and the phenotypic outcomes induced by gene silencing. This study introduces new ideas regarding the relationship between genotype and phenotype in the context of the cell cycle. We show that the analysis of molecular interaction networks can result in the identification of genes relevant to cellular processes, which is a promising avenue for future research.

Wide-area remote-sensing system of pollution and gas dispersal by near-infrared absorption based on low-loss optical fiber network

Science.gov (United States)

Inaba, H.

1986-01-01

An all optical remote sensing system utilizing long distance, ultralow loss optical fiber networks is studied and discussed for near infrared absorption measurements of combustible and/or explosive gases such as CH4 and C3H8 in our environment, including experimental results achieved in a diameter more than 20 km. The use of a near infrared wavelength range is emphasized.

Efficient Characterization of Parametric Uncertainty of Complex (Bio)chemical Networks.

Science.gov (United States)

Schillings, Claudia; Sunnåker, Mikael; Stelling, Jörg; Schwab, Christoph

2015-08-01

Parametric uncertainty is a particularly challenging and relevant aspect of systems analysis in domains such as systems biology where, both for inference and for assessing prediction uncertainties, it is essential to characterize the system behavior globally in the parameter space. However, current methods based on local approximations or on Monte-Carlo sampling cope only insufficiently with high-dimensional parameter spaces associated with complex network models. Here, we propose an alternative deterministic methodology that relies on sparse polynomial approximations. We propose a deterministic computational interpolation scheme which identifies most significant expansion coefficients adaptively. We present its performance in kinetic model equations from computational systems biology with several hundred parameters and state variables, leading to numerical approximations of the parametric solution on the entire parameter space. The scheme is based on adaptive Smolyak interpolation of the parametric solution at judiciously and adaptively chosen points in parameter space. As Monte-Carlo sampling, it is "non-intrusive" and well-suited for massively parallel implementation, but affords higher convergence rates. This opens up new avenues for large-scale dynamic network analysis by enabling scaling for many applications, including parameter estimation, uncertainty quantification, and systems design.

E-model MOS Estimate Improvement through Jitter Buffer Packet Loss Modelling

Directory of Open Access Journals (Sweden)

Adrian Kovac

2011-01-01

Full Text Available Proposed article analyses dependence of MOS as a voice call quality (QoS measure estimated through ITU-T E-model under real network conditions with jitter. In this paper, a method of jitter effect is proposed. Jitter as voice packet time uncertainty appears as increased packet loss caused by jitter memory buffer under- or overflow. Jitter buffer behaviour at receiver’s side is modelled as Pareto/D/1/K system with Pareto-distributed packet interarrival times and its performance is experimentally evaluated by using statistic tools. Jitter buffer stochastic model is then incorporated into E-model in an additive manner accounting for network jitter effects via excess packet loss complementing measured network packet loss. Proposed modification of E-model input parameter adds two degrees of freedom in modelling: network jitter and jitter buffer size.

Distribution grid reconfiguration reduces power losses and helps integrate renewables

International Nuclear Information System (INIS)

Lueken, Colleen; Carvalho, Pedro M.S.; Apt, Jay

2012-01-01

A reconfigurable network can change its topology by opening and closing switches on power lines. We use real wind, solar, load, and cost data and a model of a reconfigurable distribution grid to show that reconfiguration allows a grid operator to reduce operational losses as well as to accept more intermittent renewable generation than a static configuration can. Net present value analysis of automated switch technology shows that the return on investment is negative for this test network when considering only loss reduction, but that the investment is attractive under certain conditions when reconfiguration is used to minimize curtailment. - Highlights: ► Reconfiguration may reduce losses in grids with solar or wind distributed generation. ► Reconfigurable networks can accept more solar or wind DG than static ones. ► Using reconfiguration for loss reduction would not create a positive ROI. ► Using reconfiguration to reduce curtailment usually would create a positive ROI.

Holey fibers for low bend loss

Science.gov (United States)

Nakajima, Kazuhide; Saito, Kotaro; Yamada, Yusuke; Kurokawa, Kenji; Shimizu, Tomoya; Fukai, Chisato; Matsui, Takashi

2013-12-01

Bending-loss insensitive fiber (BIF) has proved an essential medium for constructing the current fiber to the home (FTTH) network. By contrast, the progress that has been made on holey fiber (HF) technologies provides us with novel possibilities including non-telecom applications. In this paper, we review recent progress on hole-assisted type BIF. A simple design consideration is overviewed. We then describe some of the properties of HAF including its mechanical reliability. Finally, we introduce some applications of HAF including to high power transmission. We show that HAF with a low bending loss has the potential for use in various future optical technologies as well as in the optical communication network.

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

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

2015-06-01

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

Voltage regulation and power losses reduction in a wind farm integrated MV distribution network

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Fandi, Ghaeth; Igbinovia, Famous Omar; Tlusty, Josef; Mahmoud, Rateb

2018-01-01

A medium-voltage (MV) wind production system is proposed in this paper. The system applies a medium-voltage permanent magnet synchronous generator (PMSG) as well as MV interconnection and distribution networks. The simulation scheme of an existing commercial electric-power system (Case A) and a proposed wind farm with a gearless PMSG insulated gate bipolar transistor (IGBT) power electronics converter scheme (Case B) is compared. The analyses carried out in MATLAB/Simulink environment shows an enhanced voltage profile and reduced power losses, thus, efficiency in installed IGBT power electronics devices in the wind farm. The resulting wind energy transformation scheme is a simple and controllable medium voltage application since it is not restrained by the IGBT power electronics voltage source converter (VSC) arrangement. Active and reactive power control is made possible with the aid of the gearless PMSG IGBT power converters.

Fracture-fault network characterization of pavement imagery of the Whitby Mudstone, Yorkshire

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Boersma, Quinten; Hardebol, Nico; Houben, Maartje; Barnhoorn, Auke; Drury, Martyn

2015-04-01

Natural fractures play an important role in the hydrocarbon production from tight reservoirs. The need for fracture network pathways by fraccing matters particularly for shale gas prospects, due to their micro- to nano-darcies matrix permeabilities. The study of natural fractures from outcrops helps to better understand network connectivity and possibility of reactivating pre-existing planes of weakness, induced by hydraulic stimulation. Microseismicity also show that natural fractures are reactivated during fraccing in tight gas reservoirs and influence the success of the stimulation. An accurate understanding of natural fracture networks can help in predicting the development of fracture networks. In this research we analyze an outcrop analogue, the Whitby Mustone Formation (WMF), in terms of its horizontal fracture network. The WMF is the time equivalent of the Posidonia Shale Formation (PSF), which on itself is the main shale gas prospect in the Dutch subsurface. The fracture network of the WMF is characterized by a system of steep dipping joints with two dominant directions with N-S and E-W strike. The network was digitized from bird-view imagery of the pavement with a spatial extent of ~100 m at sub-cm resolution. The imagery is interpreted in terms of orientation and length distributions, intensity and fractal dimensions. Samples from the field were analyzed for rock strength and sample mineralogy. The results indicate that the fracture networks greatly differ per bed. Observed differences are for example; the geometry of the fracture network, its cumulative length distribution law, the fracture intensity, the fracture length vs its orientation and the fractal dimension. All these parameters greatly influence fracture network connectivity, the probability that longer fractures exist within the pavement and whether the network is more prone to clustering or scattering. Apart from the differences, the networks display a fairly similar orthogonal arrangement

Characterization of interstitial lung disease in chest radiographs using SOM artificial neural network

International Nuclear Information System (INIS)

Azevedo-Marques, P.M. de; Ambrosio, P.E.; Pereira, R.R. Jr.; Valini, R. de A.; Salomao, S.C.

2007-01-01

This paper presents an automated approach to apply a self-organizing map (SOM) artificial neural network (ANN) as a tool for feature extraction and dimensionality reduction to recognize and characterize radiologic patterns of interstitial lung diseases in chest radiography. After feature extraction and dimensionality reduction a multilayer perceptron (MLP) ANN is applied for radiologic patterns classification in normal, linear, nodular or mixed. A leave-one-out methodology was applied for training and test over a database containing 17 samples of linear pattern, 9 samples of nodular pattern, 9 samples of mixed pattern and 18 samples of normal pattern. The MLP network provided an average result of 88.7% of right classification, with 100% of right classification for linear pattern, 55.5% for nodular pattern, 77.7% for mixed pattern and 100% for normal pattern. (orig.)

Visualizing the flow of evidence in network meta-analysis and characterizing mixed treatment comparisons.

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König, Jochem; Krahn, Ulrike; Binder, Harald

2013-12-30

Network meta-analysis techniques allow for pooling evidence from different studies with only partially overlapping designs for getting a broader basis for decision support. The results are network-based effect estimates that take indirect evidence into account for all pairs of treatments. The results critically depend on homogeneity and consistency assumptions, which are sometimes difficult to investigate. To support such evaluation, we propose a display of the flow of evidence and introduce new measures that characterize the structure of a mixed treatment comparison. Specifically, a linear fixed effects model for network meta-analysis is considered, where the network estimates for two treatments are linear combinations of direct effect estimates comparing these or other treatments. The linear coefficients can be seen as the generalization of weights known from classical meta-analysis. We summarize properties of these coefficients and display them as a weighted directed acyclic graph, representing the flow of evidence. Furthermore, measures are introduced that quantify the direct evidence proportion, the mean path length, and the minimal parallelism of mixed treatment comparisons. The graphical display and the measures are illustrated for two published network meta-analyses. In these applications, the proposed methods are seen to render transparent the process of data pooling in mixed treatment comparisons. They can be expected to be more generally useful for guiding and facilitating the validity assessment in network meta-analysis. Copyright © 2013 John Wiley & Sons, Ltd.

Using complex networks to characterize international business cycles.

Science.gov (United States)

Caraiani, Petre

2013-01-01

There is a rapidly expanding literature on the application of complex networks in economics that focused mostly on stock markets. In this paper, we discuss an application of complex networks to study international business cycles. We construct complex networks based on GDP data from two data sets on G7 and OECD economies. Besides the well-known correlation-based networks, we also use a specific tool for presenting causality in economics, the Granger causality. We consider different filtering methods to derive the stationary component of the GDP series for each of the countries in the samples. The networks were found to be sensitive to the detrending method. While the correlation networks provide information on comovement between the national economies, the Granger causality networks can better predict fluctuations in countries' GDP. By using them, we can obtain directed networks allows us to determine the relative influence of different countries on the global economy network. The US appears as the key player for both the G7 and OECD samples. The use of complex networks is valuable for understanding the business cycle comovements at an international level.

Using complex networks to characterize international business cycles.

Directory of Open Access Journals (Sweden)

Petre Caraiani

Full Text Available BACKGROUND: There is a rapidly expanding literature on the application of complex networks in economics that focused mostly on stock markets. In this paper, we discuss an application of complex networks to study international business cycles. METHODOLOGY/PRINCIPAL FINDINGS: We construct complex networks based on GDP data from two data sets on G7 and OECD economies. Besides the well-known correlation-based networks, we also use a specific tool for presenting causality in economics, the Granger causality. We consider different filtering methods to derive the stationary component of the GDP series for each of the countries in the samples. The networks were found to be sensitive to the detrending method. While the correlation networks provide information on comovement between the national economies, the Granger causality networks can better predict fluctuations in countries' GDP. By using them, we can obtain directed networks allows us to determine the relative influence of different countries on the global economy network. The US appears as the key player for both the G7 and OECD samples. CONCLUSION: The use of complex networks is valuable for understanding the business cycle comovements at an international level.

Structural breakdown of specialized plant-herbivore interaction networks in tropical forest edges

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Bruno Ximenes Pinho

2017-10-01

Full Text Available Plant-herbivore relationships are essential for ecosystem functioning, typically forming an ecological network with a compartmentalized (i.e. modular structure characterized by highly specialized interactions. Human disturbances can favor habitat generalist species and thus cause the collapse of this modular structure, but its effects are rarely assessed using a network-based approach. We investigate how edge proximity alters plant-insect herbivore networks by comparing forest edge and interior in a large remnant (3.500 ha of the Brazilian Atlantic forest. Given the typical dominance of pioneer plants and generalist herbivores in edge-affected habitats, we test the hypothesis that the specialized structure of plant-herbivore networks collapse in forest edges, resulting in lower modularity and herbivore specialization. Despite no differences in the number of species and interactions, the network structure presented marked differences between forest edges and interior. Herbivore specialization, modularity and number of modules were significantly higher in forest interior than edge-affected habitats. When compared to a random null model, two (22.2% and eight (88.8% networks were significantly modular in forest edge and interior, respectively. The loss of specificity and modularity in plant-herbivore networks in forest edges may be related to the loss of important functions, such as density-dependent control of superior plant competitors, which is ultimately responsible for the maintenance of biodiversity and ecosystem functions. Our results support previous warnings that focusing on traditional community measures only (e.g. species diversity may overlook important modifications in species interactions and ecosystem functioning.

Comparing flood loss models of different complexity

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Schröter, Kai; Kreibich, Heidi; Vogel, Kristin; Riggelsen, Carsten; Scherbaum, Frank; Merz, Bruno

2013-04-01

Any deliberation on flood risk requires the consideration of potential flood losses. In particular, reliable flood loss models are needed to evaluate cost-effectiveness of mitigation measures, to assess vulnerability, for comparative risk analysis and financial appraisal during and after floods. In recent years, considerable improvements have been made both concerning the data basis and the methodological approaches used for the development of flood loss models. Despite of that, flood loss models remain an important source of uncertainty. Likewise the temporal and spatial transferability of flood loss models is still limited. This contribution investigates the predictive capability of different flood loss models in a split sample cross regional validation approach. For this purpose, flood loss models of different complexity, i.e. based on different numbers of explaining variables, are learned from a set of damage records that was obtained from a survey after the Elbe flood in 2002. The validation of model predictions is carried out for different flood events in the Elbe and Danube river basins in 2002, 2005 and 2006 for which damage records are available from surveys after the flood events. The models investigated are a stage-damage model, the rule based model FLEMOps+r as well as novel model approaches which are derived using data mining techniques of regression trees and Bayesian networks. The Bayesian network approach to flood loss modelling provides attractive additional information concerning the probability distribution of both model predictions and explaining variables.

Comprehensive characterization of lncRNA-mRNA related ceRNA network across 12 major cancers

Science.gov (United States)

Feng, Li; Li, Feng; Sun, Zeguo; Wu, Tan; Shi, Xinrui; Li, Jing; Li, Xia

2016-01-01

Recent studies indicate that long noncoding RNAs (lncRNAs) can act as competing endogenous RNAs (ceRNAs) to indirectly regulate mRNAs through shared microRNAs, which represents a novel layer of RNA crosstalk and plays critical roles in the development of tumor. However, the global regulation landscape and characterization of these lncRNA related ceRNA crosstalk in cancers is still largely unknown. Here, we systematically characterized the lncRNA related ceRNA interactions across 12 major cancers and the normal physiological states by integrating multidimensional molecule profiles of more than 5000 samples. Our study suggest the large difference of ceRNA regulation between normal and tumor states and the higher similarity across similar tissue origin of tumors. The ceRNA related molecules have more conserved features in tumor networks and they play critical roles in both the normal and tumorigenesis processes. Besides, lncRNAs in the pan-cancer ceRNA network may be potential biomarkers of tumor. By exploring hub lncRNAs, we found that these conserved key lncRNAs dominate variable tumor hallmark processes across pan-cancers. Network dynamic analysis highlights the critical roles of ceRNA regulation in tumorigenesis. By analyzing conserved ceRNA interactions, we found that miRNA mediate ceRNA regulation showed different patterns across pan-cancer; while analyzing the cancer specific ceRNA interactions reveal that lncRNAs synergistically regulated tumor driver genes of cancer hallmarks. Finally, we found that ceRNA modules have the potential to predict patient survival. Overall, our study systematically dissected the lncRNA related ceRNA networks in pan-cancer that shed new light on understanding the molecular mechanism of tumorigenesis. PMID:27580177

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

Science.gov (United States)

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

2014-03-01

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

Distress Propagation in Complex Networks: The Case of Non-Linear DebtRank.

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Marco Bardoscia

Full Text Available We consider a dynamical model of distress propagation on complex networks, which we apply to the study of financial contagion in networks of banks connected to each other by direct exposures. The model that we consider is an extension of the DebtRank algorithm, recently introduced in the literature. The mechanics of distress propagation is very simple: When a bank suffers a loss, distress propagates to its creditors, who in turn suffer losses, and so on. The original DebtRank assumes that losses are propagated linearly between connected banks. Here we relax this assumption and introduce a one-parameter family of non-linear propagation functions. As a case study, we apply this algorithm to a data-set of 183 European banks, and we study how the stability of the system depends on the non-linearity parameter under different stress-test scenarios. We find that the system is characterized by a transition between a regime where small shocks can be amplified and a regime where shocks do not propagate, and that the overall stability of the system increases between 2008 and 2013.

Energy network dispatch optimization under emergency of local energy shortage

International Nuclear Information System (INIS)

Cai, Tianxing; Zhao, Chuanyu; Xu, Qiang

2012-01-01

The consequence of short-time energy shortage under extreme conditions, such as earthquake, tsunami, and hurricane, may cause local areas to suffer from delayed rescues, widespread power outages, tremendous economic losses, and even public safety threats. In such urgent events of local energy shortage, agile energy dispatching through an effective energy transportation network, targeting the minimum energy recovery time, should be a top priority. In this paper, a novel methodology is developed for energy network dispatch optimization under emergency of local energy shortage, which includes four stages of work. First, emergency-area-centered energy network needs to be characterized, where the capacity, quantity, and availability of various energy sources are determined. Second, the energy initial situation under emergency conditions needs to be identified. Then, the energy dispatch optimization is conducted based on a developed MILP (mixed-integer linear programming) model in the third stage. Finally, the sensitivity of the minimum dispatch time with respect to uncertainty parameters is characterized by partitioning the entire space of uncertainty parameters into multiple subspaces. The efficacy of the developed methodology is demonstrated via a case study with in-depth discussions. -- Highlights: ► Address the energy network dispatch problem under emergency of local energy shortage. ► Minimize the energy restoration time for the entire energy network under emergency events. ► Develop a new MILP model and a sensitivity analysis method with respect to uncertainties.

Computational simulations of frictional losses in pipe networks confirmed in experimental apparatusses designed by honors students

Science.gov (United States)

Pohlman, Nicholas A.; Hynes, Eric; Kutz, April

2015-11-01

Lectures in introductory fluid mechanics at NIU are a combination of students with standard enrollment and students seeking honors credit for an enriching experience. Most honors students dread the additional homework problems or an extra paper assigned by the instructor. During the past three years, honors students of my class have instead collaborated to design wet-lab experiments for their peers to predict variable volume flow rates of open reservoirs driven by gravity. Rather than learn extra, the honors students learn the Bernoulli head-loss equation earlier to design appropriate systems for an experimental wet lab. Prior designs incorporated minor loss features such as sudden contraction or multiple unions and valves. The honors students from Spring 2015 expanded the repertoire of available options by developing large scale set-ups with multiple pipe networks that could be combined together to test the flexibility of the student team's computational programs. The engagement of bridging the theory with practice was appreciated by all of the students such that multiple teams were able to predict performance within 4% accuracy. The challenges, schedules, and cost estimates of incorporating the experimental lab into an introductory fluid mechanics course will be reported.

The correlation of metrics in complex networks with applications in functional brain networks

International Nuclear Information System (INIS)

Li, C; Wang, H; Van Mieghem, P; De Haan, W; Stam, C J

2011-01-01

An increasing number of network metrics have been applied in network analysis. If metric relations were known better, we could more effectively characterize networks by a small set of metrics to discover the association between network properties/metrics and network functioning. In this paper, we investigate the linear correlation coefficients between widely studied network metrics in three network models (Bárabasi–Albert graphs, Erdös–Rényi random graphs and Watts–Strogatz small-world graphs) as well as in functional brain networks of healthy subjects. The metric correlations, which we have observed and theoretically explained, motivate us to propose a small representative set of metrics by including only one metric from each subset of mutually strongly dependent metrics. The following contributions are considered important. (a) A network with a given degree distribution can indeed be characterized by a small representative set of metrics. (b) Unweighted networks, which are obtained from weighted functional brain networks with a fixed threshold, and Erdös–Rényi random graphs follow a similar degree distribution. Moreover, their metric correlations and the resultant representative metrics are similar as well. This verifies the influence of degree distribution on metric correlations. (c) Most metric correlations can be explained analytically. (d) Interestingly, the most studied metrics so far, the average shortest path length and the clustering coefficient, are strongly correlated and, thus, redundant. Whereas spectral metrics, though only studied recently in the context of complex networks, seem to be essential in network characterizations. This representative set of metrics tends to both sufficiently and effectively characterize networks with a given degree distribution. In the study of a specific network, however, we have to at least consider the representative set so that important network properties will not be neglected

Characterization of Early Cortical Neural Network ...

Science.gov (United States)

We examined the development of neural network activity using microelectrode array (MEA) recordings made in multi-well MEA plates (mwMEAs) over the first 12 days in vitro (DIV). In primary cortical cultures made from postnatal rats, action potential spiking activity was essentially absent on DIV 2 and developed rapidly between DIV 5 and 12. Spiking activity was primarily sporadic and unorganized at early DIV, and became progressively more organized with time in culture, with bursting parameters, synchrony and network bursting increasing between DIV 5 and 12. We selected 12 features to describe network activity and principal components analysis using these features demonstrated a general segregation of data by age at both the well and plate levels. Using a combination of random forest classifiers and Support Vector Machines, we demonstrated that 4 features (CV of within burst ISI, CV of IBI, network spike rate and burst rate) were sufficient to predict the age (either DIV 5, 7, 9 or 12) of each well recording with >65% accuracy. When restricting the classification problem to a binary decision, we found that classification improved dramatically, e.g. 95% accuracy for discriminating DIV 5 vs DIV 12 wells. Further, we present a novel resampling approach to determine the number of wells that might be needed for conducting comparisons of different treatments using mwMEA plates. Overall, these results demonstrate that network development on mwMEA plates is similar to

Macrocell path loss prediction using artificial intelligence techniques

Science.gov (United States)

Usman, Abraham U.; Okereke, Okpo U.; Omizegba, Elijah E.

2014-04-01

The prediction of propagation loss is a practical non-linear function approximation problem which linear regression or auto-regression models are limited in their ability to handle. However, some computational Intelligence techniques such as artificial neural networks (ANNs) and adaptive neuro-fuzzy inference systems (ANFISs) have been shown to have great ability to handle non-linear function approximation and prediction problems. In this study, the multiple layer perceptron neural network (MLP-NN), radial basis function neural network (RBF-NN) and an ANFIS network were trained using actual signal strength measurement taken at certain suburban areas of Bauchi metropolis, Nigeria. The trained networks were then used to predict propagation losses at the stated areas under differing conditions. The predictions were compared with the prediction accuracy of the popular Hata model. It was observed that ANFIS model gave a better fit in all cases having higher R2 values in each case and on average is more robust than MLP and RBF models as it generalises better to a different data.

Optimizing Low Speed VoIP Network for Rural Next Generation Network (R-NGN

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Yoanes Bandung

2007-11-01

Full Text Available In this research, we propose an optimization method based-on E-Model for designing an efficient low speed VoIP network for Rural Next Generation Network (R-NGN. We are choosing 128 kbps and 256 kbps bandwidth as the typical community link to be used in the designing of R-NGN infrastructure. The method is based on selection of some VoIP network parameters such as voice coder, communication protocol, packet loss level, network utilization and resource allocation. We draw analytic approach for achieving rating value (R of E-model that represent level of quality of service. In this approach, we focus on delay and packet loss calculation to find the rating value. We state the rating value = 70 as minimum level of quality of service for each call, equivalent to 3.6 of Mean Opinion Score (MOS. In our experiments, either G.723.1 5.3 kbps or G.729 is chosen for maximizing the number of VoIP calls, it depends on link utilization and level of packet loss.

Graph theoretical analysis and application of fMRI-based brain network in Alzheimer's disease

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LIU Xue-na

2012-08-01

Full Text Available Alzheimer's disease (AD, a progressive neurodegenerative disease, is clinically characterized by impaired memory and many other cognitive functions. However, the pathophysiological mechanisms underlying the disease are not thoroughly understood. In recent years, using functional magnetic resonance imaging (fMRI as well as advanced graph theory based network analysis approach, several studies of patients with AD suggested abnormal topological organization in both global and regional properties of functional brain networks, specifically, as demonstrated by a loss of small-world network characteristics. These studies provide novel insights into the pathophysiological mechanisms of AD and could be helpful in developing imaging biomarkers for disease diagnosis. In this paper we introduce the essential concepts of complex brain networks theory, and review recent advances of the study on human functional brain networks in AD, especially focusing on the graph theoretical analysis of small-world network based on fMRI. We also propound the existent problems and research orientation.

Motif distributions in phase-space networks for characterizing experimental two-phase flow patterns with chaotic features.

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Gao, Zhong-Ke; Jin, Ning-De; Wang, Wen-Xu; Lai, Ying-Cheng

2010-07-01

The dynamics of two-phase flows have been a challenging problem in nonlinear dynamics and fluid mechanics. We propose a method to characterize and distinguish patterns from inclined water-oil flow experiments based on the concept of network motifs that have found great usage in network science and systems biology. In particular, we construct from measured time series phase-space complex networks and then calculate the distribution of a set of distinct network motifs. To gain insight, we first test the approach using time series from classical chaotic systems and find a universal feature: motif distributions from different chaotic systems are generally highly heterogeneous. Our main finding is that the distributions from experimental two-phase flows tend to be heterogeneous as well, suggesting the underlying chaotic nature of the flow patterns. Calculation of the maximal Lyapunov exponent provides further support for this. Motif distributions can thus be a feasible tool to understand the dynamics of realistic two-phase flow patterns.

Dynamic Pathloss Model for Future Mobile Communication Networks

DEFF Research Database (Denmark)

Kumar, Ambuj; Mihovska, Albena Dimitrova; Prasad, Ramjee

2016-01-01

that are essentially static. Therefore, once the signal level drops beyond the predicted values due to any variance in the environmental conditions, very crowded areas may not be catered well enough by the deployed network that had been designed with the static path loss model. This paper proposes an approach......— Future mobile communication networks (MCNs) are expected to be more intelligent and proactive based on new capabilities that increase agility and performance. However, for any successful mobile network service, the dexterity in network deployment is a key factor. The efficiency of the network...... planning depends on how congruent the chosen path loss model and real propagation are. Various path loss models have been developed that predict the signal propagation in various morphological and climatic environments; however they consider only those physical parameters of the network environment...

Altered Brain Network in Amyotrophic Lateral Sclerosis: A Resting Graph Theory-Based Network Study at Voxel-Wise Level.

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Zhou, Chaoyang; Hu, Xiaofei; Hu, Jun; Liang, Minglong; Yin, Xuntao; Chen, Lin; Zhang, Jiuquan; Wang, Jian

2016-01-01

Amyotrophic lateral sclerosis (ALS) is a rare degenerative disorder characterized by loss of upper and lower motor neurons. Neuroimaging has provided noticeable evidence that ALS is a complex disease, and shown that anatomical and functional lesions extend beyond precentral cortices and corticospinal tracts, to include the corpus callosum; frontal, sensory, and premotor cortices; thalamus; and midbrain. The aim of this study is to investigate graph theory-based functional network abnormalities at voxel-wise level in ALS patients on a whole brain scale. Forty-three ALS patients and 44 age- and sex-matched healthy volunteers were enrolled. The voxel-wise network degree centrality (DC), a commonly employed graph-based measure of network organization, was used to characterize the alteration of whole brain functional network. Compared with the controls, the ALS patients showed significant increase of DC in the left cerebellum posterior lobes, bilateral cerebellum crus, bilateral occipital poles, right orbital frontal lobe, and bilateral prefrontal lobes; significant decrease of DC in the bilateral primary motor cortex, bilateral sensory motor region, right prefrontal lobe, left bilateral precuneus, bilateral lateral temporal lobes, left cingulate cortex, and bilateral visual processing cortex. The DC's z-scores of right inferior occipital gyrus were significant negative correlated with the ALSFRS-r scores. Our findings confirm that the regions with abnormal network DC in ALS patients were located in multiple brain regions including primary motor, somatosensory and extra-motor areas, supporting the concept that ALS is a multisystem disorder. Specifically, our study found that DC in the visual areas was altered and ALS patients with higher DC in right inferior occipital gyrus have more severity of disease. The result demonstrated that the altered DC value in this region can probably be used to assess severity of ALS.

Altered brain network in Amyotrophic Lateral Sclerosis: a resting graph theory-based network study at voxel-wise level

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Chaoyang eZhou

2016-05-01

Full Text Available Amyotrophic lateral sclerosis (ALS is a rare degenerative disorder characterized by loss of upper and lower motor neurons. Neuroimaging has provided noticeable evidence that ALS is a complex disease, and shown that anatomical and functional lesions extend beyond precentral cortices and corticospinal tracts, to include the corpus callosum; frontal, sensory, and premotor cortices; thalamus; and midbrain. The aim of this study is to investigate graph theory-based functional network abnormalities at voxel-wise level in ALS patients on a whole brain scale. Forty-three ALS patients and 44 age- and sex- matched healthy volunteers were enrolled. The voxel-wise network degree centrality (DC, a commonly employed graph-based measure of network organization, was used to characterize the alteration of whole brain functional network. Compared with the controls, the ALS patients showed significant increase of DC in the left cerebellum posterior lobes, bilateral cerebellum crus, bilateral occipital poles, right orbital frontal lobe and bilateral prefrontal lobes; significant decrease of DC in the bilateral primary motor cortex, bilateral sensory motor region, right prefrontal lobe, left bilateral precuneus, bilateral lateral temporal lobes, left cingulate cortex, and bilateral visual processing cortex. The DC’s z-scores of right inferior occipital gyrus were significant negative correlated with the ALSFRS-r scores. Our findings confirm that the regions with abnormal network DC in ALS patients were located in multiple brain regions including primary motor, somatosensory and extra-motor areas, supporting the concept that ALS is a multisystem disorder. Specifically, our study found that DC in the visual areas was altered and ALS patients with higher DC in right inferior occipital gyrus have more severity of disease. The result demonstrated that the altered DC value in this region can probably be used to assess severity of ALS.

Self-discharge analysis and characterization of supercapacitors for environmentally powered wireless sensor network applications

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Yang, Hengzhao; Zhang, Ying

2011-10-01

A new approach is presented to characterize the variable leakage resistance, a parameter in the variable leakage resistance model we developed to model supercapacitors used in environmentally powered wireless sensor network applications. Based on an analysis of the supercapacitor terminal behavior during the self-discharge, the variable leakage resistance is modeled as a function of the supercapacitor terminal voltage instead of the self-discharge time, which is more practical for an environmentally powered wireless sensor node. The new characterization approach is implemented and validated using MATLAB Simulink with a 10 F supercapacitor as an example. In addition, effects of initial voltages and temperatures on the supercapacitor self-discharge rate and the variable leakage resistance value are explored.

Natural and Synthetic Biohydrogels Design, Characterization, Network Structure Imaging and Modeling

Science.gov (United States)

Marmorat, Clement

Biocompatible hydrogels can be derived from materials that are naturally obtained, such as proteins or polysaccharides, or synthetic, such as poloxamers. In order to be classified as biocompatible, these water-swollen networks can not trigger a toxic response once introduced into a biological or physiological environment and, therefore, must be immunoneutral. Hyaluronic acid hydrogels can be great candidates for tissue engineering applications as long as the cross-linking chemistry and process does not affect the biocompatibility of the natural protein matrix. Thermoreversible hydrogels have the advantage of undergoing a sol/gel phase transition at specific temperatures. Thus, they are excellent candidates for biomedical applications such as drug delivery systems, wound healing coatings or cellular scaffolds. Although these hydrogels can be used in their natural form without further modification or chemical alteration, the original protein or polymer matrix is often strengthened by the use of a crosslinking agent to achieve a specific set of properties. In the case of gelatin fibril formation at low temperatures or the micellization of triblock copolymers in solution with temperature increase, the natural phase transition is modified when crosslinkers are introduced to alter the biohydrogels properties and, ultimately, disturb the system's equilibrium. By using spectroscopy techniques, rheology and cryo-imaging we investigated several biocompatible polymeric networks in their natural form as well as their engineered structures to better understand the mechanisms of gelation and artificial internal re-organization of the networks. Natural and synthetic biohydrogels were designed and their mechanical properties were characterized before imaging. Models that better describe the relationship between network configuration and resulting mechanical properties showed great agreement with experimental mesh size observations. Finally, a novel set of hybrid gels was developed

Identification of important nodes in directed biological networks: a network motif approach.

Directory of Open Access Journals (Sweden)

Pei Wang

Full Text Available Identification of important nodes in complex networks has attracted an increasing attention over the last decade. Various measures have been proposed to characterize the importance of nodes in complex networks, such as the degree, betweenness and PageRank. Different measures consider different aspects of complex networks. Although there are numerous results reported on undirected complex networks, few results have been reported on directed biological networks. Based on network motifs and principal component analysis (PCA, this paper aims at introducing a new measure to characterize node importance in directed biological networks. Investigations on five real-world biological networks indicate that the proposed method can robustly identify actually important nodes in different networks, such as finding command interneurons, global regulators and non-hub but evolutionary conserved actually important nodes in biological networks. Receiver Operating Characteristic (ROC curves for the five networks indicate remarkable prediction accuracy of the proposed measure. The proposed index provides an alternative complex network metric. Potential implications of the related investigations include identifying network control and regulation targets, biological networks modeling and analysis, as well as networked medicine.

Fractal network dimension and viscoelastic powerlaw behavior: II. An experimental study of structure-mimicking phantoms by magnetic resonance elastography

International Nuclear Information System (INIS)

Guo Jing; Posnansky, Oleg; Hirsch, Sebastian; Scheel, Michael; Taupitz, Matthias; Sack, Ingolf; Braun, Juergen

2012-01-01

The dynamics of the complex shear modulus, G*, of soft biological tissue is governed by the rigidity and topology of multiscale mechanical networks. Multifrequency elastography can measure the frequency dependence of G* in soft biological tissue, providing information about the structure of tissue networks at multiple scales. In this study, the viscoelastic properties of structure-mimicking phantoms containing tangled paper stripes embedded in agarose gel are investigated by multifrequency magnetic resonance elastography within the dynamic range of 40–120 Hz. The effective media viscoelastic properties are analyzed in terms of the storage modulus (the real part of G*), the loss modulus (the imaginary part of G*) and the viscoelastic powerlaw given by the two-parameter springpot model. Furthermore, diffusion tensor imaging is used for investigating the effect of network structures on water mobility. The following observations were made: the random paper networks with fractal dimensions between 2.481 and 2.755 had no or minor effects on the storage modulus, whereas the loss modulus was significantly increased about 2.2 kPa per fractal dimension unit (R = 0.962, P < 0.01). This structural sensitivity of the loss modulus was significantly correlated with the springpot powerlaw exponent (0.965, P < 0.01), while for the springpot elasticity modulus, a trend was discernable (0.895, P < 0.05). No effect of the paper network on water diffusion was observed. The gel phantoms with embedded paper stripes presented here are a feasible way for experimentally studying the effect of network topology on soft-tissue viscoelastic parameters. In the dynamic range of in vivo elastography, the fractal network dimension primarily correlates to the loss behavior of soft tissue as can be seen from the loss modulus or the powerlaw exponent of the springpot model. These findings represent the experimental underpinning of structure-sensitive elastography for an improved characterization of

Characterizing and predicting the robustness of power-law networks

International Nuclear Information System (INIS)

LaRocca, Sarah; Guikema, Seth D.

2015-01-01

Power-law networks such as the Internet, terrorist cells, species relationships, and cellular metabolic interactions are susceptible to node failures, yet maintaining network connectivity is essential for network functionality. Disconnection of the network leads to fragmentation and, in some cases, collapse of the underlying system. However, the influences of the topology of networks on their ability to withstand node failures are poorly understood. Based on a study of the response of 2000 randomly-generated power-law networks to node failures, we find that networks with higher nodal degree and clustering coefficient, lower betweenness centrality, and lower variability in path length and clustering coefficient maintain their cohesion better during such events. We also find that network robustness, i.e., the ability to withstand node failures, can be accurately predicted a priori for power-law networks across many fields. These results provide a basis for designing new, more robust networks, improving the robustness of existing networks such as the Internet and cellular metabolic pathways, and efficiently degrading networks such as terrorist cells. - Highlights: • Examine relationship between network topology and robustness to failures. • Relationship is statistically significant for scale-free networks. • Use statistical models to estimate robustness to failures for real-world networks

Study of a Modified AC Bridge Technique for Loss Angle Measurement of a Dielectric Material

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S. C. BERA

2008-09-01

Full Text Available A Wheatstone’s bridge network like Schering Bridge, DeSauty Bridge etc measures the loss angle or tangent of loss angle (tanδ of a dielectric material. In high voltage application this loss angle is generally measured by high voltage Schering Bridge. But continuous measurement of tan δ is not possible by these techniques. In the present paper a modified operational amplifiers based Schering Bridge network has been proposed for continuous measurement of tanδ in the form of a bridge network output voltage. Mathematical analysis of the proposed bridge network has been discussed in the paper and experimental work has been performed assuming the lossy dielectric material as a series combination of loss less capacitor and a resistor. Experimental results are reported in the paper. From the mathematical analysis and experimental results it is found that the output of the proposed bridge network is almost linearly related with tanδ.

Power system reconfiguration in a radial distribution network for reducing losses and to improve voltage profile using modified plant growth simulation algorithm with Distributed Generation (DG

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R. Rajaram

2015-11-01

Full Text Available Network reconfiguration which is constrained non linear optimization problem has been solved for loss minimization, load balancing, etc. for last two decades using various heuristic search evolutionary algorithms like binary particle swarm optimization, neuro-fuzzy techniques, etc. The contribution of this paper lies in considering distributed generation which are smaller power sources like solar photovoltaic cells or wind turbines connected in the customer roof top. This new connection in the radial network has made unidirectional current flow to become bidirectional there by increasing the efficiency but sometimes reducing stability of the system. Modified plant growth simulation algorithm has been applied here successfully to minimize real power loss because it does not require barrier factors or cross over rates because the objectives and constraints are dealt separately. The main advantage of this algorithm is continuous guiding search along with changing objective function because power from distributed generation is continuously varying so this can be applied for real time applications with required modifications. This algorithm here is tested for a standard 33 bus radial distribution system for loss minimization and test results here shows that this algorithm is efficient and suitable for real time applications.

In-to-out body path loss for wireless radio frequency capsule endoscopy in a human body.

Science.gov (United States)

Vermeeren, G; Tanghe, E; Thielens, A; Martens, L; Joseph, W

2016-08-01

Physical-layer characterization is important for design of in-to-out body communication for wireless body area networks (WBANs). This paper numerically investigates the path loss of an in-to-out body radio frequency (RF) wireless link between an endoscopy capsule and a receiver outside the body using a 3D electromagnetic solver. A spiral antenna in the endoscopy capsule is tuned to operate in the Medical Implant Communication Service (MICS) band at 402 MHz, accounting for the properties of the human body. The influence of misalignment, rotation of the capsule, and human body model are investigated. Semi-empirical path loss models for various homogeneous tissues and 3D realistic human body models are provided for manufacturers to evaluate the performance of in-to-out-body WBAN systems.

Effects of Gain/Loss Framing in Cyber Defense Decision-Making

Energy Technology Data Exchange (ETDEWEB)

Bos, Nathan; Paul, Celeste; Gersh, John; Greenberg, Ariel; Piatko, Christine; Sperling, Scott; Spitaletta, Jason; Arendt, Dustin L.; Burtner, Edwin R.

2016-10-24

Cyber defense requires decision making under uncertainty. Yet this critical area has not been a strong focus of research in judgment and decision-making. Future defense systems, which will rely on software-defined networks and may employ ‘moving target’ defenses, will increasingly automate lower level detection and analysis, but will still require humans in the loop for higher level judgment. We studied the decision making process and outcomes of 17 experienced network defense professionals who worked through a set of realistic network defense scenarios. We manipulated gain versus loss framing in a cyber defense scenario, and found significant effects in one of two focal problems. Defenders that began with a network already in quarantine (gain framing) used a quarantine system more than those that did not (loss framing). We also found some difference in perceived workload and efficacy. Alternate explanations of these findings and implications for network defense are discussed.

THz Tube Waveguides With Low Loss, Low Dispersion, and High Bandwidth

DEFF Research Database (Denmark)

Bao, Hualong; Nielsen, Kristian; Bang, Ole

2014-01-01

We propose, model and experimentally characterize a novel class of terahertz hollow-core tube waveguides with high-loss cladding material, resulting in propagation with low loss, low dispersion, and high useful bandwidth.......We propose, model and experimentally characterize a novel class of terahertz hollow-core tube waveguides with high-loss cladding material, resulting in propagation with low loss, low dispersion, and high useful bandwidth....

Novel Method for Measuring the Heat Collection Rate and Heat Loss Coefficient of Water-in-Glass Evacuated Tube Solar Water Heaters Based on Artificial Neural Networks and Support Vector Machine

Directory of Open Access Journals (Sweden)

Zhijian Liu

2015-08-01

Full Text Available The determinations of heat collection rate and heat loss coefficient are crucial for the evaluation of in service water-in-glass evacuated tube solar water heaters. However, the direct determination requires complex detection devices and a series of standard experiments, which also wastes too much time and manpower. To address this problem, we propose machine learning models including artificial neural networks (ANNs and support vector machines (SVM to predict the heat collection rate and heat loss coefficient without a direct determination. Parameters that can be easily obtained by “portable test instruments” were set as independent variables, including tube length, number of tubes, tube center distance, heat water mass in tank, collector area, final temperature and angle between tubes and ground, while the heat collection rate and heat loss coefficient determined by the detection device were set as dependent variables respectively. Nine hundred fifteen samples from in-service water-in-glass evacuated tube solar water heaters were used for training and testing the models. Results show that the multilayer feed-forward neural network (MLFN with 3 nodes is the best model for the prediction of heat collection rate and the general regression neural network (GRNN is the best model for the prediction of heat loss coefficient due to their low root mean square (RMS errors, short training times, and high prediction accuracies (under the tolerances of 30%, 20%, and 10%, respectively.

Perspectives and limitations of QKD integration in metropolitan area networks.

Science.gov (United States)

Aleksic, Slavisa; Hipp, Florian; Winkler, Dominic; Poppe, Andreas; Schrenk, Bernhard; Franzl, Gerald

2015-04-20

Quantum key distribution (QKD) systems have already reached a reasonable level of maturity. However, a smooth integration and a wide adoption of commercial QKD systems in metropolitan area networks has still remained challenging because of technical and economical obstacles. Mainly the need for dedicated fibers and the strong dependence of the secret key rate on both loss budget and background noise in the quantum channel hinder a practical, flexible and robust implementation of QKD in current and next-generation optical metro networks. In this paper, we discuss these obstacles and present approaches to share existing fiber infrastructures among quantum and classical channels. Particularly, a proposal for a smooth integration of QKD in optical metro networks, which implies removing spurious background photons caused by optical transmitters, amplifiers and nonlinear effects in fibers, is presented and discussed. We determine and characterize impairments on quantum channels caused by many classical telecom channels at practically used power levels coexisting within the same fiber. Extensive experimental results are presented and indicate that a practical integration of QKD in conventional optical metro networks is possible.

Exploring patterns of alteration in Alzheimer’s disease brain networks: a combined structural and functional connectomics analysis

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Fulvia Palesi

2016-09-01

Full Text Available Alzheimer’s disease (AD is a neurodegenerative disorder characterized by a severe derangement of cognitive functions, primarily memory, in elderly subjects. As far as the functional impairment is concerned, growing evidence supports the disconnection syndrome hypothesis. Recent investigations using fMRI have revealed a generalized alteration of resting state networks in patients affected by AD and mild cognitive impairment (MCI. However, it was unclear whether the changes in functional connectivity were accompanied by corresponding structural network changes. In this work, we have developed a novel structural/functional connectomic approach: resting state fMRI was used to identify the functional cortical network nodes and diffusion MRI to reconstruct the fiber tracts to give a weight to internodal subcortical connections. Then, local and global efficiency were determined for different networks, exploring specific alterations of integration and segregation patterns in AD and MCI patients compared to healthy controls (HC. In the default mode network (DMN, that was the most affected, axonal loss and reduced axonal integrity appeared to compromise both local and global efficiency along posterior-anterior connections. In the basal ganglia network (BGN, disruption of white matter integrity implied that main alterations occurred in local microstructure. In the anterior insular network (AIN, neuronal loss probably subtended a compromised communication with the insular cortex. Cognitive performance, evaluated by neuropsychological examinations, revealed a dependency on integration and segregation of brain networks. These findings are indicative of the fact that cognitive deficits in AD could be associated not only with cortical alterations (revealed by fMRI but also with subcortical alterations (revealed by diffusion MRI that extend beyond the areas primarily damaged by neurodegeneration, towards the support of an emerging concept of AD as a

Animal movement network analysis as a tool to map farms serving as contamination source in cattle cysticercosis

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Samuel C. Aragão

Full Text Available ABSTRACT: Bovine cysticercosis is a problem distributed worldwide that result in economic losses mainly due to the condemnation of infected carcasses. One of the difficulties in applying control measures is the identification of the source of infection, especially because cattle are typically acquired from multiple farms. Here, we tested the utility of an animal movement network constructed with data from a farm that acquires cattle from several other different farms to map the major contributors of cysticercosis propagation. Additionally, based on the results of the network analysis, we deployed a sanitary management and drug treatment scheme to decrease cysticercosis’ occurrence in the farm. Six farms that had commercial trades were identified by the animal movement network and characterized as the main contributors to the occurrence of cysticercosis in the studied farm. The identification of farms with a putative risk of Taenia saginata infection using the animal movement network along with the proper sanitary management and drug treatment resulted in a gradual decrease in cysticercosis prevalence, from 25% in 2010 to 3.7% in 2011 and 1.8% in 2012. These results suggest that the animal movement network can contribute towards controlling bovine cysticercosis, thus minimizing economic losses and preventing human taeniasis.

Dynamic Pathloss Model for Place and Time Itinerant Networks

DEFF Research Database (Denmark)

Kumar, Ambuj; Mihovska, Albena; Prasad, Ramjee

2018-01-01

that are essentially static. Therefore, once the signal level drops beyond the predicted values due to any variance in the environmental conditions, very crowded areas may not be catered well enough by the deployed network that had been designed with the static path loss model. This paper proposes an approach......t Future mobile communication networks are expected to be more intelligent and proactive based on new capabilities that increase agility and performance. However, for any successful mobile network service, the dexterity in network deployment is a key factor. The efficiency of the network planning...... depends on how congruent the chosen path loss model and real propagation are. Various path loss models have been developed that predict the signal propagation in various morphological and climatic environments; however they consider only those physical parameters of the network environment...

Power losses in electrical networks depending on weather conditions

International Nuclear Information System (INIS)

Zhelezko, Yu. S.; Kostyushko, V. A.; Krylov, S. V.; Nikiforov, E. P.; Savchenko, O. V.; Timashova, L. V.; Solomonik, E. A.

2005-01-01

Specific power losses to corona and to leakage currents over overhead insulators are presented for 110 - 750-kV transmission lines with different phase design and pole types for different weather conditions. Consumption of electric energy for ice melting on conductors of various cross sections is evaluated. Meteorological data of 1372 weather stations in Russia are processed for a period of 10 years. The territory of the country is divided into 7 regions with approximately homogeneous weather conditions. Specific power losses to corona and leakage currents over overhead insulators are presented for every region

Genotype-phenotype correlation for DFNA22: characterization of non-syndromic, autosomal dominant, progressive sensorineural hearing loss due to MYO6 mutations

DEFF Research Database (Denmark)

Topsakal, Vedat; Hilgert, Nele; van Dinther, Joost

2010-01-01

Clinical and audiological examination was done in 2 Belgian families with autosomal dominant sensorineural hearing loss (SNHL) linked to DFNA22. Nineteen subjects in family 1 had mild to moderate SNHL starting in the third decade. The hearing loss was characterized by a flat audiogram affecting all......Hz. For all hitherto known DFNA22 families the audiological and clinical characteristics were correlated with the molecular data. This study describes the phenotype of 2 Belgian families with SNHL linked to DFNA22, both with a pathogenic change in the deafness gene MYO6. The phenotypes of all hitherto...

Duality between Time Series and Networks

Science.gov (United States)

Campanharo, Andriana S. L. O.; Sirer, M. Irmak; Malmgren, R. Dean; Ramos, Fernando M.; Amaral, Luís A. Nunes.

2011-01-01

Studying the interaction between a system's components and the temporal evolution of the system are two common ways to uncover and characterize its internal workings. Recently, several maps from a time series to a network have been proposed with the intent of using network metrics to characterize time series. Although these maps demonstrate that different time series result in networks with distinct topological properties, it remains unclear how these topological properties relate to the original time series. Here, we propose a map from a time series to a network with an approximate inverse operation, making it possible to use network statistics to characterize time series and time series statistics to characterize networks. As a proof of concept, we generate an ensemble of time series ranging from periodic to random and confirm that application of the proposed map retains much of the information encoded in the original time series (or networks) after application of the map (or its inverse). Our results suggest that network analysis can be used to distinguish different dynamic regimes in time series and, perhaps more importantly, time series analysis can provide a powerful set of tools that augment the traditional network analysis toolkit to quantify networks in new and useful ways. PMID:21858093

The correlation of metrics in complex networks with applications in functional brain networks

NARCIS (Netherlands)

Li, C.; Wang, H.; De Haan, W.; Stam, C.J.; Van Mieghem, P.F.A.

2011-01-01

An increasing number of network metrics have been applied in network analysis. If metric relations were known better, we could more effectively characterize networks by a small set of metrics to discover the association between network properties/metrics and network functioning. In this paper, we

Functional-structural reorganisation of the neuronal network for auditory perception in subjects with unilateral hearing loss: Review of neuroimaging studies.

Science.gov (United States)

Heggdal, Peder O Laugen; Brännström, Jonas; Aarstad, Hans Jørgen; Vassbotn, Flemming S; Specht, Karsten

2016-02-01

This paper aims to provide a review of studies using neuroimaging to measure functional-structural reorganisation of the neuronal network for auditory perception after unilateral hearing loss. A literature search was performed in PubMed. Search criterions were peer reviewed original research papers in English completed by the 11th of March 2015. Twelve studies were found to use neuroimaging in subjects with unilateral hearing loss. An additional five papers not identified by the literature search were provided by a reviewer. Thus, a total of 17 studies were included in the review. Four different neuroimaging methods were used in these studies: Functional magnetic resonance imaging (fMRI) (n = 11), diffusion tensor imaging (DTI) (n = 4), T1/T2 volumetric images (n = 2), magnetic resonance spectroscopy (MRS) (n = 1). One study utilized two imaging methods (fMRI and T1 volumetric images). Neuroimaging techniques could provide valuable information regarding the effects of unilateral hearing loss on both auditory and non-auditory performance. fMRI-studies showing a bilateral BOLD-response in patients with unilateral hearing loss have not yet been followed by DTI studies confirming their microstructural correlates. In addition, the review shows that an auditory modality-specific deficit could affect multi-modal brain regions and their connections. Copyright © 2015 Elsevier B.V. All rights reserved.

A Flexible Load Control Strategy for Distribution Network to Reduce the Line Losses and to Eliminate the Transmission Congestion

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Beibei Wang

2017-01-01

Full Text Available There are many uncertain factors in the modern distribution network, including the access of renewable energy sources and the heavy load level. The existence of these factors has brought challenges to the stability of the power distribution network, as well as increasing the risk of exceeding transmission capacity of distribution lines. The appearance of flexible load control technology provides a new idea to solve the above problems. Air conditioners (ACs account for a great proportion of all loads. In this paper, the model of dispatching AC loads in the regional power grid is constructed, and the direct load control (DLC method is adopted to reduce the load of ACs. An improved tabu search technique is proposed to solve the problem of network dispatch in distribution systems in order to reduce the resistive line losses and to eliminate the transmission congestion in lines under normal operating conditions. The optimal node solution is obtained to find the best location and reduction capacity of ACs for load control. To demonstrate the validity and effectiveness of the proposed method, a test system is studied. The numerical results are also given in this article, which reveal that the proposed method is promising.

Thermal Loss in High-Q Antennas

DEFF Research Database (Denmark)

Barrio, Samantha Caporal Del; Bahramzy, Pevand; Svendsen, Simon

2014-01-01

Tunable antennas are very promising for future generations of mobile communications, where antennas are required to cover a wide range operating bands. This letter aims at characterizing the loss mechanism of tunable antennas. Tunable antennas typically exhibit a high Quality factor (Q), which ca...... lead to thermal loss due to the conductivity of the metal. The investigation shows that copper loss is non-negligible for high Q values. In the proposed design the copper loss is 2 dB, for a Q of 260 at 700 MHz....

Encryption for confidentiality of the network and influence of this to the quality of streaming video through network

Science.gov (United States)

Sevcik, L.; Uhrin, D.; Frnda, J.; Voznak, M.; Toral-Cruz, Homer; Mikulec, M.; Jakovlev, Sergej

2015-05-01

Nowadays, the interest in real-time services, like audio and video, is growing. These services are mostly transmitted over packet networks, which are based on IP protocol. It leads to analyses of these services and their behavior in such networks which are becoming more frequent. Video has become the significant part of all data traffic sent via IP networks. In general, a video service is one-way service (except e.g. video calls) and network delay is not such an important factor as in a voice service. Dominant network factors that influence the final video quality are especially packet loss, delay variation and the capacity of the transmission links. Analysis of video quality concentrates on the resistance of video codecs to packet loss in the network, which causes artefacts in the video. IPsec provides confidentiality in terms of safety, integrity and non-repudiation (using HMAC-SHA1 and 3DES encryption for confidentiality and AES in CBC mode) with an authentication header and ESP (Encapsulating Security Payload). The paper brings a detailed view of the performance of video streaming over an IP-based network. We compared quality of video with packet loss and encryption as well. The measured results demonstrated the relation between the video codec type and bitrate to the final video quality.

Characterization of contact structures for the spread of infectious diseases in a pork supply chain in northern Germany by dynamic network analysis of yearly and monthly networks.

Science.gov (United States)

Büttner, K; Krieter, J; Traulsen, I

2015-04-01

A major risk factor in the spread of diseases between holdings is the transport of live animals. This study analysed the animal movements of the pork supply chain of a producer group in Northern Germany. The parameters in-degree and out-degree, ingoing and outgoing infection chain, betweenness and ingoing and outgoing closeness were measured using dynamic network analysis to identify holdings with central positions in the network and to characterize the overall network topology. The potential maximum epidemic size was also estimated. All parameters were calculated for three time periods: the 3-yearly network, the yearly and the monthly networks. The yearly and the monthly networks were more fragmented than the 3-yearly network. On average, one-third of the holdings were isolated in the yearly networks and almost three quarters in the monthly networks. This represented an immense reduction in the number of holdings participating in the trade of the monthly networks. The overall network topology showed right-skewed distributions for all calculated centrality parameters indicating that network resilience was high concerning the random removal of holdings. However, for a targeted removal of holdings according to their centrality, a rapid fragmentation of the trade network could be expected. Furthermore, to capture the real importance of holdings for disease transmission, indirect trade contacts (infection chain) should be considered. In contrast to the parameters regarding direct trade contacts (degree), the infection chain parameter did not underestimate the potential risk of disease transmission. This became more obvious, the longer the observed time period was. For all three time periods, the results for the estimation of the potential maximum epidemic size illustrated that the outgoing infection chain should be chosen. It considers the chronological order and the directed nature of the contacts and has no restrictions such as the strongly connected components of a

Disentangling the co-structure of multilayer interaction networks: degree distribution and module composition in two-layer bipartite networks.

Science.gov (United States)

Astegiano, Julia; Altermatt, Florian; Massol, François

2017-11-13

Species establish different interactions (e.g. antagonistic, mutualistic) with multiple species, forming multilayer ecological networks. Disentangling network co-structure in multilayer networks is crucial to predict how biodiversity loss may affect the persistence of multispecies assemblages. Existing methods to analyse multilayer networks often fail to consider network co-structure. We present a new method to evaluate the modular co-structure of multilayer networks through the assessment of species degree co-distribution and network module composition. We focus on modular structure because of its high prevalence among ecological networks. We apply our method to two Lepidoptera-plant networks, one describing caterpillar-plant herbivory interactions and one representing adult Lepidoptera nectaring on flowers, thereby possibly pollinating them. More than 50% of the species established either herbivory or visitation interactions, but not both. These species were over-represented among plants and lepidopterans, and were present in most modules in both networks. Similarity in module composition between networks was high but not different from random expectations. Our method clearly delineates the importance of interpreting multilayer module composition similarity in the light of the constraints imposed by network structure to predict the potential indirect effects of species loss through interconnected modular networks.

Environmental cost of distribution transformer losses

International Nuclear Information System (INIS)

Georgilakis, Pavlos S.

2011-01-01

Improvements in energy efficiency of electrical equipment reduce the greenhouse gas (GHG) emissions and contribute to the protection of the environment. Moreover, as system investment and energy costs continue to increase, electric utilities are increasingly interested in installing energy-efficient transformers at their distribution networks. This paper analyzes the impact of the environmental cost of transformer losses on the economic evaluation of distribution transformers. This environmental cost is coming form the cost to buy GHG emission credits because of the GHG emissions associated with supplying transformer losses throughout the transformer lifetime. Application results on the Hellenic power system for 21 transformer offers under 9 different scenarios indicate that the environmental cost of transformer losses can reach on average 34% and 8% of transformer purchasing price for high loss and medium loss transformers, respectively. That is why it is important to incorporate the environmental cost of transformer losses into the economic evaluation of distribution transformers.

Artificial neural network application in isotopic characterization of radioactive waste drums

International Nuclear Information System (INIS)

Potiens Junior, Ademar Jose

2005-01-01

One of the most important aspects to the development of the nuclear technology is the safe management of the radioactive waste arising from several stages of the nuclear fuel cycles, as well as from production and use of radioisotope in the medicine, industry and research centers. The accurate characterization of this waste is not a simple task, given to its diversity in isotopic composition and non homogeneity in the space distribution and mass density. In this work it was developed a methodology for quantification and localization of radionuclides not non homogeneously distributed in a 200 liters drum based in the Monte Carlo Method and Artificial Neural Network (RNA), for application in the isotopic characterization of the stored radioactive waste at IPEN. Theoretical arrangements had been constructed involving the division of the radioactive waste drum in some units or cells and some possible configurations of source intensities. Beyond the determination of the detection positions, the respective detection efficiencies for each position in function of each cell of the drum had been obtained. After the construction and the training of the RNA's for each developed theoretical arrangement, the validation of the method were carried out for the two arrangements that had presented the best performance. The results obtained show that the methodology developed in this study could be an effective tool for isotopic characterization of radioactive wastes contained in many kind of packages. (author)

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

International Nuclear Information System (INIS)

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

2014-01-01

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

Classification of non-performing loans portfolio using Multilayer Perceptron artificial neural networks

Directory of Open Access Journals (Sweden)

Flávio Clésio Silva de Souza

2014-06-01

Full Text Available The purpose of the present research is to apply a Multilayer Perceptron (MLP neural network technique to create classification models from a portfolio of Non-Performing Loans (NPLs to classify this type of credit derivative. These credit derivatives are characterized as the amount of loans that were not paid and are already overdue more than 90 days. Since these titles are, because of legislative motives, moved by losses, Credit Rights Investment Funds (FDIC performs the purchase of these debts and the recovery of the credits. Using the Multilayer Perceptron (MLP architecture of Artificial Neural Network (ANN, classification models regarding the posterior recovery of these debts were created. To evaluate the performance of the models, evaluation metrics of classification relating to the neural networks with different architectures were presented. The results of the classifications were satisfactory, given the classification models were successful in the presented economics costs structure.

Characterization of Eyeball Loss in Four Cities of Colombia.

Science.gov (United States)

Moreno-Caviedes, F Hernán; Velez Cuellar, Nórida; Caicedo Zapata, Margarita; Triana Reina, Gabriel; Sánchez, Azucena

2017-09-11

Describe the socio-demographic characteristics of anophthalmic patients examined at specialized centers of four cities in Colombia to know the different causes of eyeball loss. A transversal retrospective study was done of 511 medical records from the specialized practices of four cities in Colombia. Socio-demographic data of patients who were seen between January 2011 and December 2013 were compiled. SOFA Statistics software v1.4.6 was used for this analysis. An analysis throughout the measures of central tendency for numerical variables was developed, and the descriptive statistics were used for the categorical variables. Almost 63% of the data belonged to male patients. Eyeball loss was more frequent in patients over 40 years of age. Fifty-one percent of the patients suffered eyeball loss due to traumatic causes, 40.2% due to pathological causes, and 4.6% due to congenital anomalies. The most frequent specific causes were glaucoma (19%), ocular cancer (15.4%), and home accidents (11,2%). Around 60% of the anophthalmic patients belonged to low socioeconomic level. It is important to highlight that more than half of the analyzed anophthalmia cases originated in some type of trauma; this means that they could be considered potentially avoidable losses. Complications deriving from glaucoma became the most frequent cause of anophthalmia in the pathological origin group, which suggests a reflection regarding the strategies of early detection of the disease and access to proper treatment. It is also showed the need to develop an efficient system to manage information.

Experimental Branch Retinal Vein Occlusion Induces Upstream Pericyte Loss and Vascular Destabilization.

Directory of Open Access Journals (Sweden)

Elisa Dominguez

Full Text Available Branch retinal vein occlusion (BRVO leads to extensive vascular remodeling and is important cause of visual impairment. Although the vascular morphological changes following experimental vein occlusion have been described in a variety of models using angiography, the underlying cellular events are ill defined.We here show that laser-induced experimental BRVO in mice leads to a wave of TUNEL-positive endothelial cell (EC apoptosis in the upstream vascular network associated with a transient edema and hemorrhages. Subsequently, we observe an induction of EC proliferation within the dilated vein and capillaries, detected by EdU incorporation, and the edema resolves. However, the pericytes of the upstream capillaries are severely reduced, which was associated with continuing EC apoptosis and proliferation. The vascular remodeling was associated with increased expression of TGFβ, TSP-1, but also FGF2 expression. Exposure of the experimental animals to hypoxia, when pericyte (PC dropout had occurred, led to a dramatic increase in endothelial cell proliferation, confirming the vascular instability induced by the experimental BRVO.Experimental BRVO leads to acute endothelial cells apoptosis and increased permeability. Subsequently the upstream vascular network remains destabilized, characterized by pericyte dropout, un-physiologically high endothelial cells turnover and sensitivity to hypoxia. These early changes might pave the way for capillary loss and subsequent chronic ischemia and edema that characterize the late stage disease.

Networks of networks – An introduction

International Nuclear Information System (INIS)

Kenett, Dror Y.; Perc, Matjaž; Boccaletti, Stefano

2015-01-01

Graphical abstract: Interdependent network reciprocity. Only those blue cooperative domains that are initially present on both networks survive. Abstract: This is an introduction to the special issue titled “Networks of networks” that is in the making at Chaos, Solitons & Fractals. Recent research and reviews attest to the fact that networks of networks are the next frontier in network science [1–7]. Not only are interactions limited and thus inadequately described by well-mixed models, it is also a fact that the networks that should be an integral part of such models are often interconnected, thus making the processes that are unfolding on them interdependent. From the World economy and transportation systems to social media, it is clear that processes taking place in one network might significantly affect what is happening in many other networks. Within an interdependent system, each type of interaction has a certain relevance and meaning, so that treating all the links identically inevitably leads to information loss. Networks of networks, interdependent networks, or multilayer networks are therefore a much better and realistic description of such systems, and this Special Issue is devoted to their structure, dynamics and evolution, as well as to the study of emergent properties in multi-layered systems in general. Topics of interest include but are not limited to the spread of epidemics and information, percolation, diffusion, synchronization, collective behavior, and evolutionary games on networks of networks. Interdisciplinary work on all aspects of networks of networks, regardless of background and motivation, is very welcome.

Information theoretic description of networks

Science.gov (United States)

Wilhelm, Thomas; Hollunder, Jens

2007-11-01

We present a new information theoretic approach for network characterizations. It is developed to describe the general type of networks with n nodes and L directed and weighted links, i.e., it also works for the simpler undirected and unweighted networks. The new information theoretic measures for network characterizations are based on a transmitter-receiver analogy of effluxes and influxes. Based on these measures, we classify networks as either complex or non-complex and as either democracy or dictatorship networks. Directed networks, in particular, are furthermore classified as either information spreading and information collecting networks. The complexity classification is based on the information theoretic network complexity measure medium articulation (MA). It is proven that special networks with a medium number of links ( L∼n1.5) show the theoretical maximum complexity MA=(log n)2/2. A network is complex if its MA is larger than the average MA of appropriately randomized networks: MA>MAr. A network is of the democracy type if its redundancy Rdictatorship network. In democracy networks all nodes are, on average, of similar importance, whereas in dictatorship networks some nodes play distinguished roles in network functioning. In other words, democracy networks are characterized by cycling of information (or mass, or energy), while in dictatorship networks there is a straight through-flow from sources to sinks. The classification of directed networks into information spreading and information collecting networks is based on the conditional entropies of the considered networks ( H(A/B)=uncertainty of sender node if receiver node is known, H(B/A)=uncertainty of receiver node if sender node is known): if H(A/B)>H(B/A), it is an information collecting network, otherwise an information spreading network. Finally, different real networks (directed and undirected, weighted and unweighted) are classified according to our general scheme.

Leakage detection and estimation algorithm for loss reduction in water piping networks

CSIR Research Space (South Africa)

Adedeji, KB

2017-10-01

Full Text Available the development of efficient algorithms for detecting leakage in water piping networks. Water distribution networks (WDNs) are disperse in nature with numerous number of nodes and branches. Consequently, identifying the segment(s) of the network and the exact...

Elucidating MicroRNA Regulatory Networks Using Transcriptional, Post-transcriptional, and Histone Modification Measurements

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Sara J.C. Gosline

2016-01-01

Full Text Available MicroRNAs (miRNAs regulate diverse biological processes by repressing mRNAs, but their modest effects on direct targets, together with their participation in larger regulatory networks, make it challenging to delineate miRNA-mediated effects. Here, we describe an approach to characterizing miRNA-regulatory networks by systematically profiling transcriptional, post-transcriptional and epigenetic activity in a pair of isogenic murine fibroblast cell lines with and without Dicer expression. By RNA sequencing (RNA-seq and CLIP (crosslinking followed by immunoprecipitation sequencing (CLIP-seq, we found that most of the changes induced by global miRNA loss occur at the level of transcription. We then introduced a network modeling approach that integrated these data with epigenetic data to identify specific miRNA-regulated transcription factors that explain the impact of miRNA perturbation on gene expression. In total, we demonstrate that combining multiple genome-wide datasets spanning diverse regulatory modes enables accurate delineation of the downstream miRNA-regulated transcriptional network and establishes a model for studying similar networks in other systems.

Asynchronous control for networked systems

CERN Document Server

Rubio, Francisco; Bencomo, Sebastián

2015-01-01

This book sheds light on networked control systems; it describes different techniques for asynchronous control, moving away from the periodic actions of classical control, replacing them with state-based decisions and reducing the frequency with which communication between subsystems is required. The text focuses specially on event-based control. Split into two parts, Asynchronous Control for Networked Systems begins by addressing the problems of single-loop networked control systems, laying out various solutions which include two alternative model-based control schemes (anticipatory and predictive) and the use of H2/H∞ robust control to deal with network delays and packet losses. Results on self-triggering and send-on-delta sampling are presented to reduce the need for feedback in the loop. In Part II, the authors present solutions for distributed estimation and control. They deal first with reliable networks and then extend their results to scenarios in which delays and packet losses may occur. The novel ...

Characterizing Radiation-Aged Polysiloxane-Silica Composites: Identifying Changes in Network Topology via 1H NMR

International Nuclear Information System (INIS)

Mayer, B.; Chinn, S.C.; Maxwell, R.S.; Reimer, J.

2008-01-01

Characterizing and quantifying changes in elastomeric materials upon exposure to harsh environments is important in the estimation of device lifetimes. Nuclear magnetic resonance (NMR) spectroscopy has been used effectively in the analysis of such materials and has proved to be both sensitive to micro- and macroscopic changes associated with material 'aging'. Traditional analyses, however, rely on empirical formulae containing a large number of (often arbitrary) independent variables. This ambiguity can be circumvented largely by developing models of NMR observables that are based on basic polymer physics. We compare two such models, one previously published and one derived herein, along with empirical expressions that describe the proton transverse magnetization decay associated with complex polymer networks. One particular extracted parameter, the proton-proton residual dipolar coupling (RDC), can be directly related to network topology, and a comparison of the extracted RDCs reveals high consistency among the models. An expression derived from the properties of a static Gaussian chain can minimize the number of parameters necessarily to describe the solid-like, networked proton population to a single independent parameter, the average residual dipolar coupling, D avg .

Characterization of hairless (Hr) and FGF5 genes provides insights into the molecular basis of hair loss in cetaceans.

Science.gov (United States)

Chen, Zhuo; Wang, Zhengfei; Xu, Shixia; Zhou, Kaiya; Yang, Guang

2013-02-09

Hair is one of the main distinguishing characteristics of mammals and it has many important biological functions. Cetaceans originated from terrestrial mammals and they have evolved a series of adaptations to aquatic environments, which are of evolutionary significance. However, the molecular mechanisms underlying their aquatic adaptations have not been well explored. This study provided insights into the evolution of hair loss during the transition from land to water by investigating and comparing two essential regulators of hair follicle development and hair follicle cycling, i.e., the Hairless (Hr) and FGF5 genes, in representative cetaceans and their terrestrial relatives. The full open reading frame sequences of the Hr and FGF5 genes were characterized in seven cetaceans. The sequence characteristics and evolutionary analyses suggested the functional loss of the Hr gene in cetaceans, which supports the loss of hair during their full adaptation to aquatic habitats. By contrast, positive selection for the FGF5 gene was found in cetaceans where a series of positively selected amino acid residues were identified. This is the first study to investigate the molecular basis of the hair loss in cetaceans. Our investigation of Hr and FGF5, two indispensable regulators of the hair cycle, provide some new insights into the molecular basis of hair loss in cetaceans. The results suggest that positive selection for the FGF5 gene might have promoted the termination of hair growth and early entry into the catagen stage of hair follicle cycling. Consequently, the hair follicle cycle was disrupted and the hair was lost completely due to the loss of the Hr gene function in cetaceans. This suggests that cetaceans have evolved an effective and complex mechanism for hair loss.

Extracting information from multiplex networks

Science.gov (United States)

Iacovacci, Jacopo; Bianconi, Ginestra

2016-06-01

Multiplex networks are generalized network structures that are able to describe networks in which the same set of nodes are connected by links that have different connotations. Multiplex networks are ubiquitous since they describe social, financial, engineering, and biological networks as well. Extending our ability to analyze complex networks to multiplex network structures increases greatly the level of information that is possible to extract from big data. For these reasons, characterizing the centrality of nodes in multiplex networks and finding new ways to solve challenging inference problems defined on multiplex networks are fundamental questions of network science. In this paper, we discuss the relevance of the Multiplex PageRank algorithm for measuring the centrality of nodes in multilayer networks and we characterize the utility of the recently introduced indicator function Θ ˜ S for describing their mesoscale organization and community structure. As working examples for studying these measures, we consider three multiplex network datasets coming for social science.

Resident Space Object Characterization and Behavior Understanding via Machine Learning and Ontology-based Bayesian Networks

Science.gov (United States)

Furfaro, R.; Linares, R.; Gaylor, D.; Jah, M.; Walls, R.

2016-09-01

In this paper, we present an end-to-end approach that employs machine learning techniques and Ontology-based Bayesian Networks (BN) to characterize the behavior of resident space objects. State-of-the-Art machine learning architectures (e.g. Extreme Learning Machines, Convolutional Deep Networks) are trained on physical models to learn the Resident Space Object (RSO) features in the vectorized energy and momentum states and parameters. The mapping from measurements to vectorized energy and momentum states and parameters enables behavior characterization via clustering in the features space and subsequent RSO classification. Additionally, Space Object Behavioral Ontologies (SOBO) are employed to define and capture the domain knowledge-base (KB) and BNs are constructed from the SOBO in a semi-automatic fashion to execute probabilistic reasoning over conclusions drawn from trained classifiers and/or directly from processed data. Such an approach enables integrating machine learning classifiers and probabilistic reasoning to support higher-level decision making for space domain awareness applications. The innovation here is to use these methods (which have enjoyed great success in other domains) in synergy so that it enables a "from data to discovery" paradigm by facilitating the linkage and fusion of large and disparate sources of information via a Big Data Science and Analytics framework.

Characterization of functional and structural integrity in experimental focal epilepsy: reduced network efficiency coincides with white matter changes.

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Willem M Otte

Full Text Available BACKGROUND: Although focal epilepsies are increasingly recognized to affect multiple and remote neural systems, the underlying spatiotemporal pattern and the relationships between recurrent spontaneous seizures, global functional connectivity, and structural integrity remain largely unknown. METHODOLOGY/PRINCIPAL FINDINGS: Here we utilized serial resting-state functional MRI, graph-theoretical analysis of complex brain networks and diffusion tensor imaging to characterize the evolution of global network topology, functional connectivity and structural changes in the interictal brain in relation to focal epilepsy in a rat model. Epileptic networks exhibited a more regular functional topology than controls, indicated by a significant increase in shortest path length and clustering coefficient. Interhemispheric functional connectivity in epileptic brains decreased, while intrahemispheric functional connectivity increased. Widespread reductions of fractional anisotropy were found in white matter regions not restricted to the vicinity of the epileptic focus, including the corpus callosum. CONCLUSIONS/SIGNIFICANCE: Our longitudinal study on the pathogenesis of network dynamics in epileptic brains reveals that, despite the locality of the epileptogenic area, epileptic brains differ in their global network topology, connectivity and structural integrity from healthy brains.

Influences of brain development and ageing on cortical interactive networks.

Science.gov (United States)

Zhu, Chengyu; Guo, Xiaoli; Jin, Zheng; Sun, Junfeng; Qiu, Yihong; Zhu, Yisheng; Tong, Shanbao

2011-02-01

To study the effect of brain development and ageing on the pattern of cortical interactive networks. By causality analysis of multichannel electroencephalograph (EEG) with partial directed coherence (PDC), we investigated the different neural networks involved in the whole cortex as well as the anterior and posterior areas in three age groups, i.e., children (0-10 years), mid-aged adults (26-38 years) and the elderly (56-80 years). By comparing the cortical interactive networks in different age groups, the following findings were concluded: (1) the cortical interactive network in the right hemisphere develops earlier than its left counterpart in the development stage; (2) the cortical interactive network of anterior cortex, especially at C3 and F3, is demonstrated to undergo far more extensive changes, compared with the posterior area during brain development and ageing; (3) the asymmetry of the cortical interactive networks declines during ageing with more loss of connectivity in the left frontal and central areas. The age-related variation of cortical interactive networks from resting EEG provides new insights into brain development and ageing. Our findings demonstrated that the PDC analysis of EEG is a powerful approach for characterizing the cortical functional connectivity during brain development and ageing. Copyright © 2010 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Female pattern hair loss

Directory of Open Access Journals (Sweden)

İdil Ünal

2014-06-01

Full Text Available Female androgenetic alopecia is the commonest cause of hair loss in women. It is characterized by a diffuse reduction in hair density over the crown and frontal scalp with retention of the frontal hairline and a characteristic pattern distribution in genetically predisposed women. Because of the uncertain relationship with the androgens Female Pattern Hair Loss (FPHL is the most preferred definition of the condition. This review has been focused on the clinical features, diagnosis and treatment alternatives of FPHL.

Teammates and social influence affect weight loss outcomes in a team-based weight loss competition.

Science.gov (United States)

Leahey, Tricia M; Kumar, Rajiv; Weinberg, Brad M; Wing, Rena R

2012-07-01

Team-based internet interventions are increasing in popularity as a way of promoting weight loss in large numbers of individuals. Given that social networks influence health behavior change, this study investigated the effects of teammates and social influence on individual weight loss during a team-based weight loss competition. Shape Up Rhode Island (SURI) 2009 was a 12-week online program open to adult residents of Rhode Island. Participants joined with a team and competed with other teams on weight loss and/or physical activity. Overweight/obese (OW/OB) individuals (N = 3,330; 76% female; age = 46.1 ± 10.8; BMI = 31.2 ± 5.3 kg/m(2)), representing 987 teams, completed the weight loss program. Multilevel modeling was used to examine whether weight loss clustered among teammates and whether percentage of teammates in the weight loss division and reported teammate influence on weight loss were associated with individual weight outcomes. OW/OB completers reported losing 4.2 ± 3.4% of initial body weight. Weight loss was similar among teammates (intraclass correlation coefficient (ICC) = 0.10, P social influence for weight loss were associated with greater percent weight loss (P's ≤ 0.002). Similarly, achieving a clinically significant (5%) weight loss tended to cluster within teams (ICC = 0.09; P social influence for weight loss were associated with increased likelihood of achieving a 5% weight loss (odds ratio (OR) = 1.06; OR = 1.20, respectively). These results suggest that teammates affect weight loss outcomes during a team-based intervention. Harnessing and maximizing teammate influence for weight loss may enhance weight outcomes in large-scale team-based programs.

Cross Layer Interference Management in Wireless Biomedical Networks

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Emmanouil G. Spanakis

2014-04-01

Full Text Available Interference, in wireless networks, is a central phenomenon when multiple uncoordinated links share a common communication medium. The study of the interference channel was initiated by Shannon in 1961 and since then this problem has been thoroughly elaborated at the Information theoretic level but its characterization still remains an open issue. When multiple uncoordinated links share a common medium the effect of interference is a crucial limiting factor for network performance. In this work, using cross layer cooperative communication techniques, we study how to compensate interference in the context of wireless biomedical networks, where many links transferring biomedical or other health related data may be formed and suffer from all other interfering transmissions, to allow successful receptions and improve the overall network performance. We define the interference limited communication range to be the critical communication region around a receiver, with a number of surrounding interfering nodes, within which a successful communication link can be formed. Our results indicate that we can achieve more successful transmissions by adapting the transmission rate and power, to the path loss exponent, and the selected mode of the underline communication technique allowing interference mitigation and when possible lower power consumption and increase achievable transmission rates.

Characterization of Static/Dynamic Topological Routing For Grid Networks

DEFF Research Database (Denmark)

Gutierrez Lopez, Jose Manuel; Cuevas, Ruben; Riaz, M. Tahir

2009-01-01

Grid or 2D Mesh structures are becoming one of the most attractive network topologies to study. They can be used in many different fields raging from future broadband networks to multiprocessors structures. In addition, the high requirements of future services and applications demand more flexible...... and adaptive networks. Topological routing in grid networks is a simple and efficient alternative to traditional routing techniques, e.g. routing tables, and the paper extends this kind of routing providing a "Dynamic" attribute. This new property attempts to improve the overall network performance for future...

Epidemic Wave Dynamics Attributable to Urban Community Structure: A Theoretical Characterization of Disease Transmission in a Large Network

Science.gov (United States)

Eggo, Rosalind M; Lenczner, Michael

2015-01-01

Background Multiple waves of transmission during infectious disease epidemics represent a major public health challenge, but the ecological and behavioral drivers of epidemic resurgence are poorly understood. In theory, community structure—aggregation into highly intraconnected and loosely interconnected social groups—within human populations may lead to punctuated outbreaks as diseases progress from one community to the next. However, this explanation has been largely overlooked in favor of temporal shifts in environmental conditions and human behavior and because of the difficulties associated with estimating large-scale contact patterns. Objective The aim was to characterize naturally arising patterns of human contact that are capable of producing simulated epidemics with multiple wave structures. Methods We used an extensive dataset of proximal physical contacts between users of a public Wi-Fi Internet system to evaluate the epidemiological implications of an empirical urban contact network. We characterized the modularity (community structure) of the network and then estimated epidemic dynamics under a percolation-based model of infectious disease spread on the network. We classified simulated epidemics as multiwave using a novel metric and we identified network structures that were critical to the network’s ability to produce multiwave epidemics. Results We identified robust community structure in a large, empirical urban contact network from which multiwave epidemics may emerge naturally. This pattern was fueled by a special kind of insularity in which locally popular individuals were not the ones forging contacts with more distant social groups. Conclusions Our results suggest that ordinary contact patterns can produce multiwave epidemics at the scale of a single urban area without the temporal shifts that are usually assumed to be responsible. Understanding the role of community structure in epidemic dynamics allows officials to anticipate epidemic

Performance modeling, loss networks, and statistical multiplexing

CERN Document Server

Mazumdar, Ravi

2009-01-01

This monograph presents a concise mathematical approach for modeling and analyzing the performance of communication networks with the aim of understanding the phenomenon of statistical multiplexing. The novelty of the monograph is the fresh approach and insights provided by a sample-path methodology for queueing models that highlights the important ideas of Palm distributions associated with traffic models and their role in performance measures. Also presented are recent ideas of large buffer, and many sources asymptotics that play an important role in understanding statistical multiplexing. I

Nontargeted diagnostic ion network analysis (NINA): A software to streamline the analytical workflow for untargeted characterization of natural medicines.

Science.gov (United States)

Ye, Hui; Zhu, Lin; Sun, Di; Luo, Xiaozhuo; Lu, Gaoyuan; Wang, Hong; Wang, Jing; Cao, Guoxiu; Xiao, Wei; Wang, Zhenzhong; Wang, Guangji; Hao, Haiping

2016-11-30

The characterization of herbal prescriptions serves as a foundation for quality control and regulation of herbal medicines. Previously, the characterization of herbal chemicals from natural medicines often relied on the analysis of signature fragment ions from the acquired tandem mass spectrometry (MS/MS) spectra with prior knowledge of the herbal species present in the herbal prescriptions of interest. Nevertheless, such an approach is often limited to target components, and it risks missing the critical components that we have no prior knowledge of. We previously reported a "diagnostic ion-guided network bridging" strategy. It is a generally applicable and robust approach to analyze unknown substances from complex mixtures in an untargeted manner. In this study, we have developed a standalone software named "Nontargeted Diagnostic Ion Network Analysis (NINA)" with a graphical user interface based on a strategy for post-acquisition data analysis. NINA allows one to rapidly determine the nontargeted diagnostic ions (NIs) by summarizing all of the fragment ions shared by the precursors from the acquired MS/MS spectra. A NI-guided network using bridging components that possess two or more NIs can then be established via NINA. With such a network, we could sequentially identify the structures of all the NIs once a single compound has been identified de novo. The structures of NIs can then be used as "priori" knowledge to narrow the candidates containing the sub-structure of the corresponding NI from the database hits. Subsequently, we applied the NINA software to the characterization of a model herbal prescription, Re-Du-Ning injection, and rapidly identified 56 herbal chemicals from the prescription using an ultra-performance liquid chromatography quadrupole time-of-flight system in the negative mode with no knowledge of the herbal species or herbal chemicals in the mixture. Therefore, we believe the applications of NINA will greatly facilitate the characterization

Marginal Loss Calculations for the DCOPF

Energy Technology Data Exchange (ETDEWEB)

Eldridge, Brent [Federal Energy Regulatory Commission, Washington, DC (United States); Johns Hopkins Univ., Baltimore, MD (United States); O' Neill, Richard P. [Federal Energy Regulatory Commission, Washington, DC (United States); Castillo, Andrea R. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2016-12-05

The purpose of this paper is to explain some aspects of including a marginal line loss approximation in the DCOPF. The DCOPF optimizes electric generator dispatch using simplified power flow physics. Since the standard assumptions in the DCOPF include a lossless network, a number of modifications have to be added to the model. Calculating marginal losses allows the DCOPF to optimize the location of power generation, so that generators that are closer to demand centers are relatively cheaper than remote generation. The problem formulations discussed in this paper will simplify many aspects of practical electric dispatch implementations in use today, but will include sufficient detail to demonstrate a few points with regard to the handling of losses.

Prediction of hearing loss among the noise-exposed workers in a steel factory using artificial intelligence approach.

Science.gov (United States)

Aliabadi, Mohsen; Farhadian, Maryam; Darvishi, Ebrahim

2015-08-01

Prediction of hearing loss in noisy workplaces is considered to be an important aspect of hearing conservation program. Artificial intelligence, as a new approach, can be used to predict the complex phenomenon such as hearing loss. Using artificial neural networks, this study aims to present an empirical model for the prediction of the hearing loss threshold among noise-exposed workers. Two hundred and ten workers employed in a steel factory were chosen, and their occupational exposure histories were collected. To determine the hearing loss threshold, the audiometric test was carried out using a calibrated audiometer. The personal noise exposure was also measured using a noise dosimeter in the workstations of workers. Finally, data obtained five variables, which can influence the hearing loss, were used for the development of the prediction model. Multilayer feed-forward neural networks with different structures were developed using MATLAB software. Neural network structures had one hidden layer with the number of neurons being approximately between 5 and 15 neurons. The best developed neural networks with one hidden layer and ten neurons could accurately predict the hearing loss threshold with RMSE = 2.6 dB and R(2) = 0.89. The results also confirmed that neural networks could provide more accurate predictions than multiple regressions. Since occupational hearing loss is frequently non-curable, results of accurate prediction can be used by occupational health experts to modify and improve noise exposure conditions.

Network structure of subway passenger flows

Science.gov (United States)

Xu, Q.; Mao, B. H.; Bai, Y.

2016-03-01

The results of transportation infrastructure network analyses have been used to analyze complex networks in a topological context. However, most modeling approaches, including those based on complex network theory, do not fully account for real-life traffic patterns and may provide an incomplete view of network functions. This study utilizes trip data obtained from the Beijing Subway System to characterize individual passenger movement patterns. A directed weighted passenger flow network was constructed from the subway infrastructure network topology by incorporating trip data. The passenger flow networks exhibit several properties that can be characterized by power-law distributions based on flow size, and log-logistic distributions based on the fraction of boarding and departing passengers. The study also characterizes the temporal patterns of in-transit and waiting passengers and provides a hierarchical clustering structure for passenger flows. This hierarchical flow organization varies in the spatial domain. Ten cluster groups were identified, indicating a hierarchical urban polycentric structure composed of large concentrated flows at urban activity centers. These empirical findings provide insights regarding urban human mobility patterns within a large subway network.

Functional characterization of GABAA receptor-mediated modulation of cortical neuron network activity in microelectrode array recordings

DEFF Research Database (Denmark)

Bader, Benjamin M; Steder, Anne; Klein, Anders Bue

2017-01-01

The numerous γ-aminobutyric acid type A receptor (GABAAR) subtypes are differentially expressed and mediate distinct functions at neuronal level. In this study we have investigated GABAAR-mediated modulation of the spontaneous activity patterns of primary neuronal networks from murine frontal...... of the information extractable from the MEA recordings offers interesting insights into the contributions of various GABAAR subtypes/subgroups to cortical network activity and the putative functional interplay between these receptors in these neurons....... cortex by characterizing the effects induced by a wide selection of pharmacological tools at a plethora of activity parameters in microelectrode array (MEA) recordings. The basic characteristics of the primary cortical neurons used in the recordings were studied in some detail, and the expression levels...

Detection of Frauds and Other Non-technical Losses in Power Utilities using Smart Meters: A Review

Science.gov (United States)

Ahmad, Tanveer; Ul Hasan, Qadeer

2016-06-01

Analysis of losses in power distribution system and techniques to mitigate these are two active areas of research especially in energy scarce countries like Pakistan to increase the availability of power without installing new generation. Since total energy losses account for both technical losses (TL) as well as non-technical losses (NTLs). Utility companies in developing countries are incurring of major financial losses due to non-technical losses. NTLs lead to a series of additional losses, such as damage to the network (infrastructure and the reduction of network reliability) etc. The purpose of this paper is to perform an introductory investigation of non-technical losses in power distribution systems. Additionally, analysis of NTLs using consumer energy consumption data with the help of Linear Regression Analysis has been carried out. This data focuses on the Low Voltage (LV) distribution network, which includes: residential, commercial, agricultural and industrial consumers by using the monthly kWh interval data acquired over a period (one month) of time using smart meters. In this research different prevention techniques are also discussed to prevent illegal use of electricity in the distribution of electrical power system.

Application of artificial neural networks on the characterization of radioactive waste drums

International Nuclear Information System (INIS)

Potiens Junior, Ademar Jose; Hiromoto, Goro

2011-01-01

The methodology consist of system simulation of drum-detector by Monte Carlo for obtention of counting efficiency. The obtained data were treated and a neural artificial network (RNA) were constructed for evaluation of total activity of drum. For method evaluation measurements were performed in ten position parallel to the drum axis and the results submitted to the RNA. The developed methodology showed to be effective for isotopic characterization of gamma emitter radioactive wastes distributed in a heterogeneous way in a 200 litters drum. The objective of this work as to develop a methodology of analyse for quantification and localization of radionuclides not homogeneous distributed in a 200 liters drum based on the mathematical techniques

Stream-groundwater exchange and hydrologic turnover at the network scale

Science.gov (United States)

Covino, Tim; McGlynn, Brian; Mallard, John

2011-12-01

The exchange of water between streams and groundwater can influence stream water quality, hydrologic mass balances, and attenuate solute export from watersheds. We used conservative tracer injections (chloride, Cl-) across 10 stream reaches to investigate stream water gains and losses from and to groundwater at larger spatial and temporal scales than typically associated with hyporheic exchanges. We found strong relationships between reach discharge, median tracer velocity, and gross hydrologic loss across a range of stream morphologies and sizes in the 11.4 km2 Bull Trout Watershed of central ID. We implemented these empirical relationships in a numerical network model and simulated stream water gains and losses and subsequent fractional hydrologic turnover across the stream network. We found that stream gains and losses from and to groundwater can influence source water contributions and stream water compositions across stream networks. Quantifying proportional influences of source water contributions from runoff generation locations across the network on stream water composition can provide insight into the internal mechanisms that partially control the hydrologic and biogeochemical signatures observed along networks and at watershed outlets.

Characterization of ceramic materials using ultrasonic technique in the frequency domain and artificial networks

International Nuclear Information System (INIS)

Baroni, D.B.; Bittencourt, M.S.Q.; Pereira, C.M.N.A.

2008-01-01

The ceramic material characterization is very important to guarantee its mechanical properties. In the case of nuclear fuel (UO 2 ) the adequate porosity ensures its thermal efficiency and its structural integrity that contribute to the safety at nuclear power plants. The Ultrasound Laboratory of the Nuclear Engineering Institute (LABUS/IEN) has developed a technique to measure the porosity in ceramic materials. This technique uses ultrasound signal in the frequency domain and creates spectrum patterns related to the material porosity. Trained artificial neural networks recognizes these patterns and associates them to the porosities. In this work 20 pellets of Alumina were used with porosities in the same range used in the nuclear fuel (0.70% to 4.25%). In this case the used network was able to recognize the patterns of the pellets and to associate to the porosities with 100% of precision. It was possible to distinguished pellets with a difference of 0.01% of the porosity. (author)

New hybrid frequency reuse method for packet loss minimization in LTE network.

Science.gov (United States)

Ali, Nora A; El-Dakroury, Mohamed A; El-Soudani, Magdi; ElSayed, Hany M; Daoud, Ramez M; Amer, Hassanein H

2015-11-01

This paper investigates the problem of inter-cell interference (ICI) in Long Term Evolution (LTE) mobile systems, which is one of the main problems that causes loss of packets between the base station and the mobile station. Recently, different frequency reuse methods, such as soft and fractional frequency reuse, have been introduced in order to mitigate this type of interference. In this paper, minimizing the packet loss between the base station and the mobile station is the main concern. Soft Frequency Reuse (SFR), which is the most popular frequency reuse method, is examined and the amount of packet loss is measured. In order to reduce packet loss, a new hybrid frequency reuse method is implemented. In this method, each cell occupies the same bandwidth of the SFR, but the total system bandwidth is greater than in SFR. This will provide the new method with a lot of new sub-carriers from the neighboring cells to reduce the ICI which represents a big problem in many applications and causes a lot of packets loss. It is found that the new hybrid frequency reuse method has noticeable improvement in the amount of packet loss compared to SFR method in the different frequency bands. Traffic congestion management in Intelligent Transportation system (ITS) is one of the important applications that is affected by the packet loss due to the large amount of traffic that is exchanged between the base station and the mobile node. Therefore, it is used as a studied application for the proposed frequency reuse method and the improvement in the amount of packet loss reached 49.4% in some frequency bands using the new hybrid frequency reuse method.

BN-FLEMOps pluvial - A probabilistic multi-variable loss estimation model for pluvial floods

Science.gov (United States)

Roezer, V.; Kreibich, H.; Schroeter, K.; Doss-Gollin, J.; Lall, U.; Merz, B.

2017-12-01

Pluvial flood events, such as in Copenhagen (Denmark) in 2011, Beijing (China) in 2012 or Houston (USA) in 2016, have caused severe losses to urban dwellings in recent years. These floods are caused by storm events with high rainfall rates well above the design levels of urban drainage systems, which lead to inundation of streets and buildings. A projected increase in frequency and intensity of heavy rainfall events in many areas and an ongoing urbanization may increase pluvial flood losses in the future. For an efficient risk assessment and adaptation to pluvial floods, a quantification of the flood risk is needed. Few loss models have been developed particularly for pluvial floods. These models usually use simple waterlevel- or rainfall-loss functions and come with very high uncertainties. To account for these uncertainties and improve the loss estimation, we present a probabilistic multi-variable loss estimation model for pluvial floods based on empirical data. The model was developed in a two-step process using a machine learning approach and a comprehensive database comprising 783 records of direct building and content damage of private households. The data was gathered through surveys after four different pluvial flood events in Germany between 2005 and 2014. In a first step, linear and non-linear machine learning algorithms, such as tree-based and penalized regression models were used to identify the most important loss influencing factors among a set of 55 candidate variables. These variables comprise hydrological and hydraulic aspects, early warning, precaution, building characteristics and the socio-economic status of the household. In a second step, the most important loss influencing variables were used to derive a probabilistic multi-variable pluvial flood loss estimation model based on Bayesian Networks. Two different networks were tested: a score-based network learned from the data and a network based on expert knowledge. Loss predictions are made

Reactive power compensation and loss reduction in large industrial enterprises

Energy Technology Data Exchange (ETDEWEB)

Jovanovic, S; Gajic, B; Mijailovic, S [Institute Nikola Tesla, Beograd (Yugoslavia)

1991-12-01

This paper considers the reactive power compensation and the active power and energy loss reduction of large radial power networks in the Serbian mine and smelting industry. It gives an efficient optimization procedure for positioning and sizing capacitors in large industrial systems integrated with a simple network analysis method. (Author).

Estimation of furrow irrigation sediment loss using an artificial neural network

Science.gov (United States)

The area irrigated by furrow irrigation in the U.S. has been steadily decreasing but still represents about 20% of the total irrigated area in the U.S. Furrow irrigation sediment loss is a major water quality issue and a method for estimating sediment loss is needed to quantify the environmental imp...

Significant reduction of saturation magnetization and microwave-reflection loss in barium-natural ferrite via Nd3+ substitution

Science.gov (United States)

Widanarto, W.; Ardenti, E.; Ghoshal, S. K.; Kurniawan, C.; Effendi, M.; Cahyanto, W. T.

2018-06-01

To minimize the signal degradation, many electronic devices require efficient microwave absorbers with very low reflection-losses within the X-band. We prepared a series of trivalent neodymium-ion (Nd3+) substituted barium-natural ferrite using a modified solid-state reaction method. The effect of the Nd3+-ion content on the structure, surface morphology, magnetic properties, and microwave reflection loss was studied. The composites were characterized using X-ray diffraction, a vibrating sample magnetometer, scanning electron microscopy, and a vector network analyzer. The XRD patterns of the sample without Nd3+ reveal the presence of BaFe12O19 (hexagonal) and BaFe2O4 (rhombohedral) phases. Furthermore, a new hexagonal crystal phase of Ba6Nd2Fe4O15 appeared after substituting Nd3+. The average size of the prepared barium-natural ferrite particles was estimated to be between 0.4 and 0.8 μm. Both saturation magnetization and microwave reflection losses of these barium-ferrites were significantly reduced by increasing the Nd3+ content.

Optimal Fragile Financial Networks

NARCIS (Netherlands)

Castiglionesi, F.; Navarro, N.

2007-01-01

We study a financial network characterized by the presence of depositors, banks and their shareholders. Belonging to a financial network is beneficial for both the depositors and banks' shareholders since the return to investment increases with the number of banks connected. However, the network is

Traffic Dynamics of Computer Networks

Science.gov (United States)

Fekete, Attila

2008-10-01

Two important aspects of the Internet, namely the properties of its topology and the characteristics of its data traffic, have attracted growing attention of the physics community. My thesis has considered problems of both aspects. First I studied the stochastic behavior of TCP, the primary algorithm governing traffic in the current Internet, in an elementary network scenario consisting of a standalone infinite-sized buffer and an access link. The effect of the fast recovery and fast retransmission (FR/FR) algorithms is also considered. I showed that my model can be extended further to involve the effect of link propagation delay, characteristic of WAN. I continued my thesis with the investigation of finite-sized semi-bottleneck buffers, where packets can be dropped not only at the link, but also at the buffer. I demonstrated that the behavior of the system depends only on a certain combination of the parameters. Moreover, an analytic formula was derived that gives the ratio of packet loss rate at the buffer to the total packet loss rate. This formula makes it possible to treat buffer-losses as if they were link-losses. Finally, I studied computer networks from a structural perspective. I demonstrated through fluid simulations that the distribution of resources, specifically the link bandwidth, has a serious impact on the global performance of the network. Then I analyzed the distribution of edge betweenness in a growing scale-free tree under the condition that a local property, the in-degree of the "younger" node of an arbitrary edge, is known in order to find an optimum distribution of link capacity. The derived formula is exact even for finite-sized networks. I also calculated the conditional expectation of edge betweenness, rescaled for infinite networks.

Entropy of network ensembles

Science.gov (United States)

Bianconi, Ginestra

2009-03-01

In this paper we generalize the concept of random networks to describe network ensembles with nontrivial features by a statistical mechanics approach. This framework is able to describe undirected and directed network ensembles as well as weighted network ensembles. These networks might have nontrivial community structure or, in the case of networks embedded in a given space, they might have a link probability with a nontrivial dependence on the distance between the nodes. These ensembles are characterized by their entropy, which evaluates the cardinality of networks in the ensemble. In particular, in this paper we define and evaluate the structural entropy, i.e., the entropy of the ensembles of undirected uncorrelated simple networks with given degree sequence. We stress the apparent paradox that scale-free degree distributions are characterized by having small structural entropy while they are so widely encountered in natural, social, and technological complex systems. We propose a solution to the paradox by proving that scale-free degree distributions are the most likely degree distribution with the corresponding value of the structural entropy. Finally, the general framework we present in this paper is able to describe microcanonical ensembles of networks as well as canonical or hidden-variable network ensembles with significant implications for the formulation of network-constructing algorithms.

Fibre optic connectors with high-return-loss performance

Science.gov (United States)

Knott, Michael P.; Johnson, R.; Cooke, K.; Longhurst, P. C.

1990-09-01

This paper describes the development of a single mode fibre optic connector with high return loss performance without the use of index matching. Partial reflection of incident light at a fibre optic connector interface is a recognised problem where the result can be increased noise and waveform distortion. This is particularly important for video transmission in subscriber networks which requires a high signal to noise ratio. A number of methods can be used to improve the return loss. The method described here uses a process which angles the connector endfaces. Measurements show typical return losses of -55dB can be achieved for an end angle of 6 degrees. Insertion loss results are also presented.

Latent geometry of bipartite networks

Science.gov (United States)

Kitsak, Maksim; Papadopoulos, Fragkiskos; Krioukov, Dmitri

2017-03-01

Despite the abundance of bipartite networked systems, their organizing principles are less studied compared to unipartite networks. Bipartite networks are often analyzed after projecting them onto one of the two sets of nodes. As a result of the projection, nodes of the same set are linked together if they have at least one neighbor in common in the bipartite network. Even though these projections allow one to study bipartite networks using tools developed for unipartite networks, one-mode projections lead to significant loss of information and artificial inflation of the projected network with fully connected subgraphs. Here we pursue a different approach for analyzing bipartite systems that is based on the observation that such systems have a latent metric structure: network nodes are points in a latent metric space, while connections are more likely to form between nodes separated by shorter distances. This approach has been developed for unipartite networks, and relatively little is known about its applicability to bipartite systems. Here, we fully analyze a simple latent-geometric model of bipartite networks and show that this model explains the peculiar structural properties of many real bipartite systems, including the distributions of common neighbors and bipartite clustering. We also analyze the geometric information loss in one-mode projections in this model and propose an efficient method to infer the latent pairwise distances between nodes. Uncovering the latent geometry underlying real bipartite networks can find applications in diverse domains, ranging from constructing efficient recommender systems to understanding cell metabolism.

Energy losses of superconducting power transmission cables in the grid

DEFF Research Database (Denmark)

Østergaard, Jacob; Okholm, Jan; Lomholt, Karin

2001-01-01

One of the obvious motives for development of superconducting power transmission cables is reduction of transmission losses. Loss components in superconducting cables as well as in conventional cables have been examined. These losses are used for calculating the total energy losses of conventional...... as well as superconducting cables when they are placed in the electric power transmission network. It is concluded that high load connections are necessary to obtain energy saving by the use of HTSC cables. For selected high load connections, an energy saving of 40% is expected. It is shown...

Measurements by a Vector Network Analyzer at 325 to 508 GHz

Science.gov (United States)

Fung, King Man; Samoska, Lorene; Chattopadhyay, Goutam; Gaier, Todd; Kangaslahti, Pekka; Pukala, David; Lau, Yuenie; Oleson, Charles; Denning, Anthony

2008-01-01

Recent experiments were performed in which return loss and insertion loss of waveguide test assemblies in the frequency range from 325 to 508 GHz were measured by use of a swept-frequency two-port vector network analyzer (VNA) test set. The experiments were part of a continuing effort to develop means of characterizing passive and active electronic components and systems operating at ever increasing frequencies. The waveguide test assemblies comprised WR-2.2 end sections collinear with WR-3.3 middle sections. The test set, assembled from commercially available components, included a 50-GHz VNA scattering- parameter test set and external signal synthesizers, augmented with recently developed frequency extenders, and further augmented with attenuators and amplifiers as needed to adjust radiofrequency and intermediate-frequency power levels between the aforementioned components. The tests included line-reflect-line calibration procedures, using WR-2.2 waveguide shims as the "line" standards and waveguide flange short circuits as the "reflect" standards. Calibrated dynamic ranges somewhat greater than about 20 dB for return loss and 35 dB for insertion loss were achieved. The measurement data of the test assemblies were found to substantially agree with results of computational simulations.

NQAR: Network Quality Aware Routing in Error-Prone Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Jaewon Choi

2010-01-01

Full Text Available We propose a network quality aware routing (NQAR mechanism to provide an enabling method of the delay-sensitive data delivery over error-prone wireless sensor networks. Unlike the existing routing methods that select routes with the shortest arrival latency or the minimum hop count, the proposed scheme adaptively selects the route based on the network qualities including link errors and collisions with minimum additional complexity. It is designed to avoid the paths with potential noise and collision that may cause many non-deterministic backoffs and retransmissions. We propose a generic framework to select a minimum cost route that takes the packet loss rate and collision history into account. NQAR uses a data centric approach to estimate a single-hop delay based on processing time, propagation delay, packet loss rate, number of backoffs, and the retransmission timeout between two neighboring nodes. This enables a source node to choose the shortest expected end-to-end delay path to send a delay-sensitive data. The experiment results show that NQAR reduces the end-to-end transfer delay up to approximately 50% in comparison with the latency-based directed diffusion and the hop count-based directed diffusion under the error-prone network environments. Moreover, NQAR shows better performance than those routing methods in terms of jitter, reachability, and network lifetime.

3D characterisation of RCF crack networks

Directory of Open Access Journals (Sweden)

Ahlström Johan

2014-06-01

Full Text Available Rolling contact fatigue (RCF damage is becoming more frequent with increased traffic and loading conditions in the railway industry. Defects which are characterized by a two-lobe darkened surface and a V-shaped surface-breaking crack are often so-called squats. The origination and propagation of squats in railway rails is the topic of many recent studies; the associated crack networks develop with complicated geometry near the surface of rails that is difficult to characterise using most non-destructive methods. The cracks can be examined with repeated metallographic sectioning, but the process is time-consuming and destructive. In order to reduce time, as well as information and material loss, high-resolution and high-energy X-ray imaging of railway rails was done in the current study. Combining the exposures from a range of angles using image analysis, a 3D representation of the complex crack network is achieved. The latter was complemented with metallographic sectioning to determine the accuracy of prediction of the geometrical reconstruction.

Issues in characterizing resting energy expenditure in obesity and after weight loss

Directory of Open Access Journals (Sweden)

Anja eBosy-Westphal

2013-03-01

Full Text Available Normalization of resting energy expenditure (REE for body composition using the 2-compartment model (fat mass, FM and fat-free mass, FFM has inherent limitations for the interpretation of REE and may lead to erroneous conclusions when comparing people with a wide range of adiposity as well as before and after substantial weight loss. We compared different methods of REE normalization: (i for FFM and FM (ii by the inclusion of %FM as a measure of adiposity and (iii based on organ and tissue masses. Results were compared between healthy subjects with different degrees of adiposity as well as within subject before and after weight loss. Normalizing REE from an REE vs. FFM and FM equation that (i was derived in obese participants and applied to lean people or (ii was derived before weight loss and applied after weight loss leads to the erroneous conclusion of a lower metabolic rate (i in lean persons and (ii after weight loss. This is revealed by the normalization of REE for organ and tissue masses that was not significantly different between lean and obese or between baseline and after weight loss. There is evidence for an increasing specific metabolic rate of FFM with increasing %FM that could be explained by a higher contribution of liver, kidney and heart mass to FFM in obesity. Using REE vs. FFM and FM equations specific for different levels of adiposity (% fat mass eliminated differences in REE before and after weight loss in women. In conclusion, the most established method for normalization of REE based on FFM and FM may lead to spurious conclusions about metabolic rate in obesity and the phenomenon of weight loss-associated adaptive thermogenesis. Using % fat mass-specific REE prediction from FFM and FM in kg may improve the normalization of REE when subjects with wide differences in % fat mass are investigated.

Improving Network Performance with Affinity based Mobility Model in Opportunistic Network

OpenAIRE

Suvadip Batabyal; Parama Bhaumik

2012-01-01

Opportunistic network is a type of Delay Tolerant Network which is characterized by intermittent connectivity amongst the nodes and communication largely depends upon the mobility of the participating nodes. The network being highly dynamic, traditional MANET protocols cannot be applied and the nodes must adhere to store-carry-forward mechanism. Nodes do not have the information about the network topology, number of participating nodes and the location of the destination node. Hence, message ...

Characterization and detection of thermoacoustic combustion oscillations based on statistical complexity and complex-network theory

Science.gov (United States)

Murayama, Shogo; Kinugawa, Hikaru; Tokuda, Isao T.; Gotoda, Hiroshi

2018-02-01

We present an experimental study on the characterization of dynamic behavior of flow velocity field during thermoacoustic combustion oscillations in a turbulent confined combustor from the viewpoints of statistical complexity and complex-network theory, involving detection of a precursor of thermoacoustic combustion oscillations. The multiscale complexity-entropy causality plane clearly shows the possible presence of two dynamics, noisy periodic oscillations and noisy chaos, in the shear layer regions (1) between the outer recirculation region in the dump plate and a recirculation flow in the wake of the centerbody and (2) between the outer recirculation region in the dump plate and a vortex breakdown bubble away from the centerbody. The vertex strength in the turbulence network and the community structure of the vorticity field can identify the vortical interactions during thermoacoustic combustion oscillations. Sequential horizontal visibility graph motifs are useful for capturing a precursor of themoacoustic combustion oscillations.

Characterization of nanocellulose reinforced semi-interpenetrating polymer network of poly(vinyl alcohol) & polyacrylamide composite films.

Science.gov (United States)

Mandal, Arup; Chakrabarty, Debabrata

2015-12-10

Semi-interpenetrating polymer network (semi-IPN) of poly(vinyl alcohol)/polyacrylamide was reinforced with various doses of nanocellulose. The different composite films thus prepared were characterized with respect to their mechanical, thermal, morphological and barrier properties. The composite film containing 5 wt.% of nanocellulose showed the highest tensile strength. The semi-interpenetrating polymer network of poly(vinyl alcohol)/polyacrylamide; and its various composites with nanocellulose were almost identical in their thermal stability. Each of the composites however exhibited much superior stability with respect to the linear poly(vinyl alcohol) and crosslinked polyacrylamide. The scanning electron microscopy (SEM) and atomic force microscopy (AFM) studies exhibited phase separated morphology where agglomerates of nanocellulose were found to be dispersed in the matrix of the semi-IPN. The moisture vapor transmission rate (MVTR) was the lowest for the film containing 5 wt.% of nanocellulose. Copyright © 2015 Elsevier Ltd. All rights reserved.

Latest developments for a computer aided thermohydraulic network

International Nuclear Information System (INIS)

Alemberti, A.; Graziosi, G.; Mini, G.; Susco, M.

1999-01-01

Thermohydraulic networks are I-D systems characterized by a small number of basic components (pumps, valves, heat exchangers, etc) connected by pipes and limited spatially by a defined number of boundary conditions (tanks, atmosphere, etc). The network system is simulated by the well known computer program RELAPS/mod3. Information concerning the network geometry component behaviour, initial and boundary conditions are usually supplied to the RELAPS code using an ASCII input file by means of 'input cards'. CATNET (Computer Aided Thermalhydraulic NETwork) is a graphically user interface that, under specific user guidelines which completely define its range of applicability, permits a very high level of standardization and simplification of the RELAPS/mod3 input deck development process as well as of the output processing. The characteristics of the components (pipes, valves, pumps etc), defining the network system can be entered through CATNET. The CATNET interface is provided by special functions to compute form losses in the most typical bending and branching configurations. When the input of all system components is ready, CATNET is able to generate the RELAPS/mod3 input file. Finally, by means of CATNET, the RELAPS/mod3 code can be run and its output results can be transformed to an intuitive display form. The paper presents an example of application of the CATNET interface as well as the latest developments which greatly simplified the work of the users and allowed to reduce the possibility of input errors. (authors)

Characterization of the loss allocation techniques for radial systems with distributed generation

International Nuclear Information System (INIS)

Carpaneto, Enrico; Chicco, Gianfranco; Sumaili Akilimali, Jean

2008-01-01

In the restructured electricity industry, meaningful loss allocation methods are required in order to send correct signals to the market taking into account the location and characteristics of loads and generations, including the local sources forming the distributed generation (DG). This paper addresses the issues related to loss allocation in radial distribution systems with DG, with a three-fold focus. First, the key differences in the formulation of the loss allocation problem for radial distribution systems with respect to transmission systems are discussed, specifying the modeling and computational issues concerning the treatment of the slack node in radial distribution systems. Then, the characteristics of derivative-based and circuit-based loss allocation techniques are presented and compared, illustrating the arrangements used for adapting the various techniques to be applied to radial distribution systems with DG. Finally, the effects of introducing voltage-controllable local generation on the calculation of the loss allocation coefficients are discussed, proposing the adoption of a ''reduced'' representation of the system capable of taking into proper account the characteristics of the nodes containing voltage-controllable DG units. Numerical results are provided to show the time evolution of the loss allocation coefficients for distribution systems with variable load and local generation patterns. (author)

An Assessment of Direct and Indirect Economic Losses of Climatic Extreme Events

Science.gov (United States)

Otto, C.; Willner, S. N.; Wenz, L.; Levermann, A.

2015-12-01

Risk of extreme weather events like storms, heat extremes, and floods has already risen due to anthropogenic climate change and is likely to increase further under future global warming. Additionally, the structure of the global economy has changed importantly in the last decades. In the process of globalization, local economies have become more and more interwoven forming a complex network. Together with a trend towards lean production, this has resulted in a strong dependency of local manufacturers on global supply and value added chains, which may render the economic network more vulnerable to climatic extremes; outages of local manufacturers trigger indirect losses, which spread along supply chains and can even outstrip direct losses. Accordingly, in a comprehensive climate risk assessment these inter-linkages should be considered. Here, we present acclimate, an agent based dynamic damage propagation model. Its agents are production and consumption sites, which are interlinked by economic flows accounting for the complexity as well as the heterogeneity of the global supply network. Assessing the economic response on the timescale of the adverse event, the model permits to study temporal and spatial evolution of indirect production losses during the disaster and in the subsequent recovery phase of the economy. In this study, we focus on the dynamic economic resilience defined here as the ratio of direct to total losses. This implies that the resilience of the system under consideration is low if the high indirect losses are high. We find and assess a nonlinear dependence of the resilience on the disaster size. Further, we analyze the influence of the network structure upon resilience and discuss the potential of warehousing as an adaptation option.

Human-Centric Wireless Communication Networks

OpenAIRE

Cavallari, Riccardo

2016-01-01

This thesis covers two main topics: the design and performance evaluation of Wireless Body Area Networks (WBANs), and the simulation and mathematical modeling of Delay Tolerant Networks (DTNs). Different Medium Access Control (MAC) protocols for WBANs are implemented on dedicated hardware in order to evaluate, through extensive measurement campaigns, the performance of the network in terms of packet loss rate, delay and energy consumption. Novel solutions to cope with bo...

Characterizing Signals within Lesions and Mapping Brain Network Connectivity After Traumatic Axonal Injury: A 7 Tesla Resting-State FMRI Study.

Science.gov (United States)

Lee, Seul; Polimeni, Jonathan R; Price, Collin M; Edlow, Brian L; McNab, Jennifer A

2018-04-18

Resting-state functional magnetic resonance imaging (RS-FMRI) has been widely used to map brain functional connectivity, but it is unclear how to probe connectivity within and around lesions. Here we characterize RS-FMRI signal time-course properties and evaluate different seed placements within and around hemorrhagic traumatic axonal injury lesions. RS-FMRI was performed on a 7 Tesla scanner in a patient who recovered consciousness after traumatic coma and in three healthy controls. Eleven lesions in the patient were characterized in terms of: 1) temporal signal-to-noise ratio (tSNR); 2) physiological noise, through comparison of noise regressors derived from the white matter (WM), cerebrospinal fluid (CSF) and gray matter (GM); and 3) seed-based functional connectivity. Temporal SNR at the center of the lesions was 38.3% and 74.1% lower compared to the same region in the contralesional hemisphere of the patient and in the ipsilesional hemispheres of the controls, respectively. Within the lesions, WM noise was more prominent than CSF and GM noise. Lesional seeds did not produce discernable networks, but seeds in the contralesional hemisphere revealed networks whose nodes appeared to be shifted or obscured due to overlapping or nearby lesions. Single-voxel seed analysis demonstrated that placing a seed within a lesion's periphery was necessary to identify networks associated with the lesion region. These findings provide evidence of resting-state network changes in the human brain after recovery from traumatic coma. Further, we show that seed placement within a lesion's periphery or in the contralesional hemisphere may be necessary for network identification in patients with hemorrhagic traumatic axonal injury.

Normalised flood losses in Europe: 1970-2006

Science.gov (United States)

Barredo, J. I.

2009-02-01

This paper presents an assessment of normalised flood losses in Europe for the period 1970-2006. Normalisation provides an estimate of the losses that would occur if the floods from the past take place under current societal conditions. Economic losses from floods are the result of both societal and climatological factors. Failing to adjust for time-variant socio-economic factors produces loss amounts that are not directly comparable over time, but rather show an ever-growing trend for purely socio-economic reasons. This study has used available information on flood losses from the Emergency Events Database (EM-DAT) and the Natural Hazards Assessment Network (NATHAN). Following the conceptual approach of previous studies, we normalised flood losses by considering the effects of changes in population, wealth, and inflation at the country level. Furthermore, we removed inter-country price differences by adjusting the losses for purchasing power parities (PPP). We assessed normalised flood losses in 31 European countries. These include the member states of the European Union, Norway, Switzerland, Croatia, and the Former Yugoslav Republic of Macedonia. Results show no detectable sign of human-induced climate change in normalised flood losses in Europe. The observed increase in the original flood losses is mostly driven by societal factors.

Individual Hearing Loss

Directory of Open Access Journals (Sweden)

Sébastien Santurette

2016-06-01

Full Text Available It is well-established that hearing loss does not only lead to a reduction of hearing sensitivity. Large individual differences are typically observed among listeners with hearing impairment in a wide range of suprathreshold auditory measures. In many cases, audiometric thresholds cannot fully account for such individual differences, which make it challenging to find adequate compensation strategies in hearing devices. How to characterize, model, and compensate for individual hearing loss were the main topics of the fifth International Symposium on Auditory and Audiological Research (ISAAR, held in Nyborg, Denmark, in August 2015. The following collection of papers results from some of the work that was presented and discussed at the symposium.

Cultured Neural Networks: Optimization of Patterned Network Adhesiveness and Characterization of their Neural Activity

Directory of Open Access Journals (Sweden)

W. L. C. Rutten

2006-01-01

Full Text Available One type of future, improved neural interface is the “cultured probe”. It is a hybrid type of neural information transducer or prosthesis, for stimulation and/or recording of neural activity. It would consist of a microelectrode array (MEA on a planar substrate, each electrode being covered and surrounded by a local circularly confined network (“island” of cultured neurons. The main purpose of the local networks is that they act as biofriendly intermediates for collateral sprouts from the in vivo system, thus allowing for an effective and selective neuron–electrode interface. As a secondary purpose, one may envisage future information processing applications of these intermediary networks. In this paper, first, progress is shown on how substrates can be chemically modified to confine developing networks, cultured from dissociated rat cortex cells, to “islands” surrounding an electrode site. Additional coating of neurophobic, polyimide-coated substrate by triblock-copolymer coating enhances neurophilic-neurophobic adhesion contrast. Secondly, results are given on neuronal activity in patterned, unconnected and connected, circular “island” networks. For connected islands, the larger the island diameter (50, 100 or 150 μm, the more spontaneous activity is seen. Also, activity may show a very high degree of synchronization between two islands. For unconnected islands, activity may start at 22 days in vitro (DIV, which is two weeks later than in unpatterned networks.

"De-Randomizing" Congestion Losses to Improve TCP Performance over Wired-Wireless Networks

National Research Council Canada - National Science Library

Biaz, Saad; Vaidya, Nitin H

2004-01-01

.... This paper proposes a simple biased queue management scheme that "de-randomizes" congestion losses and enables a TCP receiver to diagnose accurately the cause of a loss and inform the TCP sender to react appropriately...

Water Loss Management: Tools and Methods for Developing Countries

OpenAIRE

Mutikanga, H.E.

2012-01-01

Water utilities in developing countries are struggling to provide customers with a reliable level of service due to their peculiar water distribution characteristics including poorly zoned networks with irregular supply operating under restricted budgets. These unique conditions demand unique tools and methods for water loss control. Water loss management: Tools and Methods for Developing Countries provide a decision support toolbox (appropriate tools and methodologies) for assessing, quantif...

Spatial Characterization of Radio Propagation Channel in Urban Vehicle-to-Infrastructure Environments to Support WSNs Deployment

Directory of Open Access Journals (Sweden)

Fausto Granda

2017-06-01

Full Text Available Vehicular ad hoc Networks (VANETs enable vehicles to communicate with each other as well as with roadside units (RSUs. Although there is a significant research effort in radio channel modeling focused on vehicle-to-vehicle (V2V, not much work has been done for vehicle-to-infrastructure (V2I using 3D ray-tracing tools. This work evaluates some important parameters of a V2I wireless channel link such as large-scale path loss and multipath metrics in a typical urban scenario using a deterministic simulation model based on an in-house 3D Ray-Launching (3D-RL algorithm at 5.9 GHz. Results show the high impact that the spatial distance; link frequency; placement of RSUs; and factors such as roundabout, geometry and relative position of the obstacles have in V2I propagation channel. A detailed spatial path loss characterization of the V2I channel along the streets and avenues is presented. The 3D-RL results show high accuracy when compared with measurements, and represent more reliably the propagation phenomena when compared with analytical path loss models. Performance metrics for a real test scenario implemented with a VANET wireless sensor network implemented ad-hoc are also described. These results constitute a starting point in the design phase of Wireless Sensor Networks (WSNs radio-planning in the urban V2I deployment in terms of coverage.

Theory of spatial networks

Energy Technology Data Exchange (ETDEWEB)

Watanabe, T

1983-01-01

A new framework of synchronous parallel processing systems called spatial networks is examined, in which the family of all cellular automata is included perfectly. This framework is free from the two restrictions of cellular automata of which one is the finiteness of the set of states of a cell and the other is the countability of an array space. Throughout this article, the relationships between function and structure of spatial networks are considered. First, the necessary and sufficient condition for spatial networks to be uniformly interconnected is given. That for spatial networks to be finitely interconnected is also given with a topological approach. The characterization theorem of cellular automata comes from these results. Second, it is shown that finitely and uniformly interconnected linear spatial networks can be characterized by the convolution form. Last, the conditions for their global mappings to be injective or surjective are discussed. 10 references.

Geometry of river networks. III. Characterization of component connectivity

International Nuclear Information System (INIS)

Dodds, Peter Sheridan; Rothman, Daniel H.

2001-01-01

Essential to understanding the overall structure of river networks is a knowledge of their detailed architecture. Here we explore the presence of randomness in river network structure and the details of its consequences. We first show that an averaged view of network architecture is provided by a proposed self-similarity statement about the scaling of drainage density, a local measure of stream concentration. This scaling of drainage density is shown to imply Tokunaga's law, a description of the scaling of side branch abundance along a given stream, as well as a scaling law for stream lengths. We then consider fluctuations in drainage density and consequently the numbers of side branches. Data are analyzed for the Mississippi River basin and a model of random directed networks. Numbers of side streams are found to follow exponential distributions, as are intertributary distances along streams. Finally, we derive a joint variation of side stream abundance with stream length, affording a full description of fluctuations in network structure. Fluctuations in side stream numbers are shown to be a direct result of fluctuations in stream lengths. This is the last paper in a series of three on the geometry of river networks

On the Packet Loss Correlation in Wireless Mesh Networks

DEFF Research Database (Denmark)

Pahlevani, Peyman; Cabrera Guerrero, Juan Alberto; Roetter, Daniel Enrique Lucani

2014-01-01

/or multi-path routing approaches as well as network coding (NC) subgraph selection problems (routing in NC). This paper proposes simple channel models to incorporate the effect of correlation between receivers in a parametric fashion and supports them with a measurement campaign that leverages various...

Speech perception in noise in unilateral hearing loss

OpenAIRE

Mondelli, Maria Fernanda Capoani Garcia; dos Santos, Marina de Marchi; José, Maria Renata

2016-01-01

ABSTRACT INTRODUCTION: Unilateral hearing loss is characterized by a decrease of hearing in one ear only. In the presence of ambient noise, individuals with unilateral hearing loss are faced with greater difficulties understanding speech than normal listeners. OBJECTIVE: To evaluate the speech perception of individuals with unilateral hearing loss in speech perception with and without competitive noise, before and after the hearing aid fitting process. METHODS: The study included 30 adu...

One-step synthesis and characterization of polyaniline nanofiber/silver nanoparticle composite networks as antibacterial agents.

Science.gov (United States)

Poyraz, Selcuk; Cerkez, Idris; Huang, Tung Shi; Liu, Zhen; Kang, Litao; Luo, Jujie; Zhang, Xinyu

2014-11-26

Through a facile and effective seeding polymerization reaction via a one-step redox/complexation process, which took place in aqueous medium at ambient temperature, silver nanoparticles (Ag NPs) embedded polyaniline nanofiber (PANI NF) networks were synthesized as antibacterial agents. During the reaction, not only NF morphology formation of the resulting conducting polymers (CPs) but also amplification of the aqueous silver nitrate (AgNO3) solutions' oxidative potentials were managed by vanadium pentoxide (V2O5) sol-gel nanofibers, which acted as well-known nanofibrous seeding agents and the auxiliary oxidative agent at the same time. The PANI/Ag nanocomposites were proven to exhibit excellent antibacterial property against both Gram-negative Escherichia coli and Gram-positive Staphylococcus aureus. Antibacterial property performance and average life span of the nanocomposite network were optimized through the homogeneous distribution/embedment of Ag NPs within one-dimensional (1-D) PANI NF matrix. The antibacterial efficacy tests and nanocomposite material characterization results further indicated that the sole components of PANI/Ag have a synergistic effect to each other in terms of antibacterial property. Thus, this well-known catalytic seeding approach via a one-step oxidative polymerization reaction can be considered as a general methodology and a substantial fabrication tool to synthesize Ag NP decorated nanofibrillar PANI networks as advanced antibacterial agents.

Perioperative Vision Loss in Cervical Spinal Surgery.

Science.gov (United States)

Gabel, Brandon C; Lam, Arthur; Chapman, Jens R; Oskouian, Rod J; Nassr, Ahmad; Currier, Bradford L; Sebastian, Arjun S; Arnold, Paul M; Hamilton, Steven R; Fehlings, Michael G; Mroz, Thomas E; Riew, K Daniel

2017-04-01

Retrospective multicenter case series. To assess the rate of perioperative vision loss following cervical spinal surgery. Medical records for 17 625 patients from 21 high-volume surgical centers from the AOSpine North America Clinical Research Network who received cervical spine surgery (levels from C2 to C7) between January 1, 2005, and December 31, 2011, inclusive, were reviewed to identify occurrences of vision loss following surgery. Of the 17 625 patients in the registry, there were 13 946 patients assessed for the complication of blindness. There were 9591 cases that involved only anterior surgical approaches; the remaining 4355 cases were posterior and/or circumferential fusions. There were no cases of blindness or vision loss in the postoperative period reported during the sampling period. Perioperative vision loss following cervical spinal surgery is exceedingly rare.

Segmentation of nanotomographic cortical bone images for quantitative characterization of the osteoctyte lacuno-canalicular network

Energy Technology Data Exchange (ETDEWEB)

Ciani, A.; Kewish, C. M. [Synchrotron Soleil, L’Orme des Merisiers, 91192 Saint-Aubin (France); Guizar-Sicairos, M.; Diaz, A.; Holler, M. [Paul Scherrer Institut, 5232 Villigen PSI (Switzerland); Pallu, S.; Achiou, Z.; Jennane, R.; Toumi, H.; Lespessailles, E. [Univ Orléans, I3MTO, Ea 4708, 45000 Orléans (France)

2016-01-28

A newly developed data processing method able to characterize the osteocytes lacuno-canalicular network (LCN) is presented. Osteocytes are the most abundant cells in the bone, living in spaces called lacunae embedded inside the bone matrix and connected to each other with an extensive network of canals that allows for the exchange of nutrients and for mechanotransduction functions. The geometrical three-dimensional (3D) architecture is increasingly thought to be related to the macroscopic strength or failure of the bone and it is becoming the focus for investigating widely spread diseases such as osteoporosis. To obtain 3D LCN images non-destructively has been out of reach until recently, since tens-of-nanometers scale resolution is required. Ptychographic tomography was validated for bone imaging in [1], showing clearly the LCN. The method presented here was applied to 3D ptychographic tomographic images in order to extract morphological and geometrical parameters of the lacuno-canalicular structures.

Video Quality Prediction Models Based on Video Content Dynamics for H.264 Video over UMTS Networks

Directory of Open Access Journals (Sweden)

Asiya Khan

2010-01-01

Full Text Available The aim of this paper is to present video quality prediction models for objective non-intrusive, prediction of H.264 encoded video for all content types combining parameters both in the physical and application layer over Universal Mobile Telecommunication Systems (UMTS networks. In order to characterize the Quality of Service (QoS level, a learning model based on Adaptive Neural Fuzzy Inference System (ANFIS and a second model based on non-linear regression analysis is proposed to predict the video quality in terms of the Mean Opinion Score (MOS. The objective of the paper is two-fold. First, to find the impact of QoS parameters on end-to-end video quality for H.264 encoded video. Second, to develop learning models based on ANFIS and non-linear regression analysis to predict video quality over UMTS networks by considering the impact of radio link loss models. The loss models considered are 2-state Markov models. Both the models are trained with a combination of physical and application layer parameters and validated with unseen dataset. Preliminary results show that good prediction accuracy was obtained from both the models. The work should help in the development of a reference-free video prediction model and QoS control methods for video over UMTS networks.

Dimensioning Method for Conversational Video Applications in Wireless Convergent Networks

Directory of Open Access Journals (Sweden)

Raquel Perez Leal

2007-12-01

Full Text Available New convergent services are becoming possible, thanks to the expansion of IP networks based on the availability of innovative advanced coding formats such as H.264, which reduce network bandwidth requirements providing good video quality, and the rapid growth in the supply of dual-mode WiFi cellular terminals. This paper provides, first, a comprehensive subject overview as several technologies are involved, such as medium access protocol in IEEE802.11, H.264 advanced video coding standards, and conversational application characterization and recommendations. Second, the paper presents a new and simple dimensioning model of conversational video over wireless LAN. WLAN is addressed under the optimal network throughput and the perspective of video quality. The maximum number of simultaneous users resulting from throughput is limited by the collisions taking place in the shared medium with the statistical contention protocol. The video quality is conditioned by the packet loss in the contention protocol. Both approaches are analyzed within the scope of the advanced video codecs used in conversational video over IP, to conclude that conversational video dimensioning based on network throughput is not enough to ensure a satisfactory user experience, and video quality has to be taken also into account. Finally, the proposed model has been applied to a real-office scenario.

Dimensioning Method for Conversational Video Applications in Wireless Convergent Networks

Directory of Open Access Journals (Sweden)

Alonso JoséI

2008-01-01

Full Text Available Abstract New convergent services are becoming possible, thanks to the expansion of IP networks based on the availability of innovative advanced coding formats such as H.264, which reduce network bandwidth requirements providing good video quality, and the rapid growth in the supply of dual-mode WiFi cellular terminals. This paper provides, first, a comprehensive subject overview as several technologies are involved, such as medium access protocol in IEEE802.11, H.264 advanced video coding standards, and conversational application characterization and recommendations. Second, the paper presents a new and simple dimensioning model of conversational video over wireless LAN. WLAN is addressed under the optimal network throughput and the perspective of video quality. The maximum number of simultaneous users resulting from throughput is limited by the collisions taking place in the shared medium with the statistical contention protocol. The video quality is conditioned by the packet loss in the contention protocol. Both approaches are analyzed within the scope of the advanced video codecs used in conversational video over IP, to conclude that conversational video dimensioning based on network throughput is not enough to ensure a satisfactory user experience, and video quality has to be taken also into account. Finally, the proposed model has been applied to a real-office scenario.

Parameter-free Network Sparsification and Data Reduction by Minimal Algorithmic Information Loss

KAUST Repository

Zenil, Hector; Kiani, Narsis A.; Tegner, Jesper

2018-01-01

The study of large and complex datasets, or big data, organized as networks has emerged as one of the central challenges in most areas of science and technology. Cellular and molecular networks in biology is one of the prime examples. Henceforth, a

CMOS Silicon-on-Sapphire RF Tunable Matching Networks

Directory of Open Access Journals (Sweden)

Chamseddine Ahmad

2006-01-01

Full Text Available This paper describes the design and optimization of an RF tunable network capable of matching highly mismatched loads to 50 at 1.9 GHz. Tuning was achieved using switched capacitors with low-loss, single-transistor switches. Simulations show that the performance of the matching network depends strongly on the switch performances and on the inductor losses. A 0.5 m silicon-on-sapphire (SOS CMOS technology was chosen for network implementation because of the relatively high-quality monolithic inductors achievable in the process. The matching network provides very good matching for inductive loads, and acceptable matching for highly capacitive loads. A 1 dB compression point greater than dBm was obtained for a wide range of load impedances.

Analysis of critical operating conditions for LV distribution networks with microgrids

Science.gov (United States)

Zehir, M. A.; Batman, A.; Sonmez, M. A.; Font, A.; Tsiamitros, D.; Stimoniaris, D.; Kollatou, T.; Bagriyanik, M.; Ozdemir, A.; Dialynas, E.

2016-11-01

Increase in the penetration of Distributed Generation (DG) in distribution networks, raises the risk of voltage limit violations while contributing to line losses. Especially in low voltage (LV) distribution networks (secondary distribution networks), impacts of active power flows on the bus voltages and on the network losses are more dominant. As network operators must meet regulatory limitations, they have to take into account the most critical operating conditions in their systems. In this study, it is aimed to present the impact of the worst operation cases of LV distribution networks comprising microgrids. Simulation studies are performed on a field data-based virtual test-bed. The simulations are repeated for several cases consisting different microgrid points of connection with different network loading and microgrid supply/demand conditions.

The spread of sleep loss influences drug use in adolescent social networks.

Directory of Open Access Journals (Sweden)

Sara C Mednick

2010-03-01

Full Text Available Troubled sleep is a commonly cited consequence of adolescent drug use, but it has rarely been studied as a cause. Nor have there been any studies of the extent to which sleep behavior can spread in social networks from person to person to person. Here we map the social networks of 8,349 adolescents in order to study how sleep behavior spreads, how drug use behavior spreads, and how a friend's sleep behavior influences one's own drug use. We find clusters of poor sleep behavior and drug use that extend up to four degrees of separation (to one's friends' friends' friends' friends in the social network. Prospective regression models show that being central in the network negatively influences future sleep outcomes, but not vice versa. Moreover, if a friend sleeps networks influences the spread of another. The results indicate that interventions should focus on healthy sleep to prevent drug use and targeting specific individuals may improve outcomes across the entire social network.

Effect of latency and packet loss on achievable bandwidth

CERN Multimedia

CERN. Geneva

2015-01-01

Following an incident with a slow database replication between CERN's data centers, we discovered that even a very low rate packet loss in the network can induce significant penalties to long distance single stream TCP transfers. We explore the behaviour of multiple congestion control algorithms in a controlled loss environment in order to understand what is the achievable throughput of TCP data transfers between the Meyrin and Wigner data centres.

Characterizing the Networks of Digital Information that Support Collaborative Adaptive Forest Management in Sierra Nevada Forests

Science.gov (United States)

Lei, Shufei; Iles, Alastair; Kelly, Maggi

2015-07-01

Some of the factors that can contribute to the success of collaborative adaptive management—such as social learning, open communication, and trust—are built upon a foundation of the open exchange of information about science and management between participants and the public. Despite the importance of information transparency, the use and flow of information in collaborative adaptive management has not been characterized in detail in the literature, and currently there exist opportunities to develop strategies for increasing the exchange of information, as well as to track information flow in such contexts. As digital information channels and networks have been increased over the last decade, powerful new information monitoring tools have also been evolved allowing for the complete characterization of information products through their production, transport, use, and monitoring. This study uses these tools to investigate the use of various science and management information products in a case study—the Sierra Nevada Adaptive Management Project—using a mixed method (citation analysis, web analytics, and content analysis) research approach borrowed from the information processing and management field. The results from our case study show that information technologies greatly facilitate the flow and use of digital information, leading to multiparty collaborations such as knowledge transfer and public participation in science research. We conclude with recommendations for expanding information exchange in collaborative adaptive management by taking advantage of available information technologies and networks.

Characterizing the Networks of Digital Information that Support Collaborative Adaptive Forest Management in Sierra Nevada Forests.

Science.gov (United States)

Lei, Shufei; Iles, Alastair; Kelly, Maggi

2015-07-01

Some of the factors that can contribute to the success of collaborative adaptive management--such as social learning, open communication, and trust--are built upon a foundation of the open exchange of information about science and management between participants and the public. Despite the importance of information transparency, the use and flow of information in collaborative adaptive management has not been characterized in detail in the literature, and currently there exist opportunities to develop strategies for increasing the exchange of information, as well as to track information flow in such contexts. As digital information channels and networks have been increased over the last decade, powerful new information monitoring tools have also been evolved allowing for the complete characterization of information products through their production, transport, use, and monitoring. This study uses these tools to investigate the use of various science and management information products in a case study--the Sierra Nevada Adaptive Management Project--using a mixed method (citation analysis, web analytics, and content analysis) research approach borrowed from the information processing and management field. The results from our case study show that information technologies greatly facilitate the flow and use of digital information, leading to multiparty collaborations such as knowledge transfer and public participation in science research. We conclude with recommendations for expanding information exchange in collaborative adaptive management by taking advantage of available information technologies and networks.

Policy Networks and Forest Resource Management in Ghana

African Journals Online (AJOL)

Although the proximate causes of global· forest loss arc complex and quite ... Ghana within the framework of the Integrated Network Model. ... actors as key. to solving political, social, economic and environmental problems ... produce multiple networks. .... Timber Trade and Reconfiguration of Networks in the Late Colonial.

Communication efficiency and congestion of signal traffic in large-scale brain networks.

Science.gov (United States)

Mišić, Bratislav; Sporns, Olaf; McIntosh, Anthony R

2014-01-01

The complex connectivity of the cerebral cortex suggests that inter-regional communication is a primary function. Using computational modeling, we show that anatomical connectivity may be a major determinant for global information flow in brain networks. A macaque brain network was implemented as a communication network in which signal units flowed between grey matter nodes along white matter paths. Compared to degree-matched surrogate networks, information flow on the macaque brain network was characterized by higher loss rates, faster transit times and lower throughput, suggesting that neural connectivity may be optimized for speed rather than fidelity. Much of global communication was mediated by a "rich club" of hub regions: a sub-graph comprised of high-degree nodes that are more densely interconnected with each other than predicted by chance. First, macaque communication patterns most closely resembled those observed for a synthetic rich club network, but were less similar to those seen in a synthetic small world network, suggesting that the former is a more fundamental feature of brain network topology. Second, rich club regions attracted the most signal traffic and likewise, connections between rich club regions carried more traffic than connections between non-rich club regions. Third, a number of rich club regions were significantly under-congested, suggesting that macaque connectivity actively shapes information flow, funneling traffic towards some nodes and away from others. Together, our results indicate a critical role of the rich club of hub nodes in dynamic aspects of global brain communication.

Implementation and Characterization of Dynamic Genetic Networks in Vitro

OpenAIRE

Niederholtmeyer, Henrike Marie

2015-01-01

Transcription and translation (TX-TL) can be performed in vitro, outside of cells, allowing the assembly and analysis of genetic networks. This approach to engineering biological networks in a less complex and more controllable environment could one day allow rapid prototyping of network designs before implementing them in living cells. Furthermore, the in vitro approach provides insight into how natural biological systems are built and is instructive to define the rules for engineering biolo...

perception of communication network fraud dynamics by network ...

African Journals Online (AJOL)

ES Obe

work fraud dynamics by network administrators and stakeholders. In considering ... cyber crime within the last two years. How- ever, two-thirds of the ... ˆ increased exposure to unpredictable fi- nancial losses ... The intentions of the customers are reflected ..... 'There is a 95% confidence that the differ- ence between the ...

Community characterization of heterogeneous complex systems

International Nuclear Information System (INIS)

Tumminello, Michele; Miccichè, Salvatore; Lillo, Fabrizio; Mantegna, Rosario N; Varho, Jan; Piilo, Jyrki

2011-01-01

We introduce an analytical statistical method for characterizing the communities detected in heterogeneous complex systems. By proposing a suitable null hypothesis, our method makes use of the hypergeometric distribution to assess the probability that a given property is over-expressed in the elements of a community with respect to all the elements of the investigated set. We apply our method to two specific complex networks, namely a network of world movies and a network of physics preprints. The characterization of the elements and of the communities is done in terms of languages and countries for the movie network and of journals and subject categories for papers. We find that our method is able to characterize clearly the communities identified. Moreover our method works well both for large and for small communities

Alpha particle losses during sawtooth activity in Tokamaks

International Nuclear Information System (INIS)

Anderson, D.; Lisak, M.

1988-01-01

The time evolution of the direct losses of fusion produced alpha particles in Tokamak plasmas characterized by sawtooth activity is investigated. The alpha particle loss rate during a sawtooth period is predicted to change invertedly with the change in bulk plasma parameters but also to contain a characteristic burst at the sawtooth crash. The spectrum of the lost alpha particles is also discussed. The predictions for the time evolution and the spectrum of the losses are in qualitative agreement with recently obtained losses of 15 MeV fusion produced protons in JET. (authors)

Hydro-geomorphological characterization and classification of Chilean river networks using horizontal, vertical and climatological properties

Science.gov (United States)

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

2017-12-01

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

Spatial networks

Science.gov (United States)

Barthélemy, Marc

2011-02-01

Complex systems are very often organized under the form of networks where nodes and edges are embedded in space. Transportation and mobility networks, Internet, mobile phone networks, power grids, social and contact networks, and neural networks, are all examples where space is relevant and where topology alone does not contain all the information. Characterizing and understanding the structure and the evolution of spatial networks is thus crucial for many different fields, ranging from urbanism to epidemiology. An important consequence of space on networks is that there is a cost associated with the length of edges which in turn has dramatic effects on the topological structure of these networks. We will thoroughly explain the current state of our understanding of how the spatial constraints affect the structure and properties of these networks. We will review the most recent empirical observations and the most important models of spatial networks. We will also discuss various processes which take place on these spatial networks, such as phase transitions, random walks, synchronization, navigation, resilience, and disease spread.

Cost Allocation of Transmission Losses in Electric Market Mechanism

Directory of Open Access Journals (Sweden)

Erwin Dermawan

2012-06-01

Full Text Available This paper proposes a new method to calculate cost allocation of transmission losses (losses, based on a certain price of energy (i.e. a marginal price of system. Here is developed a mathematic model through manipulating of the network equation to separate losses. This model uses complex power injection and, does not use approximations and assumptions in determining the cost allocation of losses. Its calculation begins from the results of load flow calculation and then is continued to calculate power distribution from a generator to every load and every line. Finally, to be calculated separating of losses and cost allocation of losses. The proposed method is easy to be understood and applied. An illustration results on IEEE 14-bus system show that the method is always consistent with expectancies and somewhat different with a few reference methods.

Reduction technique of drop voltage and power losses to improve power quality using ETAP Power Station simulation model

Science.gov (United States)

Satrio, Reza Indra; Subiyanto

2018-03-01

The effect of electric loads growth emerged direct impact in power systems distribution. Drop voltage and power losses one of the important things in power systems distribution. This paper presents modelling approach used to restructrure electrical network configuration, reduce drop voltage, reduce power losses and add new distribution transformer to enhance reliability of power systems distribution. Restructrure electrical network was aimed to analyse and investigate electric loads of a distribution transformer. Measurement of real voltage and real current were finished two times for each consumer, that were morning period and night period or when peak load. Design and simulation were conduct by using ETAP Power Station Software. Based on result of simulation and real measurement precentage of drop voltage and total power losses were mismatch with SPLN (Standard PLN) 72:1987. After added a new distribution transformer and restructrured electricity network configuration, the result of simulation could reduce drop voltage from 1.3 % - 31.3 % to 8.1 % - 9.6 % and power losses from 646.7 watt to 233.29 watt. Result showed, restructrure electricity network configuration and added new distribution transformer can be applied as an effective method to reduce drop voltage and reduce power losses.

Forecasting loss of ecosystem service value using a BP network: a case study of the impact of the South-to-north Water Transfer Project on the ecological environmental in Xiangfan, Hubei Province, China.

Science.gov (United States)

Chen, Yun-Feng; Zhou, Jing-Xuan; Xiao, Jie; Li, Yan-Ping

2003-12-01

To recognize and assess the impact of the South-to-north Water Transfer Project (SNWTP) on the ecological environment of Xiangfan, Hubei Province, situated in the water-out area, and develop sound scientific countermeasures. A three-layer BP network was built to simulate topology and process of the eco-economy system of Xiangfan. Historical data of ecological environmental factors and socio-economic factors as inputs, and corresponding historical data of ecosystem service value (ESV) and GDP as target outputs, were presented to train and test the network. When predicted input data after 2001 were presented to trained network as generalization sets, ESVs and GDPs of 2002, 2003, 2004... till 2050 were simulated as output in succession. Up to 2050, the area would have suffered an accumulative total ESV loss of RMB104.9 billion, which accounted for 37.36% of the present ESV. The coinstantaneous GDP would change asynchronously with ESV, it would go through an up-to-down process and finally lose RMB89.3 billion, which accounted for 18.71% of 2001. The simulation indicates that ESV loss means damage to the capability of socio-economic sustainable development, and suggests that artificial neural networks (ANNs) provide a feasible and effective method and have an important potential in ESV modeling.

Preparation and Preliminary Dielectric Characterization of Structured C60-Thiol-Ene Polymer Nanocomposites Assembled Using the Thiol-Ene Click Reaction

Directory of Open Access Journals (Sweden)

Hanaa M. Ahmed

2015-11-01

Full Text Available Fullerene-containing materials have the ability to store and release electrical energy. Therefore, fullerenes may ultimately find use in high-voltage equipment devices or as super capacitors for high electric energy storage due to this ease of manipulating their excellent dielectric properties and their high volume resistivity. A series of structured fullerene (C60 polymer nanocomposites were assembled using the thiol-ene click reaction, between alkyl thiols and allyl functionalized C60 derivatives. The resulting high-density C60-urethane-thiol-ene (C60-Thiol-Ene networks possessed excellent mechanical properties. These novel networks were characterized using standard techniques, including infrared spectroscopy (FTIR, differential scanning calorimetry (DSC, dynamic mechanical analysis (DMA, and thermal gravimetric analysis (TGA. The dielectric spectra for the prepared samples were determined over a broad frequency range at room temperature using a broadband dielectric spectrometer and a semiconductor characterization system. The changes in thermo-mechanical and electrical properties of these novel fullerene-thiol-ene composite films were measured as a function of the C60 content, and samples characterized by high dielectric permittivity and low dielectric loss were produced. In this process, variations in chemical composition of the networks were correlated to performance characteristics.

Rhizoma Dioscoreae extract protects against alveolar bone loss by regulating the cell cycle: A predictive study based on the protein‑protein interaction network.

Science.gov (United States)

Zhang, Zhi-Guo; Song, Chang-Heng; Zhang, Fang-Zhen; Chen, Yan-Jing; Xiang, Li-Hua; Xiao, Gary Guishan; Ju, Da-Hong

2016-06-01

Rhizoma Dioscoreae extract (RDE) exhibits a protective effect on alveolar bone loss in ovariectomized (OVX) rats. The aim of this study was to predict the pathways or targets that are regulated by RDE, by re‑assessing our previously reported data and conducting a protein‑protein interaction (PPI) network analysis. In total, 383 differentially expressed genes (≥3‑fold) between alveolar bone samples from the RDE and OVX group rats were identified, and a PPI network was constructed based on these genes. Furthermore, four molecular clusters (A‑D) in the PPI network with the smallest P‑values were detected by molecular complex detection (MCODE) algorithm. Using Database for Annotation, Visualization and Integrated Discovery (DAVID) and Ingenuity Pathway Analysis (IPA) tools, two molecular clusters (A and B) were enriched for biological process in Gene Ontology (GO). Only cluster A was associated with biological pathways in the IPA database. GO and pathway analysis results showed that cluster A, associated with cell cycle regulation, was the most important molecular cluster in the PPI network. In addition, cyclin‑dependent kinase 1 (CDK1) may be a key molecule achieving the cell‑cycle‑regulatory function of cluster A. From the PPI network analysis, it was predicted that delayed cell cycle progression in excessive alveolar bone remodeling via downregulation of CDK1 may be another mechanism underling the anti‑osteopenic effect of RDE on alveolar bone.

Development of a new loss allocation method for a hybrid electricity market using graph theory

International Nuclear Information System (INIS)

Lim, Valerie S.C.; McDonald, John D.F.; Saha, Tapan K.

2009-01-01

This paper introduces a new method for allocating losses in a power system using a loop-based representation of system behaviour. Using the new method, network behaviour is formulated as a series of presumed power transfers directly between market participants. In contrast to many existing loss allocation methods, this makes it easier to justify the resulting loss distribution. In addition to circumventing the problems of non-unique loss allocations, a formalised process of loop identification, using graph theory concepts, is introduced. The proposed method is applied to both the IEEE 14-bus system and a modified CIGRE Nordic 32-bus system. The results provide a demonstration of the capability of the proposed method to allocate losses in the hybrid market, and demonstrate the approach's capacity to link the technical performance of the network to market instruments. (author)

Characterization and Modeling of Network Traffic

DEFF Research Database (Denmark)

Shawky, Ahmed; Bergheim, Hans; Ragnarsson, Olafur

2011-01-01

-arrival time, IP addresses, port numbers and transport protocol are the only necessary parameters to model network traffic behaviour. In order to recreate this behaviour, a complex model is needed which is able to recreate traffic behaviour based on a set of statistics calculated from the parameters values...

Handoff mechanisms in LTE networks

Science.gov (United States)

Lal, Preeti; Yamini, Vidhu; Mohammed, V. Noor

2017-11-01

In this paper, we have analysed and studied the handoff mechanism in Long Term Evaluation (LTE) network. A LTE network has been defined with a set number of macro-cells, micro-cells and mobile devices. In this handoff mechanism distance and speed has been considered as an important parameters. The speed has been detected using the Gauss Markov Mobility Model, and from that distances have been predicted at different instances. In the handover process, Received Signal Power (RSP) for various users has been calculated with respect to base stations at various time intervals and the path loss between transmitter and receiver. A comparative study between path loss models is done in order to improve the signal power. A detailed study has been done on unnecessary handoff probability and handoff failure probability. Simulation results shows that there is an improvement in performance of the above mentioned parameters in the defined network.

Modeling of axonal endoplasmic reticulum network by spastic paraplegia proteins.

Science.gov (United States)

Yalçın, Belgin; Zhao, Lu; Stofanko, Martin; O'Sullivan, Niamh C; Kang, Zi Han; Roost, Annika; Thomas, Matthew R; Zaessinger, Sophie; Blard, Olivier; Patto, Alex L; Sohail, Anood; Baena, Valentina; Terasaki, Mark; O'Kane, Cahir J

2017-07-25

Axons contain a smooth tubular endoplasmic reticulum (ER) network that is thought to be continuous with ER throughout the neuron; the mechanisms that form this axonal network are unknown. Mutations affecting reticulon or REEP proteins, with intramembrane hairpin domains that model ER membranes, cause an axon degenerative disease, hereditary spastic paraplegia (HSP). We show that Drosophila axons have a dynamic axonal ER network, which these proteins help to model. Loss of HSP hairpin proteins causes ER sheet expansion, partial loss of ER from distal motor axons, and occasional discontinuities in axonal ER. Ultrastructural analysis reveals an extensive ER network in axons, which shows larger and fewer tubules in larvae that lack reticulon and REEP proteins, consistent with loss of membrane curvature. Therefore HSP hairpin-containing proteins are required for shaping and continuity of axonal ER, thus suggesting roles for ER modeling in axon maintenance and function.

Reinforcing styrene butadiene rubber with lignin-novolac epoxy resin networks

Directory of Open Access Journals (Sweden)

P. Yu

2015-01-01

Full Text Available In this study, lignin-novolac epoxy resin networks were fabricated in the styrene butadiene rubber (SBR matrix by combination of latex compounding and melt mixing. Firstly, SBR/lignin compounds were co-coagulated by SBR latex and lignin aqueous solution. Then the novolac epoxy resin (F51 was added in the SBR/lignin compounds by melt compounding method. F51 was directly cured by lignin via the ring-opening reaction of epoxy groups of F51 and OH groups (or COOH groups of lignin during the curing process of rubber compounds, as was particularly evident from Fourier transform infrared spectroscopy (FTIR studies and maximum torque of the curing analysis. The existence of lignin-F51 networks were also detected by scanning electron microscope (SEM and dynamic mechanical analysis (DMA. The structure of the SBR/lignin/F51 was also characterized by rubber process analyzer (RPA, thermogravimetric analysis (TGA and determination of crosslinking density. Due to rigid lignin-F51 networks achieved in SBR/lignin/F51 composites, it was found that the hardness, modulus, tear strength, crosslinking density, the temperature of 5 and 10% weight-loss were significantly enhanced with the loading of F51.

Anatomy of the bacitracin resistance network in Bacillus subtilis.

Science.gov (United States)

Radeck, Jara; Gebhard, Susanne; Orchard, Peter Shevlin; Kirchner, Marion; Bauer, Stephanie; Mascher, Thorsten; Fritz, Georg

2016-05-01

Protection against antimicrobial peptides (AMPs) often involves the parallel production of multiple, well-characterized resistance determinants. So far, little is known about how these resistance modules interact and how they jointly protect the cell. Here, we studied the interdependence between different layers of the envelope stress response of Bacillus subtilis when challenged with the lipid II cycle-inhibiting AMP bacitracin. The underlying regulatory network orchestrates the production of the ABC transporter BceAB, the UPP phosphatase BcrC and the phage-shock proteins LiaIH. Our systems-level analysis reveals a clear hierarchy, allowing us to discriminate between primary (BceAB) and secondary (BcrC and LiaIH) layers of bacitracin resistance. Deleting the primary layer provokes an enhanced induction of the secondary layer to partially compensate for this loss. This study reveals a direct role of LiaIH in bacitracin resistance, provides novel insights into the feedback regulation of the Lia system, and demonstrates a pivotal role of BcrC in maintaining cell wall homeostasis. The compensatory regulation within the bacitracin network can also explain how gene expression noise propagates between resistance layers. We suggest that this active redundancy in the bacitracin resistance network of B. subtilis is a general principle to be found in many bacterial antibiotic resistance networks. © 2016 John Wiley & Sons Ltd.

Technical and economic evaluation of voltage level in transmission network expansion planning using GA

International Nuclear Information System (INIS)

Jalilzadeh, S.; Kazemi, A.; Shayeghi, H.; Madavi, M.

2008-01-01

Transmission network expansion planning is an important part of power system planning. Its task is to determine an optimal network configuration according to load growth. It determines where, when and how many new transmission lines should be installed. Up to now, various methods have been presented to solve the static transmission network expansion planning (STNEP) problem, but in all of these methods, the STNEP problem has been solved regardless of voltage level of the lines. In this paper, due to different voltage levels in the transmission network, which cause different annual losses, STNEP has been studied considering the voltage level of the transmission lines and the network loss using the genetic algorithm (GA). Finally, the proposed idea has been examined on Garvers 6 bus network. The results show that considering the loss in a network with different voltage levels decreases the operational costs considerably, and the network satisfies the requirement of delivering electric power more safely and reliably to load centers

A simulation analysis to characterize the dynamics of vaccinating behaviour on contact networks.

Science.gov (United States)

Perisic, Ana; Bauch, Chris T

2009-05-28

Human behavior influences infectious disease transmission, and numerous "prevalence-behavior" models have analyzed this interplay. These previous analyses assumed homogeneously mixing populations without spatial or social structure. However, spatial and social heterogeneity are known to significantly impact transmission dynamics and are particularly relevant for certain diseases. Previous work has demonstrated that social contact structure can change the individual incentive to vaccinate, thus enabling eradication of a disease under a voluntary vaccination policy when the corresponding homogeneous mixing model predicts that eradication is impossible due to free rider effects. Here, we extend this work and characterize the range of possible behavior-prevalence dynamics on a network. We simulate transmission of a vaccine-preventable infection through a random, static contact network. Individuals choose whether or not to vaccinate on any given day according to perceived risks of vaccination and infection. We find three possible outcomes for behavior-prevalence dynamics on this type of network: small final number vaccinated and final epidemic size (due to rapid control through voluntary ring vaccination); large final number vaccinated and significant final epidemic size (due to imperfect voluntary ring vaccination), and little or no vaccination and large final epidemic size (corresponding to little or no voluntary ring vaccination). We also show that the social contact structure enables eradication under a broad range of assumptions, except when vaccine risk is sufficiently high, the disease risk is sufficiently low, or individuals vaccinate too late for the vaccine to be effective. For populations where infection can spread only through social contact network, relatively small differences in parameter values relating to perceived risk or vaccination behavior at the individual level can translate into large differences in population-level outcomes such as final size

A simulation analysis to characterize the dynamics of vaccinating behaviour on contact networks

Directory of Open Access Journals (Sweden)

Bauch Chris T

2009-05-01

Full Text Available Abstract Background Human behavior influences infectious disease transmission, and numerous "prevalence-behavior" models have analyzed this interplay. These previous analyses assumed homogeneously mixing populations without spatial or social structure. However, spatial and social heterogeneity are known to significantly impact transmission dynamics and are particularly relevant for certain diseases. Previous work has demonstrated that social contact structure can change the individual incentive to vaccinate, thus enabling eradication of a disease under a voluntary vaccination policy when the corresponding homogeneous mixing model predicts that eradication is impossible due to free rider effects. Here, we extend this work and characterize the range of possible behavior-prevalence dynamics on a network. Methods We simulate transmission of a vaccine-prevetable infection through a random, static contact network. Individuals choose whether or not to vaccinate on any given day according to perceived risks of vaccination and infection. Results We find three possible outcomes for behavior-prevalence dynamics on this type of network: small final number vaccinated and final epidemic size (due to rapid control through voluntary ring vaccination; large final number vaccinated and significant final epidemic size (due to imperfect voluntary ring vaccination, and little or no vaccination and large final epidemic size (corresponding to little or no voluntary ring vaccination. We also show that the social contact structure enables eradication under a broad range of assumptions, except when vaccine risk is sufficiently high, the disease risk is sufficiently low, or individuals vaccinate too late for the vaccine to be effective. Conclusion For populations where infection can spread only through social contact network, relatively small differences in parameter values relating to perceived risk or vaccination behavior at the individual level can translate into large

Ultralow loss, high Q, four port resonant couplers for quantum optics and photonics.

Science.gov (United States)

Rokhsari, H; Vahala, K J

2004-06-25

We demonstrate a low-loss, optical four port resonant coupler (add-drop geometry), using ultrahigh Q (>10(8)) toroidal microcavities. Different regimes of operation are investigated by variation of coupling between resonator and fiber taper waveguides. As a result, waveguide-to-waveguide power transfer efficiency of 93% (0.3 dB loss) and nonresonant insertion loss of 0.02% (photonic networks.

Network discovery, characterization, and prediction : a grand challenge LDRD final report.

Energy Technology Data Exchange (ETDEWEB)

Kegelmeyer, W. Philip, Jr.

2010-11-01

This report is the final summation of Sandia's Grand Challenge LDRD project No.119351, 'Network Discovery, Characterization and Prediction' (the 'NGC') which ran from FY08 to FY10. The aim of the NGC, in a nutshell, was to research, develop, and evaluate relevant analysis capabilities that address adversarial networks. Unlike some Grand Challenge efforts, that ambition created cultural subgoals, as well as technical and programmatic ones, as the insistence on 'relevancy' required that the Sandia informatics research communities and the analyst user communities come to appreciate each others needs and capabilities in a very deep and concrete way. The NGC generated a number of technical, programmatic, and cultural advances, detailed in this report. There were new algorithmic insights and research that resulted in fifty-three refereed publications and presentations; this report concludes with an abstract-annotated bibliography pointing to them all. The NGC generated three substantial prototypes that not only achieved their intended goals of testing our algorithmic integration, but which also served as vehicles for customer education and program development. The NGC, as intended, has catalyzed future work in this domain; by the end it had already brought in, in new funding, as much funding as had been invested in it. Finally, the NGC knit together previously disparate research staff and user expertise in a fashion that not only addressed our immediate research goals, but which promises to have created an enduring cultural legacy of mutual understanding, in service of Sandia's national security responsibilities in cybersecurity and counter proliferation.

Neural loss aversion differences between depression patients and healthy individuals: A functional MRI investigation.

Science.gov (United States)

Chandrasekhar Pammi, V S; Pillai Geethabhavan Rajesh, Purushothaman; Kesavadas, Chandrasekharan; Rappai Mary, Paramban; Seema, Satish; Radhakrishnan, Ashalatha; Sitaram, Ranganatha

2015-04-01

Neuroeconomics employs neuroscience techniques to explain decision-making behaviours. Prospect theory, a prominent model of decision-making, features a value function with parameters for risk and loss aversion. Recent work with normal participants identified activation related to loss aversion in brain regions including the amygdala, ventral striatum, and ventromedial prefrontal cortex. However, the brain network for loss aversion in pathologies such as depression has yet to be identified. The aim of the current study is to employ the value function from prospect theory to examine behavioural and neural manifestations of loss aversion in depressed and healthy individuals to identify the neurobiological markers of loss aversion in economic behaviour. We acquired behavioural data and fMRI scans while healthy controls and patients with depression performed an economic decision-making task. Behavioural loss aversion was higher in patients with depression than in healthy controls. fMRI results revealed that the two groups shared a brain network for value function including right ventral striatum, ventromedial prefrontal cortex, and right amygdala. However, the neural loss aversion results revealed greater activations in the right dorsal striatum and the right anterior insula for controls compared with patients with depression, and higher activations in the midbrain region ventral tegmental area for patients with depression compared with controls. These results suggest that while the brain network for loss aversion is shared between depressed and healthy individuals, some differences exist with respect to differential activation of additional areas. Our findings are relevant to identifying neurobiological markers for altered decision-making in the depressed. © The Author(s) 2015 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Interface losses in multimaterial resonators

DEFF Research Database (Denmark)

Villanueva, L.G.; Amato, B.; Larsen, Tom

2014-01-01

We present an extensive study shedding light on the role of surface and bulk losses in micromechanical resonators. We fabricate thin silicon nitride membranes of different sizes and we coat them with different thicknesses of metal. We later characterize the 81 lowest out-of-plane flexural vibrati...

Analysis of cumulative exergy losses in the chains of technological processes

International Nuclear Information System (INIS)

Szargut, J.

1989-01-01

This paper reports on cumulative exergy consumption (CExC) which characterizes the chain of technological processes leading from natural resources to the final product under consideration. The difference of CExC and exergy of material or energy carrier expresses the cumulative exergy loss (CExL) in the mentioned technological chain. Two apportionment methods of CExL have been proposed. Partial exergy losses appear in particular links of the technological chain and characterize the influence of irreversibility of these links. Constituent exergy losses express the influence of thermodynamic imperfection of constituent technological chains leading to the final link of the total technological chain. Analysis of the partial and constituent exergy losses informs about the possibilities of improvement of the technological chains

Characterizations of the Beta and the Degree Network Power Measure

NARCIS (Netherlands)

van den Brink, J.R.; Borm, P.; Hendrickx, R.; Owen, G.

2008-01-01

A symmetric network consists of a set of positions and a set of bilateral links between these positions. For every symmetric network we define a cooperative transferable utility game that measures the "power" of each coalition of positions in the network. Applying the Shapley value to this game

Information diffusion in structured online social networks

Science.gov (United States)

Li, Pei; Zhang, Yini; Qiao, Fengcai; Wang, Hui

2015-05-01

Nowadays, due to the word-of-mouth effect, online social networks have been considered to be efficient approaches to conduct viral marketing, which makes it of great importance to understand the diffusion dynamics in online social networks. However, most research on diffusion dynamics in epidemiology and existing social networks cannot be applied directly to characterize online social networks. In this paper, we propose models to characterize the information diffusion in structured online social networks with push-based forwarding mechanism. We introduce the term user influence to characterize the average number of times that messages are browsed which is incurred by a given type user generating a message, and study the diffusion threshold, above which the user influence of generating a message will approach infinity. We conduct simulations and provide the simulation results, which are consistent with the theoretical analysis results perfectly. These results are of use in understanding the diffusion dynamics in online social networks and also critical for advertisers in viral marketing who want to estimate the user influence before posting an advertisement.

Use intensity of social networks in southern Brazil

Directory of Open Access Journals (Sweden)

Rafaele Matte Wojahn

2017-08-01

Full Text Available A social network implies in connect people. This article aims to identify the use intensity of social network in Southern Brazil. The research was characterized by quantitative approach, descriptive, cross-sectional and survey, with a sample of 372 respondents. To data analysis was used descriptive analysis to characterize the sample, verify the access frequency of social networks and the daily access time, and Pearson’s Correlation to identify the daily access time and the social networks. The results indicated the social network used in more intensity is the Facebook and then Whatsapp, and the access occurs at home. However, all the social networks promote interactions toward users.

Coping with Asymmetric Channel Losses in CSMA/CA

DEFF Research Database (Denmark)

Paramanathan, Achuthan; Roetter, Daniel Enrique Lucani; Fitzek, Frank

2013-01-01

Inspired by the discrepancy between past theoretical analysis and real measurements for high-load scenarios for intersession network coding, we pinpoint and analyze the source of this discrepancy in wireless networks implementing a CSMA/CA medium access scheme. Our analysis shows that CSMA/CA is ......) confirm the sensitivity of the CSMA/CA scheme in real implementations, and (ii) shows that our adaptive protocol provides a simple, yet potent mechanism to cope with asymmetric channel losses and ultimately to enhance end-to-end throughput in high-load scenarios....

Entropy of dynamical social networks

Science.gov (United States)

Zhao, Kun; Karsai, Marton; Bianconi, Ginestra

2012-02-01

Dynamical social networks are evolving rapidly and are highly adaptive. Characterizing the information encoded in social networks is essential to gain insight into the structure, evolution, adaptability and dynamics. Recently entropy measures have been used to quantify the information in email correspondence, static networks and mobility patterns. Nevertheless, we still lack methods to quantify the information encoded in time-varying dynamical social networks. In this talk we present a model to quantify the entropy of dynamical social networks and use this model to analyze the data of phone-call communication. We show evidence that the entropy of the phone-call interaction network changes according to circadian rhythms. Moreover we show that social networks are extremely adaptive and are modified by the use of technologies such as mobile phone communication. Indeed the statistics of duration of phone-call is described by a Weibull distribution and is significantly different from the distribution of duration of face-to-face interactions in a conference. Finally we investigate how much the entropy of dynamical social networks changes in realistic models of phone-call or face-to face interactions characterizing in this way different type human social behavior.

Loss of CIB2 Causes Profound Hearing Loss and Abolishes Mechanoelectrical Transduction in Mice

Directory of Open Access Journals (Sweden)

Yanfei Wang

2017-12-01

Full Text Available Calcium and integrin-binding protein 2 (CIB2 belongs to a protein family with four known members, CIB1 through CIB4, which are characterized by multiple calcium-binding EF-hand domains. Among the family members, the Cib1 and Cib2 genes are expressed in mouse cochlear hair cells, and mutations in the human CIB2 gene have been associated with nonsyndromic deafness DFNB48 and syndromic deafness USH1J. To further explore the function of CIB1 and CIB2 in hearing, we established Cib1 and Cib2 knockout mice using the clustered regularly interspaced short palindromic repeat (CRISPR-associated Cas9 nuclease (CRISPR/Cas9 genome editing technique. We found that loss of CIB1 protein does not affect auditory function, whereas loss of CIB2 protein causes profound hearing loss in mice. Further investigation revealed that hair cell stereocilia development is affected in Cib2 knockout mice. Noticeably, loss of CIB2 abolishes mechanoelectrical transduction (MET currents in auditory hair cells. In conclusion, we show here that although both CIB1 and CIB2 are readily detected in the cochlea, only loss of CIB2 results in profound hearing loss, and that CIB2 is essential for auditory hair cell MET.

Preparation of magnetorheological elastomers and their slip-free characterization by means of parallel-plate rotational rheometry

Science.gov (United States)

Walter, Bastian L.; Pelteret, Jean-Paul; Kaschta, Joachim; Schubert, Dirk W.; Steinmann, Paul

2017-08-01

A systematic study is presented to highlight a methodology of sample preparation and subsequent slip-free characterization of magnetorheological (MR) elastomers in parallel-plate rotational rheometry. Focusing on the magnetic field-dependent nonlinear viscoelastic behavior an array of oscillatory strain sweep measurements is conducted with samples cured within the rheometer. The examined nonlinear material response (i.e. the amplitude dependence of the storage and loss moduli) as a function of the applied magnetic field is found to be qualitatively similar to the amplitude dependence of particle reinforced elastomers (i.e. the Payne effect). Therefore, the experimental data (both moduli) is decomposed similar to that for reinforced elastomers and a phenomenological model is formulated for both the storage and loss modulus to account for the physical mechanisms governing the nonlinear material characteristics. Parameter identification suggests that the material response at low magnetic fields is dominated by the polymeric network whereas the strong magneto-reinforced microstructure governs the linear and nonlinear viscoelastic behavior at high magnetic fields. The overall experimental outcome further suggests that the underlying concept of the phenomenological model for particle reinforced elastomers (i.e. destruction and reformation of the filler network) can be transfered to MR materials. Consequently, the proposed phenomenological model can be applied to quantify and further analyze the nonlinear response characteristics of MR elastomers (i.e. the amplitude dependence of the storage and loss modulus as a function of the applied magnetic field) that is closely linked to microstructural changes of the magnetizable particle network.

Interpenetrating Polymer Network Hydrogels Based on Gelatin and PVA by Biocompatible Approaches: Synthesis and Characterization

Directory of Open Access Journals (Sweden)

Eltjani-Eltahir Hago

2013-01-01

Full Text Available In this work, a new approach was introduced to prepare interpenetrating polymer network PVA/GE hydrogels by cross-linking of various concentration gelatin in the presence of transglutaminase enzyme by using the freezing-thawing cycles technique. The effects of freezing-thawing cycles on the properties of morphological characterization, gel fraction, swelling, mechanical, and MTT assay were investigated. The IPN PVA/GE hydrogels showed excellent physical and mechanical Properties. MTT assay data and the fibroblasts culture also showed excellent biocompatibility and good proliferation. This indicates that the IPN hydrogels are stable enough for various biomedical applications.

Effect of distributed generation installation on power loss using genetic algorithm method

Science.gov (United States)

Hasibuan, A.; Masri, S.; Othman, W. A. F. W. B.

2018-02-01

Injection of the generator distributed in the distribution network can affect the power system significantly. The effect that occurs depends on the allocation of DG on each part of the distribution network. Implementation of this approach has been made to the IEEE 30 bus standard and shows the optimum location and size of the DG which shows a decrease in power losses in the system. This paper aims to show the impact of distributed generation on the distribution system losses. The main purpose of installing DG on a distribution system is to reduce power losses on the power system.Some problems in power systems that can be solved with the installation of DG, one of which will be explored in the use of DG in this study is to reduce the power loss in the transmission line. Simulation results from case studies on the IEEE 30 bus standard system show that the system power loss decreased from 5.7781 MW to 1,5757 MW or just 27,27%. The simulated DG is injected to the bus with the lowest voltage drop on the bus number 8.

Nonlinear aeroacoustic characterization of Helmholtz resonators with a local-linear neuro-fuzzy network model

Science.gov (United States)

Förner, K.; Polifke, W.

2017-10-01

The nonlinear acoustic behavior of Helmholtz resonators is characterized by a data-based reduced-order model, which is obtained by a combination of high-resolution CFD simulation and system identification. It is shown that even in the nonlinear regime, a linear model is capable of describing the reflection behavior at a particular amplitude with quantitative accuracy. This observation motivates to choose a local-linear model structure for this study, which consists of a network of parallel linear submodels. A so-called fuzzy-neuron layer distributes the input signal over the linear submodels, depending on the root mean square of the particle velocity at the resonator surface. The resulting model structure is referred to as an local-linear neuro-fuzzy network. System identification techniques are used to estimate the free parameters of this model from training data. The training data are generated by CFD simulations of the resonator, with persistent acoustic excitation over a wide range of frequencies and sound pressure levels. The estimated nonlinear, reduced-order models show good agreement with CFD and experimental data over a wide range of amplitudes for several test cases.

Applying of the Artificial Neural Networks (ANN) to Identify and Characterize Sweet Spots in Shale Gas Formations

Science.gov (United States)

Puskarczyk, Edyta

2018-03-01

The main goal of the study was to enhance and improve information about the Ordovician and Silurian gas-saturated shale formations. Author focused on: firstly, identification of the shale gas formations, especially the sweet spots horizons, secondly, classification and thirdly, the accurate characterization of divisional intervals. Data set comprised of standard well logs from the selected well. Shale formations are represented mainly by claystones, siltstones, and mudstones. The formations are also partially rich in organic matter. During the calculations, information about lithology of stratigraphy weren't taken into account. In the analysis, selforganizing neural network - Kohonen Algorithm (ANN) was used for sweet spots identification. Different networks and different software were tested and the best network was used for application and interpretation. As a results of Kohonen networks, groups corresponding to the gas-bearing intervals were found. The analysis showed diversification between gas-bearing formations and surrounding beds. It is also shown that internal diversification in sweet spots is present. Kohonen algorithm was also used for geological interpretation of well log data and electrofacies prediction. Reliable characteristic into groups shows that Ja Mb and Sa Fm which are usually treated as potential sweet spots only partially have good reservoir conditions. It is concluded that ANN appears to be useful and quick tool for preliminary classification of members and sweet spots identification.

Migratory connectivity magnifies the consequences of habitat loss from sea-level rise for shorebird populations.

Science.gov (United States)

Iwamura, Takuya; Possingham, Hugh P; Chadès, Iadine; Minton, Clive; Murray, Nicholas J; Rogers, Danny I; Treml, Eric A; Fuller, Richard A

2013-06-22

Sea-level rise (SLR) will greatly alter littoral ecosystems, causing habitat change and loss for coastal species. Habitat loss is widely used as a measurement of the risk of extinction, but because many coastal species are migratory, the impact of habitat loss will depend not only on its extent, but also on where it occurs. Here, we develop a novel graph-theoretic approach to measure the vulnerability of a migratory network to the impact of habitat loss from SLR based on population flow through the network. We show that reductions in population flow far exceed the proportion of habitat lost for 10 long-distance migrant shorebirds using the East Asian-Australasian Flyway. We estimate that SLR will inundate 23-40% of intertidal habitat area along their migration routes, but cause a reduction in population flow of up to 72 per cent across the taxa. This magnifying effect was particularly strong for taxa whose migration routes contain bottlenecks-sites through which a large fraction of the population travels. We develop the bottleneck index, a new network metric that positively correlates with the predicted impacts of habitat loss on overall population flow. Our results indicate that migratory species are at greater risk than previously realized.

Performance of Group Communication Over Ad-Hoc Networks

National Research Council Canada - National Science Library

Mosko, Marc; Garcia-Luna-Aceves, J. J

2002-01-01

... through a network of cluster trees, where a spanning tree joins groups of fully connected nodes. Through numerical analysis and simulations in GloMoSim, we show throughput, goodput, and loss rates for reliable and unreliable networks...

X-raying neighbour discovery in a wireless sensor network ...

African Journals Online (AJOL)

In most wireless sensor networks, the nodes are often assumed to be stationary. However, network connectivity is subject to changes arising from interference in wireless communication, changes in transmission power or loss of synchronization among neighbouring network nodes. Hence, even after a sensor node is aware ...

Prediction and characterization of protein-protein interaction networks in swine

Directory of Open Access Journals (Sweden)

Wang Fen

2012-01-01

Full Text Available Abstract Background Studying the large-scale protein-protein interaction (PPI network is important in understanding biological processes. The current research presents the first PPI map of swine, which aims to give new insights into understanding their biological processes. Results We used three methods, Interolog-based prediction of porcine PPI network, domain-motif interactions from structural topology-based prediction of porcine PPI network and motif-motif interactions from structural topology-based prediction of porcine PPI network, to predict porcine protein interactions among 25,767 porcine proteins. We predicted 20,213, 331,484, and 218,705 porcine PPIs respectively, merged the three results into 567,441 PPIs, constructed four PPI networks, and analyzed the topological properties of the porcine PPI networks. Our predictions were validated with Pfam domain annotations and GO annotations. Averages of 70, 10,495, and 863 interactions were related to the Pfam domain-interacting pairs in iPfam database. For comparison, randomized networks were generated, and averages of only 4.24, 66.79, and 44.26 interactions were associated with Pfam domain-interacting pairs in iPfam database. In GO annotations, we found 52.68%, 75.54%, 27.20% of the predicted PPIs sharing GO terms respectively. However, the number of PPI pairs sharing GO terms in the 10,000 randomized networks reached 52.68%, 75.54%, 27.20% is 0. Finally, we determined the accuracy and precision of the methods. The methods yielded accuracies of 0.92, 0.53, and 0.50 at precisions of about 0.93, 0.74, and 0.75, respectively. Conclusion The results reveal that the predicted PPI networks are considerably reliable. The present research is an important pioneering work on protein function research. The porcine PPI data set, the confidence score of each interaction and a list of related data are available at (http://pppid.biositemap.com/.

Performance and complexity of tunable sparse network coding with gradual growing tuning functions over wireless networks

OpenAIRE

Garrido Ortiz, Pablo; Sørensen, Chres W.; Lucani Roetter, Daniel Enrique; Agüero Calvo, Ramón

2016-01-01

Random Linear Network Coding (RLNC) has been shown to be a technique with several benefits, in particular when applied over wireless mesh networks, since it provides robustness against packet losses. On the other hand, Tunable Sparse Network Coding (TSNC) is a promising concept, which leverages a trade-off between computational complexity and goodput. An optimal density tuning function has not been found yet, due to the lack of a closed-form expression that links density, performance and comp...

Wireless network interface energy consumption implications of popular streaming formats

Science.gov (United States)

Chandra, Surendar

2001-12-01

With the proliferation of mobile streaming multimedia, available battery capacity constrains the end-user experience. Since streaming applications tend to be long running, wireless network interface card's (WNIC) energy consumption is particularly an acute problem. In this work, we explore the WNIC energy consumption implications of popular multimedia streaming formats from Microsoft (Windows media), Real (Real media) and Apple (Quick Time). We investigate the energy consumption under varying stream bandwidth and network loss rates. We also explore history-based client-side strategies to reduce the energy consumed by transitioning the WNICs to a lower power consuming sleep state. We show that Microsoft media tends to transmit packets at regular intervals; streams optimized for 28.8 Kbps can save over 80% in energy consumption with 2% data loss. A high bandwidth stream (768 Kbps) can still save 57% in energy consumption with less than 0.3% data loss. For high bandwidth streams, Microsoft media exploits network-level packet fragmentation, which can lead to excessive packet loss (and wasted energy) in a lossy network. Real stream packets tend to be sent closer to each other, especially at higher bandwidths. Quicktime packets sometimes arrive in quick succession; most likely an application level fragmentation mechanism. Such packets are harder to predict at the network level without understanding the packet semantics.

Forecasting electricity infeed for distribution system networks : an analysis of the Dutch case

NARCIS (Netherlands)

Tanrisever, F.; Derinkuyu, K.; Heeren, M.

2013-01-01

Estimating and managing electricity distribution losses are the core business competencies of distribution system operators (DSOs). Since electricity demand is a major driver of network losses, it is essential for DSOs to have an accurate estimate of the electricity infeed in their network. In this

Research on spot power market equilibrium model considering the electric power network characteristics

International Nuclear Information System (INIS)

Wang, Chengmin; Jiang, Chuanwen; Chen, Qiming

2007-01-01

Equilibrium is the optimum operational condition for the power market by economics rule. A realistic spot power market cannot achieve the equilibrium condition due to network losses and congestions. The impact of the network losses and congestion on spot power market is analyzed in this paper in order to establish a new equilibrium model considering the network loss and transmission constraints. The OPF problem formulated according to the new equilibrium model is solved by means of the equal price principle. A case study on the IEEE-30-bus system is provided in order to prove the effectiveness of the proposed approach. (author)

Characterization of a wide dynamic-range, radiation-tolerant charge-digitizer asic for monitoring of Beam losses

CERN Document Server

Guido Venturini, G G; Dehning, B; Kayal, M

2012-01-01

An Application Specific Integrated Circuit (ASIC) has been designed and fabricated to provide a compact solution to digitize current signals from ionization chambers and diamond detectors, employed as beam loss monitors at CERN and several other high energy physics facilities. The circuit topology has been devised to accept positive and negative currents, to have a wide dynamic range (above 120 dB), withstand radiation levels over 10 Mrad and offer different modes of operation, covering a broad range of applications. Furthermore, an internal conversion reference is employed in the digitization, to provide an accurate absolute measurement. This paper discusses the detailed characterization of the first prototype: linearity, radiation tolerance and temperature dependence of the conversion, as well as implications and system-level considerations regarding its use for beam instrumentation applications in a high energy physics facility.

Resilience of LTE networks against smart jamming attacks

KAUST Repository

Aziz, Farhan M.; Shamma, Jeff S.; Stuber, Gordon L.

2014-01-01

Commercial LTE networks are being studied for mission-critical applications, such as public safety and smart grid communications. In this paper, LTE networks are shown vulnerable to Denial-of-Service (DOS) and loss of service attacks from smart

Wetland Loss Patterns and Inundation-Productivity ...

Science.gov (United States)

Tidal salt marsh is a key defense against, yet is especially vulnerable to, the effects of accelerated sea level rise. To determine whether salt marshes in southern New England will be stable given increasing inundation over the coming decades, we examined current loss patterns, inundation-productivity feedbacks, and sustaining processes. A multi-decadal analysis of salt marsh aerial extent using historic imagery and maps revealed that salt marsh vegetation loss is both widespread and accelerating, with vegetation loss rates over the past four decades summing to 17.3 %. Landward retreat of the marsh edge, widening and headward expansion of tidal channel networks, loss of marsh islands, and the development and enlargement of interior depressions found on the marsh platform contributed to vegetation loss. Inundation due to sea level rise is strongly suggested as a primary driver: vegetation loss rates were significantly negatively correlated with marsh elevation (r2 = 0.96; p = 0.0038), with marshes situated below mean high water (MHW) experiencing greater declines than marshes sitting well above MHW. Growth experiments with Spartina alterniflora, the Atlantic salt marsh ecosystem dominant, across a range of elevations and inundation regimes further established that greater inundation decreases belowground biomass production of S. alterniflora and, thus, negatively impacts organic matter accumulation. These results suggest that southern New England salt ma

Low-loss ultracompact optical power splitter using a multistep structure.

Science.gov (United States)

Huang, Zhe; Chan, Hau Ping; Afsar Uddin, Mohammad

2010-04-01

We propose a low-loss ultracompact optical power splitter for broadband passive optical network applications. The design is based on a multistep structure involving a two-material (core/cladding) system. The performance of the proposed device was evaluated through the three-dimensional finite-difference beam propagation method. By using the proposed design, an excess loss of 0.4 dB was achieved at a full branching angle of 24 degrees. The wavelength-dependent loss was found to be less than 0.3 dB, and the polarization-dependent loss was less than 0.05 dB from O to L bands. The device offers the potential of being mass-produced using low-cost polymer-based embossing techniques.

When Is Network Lasso Accurate?

Directory of Open Access Journals (Sweden)

Alexander Jung

2018-01-01

Full Text Available The “least absolute shrinkage and selection operator” (Lasso method has been adapted recently for network-structured datasets. In particular, this network Lasso method allows to learn graph signals from a small number of noisy signal samples by using the total variation of a graph signal for regularization. While efficient and scalable implementations of the network Lasso are available, only little is known about the conditions on the underlying network structure which ensure network Lasso to be accurate. By leveraging concepts of compressed sensing, we address this gap and derive precise conditions on the underlying network topology and sampling set which guarantee the network Lasso for a particular loss function to deliver an accurate estimate of the entire underlying graph signal. We also quantify the error incurred by network Lasso in terms of two constants which reflect the connectivity of the sampled nodes.

The Poultry-Associated Microbiome: Network Analysis and Farm-to-Fork Characterizations

Science.gov (United States)

Oakley, Brian B.; Morales, Cesar A.; Line, J.; Berrang, Mark E.; Meinersmann, Richard J.; Tillman, Glenn E.; Wise, Mark G.; Siragusa, Gregory R.; Hiett, Kelli L.; Seal, Bruce S.

2013-01-01

Microbial communities associated with agricultural animals are important for animal health, food safety, and public health. Here we combine high-throughput sequencing (HTS), quantitative-PCR assays, and network analysis to profile the poultry-associated microbiome and important pathogens at various stages of commercial poultry production from the farm to the consumer. Analysis of longitudinal data following two flocks from the farm through processing showed a core microbiome containing multiple sequence types most closely related to genera known to be pathogenic for animals and/or humans, including Campylobacter, Clostridium, and Shigella. After the final stage of commercial poultry processing, taxonomic richness was ca. 2–4 times lower than the richness of fecal samples from the same flocks and Campylobacter abundance was significantly reduced. Interestingly, however, carcasses sampled at 48 hr after processing harboured the greatest proportion of unique taxa (those not encountered in other samples), significantly more than expected by chance. Among these were anaerobes such as Prevotella, Veillonella, Leptrotrichia, and multiple Campylobacter sequence types. Retail products were dominated by Pseudomonas, but also contained 27 other genera, most of which were potentially metabolically active and encountered in on-farm samples. Network analysis was focused on the foodborne pathogen Campylobacter and revealed a majority of sequence types with no significant interactions with other taxa, perhaps explaining the limited efficacy of previous attempts at competitive exclusion of Campylobacter. These data represent the first use of HTS to characterize the poultry microbiome across a series of farm-to-fork samples and demonstrate the utility of HTS in monitoring the food supply chain and identifying sources of potential zoonoses and interactions among taxa in complex communities. PMID:23468931

The poultry-associated microbiome: network analysis and farm-to-fork characterizations.

Directory of Open Access Journals (Sweden)

Brian B Oakley

Full Text Available Microbial communities associated with agricultural animals are important for animal health, food safety, and public health. Here we combine high-throughput sequencing (HTS, quantitative-PCR assays, and network analysis to profile the poultry-associated microbiome and important pathogens at various stages of commercial poultry production from the farm to the consumer. Analysis of longitudinal data following two flocks from the farm through processing showed a core microbiome containing multiple sequence types most closely related to genera known to be pathogenic for animals and/or humans, including Campylobacter, Clostridium, and Shigella. After the final stage of commercial poultry processing, taxonomic richness was ca. 2-4 times lower than the richness of fecal samples from the same flocks and Campylobacter abundance was significantly reduced. Interestingly, however, carcasses sampled at 48 hr after processing harboured the greatest proportion of unique taxa (those not encountered in other samples, significantly more than expected by chance. Among these were anaerobes such as Prevotella, Veillonella, Leptrotrichia, and multiple Campylobacter sequence types. Retail products were dominated by Pseudomonas, but also contained 27 other genera, most of which were potentially metabolically active and encountered in on-farm samples. Network analysis was focused on the foodborne pathogen Campylobacter and revealed a majority of sequence types with no significant interactions with other taxa, perhaps explaining the limited efficacy of previous attempts at competitive exclusion of Campylobacter. These data represent the first use of HTS to characterize the poultry microbiome across a series of farm-to-fork samples and demonstrate the utility of HTS in monitoring the food supply chain and identifying sources of potential zoonoses and interactions among taxa in complex communities.

Definition of fluctuant hearing loss.

Science.gov (United States)

Shea, J J

1975-06-01

In summary, fluctuant hearing loss is defined as a disorder of the inner ear characterized by fullness, roaring tinnitus, and fluctuations in hearing. It is believed to be caused by an inadequate absorption of endolymph from the endolymphatic sac, with or without one or more metabolic disorders, that interferes with the delicate balance between the production and absorption of endolymph and thus produces cochlear hydrops. This triad of fullness, roaring tinnitus, and fluctuant hearing loss resulting from cochlear hydrops is much more common than the quadrad of true turning vertigo, fullness, roaring tinnitus, and fluctuant hearing loss due to vestibular and cochlear hydrops known as Meniere's disease. Although patients with fluctuant hearing loss only may eventually develop vertigo as the chief complaint and then be said to have Meniere's disease, it is remarkable how many patients continue to suffer mainly from cochlear symptoms at all times. It would appear, because of the greater frequency of fluctuant hearing loss than in Meniere's disease, that the cochlear labyrinth is more susceptible to hydrops than the vestibular labyrinth. For the purposes of diagnosis and treatment it is very useful to separate patients into those with fluctuant hearing loss and those with Meniere's disease.

Electron Energy-Loss Spectroscopy: Fundamentals and applications in the characterization of minerals

International Nuclear Information System (INIS)

Krishnan, K.M.

1989-04-01

The combined use of an energy-loss spectrometer and an analytical electron microscope with fine probe forming capabilities provides a wealth of information about the sample at high spatial resolution. Fundamental principles governing the physics of the interaction between the fast electron and a thin foil sample, to account for the fine structure in the inelastically scattered fast electron distribution (Electron-Energy Loss Spectroscopy, EELS), will be reviewed. General application of EELS is in the area of low atomic number elements (Z < 11) microanalysis, where it significantly complements the more widely used Energy Dispersive X-ray Spectroscopy (EDXS). However, a careful analysis of the low loss plasmon oscillations and the fine structure in the core-loss edges, can provide additional information related to the bonding and electronic structure of the sample. An illustration of this is presented from our study of Cδ diamond residue from the Allende carbonaceous chondrite. Combination of EELS with channeling effects can provide specific site occupation/valence information in crystalline materials. Details of this novel crystallographic method will be outlined and illustrated with an example of the study of chromite spinels. Finally, some pertinent experimental details will be discussed. 7 figs

Research on three-phase unbalanced distribution network reconfiguration strategy

Science.gov (United States)

Hu, Shuang; Li, Ke-Jun; Xu, Yanshun; Liu, Zhijie; Guo, Jing; Wang, Zhuodi

2017-01-01

With the development of social economy, the loads installed in the distribution network become more and more complex which may cause the three-phase unbalance problems. This paper proposes an optimal reconfiguration approach based on mixed integer quadric programming (MIQP) method to address the three-phase unbalance problem. It aims to minimize the total network losses of the system. By using several square constraints to substitute the circular constraint, the original optimization problem is linearized and converted into a mixed-integer linear programming (MILP) model. Then this MILP problem is solved in general algebraic model system (GAMS) software using CPLEX solver. The additional losses caused by three-phase unbalanced are also considered. An IEEE 34 nodes test system is used to demonstrate the feasibility and effectiveness of the proposed method. The results show that the losses and the voltage violation mitigation in the network can be reduced significantly.

On Applicability of Network Coding Technique for 6LoWPAN-based Sensor Networks.

Science.gov (United States)

Amanowicz, Marek; Krygier, Jaroslaw

2018-05-26

In this paper, the applicability of the network coding technique in 6LoWPAN-based sensor multihop networks is examined. The 6LoWPAN is one of the standards proposed for the Internet of Things architecture. Thus, we can expect the significant growth of traffic in such networks, which can lead to overload and decrease in the sensor network lifetime. The authors propose the inter-session network coding mechanism that can be implemented in resource-limited sensor motes. The solution reduces the overall traffic in the network, and in consequence, the energy consumption is decreased. Used procedures take into account deep header compressions of the native 6LoWPAN packets and the hop-by-hop changes of the header structure. Applied simplifications reduce signaling traffic that is typically occurring in network coding deployments, keeping the solution usefulness for the wireless sensor networks with limited resources. The authors validate the proposed procedures in terms of end-to-end packet delay, packet loss ratio, traffic in the air, total energy consumption, and network lifetime. The solution has been tested in a real wireless sensor network. The results confirm the efficiency of the proposed technique, mostly in delay-tolerant sensor networks.

Blocking Losses With a Photon Counter

Science.gov (United States)

Moision, Burce E.; Piazzolla, Sabino

2012-01-01

It was not known how to assess accurately losses in a communications link due to photodetector blocking, a phenomenon wherein a detector is rendered inactive for a short time after the detection of a photon. When used to detect a communications signal, blocking leads to losses relative to an ideal detector, which may be measured as a reduction in the communications rate for a given received signal power, or an increase in the signal power required to support the same communications rate. This work involved characterizing blocking losses for single detectors and arrays of detectors. Blocking may be mitigated by spreading the signal intensity over an array of detectors, reducing the count rate on any one detector. A simple approximation was made to the blocking loss as a function of the probability that a detector is unblocked at a given time, essentially treating the blocking probability as a scaling of the detection efficiency. An exact statistical characterization was derived for a single detector, and an approximation for multiple detectors. This allowed derivation of several accurate approximations to the loss. Methods were also derived to account for a rise time in recovery, and non-uniform illumination due to diffraction and atmospheric distortion of the phase front. It was assumed that the communications signal is intensity modulated and received by an array of photon-counting photodetectors. For the purpose of this analysis, it was assumed that the detectors are ideal, in that they produce a signal that allows one to reproduce the arrival times of electrons, produced either as photoelectrons or from dark noise, exactly. For single detectors, the performance of the maximum-likelihood (ML) receiver in blocking is illustrated, as well as a maximum-count (MC) receiver, that, when receiving a pulse-position-modulated (PPM) signal, selects the symbol corresponding to the slot with the largest electron count. Whereas the MC receiver saturates at high count rates

Dispersion-tailored, low-loss photonic crystal fibers for the THz range

DEFF Research Database (Denmark)

Nielsen, Kristian; Rasmussen, Henrik K.; Adam, Aurèle J.L.

2009-01-01

We have fabricated a new type of photonic crystal fibers based on a cyclic olefin copolymer, transparent in the THz range. We characterize the propagation loss, dispersion, and spatial beam profile in fibers designed for low and high dispersion.......We have fabricated a new type of photonic crystal fibers based on a cyclic olefin copolymer, transparent in the THz range. We characterize the propagation loss, dispersion, and spatial beam profile in fibers designed for low and high dispersion....

The transcriptional regulatory network of Mycobacterium tuberculosis.

Directory of Open Access Journals (Sweden)

Joaquín Sanz

Full Text Available Under the perspectives of network science and systems biology, the characterization of transcriptional regulatory (TR networks beyond the context of model organisms offers a versatile tool whose potential remains yet mainly unexplored. In this work, we present an updated version of the TR network of Mycobacterium tuberculosis (M.tb, which incorporates newly characterized transcriptional regulations coming from 31 recent, different experimental works available in the literature. As a result of the incorporation of these data, the new network doubles the size of previous data collections, incorporating more than a third of the entire genome of the bacterium. We also present an exhaustive topological analysis of the new assembled network, focusing on the statistical characterization of motifs significances and the comparison with other model organisms. The expanded M.tb transcriptional regulatory network, considering its volume and completeness, constitutes an important resource for diverse tasks such as dynamic modeling of gene expression and signaling processes, computational reliability determination or protein function prediction, being the latter of particular relevance, given that the function of only a small percent of the proteins of M.tb is known.

Network compensation for missing sensors

Science.gov (United States)

Ahumada, Albert J., Jr.; Mulligan, Jeffrey B.

1991-01-01

A network learning translation invariance algorithm to compute interpolation functions is presented. This algorithm with one fixed receptive field can construct a linear transformation compensating for gain changes, sensor position jitter, and sensor loss when there are enough remaining sensors to adequately sample the input images. However, when the images are undersampled and complete compensation is not possible, the algorithm need to be modified. For moderate sensor losses, the algorithm works if the transformation weight adjustment is restricted to the weights to output units affected by the loss.

On the Conditional Entropy of Wireless Networks

DEFF Research Database (Denmark)

Coon, Justin P.; Badiu, Mihai Alin; Gündüz, Deniz

2018-01-01

The characterization of topological uncertainty in wireless networks using the formalism of graph entropy has received interest in the spatial networks community. In this paper, we develop lower bounds on the entropy of a wireless network by conditioning on potential network observables. Two appr...... a homogeneous binomial point process in this work) and the network topology....

Performance Analysis of Congestion Control Mechanism in Software Defined Network (SDN

Directory of Open Access Journals (Sweden)

Rahman M. Z. A.

2017-01-01

Full Text Available In the near future, the traditional networks architecture will be difficult to be managed. Hence, Software Defined Network (SDN will be an alternative in the future of programmable networks to replace the conventional network architecture. The main idea of SDN architecture is to separate the forwarding plane and control plane of network system, where network operators can program packet forwarding behaviour to improve the network performance. Congestion control is important mechanism for network traffic to improve network capability and achieve high end Quality of Service (QoS. In this paper, extensive simulation is conducted to analyse the performance of SDN by implementing Link Layer Discovery Protocol (LLDP under congested network. The simulation was conducted on Mininet by creating four different fanout and the result was analysed based on differences of matrix performance. As a result, the packet loss and throughput reduction were observed when number of fanout in the topology was increased. By using LLDP protocol, huge reduction in packet loss rate has been achieved while maximizing percentage packet delivery ratio.

Multielemental characterization of sediments from rivers and reservoirs of a sediment quality monitoring network of Sao Paulo state, Brazil

Energy Technology Data Exchange (ETDEWEB)

Soares, Walace A.A.; Quinaglia, Gilson A., E-mail: wasoares@sp.gov.br, E-mail: gquinaglia@sp.gov.br [Companhia Ambiental do Estado de Sao Paulo (CETESB), SP (Brazil). Setor de Analises Toxicologicas; Favaro, Deborah I.T., E-mail: defavaro@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (LAN/CRPq/IPEN/CNEN-SP), Sao Paulo, SP (Brazil). Lab. de Analise por Ativacao Neutronica

2013-07-01

The Environment Company of the State of Sao Paulo (CETESB) by means of its quality monitoring network does, systematically, the assessment of water and sediment quality in rivers and reservoirs in the Sao Paulo state. The quality evaluation is done by means 50 parameters in water and 63 for sediment that are considered the more representative for CETESB monitoring. In 2011 the network monitoring analyzed 420 points being 24 in sediments. In the present study the multielemental characterization (total concentration) of 13 sediment samples from 24 rivers and reservoirs belonging to the CETESB monitoring network were analyzed by instrumental neutron activation analysis (INAA). The analytical validation according to precision and accuracy was checked through certified reference materials analyzes BEN (Basalt-IWG-GIT), SL-1 (Lake Sediment - IAEA) and Soil-5 (IAEA), that presents certified concentration values for all elements analyzed. The results obtained for multielemental characterization were compared to NASC values (North American Shale Composite) and the enrichment factor (EF) by using Sc as a normalizer element was calculated. The results showed higher enrichment values for As, Br, Cr, Hf, Ta, Th , U and Zn and rare earth elements (REE) Ce, Eu, La, Nd, Sm, Tb and Yb in many of the tested sediment samples indicating that there may be an anthropogenic contribution for these elements. The multielemental results were also compared to the granulometric composition of the sediment samples. Factorial and Cluster Analysis were applied and indicated that the elements distribution is controlled, mainly by the granulometric fractions of the sediments. (author)

Multielemental characterization of sediments from rivers and reservoirs of a sediment quality monitoring network of Sao Paulo state, Brazil

International Nuclear Information System (INIS)

Soares, Walace A.A.; Quinaglia, Gilson A.; Favaro, Deborah I.T.

2013-01-01

The Environment Company of the State of Sao Paulo (CETESB) by means of its quality monitoring network does, systematically, the assessment of water and sediment quality in rivers and reservoirs in the Sao Paulo state. The quality evaluation is done by means 50 parameters in water and 63 for sediment that are considered the more representative for CETESB monitoring. In 2011 the network monitoring analyzed 420 points being 24 in sediments. In the present study the multielemental characterization (total concentration) of 13 sediment samples from 24 rivers and reservoirs belonging to the CETESB monitoring network were analyzed by instrumental neutron activation analysis (INAA). The analytical validation according to precision and accuracy was checked through certified reference materials analyzes BEN (Basalt-IWG-GIT), SL-1 (Lake Sediment - IAEA) and Soil-5 (IAEA), that presents certified concentration values for all elements analyzed. The results obtained for multielemental characterization were compared to NASC values (North American Shale Composite) and the enrichment factor (EF) by using Sc as a normalizer element was calculated. The results showed higher enrichment values for As, Br, Cr, Hf, Ta, Th , U and Zn and rare earth elements (REE) Ce, Eu, La, Nd, Sm, Tb and Yb in many of the tested sediment samples indicating that there may be an anthropogenic contribution for these elements. The multielemental results were also compared to the granulometric composition of the sediment samples. Factorial and Cluster Analysis were applied and indicated that the elements distribution is controlled, mainly by the granulometric fractions of the sediments. (author)

Structural analysis of behavioral networks from the Internet

International Nuclear Information System (INIS)

Meiss, M R; Menczer, F; Vespignani, A

2008-01-01