Information processing occurs via critical avalanches in a model of the primary visual cortex

NASA Astrophysics Data System (ADS)

Bortolotto, G. S.; Girardi-Schappo, M.; Gonsalves, J. J.; Pinto, L. T.; Tragtenberg, M. H. R.

2016-01-01

We study a new biologically motivated model for the Macaque monkey primary visual cortex which presents power-law avalanches after a visual stimulus. The signal propagates through all the layers of the model via avalanches that depend on network structure and synaptic parameter. We identify four different avalanche profiles as a function of the excitatory postsynaptic potential. The avalanches follow a size-duration scaling relation and present critical exponents that match experiments. The structure of the network gives rise to a regime of two characteristic spatial scales, one of which vanishes in the thermodynamic limit.

Connecting Network Properties of Rapidly Disseminating Epizoonotics

PubMed Central

Rivas, Ariel L.; Fasina, Folorunso O.; Hoogesteyn, Almira L.; Konah, Steven N.; Febles, José L.; Perkins, Douglas J.; Hyman, James M.; Fair, Jeanne M.; Hittner, James B.; Smith, Steven D.

2012-01-01

Background To effectively control the geographical dissemination of infectious diseases, their properties need to be determined. To test that rapid microbial dispersal requires not only susceptible hosts but also a pre-existing, connecting network, we explored constructs meant to reveal the network properties associated with disease spread, which included the road structure. Methods Using geo-temporal data collected from epizoonotics in which all hosts were susceptible (mammals infected by Foot-and-mouth disease virus, Uruguay, 2001; birds infected by Avian Influenza virus H5N1, Nigeria, 2006), two models were compared: 1) ‘connectivity’, a model that integrated bio-physical concepts (the agent’s transmission cycle, road topology) into indicators designed to measure networks (‘nodes’ or infected sites with short- and long-range links), and 2) ‘contacts’, which focused on infected individuals but did not assess connectivity. Results The connectivity model showed five network properties: 1) spatial aggregation of cases (disease clusters), 2) links among similar ‘nodes’ (assortativity), 3) simultaneous activation of similar nodes (synchronicity), 4) disease flows moving from highly to poorly connected nodes (directionality), and 5) a few nodes accounting for most cases (a “20∶80″ pattern). In both epizoonotics, 1) not all primary cases were connected but at least one primary case was connected, 2) highly connected, small areas (nodes) accounted for most cases, 3) several classes of nodes were distinguished, and 4) the contact model, which assumed all primary cases were identical, captured half the number of cases identified by the connectivity model. When assessed together, the synchronicity and directionality properties explained when and where an infectious disease spreads. Conclusions Geo-temporal constructs of Network Theory’s nodes and links were retrospectively validated in rapidly disseminating infectious diseases. They distinguished classes of cases, nodes, and networks, generating information usable to revise theory and optimize control measures. Prospective studies that consider pre-outbreak predictors, such as connecting networks, are recommended. PMID:22761900

Energy efficient cooperation in underlay RFID cognitive networks for a water smart home.

PubMed

Nasir, Adnan; Hussain, Syed Imtiaz; Soong, Boon-Hee; Qaraqe, Khalid

2014-09-30

Shrinking water resources all over the world and increasing costs of water consumption have prompted water users and distribution companies to come up with water conserving strategies. We have proposed an energy-efficient smart water monitoring application in [1], using low power RFIDs. In the home environment, there exist many primary interferences within a room, such as cell-phones, Bluetooth devices, TV signals, cordless phones and WiFi devices. In order to reduce the interference from our proposed RFID network for these primary devices, we have proposed a cooperating underlay RFID cognitive network for our smart application on water. These underlay RFIDs should strictly adhere to the interference thresholds to work in parallel with the primary wireless devices [2]. This work is an extension of our previous ventures proposed in [2,3], and we enhanced the previous efforts by introducing a new system model and RFIDs. Our proposed scheme is mutually energy efficient and maximizes the signal-to-noise ratio (SNR) for the RFID link, while keeping the interference levels for the primary network below a certain threshold. A closed form expression for the probability density function (pdf) of the SNR at the destination reader/writer and outage probability are derived. Analytical results are verified through simulations. It is also shown that in comparison to non-cognitive selective cooperation, this scheme performs better in the low SNR region for cognitive networks. Moreover, the hidden Markov model's (HMM) multi-level variant hierarchical hidden Markov model (HHMM) approach is used for pattern recognition and event detection for the data received for this system [4]. Using this model, a feedback and decision algorithm is also developed. This approach has been applied to simulated water pressure data from RFID motes, which were embedded in metallic water pipes.

Guidelines for developing and updating Bayesian belief networks applied to ecological modeling and conservation.

Treesearch

B.G. Marcot; J.D. Steventon; G.D. Sutherland; R.K. McCann

2006-01-01

We provide practical guidelines for developing, testing, and revising Bayesian belief networks (BBNs). Primary steps in this process include creating influence diagrams of the hypothesized "causal web" of key factors affecting a species or ecological outcome of interest; developing a first, alpha-level BBN model from the influence diagram; revising the model...

The performance of diphoton primary vertex reconstruction methods in H → γγ+Met channel of ATLAS experiment

NASA Astrophysics Data System (ADS)

Tomiwa, K. G.

2017-09-01

The search for new physics in the H → γγ+met relies on how well the missing transverse energy is reconstructed. The Met algorithm used by the ATLAS experiment in turns uses input variables like photon and jets which depend on the reconstruction of the primary vertex. This document presents the performance of di-photon vertex reconstruction algorithms (hardest vertex method and Neural Network method). Comparing the performance of these algorithms for the nominal Standard Model sample and the Beyond Standard Model sample, we see the overall performance of the Neural Network method of primary vertex selection performed better than the Hardest vertex method.

Provider Network Development under the Department of Defense Coordinated Care Program: A Methodology for Primary Care Network Development and Its Implementation in the San Antonio Service Area

DTIC Science & Technology

1993-04-01

for using out-of- network benefits . * A gatekeeper physician controls access to the network and is paid on a capitated or discounted fee- for-service...Model ...................... 84 Figure 10. Organization Under Managed Care/HMO Concept ............... 94 APPENDIX 1. Benefit Under CCP 2. Group Model...increases, yet our health indicators have not improved (e.g., infant mortality, adult mortality, morbidity, or life expectancy). The aging population, the

Family-centred care delivery: comparing models of primary care service delivery in Ontario.

PubMed

Mayo-Bruinsma, Liesha; Hogg, William; Taljaard, Monica; Dahrouge, Simone

2013-11-01

To determine whether models of primary care service delivery differ in their provision of family-centred care (FCC) and to identify practice characteristics associated with FCC. Cross-sectional study. Primary care practices in Ontario (ie, 35 salaried community health centres, 35 fee-for-service practices, 32 capitation-based health service organizations, and 35 blended remuneration family health networks) that belong to 4 models of primary care service delivery. A total of 137 practices, 363 providers, and 5144 patients. Measures of FCC in patient and provider surveys were based on the Primary Care Assessment Tool. Statistical analyses were conducted using linear mixed regression models and generalized estimating equations. Patient-reported FCC scores were high and did not vary significantly by primary care model. Larger panel size in a practice was associated with lower odds of patients reporting FCC. Provider-reported FCC scores were significantly higher in community health centres than in family health networks (P = .035). A larger number of nurse practitioners and clinical services on-site were both associated with higher FCC scores, while scores decreased as the number of family physicians in a practice increased and if practices were more rural. Based on provider and patient reports, primary care reform strategies that encourage larger practices and more patients per family physician might compromise the provision of FCC, while strategies that encourage multidisciplinary practices and a range of services might increase FCC.

Improving Image Segmentation with Adaptive, Recurrent, Spiking Neural Network Models of the Primary Visual Cortex

DTIC Science & Technology

2017-05-19

Vijay Singh, Martin Tchernookov, Rebecca Butterfield, Ilya Nemenman, Rongrong Ji. Director Field Model of the Primary Visual Cortex for Contour...FTE Equivalent: Total Number: DISCIPLINE Vijay Singh 40 Physics 0.40 1 PERCENT_SUPPORTEDNAME FTE Equivalent: Total Number: Martin Tchernookov 0.20

Image/video understanding systems based on network-symbolic models

NASA Astrophysics Data System (ADS)

Kuvich, Gary

2004-03-01

Vision is a part of a larger information system that converts visual information into knowledge structures. These structures drive vision process, resolve ambiguity and uncertainty via feedback projections, and provide image understanding that is an interpretation of visual information in terms of such knowledge models. Computer simulation models are built on the basis of graphs/networks. The ability of human brain to emulate similar graph/network models is found. Symbols, predicates and grammars naturally emerge in such networks, and logic is simply a way of restructuring such models. Brain analyzes an image as a graph-type relational structure created via multilevel hierarchical compression of visual information. Primary areas provide active fusion of image features on a spatial grid-like structure, where nodes are cortical columns. Spatial logic and topology naturally present in such structures. Mid-level vision processes like perceptual grouping, separation of figure from ground, are special kinds of network transformations. They convert primary image structure into the set of more abstract ones, which represent objects and visual scene, making them easy for analysis by higher-level knowledge structures. Higher-level vision phenomena are results of such analysis. Composition of network-symbolic models combines learning, classification, and analogy together with higher-level model-based reasoning into a single framework, and it works similar to frames and agents. Computational intelligence methods transform images into model-based knowledge representation. Based on such principles, an Image/Video Understanding system can convert images into the knowledge models, and resolve uncertainty and ambiguity. This allows creating intelligent computer vision systems for design and manufacturing.

Engineering online and in-person social networks to sustain physical activity: application of a conceptual model.

PubMed

Rovniak, Liza S; Sallis, James F; Kraschnewski, Jennifer L; Sciamanna, Christopher N; Kiser, Elizabeth J; Ray, Chester A; Chinchilli, Vernon M; Ding, Ding; Matthews, Stephen A; Bopp, Melissa; George, Daniel R; Hovell, Melbourne F

2013-08-14

High rates of physical inactivity compromise the health status of populations globally. Social networks have been shown to influence physical activity (PA), but little is known about how best to engineer social networks to sustain PA. To improve procedures for building networks that shape PA as a normative behavior, there is a need for more specific hypotheses about how social variables influence PA. There is also a need to integrate concepts from network science with ecological concepts that often guide the design of in-person and electronically-mediated interventions. Therefore, this paper: (1) proposes a conceptual model that integrates principles from network science and ecology across in-person and electronically-mediated intervention modes; and (2) illustrates the application of this model to the design and evaluation of a social network intervention for PA. A conceptual model for engineering social networks was developed based on a scoping literature review of modifiable social influences on PA. The model guided the design of a cluster randomized controlled trial in which 308 sedentary adults were randomly assigned to three groups: WalkLink+: prompted and provided feedback on participants' online and in-person social-network interactions to expand networks for PA, plus provided evidence-based online walking program and weekly walking tips; WalkLink: evidence-based online walking program and weekly tips only; Minimal Treatment Control: weekly tips only. The effects of these treatment conditions were assessed at baseline, post-program, and 6-month follow-up. The primary outcome was accelerometer-measured PA. Secondary outcomes included objectively-measured aerobic fitness, body mass index, waist circumference, blood pressure, and neighborhood walkability; and self-reported measures of the physical environment, social network environment, and social network interactions. The differential effects of the three treatment conditions on primary and secondary outcomes will be analyzed using general linear modeling (GLM), or generalized linear modeling if the assumptions for GLM cannot be met. Results will contribute to greater understanding of how to conceptualize and implement social networks to support long-term PA. Establishing social networks for PA across multiple life settings could contribute to cultural norms that sustain active living. ClinicalTrials.gov NCT01142804.

Multiphase flow predictions from carbonate pore space images using extracted network models

NASA Astrophysics Data System (ADS)

Al-Kharusi, Anwar S.; Blunt, Martin J.

2008-06-01

A methodology to extract networks from pore space images is used to make predictions of multiphase transport properties for subsurface carbonate samples. The extraction of the network model is based on the computation of the location and sizes of pores and throats to create a topological representation of the void space of three-dimensional (3-D) rock images, using the concept of maximal balls. In this work, we follow a multistaged workflow. We start with a 2-D thin-section image; convert it statistically into a 3-D representation of the pore space; extract a network model from this image; and finally, simulate primary drainage, waterflooding, and secondary drainage flow processes using a pore-scale simulator. We test this workflow for a reservoir carbonate rock. The network-predicted absolute permeability is similar to the core plug measured value and the value computed on the 3-D void space image using the lattice Boltzmann method. The predicted capillary pressure during primary drainage agrees well with a mercury-air experiment on a core sample, indicating that we have an adequate representation of the rock's pore structure. We adjust the contact angles in the network to match the measured waterflood and secondary drainage capillary pressures. We infer a significant degree of contact angle hysteresis. We then predict relative permeabilities for primary drainage, waterflooding, and secondary drainage that agree well with laboratory measured values. This approach can be used to predict multiphase transport properties when wettability and pore structure vary in a reservoir, where experimental data is scant or missing. There are shortfalls to this approach, however. We compare results from three networks, one of which was derived from a section of the rock containing vugs. Our method fails to predict properties reliably when an unrepresentative image is processed to construct the 3-D network model. This occurs when the image volume is not sufficient to represent the geological variations observed in a core plug sample.

Robust network data envelopment analysis approach to evaluate the efficiency of regional electricity power networks under uncertainty.

PubMed

Fathollah Bayati, Mohsen; Sadjadi, Seyed Jafar

2017-01-01

In this paper, new Network Data Envelopment Analysis (NDEA) models are developed to evaluate the efficiency of regional electricity power networks. The primary objective of this paper is to consider perturbation in data and develop new NDEA models based on the adaptation of robust optimization methodology. Furthermore, in this paper, the efficiency of the entire networks of electricity power, involving generation, transmission and distribution stages is measured. While DEA has been widely used to evaluate the efficiency of the components of electricity power networks during the past two decades, there is no study to evaluate the efficiency of the electricity power networks as a whole. The proposed models are applied to evaluate the efficiency of 16 regional electricity power networks in Iran and the effect of data uncertainty is also investigated. The results are compared with the traditional network DEA and parametric SFA methods. Validity and verification of the proposed models are also investigated. The preliminary results indicate that the proposed models were more reliable than the traditional Network DEA model.

Robust network data envelopment analysis approach to evaluate the efficiency of regional electricity power networks under uncertainty

PubMed Central

Sadjadi, Seyed Jafar

2017-01-01

In this paper, new Network Data Envelopment Analysis (NDEA) models are developed to evaluate the efficiency of regional electricity power networks. The primary objective of this paper is to consider perturbation in data and develop new NDEA models based on the adaptation of robust optimization methodology. Furthermore, in this paper, the efficiency of the entire networks of electricity power, involving generation, transmission and distribution stages is measured. While DEA has been widely used to evaluate the efficiency of the components of electricity power networks during the past two decades, there is no study to evaluate the efficiency of the electricity power networks as a whole. The proposed models are applied to evaluate the efficiency of 16 regional electricity power networks in Iran and the effect of data uncertainty is also investigated. The results are compared with the traditional network DEA and parametric SFA methods. Validity and verification of the proposed models are also investigated. The preliminary results indicate that the proposed models were more reliable than the traditional Network DEA model. PMID:28953900

Proposal of a New Public Health End of Life approach for Brazil: how the Project EstaraoSeuLado-Primary Palliative Care is working and how it can help.

PubMed

Corrêa, Santiago

2018-01-01

Brazil has 206 million people, and 1.2 million deaths and 600,000 new cases of cancer per year. Palliative Care services are patchily distributed. The Family Health Strategy, made up from 41,000 primary care teams across Brazil forms a comprehensive primary care network. The Project EstaraoSeuLado-Primary Palliative Care developed working from Community Centers. We created a model based on compassionate communities, with community carers working alongside primary care teams. We identified people who need palliative care, gave them specific care and enrolled their carers into a program of monthly meetings called "Comunidade Cuidador". We discussed caring at end of life and provided skills training. During 2015 we ran 8 training programmes with an average of 10 carers. The major themes of discussion were carer burnout, dealing with denial and skills needed daily. The effect of these meetings was better relations between carers and professionals with expansion of the naturally occurring supportive network. The results of this project have been remarkable. The joint working of professionals and supportive networks together is recognised as being transformational. Carers themselves spread this approach by recommending it to others they know with life limiting illness. We will discuss the model and how it can be replicated more broadly across Brazil. Family Health teams can use tools of identification, evaluation and assessment working with networks including the community as an important part. We will propose a new model of End-of-Life Care to be adopted as national policy. We have implemented a compassionate community programme in the area of Rio Grande in Brazil. This has been a combination of primary care working in harmony with communities, providing education, resources and training to enhance the skill of communities to care for their dying. This is a necessary solution for Brazil, where resources and access to healthcare is limited. Our model is successful and increasing. We propose wider adoption of this model across Brazil and will present figures on the size of the challenge we face.

Energy Efficient Cooperation in Underlay RFID Cognitive Networks for a Water Smart Home

PubMed Central

Nasir, Adnan; Hussain, Syed Imtiaz; Soong, Boon-Hee; Qaraqe, Khalid

2014-01-01

Shrinking water resources all over the world and increasing costs of water consumption have prompted water users and distribution companies to come up with water conserving strategies. We have proposed an energy-efficient smart water monitoring application in [1], using low power RFIDs. In the home environment, there exist many primary interferences within a room, such as cell-phones, Bluetooth devices, TV signals, cordless phones and WiFi devices. In order to reduce the interference from our proposed RFID network for these primary devices, we have proposed a cooperating underlay RFID cognitive network for our smart application on water. These underlay RFIDs should strictly adhere to the interference thresholds to work in parallel with the primary wireless devices [2]. This work is an extension of our previous ventures proposed in [2,3], and we enhanced the previous efforts by introducing a new system model and RFIDs. Our proposed scheme is mutually energy efficient and maximizes the signal-to-noise ratio (SNR) for the RFID link, while keeping the interference levels for the primary network below a certain threshold. A closed form expression for the probability density function (pdf) of the SNR at the destination reader/writer and outage probability are derived. Analytical results are verified through simulations. It is also shown that in comparison to non-cognitive selective cooperation, this scheme performs better in the low SNR region for cognitive networks. Moreover, the hidden Markov model’s (HMM) multi-level variant hierarchical hidden Markov model (HHMM) approach is used for pattern recognition and event detection for the data received for this system [4]. Using this model, a feedback and decision algorithm is also developed. This approach has been applied to simulated water pressure data from RFID motes, which were embedded in metallic water pipes. PMID:25271565

Golden Ratio Genetic Algorithm Based Approach for Modelling and Analysis of the Capacity Expansion of Urban Road Traffic Network

PubMed Central

Zhang, Lun; Zhang, Meng; Yang, Wenchen; Dong, Decun

2015-01-01

This paper presents the modelling and analysis of the capacity expansion of urban road traffic network (ICURTN). Thebilevel programming model is first employed to model the ICURTN, in which the utility of the entire network is maximized with the optimal utility of travelers' route choice. Then, an improved hybrid genetic algorithm integrated with golden ratio (HGAGR) is developed to enhance the local search of simple genetic algorithms, and the proposed capacity expansion model is solved by the combination of the HGAGR and the Frank-Wolfe algorithm. Taking the traditional one-way network and bidirectional network as the study case, three numerical calculations are conducted to validate the presented model and algorithm, and the primary influencing factors on extended capacity model are analyzed. The calculation results indicate that capacity expansion of road network is an effective measure to enlarge the capacity of urban road network, especially on the condition of limited construction budget; the average computation time of the HGAGR is 122 seconds, which meets the real-time demand in the evaluation of the road network capacity. PMID:25802512

Adaptive threshold determination for efficient channel sensing in cognitive radio network using mobile sensors

NASA Astrophysics Data System (ADS)

Morshed, M. N.; Khatun, S.; Kamarudin, L. M.; Aljunid, S. A.; Ahmad, R. B.; Zakaria, A.; Fakir, M. M.

2017-03-01

Spectrum saturation problem is a major issue in wireless communication systems all over the world. Huge number of users is joining each day to the existing fixed band frequency but the bandwidth is not increasing. These requirements demand for efficient and intelligent use of spectrum. To solve this issue, the Cognitive Radio (CR) is the best choice. Spectrum sensing of a wireless heterogeneous network is a fundamental issue to detect the presence of primary users' signals in CR networks. In order to protect primary users (PUs) from harmful interference, the spectrum sensing scheme is required to perform well even in low signal-to-noise ratio (SNR) environments. Meanwhile, the sensing period is usually required to be short enough so that secondary (unlicensed) users (SUs) can fully utilize the available spectrum. CR networks can be designed to manage the radio spectrum more efficiently by utilizing the spectrum holes in primary user's licensed frequency bands. In this paper, we have proposed an adaptive threshold detection method to detect presence of PU signal using free space path loss (FSPL) model in 2.4 GHz WLAN network. The model is designed for mobile sensors embedded in smartphones. The mobile sensors acts as SU while the existing WLAN network (channels) works as PU. The theoretical results show that the desired threshold range detection of mobile sensors mainly depends on the noise floor level of the location in consideration.

An egalitarian network model for the emergence of simple and complex cells in visual cortex

PubMed Central

Tao, Louis; Shelley, Michael; McLaughlin, David; Shapley, Robert

2004-01-01

We explain how simple and complex cells arise in a large-scale neuronal network model of the primary visual cortex of the macaque. Our model consists of ≈4,000 integrate-and-fire, conductance-based point neurons, representing the cells in a small, 1-mm2 patch of an input layer of the primary visual cortex. In the model the local connections are isotropic and nonspecific, and convergent input from the lateral geniculate nucleus confers cortical cells with orientation and spatial phase preference. The balance between lateral connections and lateral geniculate nucleus drive determines whether individual neurons in this recurrent circuit are simple or complex. The model reproduces qualitatively the experimentally observed distributions of both extracellular and intracellular measures of simple and complex response. PMID:14695891

Experimental Analysis and Computational Modeling of Network States and Drug Responses in the PI3K/Akt/mTOR Network

DTIC Science & Technology

2010-09-01

Fixation was in 2% formaldehyde, followed by permeabilization in 100% methanol at -20 C. Blocking and incubation with primary/secondary antibodies ...was performed in Odyssey blocking buffer (LICOR). Primary antibodies were obtained from Cell Signaling, BD Biosciences, and Santa Cruz...Biotechnology, and Alexa fluor 488-, 555-, or 647-conjugated secondary antibodies were obtained from Invitrogen. Data were collected using an Applied Precision

FindPrimaryPairs: An efficient algorithm for predicting element-transferring reactant/product pairs in metabolic networks.

PubMed

Steffensen, Jon Lund; Dufault-Thompson, Keith; Zhang, Ying

2018-01-01

The metabolism of individual organisms and biological communities can be viewed as a network of metabolites connected to each other through chemical reactions. In metabolic networks, chemical reactions transform reactants into products, thereby transferring elements between these metabolites. Knowledge of how elements are transferred through reactant/product pairs allows for the identification of primary compound connections through a metabolic network. However, such information is not readily available and is often challenging to obtain for large reaction databases or genome-scale metabolic models. In this study, a new algorithm was developed for automatically predicting the element-transferring reactant/product pairs using the limited information available in the standard representation of metabolic networks. The algorithm demonstrated high efficiency in analyzing large datasets and provided accurate predictions when benchmarked with manually curated data. Applying the algorithm to the visualization of metabolic networks highlighted pathways of primary reactant/product connections and provided an organized view of element-transferring biochemical transformations. The algorithm was implemented as a new function in the open source software package PSAMM in the release v0.30 (https://zhanglab.github.io/psamm/).

Network Receptive Field Modeling Reveals Extensive Integration and Multi-feature Selectivity in Auditory Cortical Neurons.

PubMed

Harper, Nicol S; Schoppe, Oliver; Willmore, Ben D B; Cui, Zhanfeng; Schnupp, Jan W H; King, Andrew J

2016-11-01

Cortical sensory neurons are commonly characterized using the receptive field, the linear dependence of their response on the stimulus. In primary auditory cortex neurons can be characterized by their spectrotemporal receptive fields, the spectral and temporal features of a sound that linearly drive a neuron. However, receptive fields do not capture the fact that the response of a cortical neuron results from the complex nonlinear network in which it is embedded. By fitting a nonlinear feedforward network model (a network receptive field) to cortical responses to natural sounds, we reveal that primary auditory cortical neurons are sensitive over a substantially larger spectrotemporal domain than is seen in their standard spectrotemporal receptive fields. Furthermore, the network receptive field, a parsimonious network consisting of 1-7 sub-receptive fields that interact nonlinearly, consistently better predicts neural responses to auditory stimuli than the standard receptive fields. The network receptive field reveals separate excitatory and inhibitory sub-fields with different nonlinear properties, and interaction of the sub-fields gives rise to important operations such as gain control and conjunctive feature detection. The conjunctive effects, where neurons respond only if several specific features are present together, enable increased selectivity for particular complex spectrotemporal structures, and may constitute an important stage in sound recognition. In conclusion, we demonstrate that fitting auditory cortical neural responses with feedforward network models expands on simple linear receptive field models in a manner that yields substantially improved predictive power and reveals key nonlinear aspects of cortical processing, while remaining easy to interpret in a physiological context.

Network Receptive Field Modeling Reveals Extensive Integration and Multi-feature Selectivity in Auditory Cortical Neurons

PubMed Central

Willmore, Ben D. B.; Cui, Zhanfeng; Schnupp, Jan W. H.; King, Andrew J.

2016-01-01

Cortical sensory neurons are commonly characterized using the receptive field, the linear dependence of their response on the stimulus. In primary auditory cortex neurons can be characterized by their spectrotemporal receptive fields, the spectral and temporal features of a sound that linearly drive a neuron. However, receptive fields do not capture the fact that the response of a cortical neuron results from the complex nonlinear network in which it is embedded. By fitting a nonlinear feedforward network model (a network receptive field) to cortical responses to natural sounds, we reveal that primary auditory cortical neurons are sensitive over a substantially larger spectrotemporal domain than is seen in their standard spectrotemporal receptive fields. Furthermore, the network receptive field, a parsimonious network consisting of 1–7 sub-receptive fields that interact nonlinearly, consistently better predicts neural responses to auditory stimuli than the standard receptive fields. The network receptive field reveals separate excitatory and inhibitory sub-fields with different nonlinear properties, and interaction of the sub-fields gives rise to important operations such as gain control and conjunctive feature detection. The conjunctive effects, where neurons respond only if several specific features are present together, enable increased selectivity for particular complex spectrotemporal structures, and may constitute an important stage in sound recognition. In conclusion, we demonstrate that fitting auditory cortical neural responses with feedforward network models expands on simple linear receptive field models in a manner that yields substantially improved predictive power and reveals key nonlinear aspects of cortical processing, while remaining easy to interpret in a physiological context. PMID:27835647

The role of a bus network in access to primary health care in Metropolitan Auckland, New Zealand.

PubMed

Rocha, C M; McGuire, S; Whyman, R; Kruger, E; Tennant, M

2015-09-01

Background: This study examined the spatial accessibility of the population of metropolitan Auckland, New Zealand to the bus network, to connect them to primary health providers, in this case doctors (GP) and dentists. Analysis of accessibility by ethnic identity and socio-economic status were also carried out, because of existing health inequalities along these dimensions. The underlying hypothesis was that most people would live within easy reach of primary health providers, or easy bus transport to such providers. An integrated geographic model of bus transport routes and stops, with population and primary health providers (medical. and dental practices) was developed and analysed. Although the network of buses in metropolitan Auckland is substantial and robust it was evident that many people live more than 150 metres from a stop. Improving the access to bus stops, particularly in areas of high primary health care need (doctors and dentists), would certainly be an opportunity to enhance spatial access in a growing metropolitan area.

Optimization of OSPF Routing in IP Networks

NASA Astrophysics Data System (ADS)

Bley, Andreas; Fortz, Bernard; Gourdin, Eric; Holmberg, Kaj; Klopfenstein, Olivier; Pióro, Michał; Tomaszewski, Artur; Ümit, Hakan

The Internet is a huge world-wide packet switching network comprised of more than 13,000 distinct subnetworks, referred to as Autonomous Systems (ASs) autonomous system AS . They all rely on the Internet Protocol (IP) internet protocol IP for transport of packets across the network. And most of them use shortest path routing protocols shortest path routing!protocols , such as OSPF or IS-IS, to control the routing of IP packets routing!of IP packets within an AS. The idea of the routing is extremely simple — every packet is forwarded on IP links along the shortest route between its source and destination nodes of the AS. The AS network administrator can manage the routing of packets in the AS by supplying the so-called administrative weights of IP links, which specify the link lengths that are used by the routing protocols for their shortest path computations. The main advantage of the shortest path routing policy is its simplicity, allowing for little administrative overhead. From the network engineering perspective, however, shortest path routing can pose problems in achieving satisfactory traffic handling efficiency. As all routing paths depend on the same routing metric routing!metric , it is not possible to configure the routing paths for the communication demands between different pairs of nodes explicitly or individually; the routing can be controlled only indirectly and only as a whole by modifying the routing metric. Thus, one of the main tasks when planning such networks is to find administrative link weights that induce a globally efficient traffic routing traffic!routing configuration of an AS. It turns out that this task leads to very difficult mathematical optimization problems. In this chapter, we discuss and describe exact integer programming models and solution approaches as well as practically efficient smart heuristics for such shortest path routing problems shortest path routing!problems .

Do project management and network governance contribute to inter-organisational collaboration in primary care? A mixed methods study.

PubMed

Schepman, Sanneke; Valentijn, Pim; Bruijnzeels, Marc; Maaijen, Marlies; de Bakker, Dinny; Batenburg, Ronald; de Bont, Antoinette

2018-06-07

The need for organisational development in primary care has increased as it is accepted as a means of curbing rising costs and responding to demographic transitions. It is only within such inter-organisational networks that small-scale practices can offer treatment to complex patients and continuity of care. The aim of this paper is to explore, through the experience of professionals and patients, whether, and how, project management and network governance can improve the outcomes of projects which promote inter-organisational collaboration in primary care. This paper describes a study of projects aimed at improving inter-organisational collaboration in Dutch primary care. The projects' success in project management and network governance was monitored by interviewing project leaders and board members on the one hand, and improvement in the collaboration by surveying professionals and patients on the other. Both qualitative and quantitative methods were applied to assess the projects. These were analysed, finally, using multi-level models in order to account for the variation in the projects, professionals and patients. Successful network governance was associated positively with the professionals' satisfaction with the collaboration; but not with improvements in the quality of care as experienced by patients. Neither patients nor professionals perceived successful project management as associated with the outcomes of the collaboration projects. This study shows that network governance in particular makes a difference to the outcomes of inter-organisational collaboration in primary care. However, project management is not a predictor for successful inter-organisational collaboration in primary care.

Engineering online and in-person social networks to sustain physical activity: application of a conceptual model

PubMed Central

2013-01-01

Background High rates of physical inactivity compromise the health status of populations globally. Social networks have been shown to influence physical activity (PA), but little is known about how best to engineer social networks to sustain PA. To improve procedures for building networks that shape PA as a normative behavior, there is a need for more specific hypotheses about how social variables influence PA. There is also a need to integrate concepts from network science with ecological concepts that often guide the design of in-person and electronically-mediated interventions. Therefore, this paper: (1) proposes a conceptual model that integrates principles from network science and ecology across in-person and electronically-mediated intervention modes; and (2) illustrates the application of this model to the design and evaluation of a social network intervention for PA. Methods/Design A conceptual model for engineering social networks was developed based on a scoping literature review of modifiable social influences on PA. The model guided the design of a cluster randomized controlled trial in which 308 sedentary adults were randomly assigned to three groups: WalkLink+: prompted and provided feedback on participants’ online and in-person social-network interactions to expand networks for PA, plus provided evidence-based online walking program and weekly walking tips; WalkLink: evidence-based online walking program and weekly tips only; Minimal Treatment Control: weekly tips only. The effects of these treatment conditions were assessed at baseline, post-program, and 6-month follow-up. The primary outcome was accelerometer-measured PA. Secondary outcomes included objectively-measured aerobic fitness, body mass index, waist circumference, blood pressure, and neighborhood walkability; and self-reported measures of the physical environment, social network environment, and social network interactions. The differential effects of the three treatment conditions on primary and secondary outcomes will be analyzed using general linear modeling (GLM), or generalized linear modeling if the assumptions for GLM cannot be met. Discussion Results will contribute to greater understanding of how to conceptualize and implement social networks to support long-term PA. Establishing social networks for PA across multiple life settings could contribute to cultural norms that sustain active living. Trial registration ClinicalTrials.gov NCT01142804 PMID:23945138

Can longitudinal generalized estimating equation models distinguish network influence and homophily? An agent-based modeling approach to measurement characteristics.

PubMed

Sauser Zachrison, Kori; Iwashyna, Theodore J; Gebremariam, Achamyeleh; Hutchins, Meghan; Lee, Joyce M

2016-12-28

Connected individuals (or nodes) in a network are more likely to be similar than two randomly selected nodes due to homophily and/or network influence. Distinguishing between these two influences is an important goal in network analysis, and generalized estimating equation (GEE) analyses of longitudinal dyadic network data are an attractive approach. It is not known to what extent such regressions can accurately extract underlying data generating processes. Therefore our primary objective is to determine to what extent, and under what conditions, does the GEE-approach recreate the actual dynamics in an agent-based model. We generated simulated cohorts with pre-specified network characteristics and attachments in both static and dynamic networks, and we varied the presence of homophily and network influence. We then used statistical regression and examined the GEE model performance in each cohort to determine whether the model was able to detect the presence of homophily and network influence. In cohorts with both static and dynamic networks, we find that the GEE models have excellent sensitivity and reasonable specificity for determining the presence or absence of network influence, but little ability to distinguish whether or not homophily is present. The GEE models are a valuable tool to examine for the presence of network influence in longitudinal data, but are quite limited with respect to homophily.

Hybrid Scheme for Modeling Local Field Potentials from Point-Neuron Networks.

PubMed

Hagen, Espen; Dahmen, David; Stavrinou, Maria L; Lindén, Henrik; Tetzlaff, Tom; van Albada, Sacha J; Grün, Sonja; Diesmann, Markus; Einevoll, Gaute T

2016-12-01

With rapidly advancing multi-electrode recording technology, the local field potential (LFP) has again become a popular measure of neuronal activity in both research and clinical applications. Proper understanding of the LFP requires detailed mathematical modeling incorporating the anatomical and electrophysiological features of neurons near the recording electrode, as well as synaptic inputs from the entire network. Here we propose a hybrid modeling scheme combining efficient point-neuron network models with biophysical principles underlying LFP generation by real neurons. The LFP predictions rely on populations of network-equivalent multicompartment neuron models with layer-specific synaptic connectivity, can be used with an arbitrary number of point-neuron network populations, and allows for a full separation of simulated network dynamics and LFPs. We apply the scheme to a full-scale cortical network model for a ∼1 mm 2 patch of primary visual cortex, predict laminar LFPs for different network states, assess the relative LFP contribution from different laminar populations, and investigate effects of input correlations and neuron density on the LFP. The generic nature of the hybrid scheme and its public implementation in hybridLFPy form the basis for LFP predictions from other and larger point-neuron network models, as well as extensions of the current application with additional biological detail. © The Author 2016. Published by Oxford University Press.

Enhanced polychronization in a spiking network with metaplasticity.

PubMed

Guise, Mira; Knott, Alistair; Benuskova, Lubica

2015-01-01

Computational models of metaplasticity have usually focused on the modeling of single synapses (Shouval et al., 2002). In this paper we study the effect of metaplasticity on network behavior. Our guiding assumption is that the primary purpose of metaplasticity is to regulate synaptic plasticity, by increasing it when input is low and decreasing it when input is high. For our experiments we adopt a model of metaplasticity that demonstrably has this effect for a single synapse; our primary interest is in how metaplasticity thus defined affects network-level phenomena. We focus on a network-level phenomenon called polychronicity, that has a potential role in representation and memory. A network with polychronicity has the ability to produce non-synchronous but precisely timed sequences of neural firing events that can arise from strongly connected groups of neurons called polychronous neural groups (Izhikevich et al., 2004). Polychronous groups (PNGs) develop readily when spiking networks are exposed to repeated spatio-temporal stimuli under the influence of spike-timing-dependent plasticity (STDP), but are sensitive to changes in synaptic weight distribution. We use a technique we have recently developed called Response Fingerprinting to show that PNGs formed in the presence of metaplasticity are significantly larger than those with no metaplasticity. A potential mechanism for this enhancement is proposed that links an inherent property of integrator type neurons called spike latency to an increase in the tolerance of PNG neurons to jitter in their inputs.

Modeling Social Influences in a Knowledge Management Network

ERIC Educational Resources Information Center

Franco, Giacomo; Maresca, Paolo; Nota, Giancarlo

2010-01-01

The issue of knowledge management in a distributed network is receiving increasing attention from both scientific and industrial organizations. Research efforts in this field are motivated by the awareness that knowledge is more and more perceived as a primary economic resource and that, in the context of organization of organizations, the…

Spectrum Sharing Based on a Bertrand Game in Cognitive Radio Sensor Networks

PubMed Central

Zeng, Biqing; Zhang, Chi; Hu, Pianpian; Wang, Shengyu

2017-01-01

In the study of power control and allocation based on pricing, the utility of secondary users is usually studied from the perspective of the signal to noise ratio. The study of secondary user utility from the perspective of communication demand can not only promote the secondary users to meet the maximum communication needs, but also to maximize the utilization of spectrum resources, however, research in this area is lacking, so from the viewpoint of meeting the demand of network communication, this paper designs a two stage model to solve spectrum leasing and allocation problem in cognitive radio sensor networks (CRSNs). In the first stage, the secondary base station collects the secondary network communication requirements, and rents spectrum resources from several primary base stations using the Bertrand game to model the transaction behavior of the primary base station and secondary base station. The second stage, the subcarriers and power allocation problem of secondary base stations is defined as a nonlinear programming problem to be solved based on Nash bargaining. The simulation results show that the proposed model can satisfy the communication requirements of each user in a fair and efficient way compared to other spectrum sharing schemes. PMID:28067850

Readiness for the Patient-Centered Medical Home: structural capabilities of Massachusetts primary care practices.

PubMed

Friedberg, Mark W; Safran, Dana G; Coltin, Kathryn L; Dresser, Marguerite; Schneider, Eric C

2009-02-01

The Patient-Centered Medical Home (PCMH), a popular model for primary care reorganization, includes several structural capabilities intended to enhance quality of care. The extent to which different types of primary care practices have adopted these capabilities has not been previously studied. To measure the prevalence of recommended structural capabilities among primary care practices and to determine whether prevalence varies among practices of different size (number of physicians) and administrative affiliation with networks of practices. Cross-sectional analysis. One physician chosen at random from each of 412 primary care practices in Massachusetts was surveyed about practice capabilities during 2007. Practice size and network affiliation were obtained from an existing database. Presence of 13 structural capabilities representing 4 domains relevant to quality: patient assistance and reminders, culture of quality, enhanced access, and electronic health records (EHRs). Three hundred eight (75%) physicians responded, representing practices with a median size of 4 physicians (range 2-74). Among these practices, 64% were affiliated with 1 of 9 networks. The prevalence of surveyed capabilities ranged from 24% to 88%. Larger practice size was associated with higher prevalence for 9 of the 13 capabilities spanning all 4 domains (P < 0.05). Network affiliation was associated with higher prevalence of 5 capabilities (P < 0.05) in 3 domains. Associations were not substantively altered by statistical adjustment for other practice characteristics. Larger and network-affiliated primary care practices are more likely than smaller, non-affiliated practices to have adopted several recommended capabilities. In order to achieve PCMH designation, smaller non-affiliated practices may require the greatest investments.

A novel interacting multiple model based network intrusion detection scheme

NASA Astrophysics Data System (ADS)

Xin, Ruichi; Venkatasubramanian, Vijay; Leung, Henry

2006-04-01

In today's information age, information and network security are of primary importance to any organization. Network intrusion is a serious threat to security of computers and data networks. In internet protocol (IP) based network, intrusions originate in different kinds of packets/messages contained in the open system interconnection (OSI) layer 3 or higher layers. Network intrusion detection and prevention systems observe the layer 3 packets (or layer 4 to 7 messages) to screen for intrusions and security threats. Signature based methods use a pre-existing database that document intrusion patterns as perceived in the layer 3 to 7 protocol traffics and match the incoming traffic for potential intrusion attacks. Alternately, network traffic data can be modeled and any huge anomaly from the established traffic pattern can be detected as network intrusion. The latter method, also known as anomaly based detection is gaining popularity for its versatility in learning new patterns and discovering new attacks. It is apparent that for a reliable performance, an accurate model of the network data needs to be established. In this paper, we illustrate using collected data that network traffic is seldom stationary. We propose the use of multiple models to accurately represent the traffic data. The improvement in reliability of the proposed model is verified by measuring the detection and false alarm rates on several datasets.

Family-centred care delivery

PubMed Central

Mayo-Bruinsma, Liesha; Hogg, William; Taljaard, Monica; Dahrouge, Simone

2013-01-01

Abstract Objective To determine whether models of primary care service delivery differ in their provision of family-centred care (FCC) and to identify practice characteristics associated with FCC. Design Cross-sectional study. Setting Primary care practices in Ontario (ie, 35 salaried community health centres, 35 fee-for-service practices, 32 capitation-based health service organizations, and 35 blended remuneration family health networks) that belong to 4 models of primary care service delivery. Participants A total of 137 practices, 363 providers, and 5144 patients. Main outcome measures Measures of FCC in patient and provider surveys were based on the Primary Care Assessment Tool. Statistical analyses were conducted using linear mixed regression models and generalized estimating equations. Results Patient-reported FCC scores were high and did not vary significantly by primary care model. Larger panel size in a practice was associated with lower odds of patients reporting FCC. Provider-reported FCC scores were significantly higher in community health centres than in family health networks (P = .035). A larger number of nurse practitioners and clinical services on-site were both associated with higher FCC scores, while scores decreased as the number of family physicians in a practice increased and if practices were more rural. Conclusion Based on provider and patient reports, primary care reform strategies that encourage larger practices and more patients per family physician might compromise the provision of FCC, while strategies that encourage multidisciplinary practices and a range of services might increase FCC. PMID:24235195

International Neural Network Society Annual Meeting (1994) Held in San Diego, California on 5-9 June 1994. Volume 3.

DTIC Science & Technology

1994-06-09

Competitive Neural Nets Speed Complex Fluid Flow Calculations 1-366 T. Long, E. Hanzevack Neural Networks for Steam Boiler MIMO Modeling and Advisory Control...Gallinr The Cochlear Nucleus and Primary Cortex as a Sequence of Distributed Neural Filters in Phoneme IV-607 Perception J. Antrobus, C. Tarshish, S...propulsion linear model, a fuel flow actuator modelled as a linear second order system with position and rate limits, and a thrust vectoring actuator

Analyzing neuronal networks using discrete-time dynamics

NASA Astrophysics Data System (ADS)

Ahn, Sungwoo; Smith, Brian H.; Borisyuk, Alla; Terman, David

2010-05-01

We develop mathematical techniques for analyzing detailed Hodgkin-Huxley like models for excitatory-inhibitory neuronal networks. Our strategy for studying a given network is to first reduce it to a discrete-time dynamical system. The discrete model is considerably easier to analyze, both mathematically and computationally, and parameters in the discrete model correspond directly to parameters in the original system of differential equations. While these networks arise in many important applications, a primary focus of this paper is to better understand mechanisms that underlie temporally dynamic responses in early processing of olfactory sensory information. The models presented here exhibit several properties that have been described for olfactory codes in an insect’s Antennal Lobe. These include transient patterns of synchronization and decorrelation of sensory inputs. By reducing the model to a discrete system, we are able to systematically study how properties of the dynamics, including the complex structure of the transients and attractors, depend on factors related to connectivity and the intrinsic and synaptic properties of cells within the network.

A model for the electronic support of practice-based research networks.

PubMed

Peterson, Kevin A; Delaney, Brendan C; Arvanitis, Theodoros N; Taweel, Adel; Sandberg, Elisabeth A; Speedie, Stuart; Richard Hobbs, F D

2012-01-01

The principal goal of the electronic Primary Care Research Network (ePCRN) is to enable the development of an electronic infrastructure to support clinical research activities in primary care practice-based research networks (PBRNs). We describe the model that the ePCRN developed to enhance the growth and to expand the reach of PBRN research. Use cases and activity diagrams were developed from interviews with key informants from 11 PBRNs from the United States and United Kingdom. Discrete functions were identified and aggregated into logical components. Interaction diagrams were created, and an overall composite diagram was constructed describing the proposed software behavior. Software for each component was written and aggregated, and the resulting prototype application was pilot tested for feasibility. A practical model was then created by separating application activities into distinct software packages based on existing PBRN business rules, hardware requirements, network requirements, and security concerns. We present an information architecture that provides for essential interactions, activities, data flows, and structural elements necessary for providing support for PBRN translational research activities. The model describes research information exchange between investigators and clusters of independent data sites supported by a contracted research director. The model was designed to support recruitment for clinical trials, collection of aggregated anonymous data, and retrieval of identifiable data from previously consented patients across hundreds of practices. The proposed model advances our understanding of the fundamental roles and activities of PBRNs and defines the information exchange commonly used by PBRNs to successfully engage community health care clinicians in translational research activities. By describing the network architecture in a language familiar to that used by software developers, the model provides an important foundation for the development of electronic support for essential PBRN research activities.

Shaping Neuronal Network Activity by Presynaptic Mechanisms

PubMed Central

Ashery, Uri

2015-01-01

Neuronal microcircuits generate oscillatory activity, which has been linked to basic functions such as sleep, learning and sensorimotor gating. Although synaptic release processes are well known for their ability to shape the interaction between neurons in microcircuits, most computational models do not simulate the synaptic transmission process directly and hence cannot explain how changes in synaptic parameters alter neuronal network activity. In this paper, we present a novel neuronal network model that incorporates presynaptic release mechanisms, such as vesicle pool dynamics and calcium-dependent release probability, to model the spontaneous activity of neuronal networks. The model, which is based on modified leaky integrate-and-fire neurons, generates spontaneous network activity patterns, which are similar to experimental data and robust under changes in the model's primary gain parameters such as excitatory postsynaptic potential and connectivity ratio. Furthermore, it reliably recreates experimental findings and provides mechanistic explanations for data obtained from microelectrode array recordings, such as network burst termination and the effects of pharmacological and genetic manipulations. The model demonstrates how elevated asynchronous release, but not spontaneous release, synchronizes neuronal network activity and reveals that asynchronous release enhances utilization of the recycling vesicle pool to induce the network effect. The model further predicts a positive correlation between vesicle priming at the single-neuron level and burst frequency at the network level; this prediction is supported by experimental findings. Thus, the model is utilized to reveal how synaptic release processes at the neuronal level govern activity patterns and synchronization at the network level. PMID:26372048

General method to find the attractors of discrete dynamic models of biological systems.

PubMed

Gan, Xiao; Albert, Réka

2018-04-01

Analyzing the long-term behaviors (attractors) of dynamic models of biological networks can provide valuable insight. We propose a general method that can find the attractors of multilevel discrete dynamical systems by extending a method that finds the attractors of a Boolean network model. The previous method is based on finding stable motifs, subgraphs whose nodes' states can stabilize on their own. We extend the framework from binary states to any finite discrete levels by creating a virtual node for each level of a multilevel node, and describing each virtual node with a quasi-Boolean function. We then create an expanded representation of the multilevel network, find multilevel stable motifs and oscillating motifs, and identify attractors by successive network reduction. In this way, we find both fixed point attractors and complex attractors. We implemented an algorithm, which we test and validate on representative synthetic networks and on published multilevel models of biological networks. Despite its primary motivation to analyze biological networks, our motif-based method is general and can be applied to any finite discrete dynamical system.

General method to find the attractors of discrete dynamic models of biological systems

NASA Astrophysics Data System (ADS)

Gan, Xiao; Albert, Réka

2018-04-01

Analyzing the long-term behaviors (attractors) of dynamic models of biological networks can provide valuable insight. We propose a general method that can find the attractors of multilevel discrete dynamical systems by extending a method that finds the attractors of a Boolean network model. The previous method is based on finding stable motifs, subgraphs whose nodes' states can stabilize on their own. We extend the framework from binary states to any finite discrete levels by creating a virtual node for each level of a multilevel node, and describing each virtual node with a quasi-Boolean function. We then create an expanded representation of the multilevel network, find multilevel stable motifs and oscillating motifs, and identify attractors by successive network reduction. In this way, we find both fixed point attractors and complex attractors. We implemented an algorithm, which we test and validate on representative synthetic networks and on published multilevel models of biological networks. Despite its primary motivation to analyze biological networks, our motif-based method is general and can be applied to any finite discrete dynamical system.

Developing a Framework for Effective Network Capacity Planning

NASA Technical Reports Server (NTRS)

Yaprak, Ece

2005-01-01

As Internet traffic continues to grow exponentially, developing a clearer understanding of, and appropriately measuring, network's performance is becoming ever more critical. An important challenge faced by the Information Resources Directorate (IRD) at the Johnson Space Center in this context remains not only monitoring and maintaining a secure network, but also better understanding the capacity and future growth potential boundaries of its network. This requires capacity planning which involves modeling and simulating different network alternatives, and incorporating changes in design as technologies, components, configurations, and applications change, to determine optimal solutions in light of IRD's goals, objectives and strategies. My primary task this summer was to address this need. I evaluated network-modeling tools from OPNET Technologies Inc. and Compuware Corporation. I generated a baseline model for Building 45 using both tools by importing "real" topology/traffic information using IRD's various network management tools. I compared each tool against the other in terms of the advantages and disadvantages of both tools to accomplish IRD's goals. I also prepared step-by-step "how to design a baseline model" tutorial for both OPNET and Compuware products.

Bifurcations: Focal Points of Particle Adhesion in Microvascular Networks

PubMed Central

Prabhakarpandian, Balabhaskar; Wang, Yi; Rea-Ramsey, Angela; Sundaram, Shivshankar; Kiani, Mohammad F.; Pant, Kapil

2011-01-01

Objective Particle adhesion in vivo is dependent on microcirculation environment which features unique anatomical (bifurcations, tortuosity, cross-sectional changes) and physiological (complex hemodynamics) characteristics. The mechanisms behind these complex phenomena are not well understood. In this study, we used a recently developed in vitro model of microvascular networks, called Synthetic Microvascular Network, for characterizing particle adhesion patterns in the microcirculation. Methods Synthetic microvascular networks were fabricated using soft lithography processes followed by particle adhesion studies using avidin and biotin-conjugated microspheres. Particle adhesion patterns were subsequently analyzed using CFD based modeling. Results Experimental and modeling studies highlighted the complex and heterogeneous fluid flow patterns encountered by particles in microvascular networks resulting in significantly higher propensity of adhesion (>1.5X) near bifurcations compared to the branches of the microvascular networks. Conclusion Bifurcations are the focal points of particle adhesion in microvascular networks. Changing flow patterns and morphology near bifurcations are the primary factors controlling the preferential adhesion of functionalized particles in microvascular networks. Synthetic microvascular networks provide an in vitro framework for understanding particle adhesion. PMID:21418388

Stimulus-specific adaptation in a recurrent network model of primary auditory cortex

PubMed Central

2017-01-01

Stimulus-specific adaptation (SSA) occurs when neurons decrease their responses to frequently-presented (standard) stimuli but not, or not as much, to other, rare (deviant) stimuli. SSA is present in all mammalian species in which it has been tested as well as in birds. SSA confers short-term memory to neuronal responses, and may lie upstream of the generation of mismatch negativity (MMN), an important human event-related potential. Previously published models of SSA mostly rely on synaptic depression of the feedforward, thalamocortical input. Here we study SSA in a recurrent neural network model of primary auditory cortex. When the recurrent, intracortical synapses display synaptic depression, the network generates population spikes (PSs). SSA occurs in this network when deviants elicit a PS but standards do not, and we demarcate the regions in parameter space that allow SSA. While SSA based on PSs does not require feedforward depression, we identify feedforward depression as a mechanism for expanding the range of parameters that support SSA. We provide predictions for experiments that could help differentiate between SSA due to synaptic depression of feedforward connections and SSA due to synaptic depression of recurrent connections. Similar to experimental data, the magnitude of SSA in the model depends on the frequency difference between deviant and standard, probability of the deviant, inter-stimulus interval and input amplitude. In contrast to models based on feedforward depression, our model shows true deviance sensitivity as found in experiments. PMID:28288158

A systems-based partnership learning model for strengthening primary healthcare

PubMed Central

2013-01-01

Background Strengthening primary healthcare systems is vital to improving health outcomes and reducing inequity. However, there are few tools and models available in published literature showing how primary care system strengthening can be achieved on a large scale. Challenges to strengthening primary healthcare (PHC) systems include the dispersion, diversity and relative independence of primary care providers; the scope and complexity of PHC; limited infrastructure available to support population health approaches; and the generally poor and fragmented state of PHC information systems. Drawing on concepts of comprehensive PHC, integrated quality improvement (IQI) methods, system-based research networks, and system-based participatory action research, we describe a learning model for strengthening PHC that addresses these challenges. We describe the evolution of this model within the Australian Aboriginal and Torres Strait Islander primary healthcare context, successes and challenges in its application, and key issues for further research. Discussion IQI approaches combined with system-based participatory action research and system-based research networks offer potential to support program implementation and ongoing learning across a wide scope of primary healthcare practice and on a large scale. The Partnership Learning Model (PLM) can be seen as an integrated model for large-scale knowledge translation across the scope of priority aspects of PHC. With appropriate engagement of relevant stakeholders, the model may be applicable to a wide range of settings. In IQI, and in the PLM specifically, there is a clear role for research in contributing to refining and evaluating existing tools and processes, and in developing and trialling innovations. Achieving an appropriate balance between funding IQI activity as part of routine service delivery and funding IQI related research will be vital to developing and sustaining this type of PLM. Summary This paper draws together several different previously described concepts and extends the understanding of how PHC systems can be strengthened through systematic and partnership-based approaches. We describe a model developed from these concepts and its application in the Australian Indigenous primary healthcare context, and raise questions about sustainability and wider relevance of the model. PMID:24344640

Socialising Health Burden Through Different Network Topologies: A Simulation Study.

PubMed

Peacock, Adrian; Cheung, Anthony; Kim, Peter; Poon, Simon K

2017-01-01

An aging population and the expectation of premium quality health services combined with the increasing economic burden of the healthcare system requires a paradigm shift toward patient oriented healthcare. The guardian angel theory described by Szolovits [1] explores the notion of enlisting patients as primary providers of information and motivation to patients with similar clinical history through social connections. In this study, an agent based model was developed to simulate to explore how individuals are affected through their levels of intrinsic positivity. Ring, point-to-point (paired buddy), and random networks were modelled, with individuals able to send messages to each other given their levels of variables positivity and motivation. Of the 3 modelled networks it is apparent that the ring network provides the most equal, collective improvement in positivity and motivation for all users. Further study into other network topologies should be undertaken in the future.

EurOOHnet-the European research network for out-of-hours primary health care.

PubMed

Huibers, Linda; Philips, Hilde; Giesen, Paul; Remmen, Roy; Christensen, Morten Bondo; Bondevik, Gunnar Tschudi

2014-09-01

European countries face similar challenges in the provision of health care. Demographic factors like ageing, population growth, changing patient behaviour, and lack of work force lead to increasing demands, costs, and overcrowding of out-of-hours (OOH) care (i.e. primary care services, emergency departments (EDs), and ambulance services). These developments strain services and imply safety risks. In the last few decades, countries have been re-organizing their OOH primary health care services. AIM AND SCOPE OF THE NETWORK: We established a European research network for out-of-hours primary health care (EurOOHnet), which aims to transfer knowledge, share experiences, and conduct research. Combining research competencies and integrating results can generate a profound information flow to European researchers and decision makers in health policy, contributing towards feasible and high-quality OOH care. It also contributes to a more comparable performance level within European regions. CONDUCTED RESEARCH PROJECTS: The European research network aims to conduct mutual research projects. At present, three projects have been accomplished, among others concerning the diagnostic scope in OOH primary care services and guideline adherence for diagnosis and treatment of cystitis in OOH primary care. Future areas of research will be organizational models for OOH care; appropriate use of the OOH services; quality of telephone triage; quality of medical care; patient safety issues; use of auxiliary personnel; collaboration with EDs and ambulance care; and the role of GPs in OOH care.

Technical note: Dynamic INtegrated Gap-filling and partitioning for OzFlux (DINGO)

NASA Astrophysics Data System (ADS)

Beringer, Jason; McHugh, Ian; Hutley, Lindsay B.; Isaac, Peter; Kljun, Natascha

2017-03-01

Standardised, quality-controlled and robust data from flux networks underpin the understanding of ecosystem processes and tools necessary to support the management of natural resources, including water, carbon and nutrients for environmental and production benefits. The Australian regional flux network (OzFlux) currently has 23 active sites and aims to provide a continental-scale national research facility to monitor and assess Australia's terrestrial biosphere and climate for improved predictions. Given the need for standardised and effective data processing of flux data, we have developed a software suite, called the Dynamic INtegrated Gap-filling and partitioning for OzFlux (DINGO), that enables gap-filling and partitioning of the primary fluxes into ecosystem respiration (Fre) and gross primary productivity (GPP) and subsequently provides diagnostics and results. We outline the processing pathways and methodologies that are applied in DINGO (v13) to OzFlux data, including (1) gap-filling of meteorological and other drivers; (2) gap-filling of fluxes using artificial neural networks; (3) the u* threshold determination; (4) partitioning into ecosystem respiration and gross primary productivity; (5) random, model and u* uncertainties; and (6) diagnostic, footprint calculation, summary and results outputs. DINGO was developed for Australian data, but the framework is applicable to any flux data or regional network. Quality data from robust systems like DINGO ensure the utility and uptake of the flux data and facilitates synergies between flux, remote sensing and modelling.

A hierarchical model of metabolic machinery based on the kcore decomposition of plant metabolic networks.

PubMed

Filho, Humberto A; Machicao, Jeaneth; Bruno, Odemir M

2018-01-01

Modeling the basic structure of metabolic machinery is a challenge for modern biology. Some models based on complex networks have provided important information regarding this machinery. In this paper, we constructed metabolic networks of 17 plants covering unicellular organisms to more complex dicotyledonous plants. The metabolic networks were built based on the substrate-product model and a topological percolation was performed using the kcore decomposition. The distribution of metabolites across the percolation layers showed correlations between the metabolic integration hierarchy and the network topology. We show that metabolites concentrated in the internal network (maximum kcore) only comprise molecules of the primary basal metabolism. Moreover, we found a high proportion of a set of common metabolites, among the 17 plants, centered at the inner kcore layers. Meanwhile, the metabolites recognized as participants in the secondary metabolism of plants are concentrated in the outermost layers of the network. This data suggests that the metabolites in the central layer form a basic molecular module in which the whole plant metabolism is anchored. The elements from this central core participate in almost all plant metabolic reactions, which suggests that plant metabolic networks follows a centralized topology.

A hierarchical model of metabolic machinery based on the kcore decomposition of plant metabolic networks

PubMed Central

Filho, Humberto A.; Machicao, Jeaneth

2018-01-01

Modeling the basic structure of metabolic machinery is a challenge for modern biology. Some models based on complex networks have provided important information regarding this machinery. In this paper, we constructed metabolic networks of 17 plants covering unicellular organisms to more complex dicotyledonous plants. The metabolic networks were built based on the substrate-product model and a topological percolation was performed using the kcore decomposition. The distribution of metabolites across the percolation layers showed correlations between the metabolic integration hierarchy and the network topology. We show that metabolites concentrated in the internal network (maximum kcore) only comprise molecules of the primary basal metabolism. Moreover, we found a high proportion of a set of common metabolites, among the 17 plants, centered at the inner kcore layers. Meanwhile, the metabolites recognized as participants in the secondary metabolism of plants are concentrated in the outermost layers of the network. This data suggests that the metabolites in the central layer form a basic molecular module in which the whole plant metabolism is anchored. The elements from this central core participate in almost all plant metabolic reactions, which suggests that plant metabolic networks follows a centralized topology. PMID:29734359

Impacts of alternative climate information on hydrologic processes with SWAT: A comparison of NCDC, PRISM and NEXRAD datasets

USDA-ARS?s Scientific Manuscript database

Precipitation and temperature are two primary drivers that significantly affect hydrologic processes in a watershed. A network of land-based National Climatic Data Center (NCDC) weather stations has been typically used as a primary source of climate input for agro-ecosystem models. However, the ne...

Model-based analysis of pattern motion processing in mouse primary visual cortex

PubMed Central

Muir, Dylan R.; Roth, Morgane M.; Helmchen, Fritjof; Kampa, Björn M.

2015-01-01

Neurons in sensory areas of neocortex exhibit responses tuned to specific features of the environment. In visual cortex, information about features such as edges or textures with particular orientations must be integrated to recognize a visual scene or object. Connectivity studies in rodent cortex have revealed that neurons make specific connections within sub-networks sharing common input tuning. In principle, this sub-network architecture enables local cortical circuits to integrate sensory information. However, whether feature integration indeed occurs locally in rodent primary sensory areas has not been examined directly. We studied local integration of sensory features in primary visual cortex (V1) of the mouse by presenting drifting grating and plaid stimuli, while recording the activity of neuronal populations with two-photon calcium imaging. Using a Bayesian model-based analysis framework, we classified single-cell responses as being selective for either individual grating components or for moving plaid patterns. Rather than relying on trial-averaged responses, our model-based framework takes into account single-trial responses and can easily be extended to consider any number of arbitrary predictive models. Our analysis method was able to successfully classify significantly more responses than traditional partial correlation (PC) analysis, and provides a rigorous statistical framework to rank any number of models and reject poorly performing models. We also found a large proportion of cells that respond strongly to only one stimulus class. In addition, a quarter of selectively responding neurons had more complex responses that could not be explained by any simple integration model. Our results show that a broad range of pattern integration processes already take place at the level of V1. This diversity of integration is consistent with processing of visual inputs by local sub-networks within V1 that are tuned to combinations of sensory features. PMID:26300738

ANIMAL MODELS OF DYSTONIA: LESSONS FROM A MUTANT RAT

PubMed Central

LeDoux, Mark S.

2010-01-01

Dystonia is a motor sign characterized by involuntary muscle contractions which produce abnormal postures. Genetic factors contribute significantly to primary dystonia. In comparison, secondary dystonia can be caused by a wide variety of metabolic, structural, infectious, toxic and inflammatory insults to the nervous system. Although classically ascribed to dysfunction of the basal ganglia, studies of diverse animal models have pointed out that dystonia is a network disorder with important contributions from abnormal olivocerebellar signaling. In particular, work with the dystonic (dt) rat has engendered dramatic paradigm shifts in dystonia research. The dt rat manifests generalized dystonia caused by deficiency of the neuronally-restricted protein caytaxin. Electrophysiological and biochemical studies have shown that defects at the climbing fiber-Purkinje cell synapse in the dt rat lead to abnormal bursting firing patterns in the cerebellar nuclei, which increases linearly with postnatal age. In a general sense, the dt rat has shown the scientific and clinical communities that dystonia can arise from dysfunctional cerebellar cortex. Furthermore, work with the dt rat has provided evidence that dystonia (1) is a neurodevelopmental network disorder and (2) can be driven by abnormal cerebellar output. In large part, work with other animal models has expanded upon studies in the dt rat and shown that primary dystonia is a multi-nodal network disorder associated with defective sensorimotor integration. In addition, experiments in genetically-engineered models have been used to examine the underlying cellular pathologies that drive primary dystonia. PMID:21081162

Predawn plasma bubble cluster observed in Southeast Asia

NASA Astrophysics Data System (ADS)

Watthanasangmechai, Kornyanat; Yamamoto, Mamoru; Saito, Akinori; Tsunoda, Roland; Yokoyama, Tatsuhiro; Supnithi, Pornchai; Ishii, Mamoru; Yatini, Clara

2016-06-01

Predawn plasma bubble was detected as deep plasma depletion by GNU Radio Beacon Receiver (GRBR) network and in situ measurement onboard Defense Meteorological Satellite Program F15 (DMSPF15) satellite and was confirmed by sparse GPS network in Southeast Asia. In addition to the deep depletion, the GPS network revealed the coexisting submesoscale irregularities. A deep depletion is regarded as a primary bubble. Submesoscale irregularities are regarded as secondary bubbles. Primary bubble and secondary bubbles appeared together as a cluster with zonal wavelength of 50 km. An altitude of secondary bubbles happened to be lower than that of the primary bubble in the same cluster. The observed pattern of plasma bubble cluster is consistent with the simulation result of the recent high-resolution bubble (HIRB) model. This event is only a single event out of 76 satellite passes at nighttime during 3-25 March 2012 that significantly shows plasma depletion at plasma bubble wall. The inside structure of the primary bubble was clearly revealed from the in situ density data of DMSPF15 satellite and the ground-based GRBR total electron content.

Experimental and Computational Studies of Cortical Neural Network Properties Through Signal Processing

NASA Astrophysics Data System (ADS)

Clawson, Wesley Patrick

Previous studies, both theoretical and experimental, of network level dynamics in the cerebral cortex show evidence for a statistical phenomenon called criticality; a phenomenon originally studied in the context of phase transitions in physical systems and that is associated with favorable information processing in the context of the brain. The focus of this thesis is to expand upon past results with new experimentation and modeling to show a relationship between criticality and the ability to detect and discriminate sensory input. A line of theoretical work predicts maximal sensory discrimination as a functional benefit of criticality, which can then be characterized using mutual information between sensory input, visual stimulus, and neural response,. The primary finding of our experiments in the visual cortex in turtles and neuronal network modeling confirms this theoretical prediction. We show that sensory discrimination is maximized when visual cortex operates near criticality. In addition to presenting this primary finding in detail, this thesis will also address our preliminary results on change-point-detection in experimentally measured cortical dynamics.

Dual Neural Network Model for the Evolution of Speech and Language.

PubMed

Hage, Steffen R; Nieder, Andreas

2016-12-01

Explaining the evolution of speech and language poses one of the biggest challenges in biology. We propose a dual network model that posits a volitional articulatory motor network (VAMN) originating in the prefrontal cortex (PFC; including Broca's area) that cognitively controls vocal output of a phylogenetically conserved primary vocal motor network (PVMN) situated in subcortical structures. By comparing the connections between these two systems in human and nonhuman primate brains, we identify crucial biological preadaptations in monkeys for the emergence of a language system in humans. This model of language evolution explains the exclusiveness of non-verbal communication sounds (e.g., cries) in infants with an immature PFC, as well as the observed emergence of non-linguistic vocalizations in adults after frontal lobe pathologies. Copyright © 2016 Elsevier Ltd. All rights reserved.

Neural networks to predict exosphere temperature corrections

NASA Astrophysics Data System (ADS)

Choury, Anna; Bruinsma, Sean; Schaeffer, Philippe

2013-10-01

Precise orbit prediction requires a forecast of the atmospheric drag force with a high degree of accuracy. Artificial neural networks are universal approximators derived from artificial intelligence and are widely used for prediction. This paper presents a method of artificial neural networking for prediction of the thermosphere density by forecasting exospheric temperature, which will be used by the semiempirical thermosphere Drag Temperature Model (DTM) currently developed. Artificial neural network has shown to be an effective and robust forecasting model for temperature prediction. The proposed model can be used for any mission from which temperature can be deduced accurately, i.e., it does not require specific training. Although the primary goal of the study was to create a model for 1 day ahead forecast, the proposed architecture has been generalized to 2 and 3 days prediction as well. The impact of artificial neural network predictions has been quantified for the low-orbiting satellite Gravity Field and Steady-State Ocean Circulation Explorer in 2011, and an order of magnitude smaller orbit errors were found when compared with orbits propagated using the thermosphere model DTM2009.

Physician Networks and Ambulatory Care-sensitive Admissions.

PubMed

Casalino, Lawrence P; Pesko, Michael F; Ryan, Andrew M; Nyweide, David J; Iwashyna, Theodore J; Sun, Xuming; Mendelsohn, Jayme; Moody, James

2015-06-01

Research on the quality and cost of care traditionally focuses on individual physicians or medical groups. Social network theory suggests that the care a patient receives also depends on the network of physicians with whom a patient's physician is connected. The objectives of the study are: (1) identify physician networks; (2) determine whether the rate of ambulatory care-sensitive hospital admissions (ACSAs) varies across networks--even different networks at the same hospital; and (3) determine the relationship between ACSA rates and network characteristics. We identified networks by applying network detection algorithms to Medicare 2008 claims for 987,000 beneficiaries in 5 states. We estimated a fixed-effects model to determine the relationship between networks and ACSAs and a multivariable model to determine the relationship between network characteristics and ACSAs. We identified 417 networks. Mean size: 129 physicians; range, 26-963. In the fixed-effects model, ACSA rates varied significantly across networks: there was a 46% difference in rates between networks at the 25th and 75th performance percentiles. At 95% of hospitals with admissions from 2 networks, the networks had significantly different ACSA rates; the mean difference was 36% of the mean ACSA rate. Networks with a higher percentage of primary-care physicians and networks in which patients received care from a larger number of physicians had higher ACSA rates. Physician networks have a relationship with ACSAs that is independent of the physicians in the network. Physician networks could be an important focus for understanding variations in medical care and for intervening to improve care.

Replicating receptive fields of simple and complex cells in primary visual cortex in a neuronal network model with temporal and population sparseness and reliability.

PubMed

Tanaka, Takuma; Aoyagi, Toshio; Kaneko, Takeshi

2012-10-01

We propose a new principle for replicating receptive field properties of neurons in the primary visual cortex. We derive a learning rule for a feedforward network, which maintains a low firing rate for the output neurons (resulting in temporal sparseness) and allows only a small subset of the neurons in the network to fire at any given time (resulting in population sparseness). Our learning rule also sets the firing rates of the output neurons at each time step to near-maximum or near-minimum levels, resulting in neuronal reliability. The learning rule is simple enough to be written in spatially and temporally local forms. After the learning stage is performed using input image patches of natural scenes, output neurons in the model network are found to exhibit simple-cell-like receptive field properties. When the output of these simple-cell-like neurons are input to another model layer using the same learning rule, the second-layer output neurons after learning become less sensitive to the phase of gratings than the simple-cell-like input neurons. In particular, some of the second-layer output neurons become completely phase invariant, owing to the convergence of the connections from first-layer neurons with similar orientation selectivity to second-layer neurons in the model network. We examine the parameter dependencies of the receptive field properties of the model neurons after learning and discuss their biological implications. We also show that the localized learning rule is consistent with experimental results concerning neuronal plasticity and can replicate the receptive fields of simple and complex cells.

Reflections from organization science on the development of primary health care research networks.

PubMed

Fenton, E; Harvey, J; Griffiths, F; Wild, A; Sturt, J

2001-10-01

In the UK, policy changes in primary health care research and development have led to the establishment of primary care research networks. These organizations aim to increase research culture, capacity and evidence base in primary care. As publicly funded bodies, these networks need to be accountable. Organizational science has studied network organizations including why and how they develop and how they function most effectively. This paper draws on organizational science to reflect on why primary care research networks appear to be appropriate for primary care research and how their structures and processes can best enable the achievement of their aims.

Highway Project Delivery Requirements

DOT National Transportation Integrated Search

1998-07-01

The purpose of the Commercial Vehicle Information Systems and Networks Model Deployment Initiative (CVISN MDI) is to demonstrate the technical and institutional feasibility, costs, and benefits of the primary Intelligent Transportation Systems (ITS) ...

The development of English primary care group governance. A scenario analysis.

PubMed

Sheaff, R

1999-01-01

At present there is a policy vacuum about what English Primary Care Groups' (PCGs) governance will be when they develop into Primary Care Trusts (PCTs). Draft legislation leaves many options open, so PCT governance is likely to 'emerge' as PCTs are created. It also remains uncertain how general practitioners (GPs) will react to the formation of PCTs and how the UK government will then respond in turn. A scenario analysis suggests three possible lines of development. The base (likeliest) scenario predicts a mainly networked form of PCT governance. An alternative scenario is of PCT governance resembling the former National Health Service internal market. A third scenario predicts 'franchise model' PCTs employing some GPs and subcontracting others. To different degrees all three scenarios predict that PCTs will retain elements of networked governance. If it fails to make GPs as accountable to NHS management as the UK government wishes, networked governance may prove only a transitional stage before English PCTs adopt either quasi-market or hierarchical governance.

Understanding ecohydrological connectivity in savannas: A system dynamics modeling approach

USDA-ARS?s Scientific Manuscript database

Ecohydrological connectivity is a system-level property that results from the linkages in the networks of water transport through ecosystems, by which feedback effects and other emergent system behaviors may be generated. We created a systems dynamic model that represents primary ecohydrological net...

Consumer, physician, and payer perspectives on primary care medication management services with a shared resource pharmacists network.

PubMed

Smith, Marie; Cannon-Breland, Michelle L; Spiggle, Susan

2014-01-01

Health care reform initiatives are examining new care delivery models and payment reform alternatives such as medical homes, health homes, community-based care transitions teams, medical neighborhoods and accountable care organizations (ACOs). Of particular interest is the extent to which pharmacists are integrated in team-based health care reform initiatives and the related perspectives of consumers, physicians, and payers. To assess the current knowledge of consumers and physicians about pharmacist training/expertise and capacity to provide primary care medication management services in a shared resource network; determine factors that will facilitate/limit consumer interest in having pharmacists as a member of a community-based "health care team;" determine factors that will facilitate/limit physician utilization of pharmacists for medication management services; and determine factors that will facilitate/limit payer reimbursement models for medication management services using a shared resource pharmacist network model. This project used qualitative research methods to assess the perceptions of consumers, primary care physicians, and payers on pharmacist-provided medication management services using a shared resource network of pharmacists. Focus groups were conducted with primary care physicians and consumers, while semi-structured discussions were conducted with a public and private payer. Most consumers viewed pharmacists in traditional dispensing roles and were unaware of the direct patient care responsibilities of pharmacists as part of community-based health teams. Physicians noted several chronic disease states where clinically-trained pharmacists could collaborate as health care team members yet had uncertainties about integrating pharmacists into their practice workflow and payment sources for pharmacist services. Payers were interested in having credentialed pharmacists provide medication management services if the services improved quality of patient care and/or prevented adverse drug events, and the services were cost neutral (at a minimum). It was difficult for most consumers and physicians to envision pharmacists practicing in non-dispensing roles. The pharmacy profession must disseminate the existing body of evidence on pharmacists as care providers of medication management services and the related impact on clinical outcomes, patient safety, and cost savings to external audiences. Without such, new pharmacist practice models may have limited acceptance by consumers, primary care physicians, and payers. Copyright © 2014 Elsevier Inc. All rights reserved.

SMC: SCENIC Model Control

NASA Technical Reports Server (NTRS)

Srivastava, Priyaka; Kraus, Jeff; Murawski, Robert; Golden, Bertsel, Jr.

2015-01-01

NASAs Space Communications and Navigation (SCaN) program manages three active networks: the Near Earth Network, the Space Network, and the Deep Space Network. These networks simultaneously support NASA missions and provide communications services to customers worldwide. To efficiently manage these resources and their capabilities, a team of student interns at the NASA Glenn Research Center is developing a distributed system to model the SCaN networks. Once complete, the system shall provide a platform that enables users to perform capacity modeling of current and prospective missions with finer-grained control of information between several simulation and modeling tools. This will enable the SCaN program to access a holistic view of its networks and simulate the effects of modifications in order to provide NASA with decisional information. The development of this capacity modeling system is managed by NASAs Strategic Center for Education, Networking, Integration, and Communication (SCENIC). Three primary third-party software tools offer their unique abilities in different stages of the simulation process. MagicDraw provides UMLSysML modeling, AGIs Systems Tool Kit simulates the physical transmission parameters and de-conflicts scheduled communication, and Riverbed Modeler (formerly OPNET) simulates communication protocols and packet-based networking. SCENIC developers are building custom software extensions to integrate these components in an end-to-end space communications modeling platform. A central control module acts as the hub for report-based messaging between client wrappers. Backend databases provide information related to mission parameters and ground station configurations, while the end user defines scenario-specific attributes for the model. The eight SCENIC interns are working under the direction of their mentors to complete an initial version of this capacity modeling system during the summer of 2015. The intern team is composed of four students in Computer Science, two in Computer Engineering, one in Electrical Engineering, and one studying Space Systems Engineering.

Building a pan-Canadian primary care sentinel surveillance network: initial development and moving forward.

PubMed

Birtwhistle, Richard; Keshavjee, Karim; Lambert-Lanning, Anita; Godwin, Marshall; Greiver, Michelle; Manca, Donna; Lagacé, Claudia

2009-01-01

The development of a pan-Canadian network of primary care research networks for studying issues in primary care has been the vision of Canadian primary care researchers for many years. With the opportunity for funding from the Public Health Agency of Canada and the support of the College of Family Physicians of Canada, we have planned and developed a project to assess the feasibility of a network of networks of family medicine practices that exclusively use electronic medical records. The Canadian Primary Care Sentinel Surveillance Network will collect longitudinal data from practices across Canada to assess the primary care epidemiology and management of 5 chronic diseases: hypertension, diabetes, depression, chronic obstructive lung disease, and osteoarthritis. This article reports on the 7-month first phase of the feasibility project of 7 regional networks in Canada to develop a business plan, including governance, mission, and vision; develop memorandum of agreements with the regional networks and their respective universities; develop and obtain approval of research ethics board applications; develop methods for data extraction, a Canadian Primary Care Sentinel Surveillance Network database, and initial assessment of the types of data that can be extracted; and recruitment of 10 practices at each network that use electronic medical records. The project will continue in phase 2 of the feasibility testing until April 2010.

Mechanical and structural model of fractal networks of fat crystals at low deformations.

PubMed

Narine, S S; Marangoni, A G

1999-12-01

Fat-crystal networks demonstrate viscoelastic behavior at very small deformations. A structural model of these networks is described and supported by polarized light and atomic-force microscopy. A mechanical model is described which allows the shear elastic modulus (G') of the system to be correlated with forces acting within the network. The fractal arrangement of the network at certain length scales is taken into consideration. It is assumed that the forces acting are due to van der Waals forces. The final expression for G' is related to the volume fraction of solid fat (Phi) via the mass fractal dimension (D) of the network, which agrees with the experimental verification of the scaling behavior of fat-crystal networks [S. S. Narine and A. G. Marangoni, Phys. Rev. E 59, 1908 (1999)]. G' was also found to be inversely proportional to the diameter of the primary particles (sigma approximately equal to 6 microm) within the network (microstructural elements) as well as to the diameter of the microstructures (xi approximately equal to 100 microm) and inversely proportional to the cube of the intermicrostructural element distance (d(0)). This formulation of the elastic modulus agrees well with experimental observations.

Effects of primary care team social networks on quality of care and costs for patients with cardiovascular disease.

PubMed

Mundt, Marlon P; Gilchrist, Valerie J; Fleming, Michael F; Zakletskaia, Larissa I; Tuan, Wen-Jan; Beasley, John W

2015-03-01

Cardiovascular disease is the leading cause of mortality and morbidity in the United States. Primary care teams can be best suited to improve quality of care and lower costs for patients with cardiovascular disease. This study evaluates the associations between primary care team communication, interaction, and coordination (ie, social networks); quality of care; and costs for patients with cardiovascular disease. Using a sociometric survey, 155 health professionals from 31 teams at 6 primary care clinics identified with whom they interact daily about patient care. Social network analysis calculated variables of density and centralization representing team interaction structures. Three-level hierarchical modeling evaluated the link between team network density, centralization, and number of patients with a diagnosis of cardiovascular disease for controlled blood pressure and cholesterol, counts of urgent care visits, emergency department visits, hospital days, and medical care costs in the previous 12 months. Teams with dense interactions among all team members were associated with fewer hospital days (rate ratio [RR] = 0.62; 95% CI, 0.50-0.77) and lower medical care costs (-$556; 95% CI, -$781 to -$331) for patients with cardiovascular disease. Conversely, teams with interactions revolving around a few central individuals were associated with increased hospital days (RR = 1.45; 95% CI, 1.09-1.94) and greater costs ($506; 95% CI, $202-$810). Team-shared vision about goals and expectations mediated the relationship between social network structures and patient quality of care outcomes. Primary care teams that are more interconnected and less centralized and that have a shared team vision are better positioned to deliver high-quality cardiovascular disease care at a lower cost. © 2015 Annals of Family Medicine, Inc.

Effects of Primary Care Team Social Networks on Quality of Care and Costs for Patients With Cardiovascular Disease

PubMed Central

Mundt, Marlon P.; Gilchrist, Valerie J.; Fleming, Michael F.; Zakletskaia, Larissa I.; Tuan, Wen-Jan; Beasley, John W.

2015-01-01

PURPOSE Cardiovascular disease is the leading cause of mortality and morbidity in the United States. Primary care teams can be best suited to improve quality of care and lower costs for patients with cardiovascular disease. This study evaluates the associations between primary care team communication, interaction, and coordination (ie, social networks); quality of care; and costs for patients with cardiovascular disease. METHODS Using a sociometric survey, 155 health professionals from 31 teams at 6 primary care clinics identified with whom they interact daily about patient care. Social network analysis calculated variables of density and centralization representing team interaction structures. Three-level hierarchical modeling evaluated the link between team network density, centralization, and number of patients with a diagnosis of cardiovascular disease for controlled blood pressure and cholesterol, counts of urgent care visits, emergency department visits, hospital days, and medical care costs in the previous 12 months. RESULTS Teams with dense interactions among all team members were associated with fewer hospital days (rate ratio [RR] = 0.62; 95% CI, 0.50–0.77) and lower medical care costs (−$556; 95% CI, −$781 to −$331) for patients with cardiovascular disease. Conversely, teams with interactions revolving around a few central individuals were associated with increased hospital days (RR = 1.45; 95% CI, 1.09–1.94) and greater costs ($506; 95% CI, $202–$810). Team-shared vision about goals and expectations mediated the relationship between social network structures and patient quality of care outcomes. CONCLUSIONS Primary care teams that are more interconnected and less centralized and that have a shared team vision are better positioned to deliver high-quality cardiovascular disease care at a lower cost. PMID:25755035

Sexual Networks and HIV Risk among Black Men Who Have Sex with Men in 6 U.S. Cities.

PubMed

Tieu, Hong-Van; Liu, Ting-Yuan; Hussen, Sophia; Connor, Matthew; Wang, Lei; Buchbinder, Susan; Wilton, Leo; Gorbach, Pamina; Mayer, Kenneth; Griffith, Sam; Kelly, Corey; Elharrar, Vanessa; Phillips, Gregory; Cummings, Vanessa; Koblin, Beryl; Latkin, Carl

2015-01-01

Sexual networks may place U.S. Black men who have sex with men (MSM) at increased HIV risk. Self-reported egocentric sexual network data from the prior six months were collected from 1,349 community-recruited Black MSM in HPTN 061, a multi-component HIV prevention intervention feasibility study. Sexual network composition, size, and density (extent to which members are having sex with one another) were compared by self-reported HIV serostatus and age of the men. GEE models assessed network and other factors associated with having a Black sex partner, having a partner with at least two age category difference (age difference between participant and partner of at least two age group categories), and having serodiscordant/serostatus unknown unprotected anal/vaginal intercourse (SDUI) in the last six months. Over half had exclusively Black partners in the last six months, 46% had a partner of at least two age category difference, 87% had ≤5 partners. Nearly 90% had sex partners who were also part of their social networks. Among HIV-negative men, not having anonymous/exchange/ trade partners and lower density were associated with having a Black partner; larger sexual network size and having non-primary partners were associated with having a partner with at least two age category difference; and having anonymous/exchange/ trade partners was associated with SDUI. Among HIV-positive men, not having non-primary partners was associated with having a Black partner; no sexual network characteristics were associated with having a partner with at least two age category difference and SDUI. Black MSM sexual networks were relatively small and often overlapped with the social networks. Sexual risk was associated with having non-primary partners and larger network size. Network interventions that engage the social networks of Black MSM, such as interventions utilizing peer influence, should be developed to address stable partnerships, number of partners, and serostatus disclosure.

Primary Care Emergency Preparedness Network, New York City, 2015: Comparison of Member and Nonmember Sites

PubMed Central

Jean, Marc C.; Chen, Bei; Molinari, Noelle-Angelique M.; LeBlanc, Tanya T.

2017-01-01

Objectives. To assess whether Primary Care Emergency Preparedness Network member sites reported indicators of preparedness for public health emergencies compared with nonmember sites. The network—a collaboration between government and New York City primary care associations—offers technical assistance to primary care sites to improve disaster preparedness and response. Methods. In 2015, we administered an online questionnaire to sites regarding facility characteristics and preparedness indicators. We estimated differences between members and nonmembers with natural logarithm–linked binomial models. Open-ended assessments identified preparedness gaps. Results. One hundred seven sites completed the survey (23.3% response rate); 47 (43.9%) were nonmembers and 60 (56.1%) were members. Members were more likely to have completed hazard vulnerability analysis (risk ratio [RR] = 1.94; 95% confidence interval [CI] = 1.28, 2.93), to have identified essential services for continuity of operations (RR = 1.39; 95% CI = 1.03, 1.86), to have memoranda of understanding with external partners (RR = 2.49; 95% CI = 1.42, 4.36), and to have completed point-of-dispensing training (RR = 4.23; 95% CI = 1.76, 10.14). Identified preparedness gaps were improved communication, resource availability, and train-the-trainer programs. Public Health Implications. Primary Care Emergency Preparedness Network membership is associated with improved public health emergency preparedness among primary care sites. PMID:28892448

Human vascular tissue models formed from human induced pluripotent stem cell derived endothelial cells

PubMed Central

Belair, David G.; Whisler, Jordan A.; Valdez, Jorge; Velazquez, Jeremy; Molenda, James A.; Vickerman, Vernella; Lewis, Rachel; Daigh, Christine; Hansen, Tyler D.; Mann, David A.; Thomson, James A.; Griffith, Linda G.; Kamm, Roger D.; Schwartz, Michael P.; Murphy, William L.

2015-01-01

Here we describe a strategy to model blood vessel development using a well-defined iPSC-derived endothelial cell type (iPSC-EC) cultured within engineered platforms that mimic the 3D microenvironment. The iPSC-ECs used here were first characterized by expression of endothelial markers and functional properties that included VEGF responsiveness, TNF-α-induced upregulation of cell adhesion molecules (MCAM/CD146; ICAM1/CD54), thrombin-dependent barrier function, shear stress-induced alignment, and 2D and 3D capillary-like network formation in Matrigel. The iPSC-ECs also formed 3D vascular networks in a variety of engineering contexts, yielded perfusable, interconnected lumen when co-cultured with primary human fibroblasts, and aligned with flow in microfluidics devices. iPSC-EC function during tubule network formation, barrier formation, and sprouting was consistent with that of primary ECs, and the results suggest a VEGF-independent mechanism for sprouting, which is relevant to therapeutic anti-angiogenesis strategies. Our combined results demonstrate the feasibility of using a well-defined, stable source of iPSC-ECs to model blood vessel formation within a variety of contexts using standard in vitro formats. PMID:25190668

78 FR 75442 - Designation of the Primary Freight Network

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-11

...] Designation of the Primary Freight Network AGENCY: Federal Highway Administration (FHWA), DOT. ACTION: Notice... period for the Designation of the highway Primary Freight Network (PFN) notice, which was published on... the complete National Freight Network (NFN), and to solicit comments on aspects of the NFN. The five...

Modeling and simulation of the data communication network at the ASRM Facility

NASA Technical Reports Server (NTRS)

Nirgudkar, R. P.; Moorhead, R. J.; Smith, W. D.

1994-01-01

This paper describes the modeling and simulation of the communication network for the NASA Advanced Solid Rocket Motor (ASRM) facility under construction at Yellow Creek near Luka, Mississippi. Manufacturing, testing, and operations at the ASRM site will be performed in different buildings scattered over an 1800 acre site. These buildings are interconnected through a local area network (LAN), which will contain one logical Fiber Distributed Data Interface (FDDI) ring acting as a backbone for the whole complex. The network contains approximately 700 multi-vendor workstations, 22 multi-vendor workcells, and 3 VAX clusters interconnected via Ethernet and FDDI. The different devices produce appreciably different traffic patterns, each pattern will be highly variable, and some patterns will be very bursty. Most traffic is between the VAX clusters and the other devices. Comdisco's Block Oriented Network Simulator (BONeS) has been used for network simulation. The two primary evaluation parameters used to judge the expected network performance are throughput and delay.

Time-Varying, Multi-Scale Adaptive System Reliability Analysis of Lifeline Infrastructure Networks

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

Gearhart, Jared Lee; Kurtz, Nolan Scot

2014-09-01

The majority of current societal and economic needs world-wide are met by the existing networked, civil infrastructure. Because the cost of managing such infrastructure is high and increases with time, risk-informed decision making is essential for those with management responsibilities for these systems. To address such concerns, a methodology that accounts for new information, deterioration, component models, component importance, group importance, network reliability, hierarchical structure organization, and efficiency concerns has been developed. This methodology analyzes the use of new information through the lens of adaptive Importance Sampling for structural reliability problems. Deterioration, multi-scale bridge models, and time-variant component importance aremore » investigated for a specific network. Furthermore, both bridge and pipeline networks are studied for group and component importance, as well as for hierarchical structures in the context of specific networks. Efficiency is the primary driver throughout this study. With this risk-informed approach, those responsible for management can address deteriorating infrastructure networks in an organized manner.« less

Significance of off-hours in centralized primary percutaneous coronary intervention network.

PubMed

Becker, David; Soos, Pal; Berta, Balazs; Nagy, Andrea; Fulop, Gabor; Szabo, Gyorgy; Barczi, Gyorgy; Belicza, Eva; Martai, Istvan; Merkely, Béla

2009-10-01

To analyze the efficacy of a regionally organized primary percutaneous coronary intervention (PCI) network at the Heart Center, Semmelweis University Budapest, part of the "Budapest model," and the factors that influence it. In order to investigate the differences between regular and off-hours patient care in a 24-hour myocardial infarction primary care system, we included 1890 consecutive, unselected patients with ST-segment elevation myocardial infarction and followed them until at least one year. The follow-up was complete for all participants. The difference between regular hours and off-hours mortality was not significant either after 30 days (8.6% vs 8.8%, respectively) or after 1 year (15.3% vs 14.7%, respectively). The rate of patients with re-infarction, frequency of re-intervention, and major adverse cardiac events, including death, re-infarction, re-intervention, and coronary artery bypass graft surgery, were similar in both patient groups. The time delay between the onset of chest pain and arrival to the clinic was 5.9+/-5.8 hours (mean+/- standard deviation) during regular hours and 5.2+/-4.6 hours during off-hours (P=0.235). Direct transport caused significant decrease in the 30-day and 1-year mortality independent of duty time (7.2% vs 9.9%, P=0.027; 12.6% vs 16.7%, P=0.028; respectively). Centralized primary PCI network of the "Budapest model" achieved the same level of patient care during both off-hours and regular hours.

A stochastic Markov chain model to describe lung cancer growth and metastasis.

PubMed

Newton, Paul K; Mason, Jeremy; Bethel, Kelly; Bazhenova, Lyudmila A; Nieva, Jorge; Kuhn, Peter

2012-01-01

A stochastic Markov chain model for metastatic progression is developed for primary lung cancer based on a network construction of metastatic sites with dynamics modeled as an ensemble of random walkers on the network. We calculate a transition matrix, with entries (transition probabilities) interpreted as random variables, and use it to construct a circular bi-directional network of primary and metastatic locations based on postmortem tissue analysis of 3827 autopsies on untreated patients documenting all primary tumor locations and metastatic sites from this population. The resulting 50 potential metastatic sites are connected by directed edges with distributed weightings, where the site connections and weightings are obtained by calculating the entries of an ensemble of transition matrices so that the steady-state distribution obtained from the long-time limit of the Markov chain dynamical system corresponds to the ensemble metastatic distribution obtained from the autopsy data set. We condition our search for a transition matrix on an initial distribution of metastatic tumors obtained from the data set. Through an iterative numerical search procedure, we adjust the entries of a sequence of approximations until a transition matrix with the correct steady-state is found (up to a numerical threshold). Since this constrained linear optimization problem is underdetermined, we characterize the statistical variance of the ensemble of transition matrices calculated using the means and variances of their singular value distributions as a diagnostic tool. We interpret the ensemble averaged transition probabilities as (approximately) normally distributed random variables. The model allows us to simulate and quantify disease progression pathways and timescales of progression from the lung position to other sites and we highlight several key findings based on the model.

Healthy eating and active living for diabetes in primary care networks (HEALD-PCN): rationale, design, and evaluation of a pragmatic controlled trial for adults with type 2 diabetes

PubMed Central

2012-01-01

Background While strong and consistent evidence supports the role of lifestyle modification in the prevention and management of type 2 diabetes (T2DM), the best strategies for program implementation to support lifestyle modification within primary care remain to be determined. The objective of the study is to evaluate the implementation of an evidence-based self- management program for patients with T2DM within a newly established primary care network (PCN) environment. Method Using a non-randomized design, participants (total N = 110 per group) will be consecutively allocated in bi-monthly blocks to either a 6-month self-management program lead by an Exercise Specialist or to usual care. Our primary outcome is self-reported physical activity and pedometer steps. Discussion The present study will assess whether a diabetes self-management program lead by an Exercise Specialist provided within a newly emerging model of primary care and linked to available community-based resources, can lead to positive changes in self-management behaviours for adults with T2DM. Ultimately, our work will serve as a platform upon which an emerging model of primary care can incorporate effective and efficient chronic disease management practices that are sustainable through partnerships with local community partners. Clinical Trials Registration ClinicalTrials.gov identifier: NCT00991380 PMID:22712881

Migration of optical core network to next generation networks - Carrier Grade Ethernet Optical Transport Network

NASA Astrophysics Data System (ADS)

Glamočanin, D.

2017-05-01

In order to maintain the continuity of the telecom operators’ network construction, while monitoring development needs, increasing customers’ demands and application of technological improvements, it is necessary to migrate optical transport core network to the next generation networks - Carrier Grade Ethernet Optical Transport Network (OTN CE). The primary objective of OTN CE is to realize an environment that is based solely on the switching in the optical domain, i.e. the realization of transparent optical networks and optical switching to the second layer of ISO / OSI model. The realization of such a network provides opportunities for further development of existing, but also technologically more demanding, new services. It is also a prerequisite to provide higher scalability, reliability, security and quality of QoS service, as well as prerequisites for the establishment of SLA (Service Level Agreement) for existing services, especially traffic in real time. This study aims to clarify the proposed model, which has the potential to be eventually adjusted in accordance with new scientific knowledge in this field as well as market requirements.

Improving Earth/Prediction Models to Improve Network Processing

NASA Astrophysics Data System (ADS)

Wagner, G. S.

2017-12-01

The United States Atomic Energy Detection System (USAEDS) primaryseismic network consists of a relatively small number of arrays andthree-component stations. The relatively small number of stationsin the USAEDS primary network make it both necessary and feasibleto optimize both station and network processing.Station processing improvements include detector tuning effortsthat use Receiver Operator Characteristic (ROC) curves to helpjudiciously set acceptable Type 1 (false) vs. Type 2 (miss) errorrates. Other station processing improvements include the use ofempirical/historical observations and continuous background noisemeasurements to compute time-varying, maximum likelihood probabilityof detection thresholds.The USAEDS network processing software makes extensive use of theazimuth and slowness information provided by frequency-wavenumberanalysis at array sites, and polarization analysis at three-componentsites. Most of the improvements in USAEDS network processing aredue to improvements in the models used to predict azimuth, slowness,and probability of detection. Kriged travel-time, azimuth andslowness corrections-and associated uncertainties-are computedusing a ground truth database. Improvements in station processingand the use of improved models for azimuth, slowness, and probabilityof detection have led to significant improvements in USADES networkprocessing.

Improved Cost-Base Design of Water Distribution Networks using Genetic Algorithm

NASA Astrophysics Data System (ADS)

Moradzadeh Azar, Foad; Abghari, Hirad; Taghi Alami, Mohammad; Weijs, Steven

2010-05-01

Population growth and progressive extension of urbanization in different places of Iran cause an increasing demand for primary needs. The water, this vital liquid is the most important natural need for human life. Providing this natural need is requires the design and construction of water distribution networks, that incur enormous costs on the country's budget. Any reduction in these costs enable more people from society to access extreme profit least cost. Therefore, investment of Municipal councils need to maximize benefits or minimize expenditures. To achieve this purpose, the engineering design depends on the cost optimization techniques. This paper, presents optimization models based on genetic algorithm(GA) to find out the minimum design cost Mahabad City's (North West, Iran) water distribution network. By designing two models and comparing the resulting costs, the abilities of GA were determined. the GA based model could find optimum pipe diameters to reduce the design costs of network. Results show that the water distribution network design using Genetic Algorithm could lead to reduction of at least 7% in project costs in comparison to the classic model. Keywords: Genetic Algorithm, Optimum Design of Water Distribution Network, Mahabad City, Iran.

Multispecialty physician networks in Ontario.

PubMed

Stukel, Therese A; Glazier, Richard H; Schultz, Susan E; Guan, Jun; Zagorski, Brandon M; Gozdyra, Peter; Henry, David A

2013-01-01

Large multispecialty physician group practices, with a central role for primary care practitioners, have been shown to achieve high-quality, low-cost care for patients with chronic disease. We assessed the extent to which informal multispecialty physician networks in Ontario could be identified by using health administrative data to exploit natural linkages among patients, physicians, and hospitals based on existing patient flow. We linked each Ontario resident to his or her usual provider of primary care over the period from fiscal year 2008/2009 to fiscal year 2010/2011. We linked each specialist to the hospital where he or she performed the most inpatient services. We linked each primary care physician to the hospital where most of his or her ambulatory patients were admitted for non-maternal medical care. Each resident was then linked to the same hospital as his or her usual provider of primary care. We computed "loyalty" as the proportion of care to network residents provided by physicians and hospitals within their network. Smaller clusters were aggregated to create networks based on a minimum population size, distance, and loyalty. Networks were not constrained geographically. We identified 78 multispecialty physician networks, comprising 12,410 primary care physicians, 14,687 specialists, and 175 acute care hospitals serving a total of 12,917,178 people. Median network size was 134,723 residents, 125 primary care physicians, and 143 specialists. Virtually all eligible residents were linked to a usual provider of primary care and to a network. Most specialists (93.5%) and primary care physicians (98.2%) were linked to a hospital. Median network physician loyalty was 68.4% for all physician visits and 81.1% for primary care visits. Median non-maternal admission loyalty was 67.4%. Urban networks had lower loyalties and were less self-contained but had more health care resources. We demonstrated the feasibility of identifying informal multispecialty physician networks in Ontario on the basis of patterns of health care-seeking behaviour. Networks were reasonably self-contained, in that individual residents received most of their care from providers within their respective networks. Formal constitution of networks could foster accountability for efficient, integrated care through care management tools and quality improvement, the ideas behind "accountable care organizations."

Gas network model allows full reservoir coupling

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

Methnani, M.M.

The gas-network flow model (Gasnet) developed for and added to an existing Qatar General Petroleum Corp. (OGPC) in-house reservoir simulator, allows improved modeling of the interaction among the reservoir, wells, and pipeline networks. Gasnet is a three-phase model that is modified to handle gas-condensate systems. The numerical solution is based on a control volume scheme that uses the concept of cells and junctions, whereby pressure and phase densities are defined in cells, while phase flows are defined at junction links. The model features common numerical equations for the reservoir, the well, and the pipeline components and an efficient state-variable solutionmore » method in which all primary variables including phase flows are solved directly. Both steady-state and transient flow events can be simulated with the same tool. Three test cases show how the model runs. One case simulates flow redistribution in a simple two-branch gas network. The second simulates a horizontal gas well in a waterflooded gas reservoir. The third involves an export gas pipeline coupled to a producing reservoir.« less

Memory-induced mechanism for self-sustaining activity in networks

NASA Astrophysics Data System (ADS)

Allahverdyan, A. E.; Steeg, G. Ver; Galstyan, A.

2015-12-01

We study a mechanism of activity sustaining on networks inspired by a well-known model of neuronal dynamics. Our primary focus is the emergence of self-sustaining collective activity patterns, where no single node can stay active by itself, but the activity provided initially is sustained within the collective of interacting agents. In contrast to existing models of self-sustaining activity that are caused by (long) loops present in the network, here we focus on treelike structures and examine activation mechanisms that are due to temporal memory of the nodes. This approach is motivated by applications in social media, where long network loops are rare or absent. Our results suggest that under a weak behavioral noise, the nodes robustly split into several clusters, with partial synchronization of nodes within each cluster. We also study the randomly weighted version of the models where the nodes are allowed to change their connection strength (this can model attention redistribution) and show that it does facilitate the self-sustained activity.

On Maximizing the Lifetime of Wireless Sensor Networks by Optimally Assigning Energy Supplies

PubMed Central

Asorey-Cacheda, Rafael; García-Sánchez, Antonio Javier; García-Sánchez, Felipe; García-Haro, Joan; Gonzalez-Castaño, Francisco Javier

2013-01-01

The extension of the network lifetime of Wireless Sensor Networks (WSN) is an important issue that has not been appropriately solved yet. This paper addresses this concern and proposes some techniques to plan an arbitrary WSN. To this end, we suggest a hierarchical network architecture, similar to realistic scenarios, where nodes with renewable energy sources (denoted as primary nodes) carry out most message delivery tasks, and nodes equipped with conventional chemical batteries (denoted as secondary nodes) are those with less communication demands. The key design issue of this network architecture is the development of a new optimization framework to calculate the optimal assignment of renewable energy supplies (primary node assignment) to maximize network lifetime, obtaining the minimum number of energy supplies and their node assignment. We also conduct a second optimization step to additionally minimize the number of packet hops between the source and the sink. In this work, we present an algorithm that approaches the results of the optimization framework, but with much faster execution speed, which is a good alternative for large-scale WSN networks. Finally, the network model, the optimization process and the designed algorithm are further evaluated and validated by means of computer simulation under realistic conditions. The results obtained are discussed comparatively. PMID:23939582

On maximizing the lifetime of Wireless Sensor Networks by optimally assigning energy supplies.

PubMed

Asorey-Cacheda, Rafael; García-Sánchez, Antonio Javier; García-Sánchez, Felipe; García-Haro, Joan; González-Castano, Francisco Javier

2013-08-09

The extension of the network lifetime of Wireless Sensor Networks (WSN) is an important issue that has not been appropriately solved yet. This paper addresses this concern and proposes some techniques to plan an arbitrary WSN. To this end, we suggest a hierarchical network architecture, similar to realistic scenarios, where nodes with renewable energy sources (denoted as primary nodes) carry out most message delivery tasks, and nodes equipped with conventional chemical batteries (denoted as secondary nodes) are those with less communication demands. The key design issue of this network architecture is the development of a new optimization framework to calculate the optimal assignment of renewable energy supplies (primary node assignment) to maximize network lifetime, obtaining the minimum number of energy supplies and their node assignment. We also conduct a second optimization step to additionally minimize the number of packet hops between the source and the sink. In this work, we present an algorithm that approaches the results of the optimization framework, but with much faster execution speed, which is a good alternative for large-scale WSN networks. Finally, the network model, the optimization process and the designed algorithm are further evaluated and validated by means of computer simulation under realistic conditions. The results obtained are discussed comparatively.

A logic model framework for evaluation and planning in a primary care practice-based research network (PBRN)

PubMed Central

Hayes, Holly; Parchman, Michael L.; Howard, Ray

2012-01-01

Evaluating effective growth and development of a Practice-Based Research Network (PBRN) can be challenging. The purpose of this article is to describe the development of a logic model and how the framework has been used for planning and evaluation in a primary care PBRN. An evaluation team was formed consisting of the PBRN directors, staff and its board members. After the mission and the target audience were determined, facilitated meetings and discussions were held with stakeholders to identify the assumptions, inputs, activities, outputs, outcomes and outcome indicators. The long-term outcomes outlined in the final logic model are two-fold: 1.) Improved health outcomes of patients served by PBRN community clinicians; and 2.) Community clinicians are recognized leaders of quality research projects. The Logic Model proved useful in identifying stakeholder interests and dissemination activities as an area that required more attention in the PBRN. The logic model approach is a useful planning tool and project management resource that increases the probability that the PBRN mission will be successfully implemented. PMID:21900441

Dissociable meta-analytic brain networks contribute to coordinated emotional processing.

PubMed

Riedel, Michael C; Yanes, Julio A; Ray, Kimberly L; Eickhoff, Simon B; Fox, Peter T; Sutherland, Matthew T; Laird, Angela R

2018-06-01

Meta-analytic techniques for mining the neuroimaging literature continue to exert an impact on our conceptualization of functional brain networks contributing to human emotion and cognition. Traditional theories regarding the neurobiological substrates contributing to affective processing are shifting from regional- towards more network-based heuristic frameworks. To elucidate differential brain network involvement linked to distinct aspects of emotion processing, we applied an emergent meta-analytic clustering approach to the extensive body of affective neuroimaging results archived in the BrainMap database. Specifically, we performed hierarchical clustering on the modeled activation maps from 1,747 experiments in the affective processing domain, resulting in five meta-analytic groupings of experiments demonstrating whole-brain recruitment. Behavioral inference analyses conducted for each of these groupings suggested dissociable networks supporting: (1) visual perception within primary and associative visual cortices, (2) auditory perception within primary auditory cortices, (3) attention to emotionally salient information within insular, anterior cingulate, and subcortical regions, (4) appraisal and prediction of emotional events within medial prefrontal and posterior cingulate cortices, and (5) induction of emotional responses within amygdala and fusiform gyri. These meta-analytic outcomes are consistent with a contemporary psychological model of affective processing in which emotionally salient information from perceived stimuli are integrated with previous experiences to engender a subjective affective response. This study highlights the utility of using emergent meta-analytic methods to inform and extend psychological theories and suggests that emotions are manifest as the eventual consequence of interactions between large-scale brain networks. © 2018 Wiley Periodicals, Inc.

Transformational leadership and group interaction as climate antecedents: a social network analysis.

PubMed

Zohar, Dov; Tenne-Gazit, Orly

2008-07-01

In order to test the social mechanisms through which organizational climate emerges, this article introduces a model that combines transformational leadership and social interaction as antecedents of climate strength (i.e., the degree of within-unit agreement about climate perceptions). Despite their longstanding status as primary variables, both antecedents have received limited empirical research. The sample consisted of 45 platoons of infantry soldiers from 5 different brigades, using safety climate as the exemplar. Results indicate a partially mediated model between transformational leadership and climate strength, with density of group communication network as the mediating variable. In addition, the results showed independent effects for group centralization of the communication and friendship networks, which exerted incremental effects on climate strength over transformational leadership. Whereas centralization of the communication network was found to be negatively related to climate strength, centralization of the friendship network was positively related to it. Theoretical and practical implications are discussed.

Integrated Evaluation of Reliability and Power Consumption of Wireless Sensor Networks.

PubMed

Dâmaso, Antônio; Rosa, Nelson; Maciel, Paulo

2017-11-05

Power consumption is a primary interest in Wireless Sensor Networks (WSNs), and a large number of strategies have been proposed to evaluate it. However, those approaches usually neither consider reliability issues nor the power consumption of applications executing in the network. A central concern is the lack of consolidated solutions that enable us to evaluate the power consumption of applications and the network stack also considering their reliabilities. To solve this problem, we introduce a fully automatic solution to design power consumption aware WSN applications and communication protocols. The solution presented in this paper comprises a methodology to evaluate the power consumption based on the integration of formal models, a set of power consumption and reliability models, a sensitivity analysis strategy to select WSN configurations and a toolbox named EDEN to fully support the proposed methodology. This solution allows accurately estimating the power consumption of WSN applications and the network stack in an automated way.

Readiness for the Patient-Centered Medical Home: Structural Capabilities of Massachusetts Primary Care Practices

PubMed Central

Friedberg, Mark W.; Safran, Dana G.; Coltin, Kathryn L.; Dresser, Marguerite

2008-01-01

Background The Patient-Centered Medical Home (PCMH), a popular model for primary care reorganization, includes several structural capabilities intended to enhance quality of care. The extent to which different types of primary care practices have adopted these capabilities has not been previously studied. Objective To measure the prevalence of recommended structural capabilities among primary care practices and to determine whether prevalence varies among practices of different size (number of physicians) and administrative affiliation with networks of practices. Design Cross-sectional analysis. Participants One physician chosen at random from each of 412 primary care practices in Massachusetts was surveyed about practice capabilities during 2007. Practice size and network affiliation were obtained from an existing database. Measurements Presence of 13 structural capabilities representing 4 domains relevant to quality: patient assistance and reminders, culture of quality, enhanced access, and electronic health records (EHRs). Main Results Three hundred eight (75%) physicians responded, representing practices with a median size of 4 physicians (range 2–74). Among these practices, 64% were affiliated with 1 of 9 networks. The prevalence of surveyed capabilities ranged from 24% to 88%. Larger practice size was associated with higher prevalence for 9 of the 13 capabilities spanning all 4 domains (P < 0.05). Network affiliation was associated with higher prevalence of 5 capabilities (P < 0.05) in 3 domains. Associations were not substantively altered by statistical adjustment for other practice characteristics. Conclusions Larger and network-affiliated primary care practices are more likely than smaller, non-affiliated practices to have adopted several recommended capabilities. In order to achieve PCMH designation, smaller non-affiliated practices may require the greatest investments. Electronic supplementary material The online version of this article (doi:10.1007/s11606-008-0856-x) contains supplementary material, which is available to authorized users. PMID:19050977

The effects of wettability and trapping on relationships between interfacial area, capillary pressure and saturation in porous media: A pore-scale network modeling approach

NASA Astrophysics Data System (ADS)

Raeesi, Behrooz; Piri, Mohammad

2009-10-01

SummaryWe use a three-dimensional mixed-wet random pore-scale network model to investigate the impact of wettability and trapping on the relationship between interfacial area, capillary pressure and saturation in two-phase drainage and imbibition processes. The model is a three-dimensional network of interconnected pores and throats of various geometrical shapes. It allows multiple phases to be present in each capillary element in wetting and spreading layers, as well as occupying the center of the pore space. Two different random networks that represent the pore space in Berea and a Saudi Arabia reservoir sandstone are used in this study. We allow the wettability of the rock surfaces contacted by oil to alter after primary drainage. The model takes into account both contact angle and trapping hystereses. We model primary oil drainage and water flooding for mixed-wet conditions, and secondary oil injection for a water-wet system. The total interfacial area for pores and throats are calculated when the system is at capillary equilibrium. They include contributions from the arc menisci (AMs) between the bulk and corner fluids, and from the main terminal menisci (MTMs) between different bulk fluids. We investigate hysteresis in these relationships by performing water injection into systems of varying wettability and initial water saturation. We show that trapping and contact angle hystereses significantly affect the interfacial area. In a strongly water-wet system, a sharp increase is observed at the beginning of water flood, which shifts the area to a higher level than primary drainage. As we change the wettability of the system from strongly water-wet to strongly oil-wet, the trapped oil saturation decreases significantly. Starting water flood from intermediate water saturations, greater than the irreducible water saturation, can also affect the non-wetting phase entrapment, resulting in different interfacial area behaviors. This can increase the interfacial area significantly in oil-wet systems. A qualitative comparison of our results with the experimental data available in literature for glass beads shows, with some expected differences, an encouraging agreement. Also, our results agree well with those generated by the previously developed models.

Sustained synchronized neuronal network activity in a human astrocyte co-culture system

PubMed Central

Kuijlaars, Jacobine; Oyelami, Tutu; Diels, Annick; Rohrbacher, Jutta; Versweyveld, Sofie; Meneghello, Giulia; Tuefferd, Marianne; Verstraelen, Peter; Detrez, Jan R.; Verschuuren, Marlies; De Vos, Winnok H.; Meert, Theo; Peeters, Pieter J.; Cik, Miroslav; Nuydens, Rony; Brône, Bert; Verheyen, An

2016-01-01

Impaired neuronal network function is a hallmark of neurodevelopmental and neurodegenerative disorders such as autism, schizophrenia, and Alzheimer’s disease and is typically studied using genetically modified cellular and animal models. Weak predictive capacity and poor translational value of these models urge for better human derived in vitro models. The implementation of human induced pluripotent stem cells (hiPSCs) allows studying pathologies in differentiated disease-relevant and patient-derived neuronal cells. However, the differentiation process and growth conditions of hiPSC-derived neurons are non-trivial. In order to study neuronal network formation and (mal)function in a fully humanized system, we have established an in vitro co-culture model of hiPSC-derived cortical neurons and human primary astrocytes that recapitulates neuronal network synchronization and connectivity within three to four weeks after final plating. Live cell calcium imaging, electrophysiology and high content image analyses revealed an increased maturation of network functionality and synchronicity over time for co-cultures compared to neuronal monocultures. The cells express GABAergic and glutamatergic markers and respond to inhibitors of both neurotransmitter pathways in a functional assay. The combination of this co-culture model with quantitative imaging of network morphofunction is amenable to high throughput screening for lead discovery and drug optimization for neurological diseases. PMID:27819315

Construction of pore network models for Berea and Fontainebleau sandstones using non-linear programing and optimization techniques

NASA Astrophysics Data System (ADS)

Sharqawy, Mostafa H.

2016-12-01

Pore network models (PNM) of Berea and Fontainebleau sandstones were constructed using nonlinear programming (NLP) and optimization methods. The constructed PNMs are considered as a digital representation of the rock samples which were based on matching the macroscopic properties of the porous media and used to conduct fluid transport simulations including single and two-phase flow. The PNMs consisted of cubic networks of randomly distributed pores and throats sizes and with various connectivity levels. The networks were optimized such that the upper and lower bounds of the pore sizes are determined using the capillary tube bundle model and the Nelder-Mead method instead of guessing them, which reduces the optimization computational time significantly. An open-source PNM framework was employed to conduct transport and percolation simulations such as invasion percolation and Darcian flow. The PNM model was subsequently used to compute the macroscopic properties; porosity, absolute permeability, specific surface area, breakthrough capillary pressure, and primary drainage curve. The pore networks were optimized to allow for the simulation results of the macroscopic properties to be in excellent agreement with the experimental measurements. This study demonstrates that non-linear programming and optimization methods provide a promising method for pore network modeling when computed tomography imaging may not be readily available.

[Attitude of primary care professionals to gender violence. A comparative study between Catalonia and Costa Rica].

PubMed

Rojas Loría, Kattia; Gutiérrez Rosado, Teresa; Alvarado, Ricardo; Fernández Sánchez, Anna

2015-10-01

Describe the relationship between the attitude towards violence against women (VAW) of professionals of the health of primary care with variables such professional satisfaction, workload, orientation of professional practice, knowledge, training and use of network in Catalonia and Costa Rica. Cross-exploratory and comparative study. Primary care in Barcelona and nearby counties and the Greater Metropolitan Area (GAM) of Costa Rica. 235 primary health professionals of Medicine, Nursing, Psychology and Social Work. Questionnaire with eight sections about attitudes, professional satisfaction, and orientation of professional practice, workload, knowledge, training and use of network. Three types of analysis were carried out: a descriptive one by country; a bivariate analysis; and a multivariable linear regression model. Primary Health Professionals attitudes towards VAW health were similar in both contexts (Catalonia: 3.90 IC 95% 3.84-3.96; Costa Rica: 4.03 IC 95% 3.94-4.13). The variables associated with attitudes towards VAW were: Use of network resources (B=0.20, 95% CI -0.14-0.25, P=<.001), Training (B=0.10, 95% CI 0.04 to 0.17, P=<0.001), and country, Costa Rica (B=0.16, 95% CI 0.06 to 0.25, P=<0.001). There was no interaction between the country and the other variables, suggesting that the association between the variables and the attitude is similar in both countries. The results suggest that increased use of network resources and training are related to a positive attitude towards VWA in primary health professionals, both in Catalonia and Costa Rica. Copyright © 2014 Elsevier España, S.L.U. All rights reserved.

Near real-time traffic routing

NASA Technical Reports Server (NTRS)

Yang, Chaowei (Inventor); Xie, Jibo (Inventor); Zhou, Bin (Inventor); Cao, Ying (Inventor)

2012-01-01

A near real-time physical transportation network routing system comprising: a traffic simulation computing grid and a dynamic traffic routing service computing grid. The traffic simulator produces traffic network travel time predictions for a physical transportation network using a traffic simulation model and common input data. The physical transportation network is divided into a multiple sections. Each section has a primary zone and a buffer zone. The traffic simulation computing grid includes multiple of traffic simulation computing nodes. The common input data includes static network characteristics, an origin-destination data table, dynamic traffic information data and historical traffic data. The dynamic traffic routing service computing grid includes multiple dynamic traffic routing computing nodes and generates traffic route(s) using the traffic network travel time predictions.

Using Social Network Theory to Influence the Development of State and Local Primary Prevention Capacity-Building Teams

ERIC Educational Resources Information Center

Cook-Craig, Patricia G.

2010-01-01

This article examines the role that social network theory and social network analysis has played in assessing and developing effective primary prevention networks across a southeastern state. In 2004 the state began an effort to develop a strategic plan for the primary prevention of violence working with local communities across the state. The…

Redundant Design in Interdependent Networks

PubMed Central

2016-01-01

Modern infrastructure networks are often coupled together and thus could be modeled as interdependent networks. Overload and interdependent effect make interdependent networks more fragile when suffering from attacks. Existing research has primarily concentrated on the cascading failure process of interdependent networks without load, or the robustness of isolated network with load. Only limited research has been done on the cascading failure process caused by overload in interdependent networks. Redundant design is a primary approach to enhance the reliability and robustness of the system. In this paper, we propose two redundant methods, node back-up and dependency redundancy, and the experiment results indicate that two measures are effective and costless. Two detailed models about redundant design are introduced based on the non-linear load-capacity model. Based on the attributes and historical failure distribution of nodes, we introduce three static selecting strategies-Random-based, Degree-based, Initial load-based and a dynamic strategy-HFD (historical failure distribution) to identify which nodes could have a back-up with priority. In addition, we consider the cost and efficiency of different redundant proportions to determine the best proportion with maximal enhancement and minimal cost. Experiments on interdependent networks demonstrate that the combination of HFD and dependency redundancy is an effective and preferred measure to implement redundant design on interdependent networks. The results suggest that the redundant design proposed in this paper can permit construction of highly robust interactive networked systems. PMID:27764174

Multispecialty physician networks in Ontario

PubMed Central

Stukel, Therese A; Glazier, Richard H; Schultz, Susan E; Guan, Jun; Zagorski, Brandon M; Gozdyra, Peter; Henry, David A

2013-01-01

Background Large multispecialty physician group practices, with a central role for primary care practitioners, have been shown to achieve high-quality, low-cost care for patients with chronic disease. We assessed the extent to which informal multispecialty physician networks in Ontario could be identified by using health administrative data to exploit natural linkages among patients, physicians, and hospitals based on existing patient flow. Methods We linked each Ontario resident to his or her usual provider of primary care over the period from fiscal year 2008/2009 to fiscal year 2010/2011. We linked each specialist to the hospital where he or she performed the most inpatient services. We linked each primary care physician to the hospital where most of his or her ambulatory patients were admitted for non-maternal medical care. Each resident was then linked to the same hospital as his or her usual provider of primary care. We computed “loyalty” as the proportion of care to network residents provided by physicians and hospitals within their network. Smaller clusters were aggregated to create networks based on a minimum population size, distance, and loyalty. Networks were not constrained geographically. Results We identified 78 multispecialty physician networks, comprising 12 410 primary care physicians, 14 687 specialists, and 175 acute care hospitals serving a total of 12 917 178 people. Median network size was 134 723 residents, 125 primary care physicians, and 143 specialists. Virtually all eligible residents were linked to a usual provider of primary care and to a network. Most specialists (93.5%) and primary care physicians (98.2%) were linked to a hospital. Median network physician loyalty was 68.4% for all physician visits and 81.1% for primary care visits. Median non-maternal admission loyalty was 67.4%. Urban networks had lower loyalties and were less self-contained but had more health care resources. Interpretation We demonstrated the feasibility of identifying informal multispecialty physician networks in Ontario on the basis of patterns of health care–seeking behaviour. Networks were reasonably self-contained, in that individual residents received most of their care from providers within their respective networks. Formal constitution of networks could foster accountability for efficient, integrated care through care management tools and quality improvement, the ideas behind “accountable care organizations.” PMID:24348884

Failure prediction using machine learning and time series in optical network.

PubMed

Wang, Zhilong; Zhang, Min; Wang, Danshi; Song, Chuang; Liu, Min; Li, Jin; Lou, Liqi; Liu, Zhuo

2017-08-07

In this paper, we propose a performance monitoring and failure prediction method in optical networks based on machine learning. The primary algorithms of this method are the support vector machine (SVM) and double exponential smoothing (DES). With a focus on risk-aware models in optical networks, the proposed protection plan primarily investigates how to predict the risk of an equipment failure. To the best of our knowledge, this important problem has not yet been fully considered. Experimental results showed that the average prediction accuracy of our method was 95% when predicting the optical equipment failure state. This finding means that our method can forecast an equipment failure risk with high accuracy. Therefore, our proposed DES-SVM method can effectively improve traditional risk-aware models to protect services from possible failures and enhance the optical network stability.

Software licensing policy for the Open Source Application Development Portal (OSADP).

DOT National Transportation Integrated Search

1998-07-01

The purpose of the Commercial Vehicle Information Systems and Networks Model Deployment Initiative (CVISN MDI) is to demonstrate the technical and institutional feasibility, costs, and benefits of the primary Intelligent Transportation Systems (ITS) ...

A binomial modeling approach for upscaling colloid transport under unfavorable conditions: Emergent prediction of extended tailing

NASA Astrophysics Data System (ADS)

Hilpert, Markus; Rasmuson, Anna; Johnson, William P.

2017-07-01

Colloid transport in saturated porous media is significantly influenced by colloidal interactions with grain surfaces. Near-surface fluid domain colloids experience relatively low fluid drag and relatively strong colloidal forces that slow their downgradient translation relative to colloids in bulk fluid. Near-surface fluid domain colloids may reenter into the bulk fluid via diffusion (nanoparticles) or expulsion at rear flow stagnation zones, they may immobilize (attach) via primary minimum interactions, or they may move along a grain-to-grain contact to the near-surface fluid domain of an adjacent grain. We introduce a simple model that accounts for all possible permutations of mass transfer within a dual pore and grain network. The primary phenomena thereby represented in the model are mass transfer of colloids between the bulk and near-surface fluid domains and immobilization. Colloid movement is described by a Markov chain, i.e., a sequence of trials in a 1-D network of unit cells, which contain a pore and a grain. Using combinatorial analysis, which utilizes the binomial coefficient, we derive the residence time distribution, i.e., an inventory of the discrete colloid travel times through the network and of their probabilities to occur. To parameterize the network model, we performed mechanistic pore-scale simulations in a single unit cell that determined the likelihoods and timescales associated with the above colloid mass transfer processes. We found that intergrain transport of colloids in the near-surface fluid domain can cause extended tailing, which has traditionally been attributed to hydrodynamic dispersion emanating from flow tortuosity of solute trajectories.

Application of stochastic automata networks for creation of continuous time Markov chain models of voltage gating of gap junction channels.

PubMed

Snipas, Mindaugas; Pranevicius, Henrikas; Pranevicius, Mindaugas; Pranevicius, Osvaldas; Paulauskas, Nerijus; Bukauskas, Feliksas F

2015-01-01

The primary goal of this work was to study advantages of numerical methods used for the creation of continuous time Markov chain models (CTMC) of voltage gating of gap junction (GJ) channels composed of connexin protein. This task was accomplished by describing gating of GJs using the formalism of the stochastic automata networks (SANs), which allowed for very efficient building and storing of infinitesimal generator of the CTMC that allowed to produce matrices of the models containing a distinct block structure. All of that allowed us to develop efficient numerical methods for a steady-state solution of CTMC models. This allowed us to accelerate CPU time, which is necessary to solve CTMC models, ~20 times.

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

NASA Astrophysics Data System (ADS)

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

2015-08-01

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

Bidirectional influence: A longitudinal analysis of size of drug network and depression among inner-city residents in Baltimore, Maryland

PubMed Central

Yang, Jingyan; Latkin, Carl A.; Davey-Rothwell, Melissa

2015-01-01

BACKGROUND The prevalence of depression among drug users is high. It has been recognized that drug use behaviors can be influenced and spread through social networks. OBJECTIVES We investigated the directional relationship between social network factors and depressive symptoms among a sample of inner-city residents in Baltimore, MD. METHODS We performed a longitudinal study of four-wave data collected from a network-based HIV/STI prevention intervention for women and network members, consisting of both men and women. Our primary outcome and exposure were depression using CESD scale and social network characteristics, respectively. Linear mixed model with clustering adjustment was used to account for both repeated measurement and network design. RESULTS Of the 746 participants, those who had high levels of depression tended to be female, less educated, homeless, smokers, and did not have a main partner. In the univariate longitudinal model, larger size of drug network was significantly associated with depression (OR=1.38, p<0.001). This relationship held after controlling for age, gender, homeless in the past six months, college education, having a main partner, cigarette smoking, perceived health, and social support network (aOR=1.19, p=0.001). In the univariate mixed model using depression to predict size of drug network, the data suggested that depression was associated with larger size of drug network (coef.=1.23, p<0.001) and the same relation held in multivariate model (adjusted coef.=1.08, p=0.001). CONCLUSIONS The results suggest that larger size of drug network is a risk factor for depression, and vice versa. Further intervention strategies to reduce depression should address social networks factors. PMID:26584046

Theory of correlation in a network with synaptic depression

NASA Astrophysics Data System (ADS)

Igarashi, Yasuhiko; Oizumi, Masafumi; Okada, Masato

2012-01-01

Synaptic depression affects not only the mean responses of neurons but also the correlation of response variability in neural populations. Although previous studies have constructed a theory of correlation in a spiking neuron model by using the mean-field theory framework, synaptic depression has not been taken into consideration. We expanded the previous theoretical framework in this study to spiking neuron models with short-term synaptic depression. On the basis of this theory we analytically calculated neural correlations in a ring attractor network with Mexican-hat-type connectivity, which was used as a model of the primary visual cortex. The results revealed that synaptic depression reduces neural correlation, which could be beneficial for sensory coding. Furthermore, our study opens the way for theoretical studies on the effect of interaction change on the linear response function in large stochastic networks.

A trans-disciplinary approach to the evaluation of social determinants of health in a Hispanic population.

PubMed

Dulin, Michael F; Tapp, Hazel; Smith, Heather A; de Hernandez, Brisa Urquieta; Coffman, Maren J; Ludden, Tom; Sorensen, Janni; Furuseth, Owen J

2012-09-11

Individual and community health are adversely impacted by disparities in health outcomes among disadvantaged and vulnerable populations. Understanding the underlying causes for variations in health outcomes is an essential step towards developing effective interventions to ameliorate inequalities and subsequently improve overall community health. Working at the neighborhood scale, this study examines multiple social determinates that can cause health disparities including low neighborhood wealth, weak social networks, inadequate public infrastructure, the presence of hazardous materials in or near a neighborhood, and the lack of access to primary care services. The goal of this research is to develop innovative and replicable strategies to improve community health in disadvantaged communities such as newly arrived Hispanic immigrants. This project is taking place within a primary care practice-based research network (PBRN) using key principles of community-based participatory research (CBPR). Associations between social determinants and rates of hospitalizations, emergency department (ED) use, and ED use for primary care treatable or preventable conditions are being examined. Geospatial models are in development using both hospital and community level data to identify local areas where interventions to improve disparities would have the greatest impact. The developed associations between social determinants and health outcomes as well as the geospatial models will be validated using community surveys and qualitative methods. A rapidly growing and underserved Hispanic immigrant population will be the target of an intervention informed by the research process to impact utilization of primary care services and designed, deployed, and evaluated using the geospatial tools and qualitative research findings. The purpose of this intervention will be to reduce health disparities by improving access to, and utilization of, primary care and preventative services. The results of this study will demonstrate the importance of several novel approaches to ameliorating health disparities, including the use of CBPR, the effectiveness of community-based interventions to influence health outcomes by leveraging social networks, and the importance of primary care access in ameliorating health disparities.

The effect of provider affiliation with a primary care network on emergency department visits and hospital admissions.

PubMed

McAlister, Finlay A; Bakal, Jeffrey A; Green, Lee; Bahler, Brad; Lewanczuk, Richard

2018-03-12

Primary care networks are designed to facilitate access to inter-professional, team-based care. We compared health outcomes associated with primary care networks versus conventional primary care. We obtained data on all adult residents of Alberta who visited a primary care physician during fiscal years 2008 and 2009 and classified them as affiliated with a primary care network or not, based on the physician most involved in their care. The primary outcome was an emergency department visit or nonelective hospital admission for a Patient Medical Home indicator condition (asthma, chronic obstructive pulmonary disease, heart failure, coronary disease, hypertension and diabetes) within 12 months. Adults receiving care within a primary care network ( n = 1 502 916) were older and had higher comorbidity burdens than those receiving conventional primary care ( n = 1 109 941). Patients in a primary care network were less likely to visit the emergency department for an indicator condition (1.4% v. 1.7%, mean 0.031 v. 0.035 per patient, adjusted risk ratio [RR] 0.98, 95% confidence interval [CI] 0.96-0.99) or for any cause (25.5% v. 30.5%, mean 0.55 v. 0.72 per patient, adjusted RR 0.93, 95% CI 0.93-0.94), but were more likely to be admitted to hospital for an indicator condition (0.6% v. 0.6%, mean 0.018 v. 0.017 per patient, adjusted RR 1.07, 95% CI 1.03-1.11) or all-cause (9.3% v. 9.1%, mean 0.25 v. 0.23 per patient, adjusted RR 1.08, 95% CI 1.07-1.09). Patients in a primary care network had 169 fewer all-cause emergency department visits and 86 fewer days in hospital (owing to shorter lengths of stay) per 1000 patient-years. Care within a primary care network was associated with fewer emergency department visits and fewer hospital days. © 2018 Joule Inc. or its licensors.

The effect of provider affiliation with a primary care network on emergency department visits and hospital admissions

PubMed Central

Bakal, Jeffrey A.; Green, Lee; Bahler, Brad; Lewanczuk, Richard

2018-01-01

BACKGROUND: Primary care networks are designed to facilitate access to inter-professional, team-based care. We compared health outcomes associated with primary care networks versus conventional primary care. METHODS: We obtained data on all adult residents of Alberta who visited a primary care physician during fiscal years 2008 and 2009 and classified them as affiliated with a primary care network or not, based on the physician most involved in their care. The primary outcome was an emergency department visit or nonelective hospital admission for a Patient Medical Home indicator condition (asthma, chronic obstructive pulmonary disease, heart failure, coronary disease, hypertension and diabetes) within 12 months. RESULTS: Adults receiving care within a primary care network (n = 1 502 916) were older and had higher comorbidity burdens than those receiving conventional primary care (n = 1 109 941). Patients in a primary care network were less likely to visit the emergency department for an indicator condition (1.4% v. 1.7%, mean 0.031 v. 0.035 per patient, adjusted risk ratio [RR] 0.98, 95% confidence interval [CI] 0.96–0.99) or for any cause (25.5% v. 30.5%, mean 0.55 v. 0.72 per patient, adjusted RR 0.93, 95% CI 0.93–0.94), but were more likely to be admitted to hospital for an indicator condition (0.6% v. 0.6%, mean 0.018 v. 0.017 per patient, adjusted RR 1.07, 95% CI 1.03–1.11) or all-cause (9.3% v. 9.1%, mean 0.25 v. 0.23 per patient, adjusted RR 1.08, 95% CI 1.07–1.09). Patients in a primary care network had 169 fewer all-cause emergency department visits and 86 fewer days in hospital (owing to shorter lengths of stay) per 1000 patient-years. INTERPRETATION: Care within a primary care network was associated with fewer emergency department visits and fewer hospital days. PMID:29530868

Scaling Dissolved Nutrient Removal in River Networks: A Comparative Modeling Investigation

NASA Astrophysics Data System (ADS)

Ye, Sheng; Reisinger, Alexander J.; Tank, Jennifer L.; Baker, Michelle A.; Hall, Robert O.; Rosi, Emma J.; Sivapalan, Murugesu

2017-11-01

Along the river network, water, sediment, and nutrients are transported, cycled, and altered by coupled hydrological and biogeochemical processes. Our current understanding of the rates and processes controlling the cycling and removal of dissolved inorganic nutrients in river networks is limited due to a lack of empirical measurements in large, (nonwadeable), rivers. The goal of this paper was to develop a coupled hydrological and biogeochemical process model to simulate nutrient uptake at the network scale during summer base flow conditions. The model was parameterized with literature values from headwater streams, and empirical measurements made in 15 rivers with varying hydrological, biological, and topographic characteristics, to simulate nutrient uptake at the network scale. We applied the coupled model to 15 catchments describing patterns in uptake for three different solutes to determine the role of rivers in network-scale nutrient cycling. Model simulation results, constrained by empirical data, suggested that rivers contributed proportionally more to nutrient removal than headwater streams given the fraction of their length represented in a network. In addition, variability of nutrient removal patterns among catchments was varied among solutes, and as expected, was influenced by nutrient concentration and discharge. Net ammonium uptake was not significantly correlated with any environmental descriptor. In contrast, net daily nitrate removal was linked to suspended chlorophyll a (an indicator of primary producers) and land use characteristics. Finally, suspended sediment characteristics and agricultural land use were correlated with net daily removal of soluble reactive phosphorus, likely reflecting abiotic sorption dynamics. Rivers are understudied relative to streams, and our model suggests that rivers can contribute more to network-scale nutrient removal than would be expected based upon their representative fraction of network channel length.

Resting state brain networks in the prairie vole.

PubMed

Ortiz, Juan J; Portillo, Wendy; Paredes, Raul G; Young, Larry J; Alcauter, Sarael

2018-01-19

Resting state functional magnetic resonance imaging (rsfMRI) has shown the hierarchical organization of the human brain into large-scale complex networks, referred as resting state networks. This technique has turned into a promising translational research tool after the finding of similar resting state networks in non-human primates, rodents and other animal models of great value for neuroscience. Here, we demonstrate and characterize the presence of resting states networks in Microtus ochrogaster, the prairie vole, an extraordinary animal model to study complex human-like social behavior, with potential implications for the research of normal social development, addiction and neuropsychiatric disorders. Independent component analysis of rsfMRI data from isoflurane-anestethized prairie voles resulted in cortical and subcortical networks, including primary motor and sensory networks, but also included putative salience and default mode networks. We further discuss how future research could help to close the gap between the properties of the large scale functional organization and the underlying neurobiology of several aspects of social cognition. These results contribute to the evidence of preserved resting state brain networks across species and provide the foundations to explore the use of rsfMRI in the prairie vole for basic and translational research.

Model for collaboration: a rural medicine and academic health center teleradiology project

NASA Astrophysics Data System (ADS)

Van Slyke, Mark A.; Eggli, Douglas F.; Prior, Fred W.; Salmon, William; Pappas, Gregory; Vanatta, Fred; Goldfetter, Warren; Hashem, Said

1996-05-01

A pilot project was developed to explore the role of subspecialty radiology support to rural medicine sites over a long-distance network. A collaborative relationship between 2 rural radiology practices and an academic health was established. Project objectives included: (1) Does the subspecialty consultation significantly change diagnosis patterns at the rural site? (2) Is there value added as measured by improved clinical care or an overall decreased cost of care? (3) Can a collaborative model be economically self-supportive? (4) Does the collaborative model encourage and support education and collegial relationships? Two rural hospitals were selected based on the level of imaging technology and willingness to cooperate. Image capture and network technology was chosen to make the network process transparent to the users. DICOM standard interfaces were incorporated into existing CT and MRI scanners and a film digitizer. Nuclear medicine images were transferred and viewed using a proprietary vendor protocol. Relevant clinical data was managed by a custom designed PC based Lotus Notes application (Patient Study Tracking System: PaSTS) (Pennsylvania Blue Shield Institute). All data was transferred over a Frame Relay network and managed by the Pennsylvania Commonwealth sponsored PA Health Net. Images, other than nuclear medicine, were viewed on a GE Advantage viewing station using a pair of 2 X 2.5 K gray scale monitors. Patient text data was managed by the PaSTS PC and displayed on a separate 15' color monitor. A total of 476 radiology studies were networked into the AHC. Randomly chosen research studies comprised 82% of the case work. Consultative and primary read cases comprised 17% and 1% respectively. The exercise was judged effective by both rural sites. Significant findings and diagnoses were confirmed in 73% of cases with discrepant findings in only 4%. One site benefited by adopting more advanced imaging techniques increasing the sophistication of radiology services. The primary value for the referring sites was the added confidence provided by the subspecialty overreads. An educational value was recognized by all. In conclusion, the networking of rural health care sites to an AHC subspecialty radiology practice was successful primarily in increasing the diagnostic confidence at the rural site. Other benefits included: education; increased rural imaging and an opportunity to provide primary interpretation when the rural radiologist is not available. However, the rate of rural generated consultation was low (17%) and is unlikely to support the costs of a high speed network. To support, rather than replace, rural radiology requires a lower cost network and a mechanism for payment for these services.

A Hybrid Satellite-Terrestrial Approach to Aeronautical Communication Networks

NASA Technical Reports Server (NTRS)

Kerczewski, Robert J.; Chomos, Gerald J.; Griner, James H.; Mainger, Steven W.; Martzaklis, Konstantinos S.; Kachmar, Brian A.

2000-01-01

Rapid growth in air travel has been projected to continue for the foreseeable future. To maintain a safe and efficient national and global aviation system, significant advances in communications systems supporting aviation are required. Satellites will increasingly play a critical role in the aeronautical communications network. At the same time, current ground-based communications links, primarily very high frequency (VHF), will continue to be employed due to cost advantages and legacy issues. Hence a hybrid satellite-terrestrial network, or group of networks, will emerge. The increased complexity of future aeronautical communications networks dictates that system-level modeling be employed to obtain an optimal system fulfilling a majority of user needs. The NASA Glenn Research Center is investigating the current and potential future state of aeronautical communications, and is developing a simulation and modeling program to research future communications architectures for national and global aeronautical needs. This paper describes the primary requirements, the current infrastructure, and emerging trends of aeronautical communications, including a growing role for satellite communications. The need for a hybrid communications system architecture approach including both satellite and ground-based communications links is explained. Future aeronautical communication network topologies and key issues in simulation and modeling of future aeronautical communications systems are described.

Correlates of caregiver burden among family caregivers of older Korean Americans.

PubMed

Casado, Banghwa; Sacco, Paul

2012-05-01

Despite the rapid growth of older ethnic minority populations, knowledge is limited about informal caregiving among these groups. Our aim was to identify correlates of caregiver burden among family caregivers of older Korean Americans (KAs). A cross-sectional survey collected data from 146 KA caregivers. Using a modified stress-appraisal model, we examined background and context characteristics (caregiver sex, relationship to care recipient, college education, English proficiency, time in caregiving role, family support network, friend support network), a primary stressor (care recipient functional dependency), a primary appraisal (caregiving hours), and resources (family agreement, care management self-efficacy, service use self-efficacy) as potential correlates of caregiver burden. Interactions between the primary stressor, primary appraisal, and resources were also tested. Being female and the care recipient's spouse were associated with higher burden. Conversely, a larger family support network, greater family agreement, and greater care management self-efficacy were associated with lower burden. A significant interaction was detected between functional dependency and family agreement; higher levels of family agreement moderated the association between care recipient functional dependency and caregiver burden. Interventions to reduce caregiver burden in KA caregivers may be more effective if they include approaches specifically designed to build family support, improve family agreement, and increase caregivers' self-efficacy.

Reservoir characterization using core, well log, and seismic data and intelligent software

NASA Astrophysics Data System (ADS)

Soto Becerra, Rodolfo

We have developed intelligent software, Oilfield Intelligence (OI), as an engineering tool to improve the characterization of oil and gas reservoirs. OI integrates neural networks and multivariate statistical analysis. It is composed of five main subsystems: data input, preprocessing, architecture design, graphics design, and inference engine modules. More than 1,200 lines of programming code as M-files using the language MATLAB been written. The degree of success of many oil and gas drilling, completion, and production activities depends upon the accuracy of the models used in a reservoir description. Neural networks have been applied for identification of nonlinear systems in almost all scientific fields of humankind. Solving reservoir characterization problems is no exception. Neural networks have a number of attractive features that can help to extract and recognize underlying patterns, structures, and relationships among data. However, before developing a neural network model, we must solve the problem of dimensionality such as determining dominant and irrelevant variables. We can apply principal components and factor analysis to reduce the dimensionality and help the neural networks formulate more realistic models. We validated OI by obtaining confident models in three different oil field problems: (1) A neural network in-situ stress model using lithology and gamma ray logs for the Travis Peak formation of east Texas, (2) A neural network permeability model using porosity and gamma ray and a neural network pseudo-gamma ray log model using 3D seismic attributes for the reservoir VLE 196 Lamar field located in Block V of south-central Lake Maracaibo (Venezuela), and (3) Neural network primary ultimate oil recovery (PRUR), initial waterflooding ultimate oil recovery (IWUR), and infill drilling ultimate oil recovery (IDUR) models using reservoir parameters for San Andres and Clearfork carbonate formations in west Texas. In all cases, we compared the results from the neural network models with the results from regression statistical and non-parametric approach models. The results show that it is possible to obtain the highest cross-correlation coefficient between predicted and actual target variables, and the lowest average absolute errors using the integrated techniques of multivariate statistical analysis and neural networks in our intelligent software.

Mass balances of dissolved gases at river network scales across biomes.

NASA Astrophysics Data System (ADS)

Wollheim, W. M.; Stewart, R. J.; Sheehan, K.

2016-12-01

Estimating aquatic metabolism and gas fluxes at broad spatial scales is needed to evaluate the role of aquatic ecosystems in continental carbon cycles. We applied a river network model, FrAMES, to quantify the mass balances of dissolved oxygen at river network scales across five river networks in different biomes. The model accounts for hydrology; spatially varying re-aeration rates due to flow, slope, and water temperature; gas inputs via terrestrial runoff; variation in light due to canopy cover and water depth; benthic gross primary production; and benthic respiration. The model was parameterized using existing groundwater information and empirical relationships of GPP, R, and re-aeration, and was tested using dissolved oxygen patterns measured throughout river networks. We found that during summers, internal aquatic production dominates the river network mass balance of Kings Cr., Konza Prairie, KS (16.3 km2), whereas terrestrial inputs and aeration dominate the network mass balance at Coweeta Cr., Coweeta Forest, NC (15.7 km2). At network scales, both river networks are net heterotrophic, with Coweeta more so than Kings Cr. (P:R 0.6 vs. 0.7, respectively). The river network of Kings Creek showed higher network-scale GPP and R compared to Coweeta, despite having a lower drainage density because streams are on average wider so cumulative benthic surface areas are similar. Our findings suggest that the role of aquatic systems in watershed carbon balances will depend on interactions of drainage density, channel hydraulics, terrestrial vegetation, and biological activity.

Graph theoretical modeling of baby brain networks.

PubMed

Zhao, Tengda; Xu, Yuehua; He, Yong

2018-06-12

The human brain undergoes explosive growth during the prenatal period and the first few postnatal years, establishing an early infrastructure for the later development of behaviors and cognitions. Revealing the developmental rules during the early phrase is essential in understanding the emergence of brain function and the origin of developmental disorders. The graph-theoretical network modeling in combination with multiple neuroimaging probes provides an important research framework to explore early development of the topological wiring and organizational paradigms of the brain. Here, we reviewed studies which employed neuroimaging and graph-theoretical modeling to investigate brain network development from approximately 20 gestational weeks to 2 years of age. Specifically, the structural and functional brain networks have evolved to highly efficient topological architectures in the early stage; where the structural network remains ahead and paves the way for the development of functional network. The brain network develops in a heterogeneous order, from primary to higher-order systems and from a tendency of network segregation to network integration in the prenatal and postnatal periods. The early brain network topologies show abilities in predicting certain cognitive and behavior performance in later life, and their impairments are likely to continue into childhood and even adulthood. These macroscopic topological changes are found to be associated with possible microstructural maturations, such as axonal growth and myelinations. Collectively, this review provides a detailed delineation of the early changes of the baby brains in the graph-theoretical modeling framework, which opens up a new avenue to understand the developmental principles of the connectome. Copyright © 2018. Published by Elsevier Inc.

Doctors' opinion on the contribution of coordination mechanisms to improving clinical coordination between primary and outpatient secondary care in the Catalan national health system.

PubMed

Aller, Marta-Beatriz; Vargas, Ingrid; Coderch, Jordi; Vázquez, Maria-Luisa

2017-12-22

Clinical coordination is considered a health policy priority as its absence can lead to poor quality of care and inefficiency. A key challenge is to identify which strategies should be implemented to improve coordination. The aim is to analyse doctors' opinions on the contribution of mechanisms to improving clinical coordination between primary and outpatient secondary care and the factors influencing their use. A qualitative descriptive study in three healthcare networks of the Catalan national health system. A two-stage theoretical sample was designed: in the first stage, networks with different management models were selected; in the second, primary care (n = 26) and secondary care (n = 24) doctors. Data were collected using semi-structured interviews. Final sample size was reached by saturation. A thematic content analysis was conducted, segmented by network and care level. With few differences across networks, doctors identified similar mechanisms contributing to clinical coordination: 1) shared EMR facilitating clinical information transfer and uptake; 2) mechanisms enabling problem-solving communication and agreement on clinical approaches, which varied across networks (joint clinical case conferences, which also promote mutual knowledge and training of primary care doctors; virtual consultations through EMR and email); and 3) referral protocols and use of the telephone facilitating access to secondary care after referrals. Doctors identified organizational (insufficient time, incompatible timetables, design of mechanisms) and professional factors (knowing each other, attitude towards collaboration, concerns over misdiagnosis) that influence the use of mechanisms. Mechanisms that most contribute to clinical coordination are feedback mechanisms, that is those based on mutual adjustment, that allow doctors to exchange information and communicate. Their use might be enhanced by focusing on adequate working conditions, mechanism design and creating conditions that promote mutual knowledge and positive attitudes towards collaboration.

Optimization of hierarchical structure and nanoscale-enabled plasmonic refraction for window electrodes in photovoltaics.

PubMed

Han, Bing; Peng, Qiang; Li, Ruopeng; Rong, Qikun; Ding, Yang; Akinoglu, Eser Metin; Wu, Xueyuan; Wang, Xin; Lu, Xubing; Wang, Qianming; Zhou, Guofu; Liu, Jun-Ming; Ren, Zhifeng; Giersig, Michael; Herczynski, Andrzej; Kempa, Krzysztof; Gao, Jinwei

2016-09-26

An ideal network window electrode for photovoltaic applications should provide an optimal surface coverage, a uniform current density into and/or from a substrate, and a minimum of the overall resistance for a given shading ratio. Here we show that metallic networks with quasi-fractal structure provides a near-perfect practical realization of such an ideal electrode. We find that a leaf venation network, which possesses key characteristics of the optimal structure, indeed outperforms other networks. We further show that elements of hierarchal topology, rather than details of the branching geometry, are of primary importance in optimizing the networks, and demonstrate this experimentally on five model artificial hierarchical networks of varied levels of complexity. In addition to these structural effects, networks containing nanowires are shown to acquire transparency exceeding the geometric constraint due to the plasmonic refraction.

[A historical and conceptual model for Primary Health Care: challenges for the organization of primary care and the Family Health Strategy in large Brazilian cities].

PubMed

Conill, Eleonor Minho

2008-01-01

This paper focuses on the experience with Primary Health Care as a strategy for reorganizing the health care model, based on reforms in this direction and their implementation in the Brazilian case. The article identifies a shift in the discourse concerning health sector reforms, with a return to emphasis on primary care and integration of services. The Brazilian context demands reflection on the possibilities for synergy between this strategy and other social policies and the factors needed to ensure adequate performance. Evaluation research has suggested that primary care activities are slightly superior as compared to traditional health care units, despite persistent difficulties in access, physical infrastructure, team formation, management, and organization of the network. These difficulties correlate with a low level of public financing, persistent segmentation of the system, and weak integration of primary care services with other levels of care. From the technical perspective, a reasonable target is to guarantee the strategy's continuity with the necessary adjustments, conditioned by the dynamics of the health care technical models involved in the dispute.

Parallel approach to identifying the well-test interpretation model using a neurocomputer

NASA Astrophysics Data System (ADS)

May, Edward A., Jr.; Dagli, Cihan H.

1996-03-01

The well test is one of the primary diagnostic and predictive tools used in the analysis of oil and gas wells. In these tests, a pressure recording device is placed in the well and the pressure response is recorded over time under controlled flow conditions. The interpreted results are indicators of the well's ability to flow and the damage done to the formation surrounding the wellbore during drilling and completion. The results are used for many purposes, including reservoir modeling (simulation) and economic forecasting. The first step in the analysis is the identification of the Well-Test Interpretation (WTI) model, which determines the appropriate solution method. Mis-identification of the WTI model occurs due to noise and non-ideal reservoir conditions. Previous studies have shown that a feed-forward neural network using the backpropagation algorithm can be used to identify the WTI model. One of the drawbacks to this approach is, however, training time, which can run into days of CPU time on personal computers. In this paper a similar neural network is applied using both a personal computer and a neurocomputer. Input data processing, network design, and performance are discussed and compared. The results show that the neurocomputer greatly eases the burden of training and allows the network to outperform a similar network running on a personal computer.

A Tool for Modelling the Probability of Landslides Impacting Road Networks

NASA Astrophysics Data System (ADS)

Taylor, Faith E.; Santangelo, Michele; Marchesini, Ivan; Malamud, Bruce D.; Guzzetti, Fausto

2014-05-01

Triggers such as earthquakes or heavy rainfall can result in hundreds to thousands of landslides occurring across a region within a short space of time. These landslides can in turn result in blockages across the road network, impacting how people move about a region. Here, we show the development and application of a semi-stochastic model to simulate how landslides intersect with road networks during a triggered landslide event. This was performed by creating 'synthetic' triggered landslide inventory maps and overlaying these with a road network map to identify where road blockages occur. Our landslide-road model has been applied to two regions: (i) the Collazzone basin (79 km2) in Central Italy where 422 landslides were triggered by rapid snowmelt in January 1997, (ii) the Oat Mountain quadrangle (155 km2) in California, USA, where 1,350 landslides were triggered by the Northridge Earthquake (M = 6.7) in January 1994. For both regions, detailed landslide inventory maps for the triggered events were available, in addition to maps of landslide susceptibility and road networks of primary, secondary and tertiary roads. To create 'synthetic' landslide inventory maps, landslide areas (AL) were randomly selected from a three-parameter inverse gamma probability density function, consisting of a power law decay of about -2.4 for medium and large values of AL and an exponential rollover for small values of AL. The number of landslide areas selected was based on the observed density of landslides (number of landslides km-2) in the triggered event inventories. Landslide shapes were approximated as ellipses, where the ratio of the major and minor axes varies with AL. Landslides were then dropped over the region semi-stochastically, conditioned by a landslide susceptibility map, resulting in a synthetic landslide inventory map. The originally available landslide susceptibility maps did not take into account susceptibility changes in the immediate vicinity of roads, therefore our landslide susceptibility map was adjusted to further reduce the susceptibility near each road based on the road level (primary, secondary, tertiary). For each model run, we superimposed the spatial location of landslide drops with the road network, and recorded the number, size and location of road blockages recorded, along with landslides within 50 and 100 m of the different road levels. Network analysis tools available in GRASS GIS were also applied to measure the impact upon the road network in terms of connectivity. The model was performed 100 times in a Monte-Carlo simulation for each region. Initial results show reasonable agreement between model output and the observed landslide inventories in terms of the number of road blockages. In Collazzone (length of road network = 153 km, landslide density = 5.2 landslides km-2), the median number of modelled road blockages over 100 model runs was 5 (±2.5 standard deviation) compared to the mapped inventory observed number of 5 road blockages. In Northridge (length of road network = 780 km, landslide density = 8.7 landslides km-2), the median number of modelled road blockages over 100 model runs was 108 (±17.2 standard deviation) compared to the mapped inventory observed number of 48 road blockages. As we progress with model development, we believe this semi-stochastic modelling approach will potentially aid civil protection agencies to explore different scenarios of road network potential damage as the result of different magnitude landslide triggering event scenarios.

A Model of Mental State Transition Network

NASA Astrophysics Data System (ADS)

Xiang, Hua; Jiang, Peilin; Xiao, Shuang; Ren, Fuji; Kuroiwa, Shingo

Emotion is one of the most essential and basic attributes of human intelligence. Current AI (Artificial Intelligence) research is concentrating on physical components of emotion, rarely is it carried out from the view of psychology directly(1). Study on the model of artificial psychology is the first step in the development of human-computer interaction. As affective computing remains unpredictable, creating a reasonable mental model becomes the primary task for building a hybrid system. A pragmatic mental model is also the fundament of some key topics such as recognition and synthesis of emotions. In this paper a Mental State Transition Network Model(2) is proposed to detect human emotions. By a series of psychological experiments, we present a new way to predict coming human's emotions depending on the various current emotional states under various stimuli. Besides, people in different genders and characters are taken into consideration in our investigation. According to the psychological experiments data derived from 200 questionnaires, a Mental State Transition Network Model for describing the transitions in distribution among the emotions and relationships between internal mental situations and external are concluded. Further more the coefficients of the mental transition network model were achieved. Comparing seven relative evaluating experiments, an average precision rate of 0.843 is achieved using a set of samples for the proposed model.

Genetic and Diagnostic Biomarker Development in ASD Toddlers Using Resting-State Functional MRI

DTIC Science & Technology

by the principal investigators are being mined for ASD relevant biomarkers. Structural and (constrained) functional meta-analyses of previously...ASD and typically developing (TD) individuals. These regions-of-interest will be extended through additional functional meta-analyses, network models will be created, and these models will be applied to primary ASD data .

Achieving excellence in veterans healthcare--a balanced scorecard approach.

PubMed

Biro, Lawrence A; Moreland, Michael E; Cowgill, David E

2003-01-01

This article provides healthcare administrators and managers with a framework and model for developing a balanced scorecard and demonstrates the remarkable success of this process, which brings focus to leadership decisions about the allocation of resources. This scorecard was developed as a top management tool designed to structure multiple priorities of a large, complex, integrated healthcare system and to establish benchmarks to measure success in achieving targets for performance in identified areas. Significant benefits and positive results were derived from the implementation of the balanced scorecard, based upon benchmarks considered to be critical success factors. The network's chief executive officer and top leadership team set and articulated the network's primary operating principles: quality and efficiency in the provision of comprehensive healthcare and support services. Under the weighted benchmarks of the balanced scorecard, the facilities in the network were mandated to adhere to one non-negotiable tenet: providing care that is second to none. The balanced scorecard approach to leadership continuously ensures that this is the primary goal and focal point for all activity within the network. To that end, systems are always in place to ensure that the network is fully successful on all performance measures relating to quality.

A Distance-based Energy Aware Routing algorithm for wireless sensor networks.

PubMed

Wang, Jin; Kim, Jeong-Uk; Shu, Lei; Niu, Yu; Lee, Sungyoung

2010-01-01

Energy efficiency and balancing is one of the primary challenges for wireless sensor networks (WSNs) since the tiny sensor nodes cannot be easily recharged once they are deployed. Up to now, many energy efficient routing algorithms or protocols have been proposed with techniques like clustering, data aggregation and location tracking etc. However, many of them aim to minimize parameters like total energy consumption, latency etc., which cause hotspot nodes and partitioned network due to the overuse of certain nodes. In this paper, a Distance-based Energy Aware Routing (DEAR) algorithm is proposed to ensure energy efficiency and energy balancing based on theoretical analysis of different energy and traffic models. During the routing process, we consider individual distance as the primary parameter in order to adjust and equalize the energy consumption among involved sensors. The residual energy is also considered as a secondary factor. In this way, all the intermediate nodes will consume their energy at similar rate, which maximizes network lifetime. Simulation results show that the DEAR algorithm can reduce and balance the energy consumption for all sensor nodes so network lifetime is greatly prolonged compared to other routing algorithms.

Burstiness and tie activation strategies in time-varying social networks.

PubMed

Ubaldi, Enrico; Vezzani, Alessandro; Karsai, Márton; Perra, Nicola; Burioni, Raffaella

2017-04-13

The recent developments in the field of social networks shifted the focus from static to dynamical representations, calling for new methods for their analysis and modelling. Observations in real social systems identified two main mechanisms that play a primary role in networks' evolution and influence ongoing spreading processes: the strategies individuals adopt when selecting between new or old social ties, and the bursty nature of the social activity setting the pace of these choices. We introduce a time-varying network model accounting both for ties selection and burstiness and we analytically study its phase diagram. The interplay of the two effects is non trivial and, interestingly, the effects of burstiness might be suppressed in regimes where individuals exhibit a strong preference towards previously activated ties. The results are tested against numerical simulations and compared with two empirical datasets with very good agreement. Consequently, the framework provides a principled method to classify the temporal features of real networks, and thus yields new insights to elucidate the effects of social dynamics on spreading processes.

A regularization approach to continuous learning with an application to financial derivatives pricing.

PubMed

Ormoneit, D

1999-12-01

We consider the training of neural networks in cases where the nonlinear relationship of interest gradually changes over time. One possibility to deal with this problem is by regularization where a variation penalty is added to the usual mean squared error criterion. To learn the regularized network weights we suggest the Iterative Extended Kalman Filter (IEKF) as a learning rule, which may be derived from a Bayesian perspective on the regularization problem. A primary application of our algorithm is in financial derivatives pricing, where neural networks may be used to model the dependency of the derivatives' price on one or several underlying assets. After giving a brief introduction to the problem of derivatives pricing we present experiments with German stock index options data showing that a regularized neural network trained with the IEKF outperforms several benchmark models and alternative learning procedures. In particular, the performance may be greatly improved using a newly designed neural network architecture that accounts for no-arbitrage pricing restrictions.

Integrated Evaluation of Reliability and Power Consumption of Wireless Sensor Networks

PubMed Central

Dâmaso, Antônio; Maciel, Paulo

2017-01-01

Power consumption is a primary interest in Wireless Sensor Networks (WSNs), and a large number of strategies have been proposed to evaluate it. However, those approaches usually neither consider reliability issues nor the power consumption of applications executing in the network. A central concern is the lack of consolidated solutions that enable us to evaluate the power consumption of applications and the network stack also considering their reliabilities. To solve this problem, we introduce a fully automatic solution to design power consumption aware WSN applications and communication protocols. The solution presented in this paper comprises a methodology to evaluate the power consumption based on the integration of formal models, a set of power consumption and reliability models, a sensitivity analysis strategy to select WSN configurations and a toolbox named EDEN to fully support the proposed methodology. This solution allows accurately estimating the power consumption of WSN applications and the network stack in an automated way. PMID:29113078

A network perspective on comorbid depression in adolescents with obsessive-compulsive disorder.

PubMed

Jones, Payton J; Mair, Patrick; Riemann, Bradley C; Mugno, Beth L; McNally, Richard J

2018-01-01

People with obsessive-compulsive disorder [OCD] frequently suffer from depression, a comorbidity associated with greater symptom severity and suicide risk. We examined the associations between OCD and depression symptoms in 87 adolescents with primary OCD. We computed an association network, a graphical LASSO, and a directed acyclic graph (DAG) to model symptom interactions. Models showed OCD and depression as separate syndromes linked by bridge symptoms. Bridges between the two disorders emerged between obsessional problems in the OCD syndrome, and guilt, concentration problems, and sadness in the depression syndrome. A directed network indicated that OCD symptoms directionally precede depression symptoms. Concentration impairment emerged as a highly central node that may be distinctive to adolescents. We conclude that the network approach to mental disorders provides a new way to understand the etiology and maintenance of comorbid OCD-depression. Network analysis can improve research and treatment of mental disorder comorbidities by generating hypotheses concerning potential causal symptom structures and by identifying symptoms that may bridge disorders. Copyright © 2017 Elsevier Ltd. All rights reserved.

Meeting the Mental Health Needs of Low-Income Immigrants in Primary Care: A Community Adaptation of an Evidence-Based Model

PubMed Central

Kaltman, Stacey; Pauk, Jennifer; Alter, Carol L.

2011-01-01

Low-income, uninsured immigrants are burdened by poverty and a high prevalence of trauma exposure, and thus are vulnerable to mental health problems. Disparities in access to mental health services highlight the importance of adapting evidence-based interventions in primary care settings that serve this population. In 2005, The Montgomery Cares Behavioral Health Program (MCBHP) began adapting and implementing a collaborative care model for the treatment of depression and anxiety disorders in a network of primary care clinics that serve low-income, uninsured residents of Montgomery County, Maryland, the majority of whom are immigrants. In its 6th year now, the program has generated much needed knowledge about the adaptation of this evidence-based model. The current article describes the adaptations to the traditional collaborative care model that were necessitated by patient characteristics and the clinic environment. PMID:21977940

Functional connectivity analysis in resting state fMRI with echo-state networks and non-metric clustering for network structure recovery

NASA Astrophysics Data System (ADS)

Wismüller, Axel; DSouza, Adora M.; Abidin, Anas Z.; Wang, Xixi; Hobbs, Susan K.; Nagarajan, Mahesh B.

2015-03-01

Echo state networks (ESN) are recurrent neural networks where the hidden layer is replaced with a fixed reservoir of neurons. Unlike feed-forward networks, neuron training in ESN is restricted to the output neurons alone thereby providing a computational advantage. We demonstrate the use of such ESNs in our mutual connectivity analysis (MCA) framework for recovering the primary motor cortex network associated with hand movement from resting state functional MRI (fMRI) data. Such a framework consists of two steps - (1) defining a pair-wise affinity matrix between different pixel time series within the brain to characterize network activity and (2) recovering network components from the affinity matrix with non-metric clustering. Here, ESNs are used to evaluate pair-wise cross-estimation performance between pixel time series to create the affinity matrix, which is subsequently subject to non-metric clustering with the Louvain method. For comparison, the ground truth of the motor cortex network structure is established with a task-based fMRI sequence. Overlap between the primary motor cortex network recovered with our model free MCA approach and the ground truth was measured with the Dice coefficient. Our results show that network recovery with our proposed MCA approach is in close agreement with the ground truth. Such network recovery is achieved without requiring low-pass filtering of the time series ensembles prior to analysis, an fMRI preprocessing step that has courted controversy in recent years. Thus, we conclude our MCA framework can allow recovery and visualization of the underlying functionally connected networks in the brain on resting state fMRI.

Application of Stochastic Automata Networks for Creation of Continuous Time Markov Chain Models of Voltage Gating of Gap Junction Channels

PubMed Central

Pranevicius, Henrikas; Pranevicius, Mindaugas; Pranevicius, Osvaldas; Bukauskas, Feliksas F.

2015-01-01

The primary goal of this work was to study advantages of numerical methods used for the creation of continuous time Markov chain models (CTMC) of voltage gating of gap junction (GJ) channels composed of connexin protein. This task was accomplished by describing gating of GJs using the formalism of the stochastic automata networks (SANs), which allowed for very efficient building and storing of infinitesimal generator of the CTMC that allowed to produce matrices of the models containing a distinct block structure. All of that allowed us to develop efficient numerical methods for a steady-state solution of CTMC models. This allowed us to accelerate CPU time, which is necessary to solve CTMC models, ∼20 times. PMID:25705700

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

DOE PAGES

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

2015-05-27

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

Development of analytic intermodal freight networks for use within a GIS

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

Southworth, F.; Xiong, D.; Middendorf, D.

1997-05-01

The paper discusses the practical issues involved in constructing intermodal freight networks that can be used within GIS platforms to support inter-regional freight routing and subsequent (for example, commodity flow) analysis. The procedures described can be used to create freight-routable and traffic flowable interstate and intermodal networks using some combination of highway, rail, water and air freight transportation. Keys to realistic freight routing are the identification of intermodal transfer locations and associated terminal functions, a proper handling of carrier-owned and operated sub-networks within each of the primary modes of transport, and the ability to model the types of carrier servicesmore » being offered.« less

Primary care quality in the Medicare Program: comparing the performance of Medicare health maintenance organizations and traditional fee-for-service medicare.

PubMed

Safran, Dana Gelb; Wilson, Ira B; Rogers, William H; Montgomery, Jana E; Chang, Hong

2002-04-08

Since 1972, Medicare beneficiaries have had the option of enrolling in a Medicare-qualified health maintenance organization (HMO). Little information exists to inform beneficiaries' choices between the traditional fee-for-service (FFS) Medicare program and an HMO. To compare the primary care received by seniors in Medicare HMOs with that of seniors in the traditional FFS Medicare program, and among HMOs, and to examine performance differences associated with HMO model-type and profit status. Data were derived from a cross-sectional observational survey of Medicare beneficiaries 65 years or older in the 13 states with mature, substantial Medicare HMO markets. Only beneficiaries continuously enrolled for 12 months or more in traditional FFS Medicare or a qualified Medicare HMO were eligible. Data were obtained using a 5-stage protocol involving mail and telephone (64% response rate). Analyses included respondents who identified a primary physician and had all required data elements (N = 8828). We compared FFS and HMO performance on 11 summary scales measuring 7 defining characteristics of primary care: (1) access, (2) continuity, (3) integration, (4) comprehensiveness, (5) "whole-person" orientation, (6) clinical interaction, and (7) sustained clinician-patient partnership. For 9 of 11 indicators, performance favored traditional FFS Medicare over HMOs (P<.001). Financial access favored HMOs (P<.001). Preventive counseling did not differ by system. Network-model HMOs performed more favorably than staff/group-model HMOs on 9 of 11 indicators (P<.001). Few differences were associated with HMO profit status. The findings are consistent with previous comparisons of indemnity insurance and network-model and staff/group-model HMOs in elderly and nonelderly populations. The stability of results across time, geography, and populations suggests that the relative strengths and weaknesses of each system are enduring attributes of their care. Medicare enrollees seem to face the perennial cost-quality trade-off: that is, deciding whether the advantages of primary care under traditional FFS Medicare are worth the higher out-of-pocket costs.

Development of a Bayesian Belief Network Runway Incursion and Excursion Model

NASA Technical Reports Server (NTRS)

Green, Lawrence L.

2014-01-01

In a previous work, a statistical analysis of runway incursion (RI) event data was conducted to ascertain the relevance of this data to the top ten Technical Challenges (TC) of the National Aeronautics and Space Administration (NASA) Aviation Safety Program (AvSP). The study revealed connections to several of the AvSP top ten TC and identified numerous primary causes and contributing factors of RI events. The statistical analysis served as the basis for developing a system-level Bayesian Belief Network (BBN) model for RI events, also previously reported. Through literature searches and data analysis, this RI event network has now been extended to also model runway excursion (RE) events. These RI and RE event networks have been further modified and vetted by a Subject Matter Expert (SME) panel. The combined system-level BBN model will allow NASA to generically model the causes of RI and RE events and to assess the effectiveness of technology products being developed under NASA funding. These products are intended to reduce the frequency of runway safety incidents/accidents, and to improve runway safety in general. The development and structure of the BBN for both RI and RE events are documented in this paper.

A modular network for legged locomotion

NASA Astrophysics Data System (ADS)

Golubitsky, Martin; Stewart, Ian; Buono, Pietro-Luciano; Collins, J. J.

1998-04-01

In this paper we use symmetry methods to study networks of coupled cells, which are models for central pattern generators (CPGs). In these models the cells obey identical systems of differential equations and the network specifies how cells are coupled. Previously, Collins and Stewart showed that the phase relations of many of the standard gaits of quadrupeds and hexapods can be obtained naturally via Hopf bifurcation in small networks. For example, the networks they used to study quadrupeds all had four cells, with the understanding that each cell determined the phase of the motion of one leg. However, in their work it seemed necessary to employ several different four-oscillator networks to obtain all of the standard quadrupedal gaits. We show that this difficulty with four-oscillator networks is unavoidable, but that the problems can be overcome by using a larger network. Specifically, we show that the standard gaits of a quadruped, including walk, trot and pace, cannot all be realized by a single four-cell network without introducing unwanted conjugacies between trot and pace - conjugacies that imply a dynamic equivalence between these gaits that seems inconsistent with observations. In this sense a single network with four cells cannot model the CPG of a quadruped. We also introduce a single eight-cell network that can model all of the primary gaits of quadrupeds without these unwanted conjugacies. Moreover, this network is modular in that it naturally generalizes to provide models of gaits in hexapods, centipedes, and millipedes. The analysis of models for many-legged animals shows that wave-like motions, similar to those obtained by Kopell and Ermentrout, can be expected. However, our network leads to a prediction that the wavelength of the wave motion will divide twice the length of the animal. Indeed, we reproduce illustrations of wave-like motions in centipedes where the animal is approximately one-and-a-half wavelength long - motions that are consistent with this prediction. We discuss the implications of these results for the development of modular control networks for adaptive legged robots.

Structure, function, and control of the human musculoskeletal network

PubMed Central

Murphy, Andrew C.; Muldoon, Sarah F.; Baker, David; Lastowka, Adam; Bennett, Brittany; Yang, Muzhi

2018-01-01

The human body is a complex organism, the gross mechanical properties of which are enabled by an interconnected musculoskeletal network controlled by the nervous system. The nature of musculoskeletal interconnection facilitates stability, voluntary movement, and robustness to injury. However, a fundamental understanding of this network and its control by neural systems has remained elusive. Here we address this gap in knowledge by utilizing medical databases and mathematical modeling to reveal the organizational structure, predicted function, and neural control of the musculoskeletal system. We constructed a highly simplified whole-body musculoskeletal network in which single muscles connect to multiple bones via both origin and insertion points. We demonstrated that, using this simplified model, a muscle’s role in this network could offer a theoretical prediction of the susceptibility of surrounding components to secondary injury. Finally, we illustrated that sets of muscles cluster into network communities that mimic the organization of control modules in primary motor cortex. This novel formalism for describing interactions between the muscular and skeletal systems serves as a foundation to develop and test therapeutic responses to injury, inspiring future advances in clinical treatments. PMID:29346370

Modeling and Analyzing Intrusion Attempts to a Computer Network Operating in a Defense in Depth Posture

DTIC Science & Technology

2004-09-01

protection. Firewalls, Intrusion Detection Systems (IDS’s), Anti-Virus (AV) software , and routers are such tools used. In recent years, computer security...associated with operating systems, application software , and computing hardware. When IDS’s are utilized on a host computer or network, there are two...primary approaches to detecting and / or preventing attacks. Traditional IDS’s, like most AV software , rely on known “signatures” to detect attacks

A human factors systems approach to understanding team-based primary care: a qualitative analysis

PubMed Central

Mundt, Marlon P.; Swedlund, Matthew P.

2016-01-01

Background. Research shows that high-functioning teams improve patient outcomes in primary care. However, there is no consensus on a conceptual model of team-based primary care that can be used to guide measurement and performance evaluation of teams. Objective. To qualitatively understand whether the Systems Engineering Initiative for Patient Safety (SEIPS) model could serve as a framework for creating and evaluating team-based primary care. Methods. We evaluated qualitative interview data from 19 clinicians and staff members from 6 primary care clinics associated with a large Midwestern university. All health care clinicians and staff in the study clinics completed a survey of their communication connections to team members. Social network analysis identified key informants for interviews by selecting the respondents with the highest frequency of communication ties as reported by their teammates. Semi-structured interviews focused on communication patterns, team climate and teamwork. Results. Themes derived from the interviews lent support to the SEIPS model components, such as the work system (Team, Tools and Technology, Physical Environment, Tasks and Organization), team processes and team outcomes. Conclusions. Our qualitative data support the SEIPS model as a promising conceptual framework for creating and evaluating primary care teams. Future studies of team-based care may benefit from using the SEIPS model to shift clinical practice to high functioning team-based primary care. PMID:27578837

Divergent modes of integration: the Canadian way.

PubMed

Jiwani, Izzat; Fleury, Marie-Josée

2011-01-01

The paper highlights key trajectories and outcomes of the recent policy developments toward integrated health care delivery systems in Quebec and Ontario in the primary care sector and in the development of regional networks of health and social services. It particularly explores how policy legacies, interests and cultures may be mitigated to develop and sustain different models of integrated health care that are pertinent to the local contexts. In Quebec, three decades of iterative developments in health and social services evolved in 2005 into integrated centres for health and social services at the local levels (CSSSs). Four integrated university-based health care networks provide ultra-specialised services. Family Medicine Groups and network clinics are designed to enhance access and continuity of care. Ontario's Family Health Teams (2004) constitute an innovative public funding for private delivery model that is set up to enhance the capacity of primary care and to facilitate patient-based care. Ontario's Local Health Integration Networks (LHINs) with autonomous boards of provider organisations are intended to coordinate and integrate care. Integration strategies in Quebec and Ontario yield clinical autonomy and power to physicians while simultaneously making them key partners in change. Contextual factors combined with increased and varied forms of physician remunerations and incentives mitigated some of the challenges from policy legacies, interests and cultures. Virtual partnerships and accountability agreements between providers promise positive but gradual movement toward integrated health service systems.

Optimal investments in digital communication systems in primary exchange area

NASA Astrophysics Data System (ADS)

Garcia, R.; Hornung, R.

1980-11-01

Integer linear optimization theory, following Gomory's method, was applied to the model planning of telecommunication networks in which all future investments are made in digital systems only. The integer decision variables are the number of digital systems set up on cable or radiorelay links that can be installed. The objective function is the total cost of the extension of the existing line capacity to meet the demand between primary and local exchanges. Traffic volume constraints and flow conservation in transit nodes complete the model. Results indicating computing time and method efficiency are illustrated by an example.

Large-Scale Brain Systems in ADHD: Beyond the Prefrontal-Striatal Model

PubMed Central

Castellanos, F. Xavier; Proal, Erika

2012-01-01

Attention-deficit/hyperactivity disorder (ADHD) has long been thought to reflect dysfunction of prefrontal-striatal circuitry, with involvement of other circuits largely ignored. Recent advances in systems neuroscience-based approaches to brain dysfunction enable the development of models of ADHD pathophysiology that encompass a number of different large-scale “resting state” networks. Here we review progress in delineating large-scale neural systems and illustrate their relevance to ADHD. We relate frontoparietal, dorsal attentional, motor, visual, and default networks to the ADHD functional and structural literature. Insights emerging from mapping intrinsic brain connectivity networks provide a potentially mechanistic framework for understanding aspects of ADHD, such as neuropsychological and behavioral inconsistency, and the possible role of primary visual cortex in attentional dysfunction in the disorder. PMID:22169776

An investigation of the impact of using different methods for network meta-analysis: a protocol for an empirical evaluation.

PubMed

Karahalios, Amalia Emily; Salanti, Georgia; Turner, Simon L; Herbison, G Peter; White, Ian R; Veroniki, Areti Angeliki; Nikolakopoulou, Adriani; Mckenzie, Joanne E

2017-06-24

Network meta-analysis, a method to synthesise evidence from multiple treatments, has increased in popularity in the past decade. Two broad approaches are available to synthesise data across networks, namely, arm- and contrast-synthesis models, with a range of models that can be fitted within each. There has been recent debate about the validity of the arm-synthesis models, but to date, there has been limited empirical evaluation comparing results using the methods applied to a large number of networks. We aim to address this gap through the re-analysis of a large cohort of published networks of interventions using a range of network meta-analysis methods. We will include a subset of networks from a database of network meta-analyses of randomised trials that have been identified and curated from the published literature. The subset of networks will include those where the primary outcome is binary, the number of events and participants are reported for each direct comparison, and there is no evidence of inconsistency in the network. We will re-analyse the networks using three contrast-synthesis methods and two arm-synthesis methods. We will compare the estimated treatment effects, their standard errors, treatment hierarchy based on the surface under the cumulative ranking (SUCRA) curve, the SUCRA value, and the between-trial heterogeneity variance across the network meta-analysis methods. We will investigate whether differences in the results are affected by network characteristics and baseline risk. The results of this study will inform whether, in practice, the choice of network meta-analysis method matters, and if it does, in what situations differences in the results between methods might arise. The results from this research might also inform future simulation studies.

Long-term optical stimulation of channelrhodopsin-expressing neurons to study network plasticity

PubMed Central

Lignani, Gabriele; Ferrea, Enrico; Difato, Francesco; Amarù, Jessica; Ferroni, Eleonora; Lugarà, Eleonora; Espinoza, Stefano; Gainetdinov, Raul R.; Baldelli, Pietro; Benfenati, Fabio

2013-01-01

Neuronal plasticity produces changes in excitability, synaptic transmission, and network architecture in response to external stimuli. Network adaptation to environmental conditions takes place in time scales ranging from few seconds to days, and modulates the entire network dynamics. To study the network response to defined long-term experimental protocols, we setup a system that combines optical and electrophysiological tools embedded in a cell incubator. Primary hippocampal neurons transduced with lentiviruses expressing channelrhodopsin-2/H134R were subjected to various photostimulation protocols in a time window in the order of days. To monitor the effects of light-induced gating of network activity, stimulated transduced neurons were simultaneously recorded using multi-electrode arrays (MEAs). The developed experimental model allows discerning short-term, long-lasting, and adaptive plasticity responses of the same neuronal network to distinct stimulation frequencies applied over different temporal windows. PMID:23970852

Optimization of hierarchical structure and nanoscale-enabled plasmonic refraction for window electrodes in photovoltaics

PubMed Central

Han, Bing; Peng, Qiang; Li, Ruopeng; Rong, Qikun; Ding, Yang; Akinoglu, Eser Metin; Wu, Xueyuan; Wang, Xin; Lu, Xubing; Wang, Qianming; Zhou, Guofu; Liu, Jun-Ming; Ren, Zhifeng; Giersig, Michael; Herczynski, Andrzej; Kempa, Krzysztof; Gao, Jinwei

2016-01-01

An ideal network window electrode for photovoltaic applications should provide an optimal surface coverage, a uniform current density into and/or from a substrate, and a minimum of the overall resistance for a given shading ratio. Here we show that metallic networks with quasi-fractal structure provides a near-perfect practical realization of such an ideal electrode. We find that a leaf venation network, which possesses key characteristics of the optimal structure, indeed outperforms other networks. We further show that elements of hierarchal topology, rather than details of the branching geometry, are of primary importance in optimizing the networks, and demonstrate this experimentally on five model artificial hierarchical networks of varied levels of complexity. In addition to these structural effects, networks containing nanowires are shown to acquire transparency exceeding the geometric constraint due to the plasmonic refraction. PMID:27667099

Long-term optical stimulation of channelrhodopsin-expressing neurons to study network plasticity.

PubMed

Lignani, Gabriele; Ferrea, Enrico; Difato, Francesco; Amarù, Jessica; Ferroni, Eleonora; Lugarà, Eleonora; Espinoza, Stefano; Gainetdinov, Raul R; Baldelli, Pietro; Benfenati, Fabio

2013-01-01

Neuronal plasticity produces changes in excitability, synaptic transmission, and network architecture in response to external stimuli. Network adaptation to environmental conditions takes place in time scales ranging from few seconds to days, and modulates the entire network dynamics. To study the network response to defined long-term experimental protocols, we setup a system that combines optical and electrophysiological tools embedded in a cell incubator. Primary hippocampal neurons transduced with lentiviruses expressing channelrhodopsin-2/H134R were subjected to various photostimulation protocols in a time window in the order of days. To monitor the effects of light-induced gating of network activity, stimulated transduced neurons were simultaneously recorded using multi-electrode arrays (MEAs). The developed experimental model allows discerning short-term, long-lasting, and adaptive plasticity responses of the same neuronal network to distinct stimulation frequencies applied over different temporal windows.

Network Analysis: Applications for the Developing Brain

PubMed Central

Chu-Shore, Catherine J.; Kramer, Mark A.; Bianchi, Matt T.; Caviness, Verne S.; Cash, Sydney S.

2011-01-01

Development of the human brain follows a complex trajectory of age-specific anatomical and physiological changes. The application of network analysis provides an illuminating perspective on the dynamic interregional and global properties of this intricate and complex system. Here, we provide a critical synopsis of methods of network analysis with a focus on developing brain networks. After discussing basic concepts and approaches to network analysis, we explore the primary events of anatomical cortical development from gestation through adolescence. Upon this framework, we describe early work revealing the evolution of age-specific functional brain networks in normal neurodevelopment. Finally, we review how these relationships can be altered in disease and perhaps even rectified with treatment. While this method of description and inquiry remains in early form, there is already substantial evidence that the application of network models and analysis to understanding normal and abnormal human neural development holds tremendous promise for future discovery. PMID:21303762

The mixed serotonin receptor agonist psilocybin reduces threat-induced modulation of amygdala connectivity

PubMed Central

Kraehenmann, Rainer; Schmidt, André; Friston, Karl; Preller, Katrin H.; Seifritz, Erich; Vollenweider, Franz X.

2015-01-01

Stimulation of serotonergic neurotransmission by psilocybin has been shown to shift emotional biases away from negative towards positive stimuli. We have recently shown that reduced amygdala activity during threat processing might underlie psilocybin's effect on emotional processing. However, it is still not known whether psilocybin modulates bottom-up or top-down connectivity within the visual-limbic-prefrontal network underlying threat processing. We therefore analyzed our previous fMRI data using dynamic causal modeling and used Bayesian model selection to infer how psilocybin modulated effective connectivity within the visual–limbic–prefrontal network during threat processing. First, both placebo and psilocybin data were best explained by a model in which threat affect modulated bidirectional connections between the primary visual cortex, amygdala, and lateral prefrontal cortex. Second, psilocybin decreased the threat-induced modulation of top-down connectivity from the amygdala to primary visual cortex, speaking to a neural mechanism that might underlie putative shifts towards positive affect states after psilocybin administration. These findings may have important implications for the treatment of mood and anxiety disorders. PMID:26909323

The mixed serotonin receptor agonist psilocybin reduces threat-induced modulation of amygdala connectivity.

PubMed

Kraehenmann, Rainer; Schmidt, André; Friston, Karl; Preller, Katrin H; Seifritz, Erich; Vollenweider, Franz X

2016-01-01

Stimulation of serotonergic neurotransmission by psilocybin has been shown to shift emotional biases away from negative towards positive stimuli. We have recently shown that reduced amygdala activity during threat processing might underlie psilocybin's effect on emotional processing. However, it is still not known whether psilocybin modulates bottom-up or top-down connectivity within the visual-limbic-prefrontal network underlying threat processing. We therefore analyzed our previous fMRI data using dynamic causal modeling and used Bayesian model selection to infer how psilocybin modulated effective connectivity within the visual-limbic-prefrontal network during threat processing. First, both placebo and psilocybin data were best explained by a model in which threat affect modulated bidirectional connections between the primary visual cortex, amygdala, and lateral prefrontal cortex. Second, psilocybin decreased the threat-induced modulation of top-down connectivity from the amygdala to primary visual cortex, speaking to a neural mechanism that might underlie putative shifts towards positive affect states after psilocybin administration. These findings may have important implications for the treatment of mood and anxiety disorders.

Integration and continuity of Care in health care network models for frail older adults

PubMed Central

Veras, Renato Peixoto; Caldas, Célia Pereira; da Motta, Luciana Branco; de Lima, Kenio Costa; Siqueira, Ricardo Carreño; Rodrigues, Renata Teixeira da Silva Vendas; Santos, Luciana Maria Alves Martins; Guerra, Ana Carolina Lima Cavaletti

2014-01-01

A detailed review was conducted of the literature on models evaluating the effectiveness of integrated and coordinated care networks for the older population. The search made use of the following bibliographic databases: Pubmed, The Cochrane Library, LILACS, Web of Science, Scopus and SciELO. Twelve articles on five different models were included for discussion. Analysis of the literature showed that the services provided were based on primary care, including services within the home. Service users relied on the integration of primary and hospital care, day centers and in-home and social services. Care plans and case management were key elements in care continuity. This approach was shown to be effective in the studies, reducing the need for hospital care, which resulted in savings for the system. There was reduced prevalence of functional loss and improved satisfaction and quality of life on the part of service users and their families. The analysis reinforced the need for change in the approach to health care for older adults and the integration and coordination of services is an efficient way of initiating this change. PMID:24897058

Primary sex determination of placental mammals: a modelling study uncovers dynamical developmental constraints in the formation of Sertoli and granulosa cells.

PubMed

Sánchez, Lucas; Chaouiya, Claudine

2016-05-26

Primary sex determination in placental mammals is a very well studied developmental process. Here, we aim to investigate the currently established scenario and to assess its adequacy to fully recover the observed phenotypes, in the wild type and perturbed situations. Computational modelling allows clarifying network dynamics, elucidating crucial temporal constrains as well as interplay between core regulatory modules. Relying on a comprehensive revision of the literature, we define a logical model that integrates the current knowledge of the regulatory network controlling this developmental process. Our analysis indicates the necessity for some genes to operate at distinct functional thresholds and for specific developmental conditions to ensure the reproducibility of the sexual pathways followed by bi-potential gonads developing into either testes or ovaries. Our model thus allows studying the dynamics of wild type and mutant XX and XY gonads. Furthermore, the model analysis reveals that the gonad sexual fate results from the operation of two sub-networks associated respectively with an initiation and a maintenance phases. At the core of the process is the resolution of two connected feedback loops: the mutual inhibition of Sox9 and ß-catenin at the initiation phase, which in turn affects the mutual inhibition between Dmrt1 and Foxl2, at the maintenance phase. Three developmental signals related to the temporal activity of those sub-networks are required: a signal that determines Sry activation, marking the beginning of the initiation phase, and two further signals that define the transition from the initiation to the maintenance phases, by inhibiting the Wnt4 signalling pathway on the one hand, and by activating Foxl2 on the other hand. Our model reproduces a wide range of experimental data reported for the development of wild type and mutant gonads. It also provides a formal support to crucial aspects of the gonad sexual development and predicts gonadal phenotypes for mutations not tested yet.

Using Social Network Analysis to Investigate Positive EOL Communication.

PubMed

Xu, Jiayun; Yang, Rumei; Wilson, Andrew; Reblin, Maija; Clayton, Margaret F; Ellington, Lee

2018-04-30

End of life (EOL) communication is a complex process involving the whole family and multiple care providers. Applications of analysis techniques that account for communication beyond the patient and patient/provider, will improve clinical understanding of EOL communication. To introduce the use of social network analysis to EOL communication data, and to provide an example of applying social network analysis to home hospice interactions. We provide a description of social network analysis using social network analysis to model communication patterns during home hospice nursing visits. We describe three social network attributes (i.e. magnitude, directionality, and reciprocity) in the expression of positive emotion among hospice nurses, family caregivers, and hospice cancer patients. Differences in communication structure by primary family caregiver gender and across time were also examined. Magnitude (frequency) in the expression of positive emotion occurred most often between nurses and caregivers or nurses and patients. Female caregivers directed more positive emotion to nurses, and nurses directed more positive emotion to other family caregivers when the primary family caregiver was male. Reciprocity (mutuality) in positive emotion declined towards day of death, but increased on day of actual patient death. There was variation in reciprocity by the type of positive emotion expressed. Our example demonstrates that social network analysis can be used to better understand the process of EOL communication. Social network analysis can be expanded to other areas of EOL research, such as EOL decision-making and health care teamwork. Copyright © 2018. Published by Elsevier Inc.

Recent Results From the NOAA/ESRL GMD Tall Tower Network

NASA Astrophysics Data System (ADS)

Andrews, A. E.; Tans, P. P.; Peters, W.; Hirsch, A.; Sweeney, C.; Petron, G.; Kofler, J.; Zhao, C.; Masarie, K.; Wofsy, S. C.; Matross, D. M.; Mahadevan, P.; Longo, M.; Gerbig, C.; Lin, J. C.

2006-12-01

We will present a summary of new results from NOAA Earth System Research Laboratory`s Tall Tower greenhouse gas monitoring network. The tower network is operated by the Global Monitoring Division, which also maintains the global Cooperative Air Sampling network and a network of aircraft profiling sites over North America. Tall tower CO2 mixing ratio measurements are sensitive to upwind fluxes over scales of hundreds of kilometers, and the primary objective of the tower network is to obtain regionally representative carbon flux estimates for the North American continent. Mixing ratios of CO2 and CO are measured semi-continuously at the towers, and the KWKT-TV tower site near Moody, TX has recently also been equipped with sensors to measure radon and O3. Daily flask samples are collected at the KWKT tower and analyzed for CO2, CO, CH4, SF6, N2O, H2, stable isotopes of CO2 and CH4, COS, and a variety of halocarbon and hydrocarbon species. Daily flask sampling will be implemented at all tower sites within the next few years. We have used the Stochastic Time Inverted Lagrangian Transport (STILT) model to investigate upwind influences on the tower observations. CO measurements provide an indicator of polluted air masses, and we will present a summary of the frequency and origin of pollution events observed at the towers. We will present an analysis of the primary factors contributing to observed CO2 variability along with average seasonal and diurnal cycles of CO2 at the tower sites. Tower measurements are being used to evaluate atmospheric transport models in the context of the Transcom Continuous experiment and are an important constraint for CO2 data assimilation systems that produce regional to global carbon flux estimates with up to weekly resolution.

A coupled upland-erosion and instream hydrodynamic-sediment transport model for evaluating sediment transport in forested watersheds

Treesearch

W. J. Conroy; R. H. Hotchkiss; W. J. Elliot

2006-01-01

This article describes a prototype modeling system for assessing forest management-related erosion at its source and predicting sediment transport from hillslopes to stream channels and through channel networks to a watershed outlet. We demonstrate that it is possible to develop a land management tool capable of accurately assessing the primary impacts of...

Cognitive components of a mathematical processing network in 9-year-old children.

PubMed

Szűcs, Dénes; Devine, Amy; Soltesz, Fruzsina; Nobes, Alison; Gabriel, Florence

2014-07-01

We determined how various cognitive abilities, including several measures of a proposed domain-specific number sense, relate to mathematical competence in nearly 100 9-year-old children with normal reading skill. Results are consistent with an extended number processing network and suggest that important processing nodes of this network are phonological processing, verbal knowledge, visuo-spatial short-term and working memory, spatial ability and general executive functioning. The model was highly specific to predicting arithmetic performance. There were no strong relations between mathematical achievement and verbal short-term and working memory, sustained attention, response inhibition, finger knowledge and symbolic number comparison performance. Non-verbal intelligence measures were also non-significant predictors when added to our model. Number sense variables were non-significant predictors in the model and they were also non-significant predictors when entered into regression analysis with only a single visuo-spatial WM measure. Number sense variables were predicted by sustained attention. Results support a network theory of mathematical competence in primary school children and falsify the importance of a proposed modular 'number sense'. We suggest an 'executive memory function centric' model of mathematical processing. Mapping a complex processing network requires that studies consider the complex predictor space of mathematics rather than just focusing on a single or a few explanatory factors.

Cognitive components of a mathematical processing network in 9-year-old children

PubMed Central

Szűcs, Dénes; Devine, Amy; Soltesz, Fruzsina; Nobes, Alison; Gabriel, Florence

2014-01-01

We determined how various cognitive abilities, including several measures of a proposed domain-specific number sense, relate to mathematical competence in nearly 100 9-year-old children with normal reading skill. Results are consistent with an extended number processing network and suggest that important processing nodes of this network are phonological processing, verbal knowledge, visuo-spatial short-term and working memory, spatial ability and general executive functioning. The model was highly specific to predicting arithmetic performance. There were no strong relations between mathematical achievement and verbal short-term and working memory, sustained attention, response inhibition, finger knowledge and symbolic number comparison performance. Non-verbal intelligence measures were also non-significant predictors when added to our model. Number sense variables were non-significant predictors in the model and they were also non-significant predictors when entered into regression analysis with only a single visuo-spatial WM measure. Number sense variables were predicted by sustained attention. Results support a network theory of mathematical competence in primary school children and falsify the importance of a proposed modular ‘number sense’. We suggest an ‘executive memory function centric’ model of mathematical processing. Mapping a complex processing network requires that studies consider the complex predictor space of mathematics rather than just focusing on a single or a few explanatory factors. PMID:25089322

The role of propriospinal neuronal network in transmitting the alternating muscular activities of flexor and extensor in parkinsonian tremor.

PubMed

Hao, M; He, X; Lan, N

2012-01-01

It has been shown that normal cyclic movement of human arm and resting limb tremor in Parkinson's disease (PD) are associated with the oscillatory neuronal activities in different cerebral networks, which are transmitted to the antagonistic muscles via the same spinal pathway. There are mono-synaptic and multi-synaptic corticospinal pathways for conveying motor commands. This study investigates the plausible role of propriospinal neuronal (PN) network in the C3-C4 levels in multi-synaptic transmission of cortical commands for oscillatory movements. A PN network model is constructed based on known neurophysiological connections, and is hypothesized to achieve the conversion of cortical oscillations into alternating antagonistic muscle bursts. Simulations performed with a virtual arm (VA) model indicate that without the PN network, the alternating bursts of antagonistic muscle EMG could not be reliably generated, whereas with the PN network, the alternating pattern of bursts were naturally displayed in the three pairs of antagonist muscles. Thus, it is suggested that oscillations in the primary motor cortex (M1) of single and double tremor frequencies are processed at the PN network to compute the alternating burst pattern in the flexor and extensor muscles.

Altered resting-state effective connectivity of fronto-parietal motor control systems on the primary motor network following stroke

PubMed Central

Inman, Cory S.; James, G. Andrew; Hamann, Stephan; Rajendra, Justin K.; Pagnoni, Giuseppe; Butler, Andrew J.

2011-01-01

Previous brain imaging work suggests that stroke alters the effective connectivity (the influence neural regions exert upon each other) of motor execution networks. The present study examines the intrinsic effective connectivity of top-down motor control in stroke survivors (n=13) relative to healthy participants (n=12). Stroke survivors exhibited significant deficits in motor function, as assessed by the Fugl-Meyer Motor Assessment. We used structural equation modeling (SEM) of resting-state fMRI data to investigate the relationship between motor deficits and the intrinsic effective connectivity between brain regions involved in motor control and motor execution. An exploratory adaptation of SEM determined the optimal model of motor execution effective connectivity in healthy participants, and confirmatory SEM assessed stroke survivors’ fit to that model. We observed alterations in spontaneous resting-state effective connectivity from fronto-parietal guidance systems to the motor network in stroke survivors. More specifically, diminished connectivity was found in connections from the superior parietal cortex to primary motor cortex and supplementary motor cortex. Furthermore, the paths demonstrated large individual variance in stroke survivors but less variance in healthy participants. These findings suggest that characterizing the deficits in resting-state connectivity of top-down processes in stroke survivors may help optimize cognitive and physical rehabilitation therapies by individually targeting specific neural pathway. PMID:21839174

Understanding the influence of all nodes in a network

PubMed Central

Lawyer, Glenn

2015-01-01

Centrality measures such as the degree, k-shell, or eigenvalue centrality can identify a network's most influential nodes, but are rarely usefully accurate in quantifying the spreading power of the vast majority of nodes which are not highly influential. The spreading power of all network nodes is better explained by considering, from a continuous-time epidemiological perspective, the distribution of the force of infection each node generates. The resulting metric, the expected force, accurately quantifies node spreading power under all primary epidemiological models across a wide range of archetypical human contact networks. When node power is low, influence is a function of neighbor degree. As power increases, a node's own degree becomes more important. The strength of this relationship is modulated by network structure, being more pronounced in narrow, dense networks typical of social networking and weakening in broader, looser association networks such as the Internet. The expected force can be computed independently for individual nodes, making it applicable for networks whose adjacency matrix is dynamic, not well specified, or overwhelmingly large. PMID:25727453

Studying the Impact of Distributed Solar PV on Power Systems using Integrated Transmission and Distribution Models: Preprint

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

Jain, Himanshu; Palmintier, Bryan S; Krad, Ibrahim

This paper presents the results of a distributed solar PV impact assessment study that was performed using a synthetic integrated transmission (T) and distribution (D) model. The primary objective of the study was to present a new approach for distributed solar PV impact assessment, where along with detailed models of transmission and distribution networks, consumer loads were modeled using the physics of end-use equipment, and distributed solar PV was geographically dispersed and connected to the secondary distribution networks. The highlights of the study results were (i) increase in the Area Control Error (ACE) at high penetration levels of distributed solarmore » PV; and (ii) differences in distribution voltages profiles and voltage regulator operations between integrated T&D and distribution only simulations.« less

Computational Model of Primary Visual Cortex Combining Visual Attention for Action Recognition

PubMed Central

Shu, Na; Gao, Zhiyong; Chen, Xiangan; Liu, Haihua

2015-01-01

Humans can easily understand other people’s actions through visual systems, while computers cannot. Therefore, a new bio-inspired computational model is proposed in this paper aiming for automatic action recognition. The model focuses on dynamic properties of neurons and neural networks in the primary visual cortex (V1), and simulates the procedure of information processing in V1, which consists of visual perception, visual attention and representation of human action. In our model, a family of the three-dimensional spatial-temporal correlative Gabor filters is used to model the dynamic properties of the classical receptive field of V1 simple cell tuned to different speeds and orientations in time for detection of spatiotemporal information from video sequences. Based on the inhibitory effect of stimuli outside the classical receptive field caused by lateral connections of spiking neuron networks in V1, we propose surround suppressive operator to further process spatiotemporal information. Visual attention model based on perceptual grouping is integrated into our model to filter and group different regions. Moreover, in order to represent the human action, we consider the characteristic of the neural code: mean motion map based on analysis of spike trains generated by spiking neurons. The experimental evaluation on some publicly available action datasets and comparison with the state-of-the-art approaches demonstrate the superior performance of the proposed model. PMID:26132270

Implementation of a health data-sharing infrastructure across diverse primary care organizations.

PubMed

Cole, Allison M; Stephens, Kari A; Keppel, Gina A; Lin, Ching-Ping; Baldwin, Laura-Mae

2014-01-01

Practice-based research networks bring together academic researchers and primary care clinicians to conduct research that improves health outcomes in real-world settings. The Washington, Wyoming, Alaska, Montana, and Idaho region Practice and Research Network implemented a health data-sharing infrastructure across 9 clinics in 3 primary care organizations. Following implementation, we identified challenges and solutions. Challenges included working with diverse primary care organizations, adoption of health information data-sharing technology in a rapidly changing local and national landscape, and limited resources for implementation. Overarching solutions included working with a multidisciplinary academic implementation team, maintaining flexibility, and starting with an established network for primary care organizations. Approaches outlined may generalize to similar initiatives and facilitate adoption of health data sharing in other practice-based research networks.

Implementation of a Health Data-Sharing Infrastructure Across Diverse Primary Care Organizations

PubMed Central

Cole, Allison M.; Stephens, Kari A.; Keppel, Gina A.; Lin, Ching-Ping; Baldwin, Laura-Mae

2014-01-01

Practice-based research networks bring together academic researchers and primary care clinicians to conduct research that improves health outcomes in real-world settings. The Washington, Wyoming, Alaska, Montana, and Idaho region Practice and Research Network implemented a health data-sharing infrastructure across 9 clinics in 3 primary care organizations. Following implementation, we identified challenges and solutions. Challenges included working with diverse primary care organizations, adoption of health information data-sharing technology in a rapidly changing local and national landscape, and limited resources for implementation. Overarching solutions included working with a multidisciplinary academic implementation team, maintaining flexibility, and starting with an established network for primary care organizations. Approaches outlined may generalize to similar initiatives and facilitate adoption of health data sharing in other practice-based research networks. PMID:24594564

Power plant fault detection using artificial neural network

NASA Astrophysics Data System (ADS)

Thanakodi, Suresh; Nazar, Nazatul Shiema Moh; Joini, Nur Fazriana; Hidzir, Hidzrin Dayana Mohd; Awira, Mohammad Zulfikar Khairul

2018-02-01

The fault that commonly occurs in power plants is due to various factors that affect the system outage. There are many types of faults in power plants such as single line to ground fault, double line to ground fault, and line to line fault. The primary aim of this paper is to diagnose the fault in 14 buses power plants by using an Artificial Neural Network (ANN). The Multilayered Perceptron Network (MLP) that detection trained utilized the offline training methods such as Gradient Descent Backpropagation (GDBP), Levenberg-Marquardt (LM), and Bayesian Regularization (BR). The best method is used to build the Graphical User Interface (GUI). The modelling of 14 buses power plant, network training, and GUI used the MATLAB software.

A Spiking Neurocomputational Model of High-Frequency Oscillatory Brain Responses to Words and Pseudowords

PubMed Central

Garagnani, Max; Lucchese, Guglielmo; Tomasello, Rosario; Wennekers, Thomas; Pulvermüller, Friedemann

2017-01-01

Experimental evidence indicates that neurophysiological responses to well-known meaningful sensory items and symbols (such as familiar objects, faces, or words) differ from those to matched but novel and senseless materials (unknown objects, scrambled faces, and pseudowords). Spectral responses in the high beta- and gamma-band have been observed to be generally stronger to familiar stimuli than to unfamiliar ones. These differences have been hypothesized to be caused by the activation of distributed neuronal circuits or cell assemblies, which act as long-term memory traces for learned familiar items only. Here, we simulated word learning using a biologically constrained neurocomputational model of the left-hemispheric cortical areas known to be relevant for language and conceptual processing. The 12-area spiking neural-network architecture implemented replicates physiological and connectivity features of primary, secondary, and higher-association cortices in the frontal, temporal, and occipital lobes of the human brain. We simulated elementary aspects of word learning in it, focussing specifically on semantic grounding in action and perception. As a result of spike-driven Hebbian synaptic plasticity mechanisms, distributed, stimulus-specific cell-assembly (CA) circuits spontaneously emerged in the network. After training, presentation of one of the learned “word” forms to the model correlate of primary auditory cortex induced periodic bursts of activity within the corresponding CA, leading to oscillatory phenomena in the entire network and spontaneous across-area neural synchronization. Crucially, Morlet wavelet analysis of the network's responses recorded during presentation of learned meaningful “word” and novel, senseless “pseudoword” patterns revealed stronger induced spectral power in the gamma-band for the former than the latter, closely mirroring differences found in neurophysiological data. Furthermore, coherence analysis of the simulated responses uncovered dissociated category specific patterns of synchronous oscillations in distant cortical areas, including indirectly connected primary sensorimotor areas. Bridging the gap between cellular-level mechanisms, neuronal-population behavior, and cognitive function, the present model constitutes the first spiking, neurobiologically, and anatomically realistic model able to explain high-frequency oscillatory phenomena indexing language processing on the basis of dynamics and competitive interactions of distributed cell-assembly circuits which emerge in the brain as a result of Hebbian learning and sensorimotor experience. PMID:28149276

Commissioning and equity in primary care in Australia: Views from Primary Health Networks.

PubMed

Henderson, Julie; Javanparast, Sara; MacKean, Tamara; Freeman, Toby; Baum, Fran; Ziersch, Anna

2018-01-01

This paper reports findings from 55 stakeholder interviews undertaken in six Primary Health Networks (PHNs) in Australia as part of a study of the impact of population health planning in regional primary health organisations on service access and equity. Primary healthcare planning is currently undertaken by PHNs which were established in 2015 as commissioning organisations. This was a departure from the role of Medicare Locals, the previous regional primary health organisations which frequently provided services. This paper addresses perceptions of 23 senior staff, 11 board members and 21 members of clinical and community advisory councils or health priority groups from six case study PHNs on the impact of commissioning on equity. Participants view the collection of population health data as facilitating service access through redistributing services on the basis of need and through bringing objectivity to decision-making about services. Conversely, participants question the impact of the political and geographical context and population profile on capacity to improve service access and equity through service commissioning. Service delivery was seen as fragmented, the model is at odds with the manner in which Aboriginal Community Controlled Health Organisations (ACCHOs) operate and rural regions lack services to commission. As a consequence, reliance upon commissioning of services may not be appropriate for the Australian primary healthcare context. © 2017 John Wiley & Sons Ltd.

Control of polymer network topology in semi-batch systems

NASA Astrophysics Data System (ADS)

Wang, Rui; Olsen, Bradley; Johnson, Jeremiah

Polymer networks invariably possess topological defects: loops of different orders. Since small loops (primary loops and secondary loops) both lower the modulus of network and lead to stress concentration that causes material failure at low deformation, it is desirable to greatly reduce the loop fraction. We have shown that achieving loop fraction close to zero is extremely difficult in the batch process due to the slow decay of loop fraction with the polymer concentration and chain length. Here, we develop a modified kinetic graph theory that can model network formation reactions in semi-batch systems. We demonstrate that the loop fraction is not sensitive to the feeding policy if the reaction volume maintains constant during the network formation. However, if we initially put concentrated solution of small junction molecules in the reactor and continuously adding polymer solutions, the fractions of both primary loop and higher-order loops will be significantly reduced. There is a limiting value (nonzero) of loop fraction that can be achieved in the semi-batch system in condition of extremely slow feeding rate. This minimum loop fraction only depends on a single dimensionless variable, the product of concentration and with single chain pervaded volume, and defines an operating zone in which the loop fraction of polymer networks can be controlled through adjusting the feeding rate of the semi-batch process.

Code System to Calculate Tornado-Induced Flow Material Transport.

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

ANDRAE, R. W.

1999-11-18

Version: 00 TORAC models tornado-induced flows, pressures, and material transport within structures. Its use is directed toward nuclear fuel cycle facilities and their primary release pathway, the ventilation system. However, it is applicable to other structures and can model other airflow pathways within a facility. In a nuclear facility, this network system could include process cells, canyons, laboratory offices, corridors, and offgas systems. TORAC predicts flow through a network system that also includes ventilation system components such as filters, dampers, ducts, and blowers. These ventilation system components are connected to the rooms and corridors of the facility to form amore » complete network for moving air through the structure and, perhaps, maintaining pressure levels in certain areas. The material transport capability in TORAC is very basic and includes convection, depletion, entrainment, and filtration of material.« less

Fuzzy Logic Based Anomaly Detection for Embedded Network Security Cyber Sensor

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

Ondrej Linda; Todd Vollmer; Jason Wright

Resiliency and security in critical infrastructure control systems in the modern world of cyber terrorism constitute a relevant concern. Developing a network security system specifically tailored to the requirements of such critical assets is of a primary importance. This paper proposes a novel learning algorithm for anomaly based network security cyber sensor together with its hardware implementation. The presented learning algorithm constructs a fuzzy logic rule based model of normal network behavior. Individual fuzzy rules are extracted directly from the stream of incoming packets using an online clustering algorithm. This learning algorithm was specifically developed to comply with the constrainedmore » computational requirements of low-cost embedded network security cyber sensors. The performance of the system was evaluated on a set of network data recorded from an experimental test-bed mimicking the environment of a critical infrastructure control system.« less

Results from a model-independent method of monitoring a geodetic network for patterns of transient deformation

NASA Technical Reports Server (NTRS)

Hurst, Kenneth; Granat, Robert

2005-01-01

We have implmented two multi-station detectors for transient crustal deformation within the Southern California Integrated GPS (SCGIN). One the the primary goals of SCIGN is to detect transient deformation associated with the earthquake cycle in Southern California.

A human factors systems approach to understanding team-based primary care: a qualitative analysis.

PubMed

Mundt, Marlon P; Swedlund, Matthew P

2016-12-01

Research shows that high-functioning teams improve patient outcomes in primary care. However, there is no consensus on a conceptual model of team-based primary care that can be used to guide measurement and performance evaluation of teams. To qualitatively understand whether the Systems Engineering Initiative for Patient Safety (SEIPS) model could serve as a framework for creating and evaluating team-based primary care. We evaluated qualitative interview data from 19 clinicians and staff members from 6 primary care clinics associated with a large Midwestern university. All health care clinicians and staff in the study clinics completed a survey of their communication connections to team members. Social network analysis identified key informants for interviews by selecting the respondents with the highest frequency of communication ties as reported by their teammates. Semi-structured interviews focused on communication patterns, team climate and teamwork. Themes derived from the interviews lent support to the SEIPS model components, such as the work system (Team, Tools and Technology, Physical Environment, Tasks and Organization), team processes and team outcomes. Our qualitative data support the SEIPS model as a promising conceptual framework for creating and evaluating primary care teams. Future studies of team-based care may benefit from using the SEIPS model to shift clinical practice to high functioning team-based primary care. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

A network-based approach for semi-quantitative knowledge mining and its application to yield variability

NASA Astrophysics Data System (ADS)

Schauberger, Bernhard; Rolinski, Susanne; Müller, Christoph

2016-12-01

Variability of crop yields is detrimental for food security. Under climate change its amplitude is likely to increase, thus it is essential to understand the underlying causes and mechanisms. Crop models are the primary tool to project future changes in crop yields under climate change. A systematic overview of drivers and mechanisms of crop yield variability (YV) can thus inform crop model development and facilitate improved understanding of climate change impacts on crop yields. Yet there is a vast body of literature on crop physiology and YV, which makes a prioritization of mechanisms for implementation in models challenging. Therefore this paper takes on a novel approach to systematically mine and organize existing knowledge from the literature. The aim is to identify important mechanisms lacking in models, which can help to set priorities in model improvement. We structure knowledge from the literature in a semi-quantitative network. This network consists of complex interactions between growing conditions, plant physiology and crop yield. We utilize the resulting network structure to assign relative importance to causes of YV and related plant physiological processes. As expected, our findings confirm existing knowledge, in particular on the dominant role of temperature and precipitation, but also highlight other important drivers of YV. More importantly, our method allows for identifying the relevant physiological processes that transmit variability in growing conditions to variability in yield. We can identify explicit targets for the improvement of crop models. The network can additionally guide model development by outlining complex interactions between processes and by easily retrieving quantitative information for each of the 350 interactions. We show the validity of our network method as a structured, consistent and scalable dictionary of literature. The method can easily be applied to many other research fields.

Elasticity and photoelasticity relationships for polyethylene terephthalate fiber networks by molecular simulation

NASA Astrophysics Data System (ADS)

Nayak, Kapileswar; Das, Sushanta; Nanavati, Hemant

2008-01-01

We present a framework for the development of elasticity and photoelasticity relationships for polyethylene terephthalate fiber networks, incorporating aspects of the primary molecular structure. Semicrystalline polymeric fiber networks are modeled as sequentially arranged crystalline and amorphous regions. Rotational isomeric states-Monte Carlo simulations of amorphous chains of up to 360 bonds (degree of polymerization, DP =60), confined between and bridging infinite impenetrable crystalline walls, have been characterized by Ω, the probability density of the intercrystal separation h, and Δβ, the polarizability anisotropy. lnΩ and Δβ have been modeled as functions of h, yielding the chain deformation relationships. The development has been extended to the fiber network to yield the photoelasticity relationships. We execute our framework by fitting to experimental stress-elongation data and employing the single fitted parameter to directly predict the birefringence-elongation behavior, without any further fitting. Incorporating the effect of strain-induced crystallization into the framework makes it physically more meaningful and yields accurate predictions of the birefringence-elongation behavior.

Project ECHO: A Telementoring Network Model for Continuing Professional Development.

PubMed

Arora, Sanjeev; Kalishman, Summers G; Thornton, Karla A; Komaromy, Miriam S; Katzman, Joanna G; Struminger, Bruce B; Rayburn, William F

2017-01-01

A major challenge with current systems of CME is the inability to translate the explosive growth in health care knowledge into daily practice. Project ECHO (Extension for Community Healthcare Outcomes) is a telementoring network designed for continuing professional development (CPD) and improving patient outcomes. The purpose of this article was to describe how the model has complied with recommendations from several authoritative reports about redesigning and enhancing CPD. This model links primary care clinicians through a knowledge network with an interprofessional team of specialists from an academic medical center who provide telementoring and ongoing education enabling community clinicians to treat patients with a variety of complex conditions. Knowledge and skills are shared during weekly condition-specific videoconferences. The model exemplifies learning as described in the seven levels of CPD by Moore (participation, satisfaction, learning, competence, performance, patient, and community health). The model is also aligned with recommendations from four national reports intended to redesign knowledge transfer in improving health care. Efforts in learning sessions focus on information that is relevant to practice, focus on evidence, education methodology, tailoring of recommendations to individual needs and community resources, and interprofessionalism. Project ECHO serves as a telementoring network model of CPD that aligns with current best practice recommendations for CME. This transformative initiative has the potential to serve as a leading model for larger scale CPD, nationally and globally, to enhance access to care, improve quality, and reduce cost.

Comprehensive heat transfer correlation for water/ethylene glycol-based graphene (nitrogen-doped graphene) nanofluids derived by artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS)

NASA Astrophysics Data System (ADS)

Savari, Maryam; Moghaddam, Amin Hedayati; Amiri, Ahmad; Shanbedi, Mehdi; Ayub, Mohamad Nizam Bin

2017-10-01

Herein, artificial neural network and adaptive neuro-fuzzy inference system are employed for modeling the effects of important parameters on heat transfer and fluid flow characteristics of a car radiator and followed by comparing with those of the experimental results for testing data. To this end, two novel nanofluids (water/ethylene glycol-based graphene and nitrogen-doped graphene nanofluids) were experimentally synthesized. Then, Nusselt number was modeled with respect to the variation of inlet temperature, Reynolds number, Prandtl number and concentration, which were defined as the input (design) variables. To reach reliable results, we divided these data into train and test sections to accomplish modeling. Artificial networks were instructed by a major part of experimental data. The other part of primary data which had been considered for testing the appropriateness of the models was entered into artificial network models. Finally, predictad results were compared to the experimental data to evaluate validity. Confronted with high-level of validity confirmed that the proposed modeling procedure by BPNN with one hidden layer and five neurons is efficient and it can be expanded for all water/ethylene glycol-based carbon nanostructures nanofluids. Finally, we expanded our data collection from model and could present a fundamental correlation for calculating Nusselt number of the water/ethylene glycol-based nanofluids including graphene or nitrogen-doped graphene.

Burstiness and tie activation strategies in time-varying social networks

NASA Astrophysics Data System (ADS)

Ubaldi, Enrico; Vezzani, Alessandro; Karsai, Márton; Perra, Nicola; Burioni, Raffaella

2017-04-01

The recent developments in the field of social networks shifted the focus from static to dynamical representations, calling for new methods for their analysis and modelling. Observations in real social systems identified two main mechanisms that play a primary role in networks’ evolution and influence ongoing spreading processes: the strategies individuals adopt when selecting between new or old social ties, and the bursty nature of the social activity setting the pace of these choices. We introduce a time-varying network model accounting both for ties selection and burstiness and we analytically study its phase diagram. The interplay of the two effects is non trivial and, interestingly, the effects of burstiness might be suppressed in regimes where individuals exhibit a strong preference towards previously activated ties. The results are tested against numerical simulations and compared with two empirical datasets with very good agreement. Consequently, the framework provides a principled method to classify the temporal features of real networks, and thus yields new insights to elucidate the effects of social dynamics on spreading processes.

Networks In ACA Marketplaces Are Narrower For Mental Health Care Than For Primary Care.

PubMed

Zhu, Jane M; Zhang, Yuehan; Polsky, Daniel

2017-09-01

There is increasing concern about the extent to which narrow-network plans, generally defined as those including fewer than 25 percent of providers in a given health insurance market, affect consumers' choice of and access to specialty providers-particularly in mental health care. Using data for 2016 from 531 unique provider networks in the Affordable Care Act Marketplaces, we evaluated how network size and the percentage of providers who participate in any network differ between mental health care providers and a control group of primary care providers. Compared to primary care networks, participation in mental health networks was low, with only 42.7 percent of psychiatrists and 19.3 percent of nonphysician mental health care providers participating in any network. On average, plan networks included 24.3 percent of all primary care providers and 11.3 percent of all mental health care providers practicing in a given state-level market. These findings raise important questions about provider-side barriers to meeting the goal of mental health parity regulations: that insurers cover mental health services on a par with general medical and surgical services. Concerted efforts to increase network participation by mental health care providers, along with greater regulatory attention to network size and composition, could improve consumer choice and complement efforts to achieve mental health parity. Project HOPE—The People-to-People Health Foundation, Inc.

Models for IP/MPLS routing performance: convergence, fast reroute, and QoS impact

NASA Astrophysics Data System (ADS)

Choudhury, Gagan L.

2004-09-01

We show how to model the black-holing and looping of traffic during an Interior Gateway Protocol (IGP) convergence event at an IP network and how to significantly improve both the convergence time and packet loss duration through IGP parameter tuning and algorithmic improvement. We also explore some congestion avoidance and congestion control algorithms that can significantly improve stability of networks in the face of occasional massive control message storms. Specifically we show the positive impacts of prioritizing Hello and Acknowledgement packets and slowing down LSA generation and retransmission generation on detecting congestion in the network. For some types of video, voice signaling and circuit emulation applications it is necessary to reduce traffic loss durations following a convergence event to below 100 ms and we explore that using Fast Reroute algorithms based on Multiprotocol Label Switching Traffic Engineering (MPLS-TE) that effectively bypasses IGP convergence. We explore the scalability of primary and backup MPLS-TE tunnels where MPLS-TE domain is in the backbone-only or edge-to-edge. We also show how much extra backbone resource is needed to support Fast Reroute and how can that be reduced by taking advantage of Constrained Shortest Path (CSPF) routing of MPLS-TE and by reserving less than 100% of primary tunnel bandwidth during Fast Reroute.

Unlocking Proteomic Heterogeneity in Complex Diseases through Visual Analytics

PubMed Central

Bhavnani, Suresh K.; Dang, Bryant; Bellala, Gowtham; Divekar, Rohit; Visweswaran, Shyam; Brasier, Allan; Kurosky, Alex

2015-01-01

Despite years of preclinical development, biological interventions designed to treat complex diseases like asthma often fail in phase III clinical trials. These failures suggest that current methods to analyze biomedical data might be missing critical aspects of biological complexity such as the assumption that cases and controls come from homogeneous distributions. Here we discuss why and how methods from the rapidly evolving field of visual analytics can help translational teams (consisting of biologists, clinicians, and bioinformaticians) to address the challenge of modeling and inferring heterogeneity in the proteomic and phenotypic profiles of patients with complex diseases. Because a primary goal of visual analytics is to amplify the cognitive capacities of humans for detecting patterns in complex data, we begin with an overview of the cognitive foundations for the field of visual analytics. Next, we organize the primary ways in which a specific form of visual analytics called networks have been used to model and infer biological mechanisms, which help to identify the properties of networks that are particularly useful for the discovery and analysis of proteomic heterogeneity in complex diseases. We describe one such approach called subject-protein networks, and demonstrate its application on two proteomic datasets. This demonstration provides insights to help translational teams overcome theoretical, practical, and pedagogical hurdles for the widespread use of subject-protein networks for analyzing molecular heterogeneities, with the translational goal of designing biomarker-based clinical trials, and accelerating the development of personalized approaches to medicine. PMID:25684269

Primary care research conducted in networks: getting down to business.

PubMed

Mold, James W

2012-01-01

This seventh annual practice-based research theme issue of the Journal of the American Board of Family Medicine highlights primary care research conducted in practice-based research networks (PBRNs). The issue includes discussion of (1) theoretical and methodological research, (2) health care research (studies addressing primary care processes), (3) clinical research (studies addressing the impact of primary care on patients), and (4) health systems research (studies of health system issues impacting primary care including the quality improvement process). We had a noticeable increase in submissions from PBRN collaborations, that is, studies that involved multiple networks. As PBRNs cooperate to recruit larger and more diverse patient samples, greater generalizability and applicability of findings lead to improved primary care processes.

Artificial neural network models: A decision support tool for enhancing seedling selection in sugarcane

USDA-ARS?s Scientific Manuscript database

Currently, sugarcane selection begins at the seedling stage with visual selection for cane yield and other yield-related traits. Although subjective and inefficient, visual selection remains the primary method for selection. Visual selection is inefficient because of the confounding effect of genoty...

Thermal and Fluid Modeling of the CRYogenic Orbital TEstbed (CRYOTE) Ground Test Article (GTA)

NASA Technical Reports Server (NTRS)

Piryk, David; Schallhorn, Paul; Walls, Laurie; Stopnitzky, Benny; Rhys, Noah; Wollen, Mark

2012-01-01

The purpose of this study was to anchor thermal and fluid system models to data acquired from a ground test article (GTA) for the CRYogenic Orbital TEstbed - CRYOTE. To accomplish this analysis, it was broken into four primary tasks. These included model development, pre-test predictions, testing support at Marshall Space Flight Center (MSFC} and post-test correlations. Information from MSFC facilitated the task of refining and correlating the initial models. The primary goal of the modeling/testing/correlating efforts was to characterize heat loads throughout the ground test article. Significant factors impacting the heat loads included radiative environments, multi-layer insulation (MLI) performance, tank fill levels, tank pressures, and even contact conductance coefficients. This paper demonstrates how analytical thermal/fluid networks were established, and it includes supporting rationale for specific thermal responses seen during testing.

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

NASA Astrophysics Data System (ADS)

Kuvychko, Igor

2001-10-01

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

Integrated Regulatory and Metabolic Networks of the Marine Diatom Phaeodactylum tricornutum Predict the Response to Rising CO 2 Levels

DOE PAGES

Levering, Jennifer; Dupont, Christopher L.; Allen, Andrew E.; ...

2017-02-14

Diatoms are eukaryotic microalgae that are responsible for up to 40% of the ocean’s primary productivity. How diatoms respond to environmental perturbations such as elevated carbon concentrations in the atmosphere is currently poorly understood. We developed a transcriptional regulatory network based on various transcriptome sequencing expression libraries for different environmental responses to gain insight into the marine diatom’s metabolic and regulatory interactions and provide a comprehensive framework of responses to increasing atmospheric carbon levels. This transcriptional regulatory network was integrated with a recently published genome-scale metabolic model of Phaeodactylum tricornutum to explore the connectivity of the regulatory network and sharedmore » metabolites. The integrated regulatory and metabolic model revealed highly connected modules within carbon and nitrogen metabolism. P. tricornutum’s response to rising carbon levels was analyzed by using the recent genome-scale metabolic model with cross comparison to experimental manipulations of carbon dioxide. Using a systems biology approach, we studied the response of the marine diatom Phaeodactylum tricornutum to changing atmospheric carbon concentrations on an ocean-wide scale. By integrating an available genome-scale metabolic model and a newly developed transcriptional regulatory network inferred from transcriptome sequencing expression data, we demonstrate that carbon metabolism and nitrogen metabolism are strongly connected and the genes involved are coregulated in this model diatom. These tight regulatory constraints could play a major role during the adaptation of P. tricornutum to increasing carbon levels. The transcriptional regulatory network developed can be further used to study the effects of different environmental perturbations on P. tricornutum’s metabolism.« less

Integrated Regulatory and Metabolic Networks of the Marine Diatom Phaeodactylum tricornutum Predict the Response to Rising CO 2 Levels

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

Levering, Jennifer; Dupont, Christopher L.; Allen, Andrew E.

Diatoms are eukaryotic microalgae that are responsible for up to 40% of the ocean’s primary productivity. How diatoms respond to environmental perturbations such as elevated carbon concentrations in the atmosphere is currently poorly understood. We developed a transcriptional regulatory network based on various transcriptome sequencing expression libraries for different environmental responses to gain insight into the marine diatom’s metabolic and regulatory interactions and provide a comprehensive framework of responses to increasing atmospheric carbon levels. This transcriptional regulatory network was integrated with a recently published genome-scale metabolic model of Phaeodactylum tricornutum to explore the connectivity of the regulatory network and sharedmore » metabolites. The integrated regulatory and metabolic model revealed highly connected modules within carbon and nitrogen metabolism. P. tricornutum’s response to rising carbon levels was analyzed by using the recent genome-scale metabolic model with cross comparison to experimental manipulations of carbon dioxide. Using a systems biology approach, we studied the response of the marine diatom Phaeodactylum tricornutum to changing atmospheric carbon concentrations on an ocean-wide scale. By integrating an available genome-scale metabolic model and a newly developed transcriptional regulatory network inferred from transcriptome sequencing expression data, we demonstrate that carbon metabolism and nitrogen metabolism are strongly connected and the genes involved are coregulated in this model diatom. These tight regulatory constraints could play a major role during the adaptation of P. tricornutum to increasing carbon levels. The transcriptional regulatory network developed can be further used to study the effects of different environmental perturbations on P. tricornutum’s metabolism.« less

Primary Respiratory Chain Disease Causes Tissue-Specific Dysregulation of the Global Transcriptome and Nutrient-Sensing Signaling Network

PubMed Central

Zhang, Zhe; Tsukikawa, Mai; Peng, Min; Polyak, Erzsebet; Nakamaru-Ogiso, Eiko; Ostrovsky, Julian; McCormack, Shana; Place, Emily; Clarke, Colleen; Reiner, Gail; McCormick, Elizabeth; Rappaport, Eric; Haas, Richard; Baur, Joseph A.; Falk, Marni J.

2013-01-01

Primary mitochondrial respiratory chain (RC) diseases are heterogeneous in etiology and manifestations but collectively impair cellular energy metabolism. Mechanism(s) by which RC dysfunction causes global cellular sequelae are poorly understood. To identify a common cellular response to RC disease, integrated gene, pathway, and systems biology analyses were performed in human primary RC disease skeletal muscle and fibroblast transcriptomes. Significant changes were evident in muscle across diverse RC complex and genetic etiologies that were consistent with prior reports in other primary RC disease models and involved dysregulation of genes involved in RNA processing, protein translation, transport, and degradation, and muscle structure. Global transcriptional and post-transcriptional dysregulation was also found to occur in a highly tissue-specific fashion. In particular, RC disease muscle had decreased transcription of cytosolic ribosomal proteins suggestive of reduced anabolic processes, increased transcription of mitochondrial ribosomal proteins, shorter 5′-UTRs that likely improve translational efficiency, and stabilization of 3′-UTRs containing AU-rich elements. RC disease fibroblasts showed a strikingly similar pattern of global transcriptome dysregulation in a reverse direction. In parallel with these transcriptional effects, RC disease dysregulated the integrated nutrient-sensing signaling network involving FOXO, PPAR, sirtuins, AMPK, and mTORC1, which collectively sense nutrient availability and regulate cellular growth. Altered activities of central nodes in the nutrient-sensing signaling network were validated by phosphokinase immunoblot analysis in RC inhibited cells. Remarkably, treating RC mutant fibroblasts with nicotinic acid to enhance sirtuin and PPAR activity also normalized mTORC1 and AMPK signaling, restored NADH/NAD+ redox balance, and improved cellular respiratory capacity. These data specifically highlight a common pathogenesis extending across different molecular and biochemical etiologies of individual RC disorders that involves global transcriptome modifications. We further identify the integrated nutrient-sensing signaling network as a common cellular response that mediates, and may be amenable to targeted therapies for, tissue-specific sequelae of primary mitochondrial RC disease. PMID:23894440

Dependence of physical and mechanical properties on polymer architecture for model polymer networks

NASA Astrophysics Data System (ADS)

Guo, Ruilan

Effect of architecture at nanoscale on the macroscopic properties of polymer materials has long been a field of major interest, as evidenced by inhomogeneities in networks, multimodal network topologies, etc. The primary purpose of this research is to establish the architecture-property relationship of polymer networks by studying the physical and mechanical responses of a series of topologically different PTHF networks. Monodispersed allyl-tenninated PTHF precursors were synthesized through "living" cationic polymerization and functional end-capping. Model networks of various crosslink densities and inhomogeneities levels (unimodal, bimodal and clustered) were prepared by endlinking precursors via thiol-ene reaction. Thermal characteristics, i.e., glass transition, melting point, and heat of fusion, of model PTHF networks were investigated as functions of crosslink density and inhomogeneities, which showed different dependence on these two architectural parameters. Study of freezing point depression (FPD) of solvent confined in swollen networks indicated that the size of solvent microcrystals is comparable to the mesh size formed by intercrosslink chains depending on crosslink density and inhomogeneities. Relationship between crystal size and FPD provided a good reflection of the existing architecture facts in the networks. Mechanical responses of elastic chains to uniaxial strains were studied through SANS. Spatial inhomogeneities in bimodal and clustered networks gave rise to "abnormal butterfly patterns", which became more pronounced as elongation ratio increases. Radii of gyration of chains were analyzed at directions parallel and perpendicular to stretching axis. Dependence of Rg on lambda was compared to three rubber elasticity models and the molecular deformation mechanisms for unimodal, bimodal and clustered networks were explored. The thesis focused its last part on the investigation of evolution of free volume distribution of linear polymer (PE) subjected to uniaxial strain at various temperatures using a combination of MD, hard sphere probe method and Voronoi tessellation. Combined effects of temperature and strain on free volume were studied and mechanism of formation of large and ellipsoidal free volume voids was explored.

Measuring social networks in British primary schools through scientific engagement

PubMed Central

Conlan, A. J. K.; Eames, K. T. D.; Gage, J. A.; von Kirchbach, J. C.; Ross, J. V.; Saenz, R. A.; Gog, J. R.

2011-01-01

Primary schools constitute a key risk group for the transmission of infectious diseases, concentrating great numbers of immunologically naive individuals at high densities. Despite this, very little is known about the social patterns of mixing within a school, which are likely to contribute to disease transmission. In this study, we present a novel approach where scientific engagement was used as a tool to access school populations and measure social networks between young (4–11 years) children. By embedding our research project within enrichment activities to older secondary school (13–15) children, we could exploit the existing links between schools to achieve a high response rate for our study population (around 90% in most schools). Social contacts of primary school children were measured through self-reporting based on a questionnaire design, and analysed using the techniques of social network analysis. We find evidence of marked social structure and gender assortativity within and between classrooms in the same school. These patterns have been previously reported in smaller studies, but to our knowledge no study has attempted to exhaustively sample entire school populations. Our innovative approach facilitates access to a vitally important (but difficult to sample) epidemiological sub-group. It provides a model whereby scientific communication can be used to enhance, rather than merely complement, the outcomes of research. PMID:21047859

Controls on Martian Hydrothermal Systems: Application to Valley Network and Magnetic Anomaly Formation

NASA Technical Reports Server (NTRS)

Harrison, Keith P.; Grimm, Robert E.

2002-01-01

Models of hydrothermal groundwater circulation can quantify limits to the role of hydrothermal activity in Martian crustal processes. We present here the results of numerical simulations of convection in a porous medium due to the presence of a hot intruded magma chamber. The parameter space includes magma chamber depth, volume, aspect ratio, and host rock permeability and porosity. A primary goal of the models is the computation of surface discharge. Discharge increases approximately linearly with chamber volume, decreases weakly with depth (at low geothermal gradients), and is maximized for equant-shaped chambers. Discharge increases linearly with permeability until limited by the energy available from the intrusion. Changes in the average porosity are balanced by changes in flow velocity and therefore have little effect. Water/rock ratios of approximately 0.1, obtained by other workers from models based on the mineralogy of the Shergotty meteorite, imply minimum permeabilities of 10(exp -16) sq m2 during hydrothermal alteration. If substantial vapor volumes are required for soil alteration, the permeability must exceed 10(exp -15) sq m. The principal application of our model is to test the viability of hydrothermal circulation as the primary process responsible for the broad spatial correlation of Martian valley networks with magnetic anomalies. For host rock permeabilities as low as 10(exp -17) sq m and intrusion volumes as low as 50 cu km, the total discharge due to intrusions building that part of the southern highlands crust associated with magnetic anomalies spans a comparable range as the inferred discharge from the overlying valley networks.

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

PubMed

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

2018-04-01

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

Prediction of movement intention using connectivity within motor-related network: An electrocorticography study.

PubMed

Kang, Byeong Keun; Kim, June Sic; Ryun, Seokyun; Chung, Chun Kee

2018-01-01

Most brain-machine interface (BMI) studies have focused only on the active state of which a BMI user performs specific movement tasks. Therefore, models developed for predicting movements were optimized only for the active state. The models may not be suitable in the idle state during resting. This potential maladaptation could lead to a sudden accident or unintended movement resulting from prediction error. Prediction of movement intention is important to develop a more efficient and reasonable BMI system which could be selectively operated depending on the user's intention. Physical movement is performed through the serial change of brain states: idle, planning, execution, and recovery. The motor networks in the primary motor cortex and the dorsolateral prefrontal cortex are involved in these movement states. Neuronal communication differs between the states. Therefore, connectivity may change depending on the states. In this study, we investigated the temporal dynamics of connectivity in dorsolateral prefrontal cortex and primary motor cortex to predict movement intention. Movement intention was successfully predicted by connectivity dynamics which may reflect changes in movement states. Furthermore, dorsolateral prefrontal cortex is crucial in predicting movement intention to which primary motor cortex contributes. These results suggest that brain connectivity is an excellent approach in predicting movement intention.

A hydrologic network supporting spatially referenced regression modeling in the Chesapeake Bay watershed

USGS Publications Warehouse

Brakebill, J.W.; Preston, S.D.

2003-01-01

The U.S. Geological Survey has developed a methodology for statistically relating nutrient sources and land-surface characteristics to nutrient loads of streams. The methodology is referred to as SPAtially Referenced Regressions On Watershed attributes (SPARROW), and relates measured stream nutrient loads to nutrient sources using nonlinear statistical regression models. A spatially detailed digital hydrologic network of stream reaches, stream-reach characteristics such as mean streamflow, water velocity, reach length, and travel time, and their associated watersheds supports the regression models. This network serves as the primary framework for spatially referencing potential nutrient source information such as atmospheric deposition, septic systems, point-sources, land use, land cover, and agricultural sources and land-surface characteristics such as land use, land cover, average-annual precipitation and temperature, slope, and soil permeability. In the Chesapeake Bay watershed that covers parts of Delaware, Maryland, Pennsylvania, New York, Virginia, West Virginia, and Washington D.C., SPARROW was used to generate models estimating loads of total nitrogen and total phosphorus representing 1987 and 1992 land-surface conditions. The 1987 models used a hydrologic network derived from an enhanced version of the U.S. Environmental Protection Agency's digital River Reach File, and course resolution Digital Elevation Models (DEMs). A new hydrologic network was created to support the 1992 models by generating stream reaches representing surface-water pathways defined by flow direction and flow accumulation algorithms from higher resolution DEMs. On a reach-by-reach basis, stream reach characteristics essential to the modeling were transferred to the newly generated pathways or reaches from the enhanced River Reach File used to support the 1987 models. To complete the new network, watersheds for each reach were generated using the direction of surface-water flow derived from the DEMs. This network improves upon existing digital stream data by increasing the level of spatial detail and providing consistency between the reach locations and topography. The hydrologic network also aids in illustrating the spatial patterns of predicted nutrient loads and sources contributed locally to each stream, and the percentages of nutrient load that reach Chesapeake Bay.

Contextual Modulation is Related to Efficiency in a Spiking Network Model of Visual Cortex.

PubMed

Sharifian, Fariba; Heikkinen, Hanna; Vigário, Ricardo; Vanni, Simo

2015-01-01

In the visual cortex, stimuli outside the classical receptive field (CRF) modulate the neural firing rate, without driving the neuron by themselves. In the primary visual cortex (V1), such contextual modulation can be parametrized with an area summation function (ASF): increasing stimulus size causes first an increase and then a decrease of firing rate before reaching an asymptote. Earlier work has reported increase of sparseness when CRF stimulation is extended to its surroundings. However, there has been no clear connection between the ASF and network efficiency. Here we aimed to investigate possible link between ASF and network efficiency. In this study, we simulated the responses of a biomimetic spiking neural network model of the visual cortex to a set of natural images. We varied the network parameters, and compared the V1 excitatory neuron spike responses to the corresponding responses predicted from earlier single neuron data from primate visual cortex. The network efficiency was quantified with firing rate (which has direct association to neural energy consumption), entropy per spike and population sparseness. All three measures together provided a clear association between the network efficiency and the ASF. The association was clear when varying the horizontal connectivity within V1, which influenced both the efficiency and the distance to ASF, DAS. Given the limitations of our biophysical model, this association is qualitative, but nevertheless suggests that an ASF-like receptive field structure can cause efficient population response.

A Case for Telestroke in Military Medicine: A Retrospective Analysis of Stroke Cost and Outcomes in U.S. Military Health-Care System.

PubMed

Dave, Ajal; Cagniart, Kendra; Holtkamp, Matthew D

2018-06-07

The development of primary stroke centers has improved outcomes for stroke patients. Telestroke networks have expanded the reach of stroke experts to underserved, geographically remote areas. This study illustrates the outcome and cost differences between neurology and primary care ischemic stroke admissions to demonstrate a need for telestroke networks within the Military Health System (MHS). All adult admissions with a primary diagnosis of ischemic stroke in the MHS Military Mart database from calendar years 2010 to 2015 were reviewed. Neurology, primary care, and intensive care unit (ICU) admissions were compared across primary outcomes of (1) disposition status and (2) intravenous tissue plasminogen activator administration and for secondary outcomes of (1) total cost of hospitalization and (2) length of stay (LOS). A total of 3623 admissions met the study's parameters. The composition was neurology 462 (12.8%), primary care 2324 (64.1%), ICU 677 (18.7%), and other/unknown 160 (4.4%). Almost all neurology admissions (97%) were at the 3 neurology training programs, whereas a strong majority of primary care admissions (80%) were at hospitals without a neurology admitting service. Hospitals without a neurology admitting service had more discharges to rehabilitation facilities and higher rates of in-hospital mortality. LOS was also longer in primary care admissions. Ischemic stroke admissions to neurology had better outcomes and decreased LOS when compared to primary care within the MHS. This demonstrates a possible gap in care. Implementation of a hub and spoke telestroke model is a potential solution. Published by Elsevier Inc.

Risk and resilience in military families experiencing deployment: the role of the family attachment network.

PubMed

Riggs, Shelley A; Riggs, David S

2011-10-01

Deployment separation constitutes a significant stressor for U.S. military men and women and their families. Many military personnel return home struggling with physical and/or psychological injuries that challenge their ability to reintegrate and contribute to marital problems, family dysfunction, and emotional or behavioral disturbance in spouses and children. Yet research examining the psychological health and functioning of military families is scarce and rarely driven by developmental theory. The primary purpose of this theoretical paper is to describe a family attachment network model of military families during deployment and reintegration that is grounded in attachment theory and family systems theory. This integrative perspective provides a solid empirical foundation and a comprehensive account of individual and family risk and resilience during military-related separations and reunions. The proposed family attachment network model will inform future research and intervention efforts with service members and their families.

Investigation of automated task learning, decomposition and scheduling

NASA Technical Reports Server (NTRS)

Livingston, David L.; Serpen, Gursel; Masti, Chandrashekar L.

1990-01-01

The details and results of research conducted in the application of neural networks to task planning and decomposition are presented. Task planning and decomposition are operations that humans perform in a reasonably efficient manner. Without the use of good heuristics and usually much human interaction, automatic planners and decomposers generally do not perform well due to the intractable nature of the problems under consideration. The human-like performance of neural networks has shown promise for generating acceptable solutions to intractable problems such as planning and decomposition. This was the primary reasoning behind attempting the study. The basis for the work is the use of state machines to model tasks. State machine models provide a useful means for examining the structure of tasks since many formal techniques have been developed for their analysis and synthesis. It is the approach to integrate the strong algebraic foundations of state machines with the heretofore trial-and-error approach to neural network synthesis.

Limit Theorems and Their Relation to Solute Transport in Simulated Fractured Media

NASA Astrophysics Data System (ADS)

Reeves, D. M.; Benson, D. A.; Meerschaert, M. M.

2003-12-01

Solute particles that travel through fracture networks are subject to wide velocity variations along a restricted set of directions. This may result in super-Fickian dispersion along a few primary scaling directions. The fractional advection-dispersion equation (FADE), a modification of the original advection-dispersion equation in which a fractional derivative replaces the integer-order dispersion term, has the ability to model rapid, non-Gaussian solute transport. The FADE assumes that solute particle motions converge to either α -stable or operator stable densities, which are modeled by spatial fractional derivatives. In multiple dimensions, the multi-fractional dispersion derivative dictates the order and weight of differentiation in all directions, which correspond to the statistics of large particle motions in all directions. This study numerically investigates the presence of super- Fickian solute transport through simulated two-dimensional fracture networks. An ensemble of networks is gen

Machine Learning Methods for Analysis of Metabolic Data and Metabolic Pathway Modeling

PubMed Central

Cuperlovic-Culf, Miroslava

2018-01-01

Machine learning uses experimental data to optimize clustering or classification of samples or features, or to develop, augment or verify models that can be used to predict behavior or properties of systems. It is expected that machine learning will help provide actionable knowledge from a variety of big data including metabolomics data, as well as results of metabolism models. A variety of machine learning methods has been applied in bioinformatics and metabolism analyses including self-organizing maps, support vector machines, the kernel machine, Bayesian networks or fuzzy logic. To a lesser extent, machine learning has also been utilized to take advantage of the increasing availability of genomics and metabolomics data for the optimization of metabolic network models and their analysis. In this context, machine learning has aided the development of metabolic networks, the calculation of parameters for stoichiometric and kinetic models, as well as the analysis of major features in the model for the optimal application of bioreactors. Examples of this very interesting, albeit highly complex, application of machine learning for metabolism modeling will be the primary focus of this review presenting several different types of applications for model optimization, parameter determination or system analysis using models, as well as the utilization of several different types of machine learning technologies. PMID:29324649

Machine Learning Methods for Analysis of Metabolic Data and Metabolic Pathway Modeling.

PubMed

Cuperlovic-Culf, Miroslava

2018-01-11

Machine learning uses experimental data to optimize clustering or classification of samples or features, or to develop, augment or verify models that can be used to predict behavior or properties of systems. It is expected that machine learning will help provide actionable knowledge from a variety of big data including metabolomics data, as well as results of metabolism models. A variety of machine learning methods has been applied in bioinformatics and metabolism analyses including self-organizing maps, support vector machines, the kernel machine, Bayesian networks or fuzzy logic. To a lesser extent, machine learning has also been utilized to take advantage of the increasing availability of genomics and metabolomics data for the optimization of metabolic network models and their analysis. In this context, machine learning has aided the development of metabolic networks, the calculation of parameters for stoichiometric and kinetic models, as well as the analysis of major features in the model for the optimal application of bioreactors. Examples of this very interesting, albeit highly complex, application of machine learning for metabolism modeling will be the primary focus of this review presenting several different types of applications for model optimization, parameter determination or system analysis using models, as well as the utilization of several different types of machine learning technologies.

Modeling Neisseria meningitidis metabolism: from genome to metabolic fluxes

PubMed Central

Baart, Gino JE; Zomer, Bert; de Haan, Alex; van der Pol, Leo A; Beuvery, E Coen; Tramper, Johannes; Martens, Dirk E

2007-01-01

Background Neisseria meningitidis is a human pathogen that can infect diverse sites within the human host. The major diseases caused by N. meningitidis are responsible for death and disability, especially in young infants. In general, most of the recent work on N. meningitidis focuses on potential antigens and their functions, immunogenicity, and pathogenicity mechanisms. Very little work has been carried out on Neisseria primary metabolism over the past 25 years. Results Using the genomic database of N. meningitidis serogroup B together with biochemical and physiological information in the literature we constructed a genome-scale flux model for the primary metabolism of N. meningitidis. The validity of a simplified metabolic network derived from the genome-scale metabolic network was checked using flux-balance analysis in chemostat cultures. Several useful predictions were obtained from in silico experiments, including substrate preference. A minimal medium for growth of N. meningitidis was designed and tested succesfully in batch and chemostat cultures. Conclusion The verified metabolic model describes the primary metabolism of N. meningitidis in a chemostat in steady state. The genome-scale model is valuable because it offers a framework to study N. meningitidis metabolism as a whole, or certain aspects of it, and it can also be used for the purpose of vaccine process development (for example, the design of growth media). The flux distribution of the main metabolic pathways (that is, the pentose phosphate pathway and the Entner-Douderoff pathway) indicates that the major part of pyruvate (69%) is synthesized through the ED-cleavage, a finding that is in good agreement with literature. PMID:17617894

78 FR 43000 - Financial Crimes Enforcement Network; Proposed Renewal Without Change; Comment Request...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-07-18

... Institution of Primary Money Laundering Concern AGENCY: Financial Crimes Enforcement Network, Department of... primary money laundering concern. This request for comments is being made pursuant to the Paperwork... Institution of Primary Money Laundering Concern. Office of Management and Budget Control Number: 1506-0036...

Expanding Health Care Access Through Education: Dissemination and Implementation of the ECHO Model.

PubMed

Katzman, Joanna G; Galloway, Kevin; Olivas, Cynthia; McCoy-Stafford, Kimberly; Duhigg, Daniel; Comerci, George; Kalishman, Summers; Buckenmaier, Chester C; McGhee, Laura; Joltes, Kristin; Bradford, Andrea; Shelley, Brian; Hernandez, Jessica; Arora, Sanjeev

2016-03-01

Project ECHO (Extension for Community Healthcare Outcomes) is an evidence-based model that provides high-quality medical education for common and complex diseases through telementoring and comanagement of patients with primary care clinicians. In a one to many knowledge network, the ECHO model helps to bridge the gap between primary care clinicians and specialists by enhancing the knowledge, skills, confidence, and practice of primary care clinicians in their local communities. As a result, patients in rural and urban underserved areas are able to receive best practice care without long waits or having to travel long distances. The ECHO model has been replicated in 43 university hubs in the United States and five other countries. A new replication tool was developed by the Project ECHO Pain team and U.S. Army Medical Command to ensure a high-fidelity replication of the model. The adoption of the tool led to successful replication of ECHO in the Army Pain initiative. This replication tool has the potential to improve the fidelity of ECHO replication efforts around the world. Reprint & Copyright © 2016 Association of Military Surgeons of the U.S.

Gene Discovery of Characteristic Metabolic Pathways in the Tea Plant (Camellia sinensis) Using ‘Omics’-Based Network Approaches: A Future Perspective

PubMed Central

Zhang, Shihua; Zhang, Liang; Tai, Yuling; Wang, Xuewen; Ho, Chi-Tang; Wan, Xiaochun

2018-01-01

Characteristic secondary metabolites, including flavonoids, theanine and caffeine, in the tea plant (Camellia sinensis) are the primary sources of the rich flavors, fresh taste, and health benefits of tea. The decoding of genes involved in these characteristic components is still significantly lagging, which lays an obstacle for applied genetic improvement and metabolic engineering. With the popularity of high-throughout transcriptomics and metabolomics, ‘omics’-based network approaches, such as gene co-expression network and gene-to-metabolite network, have emerged as powerful tools for gene discovery of plant-specialized (secondary) metabolism. Thus, it is pivotal to summarize and introduce such system-based strategies in facilitating gene identification of characteristic metabolic pathways in the tea plant (or other plants). In this review, we describe recent advances in transcriptomics and metabolomics for transcript and metabolite profiling, and highlight ‘omics’-based network strategies using successful examples in model and non-model plants. Further, we summarize recent progress in ‘omics’ analysis for gene identification of characteristic metabolites in the tea plant. Limitations of the current strategies are discussed by comparison with ‘omics’-based network approaches. Finally, we demonstrate the potential of introducing such network strategies in the tea plant, with a prospects ending for a promising network discovery of characteristic metabolite genes in the tea plant. PMID:29915604

Implementing Key Strategies for Successful Network Integration in the Quebec Substance-Use Disorders Programme

PubMed Central

Perreault, Michel; Grenier, Guy; Imboua, Armelle; Brochu, Serge

2016-01-01

Background: Fragmentation and lack of coordination often occur among organisations offering treatment for individuals with substance-use disorders. Better integration from a system perspective within a network of organisations offering substance-use disorder services can be developed using various integration strategies at the administrative and clinical levels. This study aims to identify integration strategies implemented in Quebec substance-use disorder networks and to assess their strengths and limitations. Methods: A total of 105 stakeholders representing two regions and four local substance-use disorder networks participated in focus groups or individual interviews. Thematic qualitative and descriptive quantitative analyses were conducted. Results: Six types of service integration strategies have been implemented to varying degrees in substance-use disorder networks. They are: 1) coordination activities-governance, 2) primary-care consolidation models, 3) information and monitoring management tools, 4) service coordination strategies, 5) clinical evaluation tools and 6) training activities. Conclusion: Important investments have been made in Quebec for the training and assessment of individuals with substance-use disorders, particularly in terms of support for emergency room liaison teams and the introduction of standardised clinical evaluation tools. However, the development of integration strategies was insufficient to ensure the implementation of successful networks. Planning, consolidation of primary care for substance-use disorders and systematic implementation of various clinical and administrative integration strategies are needed in order to ensure a better continuum of care for individuals with substance-use disorders. PMID:27616951

Collaborative Network Management for Enhancing Quality Education of Primary Schools

ERIC Educational Resources Information Center

Chaikoed, Wisithsak; Sirisuthi, Chaiyuth; Numnaphol, Kochaporn

2017-01-01

This research aims to study the network and collaborative factors that enhance quality education of primary schools. Different methods were used in this research work: (1) Related approaches, theories, and research literatures and (2) Scholars were interviewed on 871 issues in the form of questionnaire, and the collaborative network factors were…

The influence of social networks on patients' attitudes toward type II diabetes.

PubMed

Mani, Nandini; Caiola, Enrico; Fortuna, Robert J

2011-10-01

Social networks are increasingly recognized as important determinants of many chronic diseases, yet little data exist regarding the influence of social networks on diabetes. We surveyed diabetic patients to determine how social networks affect their overall level of concern regarding diabetes and its complications. We adapted a previously published instrument and surveyed 240 diabetic patients at two primary care practices. Patients recorded the number of family and friends who had diabetes and rated their level of concern about diabetes on a scale of 0% (no concern) to 100% (extremely concerned). Our primary outcome variable was patients' level of concern (<75% or ≥75%). We developed logistic regression models to determine the effect of disease burden in patients' social networks on expressed level of concern about diabetes. We received 154 surveys (64% response rate). We found that for each additional family member with diabetes, patients expressed a greater level of concern about diabetes (AOR 1.5; 95% CI 1.2-2.0) and its potential complications (AOR 1.4; 95% CI 1.1-1.7). Similarly, patients with an increased number of friends with diabetes expressed greater concern about diabetes (AOR 1.5; 95% CI 1.2-1.9) and its complications (AOR 1.3; 95% CI 1.1-1.7). Patients with a higher prevalence of diabetes within their social networks expressed greater concern about diabetes and diabetic complications. Determining disease burden within patients' social networks may allow physicians to better understand patients' perspectives on their disease and ultimately help them achieve meaningful behavioral change.

Mass Balance of Multiyear Sea Ice in the Southern Beaufort Sea

DTIC Science & Technology

2012-09-30

datasets. Table 1 lists the primary data sources to be used. To determine sources and sinks of MY ice, we use a simple model of MY ice circulation, which is...shown in Figure 1. In this model , we consider the Beaufort Sea to consist of four zones defined by mean drift of sea ice in summer and winter, such...Healy/Louis S. St. Laurant cruises 1 Seasonal Ice Zone Observing Network 2 Polar Airborne Measurements and Arctic Regional Climate Model

Human Odometry Verifies the Symmetry Perspective on Bipedal Gaits

ERIC Educational Resources Information Center

Turvey, M. T.; Harrison, Steven J.; Frank, Till D.; Carello, Claudia

2012-01-01

Bipedal gaits have been classified on the basis of the group symmetry of the minimal network of identical differential equations (alias "cells") required to model them. Primary gaits are characterized by dihedral symmetry, whereas secondary gaits are characterized by a lower, cyclic symmetry. This fact was used in a test of human…

Upper Washita River experimental watersheds: Multiyear stability of soil water content profiles

USDA-ARS?s Scientific Manuscript database

Scaling in situ soil water content time series data to a large spatial domain is a key element of watershed environmental monitoring and modeling. The primary method of estimating and monitoring large-scale soil water content distributions is via in situ networks. It is critical to establish the s...

Engineering the Mechanical Properties of Polymer Networks with Precise Doping of Primary Defects.

PubMed

Chan, Doreen; Ding, Yichuan; Dauskardt, Reinhold H; Appel, Eric A

2017-12-06

Polymer networks are extensively utilized across numerous applications ranging from commodity superabsorbent polymers and coatings to high-performance microelectronics and biomaterials. For many applications, desirable properties are known; however, achieving them has been challenging. Additionally, the accurate prediction of elastic modulus has been a long-standing difficulty owing to the presence of loops. By tuning the prepolymer formulation through precise doping of monomers, specific primary network defects can be programmed into an elastomeric scaffold, without alteration of their resulting chemistry. The addition of these monomers that respond mechanically as primary defects is used both to understand their impact on the resulting mechanical properties of the materials and as a method to engineer the mechanical properties. Indeed, these materials exhibit identical bulk and surface chemistry, yet vastly different mechanical properties. Further, we have adapted the real elastic network theory (RENT) to the case of primary defects in the absence of loops, thus providing new insights into the mechanism for material strength and failure in polymer networks arising from primary network defects, and to accurately predict the elastic modulus of the polymer system. The versatility of the approach we describe and the fundamental knowledge gained from this study can lead to new advancements in the development of novel materials with precisely defined and predictable chemical, physical, and mechanical properties.

Structural kinetic modeling of metabolic networks.

PubMed

Steuer, Ralf; Gross, Thilo; Selbig, Joachim; Blasius, Bernd

2006-08-08

To develop and investigate detailed mathematical models of metabolic processes is one of the primary challenges in systems biology. However, despite considerable advance in the topological analysis of metabolic networks, kinetic modeling is still often severely hampered by inadequate knowledge of the enzyme-kinetic rate laws and their associated parameter values. Here we propose a method that aims to give a quantitative account of the dynamical capabilities of a metabolic system, without requiring any explicit information about the functional form of the rate equations. Our approach is based on constructing a local linear model at each point in parameter space, such that each element of the model is either directly experimentally accessible or amenable to a straightforward biochemical interpretation. This ensemble of local linear models, encompassing all possible explicit kinetic models, then allows for a statistical exploration of the comprehensive parameter space. The method is exemplified on two paradigmatic metabolic systems: the glycolytic pathway of yeast and a realistic-scale representation of the photosynthetic Calvin cycle.

[The reform of primary health care: the economic, care and satisfaction results].

PubMed

Durán, J; Jodar, G; Pociello, V; Parellada, N; Martín, A; Pradas, J

1999-05-15

To compare the overall effect on the general public before and after the primary care reform, its economic outcome and professional satisfaction, following the model of the European Foundation for Quality Management. A descriptive analysis of results at reformed primary care centres compared with results at non-reformed centres in the same city. The study was conducted at Sant Boi de Llobregat, a town of 77,591 inhabitants in Baix Llobregat county (Barcelona). 32.7% of the population was covered by two reformed centres. The rest was covered by one single non-reformed primary care centre. Clinical audits and data on pharmaceutical prescription quality were used to find attendance. For economic results, the formula of attribution of cost/inhabitant and cost/inhabitant seen, including the costs of labour, structure, referral, further tests and pharmacy, were used. The satisfaction of the outside customer (user) was measured by a population survey. Internal customer satisfaction was measured by a survey of the professionals. Results were compared with those for 1997. The study showed that the reformed primary care sector's results, measured in terms of professional satisfaction, user-outside customer, attendance, economic results and social impact, were better than the non-reformed sector's. Inside and outside customers' satisfaction was higher in the reformed network. The cost per inhabitant in the reformed network was 31,874 pesetas, against 25,177 in the non-reformed network. The cost per inhabitant seen was 34,482 and 44,603, respectively. The reform creates efficient resource management and greater satisfaction of the general public and professionals, when an indicator sensitive to the real use of services is used.

Results and evaluation of a pilot primary monitoring network, San Francisco Bay, California, 1978

USGS Publications Warehouse

Bradford, W.L.; Iwatsubo, R.T.

1980-01-01

A primary monitoring network of 12 stations, with measurements at 1-meter depth intervals every 2 weeks during periods of high inflow from the Sacramento-San Joaquin River delta, and every 4-6 weeks during seasonal low delta inflows, appears adequate to observe major changes in ambient water quality in San Francisco Bay. A 1-year study tested the network operation and determined that analysis of the data could demonstrate the major changes in salinity, temperature, and light-attenuation distributions known to occur, based on earlier research, in response to variations of delta inflow and to other physical processes. Observations of eddies at two stations, of the influence of water from a river flooding in the extreme south bay, and of difference in salinity and temperature laterally across the entrance to the south bay are all new but are consistent with existing models. The pH, dissolved oxygen, and light-attenuation measurements, while adequate to observe small-scale vertical variations, are not sufficiently sensitive to detect the effects of phytoplankton blooms. (USGS)

Analysis of Time-Dependent Brain Network on Active and MI Tasks for Chronic Stroke Patients

PubMed Central

Chang, Won Hyuk; Kim, Yun-Hee; Lee, Seong-Whan; Kwon, Gyu Hyun

2015-01-01

Several researchers have analyzed brain activities by investigating brain networks. However, there is a lack of the research on the temporal characteristics of the brain network during a stroke by EEG and the comparative studies between motor execution and imagery, which became known to have similar motor functions and pathways. In this study, we proposed the possibility of temporal characteristics on the brain networks of a stroke. We analyzed the temporal properties of the brain networks for nine chronic stroke patients by the active and motor imagery tasks by EEG. High beta band has a specific role in the brain network during motor tasks. In the high beta band, for the active task, there were significant characteristics of centrality and small-worldness on bilateral primary motor cortices at the initial motor execution. The degree centrality significantly increased on the contralateral primary motor cortex, and local efficiency increased on the ipsilateral primary motor cortex. These results indicate that the ipsilateral primary motor cortex constructed a powerful subnetwork by influencing the linked channels as compensatory effect, although the contralateral primary motor cortex organized an inefficient network by using the connected channels due to lesions. For the MI task, degree centrality and local efficiency significantly decreased on the somatosensory area at the initial motor imagery. Then, there were significant correlations between the properties of brain networks and motor function on the contralateral primary motor cortex and somatosensory area for each motor execution/imagery task. Our results represented that the active and MI tasks have different mechanisms of motor acts. Based on these results, we indicated the possibility of customized rehabilitation according to different motor tasks. We expect these results to help in the construction of the customized rehabilitation system depending on motor tasks by understanding temporal functional characteristics on brain network for a stroke. PMID:26656269

Evolution versus "intelligent design": comparing the topology of protein-protein interaction networks to the Internet.

PubMed

Yang, Q; Siganos, G; Faloutsos, M; Lonardi, S

2006-01-01

Recent research efforts have made available genome-wide, high-throughput protein-protein interaction (PPI) maps for several model organisms. This has enabled the systematic analysis of PPI networks, which has become one of the primary challenges for the system biology community. In this study, we attempt to understand better the topological structure of PPI networks by comparing them against man-made communication networks, and more specifically, the Internet. Our comparative study is based on a comprehensive set of graph metrics. Our results exhibit an interesting dichotomy. On the one hand, both networks share several macroscopic properties such as scale-free and small-world properties. On the other hand, the two networks exhibit significant topological differences, such as the cliqueishness of the highest degree nodes. We attribute these differences to the distinct design principles and constraints that both networks are assumed to satisfy. We speculate that the evolutionary constraints that favor the survivability and diversification are behind the building process of PPI networks, whereas the leading force in shaping the Internet topology is a decentralized optimization process geared towards efficient node communication.

Primary health care teams and the patient perspective: a social network analysis.

PubMed

Cheong, Lynn H M; Armour, Carol L; Bosnic-Anticevich, Sinthia Z

2013-01-01

Multidisciplinary care (MDC) has been proposed as a potential strategy to address the rising challenges of modern health issues. However, it remains unclear as to how patients' health connections may impact on multidisciplinary processes and outcomes. This research aims to gain a deeper understanding of patients' potential role in MDC: i) describe patients' health networks, ii) compare different care groups, iii) gain an understanding of the nature and extent of their interactions, and iv) identify the role of pharmacists within patient networks. In-depth, semi-structured interviews were conducted with asthma patients from Sydney, Australia. Participants were recruited from a range of standard asthma health care access points (community group) and a specialized multidisciplinary asthma clinic (clinic group). Quantitative social network analysis provided structural insight into asthma networks while qualitative social network analysis assisted in interpretation of network data. A total of 47 interviews were conducted (26 community group participants and 21 clinic group participants). Although participants' asthma networks consisted of a range of health care professionals (HCPs), these did not reflect or encourage MDC. Not only did participants favor minimal interaction with any HCP, they preferred sole-charge care and were found to strongly rely on lay individuals such as family and friends. While general practitioners and respiratory specialists were participants' principal choice of HCP, community pharmacists were less regarded. Limited opportunities were presented for HCPs to collaborate, particularly pharmacists. As patients' choices of HCPs may strongly influence collaborative processes and outcomes, this research highlights the need to consider patient perspectives in the development of MDC models in primary care. Copyright © 2013 Elsevier Inc. All rights reserved.

Development of a Bayesian Belief Network Runway Incursion Model

NASA Technical Reports Server (NTRS)

Green, Lawrence L.

2014-01-01

In a previous paper, a statistical analysis of runway incursion (RI) events was conducted to ascertain their relevance to the top ten Technical Challenges (TC) of the National Aeronautics and Space Administration (NASA) Aviation Safety Program (AvSP). The study revealed connections to perhaps several of the AvSP top ten TC. That data also identified several primary causes and contributing factors for RI events that served as the basis for developing a system-level Bayesian Belief Network (BBN) model for RI events. The system-level BBN model will allow NASA to generically model the causes of RI events and to assess the effectiveness of technology products being developed under NASA funding. These products are intended to reduce the frequency of RI events in particular, and to improve runway safety in general. The development, structure and assessment of that BBN for RI events by a Subject Matter Expert panel are documented in this paper.

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

NASA Astrophysics Data System (ADS)

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

2015-06-01

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

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

DOE PAGES

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

2015-06-11

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

Visualization and Hierarchical Analysis of Flow in Discrete Fracture Network Models

NASA Astrophysics Data System (ADS)

Aldrich, G. A.; Gable, C. W.; Painter, S. L.; Makedonska, N.; Hamann, B.; Woodring, J.

2013-12-01

Flow and transport in low permeability fractured rock is primary in interconnected fracture networks. Prediction and characterization of flow and transport in fractured rock has important implications in underground repositories for hazardous materials (eg. nuclear and chemical waste), contaminant migration and remediation, groundwater resource management, and hydrocarbon extraction. We have developed methods to explicitly model flow in discrete fracture networks and track flow paths using passive particle tracking algorithms. Visualization and analysis of particle trajectory through the fracture network is important to understanding fracture connectivity, flow patterns, potential contaminant pathways and fast paths through the network. However, occlusion due to the large number of highly tessellated and intersecting fracture polygons preclude the effective use of traditional visualization methods. We would also like quantitative analysis methods to characterize the trajectory of a large number of particle paths. We have solved these problems by defining a hierarchal flow network representing the topology of particle flow through the fracture network. This approach allows us to analyses the flow and the dynamics of the system as a whole. We are able to easily query the flow network, and use paint-and-link style framework to filter the fracture geometry and particle traces based on the flow analytics. This allows us to greatly reduce occlusion while emphasizing salient features such as the principal transport pathways. Examples are shown that demonstrate the methodology and highlight how use of this new method allows quantitative analysis and characterization of flow and transport in a number of representative fracture networks.

Meta-connectomics: human brain network and connectivity meta-analyses.

PubMed

Crossley, N A; Fox, P T; Bullmore, E T

2016-04-01

Abnormal brain connectivity or network dysfunction has been suggested as a paradigm to understand several psychiatric disorders. We here review the use of novel meta-analytic approaches in neuroscience that go beyond a summary description of existing results by applying network analysis methods to previously published studies and/or publicly accessible databases. We define this strategy of combining connectivity with other brain characteristics as 'meta-connectomics'. For example, we show how network analysis of task-based neuroimaging studies has been used to infer functional co-activation from primary data on regional activations. This approach has been able to relate cognition to functional network topology, demonstrating that the brain is composed of cognitively specialized functional subnetworks or modules, linked by a rich club of cognitively generalized regions that mediate many inter-modular connections. Another major application of meta-connectomics has been efforts to link meta-analytic maps of disorder-related abnormalities or MRI 'lesions' to the complex topology of the normative connectome. This work has highlighted the general importance of network hubs as hotspots for concentration of cortical grey-matter deficits in schizophrenia, Alzheimer's disease and other disorders. Finally, we show how by incorporating cellular and transcriptional data on individual nodes with network models of the connectome, studies have begun to elucidate the microscopic mechanisms underpinning the macroscopic organization of whole-brain networks. We argue that meta-connectomics is an exciting field, providing robust and integrative insights into brain organization that will likely play an important future role in consolidating network models of psychiatric disorders.

Single-phase and two-phase flow properties of mesaverde tight sandstone formation; random-network modeling approach

NASA Astrophysics Data System (ADS)

Bashtani, Farzad; Maini, Brij; Kantzas, Apostolos

2016-08-01

3D random networks are constructed in order to represent the tight Mesaverde formation which is located in north Wyoming, USA. The porous-space is represented by pore bodies of different shapes and sizes which are connected to each other by pore throats of varying length and diameter. Pore bodies are randomly distributed in space and their connectivity varies based on the connectivity number distribution which is used in order to generate the network. Network representations are then validated using publicly available mercury porosimetry experiments. The network modeling software solves the fundamental equations of two-phase immiscible flow incorporating wettability and contact angle variability. Quasi-static displacement is assumed. Single phase macroscopic properties (porosity, permeability) are calculated and whenever possible are compared to experimental data. Using this information drainage and imbibition capillary pressure, and relative permeability curves are predicted and (whenever possible) compared to experimental data. The calculated information is grouped and compared to available literature information on typical behavior of tight formations. Capillary pressure curve for primary drainage process is predicted and compared to experimental mercury porosimetry in order to validate the virtual porous media by history matching. Relative permeability curves are also calculated and presented.

A convergent model for distributed processing of Big Sensor Data in urban engineering networks

NASA Astrophysics Data System (ADS)

Parygin, D. S.; Finogeev, A. G.; Kamaev, V. A.; Finogeev, A. A.; Gnedkova, E. P.; Tyukov, A. P.

2017-01-01

The problems of development and research of a convergent model of the grid, cloud, fog and mobile computing for analytical Big Sensor Data processing are reviewed. The model is meant to create monitoring systems of spatially distributed objects of urban engineering networks and processes. The proposed approach is the convergence model of the distributed data processing organization. The fog computing model is used for the processing and aggregation of sensor data at the network nodes and/or industrial controllers. The program agents are loaded to perform computing tasks for the primary processing and data aggregation. The grid and the cloud computing models are used for integral indicators mining and accumulating. A computing cluster has a three-tier architecture, which includes the main server at the first level, a cluster of SCADA system servers at the second level, a lot of GPU video cards with the support for the Compute Unified Device Architecture at the third level. The mobile computing model is applied to visualize the results of intellectual analysis with the elements of augmented reality and geo-information technologies. The integrated indicators are transferred to the data center for accumulation in a multidimensional storage for the purpose of data mining and knowledge gaining.

Neural network configuration and efficiency underlies individual differences in spatial orientation ability.

PubMed

Arnold, Aiden E G F; Protzner, Andrea B; Bray, Signe; Levy, Richard M; Iaria, Giuseppe

2014-02-01

Spatial orientation is a complex cognitive process requiring the integration of information processed in a distributed system of brain regions. Current models on the neural basis of spatial orientation are based primarily on the functional role of single brain regions, with limited understanding of how interaction among these brain regions relates to behavior. In this study, we investigated two sources of variability in the neural networks that support spatial orientation--network configuration and efficiency--and assessed whether variability in these topological properties relates to individual differences in orientation accuracy. Participants with higher accuracy were shown to express greater activity in the right supramarginal gyrus, the right precentral cortex, and the left hippocampus, over and above a core network engaged by the whole group. Additionally, high-performing individuals had increased levels of global efficiency within a resting-state network composed of brain regions engaged during orientation and increased levels of node centrality in the right supramarginal gyrus, the right primary motor cortex, and the left hippocampus. These results indicate that individual differences in the configuration of task-related networks and their efficiency measured at rest relate to the ability to spatially orient. Our findings advance systems neuroscience models of orientation and navigation by providing insight into the role of functional integration in shaping orientation behavior.

Predicting the performance of local seismic networks using Matlab and Google Earth.

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

Chael, Eric Paul

2009-11-01

We have used Matlab and Google Earth to construct a prototype application for modeling the performance of local seismic networks for monitoring small, contained explosions. Published equations based on refraction experiments provide estimates of peak ground velocities as a function of event distance and charge weight. Matlab routines implement these relations to calculate the amplitudes across a network of stations from sources distributed over a geographic grid. The amplitudes are then compared to ambient noise levels at the stations, and scaled to determine the smallest yield that could be detected at each source location by a specified minimum number ofmore » stations. We use Google Earth as the primary user interface, both for positioning the stations of a hypothetical local network, and for displaying the resulting detection threshold contours.« less

Integrated risk/cost planning models for the US Air Traffic system

NASA Technical Reports Server (NTRS)

Mulvey, J. M.; Zenios, S. A.

1985-01-01

A prototype network planning model for the U.S. Air Traffic control system is described. The model encompasses the dual objectives of managing collision risks and transportation costs where traffic flows can be related to these objectives. The underlying structure is a network graph with nonseparable convex costs; the model is solved efficiently by capitalizing on its intrinsic characteristics. Two specialized algorithms for solving the resulting problems are described: (1) truncated Newton, and (2) simplicial decomposition. The feasibility of the approach is demonstrated using data collected from a control center in the Midwest. Computational results with different computer systems are presented, including a vector supercomputer (CRAY-XMP). The risk/cost model has two primary uses: (1) as a strategic planning tool using aggregate flight information, and (2) as an integrated operational system for forecasting congestion and monitoring (controlling) flow throughout the U.S. In the latter case, access to a supercomputer is required due to the model's enormous size.

An executable specification for the message processor in a simple combining network

NASA Technical Reports Server (NTRS)

Middleton, David

1995-01-01

While the primary function of the network in a parallel computer is to communicate data between processors, it is often useful if the network can also perform rudimentary calculations. That is, some simple processing ability in the network itself, particularly for performing parallel prefix computations, can reduce both the volume of data being communicated and the computational load on the processors proper. Unfortunately, typical implementations of such networks require a large fraction of the hardware budget, and so combining networks are viewed as being impractical. The FFP Machine has such a combining network, and various characteristics of the machine allow a good deal of simplification in the network design. Despite being simple in construction however, the network relies on many subtle details to work correctly. This paper describes an executable model of the network which will serve several purposes. It provides a complete and detailed description of the network which can substantiate its ability to support necessary functions. It provides an environment in which algorithms to be run on the network can be designed and debugged more easily than they would on physical hardware. Finally, it provides the foundation for exploring the design of the message receiving facility which connects the network to the individual processors.

Dependency-based Siamese long short-term memory network for learning sentence representations

PubMed Central

Zhu, Wenhao; Ni, Jianyue; Wei, Baogang; Lu, Zhiguo

2018-01-01

Textual representations play an important role in the field of natural language processing (NLP). The efficiency of NLP tasks, such as text comprehension and information extraction, can be significantly improved with proper textual representations. As neural networks are gradually applied to learn the representation of words and phrases, fairly efficient models of learning short text representations have been developed, such as the continuous bag of words (CBOW) and skip-gram models, and they have been extensively employed in a variety of NLP tasks. Because of the complex structure generated by the longer text lengths, such as sentences, algorithms appropriate for learning short textual representations are not applicable for learning long textual representations. One method of learning long textual representations is the Long Short-Term Memory (LSTM) network, which is suitable for processing sequences. However, the standard LSTM does not adequately address the primary sentence structure (subject, predicate and object), which is an important factor for producing appropriate sentence representations. To resolve this issue, this paper proposes the dependency-based LSTM model (D-LSTM). The D-LSTM divides a sentence representation into two parts: a basic component and a supporting component. The D-LSTM uses a pre-trained dependency parser to obtain the primary sentence information and generate supporting components, and it also uses a standard LSTM model to generate the basic sentence components. A weight factor that can adjust the ratio of the basic and supporting components in a sentence is introduced to generate the sentence representation. Compared with the representation learned by the standard LSTM, the sentence representation learned by the D-LSTM contains a greater amount of useful information. The experimental results show that the D-LSTM is superior to the standard LSTM for sentences involving compositional knowledge (SICK) data. PMID:29513748

Comment on "A dynamic network model of mTOR signaling reveals TSC-independent mTORC2 regulation": building a model of the mTOR signaling network with a potentially faulty tool.

PubMed

Manning, Brendan D

2012-07-10

In their study published in Science Signaling (Research Article, 27 March 2012, DOI: 10.1126/scisignal.2002469), Dalle Pezze et al. tackle the dynamic and complex wiring of the signaling network involving the protein kinase mTOR, which exists within two distinct protein complexes (mTORC1 and mTORC2) that differ in their regulation and function. The authors use a combination of immunoblotting for specific phosphorylation events and computational modeling. The primary experimental tool employed is to monitor the autophosphorylation of mTOR on Ser(2481) in cell lysates as a surrogate for mTOR activity, which the authors conclude is a specific readout for mTORC2. However, Ser(2481) phosphorylation occurs on both mTORC1 and mTORC2 and will dynamically change as the network through which these two complexes are connected is manipulated. Therefore, models of mTOR network regulation built using this tool are inherently imperfect and open to alternative explanations. Specific issues with the main conclusion made in this study, involving the TSC1-TSC2 (tuberous sclerosis complex 1 and 2) complex and its potential regulation of mTORC2, are discussed here. A broader goal of this Letter is to clarify to other investigators the caveats of using mTOR Ser(2481) phosphorylation in cell lysates as a specific readout for either of the two mTOR complexes.

A Mechanistic Model of Human Recall of Social Network Structure and Relationship Affect.

PubMed

Omodei, Elisa; Brashears, Matthew E; Arenas, Alex

2017-12-07

The social brain hypothesis argues that the need to deal with social challenges was key to our evolution of high intelligence. Research with non-human primates as well as experimental and fMRI studies in humans produce results consistent with this claim, leading to an estimate that human primary groups should consist of roughly 150 individuals. Gaps between this prediction and empirical observations can be partially accounted for using "compression heuristics", or schemata that simplify the encoding and recall of social information. However, little is known about the specific algorithmic processes used by humans to store and recall social information. We describe a mechanistic model of human network recall and demonstrate its sufficiency for capturing human recall behavior observed in experimental contexts. We find that human recall is predicated on accurate recall of a small number of high degree network nodes and the application of heuristics for both structural and affective information. This provides new insight into human memory, social network evolution, and demonstrates a novel approach to uncovering human cognitive operations.

A Network Model of Observation and Imitation of Speech

PubMed Central

Mashal, Nira; Solodkin, Ana; Dick, Anthony Steven; Chen, E. Elinor; Small, Steven L.

2012-01-01

Much evidence has now accumulated demonstrating and quantifying the extent of shared regional brain activation for observation and execution of speech. However, the nature of the actual networks that implement these functions, i.e., both the brain regions and the connections among them, and the similarities and differences across these networks has not been elucidated. The current study aims to characterize formally a network for observation and imitation of syllables in the healthy adult brain and to compare their structure and effective connectivity. Eleven healthy participants observed or imitated audiovisual syllables spoken by a human actor. We constructed four structural equation models to characterize the networks for observation and imitation in each of the two hemispheres. Our results show that the network models for observation and imitation comprise the same essential structure but differ in important ways from each other (in both hemispheres) based on connectivity. In particular, our results show that the connections from posterior superior temporal gyrus and sulcus to ventral premotor, ventral premotor to dorsal premotor, and dorsal premotor to primary motor cortex in the left hemisphere are stronger during imitation than during observation. The first two connections are implicated in a putative dorsal stream of speech perception, thought to involve translating auditory speech signals into motor representations. Thus, the current results suggest that flow of information during imitation, starting at the posterior superior temporal cortex and ending in the motor cortex, enhances input to the motor cortex in the service of speech execution. PMID:22470360

Moving across Physical and Online Spaces: A Case Study in a Blended Primary Classroom

ERIC Educational Resources Information Center

Thibaut, Patricia; Curwood, Jen Scott; Carvalho, Lucila; Simpson, Alyson

2015-01-01

With the introduction of digital tools and online connectivity in primary schools, the shape of teaching and learning is shifting beyond the physical classroom. Drawing on the architecture of productive learning networks framework, we examine the affordances and limitations of an upper primary learning network and focus on how the digital and…

Networked remote area dental services: a viable, sustainable approach to oral health care in challenging environments.

PubMed

Dyson, Kate; Kruger, Estie; Tennant, Marc

2012-12-01

This study examines the cost effectiveness of a model of remote area oral health service. Retrospective financial analysis. Rural and remote primary health services. Clinical activity data and associated cost data relating to the provision of a networked visiting oral health service by the Centre for Rural and Remote Oral Health formed the basis of the study data frameset. The cost-effectiveness of the Centre's model of service provision at five rural and remote sites in Western Australia during the calendar years 2006, 2008 and 2010 was examined in the study. Calculations of the service provision costs and value of care provided were made using data records and the Fee Schedule of Dental Services for Dentists. The ratio of service provision costs to the value of care provided was determined for each site and was benchmarked against the equivalent ratios applicable to large scale government sector models of service provision. The use of networked models have been effective in other disciplines but this study is the first to show a networked hub and spoke approach of five spokes to one hub is cost efficient in remote oral health care. By excluding special cost-saving initiatives introduced by the Centre, the study examines easily translatable direct service provision costs against direct clinical care outcomes in some of Australia's most challenging locations. This study finds that networked hub and spoke models of care can be financially efficient arrangements in remote oral health care. © 2012 The Authors. Australian Journal of Rural Health © National Rural Health Alliance Inc.

Artificial neural network modeling of dissolved oxygen in the Heihe River, Northwestern China.

PubMed

Wen, Xiaohu; Fang, Jing; Diao, Meina; Zhang, Chuanqi

2013-05-01

Identification and quantification of dissolved oxygen (DO) profiles of river is one of the primary concerns for water resources managers. In this research, an artificial neural network (ANN) was developed to simulate the DO concentrations in the Heihe River, Northwestern China. A three-layer back-propagation ANN was used with the Bayesian regularization training algorithm. The input variables of the neural network were pH, electrical conductivity, chloride (Cl(-)), calcium (Ca(2+)), total alkalinity, total hardness, nitrate nitrogen (NO3-N), and ammonical nitrogen (NH4-N). The ANN structure with 14 hidden neurons obtained the best selection. By making comparison between the results of the ANN model and the measured data on the basis of correlation coefficient (r) and root mean square error (RMSE), a good model-fitting DO values indicated the effectiveness of neural network model. It is found that the coefficient of correlation (r) values for the training, validation, and test sets were 0.9654, 0.9841, and 0.9680, respectively, and the respective values of RMSE for the training, validation, and test sets were 0.4272, 0.3667, and 0.4570, respectively. Sensitivity analysis was used to determine the influence of input variables on the dependent variable. The most effective inputs were determined as pH, NO3-N, NH4-N, and Ca(2+). Cl(-) was found to be least effective variables on the proposed model. The identified ANN model can be used to simulate the water quality parameters.

Ocean plankton. Determinants of community structure in the global plankton interactome.

PubMed

Lima-Mendez, Gipsi; Faust, Karoline; Henry, Nicolas; Decelle, Johan; Colin, Sébastien; Carcillo, Fabrizio; Chaffron, Samuel; Ignacio-Espinosa, J Cesar; Roux, Simon; Vincent, Flora; Bittner, Lucie; Darzi, Youssef; Wang, Jun; Audic, Stéphane; Berline, Léo; Bontempi, Gianluca; Cabello, Ana M; Coppola, Laurent; Cornejo-Castillo, Francisco M; d'Ovidio, Francesco; De Meester, Luc; Ferrera, Isabel; Garet-Delmas, Marie-José; Guidi, Lionel; Lara, Elena; Pesant, Stéphane; Royo-Llonch, Marta; Salazar, Guillem; Sánchez, Pablo; Sebastian, Marta; Souffreau, Caroline; Dimier, Céline; Picheral, Marc; Searson, Sarah; Kandels-Lewis, Stefanie; Gorsky, Gabriel; Not, Fabrice; Ogata, Hiroyuki; Speich, Sabrina; Stemmann, Lars; Weissenbach, Jean; Wincker, Patrick; Acinas, Silvia G; Sunagawa, Shinichi; Bork, Peer; Sullivan, Matthew B; Karsenti, Eric; Bowler, Chris; de Vargas, Colomban; Raes, Jeroen

2015-05-22

Species interaction networks are shaped by abiotic and biotic factors. Here, as part of the Tara Oceans project, we studied the photic zone interactome using environmental factors and organismal abundance profiles and found that environmental factors are incomplete predictors of community structure. We found associations across plankton functional types and phylogenetic groups to be nonrandomly distributed on the network and driven by both local and global patterns. We identified interactions among grazers, primary producers, viruses, and (mainly parasitic) symbionts and validated network-generated hypotheses using microscopy to confirm symbiotic relationships. We have thus provided a resource to support further research on ocean food webs and integrating biological components into ocean models. Copyright © 2015, American Association for the Advancement of Science.

A group evolving-based framework with perturbations for link prediction

NASA Astrophysics Data System (ADS)

Si, Cuiqi; Jiao, Licheng; Wu, Jianshe; Zhao, Jin

2017-06-01

Link prediction is a ubiquitous application in many fields which uses partially observed information to predict absence or presence of links between node pairs. The group evolving study provides reasonable explanations on the behaviors of nodes, relations between nodes and community formation in a network. Possible events in group evolution include continuing, growing, splitting, forming and so on. The changes discovered in networks are to some extent the result of these events. In this work, we present a group evolving-based characterization of node's behavioral patterns, and via which we can estimate the probability they tend to interact. In general, the primary aim of this paper is to offer a minimal toy model to detect missing links based on evolution of groups and give a simpler explanation on the rationality of the model. We first introduce perturbations into networks to obtain stable cluster structures, and the stable clusters determine the stability of each node. Then fluctuations, another node behavior, are assumed by the participation of each node to its own belonging group. Finally, we demonstrate that such characteristics allow us to predict link existence and propose a model for link prediction which outperforms many classical methods with a decreasing computational time in large scales. Encouraging experimental results obtained on real networks show that our approach can effectively predict missing links in network, and even when nearly 40% of the edges are missing, it also retains stationary performance.

Biologically Informed Individual-based Network Model for Rift Valley Fever in the US and Evaluation of Mitigation Strategies

USDA-ARS?s Scientific Manuscript database

Rift Valley fever (RVF) is a zoonotic disease endemic in Sub-Saharan Africa with periodic outbreaks in human and animal populations. Mosquitoes are the primary disease vectors; however, Rift Valley fever virus (RVFV) can also spread by direct contact with infected tissues. The transmission cycle is ...

A TDMA Broadcast Satellite/Ground Architecture for the Aeronautical Telecommunications Network

NASA Technical Reports Server (NTRS)

Shamma, Mohammed A.; Raghavan, Rajesh S.

2003-01-01

An initial evaluation of a TDMA satellite broadcast architecture with an integrated ground network is proposed in this study as one option for the Aeronautical Telecommunications Network (ATN). The architecture proposed consists of a ground based network that is dedicated to the reception and transmissions of Automatic Dependent Surveillance Broadcast (ADS-B) messages from Mode-S or UAT type systems, along with tracks from primary and secondary surveillance radars. Additionally, the ground network could contain VHF Digital Link Mode 2, 3 or 4 transceivers for the reception and transmissions of Controller-Pilot Data Link Communications (CPDLC) messages and for voice. The second part of the ATN network consists of a broadcast satellite based system that is mainly dedicated for the transmission of surveillance data as well as En-route Flight Information Service Broadcast (FIS-B) to all aircraft. The system proposed integrates those two network to provide a nation wide comprehensive service utilizing near term or existing technologies and hence keeping the economic factor in prospective. The next few sections include a background introduction, the ground subnetwork, the satellite subnetwork, modeling and simulations, and conclusion and recommendations.

Integration in primary community care networks (PCCNs): examination of governance, clinical, marketing, financial, and information infrastructures in a national demonstration project in Taiwan

PubMed Central

Lin, Blossom Yen-Ju

2007-01-01

Background Taiwan's primary community care network (PCCN) demonstration project, funded by the Bureau of National Health Insurance on March 2003, was established to discourage hospital shopping behavior of people and drive the traditional fragmented health care providers into cooperate care models. Between 2003 and 2005, 268 PCCNs were established. This study profiled the individual members in the PCCNs to study the nature and extent to which their network infrastructures have been integrated among the members (clinics and hospitals) within individual PCCNs. Methods The thorough questionnaire items, covering the network working infrastructures – governance, clinical, marketing, financial, and information integration in PCCNs, were developed with validity and reliability confirmed. One thousand five hundred and fifty-seven clinics that had belonged to PCCNs for more than one year, based on the 2003–2005 Taiwan Primary Community Care Network List, were surveyed by mail. Nine hundred and twenty-eight clinic members responded to the surveys giving a 59.6 % response rate. Results Overall, the PCCNs' members had higher involvement in the governance infrastructure, which was usually viewed as the most important for establishment of core values in PCCNs' organization design and management at the early integration stage. In addition, it found that there existed a higher extent of integration of clinical, marketing, and information infrastructures among the hospital-clinic member relationship than those among clinic members within individual PCCNs. The financial infrastructure was shown the least integrated relative to other functional infrastructures at the early stage of PCCN formation. Conclusion There was still room for better integrated partnerships, as evidenced by the great variety of relationships and differences in extent of integration in this study. In addition to provide how the network members have done for their initial work at the early stage of network forming in this study, the detailed surveyed items, the concepts proposed by the managerial and theoretical professionals, could be a guide for those health care providers who have willingness to turn their business into multi-organizations. PMID:17577422

Integration in primary community care networks (PCCNs): examination of governance, clinical, marketing, financial, and information infrastructures in a national demonstration project in Taiwan.

PubMed

Lin, Blossom Yen-Ju

2007-06-19

Taiwan's primary community care network (PCCN) demonstration project, funded by the Bureau of National Health Insurance on March 2003, was established to discourage hospital shopping behavior of people and drive the traditional fragmented health care providers into cooperate care models. Between 2003 and 2005, 268 PCCNs were established. This study profiled the individual members in the PCCNs to study the nature and extent to which their network infrastructures have been integrated among the members (clinics and hospitals) within individual PCCNs. The thorough questionnaire items, covering the network working infrastructures--governance, clinical, marketing, financial, and information integration in PCCNs, were developed with validity and reliability confirmed. One thousand five hundred and fifty-seven clinics that had belonged to PCCNs for more than one year, based on the 2003-2005 Taiwan Primary Community Care Network List, were surveyed by mail. Nine hundred and twenty-eight clinic members responded to the surveys giving a 59.6 % response rate. Overall, the PCCNs' members had higher involvement in the governance infrastructure, which was usually viewed as the most important for establishment of core values in PCCNs' organization design and management at the early integration stage. In addition, it found that there existed a higher extent of integration of clinical, marketing, and information infrastructures among the hospital-clinic member relationship than those among clinic members within individual PCCNs. The financial infrastructure was shown the least integrated relative to other functional infrastructures at the early stage of PCCN formation. There was still room for better integrated partnerships, as evidenced by the great variety of relationships and differences in extent of integration in this study. In addition to provide how the network members have done for their initial work at the early stage of network forming in this study, the detailed surveyed items, the concepts proposed by the managerial and theoretical professionals, could be a guide for those health care providers who have willingness to turn their business into multi-organizations.

Prediction of miRNA-mRNA associations in Alzheimer's disease mice using network topology.

PubMed

Noh, Haneul; Park, Charny; Park, Soojun; Lee, Young Seek; Cho, Soo Young; Seo, Hyemyung

2014-08-03

Little is known about the relationship between miRNA and mRNA expression in Alzheimer's disease (AD) at early- or late-symptomatic stages. Sequence-based target prediction algorithms and anti-correlation profiles have been applied to predict miRNA targets using omics data, but this approach often leads to false positive predictions. Here, we applied the joint profiling analysis of mRNA and miRNA expression levels to Tg6799 AD model mice at 4 and 8 months of age using a network topology-based method. We constructed gene regulatory networks and used the PageRank algorithm to predict significant interactions between miRNA and mRNA. In total, 8 cluster modules were predicted by the transcriptome data for co-expression networks of AD pathology. In total, 54 miRNAs were identified as being differentially expressed in AD. Among these, 50 significant miRNA-mRNA interactions were predicted by integrating sequence target prediction, expression analysis, and the PageRank algorithm. We identified a set of miRNA-mRNA interactions that were changed in the hippocampus of Tg6799 AD model mice. We determined the expression levels of several candidate genes and miRNA. For functional validation in primary cultured neurons from Tg6799 mice (MT) and littermate (LM) controls, the overexpression of ARRDC3 enhanced PPP1R3C expression. ARRDC3 overexpression showed the tendency to decrease the expression of miR139-5p and miR3470a in both LM and MT primary cells. Pathological environment created by Aβ treatment increased the gene expression of PPP1R3C and Sfpq but did not significantly alter the expression of miR139-5p or miR3470a. Aβ treatment increased the promoter activity of ARRDC3 gene in LM primary cells but not in MT primary cells. Our results demonstrate AD-specific changes in the miRNA regulatory system as well as the relationship between the expression levels of miRNAs and their targets in the hippocampus of Tg6799 mice. These data help further our understanding of the function and mechanism of various miRNAs and their target genes in the molecular pathology of AD.

How do people with dementia utilise primary care physicians and specialists within dementia networks? Results of the Dementia Networks in Germany (DemNet-D) study.

PubMed

Wübbeler, Markus; Thyrian, Jochen René; Michalowsky, Bernhard; Erdmann, Pia; Hertel, Johannes; Holle, Bernhard; Gräske, Johannes; Schäfer-Walkmann, Susanne; Hoffmann, Wolfgang

2017-01-01

Outpatient dementia healthcare is predominantly fragmented, and dementia networks (DNs) represent an integrated care concept to overcome this problem. Little is known about the patients of these networks with regard to utilisation of physicians and associated factors. We interviewed 560 caregivers of people with dementia in 13 different DNs in Germany in 2013 and assessed socio-demographics, clinical data and physician utilisation. Networks were categorised in predominantly medical DNs and community-oriented DNs. Descriptive and multivariate statistical models were used to identify associated factors between DNs and users' data. Overall, the users of networks received high rates of physician care; 93% of the sample stated at least one contact with a primary care physician within the last 6 months, and 74% had been treated by a specialist (neurology/psychiatry physician). Only 5% of the sample had no contact with a physician in the 6 months preceding the interview. Females showed a lower odds for physician specialist consultations (OR = 0.641). Users of medical DNs receive greater specialist consultations overall (OR = 8.370). Compared to the German general population and people with dementia in other settings, users of DNs receive physician care more regularly, especially with regard to the consultations of neurologist/psychiatrists. Therefore, DNs seem to perform a supportive role within the integration of physician healthcare. More research is needed on the appropriate relationship between the needs of the people with dementia and utilisation behaviour. © 2016 John Wiley & Sons Ltd.

Primary Health Care: care coordinator in regionalized networks?

PubMed Central

de Almeida, Patty Fidelis; dos Santos, Adriano Maia

2016-01-01

RESUMO OBJECTIVE To analyze the breadth of care coordination by Primary Health Care in three health regions. METHODS This is a quantitative and qualitative case study. Thirty-one semi-structured interviews with municipal, regional and state managers were carried out, besides a cross-sectional survey with the administration of questionnaires to physicians (74), nurses (127), and a representative sample of users (1,590) of Estratégia Saúde da Família (Family Health Strategy) in three municipal centers of health regions in the state of Bahia. RESULTS Primary Health Care as first contact of preference faced strong competition from hospital outpatient and emergency services outside the network. Issues related to access to and provision of specialized care were aggravated by dependence on the private sector in the regions, despite progress observed in institutionalizing flows starting out from Primary Health Care. The counter-referral system was deficient and interprofessional communication was scarce, especially concerning services provided by the contracted network. CONCLUSIONS Coordination capacity is affected both by the fragmentation of the regional network and intrinsic problems in Primary Health Care, which poorly supported in its essential attributes. Although the health regions have common problems, Primary Health Care remains a subject confined to municipal boundaries. PMID:28099663

Link Connectivity and Coverage of Underwater Cognitive Acoustic Networks under Spectrum Constraint

PubMed Central

Wang, Qiu; Cheang, Chak Fong

2017-01-01

Extensive attention has been given to the use of cognitive radio technology in underwater acoustic networks since the acoustic spectrum became scarce due to the proliferation of human aquatic activities. Most of the recent studies on underwater cognitive acoustic networks (UCANs) mainly focus on spectrum management or protocol design. Few efforts have addressed the quality-of-service (QoS) of UCANs. In UCANs, secondary users (SUs) have lower priority to use acoustic spectrum than primary users (PUs) with higher priority to access spectrum. As a result, the QoS of SUs is difficult to ensure in UCANs. This paper proposes an analytical model to investigate the link connectivity and the probability of coverage of SUs in UCANs. In particular, this model takes both topological connectivity and spectrum availability into account, though spectrum availability has been ignored in most recent studies. We conduct extensive simulations to evaluate the effectiveness and the accuracy of our proposed model. Simulation results show that our proposed model is quite accurate. Besides, our results also imply that the link connectivity and the probability of coverage of SUs heavily depend on both the underwater acoustic channel conditions and the activities of PUs. PMID:29215561

No longer simply a Practice-based Research Network (PBRN) health improvement networks.

PubMed

Williams, Robert L; Rhyne, Robert L

2011-01-01

While primary care Practice-based Research Networks are best known for their original, research purpose, evidence accumulating over the last several years is demonstrating broader values of these collaborations. Studies have demonstrated their role in quality improvement and practice change, in continuing professional education, in clinician retention in medically underserved areas, and in facilitating transition of primary care organization. A role in informing and facilitating health policy development is also suggested. Taking into account this more robust potential, we propose a new title, the Health Improvement Network, and a new vision for Practice-based Research Networks.

[Primary Health Care in Austria - Tu Felix Austria nube - Concept for networking in the primary care of Upper Austria].

PubMed

Kriegel, Johannes; Rebhandl, Erwin; Hockl, Wolfgang; Stöbich, Anna-Maria

2017-10-01

The primary health care in rural areas in Austria is currently determined by challenges such as ageing of the population, the shift towards chronic and age-related illnesses, the specialist medical and hospital-related education and training of physicians' as well growing widespread difficulty of staffing doctor's office. The objective is to realize a general practitioner centered and team-oriented primary health care (PHC) approach by establishing networked primary health care in rural areas of Austria. Using literature research, online survey, expert interviews and expert workshops, we identified different challenges in terms of primary health care in rural areas. Further, current resources and capacities of primary health care in rural areas were identified using the example of the district of Rohrbach. Twelve design dimensions and 51 relevant measurement indicators of a PHC network were delineated and described. Based on this, 12 design approaches of PHC concept for the GP-centered and team-oriented primary health care in rural areas have been developed.

Simulating secondary waterflooding in heterogeneous rocks with variable wettability using an image-based, multiscale pore network model

NASA Astrophysics Data System (ADS)

Bultreys, Tom; Van Hoorebeke, Luc; Cnudde, Veerle

2016-09-01

The two-phase flow properties of natural rocks depend strongly on their pore structure and wettability, both of which are often heterogeneous throughout the rock. To better understand and predict these properties, image-based models are being developed. Resulting simulations are however problematic in several important classes of rocks with broad pore-size distributions. We present a new multiscale pore network model to simulate secondary waterflooding in these rocks, which may undergo wettability alteration after primary drainage. This novel approach permits to include the effect of microporosity on the imbibition sequence without the need to describe each individual micropore. Instead, we show that fluid transport through unresolved pores can be taken into account in an upscaled fashion, by the inclusion of symbolic links between macropores, resulting in strongly decreased computational demands. Rules to describe the behavior of these links in the quasistatic invasion sequence are derived from percolation theory. The model is validated by comparison to a fully detailed network representation, which takes each separate micropore into account. Strongly and weakly water-and oil-wet simulations show good results, as do mixed-wettability scenarios with different pore-scale wettability distributions. We also show simulations on a network extracted from a micro-CT scan of Estaillades limestone, which yields good agreement with water-wet and mixed-wet experimental results.

Inference of gene regulatory networks from genome-wide knockout fitness data

PubMed Central

Wang, Liming; Wang, Xiaodong; Arkin, Adam P.; Samoilov, Michael S.

2013-01-01

Motivation: Genome-wide fitness is an emerging type of high-throughput biological data generated for individual organisms by creating libraries of knockouts, subjecting them to broad ranges of environmental conditions, and measuring the resulting clone-specific fitnesses. Since fitness is an organism-scale measure of gene regulatory network behaviour, it may offer certain advantages when insights into such phenotypical and functional features are of primary interest over individual gene expression. Previous works have shown that genome-wide fitness data can be used to uncover novel gene regulatory interactions, when compared with results of more conventional gene expression analysis. Yet, to date, few algorithms have been proposed for systematically using genome-wide mutant fitness data for gene regulatory network inference. Results: In this article, we describe a model and propose an inference algorithm for using fitness data from knockout libraries to identify underlying gene regulatory networks. Unlike most prior methods, the presented approach captures not only structural, but also dynamical and non-linear nature of biomolecular systems involved. A state–space model with non-linear basis is used for dynamically describing gene regulatory networks. Network structure is then elucidated by estimating unknown model parameters. Unscented Kalman filter is used to cope with the non-linearities introduced in the model, which also enables the algorithm to run in on-line mode for practical use. Here, we demonstrate that the algorithm provides satisfying results for both synthetic data as well as empirical measurements of GAL network in yeast Saccharomyces cerevisiae and TyrR–LiuR network in bacteria Shewanella oneidensis. Availability: MATLAB code and datasets are available to download at http://www.duke.edu/∼lw174/Fitness.zip and http://genomics.lbl.gov/supplemental/fitness-bioinf/ Contact: wangx@ee.columbia.edu or mssamoilov@lbl.gov Supplementary information: Supplementary data are available at Bioinformatics online PMID:23271269

Utilization-Based Modeling and Optimization for Cognitive Radio Networks

NASA Astrophysics Data System (ADS)

Liu, Yanbing; Huang, Jun; Liu, Zhangxiong

The cognitive radio technique promises to manage and allocate the scarce radio spectrum in the highly varying and disparate modern environments. This paper considers a cognitive radio scenario composed of two queues for the primary (licensed) users and cognitive (unlicensed) users. According to the Markov process, the system state equations are derived and an optimization model for the system is proposed. Next, the system performance is evaluated by calculations which show the rationality of our system model. Furthermore, discussions among different parameters for the system are presented based on the experimental results.

Establishing ecological networks for habitat conservation in the case of Çeşme-Urla Peninsula, Turkey.

PubMed

Hepcan, Ciğdem Coşkun; Ozkan, Mehmet Bülent

2011-03-01

The study involves the Çeşme-Urla Peninsula, where habitat fragmentation and loss, which threaten biological diversity, have become an urgent matter of concern in recent decades. The study area has been subjected to anthropogenic pressures and alterations due to ongoing and impending land uses. Therefore, ecological networks, as an appropriate way to deal with habitat fragmentation and loss and to improve ecological quality, were identified in the study area as one of the early attempts in the country to maintain its rich biodiversity. In this sense, core areas and ecological linkages as primary components of ecological networks were established on the basis of sustaining natural habitats. A GIS-based model was created to identify core areas and to facilitate the ecological connectivity. The modeling process for core areas and corridors combined 14 and 21 different variables, respectively. The variables were used as environmental inputs in the model, and all analyses were materialized in ArcGIS 9.2 using grid functions of image analysis and spatial analyst modules. As a result, six core areas and 36 corridor alternatives were materialized. Furthermore, some recommendations for the implementation and management of the proposed ecological networks were revealed and discussed.

Optogenetic stimulation of multiwell MEA plates for neural and cardiac applications

NASA Astrophysics Data System (ADS)

Clements, Isaac P.; Millard, Daniel C.; Nicolini, Anthony M.; Preyer, Amanda J.; Grier, Robert; Heckerling, Andrew; Blum, Richard A.; Tyler, Phillip; McSweeney, K. M.; Lu, Yi-Fan; Hall, Diana; Ross, James D.

2016-03-01

Microelectrode array (MEA) technology enables advanced drug screening and "disease-in-a-dish" modeling by measuring the electrical activity of cultured networks of neural or cardiac cells. Recent developments in human stem cell technologies, advancements in genetic models, and regulatory initiatives for drug screening have increased the demand for MEA-based assays. In response, Axion Biosystems previously developed a multiwell MEA platform, providing up to 96 MEA culture wells arrayed into a standard microplate format. Multiwell MEA-based assays would be further enhanced by optogenetic stimulation, which enables selective excitation and inhibition of targeted cell types. This capability for selective control over cell culture states would allow finer pacing and probing of cell networks for more reliable and complete characterization of complex network dynamics. Here we describe a system for independent optogenetic stimulation of each well of a 48-well MEA plate. The system enables finely graded control of light delivery during simultaneous recording of network activity in each well. Using human induced pluripotent stem cell (hiPSC) derived cardiomyocytes and rodent primary neuronal cultures, we demonstrate high channel-count light-based excitation and suppression in several proof-of-concept experimental models. Our findings demonstrate advantages of combining multiwell optical stimulation and MEA recording for applications including cardiac safety screening, neural toxicity assessment, and advanced characterization of complex neuronal diseases.

Yeast Phenomics: An Experimental Approach for Modeling Gene Interaction Networks that Buffer Disease

PubMed Central

Hartman, John L.; Stisher, Chandler; Outlaw, Darryl A.; Guo, Jingyu; Shah, Najaf A.; Tian, Dehua; Santos, Sean M.; Rodgers, John W.; White, Richard A.

2015-01-01

The genome project increased appreciation of genetic complexity underlying disease phenotypes: many genes contribute each phenotype and each gene contributes multiple phenotypes. The aspiration of predicting common disease in individuals has evolved from seeking primary loci to marginal risk assignments based on many genes. Genetic interaction, defined as contributions to a phenotype that are dependent upon particular digenic allele combinations, could improve prediction of phenotype from complex genotype, but it is difficult to study in human populations. High throughput, systematic analysis of S. cerevisiae gene knockouts or knockdowns in the context of disease-relevant phenotypic perturbations provides a tractable experimental approach to derive gene interaction networks, in order to deduce by cross-species gene homology how phenotype is buffered against disease-risk genotypes. Yeast gene interaction network analysis to date has revealed biology more complex than previously imagined. This has motivated the development of more powerful yeast cell array phenotyping methods to globally model the role of gene interaction networks in modulating phenotypes (which we call yeast phenomic analysis). The article illustrates yeast phenomic technology, which is applied here to quantify gene X media interaction at higher resolution and supports use of a human-like media for future applications of yeast phenomics for modeling human disease. PMID:25668739

[Primary Health Care in the coordination of health care networks: an integrative review].

PubMed

Rodrigues, Ludmila Barbosa Bandeira; Silva, Patricia Costa Dos Santos; Peruhype, Rarianne Carvalho; Palha, Pedro Fredemir; Popolin, Marcela Paschoal; Crispim, Juliane de Almeida; Pinto, Ione Carvalho; Monroe, Aline Aparecida; Arcêncio, Ricardo Alexandre

2014-02-01

Health systems organized in health care networks and coordinated by Primary Health Care can contribute to an improvement in clinical quality with a positive impact on health outcomes and user satisfaction (by improving access and resolubility) and a reduction in the costs of local health systems. Thus, the scope of this paper is to analyze the scientific output about the evidence, potential, challenges and prospects of Primary Health Care in the coordination of Health Care Networks. To achieve this, the integrative review method was selected covering the period between 2000 and 2011. The databases selected were Medline (Medical Literature Analysis and Retrieval System online), Lilacs (Latin American Literature in Health Sciences) and SciELO (Scientific Electronic Library Online). Eighteen articles fulfilled the selection criteria. It was seen that the potential impacts of primary care services supersede the inherent weaknesses. However, the results revealed the need for research with a higher level of classification of the scientific evidence about the role of Primary Healh Care in the coordination of Health Care Networks.

[Improving Health Care for Patients with Somatoform and Functional Disorders: A Collaborative Stepped Care Network (Sofu-Net)].

PubMed

Shedden-Mora, Meike; Lau, Katharina; Kuby, Amina; Groß, Beatrice; Gladigau, Maria; Fabisch, Alexandra; Löwe, Bernd

2015-07-01

The management of somatoform disorders in primary care is often limited due to low diagnostic accuracy, delayed referral to psychotherapy and overuse of health care. To address these difficulties, this study aimed to establish a collaborative stepped health care network (Sofu-Net). Sofu-Net was established among 41 primary care physicians, 35 psychotherapists and 8 mental health clinics. Baseline assessment in primary care showed elevated psychopathology and deficits in health care among patients with somatoform symptoms. Network partners provided positive evaluations of Sofu-Net. © Georg Thieme Verlag KG Stuttgart · New York.

Reducing Cancer Disparities Through Innovative Partnerships: A Collaboration of the South Carolina Cancer Prevention and Control Research Network and Federally Qualified Health Centers

PubMed Central

Young, Vicki M.; Freedman, Darcy A.; Adams, Swann Arp; Brandt, Heather M.; Xirasagar, Sudha; Felder, Tisha M.; Ureda, John R.; Hurley, Thomas; Khang, Leepao; Campbell, Dayna; Hébert, James R.

2011-01-01

The South Carolina Cancer Prevention and Control Research Network, in partnership with the South Carolina Primary Health Care Association, and Federally Qualified Health Centers (FQHCs), aims to promote evidence-based cancer interventions in community-based primary care settings. Partnership activities include (1) examining FQHCs’ readiness and capacity for conducting research, (2) developing a cancer-focused data sharing network, and (3) integrating a farmers’ market within an FQHC. These activities identify unique opportunities for public health and primary care collaborations. PMID:21932143

InFlo: a novel systems biology framework identifies cAMP-CREB1 axis as a key modulator of platinum resistance in ovarian cancer.

PubMed

Dimitrova, N; Nagaraj, A B; Razi, A; Singh, S; Kamalakaran, S; Banerjee, N; Joseph, P; Mankovich, A; Mittal, P; DiFeo, A; Varadan, V

2017-04-27

Characterizing the complex interplay of cellular processes in cancer would enable the discovery of key mechanisms underlying its development and progression. Published approaches to decipher driver mechanisms do not explicitly model tissue-specific changes in pathway networks and the regulatory disruptions related to genomic aberrations in cancers. We therefore developed InFlo, a novel systems biology approach for characterizing complex biological processes using a unique multidimensional framework integrating transcriptomic, genomic and/or epigenomic profiles for any given cancer sample. We show that InFlo robustly characterizes tissue-specific differences in activities of signalling networks on a genome scale using unique probabilistic models of molecular interactions on a per-sample basis. Using large-scale multi-omics cancer datasets, we show that InFlo exhibits higher sensitivity and specificity in detecting pathway networks associated with specific disease states when compared to published pathway network modelling approaches. Furthermore, InFlo's ability to infer the activity of unmeasured signalling network components was also validated using orthogonal gene expression signatures. We then evaluated multi-omics profiles of primary high-grade serous ovarian cancer tumours (N=357) to delineate mechanisms underlying resistance to frontline platinum-based chemotherapy. InFlo was the only algorithm to identify hyperactivation of the cAMP-CREB1 axis as a key mechanism associated with resistance to platinum-based therapy, a finding that we subsequently experimentally validated. We confirmed that inhibition of CREB1 phosphorylation potently sensitized resistant cells to platinum therapy and was effective in killing ovarian cancer stem cells that contribute to both platinum-resistance and tumour recurrence. Thus, we propose InFlo to be a scalable and widely applicable and robust integrative network modelling framework for the discovery of evidence-based biomarkers and therapeutic targets.

Network modulation during complex syntactic processing

PubMed Central

den Ouden, Dirk-Bart; Saur, Dorothee; Mader, Wolfgang; Schelter, Björn; Lukic, Sladjana; Wali, Eisha; Timmer, Jens; Thompson, Cynthia K.

2011-01-01

Complex sentence processing is supported by a left-lateralized neural network including inferior frontal cortex and posterior superior temporal cortex. This study investigates the pattern of connectivity and information flow within this network. We used fMRI BOLD data derived from 12 healthy participants reported in an earlier study (Thompson, C. K., Den Ouden, D. B., Bonakdarpour, B., Garibaldi, K., & Parrish, T. B. (2010b). Neural plasticity and treatment-induced recovery of sentence processing in agrammatism. Neuropsychologia, 48(11), 3211-3227) to identify activation peaks associated with object-cleft over syntactically less complex subject-cleft processing. Directed Partial Correlation Analysis was conducted on time series extracted from participant-specific activation peaks and showed evidence of functional connectivity between four regions, linearly between premotor cortex, inferior frontal gyrus, posterior superior temporal sulcus and anterior middle temporal gyrus. This pattern served as the basis for Dynamic Causal Modeling of networks with a driving input to posterior superior temporal cortex, which likely supports thematic role assignment, and networks with a driving input to inferior frontal cortex, a core region associated with syntactic computation. The optimal model was determined through both frequentist and Bayesian model selection and turned out to reflect a network with a primary drive from inferior frontal cortex and modulation of the connection between inferior frontal and posterior superior temporal cortex by complex sentence processing. The winning model also showed a substantive role for a feedback mechanism from posterior superior temporal cortex back to inferior frontal cortex. We suggest that complex syntactic processing is driven by word-order analysis, supported by inferior frontal cortex, in an interactive relation with posterior superior temporal cortex, which supports verb argument structure processing. PMID:21820518

Systemic delay propagation in the US airport network

PubMed Central

Fleurquin, Pablo; Ramasco, José J.; Eguiluz, Victor M.

2013-01-01

Technologically driven transport systems are characterized by a networked structure connecting operation centers and by a dynamics ruled by pre-established schedules. Schedules impose serious constraints on the timing of the operations, condition the allocation of resources and define a baseline to assess system performance. Here we study the performance of an air transportation system in terms of delays. Technical, operational or meteorological issues affecting some flights give rise to primary delays. When operations continue, such delays can propagate, magnify and eventually involve a significant part of the network. We define metrics able to quantify the level of network congestion and introduce a model that reproduces the delay propagation patterns observed in the U.S. performance data. Our results indicate that there is a non-negligible risk of systemic instability even under normal operating conditions. We also identify passenger and crew connectivity as the most relevant internal factor contributing to delay spreading. PMID:23362459

Mechanics of membrane bulging during cell-wall disruption in Gram-negative bacteria

NASA Astrophysics Data System (ADS)

Daly, Kristopher E.; Huang, Kerwyn Casey; Wingreen, Ned S.; Mukhopadhyay, Ranjan

2011-04-01

The bacterial cell wall is a network of sugar strands crosslinked by peptides that serve as the primary structure for bearing osmotic stress. Despite its importance in cellular survival, the robustness of the cell wall to network defects has been relatively unexplored. Treatment of the Gram-negative bacterium Escherichia coli with the antibiotic vancomycin, which disrupts the crosslinking of new material during growth, leads to the development of pronounced bulges and eventually of cell lysis. Here, we model the mechanics of the bulging of the cytoplasmic membrane through pores in the cell wall. We find that the membrane undergoes a transition between a nearly flat state and a spherical bulge at a critical pore radius of ~20 nm. This critical pore size is large compared to the typical distance between neighboring peptides and glycan strands, and hence pore size acts as a constraint on network integrity. We also discuss the general implications of our model to membrane deformations in eukaryotic blebbing and vesiculation in red blood cells.

Trophic network models explain instability of Early Triassic terrestrial communities

PubMed Central

Roopnarine, Peter D; Angielczyk, Kenneth D; Wang, Steve C; Hertog, Rachel

2007-01-01

Studies of the end-Permian mass extinction have emphasized potential abiotic causes and their direct biotic effects. Less attention has been devoted to secondary extinctions resulting from ecological crises and the effect of community structure on such extinctions. Here we use a trophic network model that combines topological and dynamic approaches to simulate disruptions of primary productivity in palaeocommunities. We apply the model to Permian and Triassic communities of the Karoo Basin, South Africa, and show that while Permian communities bear no evidence of being especially susceptible to extinction, Early Triassic communities appear to have been inherently less stable. Much of the instability results from the faster post-extinction diversification of amphibian guilds relative to amniotes. The resulting communities differed fundamentally in structure from their Permian predecessors. Additionally, our results imply that changing community structures over time may explain long-term trends like declining rates of Phanerozoic background extinction PMID:17609191

Motor deficits correlate with resting state motor network connectivity in patients with brain tumours

PubMed Central

Mikell, Charles B.; Youngerman, Brett E.; Liston, Conor; Sisti, Michael B.; Bruce, Jeffrey N.; Small, Scott A.; McKhann, Guy M.

2012-01-01

While a tumour in or abutting primary motor cortex leads to motor weakness, how tumours elsewhere in the frontal or parietal lobes affect functional connectivity in a weak patient is less clear. We hypothesized that diminished functional connectivity in a distributed network of motor centres would correlate with motor weakness in subjects with brain masses. Furthermore, we hypothesized that interhemispheric connections would be most vulnerable to subtle disruptions in functional connectivity. We used task-free functional magnetic resonance imaging connectivity to probe motor networks in control subjects and patients with brain tumours (n = 22). Using a control dataset, we developed a method for automated detection of key nodes in the motor network, including the primary motor cortex, supplementary motor area, premotor area and superior parietal lobule, based on the anatomic location of the hand-motor knob in the primary motor cortex. We then calculated functional connectivity between motor network nodes in control subjects, as well as patients with and without brain masses. We used this information to construct weighted, undirected graphs, which were then compared to variables of interest, including performance on a motor task, the grooved pegboard. Strong connectivity was observed within the identified motor networks between all nodes bilaterally, and especially between the primary motor cortex and supplementary motor area. Reduced connectivity was observed in subjects with motor weakness versus subjects with normal strength (P < 0.001). This difference was driven mostly by decreases in interhemispheric connectivity between the primary motor cortices (P < 0.05) and between the left primary motor cortex and the right premotor area (P < 0.05), as well as other premotor area connections. In the subjects without motor weakness, however, performance on the grooved pegboard did not relate to interhemispheric connectivity, but rather was inversely correlated with connectivity between the left premotor area and left supplementary motor area, for both the left and the right hands (P < 0.01). Finally, two subjects who experienced severe weakness following surgery for their brain tumours were followed longitudinally, and the subject who recovered showed reconstitution of her motor network at follow-up. The subject who was persistently weak did not reconstitute his motor network. Motor weakness in subjects with brain tumours that do not involve primary motor structures is associated with decreased connectivity within motor functional networks, particularly interhemispheric connections. Motor networks become weaker as the subjects become weaker, and may become strong again during motor recovery. PMID:22408270

Tufts academic health information network: concept and scenario.

PubMed

Stearns, N S

1986-04-01

Tufts University School of Medicine's new health sciences education building, the Arthur M. Sackler Center for Health Communications, will house a modern medical library and computer center, classrooms, auditoria, and media facilities. The building will also serve as the center for an information and communication network linking the medical school and adjacent New England Medical Center, Tufts' primary teaching hospital, with Tufts Associated Teaching Hospitals throughout New England. Ultimately, the Tufts network will join other gateway networks, information resource facilities, health care institutions, and medical schools throughout the world. The center and the network are intended to facilitate and improve the education of health professionals, the delivery of health care to patients, the conduct of research, and the implementation of administrative management approaches that should provide more efficient utilization of resources and save dollars. A model and scenario show how health care delivery and health care education are integrated through better use of information transfer technologies by health information specialists, practitioners, and educators.

Tufts academic health information network: concept and scenario.

PubMed Central

Stearns, N S

1986-01-01

Tufts University School of Medicine's new health sciences education building, the Arthur M. Sackler Center for Health Communications, will house a modern medical library and computer center, classrooms, auditoria, and media facilities. The building will also serve as the center for an information and communication network linking the medical school and adjacent New England Medical Center, Tufts' primary teaching hospital, with Tufts Associated Teaching Hospitals throughout New England. Ultimately, the Tufts network will join other gateway networks, information resource facilities, health care institutions, and medical schools throughout the world. The center and the network are intended to facilitate and improve the education of health professionals, the delivery of health care to patients, the conduct of research, and the implementation of administrative management approaches that should provide more efficient utilization of resources and save dollars. A model and scenario show how health care delivery and health care education are integrated through better use of information transfer technologies by health information specialists, practitioners, and educators. PMID:3708191

Global report on primary immunodeficiencies: 2018 update from the Jeffrey Modell Centers Network on disease classification, regional trends, treatment modalities, and physician reported outcomes.

PubMed

Modell, Vicki; Orange, Jordan S; Quinn, Jessica; Modell, Fred

2018-05-09

Primary immunodeficiencies (PI) are genetic defects of the immune system that result in chronic, serious, and often life-threatening infections, if not diagnosed and treated. Many patients with PI are undiagnosed, underdiagnosed, or misdiagnosed. In fact, recent studies have shown that PI may be more common than previously estimated and that as many as 1% of the population may be affected with a PI when all types and varieties are considered. In order to raise awareness of PI with the overall goal of reducing associated morbidity and mortality, the Jeffrey Modell Foundation (JMF) established a network of specialized centers that could better identify, diagnose, treat, and follow patients with PI disorders. Over the past decade, the Jeffrey Modell Centers Network (JMCN) has provided the infrastructure to accept referrals, provide diagnosis, and offer treatments. Currently, the network consists of 792 Expert Physicians at 358 institutions, in 277 cities, and 86 countries spanning 6 continents. JMF developed an annual survey for physician experts within the JMCN, using the categories and gene defects identified by the International Union of Immunological Societies Expert Committee for the Classification of PI, to report on the number of patients identified with PI; treatment modalities, including immunoglobulins, transplantation, and gene therapy; and data on gender and age. Center Directors also provided physician-reported outcomes and differentials pre- and post-diagnosis. The current physician-reported data reflect an increase in diagnosed patients, as well as those receiving treatment. Suspected patients are being identified and referred so that they can receive early and appropriate diagnosis and treatment. The significant increase in patients identified with a PI is due, in part, to expanding education and awareness initiatives, newborn screening, and the expansion of molecular diagnosis and sequencing. To our knowledge, this is the most extensive single physician report on patients with PI around the world.

Prediction of 5-year overall survival in cervical cancer patients treated with radical hysterectomy using computational intelligence methods.

PubMed

Obrzut, Bogdan; Kusy, Maciej; Semczuk, Andrzej; Obrzut, Marzanna; Kluska, Jacek

2017-12-12

Computational intelligence methods, including non-linear classification algorithms, can be used in medical research and practice as a decision making tool. This study aimed to evaluate the usefulness of artificial intelligence models for 5-year overall survival prediction in patients with cervical cancer treated by radical hysterectomy. The data set was collected from 102 patients with cervical cancer FIGO stage IA2-IIB, that underwent primary surgical treatment. Twenty-three demographic, tumor-related parameters and selected perioperative data of each patient were collected. The simulations involved six computational intelligence methods: the probabilistic neural network (PNN), multilayer perceptron network, gene expression programming classifier, support vector machines algorithm, radial basis function neural network and k-Means algorithm. The prediction ability of the models was determined based on the accuracy, sensitivity, specificity, as well as the area under the receiver operating characteristic curve. The results of the computational intelligence methods were compared with the results of linear regression analysis as a reference model. The best results were obtained by the PNN model. This neural network provided very high prediction ability with an accuracy of 0.892 and sensitivity of 0.975. The area under the receiver operating characteristics curve of PNN was also high, 0.818. The outcomes obtained by other classifiers were markedly worse. The PNN model is an effective tool for predicting 5-year overall survival in cervical cancer patients treated with radical hysterectomy.

Science of the science, drug discovery and artificial neural networks.

PubMed

Patel, Jigneshkumar

2013-03-01

Drug discovery process many times encounters complex problems, which may be difficult to solve by human intelligence. Artificial Neural Networks (ANNs) are one of the Artificial Intelligence (AI) technologies used for solving such complex problems. ANNs are widely used for primary virtual screening of compounds, quantitative structure activity relationship studies, receptor modeling, formulation development, pharmacokinetics and in all other processes involving complex mathematical modeling. Despite having such advanced technologies and enough understanding of biological systems, drug discovery is still a lengthy, expensive, difficult and inefficient process with low rate of new successful therapeutic discovery. In this paper, author has discussed the drug discovery science and ANN from very basic angle, which may be helpful to understand the application of ANN for drug discovery to improve efficiency.

Systematically Studying Kinase Inhibitor Induced Signaling Network Signatures by Integrating Both Therapeutic and Side Effects

PubMed Central

Shao, Hongwei; Peng, Tao; Ji, Zhiwei; Su, Jing; Zhou, Xiaobo

2013-01-01

Substantial effort in recent years has been devoted to analyzing data based large-scale biological networks, which provide valuable insight into the topologies of complex biological networks but are rarely context specific and cannot be used to predict the responses of cell signaling proteins to specific ligands or compounds. In this work, we proposed a novel strategy to investigate kinase inhibitor induced pathway signatures by integrating multiplex data in Library of Integrated Network-based Cellular Signatures (LINCS), e.g. KINOMEscan data and cell proliferation/mitosis imaging data. Using this strategy, we first established a PC9 cell line specific pathway model to investigate the pathway signatures in PC9 cell line when perturbed by a small molecule kinase inhibitor GW843682. This specific pathway revealed the role of PI3K/AKT in modulating the cell proliferation process and the absence of two anti-proliferation links, which indicated a potential mechanism of abnormal expansion in PC9 cell number. Incorporating the pathway model for side effects on primary human hepatocytes, it was used to screen 27 kinase inhibitors in LINCS database and PF02341066, known as Crizotinib, was finally suggested with an optimal concentration 4.6 uM to suppress PC9 cancer cell expansion while avoiding severe damage to primary human hepatocytes. Drug combination analysis revealed that the synergistic effect region can be predicted straightforwardly based on a threshold which is an inherent property of each kinase inhibitor. Furthermore, this integration strategy can be easily extended to other specific cell lines to be a powerful tool for drug screen before clinical trials. PMID:24339888

[The Bellagio Model: an evidence-informed, international framework for population-oriented primary care. First experiences].

PubMed

Schlette, Sophia; Lisac, Melanie; Wagner, Ed; Gensichen, Jochen

2009-01-01

The Bellagio Model for Population-oriented Primary Care is an evidence-informed framework to assess accessible care for sick, vulnerable, and healthy people. The model was developed in spring 2008 by a multidisciplinary group of 24 experts from nine countries. The purpose of their gathering was to determine success factors for effective 21st century primary care based on state-of-the-art research findings, models, and empirical experience, and to assist with its implementation in practice, management, and health policy. Against the backdrop of "partialization", fragmentation in open health care systems, and the growing numbers of chronically ill or fragile people or those in need of any other kind of care, today's health care systems do not provide the much needed anchor point for continuing coordination and assistance prior, during and following an episode of illness. The Bellagio Model consists of ten key elements, which can make a substantial contribution to identify and overcome current gaps in primary care by using a synergetic approach. These elements are Shared Leadership, Public Trust, Horizontal and Vertical Integration, Networking of Professionals, Standardized Measurement, Research and Development, Payment Mix, Infrastructure, Programmes for Practice Improvement, and Population-oriented Management. All of these elements, which have been identified as being equally necessary, are also alike in that they involve all those responsible for health care: providers, managers, and policymakers.

Petri Net computational modelling of Langerhans cell Interferon Regulatory Factor Network predicts their role in T cell activation.

PubMed

Polak, Marta E; Ung, Chuin Ying; Masapust, Joanna; Freeman, Tom C; Ardern-Jones, Michael R

2017-04-06

Langerhans cells (LCs) are able to orchestrate adaptive immune responses in the skin by interpreting the microenvironmental context in which they encounter foreign substances, but the regulatory basis for this has not been established. Utilising systems immunology approaches combining in silico modelling of a reconstructed gene regulatory network (GRN) with in vitro validation of the predictions, we sought to determine the mechanisms of regulation of immune responses in human primary LCs. The key role of Interferon regulatory factors (IRFs) as controllers of the human Langerhans cell response to epidermal cytokines was revealed by whole transcriptome analysis. Applying Boolean logic we assembled a Petri net-based model of the IRF-GRN which provides molecular pathway predictions for the induction of different transcriptional programmes in LCs. In silico simulations performed after model parameterisation with transcription factor expression values predicted that human LC activation of antigen-specific CD8 T cells would be differentially regulated by epidermal cytokine induction of specific IRF-controlled pathways. This was confirmed by in vitro measurement of IFN-γ production by activated T cells. As a proof of concept, this approach shows that stochastic modelling of a specific immune networks renders transcriptome data valuable for the prediction of functional outcomes of immune responses.

Air quality in California forests: current efforts to initiate biomonitoring with lichens.

Treesearch

Sarah Jovan

2002-01-01

The primary objective of the Forest Health Monitoring indicator project is to develop models that use the composition of epiphytic lichen communities to detect and monitor air quality in forests. The designs of existing air quality monitoring networks in California do not provide adequate representation of rural areas to assess impacts to forests. This article is...

Social Networking Sites and Cyberdemocracy: A New Model of Dialogic Interactivity and Political Moblization in the Case of South Korea

ERIC Educational Resources Information Center

Chun, Heasun

2013-01-01

The primary purpose of this study is to test whether dialogic interactions via SNSs can help revive political participation and help citizens to become involved in real-world politics. In a Tocquevillian sense, this study assumes a positive relationship between virtual associational life and political participation and therefore argues that SNSs…

A Spectrum Access Based on Quality of Service (QoS) in Cognitive Radio Networks.

PubMed

Zhai, Linbo; Wang, Hua; Gao, Chuangen

2016-01-01

The quality of service (QoS) is important issue for cognitive radio networks. In the cognitive radio system, the licensed users, also called primary users (PUs), are authorized to utilize the wireless spectrum, while unlicensed users, also called secondary users (SUs), are not authorized to use the wireless spectrum. SUs access the wireless spectrum opportunistically when the spectrum is idle. While SUs use an idle channel, the instance that PUs come back makes SUs terminate their communications and leave the current channel. Therefore, quality of service (QoS) is difficult to be ensured for SUs. In this paper, we first propose an analysis model to obtain QoS for cognitive radio networks such as blocking probability, completed traffic and termination probability of SUs. When the primary users use the channels frequently, QoS of SUs is difficult to be ensured, especially the termination probability. Then, we propose a channel reservation scheme to improve QoS of SUs. The scheme makes the terminated SUs move to the reserved channels and keep on communications. Simulation results show that our scheme can improve QoS of SUs especially the termination probability with a little cost of blocking probability in dynamic environment.

Virtual network computing: cross-platform remote display and collaboration software.

PubMed

Konerding, D E

1999-04-01

VNC (Virtual Network Computing) is a computer program written to address the problem of cross-platform remote desktop/application display. VNC uses a client/server model in which an image of the desktop of the server is transmitted to the client and displayed. The client collects mouse and keyboard input from the user and transmits them back to the server. The VNC client and server can run on Windows 95/98/NT, MacOS, and Unix (including Linux) operating systems. VNC is multi-user on Unix machines (any number of servers can be run are unrelated to the primary display of the computer), while it is effectively single-user on Macintosh and Windows machines (only one server can be run, displaying the contents of the primary display of the server). The VNC servers can be configured to allow more than one client to connect at one time, effectively allowing collaboration through the shared desktop. I describe the function of VNC, provide details of installation, describe how it achieves its goal, and evaluate the use of VNC for molecular modelling. VNC is an extremely useful tool for collaboration, instruction, software development, and debugging of graphical programs with remote users.

Hidden Markov models and other machine learning approaches in computational molecular biology

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

Baldi, P.

1995-12-31

This tutorial was one of eight tutorials selected to be presented at the Third International Conference on Intelligent Systems for Molecular Biology which was held in the United Kingdom from July 16 to 19, 1995. Computational tools are increasingly needed to process the massive amounts of data, to organize and classify sequences, to detect weak similarities, to separate coding from non-coding regions, and reconstruct the underlying evolutionary history. The fundamental problem in machine learning is the same as in scientific reasoning in general, as well as statistical modeling: to come up with a good model for the data. In thismore » tutorial four classes of models are reviewed. They are: Hidden Markov models; artificial Neural Networks; Belief Networks; and Stochastic Grammars. When dealing with DNA and protein primary sequences, Hidden Markov models are one of the most flexible and powerful alignments and data base searches. In this tutorial, attention is focused on the theory of Hidden Markov Models, and how to apply them to problems in molecular biology.« less

Results of a quantitative survey to explore both perceptions of the purposes of follow-up and preferences for methods of follow-up delivery among service users, primary care practitioners and specialist clinicians after cancer treatment.

PubMed

Frew, G; Smith, A; Zutshi, B; Young, N; Aggarwal, A; Jones, P; Kockelbergh, R; Richards, M; Maher, E J

2010-12-01

To ascertain perceptions of reasons for follow-up after cancer treatment among service users (patients and carers), primary care practitioners and specialist clinicians (doctors and specialist nurses) and to identify levels of preference for different models of follow-up and the effect of an individual's experience on preferred models. A national survey designed to meet the needs of each key respondent group was carried out after a structured literature review, an extensive consultation process and a pilot scheme. Respondents were asked to assess their degree of preference for 10 pre-selected indications for follow-up. Eight models of follow-up were also identified and respondents were asked to state their experience and preference for each type. The questionnaire was distributed nationally via the 34 cancer networks in England and was available both online and in hard copy (postal). The uptake for the electronic format was in the main by primary care practitioners and specialist clinicians. Service users preferred the paper (postal) format. The survey was also publicised through the primary care and patient partnership forums at a Cancer Network Development event. In total, 2928 responses were received, comprising service users (21% of the sample), primary care practitioners (32%) and specialist clinicians (47%). Eighty-six per cent of responses were received from the 10 strategic health authorities in England, with the remaining 14% from Scotland, Wales and The Isle of Man. The responses from Scotland, Wales and the Isle of Man generally occurred where they interfaced with English cancer networks or had been engaged through word of mouth by colleagues. Among all respondents the main aims of cancer follow-up were considered to be: (1) to monitor for early complications after treatment; (2) to detect recurrences early; (3) to detect late effects of treatment. The most commonly experienced method of follow-up among all respondent groups was outpatient review with a doctor. This was considered to be the most preferred follow-up option among service users (86%). The least preferred option among service users was postal follow-up (32%). Primary care practitioners and specialist clinicians were more likely than service users to have experienced alternative methods of follow-up, such as telephone follow-up, self-triggered referral and non-specialist follow-up. These models were highly rated by those who had experience of them. There was a reasonable level of consensus between service users, primary care practitioners and specialist clinicians as to the reasons for follow-up. Service users seemed to have higher expectations of follow-up, particularly in relation to detecting recurrences early. As respondents were more likely to prefer a method of follow-up delivery that they had experienced than one they had not; there could be resistance to change from established methods to new methods without adequate explanation. This suggests that the communication of new methods could be critical to their successful introduction. Copyright © 2010 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Body representations in the human brain revealed by kinesthetic illusions and their essential contributions to motor control and corporeal awareness.

PubMed

Naito, Eiichi; Morita, Tomoyo; Amemiya, Kaoru

2016-03-01

The human brain can generate a continuously changing postural model of our body. Somatic (proprioceptive) signals from skeletal muscles and joints contribute to the formation of the body representation. Recent neuroimaging studies of proprioceptive bodily illusions have elucidated the importance of three brain systems (motor network, specialized parietal systems, right inferior fronto-parietal network) in the formation of the human body representation. The motor network, especially the primary motor cortex, processes afferent input from skeletal muscles. Such information may contribute to the formation of kinematic/dynamic postural models of limbs, thereby enabling fast online feedback control. Distinct parietal regions appear to play specialized roles in the transformation/integration of information across different coordinate systems, which may subserve the adaptability and flexibility of the body representation. Finally, the right inferior fronto-parietal network, connected by the inferior branch of the superior longitudinal fasciculus, is consistently recruited when an individual experiences various types of bodily illusions and its possible roles relate to corporeal awareness, which is likely elicited through a series of neuronal processes of monitoring and accumulating bodily information and updating the body representation. Because this network is also recruited when identifying one's own features, the network activity could be a neuronal basis for self-consciousness. Copyright © 2015 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

Neural electrical activity and neural network growth.

PubMed

Gafarov, F M

2018-05-01

The development of central and peripheral neural system depends in part on the emergence of the correct functional connectivity in its input and output pathways. Now it is generally accepted that molecular factors guide neurons to establish a primary scaffold that undergoes activity-dependent refinement for building a fully functional circuit. However, a number of experimental results obtained recently shows that the neuronal electrical activity plays an important role in the establishing of initial interneuronal connections. Nevertheless, these processes are rather difficult to study experimentally, due to the absence of theoretical description and quantitative parameters for estimation of the neuronal activity influence on growth in neural networks. In this work we propose a general framework for a theoretical description of the activity-dependent neural network growth. The theoretical description incorporates a closed-loop growth model in which the neural activity can affect neurite outgrowth, which in turn can affect neural activity. We carried out the detailed quantitative analysis of spatiotemporal activity patterns and studied the relationship between individual cells and the network as a whole to explore the relationship between developing connectivity and activity patterns. The model, developed in this work will allow us to develop new experimental techniques for studying and quantifying the influence of the neuronal activity on growth processes in neural networks and may lead to a novel techniques for constructing large-scale neural networks by self-organization. Copyright © 2018 Elsevier Ltd. All rights reserved.

Assessing sensory versus optogenetic network activation by combining (o)fMRI with optical Ca2+ recordings.

PubMed

Schmid, Florian; Wachsmuth, Lydia; Schwalm, Miriam; Prouvot, Pierre-Hugues; Jubal, Eduardo Rosales; Fois, Consuelo; Pramanik, Gautam; Zimmer, Claus; Faber, Cornelius; Stroh, Albrecht

2016-11-01

Encoding of sensory inputs in the cortex is characterized by sparse neuronal network activation. Optogenetic stimulation has previously been combined with fMRI (ofMRI) to probe functional networks. However, for a quantitative optogenetic probing of sensory-driven sparse network activation, the level of similarity between sensory and optogenetic network activation needs to be explored. Here, we complement ofMRI with optic fiber-based population Ca 2+ recordings for a region-specific readout of neuronal spiking activity in rat brain. Comparing Ca 2+ responses to the blood oxygenation level-dependent signal upon sensory stimulation with increasing frequencies showed adaptation of Ca 2+ transients contrasted by an increase of blood oxygenation level-dependent responses, indicating that the optical recordings convey complementary information on neuronal network activity to the corresponding hemodynamic response. To study the similarity of optogenetic and sensory activation, we quantified the density of cells expressing channelrhodopsin-2 and modeled light propagation in the tissue. We estimated the effectively illuminated volume and numbers of optogenetically stimulated neurons, being indicative of sparse activation. At the functional level, upon either sensory or optogenetic stimulation we detected single-peak short-latency primary Ca 2+ responses with similar amplitudes and found that blood oxygenation level-dependent responses showed similar time courses. These data suggest that ofMRI can serve as a representative model for functional brain mapping. © The Author(s) 2015.

Technologies and Approaches to Elucidate and Model the Virulence Program of Salmonella.

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

McDermott, Jason E.; Yoon, Hyunjin; Nakayasu, Ernesto S.

Salmonella is a primary cause of enteric diseases in a variety of animals. During its evolution into a pathogenic bacterium, Salmonella acquired an elaborate regulatory network that responds to multiple environmental stimuli within host animals and integrates them resulting in fine regulation of the virulence program. The coordinated action by this regulatory network involves numerous virulence regulators, necessitating genome-wide profiling analysis to assess and combine efforts from multiple regulons. In this review we discuss recent high-throughput analytic approaches to understand the regulatory network of Salmonella that controls virulence processes. Application of high-throughput analyses have generated a large amount of datamore » and driven development of computational approaches required for data integration. Therefore, we also cover computer-aided network analyses to infer regulatory networks, and demonstrate how genome-scale data can be used to construct regulatory and metabolic systems models of Salmonella pathogenesis. Genes that are coordinately controlled by multiple virulence regulators under infectious conditions are more likely to be important for pathogenesis. Thus, reconstructing the global regulatory network during infection or, at the very least, under conditions that mimic the host cellular environment not only provides a bird’s eye view of Salmonella survival strategy in response to hostile host environments but also serves as an efficient means to identify novel virulence factors that are essential for Salmonella to accomplish systemic infection in the host.« less

Deriving a light use efficiency model from eddy covariance flux data for predicting daily gross primary production across biomes

USGS Publications Warehouse

Yuan, W.; Liu, S.; Zhou, G.; Tieszen, L.L.; Baldocchi, D.; Bernhofer, C.; Gholz, H.; Goldstein, Allen H.; Goulden, M.L.; Hollinger, D.Y.; Hu, Y.; Law, B.E.; Stoy, Paul C.; Vesala, T.; Wofsy, S.C.

2007-01-01

The quantitative simulation of gross primary production (GPP) at various spatial and temporal scales has been a major challenge in quantifying the global carbon cycle. We developed a light use efficiency (LUE) daily GPP model from eddy covariance (EC) measurements. The model, called EC-LUE, is driven by only four variables: normalized difference vegetation index (NDVI), photosynthetically active radiation (PAR), air temperature, and the Bowen ratio of sensible to latent heat flux (used to calculate moisture stress). The EC-LUE model relies on two assumptions: First, that the fraction of absorbed PAR (fPAR) is a linear function of NDVI; Second, that the realized light use efficiency, calculated from a biome-independent invariant potential LUE, is controlled by air temperature or soil moisture, whichever is most limiting. The EC-LUE model was calibrated and validated using 24,349 daily GPP estimates derived from 28 eddy covariance flux towers from the AmeriFlux and EuroFlux networks, covering a variety of forests, grasslands and savannas. The model explained 85% and 77% of the observed variations of daily GPP for all the calibration and validation sites, respectively. A comparison with GPP calculated from the Moderate Resolution Imaging Spectroradiometer (MODIS) indicated that the EC-LUE model predicted GPP that better matched tower data across these sites. The realized LUE was predominantly controlled by moisture conditions throughout the growing season, and controlled by temperature only at the beginning and end of the growing season. The EC-LUE model is an alternative approach that makes it possible to map daily GPP over large areas because (1) the potential LUE is invariant across various land cover types and (2) all driving forces of the model can be derived from remote sensing data or existing climate observation networks.

A Binomial Modeling Approach for Upscaling Colloid Transport Under Unfavorable Attachment Conditions: Emergent Prediction of Nonmonotonic Retention Profiles

NASA Astrophysics Data System (ADS)

Hilpert, Markus; Johnson, William P.

2018-01-01

We used a recently developed simple mathematical network model to upscale pore-scale colloid transport information determined under unfavorable attachment conditions. Classical log-linear and nonmonotonic retention profiles, both well-reported under favorable and unfavorable attachment conditions, respectively, emerged from our upscaling. The primary attribute of the network is colloid transfer between bulk pore fluid, the near-surface fluid domain (NSFD), and attachment (treated as irreversible). The network model accounts for colloid transfer to the NSFD of downgradient grains and for reentrainment to bulk pore fluid via diffusion or via expulsion at rear flow stagnation zones (RFSZs). The model describes colloid transport by a sequence of random trials in a one-dimensional (1-D) network of Happel cells, which contain a grain and a pore. Using combinatorial analysis that capitalizes on the binomial coefficient, we derived from the pore-scale information the theoretical residence time distribution of colloids in the network. The transition from log-linear to nonmonotonic retention profiles occurs when the conditions underlying classical filtration theory are not fulfilled, i.e., when an NSFD colloid population is maintained. Then, nonmonotonic retention profiles result potentially both for attached and NSFD colloids. The concentration maxima shift downgradient depending on specific parameter choice. The concentration maxima were also shown to shift downgradient temporally (with continued elution) under conditions where attachment is negligible, explaining experimentally observed downgradient transport of retained concentration maxima of adhesion-deficient bacteria. For the case of zero reentrainment, we develop closed-form, analytical expressions for the shape, and the maximum of the colloid retention profile.

A vascular biology network model focused on inflammatory processes to investigate atherogenesis and plaque instability

PubMed Central

2014-01-01

Background Numerous inflammation-related pathways have been shown to play important roles in atherogenesis. Rapid and efficient assessment of the relative influence of each of those pathways is a challenge in the era of “omics” data generation. The aim of the present work was to develop a network model of inflammation-related molecular pathways underlying vascular disease to assess the degree of translatability of preclinical molecular data to the human clinical setting. Methods We constructed and evaluated the Vascular Inflammatory Processes Network (V-IPN), a model representing a collection of vascular processes modulated by inflammatory stimuli that lead to the development of atherosclerosis. Results Utilizing the V-IPN as a platform for biological discovery, we have identified key vascular processes and mechanisms captured by gene expression profiling data from four independent datasets from human endothelial cells (ECs) and human and murine intact vessels. Primary ECs in culture from multiple donors revealed a richer mapping of mechanisms identified by the V-IPN compared to an immortalized EC line. Furthermore, an evaluation of gene expression datasets from aortas of old ApoE-/- mice (78 weeks) and human coronary arteries with advanced atherosclerotic lesions identified significant commonalities in the two species, as well as several mechanisms specific to human arteries that are consistent with the development of unstable atherosclerotic plaques. Conclusions We have generated a new biological network model of atherogenic processes that demonstrates the power of network analysis to advance integrative, systems biology-based knowledge of cross-species translatability, plaque development and potential mechanisms leading to plaque instability. PMID:24965703

Statistical Neurodynamics.

NASA Astrophysics Data System (ADS)

Paine, Gregory Harold

1982-03-01

The primary objective of the thesis is to explore the dynamical properties of small nerve networks by means of the methods of statistical mechanics. To this end, a general formalism is developed and applied to elementary groupings of model neurons which are driven by either constant (steady state) or nonconstant (nonsteady state) forces. Neuronal models described by a system of coupled, nonlinear, first-order, ordinary differential equations are considered. A linearized form of the neuronal equations is studied in detail. A Lagrange function corresponding to the linear neural network is constructed which, through a Legendre transformation, provides a constant of motion. By invoking the Maximum-Entropy Principle with the single integral of motion as a constraint, a probability distribution function for the network in a steady state can be obtained. The formalism is implemented for some simple networks driven by a constant force; accordingly, the analysis focuses on a study of fluctuations about the steady state. In particular, a network composed of N noninteracting neurons, termed Free Thinkers, is considered in detail, with a view to interpretation and numerical estimation of the Lagrange multiplier corresponding to the constant of motion. As an archetypical example of a net of interacting neurons, the classical neural oscillator, consisting of two mutually inhibitory neurons, is investigated. It is further shown that in the case of a network driven by a nonconstant force, the Maximum-Entropy Principle can be applied to determine a probability distribution functional describing the network in a nonsteady state. The above examples are reconsidered with nonconstant driving forces which produce small deviations from the steady state. Numerical studies are performed on simplified models of two physical systems: the starfish central nervous system and the mammalian olfactory bulb. Discussions are given as to how statistical neurodynamics can be used to gain a better understanding of the behavior of these systems.

Early-life exposure to caffeine affects the construction and activity of cortical networks in mice.

PubMed

Fazeli, Walid; Zappettini, Stefania; Marguet, Stephan Lawrence; Grendel, Jasper; Esclapez, Monique; Bernard, Christophe; Isbrandt, Dirk

2017-09-01

The consumption of psychoactive drugs during pregnancy can have deleterious effects on newborns. It remains unclear whether early-life exposure to caffeine, the most widely consumed psychoactive substance, alters brain development. We hypothesized that maternal caffeine ingestion during pregnancy and the early postnatal period in mice affects the construction and activity of cortical networks in offspring. To test this hypothesis, we focused on primary visual cortex (V1) as a model neocortical region. In a study design mimicking the daily consumption of approximately three cups of coffee during pregnancy in humans, caffeine was added to the drinking water of female mice and their offspring were compared to control offspring. Caffeine altered the construction of GABAergic neuronal networks in V1, as reflected by a reduced number of somatostatin-containing GABA neurons at postnatal days 6-7, with the remaining ones showing poorly developed dendritic arbors. These findings were accompanied by increased synaptic activity in vitro and elevated network activity in vivo in V1. Similarly, in vivo hippocampal network activity was altered from the neonatal period until adulthood. Finally, caffeine-exposed offspring showed increased seizure susceptibility in a hyperthermia-induced seizure model. In summary, our results indicate detrimental effects of developmental caffeine exposure on mouse brain development. Copyright © 2017 Elsevier Inc. All rights reserved.

Fuzzy logic and neural networks in artificial intelligence and pattern recognition

NASA Astrophysics Data System (ADS)

Sanchez, Elie

1991-10-01

With the use of fuzzy logic techniques, neural computing can be integrated in symbolic reasoning to solve complex real world problems. In fact, artificial neural networks, expert systems, and fuzzy logic systems, in the context of approximate reasoning, share common features and techniques. A model of Fuzzy Connectionist Expert System is introduced, in which an artificial neural network is designed to construct the knowledge base of an expert system from, training examples (this model can also be used for specifications of rules in fuzzy logic control). Two types of weights are associated with the synaptic connections in an AND-OR structure: primary linguistic weights, interpreted as labels of fuzzy sets, and secondary numerical weights. Cell activation is computed through min-max fuzzy equations of the weights. Learning consists in finding the (numerical) weights and the network topology. This feedforward network is described and first illustrated in a biomedical application (medical diagnosis assistance from inflammatory-syndromes/proteins profiles). Then, it is shown how this methodology can be utilized for handwritten pattern recognition (characters play the role of diagnoses): in a fuzzy neuron describing a number for example, the linguistic weights represent fuzzy sets on cross-detecting lines and the numerical weights reflect the importance (or weakness) of connections between cross-detecting lines and characters.

Integrating System Dynamics and Bayesian Networks with Application to Counter-IED Scenarios

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

Jarman, Kenneth D.; Brothers, Alan J.; Whitney, Paul D.

2010-06-06

The practice of choosing a single modeling paradigm for predictive analysis can limit the scope and relevance of predictions and their utility to decision-making processes. Considering multiple modeling methods simultaneously may improve this situation, but a better solution provides a framework for directly integrating different, potentially complementary modeling paradigms to enable more comprehensive modeling and predictions, and thus better-informed decisions. The primary challenges of this kind of model integration are to bridge language and conceptual gaps between modeling paradigms, and to determine whether natural and useful linkages can be made in a formal mathematical manner. To address these challenges inmore » the context of two specific modeling paradigms, we explore mathematical and computational options for linking System Dynamics (SD) and Bayesian network (BN) models and incorporating data into the integrated models. We demonstrate that integrated SD/BN models can naturally be described as either state space equations or Dynamic Bayes Nets, which enables the use of many existing computational methods for simulation and data integration. To demonstrate, we apply our model integration approach to techno-social models of insurgent-led attacks and security force counter-measures centered on improvised explosive devices.« less

Multi-Objective Design Of Optimal Greenhouse Gas Observation Networks

NASA Astrophysics Data System (ADS)

Lucas, D. D.; Bergmann, D. J.; Cameron-Smith, P. J.; Gard, E.; Guilderson, T. P.; Rotman, D.; Stolaroff, J. K.

2010-12-01

One of the primary scientific functions of a Greenhouse Gas Information System (GHGIS) is to infer GHG source emission rates and their uncertainties by combining measurements from an observational network with atmospheric transport modeling. Certain features of the observational networks that serve as inputs to a GHGIS --for example, sampling location and frequency-- can greatly impact the accuracy of the retrieved GHG emissions. Observation System Simulation Experiments (OSSEs) provide a framework to characterize emission uncertainties associated with a given network configuration. By minimizing these uncertainties, OSSEs can be used to determine optimal sampling strategies. Designing a real-world GHGIS observing network, however, will involve multiple, conflicting objectives; there will be trade-offs between sampling density, coverage and measurement costs. To address these issues, we have added multi-objective optimization capabilities to OSSEs. We demonstrate these capabilities by quantifying the trade-offs between retrieval error and measurement costs for a prototype GHGIS, and deriving GHG observing networks that are Pareto optimal. [LLNL-ABS-452333: This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Organization of managed clinical networking for home parenteral nutrition.

PubMed

Baxter, Janet P; McKee, Ruth F

2006-05-01

Home parenteral nutrition (HPN) is an established treatment for intestinal failure, and organization of HPN is variable throughout the UK and Europe. Managed clinical networking is the single most important feature of the UK National Health Service strategy for acute services in Scotland and has the potential to improve the management of HPN patients. This review addresses the role of managed clinical networking in HPN and compares outcome data between centres. The Scottish HPN Managed Clinical Network has published the main body of the current literature supporting the concept of managed clinical networking in this context. The Network is responsible for the organization and quality assurance of HPN provision in Scotland, and has been established for 5 years. It has captured significant patient data for the purpose of clinical audit and illustrates that this is an effective model for the management of this patient population. This review provides advice for other areas wishing to improve equity of access, and to smooth the patient journey between primary, secondary and tertiary health care in the context of artificial nutrition support.

Distribution of Orientation Selectivity in Recurrent Networks of Spiking Neurons with Different Random Topologies

PubMed Central

Sadeh, Sadra; Rotter, Stefan

2014-01-01

Neurons in the primary visual cortex are more or less selective for the orientation of a light bar used for stimulation. A broad distribution of individual grades of orientation selectivity has in fact been reported in all species. A possible reason for emergence of broad distributions is the recurrent network within which the stimulus is being processed. Here we compute the distribution of orientation selectivity in randomly connected model networks that are equipped with different spatial patterns of connectivity. We show that, for a wide variety of connectivity patterns, a linear theory based on firing rates accurately approximates the outcome of direct numerical simulations of networks of spiking neurons. Distance dependent connectivity in networks with a more biologically realistic structure does not compromise our linear analysis, as long as the linearized dynamics, and hence the uniform asynchronous irregular activity state, remain stable. We conclude that linear mechanisms of stimulus processing are indeed responsible for the emergence of orientation selectivity and its distribution in recurrent networks with functionally heterogeneous synaptic connectivity. PMID:25469704

Salience network dynamics underlying successful resistance of temptation

PubMed Central

Nomi, Jason S; Calhoun, Vince D; Stelzel, Christine; Paschke, Lena M; Gaschler, Robert; Goschke, Thomas; Walter, Henrik; Uddin, Lucina Q

2017-01-01

Abstract Self-control and the ability to resist temptation are critical for successful completion of long-term goals. Contemporary models in cognitive neuroscience emphasize the primary role of prefrontal cognitive control networks in aligning behavior with such goals. Here, we use gaze pattern analysis and dynamic functional connectivity fMRI data to explore how individual differences in the ability to resist temptation are related to intrinsic brain dynamics of the cognitive control and salience networks. Behaviorally, individuals exhibit greater gaze distance from target location (e.g. higher distractibility) during presentation of tempting erotic images compared with neutral images. Individuals whose intrinsic dynamic functional connectivity patterns gravitate toward configurations in which salience detection systems are less strongly coupled with visual systems resist tempting distractors more effectively. The ability to resist tempting distractors was not significantly related to intrinsic dynamics of the cognitive control network. These results suggest that susceptibility to temptation is governed in part by individual differences in salience network dynamics and provide novel evidence for involvement of brain systems outside canonical cognitive control networks in contributing to individual differences in self-control. PMID:29048582

Hypergravity Loading the Cultured Osteoblasts: Modeling and Experimental Analysis of Cellular Morphology and the Cytoskeleton

NASA Technical Reports Server (NTRS)

Searby, N. D.; Steele, C. R.; Globus, R. K.; Dalton, Bonnie P. (Technical Monitor)

2001-01-01

Bone forming cells, osteoblasts, respond to various mechanical forces, including mechanical strain and fluid-induced shear stress. This study examined whether osteoblasts detect changes in gravity as a mechanical force, as assessed by cellular morphology and dimensions of the cytoskeletal network. We used modeling to evaluate how gravity influences cell morphology given theoretical differences in densities between the surrounding medium, cytoplasm, and nucleus. A mechanical model was built based on analysis of axisymmetric shell structures (Fast4 software) to study the effects of 10 times gravity (10G) on cell height. The model indicated 0.02% decrease in overall cell height when the medium was 10% denser than the nucleus or cytoplasm, 5.9 x 10(exp-5)% decrease when the nucleus was 10% denser than the cytoplasm or medium, and 1.3 x 10(exp-5)% decrease when the cell cytoplasm was 10% denser than the nucleus or medium. To experimentally evaluate the influence of gravity, cultured primary fetal rat osteoblasts were grown to near confluence and centrifuged at 10G for 3 hours. Actin, microtubules, and nuclei were fluorescently labeled and analyzed by confocal microscopy to determine overall microtubule and actin network height. Centrifugation led to an apparent reduction in height of both the microtubule (-16%) and the actin (-20%) networks relative to stationary controls. Thus, both modeling and experiments indicate that hypergravity reduces the height of the osteoblast cell layer and their microtubule and actin networks. This combination of modeling and experimental analyses will help us to better understand the mechanical loading of osteoblasts.

Increasing research capacity and changing the culture of primary care towards reflective inquiring practice: the experience of the West London Research Network (WeLReN).

PubMed

Thomas, P; While, A

2001-05-01

A number of primary care research networks were set up throughout England in 1998 in order to (1) improve the quality of primary care research (2) increase the research capacity of primary care, and (3) change the culture of primary care towards reflective inquiring practice (NHSE, 2000b). It is not clear how best to operate a network to achieve these diverse aims. This paper describes the first 30 months of a network that adopted a whole system approach in the belief that this would offer the best chance of simultaneously achieving the three aims. A cycle of activity was designed to facilitate the formation of multidisciplinary coalitions of interest for research with complementary 'top down' and 'bottom up' programmes of work co-existing. At least 330 people participated in the generation of research questions of whom one third (33%) were general practitioners, 16% community nurses, 6% practice managers and other primary care practitioners. Over two fifths (43%) were 'key allies'--academics, health authority staff, community workers and project workers. One fifth (110) of all practices (500) in the WeLReN area have collaborated in at least one research project. The ratio of doctor:nurse participation in the 24 research project teams was markedly different in the supported coalitions (2:1) compared to projects devised and led by more experienced researchers (6:1). The evidence suggests that it is possible to operate a primary care research network in a way that develops coalitions of interest from different parts of the health care system as well as both 'top down' and 'bottom up' led projects. It is too early to tell if the approach will be able to achieve its aims in the long-term but the activity data are encouraging. There is a need for more research on the theoretical basis of network operation.

Groundwater-Surface water interaction in agricultural watershed that encompasses dense network of High Capacity wells

NASA Astrophysics Data System (ADS)

Talib, A.; Desai, A. R.

2017-12-01

The Central Sands region of Wisconsin is characterized by productive trout streams, lakes, farmland and forest. However, stream channelization, past wetland drainage, and ground water withdrawals have disrupted the hydrology of this Central Sands region. Climatically driven conditions in last decade (2000-2008) alone are unable to account for the severely depressed water levels. Increased interception and evapotranspiration from afforested areas in central sand Wisconsin may also be culprit for reduced water recharge. Hence, there is need to study the cumulative effects of changing precipitation patterns, groundwater withdrawals, and forest evapotranspiration to improve projections of the future of lake levels and water availability in this region. Here, the SWAT-MODFLOW coupled model approach was applied at large spatio-temporal scale. The coupled model fully integrates a watershed model (SWAT) with a groundwater flow model (MODFLOW). Surface water and ground water flows were simulated integratively at daily time step to estimate the groundwater discharge to the stream network in Central Sands that encompasses high capacity wells. The model was calibrated (2010-2013) and validated (2014-2017) based on streamflow, groundwater extraction, and water table elevation. As the long-term trends in some of the primary drivers is presently ambiguous in Central Sands under future climate, as is the case for total precipitation or timing of precipitation, we relied on a sensitivity student to quantitatively access how primary and secondary drivers may influence future net groundwater recharge. We demonstrate how such an approach could then be coupled with decision-making models to evaluate the effectiveness of groundwater withdrawal policies under a changing climate.

On a European collaboration to identify organizational models, potential shortcomings and improvement options in out-of-hours primary health care.

PubMed

Leutgeb, Ruediger; Walker, Nicola; Remmen, Roy; Klemenc-Ketis, Zalika; Szecsenyi, Joachim; Laux, Gunter

2014-09-01

Abstract Background: Out-of-hours care (OOHC) provision is an increasingly challenging aspect in the delivery of primary health care services. Although many European countries have implemented organizational models for out-of-hours primary care, which has been traditionally delivered by general practitioners, health care providers throughout Europe are still looking to resolve current challenges in OOHC. It is within this context that the European Research Network for Out-of-Hours Primary Health Care (EurOOHnet) was established in 2010 to investigate the provision of out-of-hours care across European countries, which have diverse political and health care systems. In this paper, we report on the EurOOHnet work related to OOHC organizational models, potential shortcomings and improvement options in out-of-hours primary health care. Needs assessment: The EurOOHnet expert working party proposed that models for OOHC should be reviewed to evaluate the availability and accessibility of OOHC for patients while also seeking ways to make the delivery of care more satisfying for service providers. To move towards resolution of OOHC challenges in primary care, as the first stage, the EurOOHnet expert working party identified the following key needs: clear and uniform definitions of the different OOHC models between different countries; adequate-ideally transnational-definitions of urgency levels and corresponding data; and educational programmes for nurses and doctors (e.g. in the use of a standardized triage system for OOHC). Finally, the need for a modern system of data transfer between different health care providers in regular care and providers in OOHC to prevent information loss was identified.

Biologically Informed Individual-Based Network Model for Rift Valley Fever in the US and Evaluation of Mitigation Strategies

PubMed Central

Scoglio, Caterina M.

2016-01-01

Rift Valley fever (RVF) is a zoonotic disease endemic in sub-Saharan Africa with periodic outbreaks in human and animal populations. Mosquitoes are the primary disease vectors; however, Rift Valley fever virus (RVFV) can also spread by direct contact with infected tissues. The transmission cycle is complex, involving humans, livestock, and multiple species of mosquitoes. The epidemiology of RVFV in endemic areas is strongly affected by climatic conditions and environmental variables. In this research, we adapt and use a network-based modeling framework to simulate the transmission of RVFV among hypothetical cattle operations in Kansas, US. Our model considers geo-located livestock populations at the individual level while incorporating the role of mosquito populations and the environment at a coarse resolution. Extensive simulations show the flexibility of our modeling framework when applied to specific scenarios to quantitatively evaluate the efficacy of mosquito control and livestock movement regulations in reducing the extent and intensity of RVF outbreaks in the United States. PMID:27662585

Biologically Informed Individual-Based Network Model for Rift Valley Fever in the US and Evaluation of Mitigation Strategies.

PubMed

Scoglio, Caterina M; Bosca, Claudio; Riad, Mahbubul H; Sahneh, Faryad D; Britch, Seth C; Cohnstaedt, Lee W; Linthicum, Kenneth J

Rift Valley fever (RVF) is a zoonotic disease endemic in sub-Saharan Africa with periodic outbreaks in human and animal populations. Mosquitoes are the primary disease vectors; however, Rift Valley fever virus (RVFV) can also spread by direct contact with infected tissues. The transmission cycle is complex, involving humans, livestock, and multiple species of mosquitoes. The epidemiology of RVFV in endemic areas is strongly affected by climatic conditions and environmental variables. In this research, we adapt and use a network-based modeling framework to simulate the transmission of RVFV among hypothetical cattle operations in Kansas, US. Our model considers geo-located livestock populations at the individual level while incorporating the role of mosquito populations and the environment at a coarse resolution. Extensive simulations show the flexibility of our modeling framework when applied to specific scenarios to quantitatively evaluate the efficacy of mosquito control and livestock movement regulations in reducing the extent and intensity of RVF outbreaks in the United States.

Improving collaboration between Primary Care Research Networks using Access Grid technology.

PubMed

Nagykaldi, Zsolt; Fox, Chester; Gallo, Steve; Stone, Joseph; Fontaine, Patricia; Peterson, Kevin; Arvanitis, Theodoros

2008-01-01

Access Grid (AG) is an Internet2-driven, high performance audio-visual conferencing technology used worldwide by academic and government organisations to enhance communication, human interaction and group collaboration. AG technology is particularly promising for improving academic multi-centre research collaborations. This manuscript describes how the AG technology was utilised by the electronic Primary Care Research Network (ePCRN) that is part of the National Institutes of Health (NIH) Roadmap initiative to improve primary care research and collaboration among practice-based research networks (PBRNs) in the USA. It discusses the design, installation and use of AG implementations, potential future applications, barriers to adoption, and suggested solutions.

Local Area Networks: Are There Advantages for Primary Schools?

ERIC Educational Resources Information Center

Aherran, Anne

1986-01-01

Examines the relative merits of using computer networks (several computers linked together and sharing a single disk drive) and stand-alone systems (self-contained units operating independently) in Australian primary school classrooms. Advances several arguments favoring stand-alone systems, which improve accessibility and enhance individual…

Motor network disruption in essential tremor: a functional and effective connectivity study.

PubMed

Buijink, Arthur W G; van der Stouwe, A M Madelein; Broersma, Marja; Sharifi, Sarvi; Groot, Paul F C; Speelman, Johannes D; Maurits, Natasha M; van Rootselaar, Anne-Fleur

2015-10-01

Although involvement of the cerebello-thalamo-cortical network has often been suggested in essential tremor, the source of oscillatory activity remains largely unknown. To elucidate mechanisms of tremor generation, it is of crucial importance to study the dynamics within the cerebello-thalamo-cortical network. Using a combination of electromyography and functional magnetic resonance imaging, it is possible to record the peripheral manifestation of tremor simultaneously with brain activity related to tremor generation. Our first aim was to study the intrinsic activity of regions within the cerebello-thalamo-cortical network using dynamic causal modelling to estimate effective connectivity driven by the concurrently recorded tremor signal. Our second aim was to objectify how the functional integrity of the cerebello-thalamo-cortical network is affected in essential tremor. We investigated the functional connectivity between cerebellar and cortical motor regions showing activations during a motor task. Twenty-two essential tremor patients and 22 healthy controls were analysed. For the effective connectivity analysis, a network of tremor-signal related regions was constructed, consisting of the left primary motor cortex, premotor cortex, supplementary motor area, left thalamus, and right cerebellar motor regions lobule V and lobule VIII. A measure of variation in tremor severity over time, derived from the electromyogram, was included as modulatory input on intrinsic connections and on the extrinsic cerebello-thalamic connections, giving a total of 128 models. Bayesian model selection and random effects Bayesian model averaging were used. Separate seed-based functional connectivity analyses for the left primary motor cortex, left supplementary motor area and right cerebellar lobules IV, V, VI and VIII were performed. We report two novel findings that support an important role for the cerebellar system in the pathophysiology of essential tremor. First, in the effective connectivity analysis, tremor variation during the motor task has an excitatory effect on both the extrinsic connection from cerebellar lobule V to the thalamus, and the intrinsic activity of cerebellar lobule V and thalamus. Second, the functional integrity of the motor network is affected in essential tremor, with a decrease in functional connectivity between cortical and cerebellar motor regions. This decrease in functional connectivity, related to the motor task, correlates with an increase in clinical tremor severity. Interestingly, increased functional connectivity between right cerebellar lobules I-IV and the left thalamus correlates with an increase in clinical tremor severity. In conclusion, our findings suggest that cerebello-dentato-thalamic activity and cerebello-cortical connectivity is disturbed in essential tremor, supporting previous evidence of functional cerebellar changes in essential tremor. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Challenges of CAC in Heterogeneous Wireless Cognitive Networks

NASA Astrophysics Data System (ADS)

Wang, Jiazheng; Fu, Xiuhua

Call admission control (CAC) is known as an effective functionality in ensuring the QoS of wireless networks. The vision of next generation wireless networks has led to the development of new call admission control (CAC) algorithms specifically designed for heterogeneous wireless Cognitive networks. However, there will be a number of challenges created by dynamic spectrum access and scheduling techniques associated with the cognitive systems. In this paper for the first time, we recommend that the CAC policies should be distinguished between primary users and secondary users. The classification of different methods of cac policies in cognitive networks contexts is proposed. Although there have been some researches within the umbrella of Joint CAC and cross-layer optimization for wireless networks, the advent of the cognitive networks adds some additional problems. We present the conceptual models for joint CAC and cross-layer optimization respectively. Also, the benefit of Cognition can only be realized fully if application requirements and traffic flow contexts are determined or inferred in order to know what modes of operation and spectrum bands to use at each point in time. The process model of Cognition involved per-flow-based CAC is presented. Because there may be a number of parameters on different levels affecting a CAC decision and the conditions for accepting or rejecting a call must be computed quickly and frequently, simplicity and practicability are particularly important for designing a feasible CAC algorithm. In a word, a more thorough understanding of CAC in heterogeneous wireless cognitive networks may help one to design better CAC algorithms.

Reperfusion therapy of myocardial infarction in Mexico: A challenge for modern cardiology.

PubMed

Martínez-Sánchez, Carlos; Arias-Mendoza, Alexandra; González-Pacheco, Héctor; Araiza-Garaygordobil, Diego; Marroquín-Donday, Luis Alfonso; Padilla-Ibarra, Jorge; Sierra-Fernández, Carlos; Altamirano-Castillo, Alfredo; Álvarez-Sangabriel, Amada; Azar-Manzur, Francisco Javier; Briseño-de la Cruz, José Luis; Mendoza-García, Salvador; Piña-Reyna, Yigal; Martínez-Ríos, Marco Antonio

Mexico has been positioned as the country with the highest mortality attributed to myocardial infarction among the members of the Organization for Economic Cooperation and Development. This rate responds to multiple factors, including a low rate of reperfusion therapy and the absence of a coordinated system of care. Primary angioplasty is the reperfusion method recommended by the guidelines, but requires multiple conditions that are not reached at all times. Early pharmacological reperfusion of the culprit coronary artery and early coronary angiography (pharmacoinvasive strategy) can be the solution to the logistical problem that primary angioplasty rises. Several studies have demonstrated pharmacoinvasive strategy as effective and safe as primary angioplasty ST-elevation myocardial infarction, which is postulated as the choice to follow in communities where access to PPCI is limited. The Mexico City Government together with the National Institute of Cardiology have developed a pharmaco-invasive reperfusion treatment program to ensure effective and timely reperfusion in STEMI. The model comprises a network of care at all three levels of health, including a system for early pharmacological reperfusion in primary care centers, a digital telemedicine system, an inter-hospital transport network to ensure primary angioplasty or early percutaneous coronary intervention after fibrinolysis and a training program with certification of the health care personal. This program intends to reduce morbidity and mortality associated with myocardial infarction. Copyright © 2016 Instituto Nacional de Cardiología Ignacio Chávez. Publicado por Masson Doyma México S.A. All rights reserved.

The right hemisphere supports but does not replace left hemisphere auditory function in patients with persisting aphasia.

PubMed

Teki, Sundeep; Barnes, Gareth R; Penny, William D; Iverson, Paul; Woodhead, Zoe V J; Griffiths, Timothy D; Leff, Alexander P

2013-06-01

In this study, we used magnetoencephalography and a mismatch paradigm to investigate speech processing in stroke patients with auditory comprehension deficits and age-matched control subjects. We probed connectivity within and between the two temporal lobes in response to phonemic (different word) and acoustic (same word) oddballs using dynamic causal modelling. We found stronger modulation of self-connections as a function of phonemic differences for control subjects versus aphasics in left primary auditory cortex and bilateral superior temporal gyrus. The patients showed stronger modulation of connections from right primary auditory cortex to right superior temporal gyrus (feed-forward) and from left primary auditory cortex to right primary auditory cortex (interhemispheric). This differential connectivity can be explained on the basis of a predictive coding theory which suggests increased prediction error and decreased sensitivity to phonemic boundaries in the aphasics' speech network in both hemispheres. Within the aphasics, we also found behavioural correlates with connection strengths: a negative correlation between phonemic perception and an inter-hemispheric connection (left superior temporal gyrus to right superior temporal gyrus), and positive correlation between semantic performance and a feedback connection (right superior temporal gyrus to right primary auditory cortex). Our results suggest that aphasics with impaired speech comprehension have less veridical speech representations in both temporal lobes, and rely more on the right hemisphere auditory regions, particularly right superior temporal gyrus, for processing speech. Despite this presumed compensatory shift in network connectivity, the patients remain significantly impaired.

The right hemisphere supports but does not replace left hemisphere auditory function in patients with persisting aphasia

PubMed Central

Barnes, Gareth R.; Penny, William D.; Iverson, Paul; Woodhead, Zoe V. J.; Griffiths, Timothy D.; Leff, Alexander P.

2013-01-01

In this study, we used magnetoencephalography and a mismatch paradigm to investigate speech processing in stroke patients with auditory comprehension deficits and age-matched control subjects. We probed connectivity within and between the two temporal lobes in response to phonemic (different word) and acoustic (same word) oddballs using dynamic causal modelling. We found stronger modulation of self-connections as a function of phonemic differences for control subjects versus aphasics in left primary auditory cortex and bilateral superior temporal gyrus. The patients showed stronger modulation of connections from right primary auditory cortex to right superior temporal gyrus (feed-forward) and from left primary auditory cortex to right primary auditory cortex (interhemispheric). This differential connectivity can be explained on the basis of a predictive coding theory which suggests increased prediction error and decreased sensitivity to phonemic boundaries in the aphasics’ speech network in both hemispheres. Within the aphasics, we also found behavioural correlates with connection strengths: a negative correlation between phonemic perception and an inter-hemispheric connection (left superior temporal gyrus to right superior temporal gyrus), and positive correlation between semantic performance and a feedback connection (right superior temporal gyrus to right primary auditory cortex). Our results suggest that aphasics with impaired speech comprehension have less veridical speech representations in both temporal lobes, and rely more on the right hemisphere auditory regions, particularly right superior temporal gyrus, for processing speech. Despite this presumed compensatory shift in network connectivity, the patients remain significantly impaired. PMID:23715097

Visual Perceptual Learning and Models.

PubMed

Dosher, Barbara; Lu, Zhong-Lin

2017-09-15

Visual perceptual learning through practice or training can significantly improve performance on visual tasks. Originally seen as a manifestation of plasticity in the primary visual cortex, perceptual learning is more readily understood as improvements in the function of brain networks that integrate processes, including sensory representations, decision, attention, and reward, and balance plasticity with system stability. This review considers the primary phenomena of perceptual learning, theories of perceptual learning, and perceptual learning's effect on signal and noise in visual processing and decision. Models, especially computational models, play a key role in behavioral and physiological investigations of the mechanisms of perceptual learning and for understanding, predicting, and optimizing human perceptual processes, learning, and performance. Performance improvements resulting from reweighting or readout of sensory inputs to decision provide a strong theoretical framework for interpreting perceptual learning and transfer that may prove useful in optimizing learning in real-world applications.

Reservoir Modeling by Data Integration via Intermediate Spaces and Artificial Intelligence Tools in MPS Simulation Frameworks

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

Ahmadi, Rouhollah, E-mail: rouhollahahmadi@yahoo.com; Khamehchi, Ehsan

Conditioning stochastic simulations are very important in many geostatistical applications that call for the introduction of nonlinear and multiple-point data in reservoir modeling. Here, a new methodology is proposed for the incorporation of different data types into multiple-point statistics (MPS) simulation frameworks. Unlike the previous techniques that call for an approximate forward model (filter) for integration of secondary data into geologically constructed models, the proposed approach develops an intermediate space where all the primary and secondary data are easily mapped onto. Definition of the intermediate space, as may be achieved via application of artificial intelligence tools like neural networks andmore » fuzzy inference systems, eliminates the need for using filters as in previous techniques. The applicability of the proposed approach in conditioning MPS simulations to static and geologic data is verified by modeling a real example of discrete fracture networks using conventional well-log data. The training patterns are well reproduced in the realizations, while the model is also consistent with the map of secondary data.« less

Cytoskeletal Network Morphology Regulates Intracellular Transport Dynamics

PubMed Central

Ando, David; Korabel, Nickolay; Huang, Kerwyn Casey; Gopinathan, Ajay

2015-01-01

Intracellular transport is essential for maintaining proper cellular function in most eukaryotic cells, with perturbations in active transport resulting in several types of disease. Efficient delivery of critical cargos to specific locations is accomplished through a combination of passive diffusion and active transport by molecular motors that ballistically move along a network of cytoskeletal filaments. Although motor-based transport is known to be necessary to overcome cytoplasmic crowding and the limited range of diffusion within reasonable timescales, the topological features of the cytoskeletal network that regulate transport efficiency and robustness have not been established. Using a continuum diffusion model, we observed that the time required for cellular transport was minimized when the network was localized near the nucleus. In simulations that explicitly incorporated network spatial architectures, total filament mass was the primary driver of network transit times. However, filament traps that redirect cargo back to the nucleus caused large variations in network transport. Filament polarity was more important than filament orientation in reducing average transit times, and transport properties were optimized in networks with intermediate motor on and off rates. Our results provide important insights into the functional constraints on intracellular transport under which cells have evolved cytoskeletal structures, and have potential applications for enhancing reactions in biomimetic systems through rational transport network design. PMID:26488648

Secret Shoppers Find Access To Providers And Network Accuracy Lacking For Those In Marketplace And Commercial Plans.

PubMed

Haeder, Simon F; Weimer, David L; Mukamel, Dana B

2016-07-01

The adequacy of provider networks for plans sold through insurance Marketplaces established under the Affordable Care Act has received much scrutiny recently. Various studies have established that networks are generally narrow. To learn more about network adequacy and access to care, we investigated two questions. First, no matter the nominal size of a network, can patients gain access to primary care services from providers of their choice in a timely manner? Second, how does access compare to plans sold outside insurance Marketplaces? We conducted a "secret shopper" survey of 743 primary care providers from five of California's nineteen insurance Marketplace pricing regions in the summer of 2015. Our findings indicate that obtaining access to primary care providers was generally equally challenging both inside and outside insurance Marketplaces. In less than 30 percent of cases were consumers able to schedule an appointment with an initially selected physician provider. Information about provider networks was often inaccurate. Problems accessing services for patients with acute conditions were particularly troubling. Effectively addressing issues of network adequacy requires more accurate provider information. Project HOPE—The People-to-People Health Foundation, Inc.

Individual Markers of Resilience in Train Traffic Control: The Role of Operators' Goals and Strategic Mental Models and Implications for Variation, Expertise, and Performance.

PubMed

Lo, Julia C; Pluyter, Kari R; Meijer, Sebastiaan A

2016-02-01

The aim of this study was to examine individual markers of resilience and obtain quantitative insights into the understanding and the implications of variation and expertise levels in train traffic operators' goals and strategic mental models and their impact on performance. The Dutch railways are one of the world's most heavy utilized railway networks and have been identified to be weak in system and organizational resilience. Twenty-two train traffic controllers enacted two scenarios in a human-in-the-loop simulator. Their experience, goals, strategic mental models, and performance were assessed through questionnaires and simulator logs. Goals were operationalized through performance indicators and strategic mental models through train completion strategies. A variation was found between operators for both self-reported primary performance indicators and completion strategies. Further, the primary goal of only 14% of the operators reflected the primary organizational goal (i.e., arrival punctuality). An incongruence was also found between train traffic controllers' self-reported performance indicators and objective performance in a more disrupted condition. The level of experience tends to affect performance differently. There is a gap between primary organizational goals and preferred individual goals. Further, the relative strong diversity in primary operator goals and strategic mental models indicates weak resilience at the individual level. With recent and upcoming large-scale changes throughout the sociotechnical space of the railway infrastructure organization, the findings are useful to facilitate future railway traffic control and the development of a resilient system. © 2015, Human Factors and Ergonomics Society.

The role of Primary Healthcare in the coordination of Health Care Networks in Rio de Janeiro, Brazil, and Lisbon region, Portugal.

PubMed

Lapão, Luís Velez; Arcêncio, Ricardo Alexandre; Popolin, Marcela Paschoal; Rodrigues, Ludmila Barbosa Bandeira

2017-03-01

Considering the trajectory of Rio de Janeiro e Lisboa region regarding strengths of the their health local systems to achieve health for all and equity, the study aimed to compare the organization of the Primary Healthcare from both regions, searching to identify the advancement which in terms of the Delivery Health Networks' coordination. It is a case study with qualitative approach and assessment dimensions. It was used material available online such as scientific manuscripts and gray literature. The results showed the different grades regarding Delivery Health Networks. Lisboa region present more advancement, because of its historic issues, it has implemented Primary Healthcare expanded and nowadays it achieved enough maturity related to coordination of its health local system and Rio de Janeiro suffers still influence from historic past regarding Primary Healthcare selective. The both regions has done strong bids in terms of electronic health records and telemedicine. After of the study, it is clearer the historic, cultural and politics and legal issue that determined the differences of the Primary Healthcare coordinator of the Delivery Health Network in Rio de Janeiro and Lisboa region.

The effects of computer-based mindfulness training on Self-control and Mindfulness within Ambulatorily assessed network Systems across Health-related domains in a healthy student population (SMASH): study protocol for a randomized controlled trial.

PubMed

Rowland, Zarah; Wenzel, Mario; Kubiak, Thomas

2016-12-01

Self-control is an important ability in everyday life, showing associations with health-related outcomes. The aim of the Self-control and Mindfulness within Ambulatorily assessed network Systems across Health-related domains (SMASH) study is twofold: first, the effectiveness of a computer-based mindfulness training will be evaluated in a randomized controlled trial. Second, the SMASH study implements a novel network approach in order to investigate complex temporal interdependencies of self-control networks across several domains. The SMASH study is a two-armed, 6-week, non-blinded randomized controlled trial that combines seven weekly laboratory meetings and 40 days of electronic diary assessments with six prompts per day in a healthy undergraduate student population at the Johannes Gutenberg University Mainz, Germany. Participants will be randomly assigned to (1) receive a computer-based mindfulness intervention or (2) to a wait-list control condition. Primary outcomes are self-reported momentary mindfulness and self-control assessed via electronic diaries. Secondary outcomes are habitual mindfulness and habitual self-control. Further measures include self-reported behaviors in specific self-control domains: emotion regulation, alcohol consumption and eating behaviors. The effects of mindfulness training on primary and secondary outcomes are explored using three-level mixed models. Furthermore, networks will be computed with vector autoregressive mixed models to investigate the dynamics at participant and group level. This study was approved by the local ethics committee (reference code 2015_JGU_psychEK_011) and follows the standards laid down in the Declaration of Helsinki (2013). This randomized controlled trial combines an intensive Ambulatory Assessment of 40 consecutive days and seven laboratory meetings. By implementing a novel network approach, underlying processes of self-control within different health domains will be identified. These results will deepen the understanding of self-control performance and will guide to just-in-time individual interventions for several health-related behaviors. ClinicalTrials.gov, NCT02647801 . Registered on 15 December 2015 (registered retrospectively). .

Anti-correlated cortical networks of intrinsic connectivity in the rat brain.

PubMed

Schwarz, Adam J; Gass, Natalia; Sartorius, Alexander; Risterucci, Celine; Spedding, Michael; Schenker, Esther; Meyer-Lindenberg, Andreas; Weber-Fahr, Wolfgang

2013-01-01

In humans, resting-state blood oxygen level-dependent (BOLD) signals in the default mode network (DMN) are temporally anti-correlated with those from a lateral cortical network involving the frontal eye fields, secondary somatosensory and posterior insular cortices. Here, we demonstrate the existence of an analogous lateral cortical network in the rat brain, extending laterally from anterior secondary sensorimotor regions to the insular cortex and exhibiting low-frequency BOLD fluctuations that are temporally anti-correlated with a midline "DMN-like" network comprising posterior/anterior cingulate and prefrontal cortices. The primary nexus for this anti-correlation relationship was the anterior secondary motor cortex, close to regions that have been identified with frontal eye fields in the rat brain. The anti-correlation relationship was corroborated after global signal removal, underscoring this finding as a robust property of the functional connectivity signature in the rat brain. These anti-correlated networks demonstrate strong anatomical homology to networks identified in human and monkey connectivity studies, extend the known preserved functional connectivity relationships between rodent and primates, and support the use of resting-state functional magnetic resonance imaging as a translational imaging method between rat models and humans.

Anti-Correlated Cortical Networks of Intrinsic Connectivity in the Rat Brain

PubMed Central

Gass, Natalia; Sartorius, Alexander; Risterucci, Celine; Spedding, Michael; Schenker, Esther; Meyer-Lindenberg, Andreas; Weber-Fahr, Wolfgang

2013-01-01

Abstract In humans, resting-state blood oxygen level-dependent (BOLD) signals in the default mode network (DMN) are temporally anti-correlated with those from a lateral cortical network involving the frontal eye fields, secondary somatosensory and posterior insular cortices. Here, we demonstrate the existence of an analogous lateral cortical network in the rat brain, extending laterally from anterior secondary sensorimotor regions to the insular cortex and exhibiting low-frequency BOLD fluctuations that are temporally anti-correlated with a midline “DMN-like” network comprising posterior/anterior cingulate and prefrontal cortices. The primary nexus for this anti-correlation relationship was the anterior secondary motor cortex, close to regions that have been identified with frontal eye fields in the rat brain. The anti-correlation relationship was corroborated after global signal removal, underscoring this finding as a robust property of the functional connectivity signature in the rat brain. These anti-correlated networks demonstrate strong anatomical homology to networks identified in human and monkey connectivity studies, extend the known preserved functional connectivity relationships between rodent and primates, and support the use of resting-state functional magnetic resonance imaging as a translational imaging method between rat models and humans. PMID:23919836

An Adaptive Resonance Theory account of the implicit learning of orthographic word forms.

PubMed

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

2010-01-01

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

Real Time Distributed Embedded Oscillator Operating Frequency Monitoring

NASA Technical Reports Server (NTRS)

Pollock, Julie (Inventor); Oliver, Brett D. (Inventor); Brickner, Christopher (Inventor)

2013-01-01

A method for clock monitoring in a network is provided. The method comprises receiving a first network clock signal at a network device and comparing the first network clock signal to a local clock signal from a primary oscillator coupled to the network device.

Use of transcriptomics and co-expression networks to analyze the interconnections between nitrogen assimilation and photorespiratory metabolism

PubMed Central

Pérez-Delgado, Carmen M.; Moyano, Tomás C.; García-Calderón, Margarita; Canales, Javier; Gutiérrez, Rodrigo A.; Márquez, Antonio J.; Betti, Marco

2016-01-01

Nitrogen is one of the most important nutrients for plants and, in natural soils, its availability is often a major limiting factor for plant growth. Here we examine the effect of different forms of nitrogen nutrition and of photorespiration on gene expression in the model legume Lotus japonicus with the aim of identifying regulatory candidate genes co-ordinating primary nitrogen assimilation and photorespiration. The transcriptomic changes produced by the use of different nitrogen sources in leaves of L. japonicus plants combined with the transcriptomic changes produced in the same tissue by different photorespiratory conditions were examined. The results obtained provide novel information on the possible role of plastidic glutamine synthetase in the response to different nitrogen sources and in the C/N balance of L. japonicus plants. The use of gene co-expression networks establishes a clear relationship between photorespiration and primary nitrogen assimilation and identifies possible transcription factors connected to the genes of both routes. PMID:27117340

A Primary Role for Nucleus Accumbens and Related Limbic Network in Vocal Tics.

PubMed

McCairn, Kevin W; Nagai, Yuji; Hori, Yukiko; Ninomiya, Taihei; Kikuchi, Erika; Lee, Ju-Young; Suhara, Tetsuya; Iriki, Atsushi; Minamimoto, Takafumi; Takada, Masahiko; Isoda, Masaki; Matsumoto, Masayuki

2016-01-20

Inappropriate vocal expressions, e.g., vocal tics in Tourette syndrome, severely impact quality of life. Neural mechanisms underlying vocal tics remain unexplored because no established animal model representing the condition exists. We report that unilateral disinhibition of the nucleus accumbens (NAc) generates vocal tics in monkeys. Whole-brain PET imaging identified prominent, bilateral limbic cortico-subcortical activation. Local field potentials (LFPs) developed abnormal spikes in the NAc and the anterior cingulate cortex (ACC). Vocalization could occur without obvious LFP spikes, however, when phase-phase coupling of alpha oscillations were accentuated between the NAc, ACC, and the primary motor cortex. These findings contrasted with myoclonic motor tics induced by disinhibition of the dorsolateral putamen, where PET activity was confined to the ipsilateral sensorimotor system and LFP spikes always preceded motor tics. We propose that vocal tics emerge as a consequence of dysrhythmic alpha coupling between critical nodes in the limbic and motor networks. VIDEO ABSTRACT. Copyright © 2016 Elsevier Inc. All rights reserved.

Real-time identification of vehicle motion-modes using neural networks

NASA Astrophysics Data System (ADS)

Wang, Lifu; Zhang, Nong; Du, Haiping

2015-01-01

A four-wheel ground vehicle has three body-dominated motion-modes, that is, bounce, roll, and pitch motion-modes. Real-time identification of these motion-modes can make vehicle suspensions, in particular, active suspensions, target on the dominant motion-mode and apply appropriate control strategies to improve its performance with less power consumption. Recently, a motion-mode energy method (MEM) was developed to identify the vehicle body motion-modes. However, this method requires the measurement of full vehicle states and road inputs, which are not always available in practice. This paper proposes an alternative approach to identify vehicle primary motion-modes with acceptable accuracy by employing neural networks (NNs). The effectiveness of the trained NNs is verified on a 10-DOF full-car model under various types of excitation inputs. The results confirm that the proposed method is effective in determining vehicle primary motion-modes with comparable accuracy to the MEM method. Experimental data is further used to validate the proposed method.

Spatial Estimation of Soil Moisture Using Synthetic Aperture Radar in Alaska

NASA Astrophysics Data System (ADS)

Meade, N. G.; Hinzman, L. D.; Kane, D. L.

1999-01-01

A spatially distributed Model of Arctic Thermal and Hydrologic processes (MATH) has been developed. One of the attributes of this model is the spatial and temporal prediction of soil moisture in the active layer. The spatially distributed output from this model required verification data obtained through remote sensing to assess performance at the watershed scale independently. Therefore, a neural network was trained to predict soil moisture contents near the ground surface. The input to train the neural network is synthetic aperture radar (SAR) pixel value, and field measurements of soil moisture, and vegetation, which were used as a surrogate for surface roughness. Once the network was trained, soil moisture predictions were made based on SAR pixel value and vegetation. These results were then used for comparison with results from the hydrologic model. The quality of neural network input was less than anticipated. Our digital elevation model (DEM) was not of high enough resolution to allow exact co-registration with soil moisture measurements; therefore, the statistical correlations were not as good as hoped. However, the spatial pattern of the SAR derived soil moisture contents compares favorably with the hydrologic MATH model results. Primary surface parameters that effect SAR include topography, surface roughness, vegetation cover and soil texture. Single parameters that are considered to influence SAR include incident angle of the radar, polarization of the radiation, signal strength and returning signal integration, to name a few. These factors influence the reflectance, but if one adequately quantifies the influences of terrain and roughness, it is considered possible to extract information on soil moisture from SAR imagery analysis and in turn use SAR imagery to validate hydrologic models

Primary Frequency Response with Aggregated DERs: Preprint

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

Guggilam, Swaroop S.; Dhople, Sairaj V.; Zhao, Changhong

2017-03-03

Power networks have to withstand a variety of disturbances that affect system frequency, and the problem is compounded with the increasing integration of intermittent renewable generation. Following a large-signal generation or load disturbance, system frequency is arrested leveraging primary frequency control provided by governor action in synchronous generators. In this work, we propose a framework for distributed energy resources (DERs) deployed in distribution networks to provide (supplemental) primary frequency response. Particularly, we demonstrate how power-frequency droop slopes for individual DERs can be designed so that the distribution feeder presents a guaranteed frequency-regulation characteristic at the feeder head. Furthermore, the droopmore » slopes are engineered such that injections of individual DERs conform to a well-defined fairness objective that does not penalize them for their location on the distribution feeder. Time-domain simulations for an illustrative network composed of a combined transmission network and distribution network with frequency-responsive DERs are provided to validate the approach.« less

From social integration to health: Durkheim in the new millennium.

PubMed

Berkman, L F; Glass, T; Brissette, I; Seeman, T E

2000-09-01

It is widely recognized that social relationships and affiliation have powerful effects on physical and mental health. When investigators write about the impact of social relationships on health, many terms are used loosely and interchangeably including social networks, social ties and social integration. The aim of this paper is to clarify these terms using a single framework. We discuss: (1) theoretical orientations from diverse disciplines which we believe are fundamental to advancing research in this area; (2) a set of definitions accompanied by major assessment tools; and (3) an overarching model which integrates multilevel phenomena. Theoretical orientations that we draw upon were developed by Durkheim whose work on social integration and suicide are seminal and John Bowlby, a psychiatrist who developed attachment theory in relation to child development and contemporary social network theorists. We present a conceptual model of how social networks impact health. We envision a cascading causal process beginning with the macro-social to psychobiological processes that are dynamically linked together to form the processes by which social integration effects health. We start by embedding social networks in a larger social and cultural context in which upstream forces are seen to condition network structure. Serious consideration of the larger macro-social context in which networks form and are sustained has been lacking in all but a small number of studies and is almost completely absent in studies of social network influences on health. We then move downstream to understand the influences network structure and function have on social and interpersonal behavior. We argue that networks operate at the behavioral level through four primary pathways: (1) provision of social support; (2) social influence; (3) on social engagement and attachment; and (4) access to resources and material goods.

Diabetes Case Management in Primary Care: The New Brunswick Experience and Expanding the Practice of the Certified Diabetes Educator Nurse into Primary Care.

PubMed

Jones, Shelley L

2015-08-01

The role of the outreach diabetes case manager in New Brunswick, Canada, was first developed in the Moncton Area of Horizon Health Network in response to a physician-identified gap between patients' diagnoses of diabetes and their attendance at the local diabetes education centre. This model of collaborative interprofessional practice increases support for primary care providers and people living with diabetes in that they are being provided the services of certified diabetes educators who can address knowledge gaps with respect to evidence-based guidelines and best practice, promote advancement of diabetes and chronic-disease management therapies and support adherence to treatment plans and self-management practices. This report chronicles a review of the implementation, expansion and evaluation of the outreach diabetes case manager model in the province of New Brunswick, Canada, along with the rationale for development of the role for registered nurses in other jurisdictions. Crown Copyright © 2015. Published by Elsevier Inc. All rights reserved.

The Changing Faces of Mentorship: Application of a Developmental Network Framework in a Health Services Research Career Development Program

PubMed Central

Finney, John W.; Bi, Xiaoyu; Maisel, Natalya C.; Hayashi, Ko P.; Weitlauf, Julie C.; Cronkite, Ruth C.

2015-01-01

Abstract Historically, mentorship has been conceived of as a dyadic relationship between a senior mentor and an early‐career investigator. Models involving multiple mentors have gained favor in recent years, but empirical research on multiple‐mentor models has been lacking. The current work aims to fill this gap by describing a long‐standing health services research mentoring program at the U.S. Department of Veterans Affairs which has adopted a network‐based approach to mentoring. As part of a broader project, we surveyed VA HSR&D Career Development Awardees who received an award between 2000 and 2012. In total, 133 awardees participated (84%). Awardees reported on the structure of mentoring relationships with their two most influential mentors. Awardees were mentored by teams consisting of one to five mentors (M = 2.7 mentors). Most often, one mentor served as primary mentor while one or more mentors played a supporting role. In most cases, an awardee‘s primary mentor was co‐located with the awardee, with fewer secondary mentors co‐located. More recently funded CDAs had more mentors and were less likely to be co‐located with secondary mentors. The VA HSR&D CDA program incorporates current thinking about Developmental Network models of mentorship into a comprehensive program providing a rich mentorship experience for its awardees. PMID:26663417

Contrast normalization contributes to a biologically-plausible model of receptive-field development in primary visual cortex (V1)

PubMed Central

Willmore, Ben D.B.; Bulstrode, Harry; Tolhurst, David J.

2012-01-01

Neuronal populations in the primary visual cortex (V1) of mammals exhibit contrast normalization. Neurons that respond strongly to simple visual stimuli – such as sinusoidal gratings – respond less well to the same stimuli when they are presented as part of a more complex stimulus which also excites other, neighboring neurons. This phenomenon is generally attributed to generalized patterns of inhibitory connections between nearby V1 neurons. The Bienenstock, Cooper and Munro (BCM) rule is a neural network learning rule that, when trained on natural images, produces model neurons which, individually, have many tuning properties in common with real V1 neurons. However, when viewed as a population, a BCM network is very different from V1 – each member of the BCM population tends to respond to the same dominant features of visual input, producing an incomplete, highly redundant code for visual information. Here, we demonstrate that, by adding contrast normalization into the BCM rule, we arrive at a neurally-plausible Hebbian learning rule that can learn an efficient sparse, overcomplete representation that is a better model for stimulus selectivity in V1. This suggests that one role of contrast normalization in V1 is to guide the neonatal development of receptive fields, so that neurons respond to different features of visual input. PMID:22230381

Implementation study of an analog spiking neural network for assisting cardiac delay prediction in a cardiac resynchronization therapy device.

PubMed

Sun, Qing; Schwartz, François; Michel, Jacques; Herve, Yannick; Dalmolin, Renzo

2011-06-01

In this paper, we aim at developing an analog spiking neural network (SNN) for reinforcing the performance of conventional cardiac resynchronization therapy (CRT) devices (also called biventricular pacemakers). Targeting an alternative analog solution in 0.13- μm CMOS technology, this paper proposes an approach to improve cardiac delay predictions in every cardiac period in order to assist the CRT device to provide real-time optimal heartbeats. The primary analog SNN architecture is proposed and its implementation is studied to fulfill the requirement of very low energy consumption. By using the Hebbian learning and reinforcement learning algorithms, the intended adaptive CRT device works with different functional modes. The simulations of both learning algorithms have been carried out, and they were shown to demonstrate the global functionalities. To improve the realism of the system, we introduce various heart behavior models (with constant/variable heart rates) that allow pathologic simulations with/without noise on the signals of the input sensors. The simulations of the global system (pacemaker models coupled with heart models) have been investigated and used to validate the analog spiking neural network implementation.

Classification of a Driver's cognitive workload levels using artificial neural network on ECG signals.

PubMed

Tjolleng, Amir; Jung, Kihyo; Hong, Wongi; Lee, Wonsup; Lee, Baekhee; You, Heecheon; Son, Joonwoo; Park, Seikwon

2017-03-01

An artificial neural network (ANN) model was developed in the present study to classify the level of a driver's cognitive workload based on electrocardiography (ECG). ECG signals were measured on 15 male participants while they performed a simulated driving task as a primary task with/without an N-back task as a secondary task. Three time-domain ECG measures (mean inter-beat interval (IBI), standard deviation of IBIs, and root mean squared difference of adjacent IBIs) and three frequencydomain ECG measures (power in low frequency, power in high frequency, and ratio of power in low and high frequencies) were calculated. To compensate for individual differences in heart response during the driving tasks, a three-step data processing procedure was performed to ECG signals of each participant: (1) selection of two most sensitive ECG measures, (2) definition of three (low, medium, and high) cognitive workload levels, and (3) normalization of the selected ECG measures. An ANN model was constructed using a feed-forward network and scaled conjugate gradient as a back-propagation learning rule. The accuracy of the ANN classification model was found satisfactory for learning data (95%) and testing data (82%). Copyright © 2016 Elsevier Ltd. All rights reserved.

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

Chinthavali, Madhu Sudhan; Campbell, Steven L

This paper presents an analytical model for wireless power transfer system used in electric vehicle application. The equivalent circuit model for each major component of the system is described, including the input voltage source, resonant network, transformer, nonlinear diode rectifier load, etc. Based on the circuit model, the primary side compensation capacitance, equivalent input impedance, active / reactive power are calculated, which provides a guideline for parameter selection. Moreover, the voltage gain curve from dc output to dc input is derived as well. A hardware prototype with series-parallel resonant stage is built to verify the developed model. The experimental resultsmore » from the hardware are compared with the model predicted results to show the validity of the model.« less

Pyrolysis process for producing fuel gas

NASA Technical Reports Server (NTRS)

Serio, Michael A. (Inventor); Kroo, Erik (Inventor); Wojtowicz, Marek A. (Inventor); Suuberg, Eric M. (Inventor)

2007-01-01

Solid waste resource recovery in space is effected by pyrolysis processing, to produce light gases as the main products (CH.sub.4, H.sub.2, CO.sub.2, CO, H.sub.2O, NH.sub.3) and a reactive carbon-rich char as the main byproduct. Significant amounts of liquid products are formed under less severe pyrolysis conditions, and are cracked almost completely to gases as the temperature is raised. A primary pyrolysis model for the composite mixture is based on an existing model for whole biomass materials, and an artificial neural network models the changes in gas composition with the severity of pyrolysis conditions.

Social networks of patients with chronic skin lesions: nursing care.

PubMed

Bandeira, Luciana Alves; Santos, Maxuel Cruz Dos; Duarte, Êrica Rosalba Mallmann; Bandeira, Andrea Gonçalves; Riquinho, Deise Lisboa; Vieira, Letícia Becker

2018-01-01

To describe the social networks of patients with chronic skin damages. A qualitative study conducted through semi-structured interviews with nine subjects with chronic skin lesions from June 2016 to March 2017; we used the theoretical-methodological framework of Lia Sanicola's Social Network. The analysis of the relational maps revealed that the primary network was formed mainly by relatives and neighbors; its characteristics, such as: reduced size, low density and few exchanges/relationships, configures fragility in these links. The secondary network was essentially described by health services, and the nurse was cited as a linker in the therapeutic process. Faced with the fragility of the links and social isolation, the primary health care professionals are fundamental foundations for the construction of networks of social support and care for patients with chronic skin lesions.

Brief encounters: what do primary care professionals contribute to peoples' self-care support network for long-term conditions? A mixed methods study.

PubMed

Rogers, Anne; Vassilev, Ivaylo; Brooks, Helen; Kennedy, Anne; Blickem, Christian

2016-02-17

Primary care professionals are presumed to play a central role in delivering long-term condition management. However the value of their contribution relative to other sources of support in the life worlds of patients has been less acknowledged. Here we explore the value of primary care professionals in people's personal communities of support for long-term condition management. A mixed methods survey with nested qualitative study designed to identify relationships and social network member's (SNM) contributions to the support work of managing a long-term condition conducted in 2010 in the North West of England. Through engagement with a concentric circles diagram three hundred participants identified 2544 network members who contributed to illness management. The results demonstrated how primary care professionals are involved relative to others in ongoing self-care management. Primary care professionals constituted 15.5 % of overall network members involved in chronic illness work. Their contribution was identified as being related to illness specific work providing less in terms of emotional work than close family members or pets and little to everyday work. The qualitative accounts suggested that primary care professionals are valued mainly for access to medication and nurses for informational and monitoring activities. Overall primary care is perceived as providing less input in terms of extended self-management support than the current literature on policy and practice suggests. Thus primary care professionals can be described as providing 'minimally provided support'. This sense of a 'minimally' provided input reinforces limited expectations and value about what primary care professionals can provide in terms of support for long-term condition management. Primary care was perceived as having an essential but limited role in making a contribution to support work for long-term conditions. This coalesces with evidence of a restricted capacity of primary care to take on the work load of self-management support work. There is a need to prioritise exploring the means by which extended self-care support could be enhanced out-with primary care. Central to this is building a system capable of engaging network capacity to mobilise resources for self-management support from open settings and the broader community.

Reciprocally-Benefited Secure Transmission for Spectrum Sensing-Based Cognitive Radio Sensor Networks

PubMed Central

Wang, Dawei; Ren, Pinyi; Du, Qinghe; Sun, Li; Wang, Yichen

2016-01-01

The rapid proliferation of independently-designed and -deployed wireless sensor networks extremely crowds the wireless spectrum and promotes the emergence of cognitive radio sensor networks (CRSN). In CRSN, the sensor node (SN) can make full use of the unutilized licensed spectrum, and the spectrum efficiency is greatly improved. However, inevitable spectrum sensing errors will adversely interfere with the primary transmission, which may result in primary transmission outage. To compensate the adverse effect of spectrum sensing errors, we propose a reciprocally-benefited secure transmission strategy, in which SN’s interference to the eavesdropper is employed to protect the primary confidential messages while the CRSN is also rewarded with a loose spectrum sensing error probability constraint. Specifically, according to the spectrum sensing results and primary users’ activities, there are four system states in this strategy. For each state, we analyze the primary secrecy rate and the SN’s transmission rate by taking into account the spectrum sensing errors. Then, the SN’s transmit power is optimally allocated for each state so that the average transmission rate of CRSN is maximized under the constraint of the primary maximum permitted secrecy outage probability. In addition, the performance tradeoff between the transmission rate of CRSN and the primary secrecy outage probability is investigated. Moreover, we analyze the primary secrecy rate for the asymptotic scenarios and derive the closed-form expression of the SN’s transmission outage probability. Simulation results show that: (1) the performance of the SN’s average throughput in the proposed strategy outperforms the conventional overlay strategy; (2) both the primary network and CRSN benefit from the proposed strategy. PMID:27897988

Telemedicine and distributed medical intelligence.

PubMed

Warner, D; Tichenor, J M; Balch, D C

1996-01-01

Recent trends in health care informatics and telemedicine indicate that systems are being developed with a primary focus on technology and business, not on the process of medicine itself. The authors present a new model of health care information, distributed medical intelligence, which promotes the development of an integrative medical communication system addressing the process of providing expert medical knowledge to the point of need. The model incorporates audio, video, high-resolution still images, and virtual reality applications into an integrated medical communications network. Three components of the model (care portals, Docking Station, and the bridge) are described. The implementation of this model at the East Carolina University School of Medicine is also outlined.

Coupling root architecture and pore network modeling - an attempt towards better understanding root-soil interactions

NASA Astrophysics Data System (ADS)

Leitner, Daniel; Bodner, Gernot; Raoof, Amir

2013-04-01

Understanding root-soil interactions is of high importance for environmental and agricultural management. Root uptake is an essential component in water and solute transport modeling. The amount of groundwater recharge and solute leaching significantly depends on the demand based plant extraction via its root system. Plant uptake however not only responds to the potential demand, but in most situations is limited by supply form the soil. The ability of the plant to access water and solutes in the soil is governed mainly by root distribution. Particularly under conditions of heterogeneous distribution of water and solutes in the soil, it is essential to capture the interaction between soil and roots. Root architecture models allow studying plant uptake from soil by describing growth and branching of root axes in the soil. Currently root architecture models are able to respond dynamically to water and nutrient distribution in the soil by directed growth (tropism), modified branching and enhanced exudation. The porous soil medium as rooting environment in these models is generally described by classical macroscopic water retention and sorption models, average over the pore scale. In our opinion this simplified description of the root growth medium implies several shortcomings for better understanding root-soil interactions: (i) It is well known that roots grow preferentially in preexisting pores, particularly in more rigid/dry soil. Thus the pore network contributes to the architectural form of the root system; (ii) roots themselves can influence the pore network by creating preferential flow paths (biopores) which are an essential element of structural porosity with strong impact on transport processes; (iii) plant uptake depend on both the spatial location of water/solutes in the pore network as well as the spatial distribution of roots. We therefore consider that for advancing our understanding in root-soil interactions, we need not only to extend our root models, but also improve the description of the rooting environment. Until now there have been no attempts to couple root architecture and pore network models. In our work we present a first attempt to join both types of models using the root architecture model of Leitner et al., (2010) and a pore network model presented by Raoof et al. (2010). The two main objectives of coupling both models are: (i) Representing the effect of root induced biopores on flow and transport processes: For this purpose a fixed root architecture created by the root model is superimposed as a secondary root induced pore network to the primary soil network, thus influencing the final pore topology in the network generation. (ii) Representing the influence of pre-existing pores on root branching: Using a given network of (rigid) pores, the root architecture model allocates its root axes into these preexisting pores as preferential growth paths with thereby shape the final root architecture. The main objective of our study is to reveal the potential of using a pore scale description of the plant growth medium for an improved representation of interaction processes at the interface of root and soil. References Raoof, A., Hassanizadeh, S.M. 2010. A New Method for Generating Pore-Network Models. Transp. Porous Med. 81, 391-407. Leitner, D, Klepsch, S., Bodner, G., Schnepf, S. 2010. A dynamic root system growth model based on L-Systems. Tropisms and coupling to nutrient uptake from soil. Plant Soil 332, 177-192.

A unified account of tilt illusions, association fields, and contour detection based on elastica.

PubMed

Keemink, Sander W; van Rossum, Mark C W

2016-09-01

As expressed in the Gestalt law of good continuation, human perception tends to associate stimuli that form smooth continuations. Contextual modulation in primary visual cortex, in the form of association fields, is believed to play an important role in this process. Yet a unified and principled account of the good continuation law on the neural level is lacking. In this study we introduce a population model of primary visual cortex. Its contextual interactions depend on the elastica curvature energy of the smoothest contour connecting oriented bars. As expected, this model leads to association fields consistent with data. However, in addition the model displays tilt-illusions for stimulus configurations with grating and single bars that closely match psychophysics. Furthermore, the model explains not only pop-out of contours amid a variety of backgrounds, but also pop-out of single targets amid a uniform background. We thus propose that elastica is a unifying principle of the visual cortical network. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

A social marketing approach to implementing evidence-based practice in VHA QUERI: the TIDES depression collaborative care model.

PubMed

Luck, Jeff; Hagigi, Fred; Parker, Louise E; Yano, Elizabeth M; Rubenstein, Lisa V; Kirchner, JoAnn E

2009-09-28

Collaborative care models for depression in primary care are effective and cost-effective, but difficult to spread to new sites. Translating Initiatives for Depression into Effective Solutions (TIDES) is an initiative to promote evidence-based collaborative care in the U.S. Veterans Health Administration (VHA). Social marketing applies marketing techniques to promote positive behavior change. Described in this paper, TIDES used a social marketing approach to foster national spread of collaborative care models. The approach relied on a sequential model of behavior change and explicit attention to audience segmentation. Segments included VHA national leadership, Veterans Integrated Service Network (VISN) regional leadership, facility managers, frontline providers, and veterans. TIDES communications, materials and messages targeted each segment, guided by an overall marketing plan. Depression collaborative care based on the TIDES model was adopted by VHA as part of the new Primary Care Mental Health Initiative and associated policies. It is currently in use in more than 50 primary care practices across the United States, and continues to spread, suggesting success for its social marketing-based dissemination strategy. Development, execution and evaluation of the TIDES marketing effort shows that social marketing is a promising approach for promoting implementation of evidence-based interventions in integrated healthcare systems.

A reliability study on brain activation during active and passive arm movements supported by an MRI-compatible robot.

PubMed

Estévez, Natalia; Yu, Ningbo; Brügger, Mike; Villiger, Michael; Hepp-Reymond, Marie-Claude; Riener, Robert; Kollias, Spyros

2014-11-01

In neurorehabilitation, longitudinal assessment of arm movement related brain function in patients with motor disability is challenging due to variability in task performance. MRI-compatible robots monitor and control task performance, yielding more reliable evaluation of brain function over time. The main goals of the present study were first to define the brain network activated while performing active and passive elbow movements with an MRI-compatible arm robot (MaRIA) in healthy subjects, and second to test the reproducibility of this activation over time. For the fMRI analysis two models were compared. In model 1 movement onset and duration were included, whereas in model 2 force and range of motion were added to the analysis. Reliability of brain activation was tested with several statistical approaches applied on individual and group activation maps and on summary statistics. The activated network included mainly the primary motor cortex, primary and secondary somatosensory cortex, superior and inferior parietal cortex, medial and lateral premotor regions, and subcortical structures. Reliability analyses revealed robust activation for active movements with both fMRI models and all the statistical methods used. Imposed passive movements also elicited mainly robust brain activation for individual and group activation maps, and reliability was improved by including additional force and range of motion using model 2. These findings demonstrate that the use of robotic devices, such as MaRIA, can be useful to reliably assess arm movement related brain activation in longitudinal studies and may contribute in studies evaluating therapies and brain plasticity following injury in the nervous system.

Modeling spatial patterns of limits to production of deposit-feeders and ectothermic predators in the northern Bering Sea

NASA Astrophysics Data System (ADS)

Lovvorn, James R.; Jacob, Ute; North, Christopher A.; Kolts, Jason M.; Grebmeier, Jacqueline M.; Cooper, Lee W.; Cui, Xuehua

2015-03-01

Network models can help generate testable predictions and more accurate projections of food web responses to environmental change. Such models depend on predator-prey interactions throughout the network. When a predator currently consumes all of its prey's production, the prey's biomass may change substantially with loss of the predator or invasion by others. Conversely, if production of deposit-feeding prey is limited by organic matter inputs, system response may be predictable from models of primary production. For sea floor communities of shallow Arctic seas, increased temperature could lead to invasion or loss of predators, while reduced sea ice or change in wind-driven currents could alter organic matter inputs. Based on field data and models for three different sectors of the northern Bering Sea, we found a number of cases where all of a prey's production was consumed but the taxa involved varied among sectors. These differences appeared not to result from numerical responses of predators to abundance of preferred prey. Rather, they appeared driven by stochastic variations in relative biomass among taxa, due largely to abiotic conditions that affect colonization and early post-larval survival. Oscillatory tendencies of top-down versus bottom-up interactions may augment these variations. Required inputs of settling microalgae exceeded existing estimates of annual primary production by 50%; thus, assessing limits to bottom-up control depends on better corrections of satellite estimates to account for production throughout the water column. Our results suggest that in this Arctic system, stochastic abiotic conditions outweigh deterministic species interactions in food web responses to a varying environment.

Practical Diagnosis and Management of Dementia Due to Alzheimer’s Disease in the Primary Care Setting: An Evidence-Based Approach

PubMed Central

Kerwin, Diana R.

2013-01-01

Objective: To review evidence-based guidance on the primary care of Alzheimer’s disease and clinical research on models of primary care for Alzheimer’s disease to present a practical summary for the primary care physician regarding the assessment and management of the disease. Data Sources: References were obtained via search using keywords Alzheimer’s disease AND primary care OR collaborative care OR case finding OR caregivers OR guidelines. Articles were limited to English language from January 1, 1990, to January 1, 2013. Study Selection: Articles were reviewed and selected on the basis of study quality and pertinence to this topic, covering a broad range of data and opinion across geographical regions and systems of care. The most recent published guidelines from major organizations were included. Results: Practice guidelines contained numerous points of consensus, with most advocating a central role for the primary care physician in the detection, diagnosis, and treatment of Alzheimer’s disease. Review of the literature indicated that optimal medical and psychosocial care for people with Alzheimer’s disease and their caregivers may be best facilitated through collaborative models of care involving the primary care physician working within a wider interdisciplinary team. Conclusions: Evidence-based guidelines assign the primary care physician a critical role in the care of people with Alzheimer’s disease. Research on models of care suggests the need for an appropriate medical/nonmedical support network to fulfill this role. Given the diversity and breadth of services required and the necessity for close coordination, nationwide implementation of team-based, collaborative care programs may represent the best option for improving care standards for patients with Alzheimer’s disease. PMID:24392252

Primary care practices' perceived constraints to engaging in research: the importance of context and 'Flow'.

PubMed

Michalec, Barret; Fagan, Heather Bittner; Rahmer, Brian

2014-01-01

The primary purpose of this study is to understand primary care practices' perceived constraints to engaging in research from micro-, meso-, and macro-level perspectives. Past research has spotlighted various barriers and hurdles that primary care practices face when attempting to engage in research efforts; yet a majority of this research has focused exclusively on micro- (physician-specific) and meso-level (practice-specific) factors. Minimal attention has been paid to the context - the more macro-level issues such as how these barriers relate to primary care practices' role within the dominant payment/reimbursement model of U.S. health-care system. Semi-structured focus groups were conducted in five U.S. practices, all owned by an independent academic medical center. Each had participated in at least one research study but were not part of a practice-based research network or affiliated with a medical school. Data were analyzed using NVIVO-9 by using a multistep coding process. Findings The perceived constraints offered by the participants echoed those featured in previous studies. Secondary analyses of the interconnected nature of these factors highlighted a valuable and sensitive 'Flow' that is evident at the individual, interaction, and organizational levels of primary care practice. Engaging in research appears to pose a significant threat to the outcomes of Flow (i.e., revenue, patient health outcomes, and the overall well-being of the practice). It is posited that the risk of not meeting expected productivity-based outcomes, which appear to be dictated by current dominant reimbursement models, frames the overall process of research-related decision making in primary care. Within the funding/reimbursement models of the US health-care system, engaging in research does not appear to be advantageous for primary care practices.

Metadata and network API aspects of a framework for storing and retrieving civil infrastructure monitoring data

NASA Astrophysics Data System (ADS)

Wong, John-Michael; Stojadinovic, Bozidar

2005-05-01

A framework has been defined for storing and retrieving civil infrastructure monitoring data over a network. The framework consists of two primary components: metadata and network communications. The metadata component provides the descriptions and data definitions necessary for cataloging and searching monitoring data. The communications component provides Java classes for remotely accessing the data. Packages of Enterprise JavaBeans and data handling utility classes are written to use the underlying metadata information to build real-time monitoring applications. The utility of the framework was evaluated using wireless accelerometers on a shaking table earthquake simulation test of a reinforced concrete bridge column. The NEESgrid data and metadata repository services were used as a backend storage implementation. A web interface was created to demonstrate the utility of the data model and provides an example health monitoring application.

Using Geographic Information Systems (GIS) to understand a community's primary care needs.

PubMed

Dulin, Michael F; Ludden, Thomas M; Tapp, Hazel; Blackwell, Joshua; de Hernandez, Brisa Urquieta; Smith, Heather A; Furuseth, Owen J

2010-01-01

A key element for reducing health care costs and improving community health is increased access to primary care and preventative health services. Geographic information systems (GIS) have the potential to assess patterns of health care utilization and community-level attributes to identify geographic regions most in need of primary care access. GIS, analytical hierarchy process, and multiattribute assessment and evaluation techniques were used to examine attributes describing primary care need and identify areas that would benefit from increased access to primary care services. Attributes were identified by a collaborative partnership working within a practice-based research network using tenets of community-based participatory research. Maps were created based on socioeconomic status, population density, insurance status, and emergency department and primary care safety-net utilization. Individual and composite maps identified areas in our community with the greatest need for increased access to primary care services. Applying GIS to commonly available community- and patient-level data can rapidly identify areas most in need of increased access to primary care services. We have termed this a Multiple Attribute Primary Care Targeting Strategy. This model can be used to plan health services delivery as well as to target and evaluate interventions designed to improve health care access.

A hierarchical model of daily stream temperature using air-water temperature synchronization, autocorrelation, and time lags

USGS Publications Warehouse

Letcher, Benjamin; Hocking, Daniel; O'Neil, Kyle; Whiteley, Andrew R.; Nislow, Keith H.; O'Donnell, Matthew

2016-01-01

Water temperature is a primary driver of stream ecosystems and commonly forms the basis of stream classifications. Robust models of stream temperature are critical as the climate changes, but estimating daily stream temperature poses several important challenges. We developed a statistical model that accounts for many challenges that can make stream temperature estimation difficult. Our model identifies the yearly period when air and water temperature are synchronized, accommodates hysteresis, incorporates time lags, deals with missing data and autocorrelation and can include external drivers. In a small stream network, the model performed well (RMSE = 0.59°C), identified a clear warming trend (0.63 °C decade−1) and a widening of the synchronized period (29 d decade−1). We also carefully evaluated how missing data influenced predictions. Missing data within a year had a small effect on performance (∼0.05% average drop in RMSE with 10% fewer days with data). Missing all data for a year decreased performance (∼0.6 °C jump in RMSE), but this decrease was moderated when data were available from other streams in the network.

Improving outcomes for patients with type 2 diabetes using general practice networks: a quality improvement project in east London.

PubMed

Hull, Sally; Chowdhury, Tahseen A; Mathur, Rohini; Robson, John

2014-02-01

Structured diabetes care can improve outcomes and reduce risk of complications, but improving care in a deprived, ethnically diverse area can prove challenging. This report evaluates a system change to enhance diabetes care delivery in a primary care setting. All 35 practices in one inner London Primary Care Trust were geographically grouped into eight networks of four to five practices, each supported by a network manager, clerical staff and an educational budget. A multidisciplinary team developed a 'care package' for type 2 diabetes management, with financial incentives based on network achievement of targets. Monthly electronic performance dashboards enabled networks to track and improve performance. Network multidisciplinary team meetings including the diabetic specialist team supported case management and education. Key measures for improvement included the number of diabetes care plans completed, proportion of patients attending for digital retinal screen and proportions of patients achieving a number of biomedical indices (blood pressure, cholesterol, glycated haemoglobin). Between 2009 and 2012, completed care plans rose from 10% to 88%. The proportion of patients attending for digital retinal screen rose from 72% to 82.8%. The proportion of patients achieving a combination of blood pressure ≤ 140/80 mm Hg and cholesterol ≤ 4 mmol/L rose from 35.3% to 46.1%. Mean glycated haemoglobin dropped from 7.80% to 7.66% (62-60 mmol/mol). Investment of financial, organisational and education resources into primary care practice networks can achieve clinically important improvements in diabetes care in deprived, ethnically diverse communities. This success is predicated on collaborative working between practices, purposively designed high-quality information on network performance and engagement between primary and secondary care clinicians.

Education for Sustainable Development and Global Citizenship: Leadership, Collaboration, and Networking in Primary Schools

ERIC Educational Resources Information Center

Bennell, Sheila J.

2015-01-01

The interaction of leadership, collaboration, and networking in the development of Education for Sustainable Development and Global Citizenship (ESDGC) is examined in five north Wales primary schools noted for their ESDGC development. Strong leadership and considerable, but varying, forms of distributed leadership were found in each of the…

Emergence of gamma motor activity in an artificial neural network model of the corticospinal system.

PubMed

Grandjean, Bernard; Maier, Marc A

2017-02-01

Muscle spindle discharge during active movement is a function of mechanical and neural parameters. Muscle length changes (and their derivatives) represent its primary mechanical, fusimotor drive its neural component. However, neither the action nor the function of fusimotor and in particular of γ-drive, have been clearly established, since γ-motor activity during voluntary, non-locomotor movements remains largely unknown. Here, using a computational approach, we explored whether γ-drive emerges in an artificial neural network model of the corticospinal system linked to a biomechanical antagonist wrist simulator. The wrist simulator included length-sensitive and γ-drive-dependent type Ia and type II muscle spindle activity. Network activity and connectivity were derived by a gradient descent algorithm to generate reciprocal, known target α-motor unit activity during wrist flexion-extension (F/E) movements. Two tasks were simulated: an alternating F/E task and a slow F/E tracking task. Emergence of γ-motor activity in the alternating F/E network was a function of α-motor unit drive: if muscle afferent (together with supraspinal) input was required for driving α-motor units, then γ-drive emerged in the form of α-γ coactivation, as predicted by empirical studies. In the slow F/E tracking network, γ-drive emerged in the form of α-γ dissociation and provided critical, bidirectional muscle afferent activity to the cortical network, containing known bidirectional target units. The model thus demonstrates the complementary aspects of spindle output and hence γ-drive: i) muscle spindle activity as a driving force of α-motor unit activity, and ii) afferent activity providing continuous sensory information, both of which crucially depend on γ-drive.

Neural network feedforward control of a closed-circuit wind tunnel

NASA Astrophysics Data System (ADS)

Sutcliffe, Peter

Accurate control of wind-tunnel test conditions can be dramatically enhanced using feedforward control architectures which allow operating conditions to be maintained at a desired setpoint through the use of mathematical models as the primary source of prediction. However, as the desired accuracy of the feedforward prediction increases, the model complexity also increases, so that an ever increasing computational load is incurred. This drawback can be avoided by employing a neural network that is trained offline using the output of a high fidelity wind-tunnel mathematical model, so that the neural network can rapidly reproduce the predictions of the model with a greatly reduced computational overhead. A novel neural network database generation method, developed through the use of fractional factorial arrays, was employed such that a neural network can accurately predict wind-tunnel parameters across a wide range of operating conditions whilst trained upon a highly efficient database. The subsequent network was incorporated into a Neural Network Model Predictive Control (NNMPC) framework to allow an optimised output schedule capable of providing accurate control of the wind-tunnel operating parameters. Facilitation of an optimised path through the solution space is achieved through the use of a chaos optimisation algorithm such that a more globally optimum solution is likely to be found with less computational expense than the gradient descent method. The parameters associated with the NNMPC such as the control horizon are determined through the use of a Taguchi methodology enabling the minimum number of experiments to be carried out to determine the optimal combination. The resultant NNMPC scheme was employed upon the Hessert Low Speed Wind Tunnel at the University of Notre Dame to control the test-section temperature such that it follows a pre-determined reference trajectory during changes in the test-section velocity. Experimental testing revealed that the derived NNMPC controller provided an excellent level of control over the test-section temperature in adherence to a reference trajectory even when faced with unforeseen disturbances such as rapid changes in the operating environment.

Statistical Comparison of Spike Responses to Natural Stimuli in Monkey Area V1 With Simulated Responses of a Detailed Laminar Network Model for a Patch of V1

PubMed Central

Schuch, Klaus; Logothetis, Nikos K.; Maass, Wolfgang

2011-01-01

A major goal of computational neuroscience is the creation of computer models for cortical areas whose response to sensory stimuli resembles that of cortical areas in vivo in important aspects. It is seldom considered whether the simulated spiking activity is realistic (in a statistical sense) in response to natural stimuli. Because certain statistical properties of spike responses were suggested to facilitate computations in the cortex, acquiring a realistic firing regimen in cortical network models might be a prerequisite for analyzing their computational functions. We present a characterization and comparison of the statistical response properties of the primary visual cortex (V1) in vivo and in silico in response to natural stimuli. We recorded from multiple electrodes in area V1 of 4 macaque monkeys and developed a large state-of-the-art network model for a 5 × 5-mm patch of V1 composed of 35,000 neurons and 3.9 million synapses that integrates previously published anatomical and physiological details. By quantitative comparison of the model response to the “statistical fingerprint” of responses in vivo, we find that our model for a patch of V1 responds to the same movie in a way which matches the statistical structure of the recorded data surprisingly well. The deviation between the firing regimen of the model and the in vivo data are on the same level as deviations among monkeys and sessions. This suggests that, despite strong simplifications and abstractions of cortical network models, they are nevertheless capable of generating realistic spiking activity. To reach a realistic firing state, it was not only necessary to include both N-methyl-d-aspartate and GABAB synaptic conductances in our model, but also to markedly increase the strength of excitatory synapses onto inhibitory neurons (>2-fold) in comparison to literature values, hinting at the importance to carefully adjust the effect of inhibition for achieving realistic dynamics in current network models. PMID:21106898

Sol-Gel assembly of CdSe nanoparticles to form porous aerogel networks.

PubMed

Arachchige, Indika U; Brock, Stephanie L

2006-06-21

A detailed study of CdSe aerogels prepared by oxidative aggregation of primary nanoparticles (prepared at room temperature and high temperature conditions, >250 degrees C), followed by CO2 supercritical drying, is described. The resultant materials are mesoporous, with an interconnected network of colloidal nanoparticles, and exhibit BET surface areas up to 224 m2/g and BJH average pore diameters in the range of 16-32 nm. Powder X-ray diffraction studies indicate that these materials retain the crystal structure of the primary nanoparticles, with a slight increase in primary particle size upon gelation and aerogel formation. Optical band gap measurements and photoluminescence studies show that the as-prepared aerogels retain the quantum-confined optical properties of the nanoparticle building blocks despite being connected into a 3-D network. The specific optical characteristics of the aerogel can be further modified by surface ligand exchange at the wet-gel stage, without destroying the gel network.

Decay of interspecific avian flock networks along a disturbance gradient in Amazonia.

PubMed

Mokross, Karl; Ryder, Thomas B; Côrtes, Marina Corrêa; Wolfe, Jared D; Stouffer, Philip C

2014-02-07

Our understanding of how anthropogenic habitat change shapes species interactions is in its infancy. This is in large part because analytical approaches such as network theory have only recently been applied to characterize complex community dynamics. Network models are a powerful tool for quantifying how ecological interactions are affected by habitat modification because they provide metrics that quantify community structure and function. Here, we examine how large-scale habitat alteration has affected ecological interactions among mixed-species flocking birds in Amazonian rainforest. These flocks provide a model system for investigating how habitat heterogeneity influences non-trophic interactions and the subsequent social structure of forest-dependent mixed-species bird flocks. We analyse 21 flock interaction networks throughout a mosaic of primary forest, fragments of varying sizes and secondary forest (SF) at the Biological Dynamics of Forest Fragments Project in central Amazonian Brazil. Habitat type had a strong effect on network structure at the levels of both species and flock. Frequency of associations among species, as summarized by weighted degree, declined with increasing levels of forest fragmentation and SF. At the flock level, clustering coefficients and overall attendance positively correlated with mean vegetation height, indicating a strong effect of habitat structure on flock cohesion and stability. Prior research has shown that trophic interactions are often resilient to large-scale changes in habitat structure because species are ecologically redundant. By contrast, our results suggest that behavioural interactions and the structure of non-trophic networks are highly sensitive to environmental change. Thus, a more nuanced, system-by-system approach may be needed when thinking about the resiliency of ecological networks.

Competition among gene regulatory networks imposes order within the eye-antennal disc of Drosophila

PubMed Central

Weasner, Bonnie M.; Kumar, Justin P.

2013-01-01

The eye-antennal disc of Drosophila gives rise to numerous adult tissues, including the compound eyes, ocelli, antennae, maxillary palps and surrounding head capsule. The fate of each tissue is governed by the activity of unique gene regulatory networks (GRNs). The fate of the eye, for example, is controlled by a set of fourteen interlocking genes called the retinal determination (RD) network. Mutations within network members lead to replacement of the eyes with head capsule. Several studies have suggested that in these instances all retinal progenitor and precursor cells are eliminated via apoptosis and as a result the surrounding head capsule proliferates to compensate for retinal tissue loss. This model implies that the sole responsibility of the RD network is to promote the fate of the eye. We have re-analyzed eyes absent mutant discs and propose an alternative model. Our data suggests that in addition to promoting an eye fate the RD network simultaneously functions to actively repress GRNs that are responsible for directing antennal and head capsule fates. Compromising the RD network leads to the inappropriate expression of several head capsule selector genes such as cut, Lim1 and wingless. Instead of undergoing apoptosis, a population of mutant retinal progenitors and precursor cells adopt a head capsule fate. This transformation is accompanied by an adjustment of cell proliferation rates such that just enough head capsule is generated to produce an intact adult head. We propose that GRNs simultaneously promote primary fates, inhibit alternative fates and establish cell proliferation states. PMID:23222441

Vitamin D and ferritin correlation with chronic neck pain using standard statistics and a novel artificial neural network prediction model.

PubMed

Eloqayli, Haytham; Al-Yousef, Ali; Jaradat, Raid

2018-02-15

Despite the high prevalence of chronic neck pain, there is limited consensus about the primary etiology, risk factors, diagnostic criteria and therapeutic outcome. Here, we aimed to determine if Ferritin and Vitamin D are modifiable risk factors with chronic neck pain using slandered statistics and artificial intelligence neural network (ANN). Fifty-four patients with chronic neck pain treated between February 2016 and August 2016 in King Abdullah University Hospital and 54 patients age matched controls undergoing outpatient or minor procedures were enrolled. Patients and control demographic parameters, height, weight and single measurement of serum vitamin D, Vitamin B12, ferritin, calcium, phosphorus, zinc were obtained. An ANN prediction model was developed. The statistical analysis reveals that patients with chronic neck pain have significantly lower serum Vitamin D and Ferritin (p-value <.05). 90% of patients with chronic neck pain were females. Multilayer Feed Forward Neural Network with Back Propagation(MFFNN) prediction model were developed and designed based on vitamin D and ferritin as input variables and CNP as output. The ANN model output results show that, 92 out of 108 samples were correctly classified with 85% classification accuracy. Although Iron and vitamin D deficiency cannot be isolated as the sole risk factors of chronic neck pain, they should be considered as two modifiable risk. The high prevalence of chronic neck pain, hypovitaminosis D and low ferritin amongst women is of concern. Bioinformatics predictions with artificial neural network can be of future benefit in classification and prediction models for chronic neck pain. We hope this initial work will encourage a future larger cohort study addressing vitamin D and iron correction as modifiable factors and the application of artificial intelligence models in clinical practice.

Biomarker microRNAs for prostate cancer metastasis: screened with a network vulnerability analysis model.

PubMed

Lin, Yuxin; Chen, Feifei; Shen, Li; Tang, Xiaoyu; Du, Cui; Sun, Zhandong; Ding, Huijie; Chen, Jiajia; Shen, Bairong

2018-05-21

Prostate cancer (PCa) is a fatal malignant tumor among males in the world and the metastasis is a leading cause for PCa death. Biomarkers are therefore urgently needed to detect PCa metastatic signature at the early time. MicroRNAs are small non-coding RNAs with the potential to be biomarkers for disease prediction. In addition, computer-aided biomarker discovery is now becoming an attractive paradigm for precision diagnosis and prognosis of complex diseases. In this study, we identified key microRNAs as biomarkers for predicting PCa metastasis based on network vulnerability analysis. We first extracted microRNAs and mRNAs that were differentially expressed between primary PCa and metastatic PCa (MPCa) samples. Then we constructed the MPCa-specific microRNA-mRNA network and screened microRNA biomarkers by a novel bioinformatics model. The model emphasized the characterization of systems stability changes and the network vulnerability with three measurements, i.e. the structurally single-line regulation, the functional importance of microRNA targets and the percentage of transcription factor genes in microRNA unique targets. With this model, we identified five microRNAs as putative biomarkers for PCa metastasis. Among them, miR-101-3p and miR-145-5p have been previously reported as biomarkers for PCa metastasis and the remaining three, i.e. miR-204-5p, miR-198 and miR-152, were screened as novel biomarkers for PCa metastasis. The results were further confirmed by the assessment of their predictive power and biological function analysis. Five microRNAs were identified as candidate biomarkers for predicting PCa metastasis based on our network vulnerability analysis model. The prediction performance, literature exploration and functional enrichment analysis convinced our findings. This novel bioinformatics model could be applied to biomarker discovery for other complex diseases.

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

PubMed

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

2016-06-22

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

Social Network Analysis Applied to a Historical Ethnographic Study Surrounding Home Birth.

PubMed

Andina-Diaz, Elena; Ovalle-Perandones, Mª Antonia; Ramos-Vidal, Ignacio; Camacho-Morell, Francisca; Siles-Gonzalez, Jose; Marques-Sanchez, Pilar

2018-04-24

Safety during birth has improved since hospital delivery became standard practice, but the process has also become increasingly medicalised. Hence, recent years have witnessed a growing interest in home births due to the advantages it offers to mothers and their newborn infants. The aims of the present study were to confirm the transition from a home birth model of care to a scenario in which deliveries began to occur almost exclusively in a hospital setting; to define the social networks surrounding home births; and to determine whether geography exerted any influence on the social networks surrounding home births. Adopting a qualitative approach, we recruited 19 women who had given birth at home in the mid 20th century in a rural area in Spain. We employed a social network analysis method. Our results revealed three essential aspects that remain relevant today: the importance of health professionals in home delivery care, the importance of the mother’s primary network, and the influence of the geographical location of the actors involved in childbirth. All of these factors must be taken into consideration when developing strategies for maternal health.

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

NASA Astrophysics Data System (ADS)

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

2016-06-01

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

Translating knowledge into practice and policy: the role of knowledge networks in primary health care.

PubMed

Armstrong, Kylie; Kendall, Elizabeth

The translation of information into practice is a well-recognised challenge for the health sector. In the primary healthcare sector, the last decade has seen an explosion of information generated by health systems, universities and a range of other sources. Without a system for translating that knowledge into practice and sharing it in a comprehensible form, it will remain meaningless to most practitioners. We propose the establishment of Knowledge Networks as a promising method for supporting the rapid adoption and generation of health information within the primary health care sector to advance health care services. These networks will be particularly important to the implementation of the national reform agenda, responsive decision-making and the translation of new frameworks or competencies into practice. This paper describes how interdisciplinary Knowledge Networks could be established focusing on a number of priority health research areas. Local Knowledge Networks would be used as a platform to support a collaborative web of evidence designed to influence health policy and planning. Our experience with Knowledge Networks indicates that they must be comprised of health professionals from Divisions of General Practice, researchers, policy-makers, consumers, government and non-government sectors. This paper will describe these networks and show how they might support the translation of knowledge into practice, thus driving systematic and institutional change.

Structure of the Social Support Network of Patients with Severe and Persistent Psychiatric Disorders in Follow-Ups to Primary Health Care.

PubMed

de Souza, Jacqueline; de Almeida, Letícia Yamawaka; Moll, Marciana Fernandes; Silva, Lucas Duarte; Ventura, Carla Aparecida Arena

2016-02-01

The objective of this study is to analyze the characteristics of social support networks of patients with psychiatric disorders at follow-up to primary care. This is a cross-sectional qualitative research study. Forty-five interviews were held with patients and their supporters. The results showed small and dense networks, with a strong emphasis on the bonds with formal supporters and a scant network of informal supporters. It is recommended to develop strategies to improve social support networks and use this as an outcome indicator related to social integration of these patients and to the quality of services involved with outpatient healthcare. Copyright © 2015 Elsevier Inc. All rights reserved.

Engineering-Aligned 3D Neural Circuit in Microfluidic Device.

PubMed

Bang, Seokyoung; Na, Sangcheol; Jang, Jae Myung; Kim, Jinhyun; Jeon, Noo Li

2016-01-07

The brain is one of the most important and complex organs in the human body. Although various neural network models have been proposed for in vitro 3D neuronal networks, it has been difficult to mimic functional and structural complexity of the in vitro neural circuit. Here, a microfluidic model of a simplified 3D neural circuit is reported. First, the microfluidic device is filled with Matrigel and continuous flow is delivered across the device during gelation. The fluidic flow aligns the extracellular matrix (ECM) components along the flow direction. Following the alignment of ECM fibers, neurites of primary rat cortical neurons are grown into the Matrigel at the average speed of 250 μm d(-1) and form axon bundles approximately 1500 μm in length at 6 days in vitro (DIV). Additionally, neural networks are developed from presynaptic to postsynaptic neurons at 14 DIV. The establishment of aligned 3D neural circuits is confirmed with the immunostaining of PSD-95 and synaptophysin and the observation of calcium signal transmission. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Model analysis of the link between interest rates and crashes

NASA Astrophysics Data System (ADS)

Broga, Kristijonas M.; Viegas, Eduardo; Jensen, Henrik Jeldtoft

2016-09-01

We analyse the effect of distinct levels of interest rates on the stability of the financial network under our modelling framework. We demonstrate that banking failures are likely to emerge early on under sustained high interest rates, and at much later stage-with higher probability-under a sustained low interest rate scenario. Moreover, we demonstrate that those bank failures are of a different nature: high interest rates tend to result in significantly more bankruptcies associated to credit losses whereas lack of liquidity tends to be the primary cause of failures under lower rates.

A protein phosphatase network controls the temporal and spatial dynamics of differentiation commitment in human epidermis

PubMed Central

Walko, Gernot; Viswanathan, Priyalakshmi; Tihy, Matthieu; Nijjher, Jagdeesh; Dunn, Sara-Jane; Lamond, Angus I

2017-01-01

Epidermal homeostasis depends on a balance between stem cell renewal and terminal differentiation. The transition between the two cell states, termed commitment, is poorly understood. Here, we characterise commitment by integrating transcriptomic and proteomic data from disaggregated primary human keratinocytes held in suspension to induce differentiation. Cell detachment induces several protein phosphatases, five of which - DUSP6, PPTC7, PTPN1, PTPN13 and PPP3CA – promote differentiation by negatively regulating ERK MAPK and positively regulating AP1 transcription factors. Conversely, DUSP10 expression antagonises commitment. The phosphatases form a dynamic network of transient positive and negative interactions that change over time, with DUSP6 predominating at commitment. Boolean network modelling identifies a mandatory switch between two stable states (stem and differentiated) via an unstable (committed) state. Phosphatase expression is also spatially regulated in vivo and in vitro. We conclude that an auto-regulatory phosphatase network maintains epidermal homeostasis by controlling the onset and duration of commitment. PMID:29043977

The Need and Keys for a New Generation Network Adjustment Software

NASA Astrophysics Data System (ADS)

Colomina, I.; Blázquez, M.; Navarro, J. A.; Sastre, J.

2012-07-01

Orientation and calibration of photogrammetric and remote sensing instruments is a fundamental capacity of current mapping systems and a fundamental research topic. Neither digital remote sensing acquisition systems nor direct orientation gear, like INS and GNSS technologies, made block adjustment obsolete. On the contrary, the continuous flow of new primary data acquisition systems has challenged the capacity of the legacy block adjustment systems - in general network adjustment systems - in many aspects: extensibility, genericity, portability, large data sets capacity, metadata support and many others. In this article, we concentrate on the extensibility and genericity challenges that current and future network systems shall face. For this purpose we propose a number of software design strategies with emphasis on rigorous abstract modeling that help in achieving simplicity, genericity and extensibility together with the protection of intellectual proper rights in a flexible manner. We illustrate our suggestions with the general design approach of GENA, the generic extensible network adjustment system of GeoNumerics.

Optimal satisfaction degree in energy harvesting cognitive radio networks

NASA Astrophysics Data System (ADS)

Li, Zan; Liu, Bo-Yang; Si, Jiang-Bo; Zhou, Fu-Hui

2015-12-01

A cognitive radio (CR) network with energy harvesting (EH) is considered to improve both spectrum efficiency and energy efficiency. A hidden Markov model (HMM) is used to characterize the imperfect spectrum sensing process. In order to maximize the whole satisfaction degree (WSD) of the cognitive radio network, a tradeoff between the average throughput of the secondary user (SU) and the interference to the primary user (PU) is analyzed. We formulate the satisfaction degree optimization problem as a mixed integer nonlinear programming (MINLP) problem. The satisfaction degree optimization problem is solved by using differential evolution (DE) algorithm. The proposed optimization problem allows the network to adaptively achieve the optimal solution based on its required quality of service (Qos). Numerical results are given to verify our analysis. Project supported by the National Natural Science Foundation of China (Grant No. 61301179), the Doctorial Programs Foundation of the Ministry of Education of China (Grant No. 20110203110011), and the 111 Project (Grant No. B08038).

Optimisation of sensing time and transmission time in cognitive radio-based smart grid networks

NASA Astrophysics Data System (ADS)

Yang, Chao; Fu, Yuli; Yang, Junjie

2016-07-01

Cognitive radio (CR)-based smart grid (SG) networks have been widely recognised as emerging communication paradigms in power grids. However, a sufficient spectrum resource and reliability are two major challenges for real-time applications in CR-based SG networks. In this article, we study the traffic data collection problem. Based on the two-stage power pricing model, the power price is associated with the efficient received traffic data in a metre data management system (MDMS). In order to minimise the system power price, a wideband hybrid access strategy is proposed and analysed, to share the spectrum between the SG nodes and CR networks. The sensing time and transmission time are jointly optimised, while both the interference to primary users and the spectrum opportunity loss of secondary users are considered. Two algorithms are proposed to solve the joint optimisation problem. Simulation results show that the proposed joint optimisation algorithms outperform the fixed parameters (sensing time and transmission time) algorithms, and the power cost is reduced efficiently.

Cognitive radio based optimal channel sensing and resources allocation

NASA Astrophysics Data System (ADS)

Vijayasarveswari, V.; Khatun, S.; Fakir, M. M.; Nayeem, M. N.; Kamarudin, L. M.; Jakaria, A.

2017-03-01

Cognitive radio (CR) is the latest type of wireless technoloy that is proposed to mitigate spectrum saturation problem. İn cognitve radio, secondary user will use primary user's spectrum during primary user's absence without interupting primary user's transmission. This paper focuses on practical cognitive radio network development process using Android based smart phone for the data transmission. Energy detector based sensing method was proposed and used here because it doesnot require primary user's information. Bluetooth and Wi-fi are the two available types of spectrum that was sensed for CR detection. Simulation showed cognitive radio network can be developed using Android based smart phones. So, a complete application was developed using Java based Android Eclipse program. Finally, the application was uploaded and run on Android based smart phone to form and verify CR network for channel sensing and resource allocation. The observed efficiency of the application was around 81%.

A coupled-oscillator model of olfactory bulb gamma oscillations

PubMed Central

2017-01-01

The olfactory bulb transforms not only the information content of the primary sensory representation, but also its underlying coding metric. High-variance, slow-timescale primary odor representations are transformed by bulbar circuitry into secondary representations based on principal neuron spike patterns that are tightly regulated in time. This emergent fast timescale for signaling is reflected in gamma-band local field potentials, presumably serving to efficiently integrate olfactory sensory information into the temporally regulated information networks of the central nervous system. To understand this transformation and its integration with interareal coordination mechanisms requires that we understand its fundamental dynamical principles. Using a biophysically explicit, multiscale model of olfactory bulb circuitry, we here demonstrate that an inhibition-coupled intrinsic oscillator framework, pyramidal resonance interneuron network gamma (PRING), best captures the diversity of physiological properties exhibited by the olfactory bulb. Most importantly, these properties include global zero-phase synchronization in the gamma band, the phase-restriction of informative spikes in principal neurons with respect to this common clock, and the robustness of this synchronous oscillatory regime to multiple challenging conditions observed in the biological system. These conditions include substantial heterogeneities in afferent activation levels and excitatory synaptic weights, high levels of uncorrelated background activity among principal neurons, and spike frequencies in both principal neurons and interneurons that are irregular in time and much lower than the gamma frequency. This coupled cellular oscillator architecture permits stable and replicable ensemble responses to diverse sensory stimuli under various external conditions as well as to changes in network parameters arising from learning-dependent synaptic plasticity. PMID:29140973

Comparing and contrasting 'innovation platforms' with other forms of professional networks for strengthening primary healthcare systems for Indigenous Australians.

PubMed

Bailie, Jodie; Cunningham, Frances Clare; Bainbridge, Roxanne Gwendalyn; Passey, Megan E; Laycock, Alison Frances; Bailie, Ross Stewart; Larkins, Sarah L; Brands, Jenny S M; Ramanathan, Shanthi; Abimbola, Seye; Peiris, David

2018-01-01

Efforts to strengthen health systems require the engagement of diverse, multidisciplinary stakeholder networks. Networks provide a forum for experimentation and knowledge creation, information exchange and the spread of good ideas and practice. They might be useful in addressing complex issues or 'wicked' problems, the solutions to which go beyond the control and scope of any one agency. Innovation platforms are proposed as a novel type of network because of their diverse stakeholder composition and focus on problem solving within complex systems. Thus, they have potential applicability to health systems strengthening initiatives, even though they have been predominantly applied in the international agricultural development sector. In this paper, we compare and contrast the concept of innovation platforms with other types of networks that can be used in efforts to strengthen primary healthcare systems, such as communities of practice, practice-based research networks and quality improvement collaboratives. We reflect on our ongoing research programme that applies innovation platform concepts to drive large-scale quality improvement in primary healthcare for Aboriginal and Torres Strait Islander Australians and outline our plans for evaluation. Lessons from our experience will find resonance with others working on similar initiatives in global health.

Spontaneous Up states in vitro: a single-metric index of the functional maturation and regional differentiation of the cerebral cortex.

PubMed

Rigas, Pavlos; Adamos, Dimitrios A; Sigalas, Charalambos; Tsakanikas, Panagiotis; Laskaris, Nikolaos A; Skaliora, Irini

2015-01-01

Understanding the development and differentiation of the neocortex remains a central focus of neuroscience. While previous studies have examined isolated aspects of cellular and synaptic organization, an integrated functional index of the cortical microcircuit is still lacking. Here we aimed to provide such an index, in the form of spontaneously recurring periods of persistent network activity -or Up states- recorded in mouse cortical slices. These coordinated network dynamics emerge through the orchestrated regulation of multiple cellular and synaptic elements and represent the default activity of the cortical microcircuit. To explore whether spontaneous Up states can capture developmental changes in intracortical networks we obtained local field potential recordings throughout the mouse lifespan. Two independent and complementary methodologies revealed that Up state activity is systematically modified by age, with the largest changes occurring during early development and adolescence. To explore possible regional heterogeneities we also compared the development of Up states in two distinct cortical areas and show that primary somatosensory cortex develops at a faster pace than primary motor cortex. Our findings suggest that in vitro Up states can serve as a functional index of cortical development and differentiation and can provide a baseline for comparing experimental and/or genetic mouse models.

Friends with Faces: How Social Networks Can Enhance Face Recognition and Vice Versa

NASA Astrophysics Data System (ADS)

Mavridis, Nikolaos; Kazmi, Wajahat; Toulis, Panos

The "friendship" relation, a social relation among individuals, is one of the primary relations modeled in some of the world's largest online social networking sites, such as "FaceBook." On the other hand, the "co-occurrence" relation, as a relation among faces appearing in pictures, is one that is easily detectable using modern face detection techniques. These two relations, though appearing in different realms (social vs. visual sensory), have a strong correlation: faces that co-occur in photos often belong to individuals who are friends. Using real-world data gathered from "Facebook," which were gathered as part of the "FaceBots" project, the world's first physical face-recognizing and conversing robot that can utilize and publish information on "Facebook" was established. We present here methods as well as results for utilizing this correlation in both directions. Both algorithms for utilizing knowledge of the social context for faster and better face recognition are given, as well as algorithms for estimating the friendship network of a number of individuals given photos containing their faces. The results are quite encouraging. In the primary example, doubling of the recognition accuracy as well as a sixfold improvement in speed is demonstrated. Various improvements, interesting statistics, as well as an empirical investigation leading to predictions of scalability to much bigger data sets are discussed.

Spontaneous Up states in vitro: a single-metric index of the functional maturation and regional differentiation of the cerebral cortex

PubMed Central

Rigas, Pavlos; Adamos, Dimitrios A.; Sigalas, Charalambos; Tsakanikas, Panagiotis; Laskaris, Nikolaos A.; Skaliora, Irini

2015-01-01

Understanding the development and differentiation of the neocortex remains a central focus of neuroscience. While previous studies have examined isolated aspects of cellular and synaptic organization, an integrated functional index of the cortical microcircuit is still lacking. Here we aimed to provide such an index, in the form of spontaneously recurring periods of persistent network activity -or Up states- recorded in mouse cortical slices. These coordinated network dynamics emerge through the orchestrated regulation of multiple cellular and synaptic elements and represent the default activity of the cortical microcircuit. To explore whether spontaneous Up states can capture developmental changes in intracortical networks we obtained local field potential recordings throughout the mouse lifespan. Two independent and complementary methodologies revealed that Up state activity is systematically modified by age, with the largest changes occurring during early development and adolescence. To explore possible regional heterogeneities we also compared the development of Up states in two distinct cortical areas and show that primary somatosensory cortex develops at a faster pace than primary motor cortex. Our findings suggest that in vitro Up states can serve as a functional index of cortical development and differentiation and can provide a baseline for comparing experimental and/or genetic mouse models. PMID:26528142

The primary case is not enough: Variation among individuals, groups and social networks modify bacterial transmission dynamics.

PubMed

Keiser, Carl N; Pinter-Wollman, Noa; Ziemba, Michael J; Kothamasu, Krishna S; Pruitt, Jonathan N

2018-03-01

The traits of the primary case of an infectious disease outbreak, and the circumstances for their aetiology, potentially influence the trajectory of transmission dynamics. However, these dynamics likely also depend on the traits of the individuals with whom the primary case interacts. We used the social spider Stegodyphus dumicola to test how the traits of the primary case, group phenotypic composition and group size interact to facilitate the transmission of a GFP-labelled cuticular bacterium. We also compared bacterial transmission across experimentally generated "daisy-chain" vs. "star" networks of social interactions. Finally, we compared social network structure across groups of different sizes. Groups of 10 spiders experienced more bacterial transmission events compared to groups of 30 spiders, regardless of groups' behavioural composition. Groups containing only one bold spider experienced the lowest levels of bacterial transmission regardless of group size. We found no evidence for the traits of the primary case influencing any transmission dynamics. In a second experiment, bacteria were transmitted to more individuals in experimentally induced star networks than in daisy-chains, on which transmission never exceeded three steps. In both experimental network types, transmission success depended jointly on the behavioural traits of the interacting individuals; however, the behavioural traits of the primary case were only important for transmission on star networks. Larger social groups exhibited lower interaction density (i.e. had a low ratio of observed to possible connections) and were more modular, i.e. they had more connections between nodes within a subgroup and fewer connections across subgroups. Thus, larger groups may restrict transmission by forming fewer interactions and by isolating subgroups that interacted with the primary case. These findings suggest that accounting for the traits of single exposed hosts has less power in predicting transmission dynamics compared to the larger scale factors of the social groups in which they reside. Factors like group size and phenotypic composition appear to alter social interaction patterns, which leads to differential transmission of microbes. © 2017 The Authors. Journal of Animal Ecology © 2017 British Ecological Society.

Coupled flow and deformations in granular systems beyond the pendular regime

NASA Astrophysics Data System (ADS)

Yuan, Chao; Chareyre, Bruno; Darve, Felix

2017-06-01

A pore-scale numerical model is proposed for simulating the quasi-static primary drainage and the hydro-mechanical couplings in multiphase granular systems. The solid skeleton is idealized to a dense random packing of polydisperse spheres by DEM. The fluids (nonwetting and wetting phases) space is decomposed to a network of tetrahedral pores based on the Regular Triangulation method. The local drainage rules and invasion logic are defined. The fluid forces acting on solid grains are formulated. The model can simulate the hydraulic evolution from a fully saturated state to a low level of saturation but beyond the pendular regime. The features of wetting phase entrapments and capillary fingering can also be reproduced. Finally, a primary drainage test is performed on a 40,000 spheres of sample. The water retention curve is obtained. The solid skeleton first shrinks then swells.

An actor-based model of social network influence on adolescent body size, screen time, and playing sports.

PubMed

Shoham, David A; Tong, Liping; Lamberson, Peter J; Auchincloss, Amy H; Zhang, Jun; Dugas, Lara; Kaufman, Jay S; Cooper, Richard S; Luke, Amy

2012-01-01

Recent studies suggest that obesity may be "contagious" between individuals in social networks. Social contagion (influence), however, may not be identifiable using traditional statistical approaches because they cannot distinguish contagion from homophily (the propensity for individuals to select friends who are similar to themselves) or from shared environmental influences. In this paper, we apply the stochastic actor-based model (SABM) framework developed by Snijders and colleagues to data on adolescent body mass index (BMI), screen time, and playing active sports. Our primary hypothesis was that social influences on adolescent body size and related behaviors are independent of friend selection. Employing the SABM, we simultaneously modeled network dynamics (friendship selection based on homophily and structural characteristics of the network) and social influence. We focused on the 2 largest schools in the National Longitudinal Study of Adolescent Health (Add Health) and held the school environment constant by examining the 2 school networks separately (N = 624 and 1151). Results show support in both schools for homophily on BMI, but also for social influence on BMI. There was no evidence of homophily on screen time in either school, while only one of the schools showed homophily on playing active sports. There was, however, evidence of social influence on screen time in one of the schools, and playing active sports in both schools. These results suggest that both homophily and social influence are important in understanding patterns of adolescent obesity. Intervention efforts should take into consideration peers' influence on one another, rather than treating "high risk" adolescents in isolation.

Orientation selectivity in inhibition-dominated networks of spiking neurons: effect of single neuron properties and network dynamics.

PubMed

Sadeh, Sadra; Rotter, Stefan

2015-01-01

The neuronal mechanisms underlying the emergence of orientation selectivity in the primary visual cortex of mammals are still elusive. In rodents, visual neurons show highly selective responses to oriented stimuli, but neighboring neurons do not necessarily have similar preferences. Instead of a smooth map, one observes a salt-and-pepper organization of orientation selectivity. Modeling studies have recently confirmed that balanced random networks are indeed capable of amplifying weakly tuned inputs and generating highly selective output responses, even in absence of feature-selective recurrent connectivity. Here we seek to elucidate the neuronal mechanisms underlying this phenomenon by resorting to networks of integrate-and-fire neurons, which are amenable to analytic treatment. Specifically, in networks of perfect integrate-and-fire neurons, we observe that highly selective and contrast invariant output responses emerge, very similar to networks of leaky integrate-and-fire neurons. We then demonstrate that a theory based on mean firing rates and the detailed network topology predicts the output responses, and explains the mechanisms underlying the suppression of the common-mode, amplification of modulation, and contrast invariance. Increasing inhibition dominance in our networks makes the rectifying nonlinearity more prominent, which in turn adds some distortions to the otherwise essentially linear prediction. An extension of the linear theory can account for all the distortions, enabling us to compute the exact shape of every individual tuning curve in our networks. We show that this simple form of nonlinearity adds two important properties to orientation selectivity in the network, namely sharpening of tuning curves and extra suppression of the modulation. The theory can be further extended to account for the nonlinearity of the leaky model by replacing the rectifier by the appropriate smooth input-output transfer function. These results are robust and do not depend on the state of network dynamics, and hold equally well for mean-driven and fluctuation-driven regimes of activity.

Orientation Selectivity in Inhibition-Dominated Networks of Spiking Neurons: Effect of Single Neuron Properties and Network Dynamics

PubMed Central

Sadeh, Sadra; Rotter, Stefan

2015-01-01

The neuronal mechanisms underlying the emergence of orientation selectivity in the primary visual cortex of mammals are still elusive. In rodents, visual neurons show highly selective responses to oriented stimuli, but neighboring neurons do not necessarily have similar preferences. Instead of a smooth map, one observes a salt-and-pepper organization of orientation selectivity. Modeling studies have recently confirmed that balanced random networks are indeed capable of amplifying weakly tuned inputs and generating highly selective output responses, even in absence of feature-selective recurrent connectivity. Here we seek to elucidate the neuronal mechanisms underlying this phenomenon by resorting to networks of integrate-and-fire neurons, which are amenable to analytic treatment. Specifically, in networks of perfect integrate-and-fire neurons, we observe that highly selective and contrast invariant output responses emerge, very similar to networks of leaky integrate-and-fire neurons. We then demonstrate that a theory based on mean firing rates and the detailed network topology predicts the output responses, and explains the mechanisms underlying the suppression of the common-mode, amplification of modulation, and contrast invariance. Increasing inhibition dominance in our networks makes the rectifying nonlinearity more prominent, which in turn adds some distortions to the otherwise essentially linear prediction. An extension of the linear theory can account for all the distortions, enabling us to compute the exact shape of every individual tuning curve in our networks. We show that this simple form of nonlinearity adds two important properties to orientation selectivity in the network, namely sharpening of tuning curves and extra suppression of the modulation. The theory can be further extended to account for the nonlinearity of the leaky model by replacing the rectifier by the appropriate smooth input-output transfer function. These results are robust and do not depend on the state of network dynamics, and hold equally well for mean-driven and fluctuation-driven regimes of activity. PMID:25569445

[A network to promote health systems based on primary health care in the Region of the Americas].

PubMed

Herrera Vázquez, María Magdalena; Rodríguez Avila, Nuria; Nebot Adell, Carme; Montenegro, Hernán

2007-05-01

To identify the relational components of an international network of organizations that provide technical and financial assistance to promote the development of health systems based on primary health care in the countries of the Region of the Americas; to analyze the linkages that would allow the collaborating partners of the Pan American Health Organization (PAHO) to work together on health issues; and to determine the basic theoretical elements that can help to develop action strategies that support advocacy efforts by a network. This was a qualitative and quantitative cross-sectional study based on identifying key informants and on analyzing social networks. Ethnographic and relational information from 46 international organizations was collected through a self-administered semistructured questionnaire. From 46 international health cooperation organizations, 29 decision makers from 29 organizations participated (63.0% response rate). The structure and the strength of the network was evaluated in terms of density, closeness, clustering, and centralization. The statistical analysis was done using computer programs that included UCINET, Pajek, and Microsoft Access. We found a structurally centralized theoretical network, whose nodes were clustered into four central subgroups linked by a shared vision. The leadership, influence, and political interests reflected the formal and technical-cooperation linkages, the formal support for health systems based on primary health care, and the flow of resources being more often technical ones than financial ones. The interorganizational relational components and the social-action ties that were identified could help in the development and consolidation of a thematic network for advocacy and for the management of technical and financial assistance that supports primary health care in the Americas. The linkages for joint action that were identified could advance international cooperation in developing health systems based on primary health care, once PAHO formulates clear implementation strategies and takes a leadership position in mobilizing financial resources and in creating informal and interpersonal linkages for action.

47 CFR 90.1407 - Spectrum use in the network.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 5 2011-10-01 2011-10-01 false Spectrum use in the network. 90.1407 Section 90... network. (a) Spectrum use. The Shared Wireless Broadband Network will operate using spectrum associated... from the primary public safety operations in the 763-768 MHz and 793-798 MHz bands. The network...

47 CFR 90.1407 - Spectrum use in the network.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 47 Telecommunication 5 2010-10-01 2010-10-01 false Spectrum use in the network. 90.1407 Section 90... network. (a) Spectrum use. The Shared Wireless Broadband Network will operate using spectrum associated... from the primary public safety operations in the 763-768 MHz and 793-798 MHz bands. The network...

47 CFR 27.1307 - Spectrum use in the network.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 2 2011-10-01 2011-10-01 false Spectrum use in the network. 27.1307 Section 27... network. (a) Spectrum use. The shared wireless broadband network developed by the 700 MHz Public/Private... from the primary public safety operations in the 763-768 MHz and 793-798 MHz bands. The network...

47 CFR 27.1307 - Spectrum use in the network.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 47 Telecommunication 2 2010-10-01 2010-10-01 false Spectrum use in the network. 27.1307 Section 27... network. (a) Spectrum use. The shared wireless broadband network developed by the 700 MHz Public/Private... from the primary public safety operations in the 763-768 MHz and 793-798 MHz bands. The network...

Opportunistic Capacity-Based Resource Allocation for Chunk-Based Multi-Carrier Cognitive Radio Sensor Networks

PubMed Central

Huang, Jie; Zeng, Xiaoping; Jian, Xin; Tan, Xiaoheng; Zhang, Qi

2017-01-01

The spectrum allocation for cognitive radio sensor networks (CRSNs) has received considerable research attention under the assumption that the spectrum environment is static. However, in practice, the spectrum environment varies over time due to primary user/secondary user (PU/SU) activity and mobility, resulting in time-varied spectrum resources. This paper studies resource allocation for chunk-based multi-carrier CRSNs with time-varied spectrum resources. We present a novel opportunistic capacity model through a continuous time semi-Markov chain (CTSMC) to describe the time-varied spectrum resources of chunks and, based on this, a joint power and chunk allocation model by considering the opportunistically available capacity of chunks is proposed. To reduce the computational complexity, we split this model into two sub-problems and solve them via the Lagrangian dual method. Simulation results illustrate that the proposed opportunistic capacity-based resource allocation algorithm can achieve better performance compared with traditional algorithms when the spectrum environment is time-varied. PMID:28106803

Supervised Machine Learning for Regionalization of Environmental Data: Distribution of Uranium in Groundwater in Ukraine

NASA Astrophysics Data System (ADS)

Govorov, Michael; Gienko, Gennady; Putrenko, Viktor

2018-05-01

In this paper, several supervised machine learning algorithms were explored to define homogeneous regions of con-centration of uranium in surface waters in Ukraine using multiple environmental parameters. The previous study was focused on finding the primary environmental parameters related to uranium in ground waters using several methods of spatial statistics and unsupervised classification. At this step, we refined the regionalization using Artifi-cial Neural Networks (ANN) techniques including Multilayer Perceptron (MLP), Radial Basis Function (RBF), and Convolutional Neural Network (CNN). The study is focused on building local ANN models which may significantly improve the prediction results of machine learning algorithms by taking into considerations non-stationarity and autocorrelation in spatial data.

Global dysrhythmia of cerebro-basal ganglia-cerebellar networks underlies motor tics following striatal disinhibition.

PubMed

McCairn, Kevin W; Iriki, Atsushi; Isoda, Masaki

2013-01-09

Motor tics, a cardinal symptom of Tourette syndrome (TS), are hypothesized to arise from abnormalities within cerebro-basal ganglia circuits. Yet noninvasive neuroimaging of TS has previously identified robust activation in the cerebellum. To date, electrophysiological properties of cerebellar activation and its role in basal ganglia-mediated tic expression remain unknown. We performed multisite, multielectrode recordings of single-unit activity and local field potentials from the cerebellum, basal ganglia, and primary motor cortex using a pharmacologic monkey model of motor tics/TS. Following microinjections of bicuculline into the sensorimotor putamen, periodic tics occurred predominantly in the orofacial region, and a sizable number of cerebellar neurons showed phasic changes in activity associated with tic episodes. Specifically, 64% of the recorded cerebellar cortex neurons exhibited increases in activity, and 85% of the dentate nucleus neurons displayed excitatory, inhibitory, or multiphasic responses. Critically, abnormal discharges of cerebellar cortex neurons and excitatory-type dentate neurons mostly preceded behavioral tic onset, indicating their central origins. Latencies of pathological activity in the cerebellum and primary motor cortex substantially overlapped, suggesting that aberrant signals may be traveling along divergent pathways to these structures from the basal ganglia. Furthermore, the occurrence of tic movement was most closely associated with local field potential spikes in the cerebellum and primary motor cortex, implying that these structures may function as a gate to release overt tic movements. These findings indicate that tic-generating networks in basal ganglia mediated tic disorders extend beyond classical cerebro-basal ganglia circuits, leading to global network dysrhythmia including cerebellar circuits.

Frequency-band signatures of visual responses to naturalistic input in ferret primary visual cortex during free viewing.

PubMed

Sellers, Kristin K; Bennett, Davis V; Fröhlich, Flavio

2015-02-19

Neuronal firing responses in visual cortex reflect the statistics of visual input and emerge from the interaction with endogenous network dynamics. Artificial visual stimuli presented to animals in which the network dynamics were constrained by anesthetic agents or trained behavioral tasks have provided fundamental understanding of how individual neurons in primary visual cortex respond to input. In contrast, very little is known about the mesoscale network dynamics and their relationship to microscopic spiking activity in the awake animal during free viewing of naturalistic visual input. To address this gap in knowledge, we recorded local field potential (LFP) and multiunit activity (MUA) simultaneously in all layers of primary visual cortex (V1) of awake, freely viewing ferrets presented with naturalistic visual input (nature movie clips). We found that naturalistic visual stimuli modulated the entire oscillation spectrum; low frequency oscillations were mostly suppressed whereas higher frequency oscillations were enhanced. In average across all cortical layers, stimulus-induced change in delta and alpha power negatively correlated with the MUA responses, whereas sensory-evoked increases in gamma power positively correlated with MUA responses. The time-course of the band-limited power in these frequency bands provided evidence for a model in which naturalistic visual input switched V1 between two distinct, endogenously present activity states defined by the power of low (delta, alpha) and high (gamma) frequency oscillatory activity. Therefore, the two mesoscale activity states delineated in this study may define the degree of engagement of the circuit with the processing of sensory input. Copyright © 2014 Elsevier B.V. All rights reserved.

78 FR 8686 - Establishment of the National Freight Network

Federal Register 2010, 2011, 2012, 2013, 2014

2013-02-06

... Network AGENCY: Federal Highway Administration (FHWA), DOT. ACTION: Notice. SUMMARY: This notice defines the planned process for the designation of the national freight network as required by Section 1115 of... the initial designation of the primary freight network, the designation of additional miles critical...

76 FR 72878 - Financial Crimes Enforcement Network; Amendment to the Bank Secrecy Act Regulations-Imposition of...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-28

... Iran as a Jurisdiction of Primary Money Laundering Concern AGENCY: Financial Crimes Enforcement Network... Republic of Iran (``Iran'') is a jurisdiction of primary money laundering concern pursuant to 31 U.S.C... Act amends the anti- money laundering provisions of the Bank Secrecy Act (``BSA''), codified at 12 U.S...

Cytoskeletal Network Morphology Regulates Intracellular Transport Dynamics.

PubMed

Ando, David; Korabel, Nickolay; Huang, Kerwyn Casey; Gopinathan, Ajay

2015-10-20

Intracellular transport is essential for maintaining proper cellular function in most eukaryotic cells, with perturbations in active transport resulting in several types of disease. Efficient delivery of critical cargos to specific locations is accomplished through a combination of passive diffusion and active transport by molecular motors that ballistically move along a network of cytoskeletal filaments. Although motor-based transport is known to be necessary to overcome cytoplasmic crowding and the limited range of diffusion within reasonable timescales, the topological features of the cytoskeletal network that regulate transport efficiency and robustness have not been established. Using a continuum diffusion model, we observed that the time required for cellular transport was minimized when the network was localized near the nucleus. In simulations that explicitly incorporated network spatial architectures, total filament mass was the primary driver of network transit times. However, filament traps that redirect cargo back to the nucleus caused large variations in network transport. Filament polarity was more important than filament orientation in reducing average transit times, and transport properties were optimized in networks with intermediate motor on and off rates. Our results provide important insights into the functional constraints on intracellular transport under which cells have evolved cytoskeletal structures, and have potential applications for enhancing reactions in biomimetic systems through rational transport network design. Copyright © 2015 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Dynamic recruitment of resting state sub-networks

PubMed Central

O'Neill, George C.; Bauer, Markus; Woolrich, Mark W.; Morris, Peter G.; Barnes, Gareth R.; Brookes, Matthew J.

2015-01-01

Resting state networks (RSNs) are of fundamental importance in human systems neuroscience with evidence suggesting that they are integral to healthy brain function and perturbed in pathology. Despite rapid progress in this area, the temporal dynamics governing the functional connectivities that underlie RSN structure remain poorly understood. Here, we present a framework to help further our understanding of RSN dynamics. We describe a methodology which exploits the direct nature and high temporal resolution of magnetoencephalography (MEG). This technique, which builds on previous work, extends from solving fundamental confounds in MEG (source leakage) to multivariate modelling of transient connectivity. The resulting processing pipeline facilitates direct (electrophysiological) measurement of dynamic functional networks. Our results show that, when functional connectivity is assessed in small time windows, the canonical sensorimotor network can be decomposed into a number of transiently synchronising sub-networks, recruitment of which depends on current mental state. These rapidly changing sub-networks are spatially focal with, for example, bilateral primary sensory and motor areas resolved into two separate sub-networks. The likely interpretation is that the larger canonical sensorimotor network most often seen in neuroimaging studies reflects only a temporal aggregate of these transient sub-networks. Our approach opens new frontiers to study RSN dynamics, showing that MEG is capable of revealing the spatial, temporal and spectral signature of the human connectome in health and disease. PMID:25899137

Building managed primary care practice networks to deliver better clinical care: a qualitative semi-structured interview study.

PubMed

Pawa, Jasmine; Robson, John; Hull, Sally

2017-11-01

Primary care practices are increasingly working in larger groups. In 2009, all 36 primary care practices in the London borough of Tower Hamlets were grouped geographically into eight managed practice networks to improve the quality of care they delivered. Quantitative evaluation has shown improved clinical outcomes. To provide insight into the process of network implementation, including the aims, facilitating factors, and barriers, from both the clinical and managerial perspectives. A qualitative study of network implementation in the London borough of Tower Hamlets, which serves a socially disadvantaged and ethnically diverse population. Nineteen semi-structured interviews were carried out with doctors, nurses, and managers, and were informed by existing literature on integrated care and GP networks. Interviews were recorded and transcribed, and thematic analysis used to analyse emerging themes. Interviewees agreed that networks improved clinical care and reduced variation in practice performance. Network implementation was facilitated by the balance struck between 'a given structure' and network autonomy to adopt local solutions. Improved use of data, including patient recall and peer performance indicators, were viewed as critical key factors. Targeted investment provided the necessary resources to achieve this. Barriers to implementing networks included differences in practice culture, a reluctance to share data, and increased workload. Commissioners and providers were positive about the implementation of GP networks as a way to improve the quality of clinical care in Tower Hamlets. The issues that arose may be of relevance to other areas implementing similar quality improvement programmes at scale. © British Journal of General Practice 2017.

Primary prevention of cardiovascular diseases: a cost study in family practices.

PubMed

de Bekker-Grob, Esther W; van Dulmen, Sandra; van den Berg, Matthijs; Verheij, Robert A; Slobbe, Laurentius C J

2011-07-06

Considering the scarcity of health care resources and the high costs associated with cardiovascular diseases, we investigated the spending on cardiovascular primary preventive activities and the prescribing behaviour of primary preventive cardiovascular medication (PPCM) in Dutch family practices (FPs). A mixed methods design was used, which consisted of a questionnaire (n = 80 FPs), video recordings of hypertension- or cholesterol-related general practitioner visits (n = 56), and the database of Netherlands Information Network of General Practice (n = 45 FPs; n = 157,137 patients). The questionnaire and video recordings were used to determine the average frequency and time spent on cardiovascular primary preventive activities per FP respectively. Taking into account the annual income and full time equivalents of general practitioners, health care assistants, and practice nurses as well as the practice costs, the total spending on cardiovascular primary preventive activities in Dutch FPs was calculated. The database of Netherlands Information Network of General Practice was used to determine the prescribing behaviour in Dutch FPs by conducting multilevel regression models and adjusting for patient and practice characteristics. Total expenditure on cardiovascular primary preventive activities in FPs in 2009 was €38.8 million (€2.35 per capita), of which 47% was spent on blood pressure measurements, 26% on cardiovascular risk profiling, and 11% on lifestyle counselling. Fifteen percent (€11 per capita) of all cardiovascular medication prescribed in FPs was a PPCM. FPs differed greatly on prescription of PPCM (odds ratio of 3.1). Total costs of cardiovascular primary preventive activities in FPs such as blood pressure measurements and lifestyle counselling are relatively low compared to the costs of PPCM. There is considerable heterogeneity in prescribing behaviour of PPCM between FPs. Further research is needed to determine whether such large differences in prescription rates are justified. Striving for an optimal use of cardiovascular primary preventive activities might lead to similar health outcomes, but may achieve important cost savings.

Environmental Noise, Genetic Diversity and the Evolution of Evolvability and Robustness in Model Gene Networks

PubMed Central

Steiner, Christopher F.

2012-01-01

The ability of organisms to adapt and persist in the face of environmental change is accepted as a fundamental feature of natural systems. More contentious is whether the capacity of organisms to adapt (or “evolvability”) can itself evolve and the mechanisms underlying such responses. Using model gene networks, I provide evidence that evolvability emerges more readily when populations experience positively autocorrelated environmental noise (red noise) compared to populations in stable or randomly varying (white noise) environments. Evolvability was correlated with increasing genetic robustness to effects on network viability and decreasing robustness to effects on phenotypic expression; populations whose networks displayed greater viability robustness and lower phenotypic robustness produced more additive genetic variation and adapted more rapidly in novel environments. Patterns of selection for robustness varied antagonistically with epistatic effects of mutations on viability and phenotypic expression, suggesting that trade-offs between these properties may constrain their evolutionary responses. Evolution of evolvability and robustness was stronger in sexual populations compared to asexual populations indicating that enhanced genetic variation under fluctuating selection combined with recombination load is a primary driver of the emergence of evolvability. These results provide insight into the mechanisms potentially underlying rapid adaptation as well as the environmental conditions that drive the evolution of genetic interactions. PMID:23284934

Molluscan cells in culture: primary cell cultures and cell lines

PubMed Central

Yoshino, T. P.; Bickham, U.; Bayne, C. J.

2013-01-01

In vitro cell culture systems from molluscs have significantly contributed to our basic understanding of complex physiological processes occurring within or between tissue-specific cells, yielding information unattainable using intact animal models. In vitro cultures of neuronal cells from gastropods show how simplified cell models can inform our understanding of complex networks in intact organisms. Primary cell cultures from marine and freshwater bivalve and gastropod species are used as biomonitors for environmental contaminants, as models for gene transfer technologies, and for studies of innate immunity and neoplastic disease. Despite efforts to isolate proliferative cell lines from molluscs, the snail Biomphalaria glabrata Say, 1818 embryonic (Bge) cell line is the only existing cell line originating from any molluscan species. Taking an organ systems approach, this review summarizes efforts to establish molluscan cell cultures and describes the varied applications of primary cell cultures in research. Because of the unique status of the Bge cell line, an account is presented of the establishment of this cell line, and of how these cells have contributed to our understanding of snail host-parasite interactions. Finally, we detail the difficulties commonly encountered in efforts to establish cell lines from molluscs and discuss how these difficulties might be overcome. PMID:24198436

Paediatric obesity research in early childhood and the primary care setting: the TARGet Kids! research network.

PubMed

Morinis, Julia; Maguire, Jonathon; Khovratovich, Marina; McCrindle, Brian W; Parkin, Patricia C; Birken, Catherine S

2012-04-01

Primary paediatric health care is the foundation for preventative child health. In light of the recent obesity epidemic, paediatricians find themselves at the frontline of identification and management of childhood obesity. However, it is well recognized that evidence based approaches to obesity prevention and subsequent translation of this evidence into practice are critically needed. This paper explores the role of primary care in obesity prevention and introduces a novel application and development of a primary care research network in Canada--TARGet Kids!--to develop and translate an evidence-base on effective screening and prevention of childhood obesity.

Paediatric Obesity Research in Early Childhood and the Primary Care Setting: The TARGet Kids! Research Network

PubMed Central

Morinis, Julia; Maguire, Jonathon; Khovratovich, Marina; McCrindle, Brian W.; Parkin, Patricia C.; Birken, Catherine S.

2012-01-01

Primary paediatric health care is the foundation for preventative child health. In light of the recent obesity epidemic, paediatricians find themselves at the frontline of identification and management of childhood obesity. However, it is well recognized that evidence based approaches to obesity prevention and subsequent translation of this evidence into practice are critically needed. This paper explores the role of primary care in obesity prevention and introduces a novel application and development of a primary care research network in Canada—TARGet Kids!—to develop and translate an evidence-base on effective screening and prevention of childhood obesity. PMID:22690197

Association between Organ Procurement Organization Social Network Centrality and Kidney Discard and Transplant Outcomes1

PubMed Central

Butala, Neel M.; King, Marissa D.; Reitsma, William; Formica, Richard N.; Abt, Peter L.; Reese, Peter P.; Parikh, Chirag R.

2015-01-01

Background Given growth in kidney transplant waitlists and discard rates, donor kidney acceptance is an important problem. We used network analysis to examine whether organ procurement organization (OPO) network centrality affects discard and outcomes. Methods We identified 106,160 deceased-donor kidneys recovered for transplant from 2000–2010 in SRTR. We constructed the transplant network by year with each OPO representing a node and each kidney-sharing relationship between OPOs representing a directed tie between nodes. Primary exposures were the number of different OPOs to which an OPO has given a kidney or from which an OPO has received a kidney in year preceding procurement year. Primary outcomes were discard, cold-ischemia time, delayed graft function, and 1-year graft loss. We used multivariable regression, restricting analysis to the 50% of OPOs with highest discard and stratifying remaining OPOs by kidney volume. Models controlled for kidney donor risk index, waitlist time, and kidney pumping. Results An increase in one additional OPO to which a kidney was given by a procuring OPO in a year was associated with 1.4% lower likelihood of discard for a given kidney (odds ratio, 0.986; 95% confidence interval, 0.974-0.998) among OPOs procuring high kidney volume, but 2% higher likelihood of discard (OR:1.021, CI:1.006, 1.037) among OPOs procuring low kidney volume, with mixed associations with recipient outcomes. Conclusions Our study highlights the value of network analysis in revealing how broader kidney sharing is associated with levels of organ acceptance. We conclude interventions to promote broader inter-OPO sharing could be developed to reduce discard for a subset of OPOs. PMID:26102610

Pyrolysis processing for solid waste resource recovery

NASA Technical Reports Server (NTRS)

Wojtowicz, Marek A. (Inventor); Serio, Michael A. (Inventor); Kroo, Erik (Inventor); Suuberg, Eric M. (Inventor)

2007-01-01

Solid waste resource recovery in space is effected by pyrolysis processing, to produce light gases as the main products (CH.sub.4, H.sub.2, CO.sub.2, CO, H.sub.2O, NH.sub.3) and a reactive carbon-rich char as the main byproduct. Significant amounts of liquid products are formed under less severe pyrolysis conditions, and are cracked almost completely to gases as the temperature is raised. A primary pyrolysis model for the composite mixture is based on an existing model for whole biomass materials, and an artificial neural network models the changes in gas composition with the severity of pyrolysis conditions.

An Evaluation and Demonstration of a Network Based Aircraft Telemetry System

NASA Technical Reports Server (NTRS)

Waldersen, Matt; Schnarr, Otto, III

2017-01-01

The primary topics of this presentation describe the testing of network based telemetry and RF modulation techniques. The overall intend is to aid the aerospace industry in transitioning to a network based telemetry system.

Unimodal primary sensory cortices are directly connected by long-range horizontal projections in the rat sensory cortex.

PubMed

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

2014-01-01

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

Unimodal primary sensory cortices are directly connected by long-range horizontal projections in the rat sensory cortex

PubMed Central

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

2014-01-01

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

The Mars Telecommunications Orbiter a key asset in the Mars Network

NASA Technical Reports Server (NTRS)

Abilleira, Fernando

2006-01-01

The Mars Telecommunications Orbiter (MTO) to be launched in 2009 will play a key role in the Mars Network since it will be the first interplanetary mission whose primary objective is to provide communications to existing and upcoming Mars missions, This paper presents a basic description of the primary mission an provides trajectory information for the Mars Telecommunication Orbiter.

Bringing Wellness to Schools: Opportunities for and Challenges to Mental Health Integration in School-Based Health Centers.

PubMed

Lai, Karen; Guo, Sisi; Ijadi-Maghsoodi, Roya; Puffer, Maryjane; Kataoka, Sheryl H

2016-12-01

School-based health centers (SBHCs) reduce access barriers to mental health care and improve educational outcomes for youths. This qualitative study evaluated the innovations and challenges of a unique network of SBHCs in a large, urban school district as the centers attempted to integrate health, mental health, and educational services. The 43 participants sampled included mental health providers, primary care providers, and care coordinators at 14 SBHCs. Semistructured interviews with each participant were audio recorded and transcribed. Themes were identified and coded by using Atlas.ti 5.1 and collapsed into three domains: operations, partnership, and engagement. Interviews revealed provider models ranging from single agencies offering both primary care and mental health services to colocated services. Sites where the health agency provided at least some mental health services reported more mental health screenings. Many sites used SBHC wellness coordinators and coordination team meetings to facilitate relationships between schools and health agency and community mental health clinic providers. Partnership challenges included confidentiality policies and staff turnover. Participants also highlighted student and parent engagement through culturally sensitive services, peer health advocates, and "drop-in" lunches. Staffing and operational models are critical in the success of integrating primary care, mental health care, and education. Among the provider models observed, the combined primary care and mental health provider model offered the most integrated services. Despite barriers, providers and schools have begun to implement novel solutions to operational problems and family engagement in mental health services.

Linking Structural Equation Modelling with Bayesian Network and Coastal Phytoplankton Dynamics in Bohai Bay

NASA Astrophysics Data System (ADS)

Chu, Jiangtao; Yang, Yue

2018-06-01

Bayesian networks (BN) have many advantages over other methods in ecological modelling and have become an increasingly popular modelling tool. However, BN are flawed in regard to building models based on inadequate existing knowledge. To overcome this limitation, we propose a new method that links BN with structural equation modelling (SEM). In this method, SEM is used to improve the model structure for BN. This method was used to simulate coastal phytoplankton dynamics in Bohai Bay. We demonstrate that this hybrid approach minimizes the need for expert elicitation, generates more reasonable structures for BN models and increases the BN model's accuracy and reliability. These results suggest that the inclusion of SEM for testing and verifying the theoretical structure during the initial construction stage improves the effectiveness of BN models, especially for complex eco-environment systems. The results also demonstrate that in Bohai Bay, while phytoplankton biomass has the greatest influence on phytoplankton dynamics, the impact of nutrients on phytoplankton dynamics is larger than the influence of the physical environment in summer. Furthermore, despite the Redfield ratio indicating that phosphorus should be the primary nutrient limiting factor, our results indicate that silicate plays the most important role in regulating phytoplankton dynamics in Bohai Bay.

Flux balance analysis of primary metabolism in Chlamydomonas reinhardtii.

PubMed

Boyle, Nanette R; Morgan, John A

2009-01-07

Photosynthetic organisms convert atmospheric carbon dioxide into numerous metabolites along the pathways to make new biomass. Aquatic photosynthetic organisms, which fix almost half of global inorganic carbon, have great potential: as a carbon dioxide fixation method, for the economical production of chemicals, or as a source for lipids and starch which can then be converted to biofuels. To harness this potential through metabolic engineering and to maximize production, a more thorough understanding of photosynthetic metabolism must first be achieved. A model algal species, C. reinhardtii, was chosen and the metabolic network reconstructed. Intracellular fluxes were then calculated using flux balance analysis (FBA). The metabolic network of primary metabolism for a green alga, C. reinhardtii, was reconstructed using genomic and biochemical information. The reconstructed network accounts for the intracellular localization of enzymes to three compartments and includes 484 metabolic reactions and 458 intracellular metabolites. Based on BLAST searches, one newly annotated enzyme (fructose-1,6-bisphosphatase) was added to the Chlamydomonas reinhardtii database. FBA was used to predict metabolic fluxes under three growth conditions, autotrophic, heterotrophic and mixotrophic growth. Biomass yields ranged from 28.9 g per mole C for autotrophic growth to 15 g per mole C for heterotrophic growth. The flux balance analysis model of central and intermediary metabolism in C. reinhardtii is the first such model for algae and the first model to include three metabolically active compartments. In addition to providing estimates of intracellular fluxes, metabolic reconstruction and modelling efforts also provide a comprehensive method for annotation of genome databases. As a result of our reconstruction, one new enzyme was annotated in the database and several others were found to be missing; implying new pathways or non-conserved enzymes. The use of FBA to estimate intracellular fluxes also provides flux values that can be used as a starting point for rational engineering of C. reinhardtii. From these initial estimates, it is clear that aerobic heterotrophic growth on acetate has a low yield on carbon, while mixotrophically and autotrophically grown cells are significantly more carbon efficient.

Feedback modulation of neural network synchrony and seizure susceptibility by Mdm2-p53-Nedd4-2 signaling.

PubMed

Jewett, Kathryn A; Christian, Catherine A; Bacos, Jonathan T; Lee, Kwan Young; Zhu, Jiuhe; Tsai, Nien-Pei

2016-03-22

Neural network synchrony is a critical factor in regulating information transmission through the nervous system. Improperly regulated neural network synchrony is implicated in pathophysiological conditions such as epilepsy. Despite the awareness of its importance, the molecular signaling underlying the regulation of neural network synchrony, especially after stimulation, remains largely unknown. In this study, we show that elevation of neuronal activity by the GABA(A) receptor antagonist, Picrotoxin, increases neural network synchrony in primary mouse cortical neuron cultures. The elevation of neuronal activity triggers Mdm2-dependent degradation of the tumor suppressor p53. We show here that blocking the degradation of p53 further enhances Picrotoxin-induced neural network synchrony, while promoting the inhibition of p53 with a p53 inhibitor reduces Picrotoxin-induced neural network synchrony. These data suggest that Mdm2-p53 signaling mediates a feedback mechanism to fine-tune neural network synchrony after activity stimulation. Furthermore, genetically reducing the expression of a direct target gene of p53, Nedd4-2, elevates neural network synchrony basally and occludes the effect of Picrotoxin. Finally, using a kainic acid-induced seizure model in mice, we show that alterations of Mdm2-p53-Nedd4-2 signaling affect seizure susceptibility. Together, our findings elucidate a critical role of Mdm2-p53-Nedd4-2 signaling underlying the regulation of neural network synchrony and seizure susceptibility and reveal potential therapeutic targets for hyperexcitability-associated neurological disorders.

African Scientific Network: A model to enhance scientific research in developing countries

NASA Astrophysics Data System (ADS)

Kebede, Abebe

2002-03-01

Africa has over 350 higher education institutions with a variety of experiences and priorities. The primary objectives of these institutions are to produce white-collar workers, teachers, and the work force for mining, textiles, and agricultural industries. The state of higher education and scientific research in Africa have been discussed in several conferences. The proposals that are generated by these conferences advocate structural changes in higher education, North-South institutional linkages, mobilization of the African Diaspora and funding. We propose a model African Scientific Network that would facilitate and enhance international scientific partnerships between African scientists and their counterparts elsewhere. A recent article by James Lamout (Financial Times, August 2, 2001) indicates that emigration from South Africa alone costs $8.9 billion in lost human resources. The article also stated that every year 23,000 graduates leave Africa for opportunities overseas, mainly in Europe, leaving only 20,000 scientists and engineers serving over 600 million people. The International Organization for Migration states that the brain drain of highly skilled professionals from Africa is making economic growth and poverty alleviation impossible across the continent. In our model we will focus on a possible networking mechanism where the African Diaspora will play a major role in addressing the financial and human resources needs of higher education in Africa

Absolute earthquake locations using 3-D versus 1-D velocity models below a local seismic network: example from the Pyrenees

NASA Astrophysics Data System (ADS)

Theunissen, T.; Chevrot, S.; Sylvander, M.; Monteiller, V.; Calvet, M.; Villaseñor, A.; Benahmed, S.; Pauchet, H.; Grimaud, F.

2018-03-01

Local seismic networks are usually designed so that earthquakes are located inside them (primary azimuthal gap <<180°) and close to the seismic stations (0-100 km). With these local or near-regional networks (0°-5°), many seismological observatories still routinely locate earthquakes using 1-D velocity models. Moving towards 3-D location algorithms requires robust 3-D velocity models. This work takes advantage of seismic monitoring spanning more than 30 yr in the Pyrenean region. We investigate the influence of a well-designed 3-D model with station corrections including basins structure and the geometry of the Mohorovicic discontinuity on earthquake locations. In the most favourable cases (GAP < 180° and distance to the first station lower than 15 km), results using 1-D velocity models are very similar to 3-D results. The horizontal accuracy in the 1-D case can be higher than in the 3-D case if lateral variations in the structure are not properly resolved. Depth is systematically better resolved in the 3-D model even on the boundaries of the seismic network (GAP > 180° and distance to the first station higher than 15 km). Errors on velocity models and accuracy of absolute earthquake locations are assessed based on a reference data set made of active seismic, quarry blasts and passive temporary experiments. Solutions and uncertainties are estimated using the probabilistic approach of the NonLinLoc (NLLoc) software based on Equal Differential Time. Some updates have been added to NLLoc to better focus on the final solution (outlier exclusion, multiscale grid search, S-phases weighting). Errors in the probabilistic approach are defined to take into account errors on velocity models and on arrival times. The seismicity in the final 3-D catalogue is located with a horizontal uncertainty of about 2.0 ± 1.9 km and a vertical uncertainty of about 3.0 ± 2.0 km.

Health Care in Brazil: Implications for Public Health and Epidemiology.

PubMed

Younger, David S

2016-11-01

A network of family-based community-oriented primary health programs, or Programa Agentes Communita˙rios de Saúde, and family health programs, or Programa Saúde da Família, introduced almost 2 decades ago were the Brazilian government's health care models to restructure primary care under the Unified Health System, or Sistema Único de Saúde. The latter offers comprehensive coverage to all, although it is used by those of lower income, and despite achievement in the last quarter century, access to health services and gradients of health status continue to persist along income, educational background, racial, and religious lines. Copyright © 2016 Elsevier Inc. All rights reserved.

Cargo launch vehicles to low earth orbit

NASA Technical Reports Server (NTRS)

Austin, Robert E.

1990-01-01

There are two primary space transportation capabilities required to support both base programs and expanded mission requirements: earth-to-orbit (ETO) transportation systems and space transfer vehicle systems. Existing and new ETO vehicles required to support mission requirements, and planned robotic missions, along with currently planned ETO vehicles are provided. Lunar outposts, Mars' outposts, base and expanded model, ETO vehicles, advanced avionics technologies, expert systems, network architecture and operations systems, and technology transfer are discussed.

Investigation on application of genetic algorithms to optimal reactive power dispatch of power systems

NASA Astrophysics Data System (ADS)

Wu, Q. H.; Ma, J. T.

1993-09-01

A primary investigation into application of genetic algorithms in optimal reactive power dispatch and voltage control is presented. The application was achieved, based on (the United Kingdom) National Grid 48 bus network model, using a novel genetic search approach. Simulation results, compared with that obtained using nonlinear programming methods, are included to show the potential of applications of the genetic search methodology in power system economical and secure operations.

A modelling framework to evaluate human-induced alterations of network sediment connectivity and quantify their unplanned adverse impact

NASA Astrophysics Data System (ADS)

Bizzi, S.; Schmitt, R. J. P.; Giuliani, M.; Castelletti, A.

2016-12-01

World-wide human-induced alterations of sediment transport, e.g. due to dams, sand and gravel mining along rivers and channel maintenance, translated into geomorphic changes, which have had major effects on ecosystem integrity, human livelihoods, ultimately negatively impacting also on the expected benefit from building water infrastructures. Despite considerable recent advances in modelling basin-scale hydrological and geomorphological processes, our ability to quantitatively simulate network sediment transport, foresee effects of alternative scenarios of human development on fluvial morpho-dynamics, and design anticipatory planning adaptation measures is still limited. In this work, we demonstrate the potential of a novel modelling framework called CASCADE (CAtchment SEdiment Connectivity And Delivery (Schmitt et al., 2016)) to characterize sediment connectivity at the whole river network scale, predict the disturbing effect of dams on the sediment transport, and quantify the associated loss with respect to the level of benefits that provided the economic justification for their development. CASCADE allows tracking the fate of a sediment from its source to its multiple sinks across the network. We present the results from two major, transboundary river systems (3S and Red River) in South-East Asia. We first discuss the ability of CASCADE to properly represent sediment connectivity at the network scale using available remote sensing data and information from monitoring networks. Secondly, we assess the impacts on sediment connectivity induced by existing and planned dams in the 3S and Red River basins and compare these alterations with revenues in terms of hydropower production. CASCADE outputs support a broader understanding of sediment connectivity tailored for water management issues not yet available, and it is suitable to enrich assessments of food-energy-water nexus. The model framework can be embedded into the design of optimal siting and sizing of water infrastructures at the river basin scale. This enlarges the scope of the analysis to account for human-induced alterations of network sediment connectivity, and to explore the trade-off with respect to primary operational objectives, such as hydropower production, water supply, and flood control.

Fiscal Year 2018 National Environmental Information Exchange Network Grant Solicitation Notice

EPA Pesticide Factsheets

The Exchange Network Grant Program provides funding for projects that are in line with Exchange Network priorities. The primary outcome expected from EN assistance agreements is improved access to, and exchange of, high quality environmental data.

The social network index and its relation to later-life depression among the elderly aged ≥80 years in Northern Thailand.

PubMed

Aung, Myo Nyein; Moolphate, Saiyud; Aung, Thin Nyein Nyein; Katonyoo, Chitima; Khamchai, Songyos; Wannakrairot, Pongsak

2016-01-01

Having a diverse social network is considered to be beneficial to a person's well-being. The significance, however, of social network diversity in the geriatric assessment of people aged ≥80 years has not been adequately investigated within the Southeast Asian context. This study explored the social networks belonging to the elderly aged ≥80 years and assessed the relation of social network and geriatric depression. This study was a community-based cross-sectional survey conducted in Chiang Mai Province, Northern Thailand. A representative sample of 435 community residents, aged ≥80 years, were included in a multistage sample. The participants' social network diversity was assessed by applying Cohen's social network index (SNI). The geriatric depression scale and activities of daily living measures were carried out during home visits. Descriptive analyses revealed the distribution of SNI, while the relationship between the SNI and the geriatric depression scale was examined by ordinal logistic regression models controlling possible covariants such as age, sex, and educational attainment. The median age of the sample was 83 years, with females comprising of 54.94% of the sample. The participants' children, their neighbors, and members of Buddhist temples were reported as the most frequent contacts of the study participants. Among the 435 participants, 25% were at risk of social isolation due to having a "limited" social network group (SNI 0-3), whereas 37% had a "medium" social network (SNI 4-5), and 38% had a "diverse" social network (SNI ≥6). The SNI was not different among the two sexes. Activities of daily living scores in the diverse social network group were significantly higher than those in the limited social network group. Multivariate ordinal logistic regression analysis models revealed a significant negative association between social network diversity and geriatric depression. Regular and frequent contact with various social contacts may safeguard common geriatric depression among persons aged ≥80 years. As a result, screening those at risk of social isolation is recommended to be integrated into routine primary health care-based geriatric assessment and intervention programs.

A social marketing approach to implementing evidence-based practice in VHA QUERI: the TIDES depression collaborative care model

PubMed Central

2009-01-01

Abstract Collaborative care models for depression in primary care are effective and cost-effective, but difficult to spread to new sites. Translating Initiatives for Depression into Effective Solutions (TIDES) is an initiative to promote evidence-based collaborative care in the U.S. Veterans Health Administration (VHA). Social marketing applies marketing techniques to promote positive behavior change. Described in this paper, TIDES used a social marketing approach to foster national spread of collaborative care models. TIDES social marketing approach The approach relied on a sequential model of behavior change and explicit attention to audience segmentation. Segments included VHA national leadership, Veterans Integrated Service Network (VISN) regional leadership, facility managers, frontline providers, and veterans. TIDES communications, materials and messages targeted each segment, guided by an overall marketing plan. Results Depression collaborative care based on the TIDES model was adopted by VHA as part of the new Primary Care Mental Health Initiative and associated policies. It is currently in use in more than 50 primary care practices across the United States, and continues to spread, suggesting success for its social marketing-based dissemination strategy. Discussion and conclusion Development, execution and evaluation of the TIDES marketing effort shows that social marketing is a promising approach for promoting implementation of evidence-based interventions in integrated healthcare systems. PMID:19785754

Healthy brain connectivity predicts atrophy progression in non-fluent variant of primary progressive aphasia.

PubMed

Mandelli, Maria Luisa; Vilaplana, Eduard; Brown, Jesse A; Hubbard, H Isabel; Binney, Richard J; Attygalle, Suneth; Santos-Santos, Miguel A; Miller, Zachary A; Pakvasa, Mikhail; Henry, Maya L; Rosen, Howard J; Henry, Roland G; Rabinovici, Gil D; Miller, Bruce L; Seeley, William W; Gorno-Tempini, Maria Luisa

2016-10-01

Neurodegeneration has been hypothesized to follow predetermined large-scale networks through the trans-synaptic spread of toxic proteins from a syndrome-specific epicentre. To date, no longitudinal neuroimaging study has tested this hypothesis in vivo in frontotemporal dementia spectrum disorders. The aim of this study was to demonstrate that longitudinal progression of atrophy in non-fluent/agrammatic variant primary progressive aphasia spreads over time from a syndrome-specific epicentre to additional regions, based on their connectivity to the epicentre in healthy control subjects. The syndrome-specific epicentre of the non-fluent/agrammatic variant of primary progressive aphasia was derived in a group of 10 mildly affected patients (clinical dementia rating equal to 0) using voxel-based morphometry. From this region, the inferior frontal gyrus (pars opercularis), we derived functional and structural connectivity maps in healthy controls (n = 30) using functional magnetic resonance imaging at rest and diffusion-weighted imaging tractography. Graph theory analysis was applied to derive functional network features. Atrophy progression was calculated using voxel-based morphometry longitudinal analysis on 34 non-fluent/agrammatic patients. Correlation analyses were performed to compare volume changes in patients with connectivity measures of the healthy functional and structural speech/language network. The default mode network was used as a control network. From the epicentre, the healthy functional connectivity network included the left supplementary motor area and the prefrontal, inferior parietal and temporal regions, which were connected through the aslant, superior longitudinal and arcuate fasciculi. Longitudinal grey and white matter changes were found in the left language-related regions and in the right inferior frontal gyrus. Functional connectivity strength in the healthy speech/language network, but not in the default network, correlated with longitudinal grey matter changes in the non-fluent/agrammatic variant of primary progressive aphasia. Graph theoretical analysis of the speech/language network showed that regions with shorter functional paths to the epicentre exhibited greater longitudinal atrophy. The network contained three modules, including a left inferior frontal gyrus/supplementary motor area, which was most strongly connected with the epicentre. The aslant tract was the white matter pathway connecting these two regions and showed the most significant correlation between fractional anisotropy and white matter longitudinal atrophy changes. This study showed that the pattern of longitudinal atrophy progression in the non-fluent/agrammatic variant of primary progressive aphasia relates to the strength of connectivity in pre-determined functional and structural large-scale speech production networks. These findings support the hypothesis that the spread of neurodegeneration occurs by following specific anatomical and functional neuronal network architectures. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Limits to high-speed simulations of spiking neural networks using general-purpose computers.

PubMed

Zenke, Friedemann; Gerstner, Wulfram

2014-01-01

To understand how the central nervous system performs computations using recurrent neuronal circuitry, simulations have become an indispensable tool for theoretical neuroscience. To study neuronal circuits and their ability to self-organize, increasing attention has been directed toward synaptic plasticity. In particular spike-timing-dependent plasticity (STDP) creates specific demands for simulations of spiking neural networks. On the one hand a high temporal resolution is required to capture the millisecond timescale of typical STDP windows. On the other hand network simulations have to evolve over hours up to days, to capture the timescale of long-term plasticity. To do this efficiently, fast simulation speed is the crucial ingredient rather than large neuron numbers. Using different medium-sized network models consisting of several thousands of neurons and off-the-shelf hardware, we compare the simulation speed of the simulators: Brian, NEST and Neuron as well as our own simulator Auryn. Our results show that real-time simulations of different plastic network models are possible in parallel simulations in which numerical precision is not a primary concern. Even so, the speed-up margin of parallelism is limited and boosting simulation speeds beyond one tenth of real-time is difficult. By profiling simulation code we show that the run times of typical plastic network simulations encounter a hard boundary. This limit is partly due to latencies in the inter-process communications and thus cannot be overcome by increased parallelism. Overall, these results show that to study plasticity in medium-sized spiking neural networks, adequate simulation tools are readily available which run efficiently on small clusters. However, to run simulations substantially faster than real-time, special hardware is a prerequisite.

A network model framework for prioritizing wetland conservation in the Great Plains

USGS Publications Warehouse

Albanese, Gene; Haukos, David A.

2017-01-01

ContextPlaya wetlands are the primary habitat for numerous wetland-dependent species in the Southern Great Plains of North America. Plant and wildlife populations that inhabit these wetlands are reciprocally linked through the dispersal of individuals, propagules and ultimately genes among local populations.ObjectiveTo develop and implement a framework using network models for conceptualizing, representing and analyzing potential biological flows among 48,981 spatially discrete playa wetlands in the Southern Great Plains.MethodsWe examined changes in connectivity patterns and assessed the relative importance of wetlands to maintaining these patterns by targeting wetlands for removal based on network centrality metrics weighted by estimates of habitat quality and probability of inundation.ResultsWe identified several distinct, broad-scale sub networks and phase transitions among playa wetlands in the Southern Plains. In particular, for organisms that can disperse >2 km a dense and expansive wetland sub network emerges in the Southern High Plains. This network was characterized by localized, densely connected wetland clusters at link distances (h) >2 km but <5 km and was most sensitive to changes in wetland availability (p) and configuration when h = 4 km, and p = 0.2–0.4. It transitioned to a single, large connected wetland system at broader spatial scales even when the proportion of inundated wetland was relatively low (p = 0.2).ConclusionsOur findings suggest that redundancy in the potential for broad and fine-scale movements insulates this system from damage and facilitates system-wide connectivity among populations with different dispersal capacities.

The stimulus-evoked population response in visual cortex of awake monkey is a propagating wave

PubMed Central

Muller, Lyle; Reynaud, Alexandre; Chavane, Frédéric; Destexhe, Alain

2014-01-01

Propagating waves occur in many excitable media and were recently found in neural systems from retina to neocortex. While propagating waves are clearly present under anaesthesia, whether they also appear during awake and conscious states remains unclear. One possibility is that these waves are systematically missed in trial-averaged data, due to variability. Here we present a method for detecting propagating waves in noisy multichannel recordings. Applying this method to single-trial voltage-sensitive dye imaging data, we show that the stimulus-evoked population response in primary visual cortex of the awake monkey propagates as a travelling wave, with consistent dynamics across trials. A network model suggests that this reliability is the hallmark of the horizontal fibre network of superficial cortical layers. Propagating waves with similar properties occur independently in secondary visual cortex, but maintain precise phase relations with the waves in primary visual cortex. These results show that, in response to a visual stimulus, propagating waves are systematically evoked in several visual areas, generating a consistent spatiotemporal frame for further neuronal interactions. PMID:24770473

Structural and Maturational Covariance in Early Childhood Brain Development.

PubMed

Geng, Xiujuan; Li, Gang; Lu, Zhaohua; Gao, Wei; Wang, Li; Shen, Dinggang; Zhu, Hongtu; Gilmore, John H

2017-03-01

Brain structural covariance networks (SCNs) composed of regions with correlated variation are altered in neuropsychiatric disease and change with age. Little is known about the development of SCNs in early childhood, a period of rapid cortical growth. We investigated the development of structural and maturational covariance networks, including default, dorsal attention, primary visual and sensorimotor networks in a longitudinal population of 118 children after birth to 2 years old and compared them with intrinsic functional connectivity networks. We found that structural covariance of all networks exhibit strong correlations mostly limited to their seed regions. By Age 2, default and dorsal attention structural networks are much less distributed compared with their functional maps. The maturational covariance maps, however, revealed significant couplings in rates of change between distributed regions, which partially recapitulate their functional networks. The structural and maturational covariance of the primary visual and sensorimotor networks shows similar patterns to the corresponding functional networks. Results indicate that functional networks are in place prior to structural networks, that correlated structural patterns in adult may arise in part from coordinated cortical maturation, and that regional co-activation in functional networks may guide and refine the maturation of SCNs over childhood development. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Patients' experiences in different models of community health centers in southern China.

PubMed

Wang, Harry H X; Wong, Samuel Y S; Wong, Martin C S; Wei, Xiao Lin; Wang, Jia Ji; Li, Donald K T; Tang, Jin Ling; Gao, Gemma Y; Griffiths, Sian M

2013-01-01

Current health care reforms in China have an overall goal of strengthening primary care through the establishment and expansion of primary care networks based on community health centers (CHCs). Implementation in urban areas has led to the emergence of different models of ownership and management. The objective of this study was to evaluate the primary care experiences of patients in the Pearl River Delta as measured by the Primary Care Assessment Tool (PCAT) and the relationships with ownership and management in the 3 different models we describe. This cross-sectional study was conducted on-site at CHCs in 3 cities within the Pearl River Delta, China, using a multistage cluster sampling method. A validated Mandarin Chinese version of the PCAT-Adult Edition (short version) was adopted to collect information from adult patients regarding their experiences with primary care sources. PCAT scores for individual primary care attributes and total primary care assessment scores were assessed with respect to sociodemographic characteristics, health characteristics, and health care service utilization across 3 primary care models. One thousand four hundred forty (1,440) primary care patients responded to the survey, for an overall response rate of 86.1%. Respondents gave government-owned and -managed CHCs the highest overall PCAT scores when compared with CHCs either managed by hospitals (95.18 vs 90.81; P = .005) or owned by private and social entities (95.18 vs 90.69; P =.007) as a result of better first-contact care (better first-contact utilization) and coordination of care (better service coordination and information system). Factors that were positively and significantly associated with higher overall assessment scores included the presence of a chronic condition (P <.001), having medical insurance (P = .006), and a self-reported good health status (P <.001). This study suggests that government-owned and -managed CHCs may be able to provide better first-contact care in terms of utilization and coordination of care, and may be better at solving the problem of underutilization of the CHCs as the first-contact point of care, one key problem facing the reforms in China.

A new role for primary care teams in the United States after “Obamacare:” Track and improve health insurance coverage rates

PubMed Central

DeVoe, Jennifer; Angier, Heather; Hoopes, Megan; Gold, Rachel

2017-01-01

Maintaining continuous health insurance coverage is important. With recent expansions in access to coverage in the United States after “Obamacare,” primary care teams have a new role in helping to track and improve coverage rates and to provide outreach to patients. We describe efforts to longitudinally track health insurance rates using data from the electronic health record (EHR) of a primary care network and to use these data to support practice-based insurance outreach and assistance. Although we highlight a few examples from one network, we believe there is great potential for doing this type of work in a broad range of family medicine and community health clinics that provide continuity of care. By partnering with researchers through practice-based research networks and other similar collaboratives, primary care practices can greatly expand the use of EHR data and EHR-based tools targeting improvements in health insurance and quality health care. PMID:28966926

Developing a network-level structural capacity index for structural evaluation of pavements.

DOT National Transportation Integrated Search

2013-03-01

The objective of this project was to develop a structural index for use in network-level pavement evaluation to facilitate : the inclusion of the pavements structural condition in pavement management applications. The primary goal of network-level...

Will choice-based reform work for Medicare? Evidence from the Federal Employees Health Benefits Program.

PubMed

Florence, Curtis S; Atherly, Adam; Thorpe, Kenneth E

2006-10-01

. To examine the effect of premiums and benefits on the health plan choices of older enrollees who choose Federal Employees Health Benefits Program (FEHBP) health plans as their primary payer. Administrative enrollment data from the Office of Personnel Management (OPM) and plan premiums and benefits data taken from the Checkbook Guide to health plans. We estimate individual plan choice models where the choice of health plan is a function of out-of-pocket premium, actuarial value, plan attributes, and individual characteristics. Plan attributes include plan structure (fee-for-service/preferred provider organization, point-of-service, or health maintenance organization), drug benefit structure, and whether or not the plan covers other types of spending such as dental services and diabetic supplies. The models are estimated by conditional logit. Our study focuses on three populations that currently choose FEHBP as their primary health care coverage and are similar to the Medicare population: current employees and retirees who are approaching the age of Medicare eligibility (ages 60-64) and current federal employees age 65+. Current employees age 65+ are eligible for Medicare, but their FEHBP plan is their primary payer. Retirees and employees 60-64 are not yet eligible for Medicare but are similar in many respects to recently age-eligible Medicare beneficiaries. We also estimate our model for current employees age 55 and younger as a comparison group. We select a random sample of retirees and employees age 60-64, as well as all current employees age 65+, from the OPM administrative database for the calendar year 2001. The plan choices available to each person are determined by the plans participating in their metropolitan statistical area. We match plan premium and attribute information from the Checkbook Guide to each plan in the enrollee's list of choices. We find that current workers 65+, 60-64, and non-Medicare eligible retirees are sensitive to variation in plan premiums. The premium elasticities for these groups are similar in magnitude to those of the age 55 and under employee group. Older workers and retirees not yet eligible for Medicare are willing to pay a substantial amount for plans with open provider networks. The willingness to pay for open networks is significantly greater for these groups than for younger employees. Willingness to pay for open network plans varies significantly by income, but varies little by age within group. Our finding that older workers and non-Medicare eligible retirees are sensitive to plan premiums suggests that choice-based reform of Medicare would lead to cost-conscious choices by Medicare beneficiaries. However, our finding that these groups are willing to pay more for open network plans than younger employees suggest that higher risk individuals may migrate toward higher benefit, higher cost plans. Our findings on the relationship between income and willingness to pay for open network plans suggest that means testing is a viable reform for lowering Medicare program costs.

Altered Connectivity of the Balance Processing Network After Tongue Stimulation in Balance-Impaired Individuals

PubMed Central

Tyler, Mitchell E.; Danilov, Yuri P.; Kaczmarek, Kurt A.; Meyerand, Mary E.

2013-01-01

Abstract Some individuals with balance impairment have hypersensitivity of the motion-sensitive visual cortices (hMT+) compared to healthy controls. Previous work showed that electrical tongue stimulation can reduce the exaggerated postural sway induced by optic flow in this subject population and decrease the hypersensitive response of hMT+. Additionally, a region within the brainstem (BS), likely containing the vestibular and trigeminal nuclei, showed increased optic flow-induced activity after tongue stimulation. The aim of this study was to understand how the modulation induced by tongue stimulation affects the balance-processing network as a whole and how modulation of BS structures can influence cortical activity. Four volumes of interest, discovered in a general linear model analysis, constitute major contributors to the balance-processing network. These regions were entered into a dynamic causal modeling analysis to map the network and measure any connection or topology changes due to the stimulation. Balance-impaired individuals had downregulated response of the primary visual cortex (V1) to visual stimuli but upregulated modulation of the connection between V1 and hMT+ by visual motion compared to healthy controls (p≤1E–5). This upregulation was decreased to near-normal levels after stimulation. Additionally, the region within the BS showed increased response to visual motion after stimulation compared to both prestimulation and controls. Stimulation to the tongue enters the central nervous system at the BS but likely propagates to the cortex through supramodal information transfer. We present a model to explain these brain responses that utilizes an anatomically present, but functionally dormant pathway of information flow within the processing network. PMID:23216162

Optimizing a Drone Network to Deliver Automated External Defibrillators.

PubMed

Boutilier, Justin J; Brooks, Steven C; Janmohamed, Alyf; Byers, Adam; Buick, Jason E; Zhan, Cathy; Schoellig, Angela P; Cheskes, Sheldon; Morrison, Laurie J; Chan, Timothy C Y

2017-06-20

Public access defibrillation programs can improve survival after out-of-hospital cardiac arrest, but automated external defibrillators (AEDs) are rarely available for bystander use at the scene. Drones are an emerging technology that can deliver an AED to the scene of an out-of-hospital cardiac arrest for bystander use. We hypothesize that a drone network designed with the aid of a mathematical model combining both optimization and queuing can reduce the time to AED arrival. We applied our model to 53 702 out-of-hospital cardiac arrests that occurred in the 8 regions of the Toronto Regional RescuNET between January 1, 2006, and December 31, 2014. Our primary analysis quantified the drone network size required to deliver an AED 1, 2, or 3 minutes faster than historical median 911 response times for each region independently. A secondary analysis quantified the reduction in drone resources required if RescuNET was treated as a large coordinated region. The region-specific analysis determined that 81 bases and 100 drones would be required to deliver an AED ahead of median 911 response times by 3 minutes. In the most urban region, the 90th percentile of the AED arrival time was reduced by 6 minutes and 43 seconds relative to historical 911 response times in the region. In the most rural region, the 90th percentile was reduced by 10 minutes and 34 seconds. A single coordinated drone network across all regions required 39.5% fewer bases and 30.0% fewer drones to achieve similar AED delivery times. An optimized drone network designed with the aid of a novel mathematical model can substantially reduce the AED delivery time to an out-of-hospital cardiac arrest event. © 2017 American Heart Association, Inc.

One-year simulation of ozone and particulate matter in China using WRF/CMAQ modeling system

NASA Astrophysics Data System (ADS)

Hu, Jianlin; Chen, Jianjun; Ying, Qi; Zhang, Hongliang

2016-08-01

China has been experiencing severe air pollution in recent decades. Although an ambient air quality monitoring network for criteria pollutants has been constructed in over 100 cities since 2013 in China, the temporal and spatial characteristics of some important pollutants, such as particulate matter (PM) components, remain unknown, limiting further studies investigating potential air pollution control strategies to improve air quality and associating human health outcomes with air pollution exposure. In this study, a yearlong (2013) air quality simulation using the Weather Research and Forecasting (WRF) model and the Community Multi-scale Air Quality (CMAQ) model was conducted to provide detailed temporal and spatial information of ozone (O3), total PM2.5, and chemical components. Multi-resolution Emission Inventory for China (MEIC) was used for anthropogenic emissions and observation data obtained from the national air quality monitoring network were collected to validate model performance. The model successfully reproduces the O3 and PM2.5 concentrations at most cities for most months, with model performance statistics meeting the performance criteria. However, overprediction of O3 generally occurs at low concentration range while underprediction of PM2.5 happens at low concentration range in summer. Spatially, the model has better performance in southern China than in northern China, central China, and Sichuan Basin. Strong seasonal variations of PM2.5 exist and wind speed and direction play important roles in high PM2.5 events. Secondary components have more boarder distribution than primary components. Sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), and primary organic aerosol (POA) are the most important PM2.5 components. All components have the highest concentrations in winter except secondary organic aerosol (SOA). This study proves the ability of the CMAQ model to reproduce severe air pollution in China, identifies the directions where improvements are needed, and provides information for human exposure to multiple pollutants for assessing health effects.

Artificial neural network and SARIMA based models for power load forecasting in Turkish electricity market

PubMed Central

2017-01-01

Load information plays an important role in deregulated electricity markets, since it is the primary factor to make critical decisions on production planning, day-to-day operations, unit commitment and economic dispatch. Being able to predict the load for a short term, which covers one hour to a few days, equips power generation facilities and traders with an advantage. With the deregulation of electricity markets, a variety of short term load forecasting models are developed. Deregulation in Turkish Electricity Market has started in 2001 and liberalization is still in progress with rules being effective in its predefined schedule. However, there is a very limited number of studies for Turkish Market. In this study, we introduce two different models for current Turkish Market using Seasonal Autoregressive Integrated Moving Average (SARIMA) and Artificial Neural Network (ANN) and present their comparative performances. Building models that cope with the dynamic nature of deregulated market and are able to run in real-time is the main contribution of this study. We also use our ANN based model to evaluate the effect of several factors, which are claimed to have effect on electrical load. PMID:28426739

Artificial neural network and SARIMA based models for power load forecasting in Turkish electricity market.

PubMed

Bozkurt, Ömer Özgür; Biricik, Göksel; Tayşi, Ziya Cihan

2017-01-01

Load information plays an important role in deregulated electricity markets, since it is the primary factor to make critical decisions on production planning, day-to-day operations, unit commitment and economic dispatch. Being able to predict the load for a short term, which covers one hour to a few days, equips power generation facilities and traders with an advantage. With the deregulation of electricity markets, a variety of short term load forecasting models are developed. Deregulation in Turkish Electricity Market has started in 2001 and liberalization is still in progress with rules being effective in its predefined schedule. However, there is a very limited number of studies for Turkish Market. In this study, we introduce two different models for current Turkish Market using Seasonal Autoregressive Integrated Moving Average (SARIMA) and Artificial Neural Network (ANN) and present their comparative performances. Building models that cope with the dynamic nature of deregulated market and are able to run in real-time is the main contribution of this study. We also use our ANN based model to evaluate the effect of several factors, which are claimed to have effect on electrical load.

Multi-modal two-step floating catchment area analysis of primary health care accessibility.

PubMed

Langford, Mitchel; Higgs, Gary; Fry, Richard

2016-03-01

Two-step floating catchment area (2SFCA) techniques are popular for measuring potential geographical accessibility to health care services. This paper proposes methodological enhancements to increase the sophistication of the 2SFCA methodology by incorporating both public and private transport modes using dedicated network datasets. The proposed model yields separate accessibility scores for each modal group at each demand point to better reflect the differential accessibility levels experienced by each cohort. An empirical study of primary health care facilities in South Wales, UK, is used to illustrate the approach. Outcomes suggest the bus-riding cohort of each census tract experience much lower accessibility levels than those estimated by an undifferentiated (car-only) model. Car drivers' accessibility may also be misrepresented in an undifferentiated model because they potentially profit from the lower demand placed upon service provision points by bus riders. The ability to specify independent catchment sizes for each cohort in the multi-modal model allows aspects of preparedness to travel to be investigated. Copyright © 2016. Published by Elsevier Ltd.

Doctors' experience of coordination across care levels and associated factors. A cross-sectional study in public healthcare networks of six Latin American countries.

PubMed

Vázquez, María-Luisa; Vargas, Ingrid; Garcia-Subirats, Irene; Unger, Jean-Pierre; De Paepe, Pierre; Mogollón-Pérez, Amparo Susana; Samico, Isabella; Eguiguren, Pamela; Cisneros, Angelica-Ivonne; Huerta, Adriana; Muruaga, María-Cecilia; Bertolotto, Fernando

2017-06-01

Improving coordination between primary care (PC) and secondary care (SC) has become a policy priority in recent years for many Latin American public health systems looking to reinforce a healthcare model based on PC. However, despite being a longstanding concern, it has scarcely been analyzed in this region. This paper analyses the level of clinical coordination between PC and SC experienced by doctors and explores influencing factors in public healthcare networks of Argentina, Brazil, Chile, Colombia, Mexico and Uruguay. A cross-sectional study was carried out based on a survey of doctors working in the study networks (348 doctors per country). The COORDENA questionnaire was applied to measure their experiences of clinical management and information coordination, and their related factors. Descriptive analyses were conducted and a multivariate logistic regression model was generated to assess the relationship between general perception of care coordination and associated factors. With some differences between countries, doctors generally reported limited care coordination, mainly in the transfer of information and communication for the follow-up of patients and access to SC for referred patients, especially in the case of PC doctors and, to a lesser degree, inappropriate clinical referrals and disagreement over treatments, in the case of SC doctors. Factors associated with a better general perception of coordination were: being a SC doctor, considering that there is enough time for coordination within consultation hours, job and salary satisfaction, identifying the PC doctor as the coordinator of patient care across levels, knowing the doctors of the other care level and trusting in their clinical skills. These results provide evidence of problems in the implementation of a primary care-based model that require changes in aspects of employment, organization and interaction between doctors, all key factors for coordination. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Net one, net two: the primary care network income statement.

PubMed

Halley, M D; Little, A W

1999-10-01

Although hospital-owned primary care practices have been unprofitable for most hospitals, some hospitals are achieving competitive advantage and sustainable practice operations. A key to the success of some has been a net income reporting tool that separates practice operating expenses from the costs of creating and operating a network of practices to help healthcare organization managers, physicians, and staff to identify opportunities to improve the network's financial performance. This "Net One, Net Two" reporting allows operations leadership to be held accountable for Net One expenses and strategic leadership to be held accountable for Net Two expenses.

Improved Clinical Efficacy with Wound Support Network Between Hospital and Home Care Service.

PubMed

Bergersen, Tone Kristin; Storheim, Elisabeth; Gundersen, Stina; Kleven, Linn; Johnson, Maria; Sandvik, Leiv; Kvaerner, Kari Jorunn; Ørjasæter, Nils-Otto

2016-11-01

The aim of this study was to test the efficacy of a wound support network model between the primary home care service and the hospital. The impact on wound healing rate, cost benefit, and transfer of knowledge was investigated. The intervention group was exposed to a wound support network (n = 32), and the control group continued standard organization of treatment (n = 21). Nonrandomized controlled study; observations were made before (baseline) and after the implementation of the intervention (12 weeks). Patients with chronic wounds (lasting >6 weeks and with wound area >1 cm) in Oslo, Norway. Closure of the observation wound; wound size; total number of wounds; presence of eczema, edema, and pain; number of dressings per week; time spent per dressing; and number of control appointments at the hospital. The economic impact is calculated for the hospital and for the community of Oslo, Norway. The number of control appointments (t = 3.80, P < .001) was significantly decreased, and the number of completed treatments (P = .02) was significantly increased after 12 weeks in the intervention group compared with the control group. A significant improvement was evident in the intervention group in terms of eczema (P = .02), edema (P = .03), and closing of the observational wound (46.7% cases in the intervention group versus 25.0% in the control group). A wound support network between the primary home care service and the hospital is cost-effective, improves clinical efficacy of the home care services' work, and reduces the need for consultations at the hospital.

Auditory and audio-vocal responses of single neurons in the monkey ventral premotor cortex.

PubMed

Hage, Steffen R

2018-03-20

Monkey vocalization is a complex behavioral pattern, which is flexibly used in audio-vocal communication. A recently proposed dual neural network model suggests that cognitive control might be involved in this behavior, originating from a frontal cortical network in the prefrontal cortex and mediated via projections from the rostral portion of the ventral premotor cortex (PMvr) and motor cortex to the primary vocal motor network in the brainstem. For the rapid adjustment of vocal output to external acoustic events, strong interconnections between vocal motor and auditory sites are needed, which are present at cortical and subcortical levels. However, the role of the PMvr in audio-vocal integration processes remains unclear. In the present study, single neurons in the PMvr were recorded in rhesus monkeys (Macaca mulatta) while volitionally producing vocalizations in a visual detection task or passively listening to monkey vocalizations. Ten percent of randomly selected neurons in the PMvr modulated their discharge rate in response to acoustic stimulation with species-specific calls. More than four-fifths of these auditory neurons showed an additional modulation of their discharge rates either before and/or during the monkeys' motor production of the vocalization. Based on these audio-vocal interactions, the PMvr might be well positioned to mediate higher order auditory processing with cognitive control of the vocal motor output to the primary vocal motor network. Such audio-vocal integration processes in the premotor cortex might constitute a precursor for the evolution of complex learned audio-vocal integration systems, ultimately giving rise to human speech. Copyright © 2018 Elsevier B.V. All rights reserved.

Social Network Analysis Applied to a Historical Ethnographic Study Surrounding Home Birth

PubMed Central

2018-01-01

Safety during birth has improved since hospital delivery became standard practice, but the process has also become increasingly medicalised. Hence, recent years have witnessed a growing interest in home births due to the advantages it offers to mothers and their newborn infants. The aims of the present study were to confirm the transition from a home birth model of care to a scenario in which deliveries began to occur almost exclusively in a hospital setting; to define the social networks surrounding home births; and to determine whether geography exerted any influence on the social networks surrounding home births. Adopting a qualitative approach, we recruited 19 women who had given birth at home in the mid 20th century in a rural area in Spain. We employed a social network analysis method. Our results revealed three essential aspects that remain relevant today: the importance of health professionals in home delivery care, the importance of the mother’s primary network, and the influence of the geographical location of the actors involved in childbirth. All of these factors must be taken into consideration when developing strategies for maternal health. PMID:29695089

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

PubMed

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.

Communication Efficiency and Congestion of Signal Traffic in Large-Scale Brain Networks

PubMed Central

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. PMID:24415931

Functional network integrity presages cognitive decline in preclinical Alzheimer disease.

PubMed

Buckley, Rachel F; Schultz, Aaron P; Hedden, Trey; Papp, Kathryn V; Hanseeuw, Bernard J; Marshall, Gad; Sepulcre, Jorge; Smith, Emily E; Rentz, Dorene M; Johnson, Keith A; Sperling, Reisa A; Chhatwal, Jasmeer P

2017-07-04

To examine the utility of resting-state functional connectivity MRI (rs-fcMRI) measurements of network integrity as a predictor of future cognitive decline in preclinical Alzheimer disease (AD). A total of 237 clinically normal older adults (aged 63-90 years, Clinical Dementia Rating 0) underwent baseline β-amyloid (Aβ) imaging with Pittsburgh compound B PET and structural and rs-fcMRI. We identified 7 networks for analysis, including 4 cognitive networks (default, salience, dorsal attention, and frontoparietal control) and 3 noncognitive networks (primary visual, extrastriate visual, motor). Using linear and curvilinear mixed models, we used baseline connectivity in these networks to predict longitudinal changes in preclinical Alzheimer cognitive composite (PACC) performance, both alone and interacting with Aβ burden. Median neuropsychological follow-up was 3 years. Baseline connectivity in the default, salience, and control networks predicted longitudinal PACC decline, unlike connectivity in the dorsal attention and all noncognitive networks. Default, salience, and control network connectivity was also synergistic with Aβ burden in predicting decline, with combined higher Aβ and lower connectivity predicting the steepest curvilinear decline in PACC performance. In clinically normal older adults, lower functional connectivity predicted more rapid decline in PACC scores over time, particularly when coupled with increased Aβ burden. Among examined networks, default, salience, and control networks were the strongest predictors of rate of change in PACC scores, with the inflection point of greatest decline beyond the fourth year of follow-up. These results suggest that rs-fcMRI may be a useful predictor of early, AD-related cognitive decline in clinical research settings. © 2017 American Academy of Neurology.

Traffic-aware energy saving scheme with modularization supporting in TWDM-PON

NASA Astrophysics Data System (ADS)

Xiong, Yu; Sun, Peng; Liu, Chuanbo; Guan, Jianjun

2017-01-01

Time and wavelength division multiplexed passive optical network (TWDM-PON) is considered to be a primary solution for next-generation passive optical network stage 2 (NG-PON2). Due to the feature of multi-wavelength transmission of TWDM-PON, some of the transmitters/receivers at the optical line terminal (OLT) could be shut down to reduce the energy consumption. Therefore, a novel scheme called traffic-aware energy saving scheme with modularization supporting is proposed. Through establishing the modular energy consumption model of OLT, the wavelength transmitters/receivers at OLT could be switched on or shut down adaptively depending on sensing the status of network traffic load, thus the energy consumption of OLT will be effectively reduced. Furthermore, exploring the technology of optical network unit (ONU) modularization, each module of ONU could be switched to sleep or active mode independently in order to reduce the energy consumption of ONU. Simultaneously, the polling sequence of ONU could be changed dynamically via sensing the packet arrival time. In order to guarantee the delay performance of network traffic, the sub-cycle division strategy is designed to transmit the real-time traffic preferentially. Finally, simulation results verify that the proposed scheme is able to reduce the energy consumption of the network while maintaining the traffic delay performance.

Integration of offshore wind farms through high voltage direct current networks

NASA Astrophysics Data System (ADS)

Livermore, Luke

The integration of offshore wind farms through Multi Terminal DC (MTDC) networks into the GB network was investigated. The ability of Voltage Source Converter (VSC) High Voltage Direct Current (HVDC) to damp Subsynchronous Resonance (SSR) and ride through onshore AC faults was studied. Due to increased levels of wind generation in Scotland, substantial onshore and offshore reinforcements to the GB transmission network are proposed. Possible inland reinforcements include the use of series compensation through fixed capacitors. This potentially can lead to SSR. Offshore reinforcements are proposed by two HVDC links. In addition to its primary functions of bulk power transmission, a HVDC link can be used to provide damping against SSR, and this function has been modelled. Simulation studies have been carried out in PSCAD. In addition, a real-time hardware-in-the-loop HVDC test rig has been used to implement and validate the proposed damping scheme on an experimental platform. When faults occur within AC onshore networks, offshore MTDC networks are vulnerable to DC overvoltages, potentially damaging the DC plant and cables. Power reduction and power dissipation control systems were investigated to ride through onshore AC faults. These methods do not require dedicated fast communication systems. Simulations and laboratory experiments are carried out to evaluate the control systems, with the results from the two platforms compared..

Highly accurate photogrammetric measurements of the Planck reflectors

NASA Astrophysics Data System (ADS)

Amiri Parian, Jafar; Gruen, Armin; Cozzani, Alessandro

2017-11-01

The Planck mission of the European Space Agency (ESA) is designed to image the anisotropies of the Cosmic Background Radiation Field over the whole sky. To achieve this aim, sophisticated reflectors are used as part of the Planck telescope receiving system. The system consists of secondary and primary reflectors which are sections of two different ellipsoids of revolution with mean diameters of 1 and 1.6 meters. Deformations of the reflectors which influence the optical parameters and the gain of receiving signals are investigated in vacuum and at very low temperatures. For this investigation, among the various high accuracy measurement techniques, photogrammetry was selected. With respect to the photogrammetric measurements, special considerations had to be taken into account in design steps, measurement arrangement and data processing to achieve very high accuracies. The determinability of additional parameters of the camera under the given network configuration, datum definition, reliability and precision issues as well as workspace limits and propagating errors from different sources are considered. We have designed an optimal photogrammetric network by heuristic simulation for the flight model of the primary and the secondary reflectors with relative precisions better than 1:1000'000 and 1:400'000 to achieve the requested accuracies. A least squares best fit ellipsoid method was developed to determine the optical parameters of the reflectors. In this paper we will report about the procedures, the network design and the results of real measurements.

Time-Series Transcriptomics Reveals That AGAMOUS-LIKE22 Affects Primary Metabolism and Developmental Processes in Drought-Stressed Arabidopsis[OPEN

PubMed Central

Penfold, Christopher A.; Jenkins, Dafyd J.; Legaie, Roxane; Lawson, Tracy; Vialet-Chabrand, Silvere R.M.; Subramaniam, Sunitha; Hickman, Richard; Feil, Regina; Bowden, Laura; Hill, Claire; Lunn, John E.; Finkenstädt, Bärbel; Buchanan-Wollaston, Vicky; Beynon, Jim; Wild, David L.; Ott, Sascha

2016-01-01

In Arabidopsis thaliana, changes in metabolism and gene expression drive increased drought tolerance and initiate diverse drought avoidance and escape responses. To address regulatory processes that link these responses, we set out to identify genes that govern early responses to drought. To do this, a high-resolution time series transcriptomics data set was produced, coupled with detailed physiological and metabolic analyses of plants subjected to a slow transition from well-watered to drought conditions. A total of 1815 drought-responsive differentially expressed genes were identified. The early changes in gene expression coincided with a drop in carbon assimilation, and only in the late stages with an increase in foliar abscisic acid content. To identify gene regulatory networks (GRNs) mediating the transition between the early and late stages of drought, we used Bayesian network modeling of differentially expressed transcription factor (TF) genes. This approach identified AGAMOUS-LIKE22 (AGL22), as key hub gene in a TF GRN. It has previously been shown that AGL22 is involved in the transition from vegetative state to flowering but here we show that AGL22 expression influences steady state photosynthetic rates and lifetime water use. This suggests that AGL22 uniquely regulates a transcriptional network during drought stress, linking changes in primary metabolism and the initiation of stress responses. PMID:26842464

Neural Plasticity and Memory: Is Memory Encoded in Hydrogen Bonding Patterns?

PubMed

Amtul, Zareen; Rahman, Atta-Ur

2016-02-01

Current models of memory storage recognize posttranslational modification vital for short-term and mRNA translation for long-lasting information storage. However, at the molecular level things are quite vague. A comprehensive review of the molecular basis of short and long-lasting synaptic plasticity literature leads us to propose that the hydrogen bonding pattern at the molecular level may be a permissive, vital step of memory storage. Therefore, we propose that the pattern of hydrogen bonding network of biomolecules (glycoproteins and/or DNA template, for instance) at the synapse is the critical edifying mechanism essential for short- and long-term memories. A novel aspect of this model is that nonrandom impulsive (or unplanned) synaptic activity functions as a synchronized positive-feedback rehearsal mechanism by revising the configurations of the hydrogen bonding network by tweaking the earlier tailored hydrogen bonds. This process may also maintain the elasticity of the related synapses involved in memory storage, a characteristic needed for such networks to alter intricacy and revise endlessly. The primary purpose of this review is to stimulate the efforts to elaborate the mechanism of neuronal connectivity both at molecular and chemical levels. © The Author(s) 2014.

Network model of top-down influences on local gain and contextual interactions in visual cortex.

PubMed

Piëch, Valentin; Li, Wu; Reeke, George N; Gilbert, Charles D

2013-10-22

The visual system uses continuity as a cue for grouping oriented line segments that define object boundaries in complex visual scenes. Many studies support the idea that long-range intrinsic horizontal connections in early visual cortex contribute to this grouping. Top-down influences in primary visual cortex (V1) play an important role in the processes of contour integration and perceptual saliency, with contour-related responses being task dependent. This suggests an interaction between recurrent inputs to V1 and intrinsic connections within V1 that enables V1 neurons to respond differently under different conditions. We created a network model that simulates parametrically the control of local gain by hypothetical top-down modification of local recurrence. These local gain changes, as a consequence of network dynamics in our model, enable modulation of contextual interactions in a task-dependent manner. Our model displays contour-related facilitation of neuronal responses and differential foreground vs. background responses over the neuronal ensemble, accounting for the perceptual pop-out of salient contours. It quantitatively reproduces the results of single-unit recording experiments in V1, highlighting salient contours and replicating the time course of contextual influences. We show by means of phase-plane analysis that the model operates stably even in the presence of large inputs. Our model shows how a simple form of top-down modulation of the effective connectivity of intrinsic cortical connections among biophysically realistic neurons can account for some of the response changes seen in perceptual learning and task switching.

Optimizing Power–Frequency Droop Characteristics of Distributed Energy Resources

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

Guggilam, Swaroop S.; Zhao, Changhong; Dall Anese, Emiliano

This paper outlines a procedure to design power-frequency droop slopes for distributed energy resources (DERs) installed in distribution networks to optimally participate in primary frequency response. In particular, the droop slopes are engineered such that DERs respond in proportion to their power ratings and they are not unfairly penalized in power provisioning based on their location in the distribution network. The main contribution of our approach is that a guaranteed level of frequency regulation can be guaranteed at the feeder head, while ensuring that the outputs of individual DERs conform to some well-defined notion of fairness. The approach we adoptmore » leverages an optimization-based perspective and suitable linearizations of the power-flow equations to embed notions of fairness and information regarding the physics of the power flows within the distribution network into the droop slopes. Time-domain simulations from a differential algebraic equation model of the 39-bus New England test-case system augmented with three instances of the IEEE 37-node distribution-network with frequency-sensitive DERs are provided to validate our approach.« less

Performance Evaluation of Public Non-Profit Hospitals Using a BP Artificial Neural Network: The Case of Hubei Province in China

PubMed Central

Li, Chunhui; Yu, Chuanhua

2013-01-01

To provide a reference for evaluating public non-profit hospitals in the new environment of medical reform, we established a performance evaluation system for public non-profit hospitals. The new “input-output” performance model for public non-profit hospitals is based on four primary indexes (input, process, output and effect) that include 11 sub-indexes and 41 items. The indicator weights were determined using the analytic hierarchy process (AHP) and entropy weight method. The BP neural network was applied to evaluate the performance of 14 level-3 public non-profit hospitals located in Hubei Province. The most stable BP neural network was produced by comparing different numbers of neurons in the hidden layer and using the “Leave-one-out” Cross Validation method. The performance evaluation system we established for public non-profit hospitals could reflect the basic goal of the new medical health system reform in China. Compared with PLSR, the result indicated that the BP neural network could be used effectively for evaluating the performance public non-profit hospitals. PMID:23955238

Theoretical estimates of mechanical properties of the endothelial cell cytoskeleton.

PubMed Central

Satcher, R L; Dewey, C F

1996-01-01

Current modeling of endothelial cell mechanics does not account for the network of F-actin that permeates the cytoplasm. This network, the distributed cytoplasmic structural actin (DCSA), extends from apical to basal membranes, with frequent attachments. Stress fibers are intercalated within the network, with similar frequent attachments. The microscopic structure of the DCSA resembles a foam, so that the mechanical properties can be estimated with analogy to these well-studied systems. The moduli of shear and elastic deformations are estimated to be on the order of 10(5) dynes/cm2. This prediction agrees with experimental measurements of the properties of cytoplasm and endothelial cells reported elsewhere. Stress fibers can potentially increase the modulus by a factor of 2-10, depending on whether they act in series or parallel to the network in transmitting surface forces. The deformations produced by physiological flow fields are of insufficient magnitude to disrupt cell-to-cell or DCSA cross-linkages. The questions raised by this paradox, and the ramifications of implicating the previously unreported DCSA as the primary force transmission element are discussed. Images FIGURE 2 PMID:8804594

Data mining reveals a network of early-response genes as a consensus signature of drug-induced in vitro and in vivo toxicity.

PubMed

Zhang, J D; Berntenis, N; Roth, A; Ebeling, M

2014-06-01

Gene signatures of drug-induced toxicity are of broad interest, but they are often identified from small-scale, single-time point experiments, and are therefore of limited applicability. To address this issue, we performed multivariate analysis of gene expression, cell-based assays, and histopathological data in the TG-GATEs (Toxicogenomics Project-Genomics Assisted Toxicity Evaluation system) database. Data mining highlights four genes-EGR1, ATF3, GDF15 and FGF21-that are induced 2 h after drug administration in human and rat primary hepatocytes poised to eventually undergo cytotoxicity-induced cell death. Modelling and simulation reveals that these early stress-response genes form a functional network with evolutionarily conserved structure and intrinsic dynamics. This is underlined by the fact that early induction of this network in vivo predicts drug-induced liver and kidney pathology with high accuracy. Our findings demonstrate the value of early gene-expression signatures in predicting and understanding compound-induced toxicity. The identified network can empower first-line tests that reduce animal use and costs of safety evaluation.

Using an established telehealth model to train urban primary care providers on hypertension management.

PubMed

Masi, Christopher; Hamlish, Tamara; Davis, Andrew; Bordenave, Kristine; Brown, Stephen; Perea, Brenda; Aduana, Glen; Wolfe, Marcus; Bakris, George; Johnson, Daniel

2012-01-01

The objective of this study was to determine whether a videoconference-based telehealth network can increase hypertension management knowledge and self-assessed competency among primary care providers (PCPs) working in urban Federally Qualified Health Centers (FQHCs). We created a telehealth network among 6 urban FQHCs and our institution to support a 12-session educational program designed to teach state-of-the-art hypertension management. Each 1-hour session included a brief lecture by a university-based hypertension specialist, case presentations by PCPs, and interactive discussions among the specialist and PCPs. Twelve PCPs (9 intervention and 3 controls) were surveyed at baseline and immediately following the curriculum. The mean number of correct answers on the 26-item hypertension knowledge questionnaire increased in the intervention group (13.11 [standard deviation (SD)]=3.06) to 17.44 [SD=1.59], P<.01) but not among controls (14.33 [SD=3.21] to 13.00 [SD=3.46], P=.06). Similarly, the mean score on a 7-item hypertension management self-assessed competency scale increased in the intervention group (4.68 [SD=0.94] to 5.41 [SD=0.89], P<.01) but not among controls (5.28 [SD=0.43] to 5.62 [SD=0.67], P=.64). This model holds promise for enhancing hypertension care provided by urban FQHC providers. © 2011 Wiley Periodicals, Inc.

Improving integrated care: modelling the performance of an online community of practice

PubMed Central

Díaz-Chao, Ángel; Torrent-Sellens, Joan; Lacasta-Tintorer, David; Saigí-Rubió, Francesc

2014-01-01

Introduction This article aims to confirm the following core hypothesis: a Community of Practice's use of a Web 2.0 platform for communication between primary and hospital care leads to improved primary care and fewer hospital referrals. This core hypothesis will be corroborated by testing a further five partial hypotheses that complete the main hypothesis being estimated. Methods An ad-hoc questionnaire was designed and sent to a sample group of 357 professionals from the Badalona-Sant Adrià de Besòs Primary Care Service in Catalonia, Spain, which includes nine primary care centres and three specialist care centres. The study sample was formed by 159 respondents. The partial least squares methodology was used to estimate the model of the causal relationship and the proposed hypotheses. Results It was found that when healthcare staff used social networks and information and communication technologies professionally, and the more contact hours they have with patients, the more a Web 2.0 platform was likely to be used for communication between primary and hospital care professionals. Such use led to improved primary care and fewer hospital referrals according to the opinions of health professionals on its use. Conclusions The research suggests that the efficiency of medical practice is explained by the intensity of Web 2.0 platform use for communication between primary and specialist care professionals. Public policies promoting the use of information and communication technologies in communities of practice should go beyond the technological dimension and consider other professional, organisational and social determinants. PMID:24648835

Information fusion via isocortex-based Area 37 modeling

NASA Astrophysics Data System (ADS)

Peterson, James K.

2004-08-01

A simplified model of information processing in the brain can be constructed using primary sensory input from two modalities (auditory and visual) and recurrent connections to the limbic subsystem. Information fusion would then occur in Area 37 of the temporal cortex. The creation of meta concepts from the low order primary inputs is managed by models of isocortex processing. Isocortex algorithms are used to model parietal (auditory), occipital (visual), temporal (polymodal fusion) cortex and the limbic system. Each of these four modules is constructed out of five cortical stacks in which each stack consists of three vertically oriented six layer isocortex models. The input to output training of each cortical model uses the OCOS (on center - off surround) and FFP (folded feedback pathway) circuitry of (Grossberg, 1) which is inherently a recurrent network type of learning characterized by the identification of perceptual groups. Models of this sort are thus closely related to cognitive models as it is difficult to divorce the sensory processing subsystems from the higher level processing in the associative cortex. The overall software architecture presented is biologically based and is presented as a potential architectural prototype for the development of novel sensory fusion strategies. The algorithms are motivated to some degree by specific data from projects on musical composition and autonomous fine art painting programs, but only in the sense that these projects use two specific types of auditory and visual cortex data. Hence, the architectures are presented for an artificial information processing system which utilizes two disparate sensory sources. The exact nature of the two primary sensory input streams is irrelevant.

Abnormal dopaminergic modulation of striato-cortical networks underlies levodopa-induced dyskinesias in humans

PubMed Central

Haagensen, Brian N.; Christensen, Mark S.; Madsen, Kristoffer H.; Rowe, James B.; Løkkegaard, Annemette; Siebner, Hartwig R.

2015-01-01

Dopaminergic signalling in the striatum contributes to reinforcement of actions and motivational enhancement of motor vigour. Parkinson's disease leads to progressive dopaminergic denervation of the striatum, impairing the function of cortico-basal ganglia networks. While levodopa therapy alleviates basal ganglia dysfunction in Parkinson's disease, it often elicits involuntary movements, referred to as levodopa-induced peak-of-dose dyskinesias. Here, we used a novel pharmacodynamic neuroimaging approach to identify the changes in cortico-basal ganglia connectivity that herald the emergence of levodopa-induced dyskinesias. Twenty-six patients with Parkinson's disease (age range: 51–84 years; 11 females) received a single dose of levodopa and then performed a task in which they had to produce or suppress a movement in response to visual cues. Task-related activity was continuously mapped with functional magnetic resonance imaging. Dynamic causal modelling was applied to assess levodopa-induced modulation of effective connectivity between the pre-supplementary motor area, primary motor cortex and putamen when patients suppressed a motor response. Bayesian model selection revealed that patients who later developed levodopa-induced dyskinesias, but not patients without dyskinesias, showed a linear increase in connectivity between the putamen and primary motor cortex after levodopa intake during movement suppression. Individual dyskinesia severity was predicted by levodopa-induced modulation of striato-cortical feedback connections from putamen to the pre-supplementary motor area (Pcorrected = 0.020) and primary motor cortex (Pcorrected = 0.044), but not feed-forward connections from the cortex to the putamen. Our results identify for the first time, aberrant dopaminergic modulation of striatal-cortical connectivity as a neural signature of levodopa-induced dyskinesias in humans. We argue that excessive striato-cortical connectivity in response to levodopa produces an aberrant reinforcement signal producing an abnormal motor drive that ultimately triggers involuntary movements. PMID:25882651

3D printing of layered brain-like structures using peptide modified gellan gum substrates.

PubMed

Lozano, Rodrigo; Stevens, Leo; Thompson, Brianna C; Gilmore, Kerry J; Gorkin, Robert; Stewart, Elise M; in het Panhuis, Marc; Romero-Ortega, Mario; Wallace, Gordon G

2015-10-01

The brain is an enormously complex organ structured into various regions of layered tissue. Researchers have attempted to study the brain by modeling the architecture using two dimensional (2D) in vitro cell culturing methods. While those platforms attempt to mimic the in vivo environment, they do not truly resemble the three dimensional (3D) microstructure of neuronal tissues. Development of an accurate in vitro model of the brain remains a significant obstacle to our understanding of the functioning of the brain at the tissue or organ level. To address these obstacles, we demonstrate a new method to bioprint 3D brain-like structures consisting of discrete layers of primary neural cells encapsulated in hydrogels. Brain-like structures were constructed using a bio-ink consisting of a novel peptide-modified biopolymer, gellan gum-RGD (RGD-GG), combined with primary cortical neurons. The ink was optimized for a modified reactive printing process and developed for use in traditional cell culturing facilities without the need for extensive bioprinting equipment. Furthermore the peptide modification of the gellan gum hydrogel was found to have a profound positive effect on primary cell proliferation and network formation. The neural cell viability combined with the support of neural network formation demonstrated the cell supportive nature of the matrix. The facile ability to form discrete cell-containing layers validates the application of this novel printing technique to form complex, layered and viable 3D cell structures. These brain-like structures offer the opportunity to reproduce more accurate 3D in vitro microstructures with applications ranging from cell behavior studies to improving our understanding of brain injuries and neurodegenerative diseases. Copyright © 2015 Elsevier Ltd. All rights reserved.

Association between quality domains and health care spending across physician networks

PubMed Central

Rahman, Farah; Guan, Jun; Glazier, Richard H.; Brown, Adalsteinn; Bierman, Arlene S.; Croxford, Ruth; Stukel, Therese A.

2018-01-01

One of the more fundamental health policy questions is the relationship between health care quality and spending. A better understanding of these relationships is needed to inform health systems interventions aimed at increasing quality and efficiency of care. We measured 65 validated quality indicators (QI) across Ontario physician networks. QIs were aggregated into domains representing six dimensions of care: screening and prevention, evidence-based medications, hospital-community transitions (7-day post-discharge visit with a primary care physician; 30-day post-discharge visit with a primary care physician and specialist), potentially avoidable hospitalizations and emergency department (ED) visits, potentially avoidable readmissions and unplanned returns to the ED, and poor cancer end of life care. Each domain rate was computed as a weighted average of QI rates, weighting by network population at risk. We also measured overall and sector-specific per capita healthcare network spending. We evaluated the associations between domain rates, and between domain rates and spending using weighted correlations, weighting by network population at risk, using an ecological design. All indicators were measured using Ontario health administrative databases. Large variations were seen in timely hospital-community transitions and potentially avoidable hospitalizations. Networks with timely hospital-community transitions had lower rates of avoidable admissions and readmissions (r = -0.89, -0.58, respectively). Higher physician spending, especially outpatient primary care spending, was associated with lower rates of avoidable hospitalizations (r = -0.83) and higher rates of timely hospital-community transitions (r = 0.81) and moderately associated with lower readmission rates (r = -0.46). Investment in effective primary care services may help reduce burden on the acute care sector and associated expenditures. PMID:29614131

An Energy-Efficient Spectrum-Aware Reinforcement Learning-Based Clustering Algorithm for Cognitive Radio Sensor Networks

PubMed Central

Mustapha, Ibrahim; Ali, Borhanuddin Mohd; Rasid, Mohd Fadlee A.; Sali, Aduwati; Mohamad, Hafizal

2015-01-01

It is well-known that clustering partitions network into logical groups of nodes in order to achieve energy efficiency and to enhance dynamic channel access in cognitive radio through cooperative sensing. While the topic of energy efficiency has been well investigated in conventional wireless sensor networks, the latter has not been extensively explored. In this paper, we propose a reinforcement learning-based spectrum-aware clustering algorithm that allows a member node to learn the energy and cooperative sensing costs for neighboring clusters to achieve an optimal solution. Each member node selects an optimal cluster that satisfies pairwise constraints, minimizes network energy consumption and enhances channel sensing performance through an exploration technique. We first model the network energy consumption and then determine the optimal number of clusters for the network. The problem of selecting an optimal cluster is formulated as a Markov Decision Process (MDP) in the algorithm and the obtained simulation results show convergence, learning and adaptability of the algorithm to dynamic environment towards achieving an optimal solution. Performance comparisons of our algorithm with the Groupwise Spectrum Aware (GWSA)-based algorithm in terms of Sum of Square Error (SSE), complexity, network energy consumption and probability of detection indicate improved performance from the proposed approach. The results further reveal that an energy savings of 9% and a significant Primary User (PU) detection improvement can be achieved with the proposed approach. PMID:26287191

An Energy-Efficient Spectrum-Aware Reinforcement Learning-Based Clustering Algorithm for Cognitive Radio Sensor Networks.

PubMed

Mustapha, Ibrahim; Mohd Ali, Borhanuddin; Rasid, Mohd Fadlee A; Sali, Aduwati; Mohamad, Hafizal

2015-08-13

It is well-known that clustering partitions network into logical groups of nodes in order to achieve energy efficiency and to enhance dynamic channel access in cognitive radio through cooperative sensing. While the topic of energy efficiency has been well investigated in conventional wireless sensor networks, the latter has not been extensively explored. In this paper, we propose a reinforcement learning-based spectrum-aware clustering algorithm that allows a member node to learn the energy and cooperative sensing costs for neighboring clusters to achieve an optimal solution. Each member node selects an optimal cluster that satisfies pairwise constraints, minimizes network energy consumption and enhances channel sensing performance through an exploration technique. We first model the network energy consumption and then determine the optimal number of clusters for the network. The problem of selecting an optimal cluster is formulated as a Markov Decision Process (MDP) in the algorithm and the obtained simulation results show convergence, learning and adaptability of the algorithm to dynamic environment towards achieving an optimal solution. Performance comparisons of our algorithm with the Groupwise Spectrum Aware (GWSA)-based algorithm in terms of Sum of Square Error (SSE), complexity, network energy consumption and probability of detection indicate improved performance from the proposed approach. The results further reveal that an energy savings of 9% and a significant Primary User (PU) detection improvement can be achieved with the proposed approach.

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

Dall-Anese, Emiliano; Zhao, Changhong; Guggilam, Swaroop

Power networks have to withstand a variety of disturbances that affect system frequency, and the problem is compounded with the increasing integration of intermittent renewable generation. Following a large-signal generation or load disturbance, system frequency is arrested leveraging primary frequency control provided by governor action in synchronous generators. In this work, we propose a framework for distributed energy resources (DERs) deployed in distribution networks to provide (supplemental) primary frequency response. Particularly, we demonstrate how power-frequency droop slopes for individual DERs can be designed so that the distribution feeder presents a guaranteed frequency-regulation characteristic at the feeder head. Furthermore, the droopmore » slopes are engineered such that injections of individual DERs conform to a well-defined fairness objective that does not penalize them for their location on the distribution feeder. Time-domain simulations for an illustrative network composed of a combined transmission network and distribution network with frequency-responsive DERs are provided to validate the approach.« less

Airport-Noise Levels and Annoyance Model (ALAMO) user's guide

NASA Technical Reports Server (NTRS)

Deloach, R.; Donaldson, J. L.; Johnson, M. J.

1986-01-01

A guide for the use of the Airport-Noise Level and Annoyance MOdel (ALAMO) at the Langley Research Center computer complex is provided. This document is divided into 5 primary sections, the introduction, the purpose of the model, and an in-depth description of the following subsystems: baseline, noise reduction simulation and track analysis. For each subsystem, the user is provided with a description of architecture, an explanation of subsystem use, sample results, and a case runner's check list. It is assumed that the user is familiar with the operations at the Langley Research Center (LaRC) computer complex, the Network Operating System (NOS 1.4) and CYBER Control Language. Incorporated within the ALAMO model is a census database system called SITE II.

Potential role of combined FDG PET/CT & contrast enhancement MRI in a rectal carcinoma model with nodal metastases characterized by a poor FDG-avidity.

PubMed

Farace, Paolo; Conti, Giamaica; Merigo, Flavia; Tambalo, Stefano; Marzola, Pasquina; Sbarbati, Andrea; Quarta, Carmelo; D'Ambrosio, Daniela; Chondrogiannis, Sotirios; Nanni, Cristina; Rubello, Domenico

2012-04-01

To investigate the additional role of MRI contrast enhancement (CE) in the primary tumor and the FDG uptake at PET in the lymph-node metastases. A model of colorectal cancer induced by orthotopic HT-29 cells microinjection, producing pelvic lymph node metastases, was assessed using CE-MRI and FDG-PET. Histology and GLUT-1 immunohistochemistry were performed on primary tumors and iliac lymph nodes. Primary tumors were characterized by low FDG-uptake but high CE-MRI, particularly at tumor periphery. Undetectable FDG-uptake characterized the metastatic lymph-nodes. Histology revealed large stromal bundles at tumor periphery and a dense network of stromal fibers and neoplastic cells in the inner portion of the tumors. Both primary tumors and positive lymph nodes showed poor GLUT-1 staining. Our data support the complementary role of MRI-CE and FDG PET in some types of carcinomas characterized by abundant cancer-associated stroma and poor FDG avidity consequent to poor GLUT-1 transported. In these tumors FDG-PET alone may be not completely adequate to obtain an adequate tumor radiotherapy planning, and a combination with dual CE-MRI is strongly recommended. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Understanding the implementation of evidence-based care: a structural network approach.

PubMed

Parchman, Michael L; Scoglio, Caterina M; Schumm, Phillip

2011-02-24

Recent study of complex networks has yielded many new insights into phenomenon such as social networks, the internet, and sexually transmitted infections. The purpose of this analysis is to examine the properties of a network created by the 'co-care' of patients within one region of the Veterans Health Affairs. Data were obtained for all outpatient visits from 1 October 2006 to 30 September 2008 within one large Veterans Integrated Service Network. Types of physician within each clinic were nodes connected by shared patients, with a weighted link representing the number of shared patients between each connected pair. Network metrics calculated included edge weights, node degree, node strength, node coreness, and node betweenness. Log-log plots were used to examine the distribution of these metrics. Sizes of k-core networks were also computed under multiple conditions of node removal. There were 4,310,465 encounters by 266,710 shared patients between 722 provider types (nodes) across 41 stations or clinics resulting in 34,390 edges. The number of other nodes to which primary care provider nodes have a connection (172.7) is 42% greater than that of general surgeons and two and one-half times as high as cardiology. The log-log plot of the edge weight distribution appears to be linear in nature, revealing a 'scale-free' characteristic of the network, while the distributions of node degree and node strength are less so. The analysis of the k-core network sizes under increasing removal of primary care nodes shows that about 10 most connected primary care nodes play a critical role in keeping the k-core networks connected, because their removal disintegrates the highest k-core network. Delivery of healthcare in a large healthcare system such as that of the US Department of Veterans Affairs (VA) can be represented as a complex network. This network consists of highly connected provider nodes that serve as 'hubs' within the network, and demonstrates some 'scale-free' properties. By using currently available tools to explore its topology, we can explore how the underlying connectivity of such a system affects the behavior of providers, and perhaps leverage that understanding to improve quality and outcomes of care.

A neural model of mechanisms of empathy deficits in narcissism

PubMed Central

Jankowiak-Siuda, Kamila; Zajkowski, Wojciech

2013-01-01

From a multidimensional perspective, empathy is a process that includes affective sharing and imagining and understanding the emotions of others. The primary brain structures involved in mediating the components of empathy are the anterior insula (AI), the anterior cingulate cortex (ACC), and specific regions of the medial prefrontal cortex (MPFC). The AI and ACC are the main nodes in the salience network (SN), which selects and coordinates the information flow from the intero- and exteroreceptors. AI might play a role as a crucial hub – a dynamic switch between 2 separate networks of cognitive processing: the central executive network (CEN), which is concerned with effective task execution, and the default mode network (DMN), which is involved with self-reflective processes. Given various classifications, a deficit in empathy may be considered a central dysfunctional trait in narcissism. A recent fMRI study suggests that deficit in empathy is due to a dysfunction in the right AI. Based on the acquired data, we propose a theoretical model of imbalanced SN functioning in narcissism in which the dysfunctional AI hub is responsible for constant DMN activation, which, in turn, centers one’s attention on the self. This might hinder the ability to affectively share and understand the emotions of others. This review paper on neural mechanisms of empathy deficits in narcissism aims to inspire and direct future research in this area. PMID:24189465

Negative Correlations in Visual Cortical Networks

PubMed Central

Chelaru, Mircea I.; Dragoi, Valentin

2016-01-01

The amount of information encoded by cortical circuits depends critically on the capacity of nearby neurons to exhibit trial-to-trial (noise) correlations in their responses. Depending on their sign and relationship to signal correlations, noise correlations can either increase or decrease the population code accuracy relative to uncorrelated neuronal firing. Whereas positive noise correlations have been extensively studied using experimental and theoretical tools, the functional role of negative correlations in cortical circuits has remained elusive. We addressed this issue by performing multiple-electrode recording in the superficial layers of the primary visual cortex (V1) of alert monkey. Despite the fact that positive noise correlations decayed exponentially with the difference in the orientation preference between cells, negative correlations were uniformly distributed across the population. Using a statistical model for Fisher Information estimation, we found that a mild increase in negative correlations causes a sharp increase in network accuracy even when mean correlations were held constant. To examine the variables controlling the strength of negative correlations, we implemented a recurrent spiking network model of V1. We found that increasing local inhibition and reducing excitation causes a decrease in the firing rates of neurons while increasing the negative noise correlations, which in turn increase the population signal-to-noise ratio and network accuracy. Altogether, these results contribute to our understanding of the neuronal mechanism involved in the generation of negative correlations and their beneficial impact on cortical circuit function. PMID:25217468

The impact of a social network intervention on retention in Belgian therapeutic communities: a quasi-experimental study.

PubMed

Soyez, Veerle; De Leon, George; Broekaert, Eric; Rosseel, Yves

2006-07-01

Although numerous studies recognize the importance of social network support in engaging substance abusers into treatment, there is only limited knowledge of the impact of network involvement and support during treatment. The primary objective of this research was to enhance retention in Therapeutic Community treatment utilizing a social network intervention. The specific goals of this study were (1) to determine whether different pre-treatment factors predicted treatment retention in a Therapeutic Community; and (2) to determine whether participation of significant others in a social network intervention predicted treatment retention. Consecutive admissions to four long-term residential Therapeutic Communities were assessed at intake (n = 207); the study comprised a mainly male (84.9%) sample of polydrug (41.1%) and opiate (20.8%) abusers, of whom 64.4% had ever injected drugs. Assessment involved the European version of the Addiction Severity Index (EuropASI), the Circumstances, Motivation, Readiness scales (CMR), the Dutch version of the family environment scale (GKS/FES) and an in-depth interview on social network structure and perceived social support. Network members of different cohorts were assigned to a social network intervention, which consisted of three elements (a video, participation at an induction day and participation in a discussion session). Hierarchical regression analyses showed that client-perceived social support (F1,198 = 10.9, P = 0.001) and treatment motivation and readiness (F1,198 = 8.8; P = 0.003) explained a significant proportion of the variance in treatment retention (model fit: F7,197 = 4.4; P = 0.000). By including the variable 'significant others' participation in network intervention' (network involvement) in the model, the fit clearly improved (F1,197 = 6.2; P = 0.013). At the same time, the impact of perceived social support decreased (F1,197 = 2.9; P = 0.091). Participation in the social network intervention was associated with improved treatment retention controlling for other client characteristics. This suggests that the intervention may be of benefit in the treatment of addicted individuals.

A Novel Wireless Power Transfer-Based Weighed Clustering Cooperative Spectrum Sensing Method for Cognitive Sensor Networks.

PubMed

Liu, Xin

2015-10-30

In a cognitive sensor network (CSN), the wastage of sensing time and energy is a challenge to cooperative spectrum sensing, when the number of cooperative cognitive nodes (CNs) becomes very large. In this paper, a novel wireless power transfer (WPT)-based weighed clustering cooperative spectrum sensing model is proposed, which divides all the CNs into several clusters, and then selects the most favorable CNs as the cluster heads and allows the common CNs to transfer the received radio frequency (RF) energy of the primary node (PN) to the cluster heads, in order to supply the electrical energy needed for sensing and cooperation. A joint resource optimization is formulated to maximize the spectrum access probability of the CSN, through jointly allocating sensing time and clustering number. According to the resource optimization results, a clustering algorithm is proposed. The simulation results have shown that compared to the traditional model, the cluster heads of the proposed model can achieve more transmission power and there exists optimal sensing time and clustering number to maximize the spectrum access probability.

Engineering Online and In-person Social Networks for Physical Activity: A Randomized Trial

PubMed Central

Rovniak, Liza S.; Kong, Lan; Hovell, Melbourne F.; Ding, Ding; Sallis, James F.; Ray, Chester A.; Kraschnewski, Jennifer L.; Matthews, Stephen A.; Kiser, Elizabeth; Chinchilli, Vernon M.; George, Daniel R.; Sciamanna, Christopher N.

2016-01-01

Background Social networks can influence physical activity, but little is known about how best to engineer online and in-person social networks to increase activity. Purpose To conduct a randomized trial based on the Social Networks for Activity Promotion model to assess the incremental contributions of different procedures for building social networks on objectively-measured outcomes. Methods Physically inactive adults (n = 308, age, 50.3 (SD = 8.3) years, 38.3% male, 83.4% overweight/obese) were randomized to 1 of 3 groups. The Promotion group evaluated the effects of weekly emailed tips emphasizing social network interactions for walking (e.g., encouragement, informational support); the Activity group evaluated the incremental effect of adding an evidence-based online fitness walking intervention to the weekly tips; and the Social Networks group evaluated the additional incremental effect of providing access to an online networking site for walking, and prompting walking/activity across diverse settings. The primary outcome was mean change in accelerometer-measured moderate-to-vigorous physical activity (MVPA), assessed at 3 and 9 months from baseline. Results Participants increased their MVPA by 21.0 mins/week, 95% CI [5.9, 36.1], p = .005, at 3 months, and this change was sustained at 9 months, with no between-group differences. Conclusions Although the structure of procedures for targeting social networks varied across intervention groups, the functional effect of these procedures on physical activity was similar. Future research should evaluate if more powerful reinforcers improve the effects of social network interventions. Trial Registration Number NCT01142804 PMID:27405724

Intelligent emissions controller for substance injection in the post-primary combustion zone of fossil-fired boilers

DOEpatents

Reifman, Jaques; Feldman, Earl E.; Wei, Thomas Y. C.; Glickert, Roger W.

2003-01-01

The control of emissions from fossil-fired boilers wherein an injection of substances above the primary combustion zone employs multi-layer feedforward artificial neural networks for modeling static nonlinear relationships between the distribution of injected substances into the upper region of the furnace and the emissions exiting the furnace. Multivariable nonlinear constrained optimization algorithms use the mathematical expressions from the artificial neural networks to provide the optimal substance distribution that minimizes emission levels for a given total substance injection rate. Based upon the optimal operating conditions from the optimization algorithms, the incremental substance cost per unit of emissions reduction, and the open-market price per unit of emissions reduction, the intelligent emissions controller allows for the determination of whether it is more cost-effective to achieve additional increments in emission reduction through the injection of additional substance or through the purchase of emission credits on the open market. This is of particular interest to fossil-fired electrical power plant operators. The intelligent emission controller is particularly adapted for determining the economical control of such pollutants as oxides of nitrogen (NO.sub.x) and carbon monoxide (CO) emitted by fossil-fired boilers by the selective introduction of multiple inputs of substances (such as natural gas, ammonia, oil, water-oil emulsion, coal-water slurry and/or urea, and combinations of these substances) above the primary combustion zone of fossil-fired boilers.

Continuous Dissolved Oxygen Measurements and Modelling Metabolism in Peatland Streams

PubMed Central

Dick, Jonathan J.; Soulsby, Chris; Birkel, Christian; Malcolm, Iain; Tetzlaff, Doerthe

2016-01-01

Stream water dissolved oxygen was monitored in a 3.2km2 moorland headwater catchment in the Scottish Highlands. The stream consists of three 1st order headwaters and a 2nd order main stem. The stream network is fringed by peat soils with no riparian trees, though dwarf shrubs provide shading in the lower catchment. Dissolved oxygen (DO) is regulated by the balance between atmospheric re-aeration and the metabolic processes of photosynthesis and respiration. DO was continuously measured for >1 year and the data used to calibrate a mass balance model, to estimate primary production, respiration and re-aeration for a 1st order site and in the 2nd order main stem. Results showed that the stream was always heterotrophic at both sites. Sites were most heterotrophic in the summer reflecting higher levels of stream metabolism. The 1st order stream appeared more heterotrophic which was consistent with the evident greater biomass of macrophytes in the 2nd order stream, with resulting higher primary productivity. Comparison between respiration, primary production, re-aeration and potential physical controls revealed only weak relationships. However, the most basic model parameters (e.g. the parameter linking light and photosynthesis) controlling ecosystem processes resulted in significant differences between the sites which seem related to the stream channel geometry. PMID:27556278

Nutrition in primary health care: using a Delphi process to design new interdisciplinary services.

PubMed

Brauer, Paula; Dietrich, Linda; Davidson, Bridget

2006-01-01

A modified Delphi process was used to identify key features of interdisciplinary nutrition services, including provider roles and responsibilities for Ontario Family Health Networks (FHNs), a family physician-based type of primary care. Twenty-three representatives from interested professional organizations, including three FHN demonstration sites, completed a modified Delphi process. Participants reviewed evidence from a systematic literature review, a patient survey, a costing analysis, and key informant interview results before undertaking the Delphi process. Statements describing various options for services were developed at an in-person meeting, which was followed by two rounds of e-mail questionnaires. Teleconference discussions were held between rounds. An interdisciplinary model with differing and complementary roles for health care providers emerged from the process. Additional key features addressing screening for nutrition problems, health promotion and disease prevention, team collaboration, planning and evaluation, administrative support, access to care, and medical directives/delegated acts were identified. Under the proposed model, the registered dietitian is the team member responsible for managing all aspects of nutrition services, from needs assessment to program delivery, as well as for supporting all providers' nutrition services. The proposed interdisciplinary nutrition services model merits evaluation of cost, effectiveness, applicability, and sustainability in team-based primary care service settings.

Primary healthcare solo practices: homogeneous or heterogeneous?

PubMed

Pineault, Raynald; Borgès Da Silva, Roxane; Provost, Sylvie; Beaulieu, Marie-Dominique; Boivin, Antoine; Couture, Audrey; Prud'homme, Alexandre

2014-01-01

Introduction. Solo practices have generally been viewed as forming a homogeneous group. However, they may differ on many characteristics. The objective of this paper is to identify different forms of solo practice and to determine the extent to which they are associated with patient experience of care. Methods. Two surveys were carried out in two regions of Quebec in 2010: a telephone survey of 9180 respondents from the general population and a postal survey of 606 primary healthcare (PHC) practices. Data from the two surveys were linked through the respondent's usual source of care. A taxonomy of solo practices was constructed (n = 213), using cluster analysis techniques. Bivariate and multilevel analyses were used to determine the relationship of the taxonomy with patient experience of care. Results. Four models were derived from the taxonomy. Practices in the "resourceful networked" model contrast with those of the "resourceless isolated" model to the extent that the experience of care reported by their patients is more favorable. Conclusion. Solo practice is not a homogeneous group. The four models identified have different organizational features and their patients' experience of care also differs. Some models seem to offer a better organizational potential in the context of current reforms.

Shipboard Wireless Sensor Networks Utilizing Zigbee Technology

DTIC Science & Technology

2006-09-01

This thesis studies the feasibility of utilizing Zigbee standard devices to create a shipboard wireless sensor network . Two primary methods were used...the research effort would be a completely wireless sensor network which would result in a net savings in man hours required to maintain and monitor

Predicting bulk permeability using outcrop fracture attributes: The benefits of a Maximum Likelihood Estimator

NASA Astrophysics Data System (ADS)

Rizzo, R. E.; Healy, D.; De Siena, L.

2015-12-01

The success of any model prediction is largely dependent on the accuracy with which its parameters are known. In characterising fracture networks in naturally fractured rocks, the main issues are related with the difficulties in accurately up- and down-scaling the parameters governing the distribution of fracture attributes. Optimal characterisation and analysis of fracture attributes (fracture lengths, apertures, orientations and densities) represents a fundamental step which can aid the estimation of permeability and fluid flow, which are of primary importance in a number of contexts ranging from hydrocarbon production in fractured reservoirs and reservoir stimulation by hydrofracturing, to geothermal energy extraction and deeper Earth systems, such as earthquakes and ocean floor hydrothermal venting. This work focuses on linking fracture data collected directly from outcrops to permeability estimation and fracture network modelling. Outcrop studies can supplement the limited data inherent to natural fractured systems in the subsurface. The study area is a highly fractured upper Miocene biosiliceous mudstone formation cropping out along the coastline north of Santa Cruz (California, USA). These unique outcrops exposes a recently active bitumen-bearing formation representing a geological analogue of a fractured top seal. In order to validate field observations as useful analogues of subsurface reservoirs, we describe a methodology of statistical analysis for more accurate probability distribution of fracture attributes, using Maximum Likelihood Estimators. These procedures aim to understand whether the average permeability of a fracture network can be predicted reducing its uncertainties, and if outcrop measurements of fracture attributes can be used directly to generate statistically identical fracture network models.

Cart'Eaux: an automatic mapping procedure for wastewater networks using machine learning and data mining

NASA Astrophysics Data System (ADS)

Bailly, J. S.; Delenne, C.; Chahinian, N.; Bringay, S.; Commandré, B.; Chaumont, M.; Derras, M.; Deruelle, L.; Roche, M.; Rodriguez, F.; Subsol, G.; Teisseire, M.

2017-12-01

In France, local government institutions must establish a detailed description of wastewater networks. The information should be available, but it remains fragmented (different formats held by different stakeholders) and incomplete. In the "Cart'Eaux" project, a multidisciplinary team, including an industrial partner, develops a global methodology using Machine Learning and Data Mining approaches applied to various types of large data to recover information in the aim of mapping urban sewage systems for hydraulic modelling. Deep-learning is first applied using a Convolution Neural Network to localize manhole covers on 5 cm resolution aerial RGB images. The detected manhole covers are then automatically connected using a tree-shaped graph constrained by industry rules. Based on a Delaunay triangulation, connections are chosen to minimize a cost function depending on pipe length, slope and possible intersection with roads or buildings. A stochastic version of this algorithm is currently being developed to account for positional uncertainty and detection errors, and generate sets of probable networks. As more information is required for hydraulic modeling (slopes, diameters, materials, etc.), text data mining is used to extract network characteristics from data posted on the Web or available through governmental or specific databases. Using an appropriate list of keywords, the web is scoured for documents which are saved in text format. The thematic entities are identified and linked to the surrounding spatial and temporal entities. The methodology is developed and tested on two towns in southern France. The primary results are encouraging: 54% of manhole covers are detected with few false detections, enabling the reconstruction of probable networks. The data mining results are still being investigated. It is clear at this stage that getting numerical values on specific pipes will be challenging. Thus, when no information is found, decision rules will be used to assign admissible numerical values to enable the final hydraulic modelling. Consequently, sensitivity analysis of the hydraulic model will be performed to take into account the uncertainty associated with each piece of information. Project funded by the European Regional Development Fund and the Occitanie Region.

Simplified charge separation energetics in a two-dimensional model for polymer-based photovoltaic cells.

PubMed

Sylvester-Hvid, Kristian O; Ratner, Mark A

2005-01-13

An extension of our two-dimensional working model for photovoltaic behavior in binary polymer and/or molecular photoactive blends is presented. The objective is to provide a more-realistic description of the charge generation and charge separation processes in the blend system. This is achieved by assigning an energy to each of the possible occupation states, describing the system according to a simple energy model for exciton and geminate electron-hole pair configurations. The energy model takes as primary input the ionization potential, electron affinity and optical gap of the components of the blend. The underlying photovoltaic model considers a nanoscopic subvolume of a photoactive blend and represents its p- and n-type domain morphology, in terms of a two-dimensional network of donor and acceptor sites. The nearest-neighbor hopping of charge carriers in the illuminated system is described in terms of transitions between different occupation states. The equations governing the dynamics of these states are cast into a linear master equation, which can be solved for arbitrary two-dimensional donor-acceptor networks, assuming stationary conditions. The implications of incorporating the energy model into the photovoltaic model are illustrated by simulations of the short circuit current versus thickness of the photoactive blend layer for different choices of energy parameters and donor-acceptor topology. The results suggest the existence of an optimal thickness of the photoactive film in bulk heterojunctions, based on kinetic considerations alone, and that this optimal thickness is very sensitive to the choice of energy parameters. The results also indicate space-charge limiting effects for interpenetrating donor-acceptor networks with characteristic domain sizes in the nanometer range and high driving force for the photoinduced electron transfer across the donor-acceptor internal interface.

A User-Centered Approach to Adaptive Hypertext Based on an Information Relevance Model

NASA Technical Reports Server (NTRS)

Mathe, Nathalie; Chen, James

1994-01-01

Rapid and effective to information in large electronic documentation systems can be facilitated if information relevant in an individual user's content can be automatically supplied to this user. However most of this knowledge on contextual relevance is not found within the contents of documents, it is rather established incrementally by users during information access. We propose a new model for interactively learning contextual relevance during information retrieval, and incrementally adapting retrieved information to individual user profiles. The model, called a relevance network, records the relevance of references based on user feedback for specific queries and user profiles. It also generalizes such knowledge to later derive relevant references for similar queries and profiles. The relevance network lets users filter information by context of relevance. Compared to other approaches, it does not require any prior knowledge nor training. More importantly, our approach to adaptivity is user-centered. It facilitates acceptance and understanding by users by giving them shared control over the adaptation without disturbing their primary task. Users easily control when to adapt and when to use the adapted system. Lastly, the model is independent of the particular application used to access information, and supports sharing of adaptations among users.

Developing a response to family violence in primary health care: the New Zealand experience.

PubMed

Gear, Claire; Koziol-McLain, Jane; Wilson, Denise; Clark, Faye

2016-08-20

Despite primary health care being recognised as an ideal setting to effectively respond to those experiencing family violence, responses are not widely integrated as part of routine health care. A lack of evidence testing models and approaches for health sector integration, alongside challenges of transferability and sustainability, means the best approach in responding to family violence is still unknown. The Primary Health Care Family Violence Responsiveness Evaluation Tool was developed as a guide to implement a formal systems-led response to family violence within New Zealand primary health care settings. Given the difficulties integrating effective, sustainable responses to family violence, we share the experience of primary health care sites that embarked on developing a response to family violence, presenting the enablers, barriers and resources required to maintain, progress and sustain family violence response development. In this qualitative descriptive study data were collected from two sources. Firstly semi-structured focus group interviews were conducted during 24-month follow-up evaluation visits of primary health care sites to capture the enablers, barriers and resources required to maintain, progress and sustain a response to family violence. Secondly the outcomes of a group activity to identify response development barriers and implementation strategies were recorded during a network meeting of primary health care professionals interested in family violence prevention and intervention; findings were triangulated across the two data sources. Four sites, representing three PHOs and four general practices participated in the focus group interviews; 35 delegates from across New Zealand attended the network meeting representing a wider perspective on family violence response development within primary health care. Enablers and barriers to developing a family violence response were identified across four themes: 'Getting started', 'Building effective relationships', 'Sourcing funding' and 'Shaping a national approach to family violence'. The strong commitment of key people dedicated to addressing family violence is essential for response sustainability and would be strengthened by prioritising family violence response as a national health target with dedicated resourcing. Further analysis of the health care system as a complex adaptive system may provide insight into effective approaches to response development and health system integration.

Primary care team communication networks, team climate, quality of care, and medical costs for patients with diabetes: A cross-sectional study.

PubMed

Mundt, Marlon P; Agneessens, Filip; Tuan, Wen-Jan; Zakletskaia, Larissa I; Kamnetz, Sandra A; Gilchrist, Valerie J

2016-06-01

Primary care teams play an important role in providing the best quality of care to patients with diabetes. Little evidence is available on how team communication networks and team climate contribute to high quality diabetes care. To determine whether primary care team communication and team climate are associated with health outcomes, health care utilization, and associated costs for patients with diabetes. A cross-sectional survey of primary care team members collected information on frequency of communication with other care team members about patient care and on team climate. Patient outcomes (glycemic, cholesterol, and blood pressure control, urgent care visits, emergency department visits, hospital visit days, medical costs) in the past 12 months for team diabetes patient panels were extracted from the electronic health record. The data were analyzed using nested (clinic/team/patient) generalized linear mixed modeling. 155 health professionals at 6 U.S. primary care clinics participated from May through December 2013. Primary care teams with a greater number of daily face-to-face communication ties among team members were associated with 52% (rate ratio=0.48, 95% CI: 0.22, 0.94) fewer hospital days and US$1220 (95% CI: -US$2416, -US$24) lower health-care costs per team diabetes patient in the past 12 months. In contrast, for each additional registered nurse (RN) who reported frequent daily face-to-face communication about patient care with the primary care practitioner (PCP), team diabetes patients had less-controlled HbA1c (Odds ratio=0.83, 95% CI: 0.66, 0.99), increased hospital days (RR=1.57, 95% CI: 1.10, 2.03), and higher healthcare costs (β=US$877, 95% CI: US$42, US$1713). Shared team vision, a measure of team climate, significantly mediated the relationship between team communication and patient outcomes. Primary care teams which relied on frequent daily face-to-face communication among more team members, and had a single RN communicating patient care information to the PCP, had greater shared team vision, better patient outcomes, and lower medical costs for their diabetes patient panels. Copyright © 2016 Elsevier Ltd. All rights reserved.

Primary care team communication networks, team climate, quality of care, and medical costs for patients with diabetes: A cross-sectional study

PubMed Central

Mundt, Marlon P.; Agneessens, Filip; Tuan, Wen-Jan; Zakletskaia, Larissa I.; Kamnetz, Sandra A.; Gilchrist, Valerie J.

2016-01-01

Background Primary care teams play an important role in providing the best quality of care to patients with diabetes. Little evidence is available on how team communication networks and team climate contribute to high quality diabetes care. Objective To determine whether primary care team communication and team climate are associated with health outcomes, health care utilization, and associated costs for patients with diabetes. Methods A cross-sectional survey of primary care team members collected information on frequency of communication with other care team members about patient care and on team climate. Patient outcomes (glycemic, cholesterol, and blood pressure control, urgent care visits, emergency department visits, hospital visit days, medical costs) in the past 12 months for team diabetes patient panels were extracted from the electronic health record. The data were analyzed using nested (clinic/team/patient) generalized linear mixed modeling. Participants 155 health professionals at 6 U.S. primary care clinics participated from May through December 2013. Results Primary care teams with a greater number of daily face-to-face communication ties among team members were associated with 52% (Rate Ratio=0.48, 95% CI: 0.22, 0.94) fewer hospital days and US$1220 (95% CI: -US$2416, -US$24) lower health-care costs per team diabetes patient in the past 12 months. In contrast, for each additional registered nurse (RN) who reported frequent daily face-to-face communication about patient care with the primary care practitioner (PCP), team diabetes patients had less-controlled HbA1c (Odds Ratio=0.83, 95% CI: 0.66, 0.99), increased hospital days (RR=1.57, 95% CI: 1.10, 2.03), and higher healthcare costs (β=US$877, 95% CI: US$42, US$1713). Shared team vision, a measure of team climate, significantly mediated the relationship between team communication and patient outcomes. Conclusions Primary care teams which relied on frequent daily face-to-face communication among more team members, and had a single RN communicating patient care information to the PCP, had greater shared team vision, better patient outcomes, and lower medical costs for their diabetes patient panels. PMID:27087293

Non-standard s-process in low metallicity massive rotating stars

NASA Astrophysics Data System (ADS)

Frischknecht, U.; Hirschi, R.; Thielemann, F.-K.

2012-02-01

Context. Rotation is known to have a strong impact on the nucleosynthesis of light elements in massive stars, mainly by inducing mixing in radiative zones. In particular, rotation boosts the primary nitrogen production, and models of rotating stars are able to reproduce the nitrogen observed in low-metallicity halo stars. Aims: Here we present the first grid of stellar models for rotating massive stars at low metallicity, where a full s-process network is used to study the impact of rotation-induced mixing on the neutron capture nucleosynthesis of heavy elements. Methods: We used the Geneva stellar evolution code that includes an enlarged reaction network with nuclear species up to bismuth to calculate 25 M⊙ models at three different metallicities (Z = 10-3,10-5, and 10-7) and with different initial rotation rates. Results: First, we confirm that rotation-induced mixing (shear) between the convective H-shell and He-core leads to a large production of primary 22Ne (0.1 to 1% in mass fraction), which is the main neutron source for the s-process in massive stars. Therefore rotation boosts the s-process in massive stars at all metallicities. Second, the neutron-to-seed ratio increases with decreasing Z in models including rotation, which leads to the complete consumption of all iron seeds at metallicities below Z = 10-3 by the end of core He-burning. Thus at low Z, the iron seeds are the main limitation for this boosted s-process. Third, as the metallicity decreases, the production of elements up to the Ba peak increases at the expense of the elements of the Sr peak. We studied the impact of the initial rotation rate and of the highly uncertain 17O(α,γ) rate (which strongly affects the strength of 16O as a neutron poison) on our results. This study shows that rotating models can produce significant amounts of elements up to Ba over a wide range of Z, which has important consequences for our understanding of the formation of these elements in low-metallicity environments like the halo of our galaxy and globular clusters. Fourth, compared to the He-core, the primary 22Ne production induced by rotation in the He-shell is even higher (greater than 1% in mass fraction at all metallicities), which could open the door for an explosive neutron capture nucleosynthesis in the He-shell, with a primary neutron source.

Yeast 5 – an expanded reconstruction of the Saccharomyces cerevisiae metabolic network

PubMed Central

2012-01-01

Background Efforts to improve the computational reconstruction of the Saccharomyces cerevisiae biochemical reaction network and to refine the stoichiometrically constrained metabolic models that can be derived from such a reconstruction have continued since the first stoichiometrically constrained yeast genome scale metabolic model was published in 2003. Continuing this ongoing process, we have constructed an update to the Yeast Consensus Reconstruction, Yeast 5. The Yeast Consensus Reconstruction is a product of efforts to forge a community-based reconstruction emphasizing standards compliance and biochemical accuracy via evidence-based selection of reactions. It draws upon models published by a variety of independent research groups as well as information obtained from biochemical databases and primary literature. Results Yeast 5 refines the biochemical reactions included in the reconstruction, particularly reactions involved in sphingolipid metabolism; updates gene-reaction annotations; and emphasizes the distinction between reconstruction and stoichiometrically constrained model. Although it was not a primary goal, this update also improves the accuracy of model prediction of viability and auxotrophy phenotypes and increases the number of epistatic interactions. This update maintains an emphasis on standards compliance, unambiguous metabolite naming, and computer-readable annotations available through a structured document format. Additionally, we have developed MATLAB scripts to evaluate the model’s predictive accuracy and to demonstrate basic model applications such as simulating aerobic and anaerobic growth. These scripts, which provide an independent tool for evaluating the performance of various stoichiometrically constrained yeast metabolic models using flux balance analysis, are included as Additional files 1, 2 and 3. Conclusions Yeast 5 expands and refines the computational reconstruction of yeast metabolism and improves the predictive accuracy of a stoichiometrically constrained yeast metabolic model. It differs from previous reconstructions and models by emphasizing the distinction between the yeast metabolic reconstruction and the stoichiometrically constrained model, and makes both available as Additional file 4 and Additional file 5 and at http://yeast.sf.net/ as separate systems biology markup language (SBML) files. Through this separation, we intend to make the modeling process more accessible, explicit, transparent, and reproducible. PMID:22663945

A novel framework for command and control of networked sensor systems

NASA Astrophysics Data System (ADS)

Chen, Genshe; Tian, Zhi; Shen, Dan; Blasch, Erik; Pham, Khanh

2007-04-01

In this paper, we have proposed a highly innovative advanced command and control framework for sensor networks used for future Integrated Fire Control (IFC). The primary goal is to enable and enhance target detection, validation, and mitigation for future military operations by graphical game theory and advanced knowledge information fusion infrastructures. The problem is approached by representing distributed sensor and weapon systems as generic warfare resources which must be optimized in order to achieve the operational benefits afforded by enabling a system of systems. This paper addresses the importance of achieving a Network Centric Warfare (NCW) foundation of information superiority-shared, accurate, and timely situational awareness upon which advanced automated management aids for IFC can be built. The approach uses the Data Fusion Information Group (DFIG) Fusion hierarchy of Level 0 through Level 4 to fuse the input data into assessments for the enemy target system threats in a battlespace to which military force is being applied. Compact graph models are employed across all levels of the fusion hierarchy to accomplish integrative data fusion and information flow control, as well as cross-layer sensor management. The functional block at each fusion level will have a set of innovative algorithms that not only exploit the corresponding graph model in a computationally efficient manner, but also permit combined functional experiments across levels by virtue of the unifying graphical model approach.

Toward a Network Model of MHC Class II-Restricted Antigen Processing

PubMed Central

Miller, Michael A.; Ganesan, Asha Purnima V.; Eisenlohr, Laurence C.

2013-01-01

The standard model of Major Histocompatibility Complex class II (MHCII)-restricted antigen processing depicts a straightforward, linear pathway: internalized antigens are converted into peptides that load in a chaperone dependent manner onto nascent MHCII in the late endosome, the complexes subsequently trafficking to the cell surface for recognition by CD4+ T cells (TCD4+). Several variations on this theme, both moderate and radical, have come to light but these alternatives have remained peripheral, the conventional pathway generally presumed to be the primary driver of TCD4+ responses. Here we continue to press for the conceptual repositioning of these alternatives toward the center while proposing that MHCII processing be thought of less in terms of discrete pathways and more in terms of a network whose major and minor conduits are variable depending upon many factors, including the epitope, the nature of the antigen, the source of the antigen, and the identity of the antigen-presenting cell. PMID:24379819

Structural model of homogeneous As–S glasses derived from Raman spectroscopy and high-resolution XPS

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

Golovchak, R.; Shpotyuk, O.; Mccloy, J. S.

2010-11-28

The structure of homogeneous bulk As x S 100- x (25 ≤ x ≤ 42) glasses, prepared by the conventional rocking–melting–quenching method, was investigated using high-resolution X-ray photoelectron spectroscopy (XPS) and Raman spectroscopy. It is shown that the main building blocks of their glass networks are regular AsS 3/2 pyramids and sulfur chains. In the S-rich domain, the existence of quasi-tetrahedral (QT) S = As(S 1/2) 3 units is deduced from XPS data, but with a concentration not exceeding ~3–5% of total atomic sites. Therefore, QT units do not appear as primary building blocks of the glass backbone in thesemore » materials, and an optimally-constrained network may not be an appropriate description for glasses when x < 40. Finally, it is shown that, in contrast to Se-based glasses, the ‘chain-crossing’ model is only partially applicable to sulfide glasses.« less

Questionable assumptions hampered interpretation of a network meta-analysis of primary care depression treatments.

PubMed

Linde, Klaus; Rücker, Gerta; Schneider, Antonius; Kriston, Levente

2016-03-01

We aimed to evaluate the underlying assumptions of a network meta-analysis investigating which depression treatment works best in primary care and to highlight challenges and pitfalls of interpretation under consideration of these assumptions. We reviewed 100 randomized trials investigating pharmacologic and psychological treatments for primary care patients with depression. Network meta-analysis was carried out within a frequentist framework using response to treatment as outcome measure. Transitivity was assessed by epidemiologic judgment based on theoretical and empirical investigation of the distribution of trial characteristics across comparisons. Homogeneity and consistency were investigated by decomposing the Q statistic. There were important clinical and statistically significant differences between "pure" drug trials comparing pharmacologic substances with each other or placebo (63 trials) and trials including a psychological treatment arm (37 trials). Overall network meta-analysis produced results well comparable with separate meta-analyses of drug trials and psychological trials. Although the homogeneity and consistency assumptions were mostly met, we considered the transitivity assumption unjustifiable. An exchange of experience between reviewers and, if possible, some guidance on how reviewers addressing important clinical questions can proceed in situations where important assumptions for valid network meta-analysis are not met would be desirable. Copyright © 2016 Elsevier Inc. All rights reserved.