989 resultados para Network tariffs allocation
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Agency Performance Report
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Agency Performance Plan, Iowa Communications Network
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Agency Performance Plan, Iowa Communications Network
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This report outlines the strategic plan for Iowa Communications Network, goals and mission.
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Despite recent medical progresses in patient support, the mortality of sepsis remains high. Recently, new supporting strategies were proposed to improve outcome. Whereas such strategies are currently considered as standard of care, their real impact on mortality, morbidity, length of stay, and hence, health care resources utilization has been only weakly evaluated so far. Obviously, there is a critical need for epidemiologic surveys of sepsis to better address these major issues. The Lausanne Cohort of septic patients aims at building a large clinical, biological and microbiological database that will be used as a multidisciplinary research platform to study the various pathogenic mechanisms of sepsis in collaboration with the various specialists. This could be an opportunity to strengthen the collaboration within the Swiss Latin network of Intensive Care Medicine.
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A survey was sent to over 200 Federal, State, and local agencies that might use streamflow data collected by the U. S. Geological Survey in Iowa. A total of 181 forms were returned and 112 agencies indicated that they use streamflow data. The responses show that streamflow data from the Iowa USGS stream-gaging network, which in 1996 is composed of 117 stations, are used by many agencies for many purposes and that many stations provide streamflow data that fulfill a variety of joint purposes. The median number of respondents per station that use data from the station was 6 and the median number of data-use categories indicated per station was 9. The survey results can be used by agencies that fund the Iowa USGS stream-gaging network to help them decide which stations to continue to support if it becomes necessary to reduce the size of the stream-gaging network.
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ABSTRACT : A firm's competitive advantage can arise from internal resources as well as from an interfirm network. -This dissertation investigates the competitive advantage of a firm involved in an innovation network by integrating strategic management theory and social network theory. It develops theory and provides empirical evidence that illustrates how a networked firm enables the network value and appropriates this value in an optimal way according to its strategic purpose. The four inter-related essays in this dissertation provide a framework that sheds light on the extraction of value from an innovation network by managing and designing the network in a proactive manner. The first essay reviews research in social network theory and knowledge transfer management, and identifies the crucial factors of innovation network configuration for a firm's learning performance or innovation output. The findings suggest that network structure, network relationship, and network position all impact on a firm's performance. Although the previous literature indicates that there are disagreements about the impact of dense or spare structure, as well as strong or weak ties, case evidence from Chinese software companies reveals that dense and strong connections with partners are positively associated with firms' performance. The second essay is a theoretical essay that illustrates the limitations of social network theory for explaining the source of network value and offers a new theoretical model that applies resource-based view to network environments. It suggests that network configurations, such as network structure, network relationship and network position, can be considered important network resources. In addition, this essay introduces the concept of network capability, and suggests that four types of network capabilities play an important role in unlocking the potential value of network resources and determining the distribution of network rents between partners. This essay also highlights the contingent effects of network capability on a firm's innovation output, and explains how the different impacts of network capability depend on a firm's strategic choices. This new theoretical model has been pre-tested with a case study of China software industry, which enhances the internal validity of this theory. The third essay addresses the questions of what impact network capability has on firm innovation performance and what are the antecedent factors of network capability. This essay employs a structural equation modelling methodology that uses a sample of 211 Chinese Hi-tech firms. It develops a measurement of network capability and reveals that networked firms deal with cooperation between, and coordination with partners on different levels according to their levels of network capability. The empirical results also suggests that IT maturity, the openness of culture, management system involved, and experience with network activities are antecedents of network capabilities. Furthermore, the two-group analysis of the role of international partner(s) shows that when there is a culture and norm gap between foreign partners, a firm must mobilize more resources and effort to improve its performance with respect to its innovation network. The fourth essay addresses the way in which network capabilities influence firm innovation performance. By using hierarchical multiple regression with data from Chinese Hi-tech firms, the findings suggest that there is a significant partial mediating effect of knowledge transfer on the relationships between network capabilities and innovation performance. The findings also reveal that the impacts of network capabilities divert with the environment and strategic decision the firm has made: exploration or exploitation. Network constructing capability provides a greater positive impact on and yields more contributions to innovation performance than does network operating capability in an exploration network. Network operating capability is more important than network constructing capability for innovative firms in an exploitation network. Therefore, these findings highlight that the firm can shape the innovation network proactively for better benefits, but when it does so, it should adjust its focus and change its efforts in accordance with its innovation purposes or strategic orientation.
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Ipomoea asarifolia (Desr.) Roem. & Schultz (Convolvulaceae) and Stachytarpheta cayennensis (Rich) Vahl. (Verbenaceae), two weeds found in pastures and crop areas in Brazilian Amazonia, were grown in controlled environment cabinets under high (800-1000 µmol m-² s-¹) and low (200-350 µmol m-² s-¹) light regimes during a 40-day period. For both species leaf dry mass and leaf area per total plant dry mass, and leaf area per leaf dry mass were higher for low-light plants, whereas root mass per total plant dry mass was higher for high-light plants. High-light S. cayennensis allocated significantly more biomass to reproductive tissue than low-light plants, suggesting a probably lower ability of this species to maintain itself under shaded conditions. Relative growth rate (RGR) in I. asarifolia was initially higher for high-light grown plants and after 20 days started decreasing, becoming similar to low-light plants at the last two harvests (at 30 and 40 days). In S. cayennensis, RGR was also higher for high-light plants; however, this trend was not significant at the first and last harvest dates (10 and 40 days). These results are discussed in relation to their ecological and weed management implications.
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How have changes in communications technology affected the way that misinformation spreads through a population and persists? To what extent do differences in the architecture of social networks affect the spread of misinformation, relative to the rates and rules by which individuals transmit or eliminate different pieces of information (cultural traits)? Here, we use analytical models and individual-based simulations to study how a 'cultural load' of misinformation can be maintained in a population under a balance between social transmission and selective elimination of cultural traits with low intrinsic value. While considerable research has explored how network architecture affects percolation processes, we find that the relative rates at which individuals transmit or eliminate traits can have much more profound impacts on the cultural load than differences in network architecture. In particular, the cultural load is insensitive to correlations between an individual's network degree and rate of elimination when these quantities vary among individuals. Taken together, these results suggest that changes in communications technology may have influenced cultural evolution more strongly through changes in the amount of information flow, rather than the details of who is connected to whom.
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Plants such as Arabidopsis thaliana respond to foliar shade and neighbors who may become competitors for light resources by elongation growth to secure access to unfiltered sunlight. Challenges faced during this shade avoidance response (SAR) are different under a light-absorbing canopy and during neighbor detection where light remains abundant. In both situations, elongation growth depends on auxin and transcription factors of the phytochrome interacting factor (PIF) class. Using a computational modeling approach to study the SAR regulatory network, we identify and experimentally validate a previously unidentified role for long hypocotyl in far red 1, a negative regulator of the PIFs. Moreover, we find that during neighbor detection, growth is promoted primarily by the production of auxin. In contrast, in true shade, the system operates with less auxin but with an increased sensitivity to the hormonal signal. Our data suggest that this latter signal is less robust, which may reflect a cost-to-robustness tradeoff, a system trait long recognized by engineers and forming the basis of information theory.
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BACKGROUND: Mammary adenoid cystic carcinoma (ACC) is a rare breast cancer. The aim of this retrospective study was to assess prognostic factors and patterns of failure, as well as the role of radiation therapy (RT), in ACC.¦METHODS: Between January 1980 and December 2007, 61 women with breast ACC were treated at participating centers of the Rare Cancer Network. Surgery consisted of lumpectomy in 41 patients and mastectomy in 20 patients. There were 51(84%) stage pN0 and 10 stage cN0 (16%) patients. Postoperative RT was administered to 40 patients (35 after lumpectomy, 5 after mastectomy).¦RESULTS: With a median follow-up of 79 months (range, 6-285), 5-year overall and disease-free survival rates were 94% (95% confidence interval [CI], 88%-100%) and 82% (95% CI, 71%-93%), respectively. The 5-year locoregional control (LRC) rate was 95% (95% CI, 89%-100%). Axillary lymph node dissection or sentinel node biopsy was performed in 84% of cases. All patients had stage pN0 disease. In univariate analysis, survival was not influenced by the type of surgery or the use of postoperative RT. The 5-year LRC rate was 100% in the mastectomy group versus 93% (95% CI, 83%-100%) in the breast-conserving surgery group, respectively (p = 0.16). For the breast-conserving surgery group, the use of RT significantly correlated with LRC (p = 0.03); the 5-year LRC rates were 95% (95% CI, 86%-100%) for the RT group versus 83% (95% CI, 54%-100%) for the group receiving no RT. No local failures occurred in patients with positive margins, all of whom received postoperative RT.¦CONCLUSION: Breast-conserving surgery is the treatment of choice for patients with ACC breast cancer. Axillary lymph node dissection or sentinel node biopsy might not be recommended. Postoperative RT should be proposed in the case of breast-conserving surgery.
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The growth and biomass allocation responses of the tropical forage grasses Brachiaria brizantha cv. Marandu and B. humidicola were compared for plants grown outdoors, in pots, in full sunlight and those shaded to 30% of full sunlight over a 30day period. The objective was to evaluate the acclimation capacity of these species to low light. Both species were able to quickly develop phenotypic adjustments in response to low light. Specific leaf area and leaf area ratio were higher for low-light plants during the entire experimental period. Low-light plants allocated significantly less biomass to root and more to leaf tissue than high-light plants. However, the biomass allocation pattern to culms was different for the two species under low light: it increased in B. brizantha, but decreased in B. humidicola, probably as a reflection of the growth habits of these species. Relative growth rate and tillering were higher in high-light plants. Leaf elongation rate was significantly increased on both species under low light; however, the difference between treatments was higher in B. brizantha. These results are discussed in relation to the pasture management implications.
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Introduction: The field of Connectomic research is growing rapidly, resulting from methodological advances in structural neuroimaging on many spatial scales. Especially progress in Diffusion MRI data acquisition and processing made available macroscopic structural connectivity maps in vivo through Connectome Mapping Pipelines (Hagmann et al, 2008) into so-called Connectomes (Hagmann 2005, Sporns et al, 2005). They exhibit both spatial and topological information that constrain functional imaging studies and are relevant in their interpretation. The need for a special-purpose software tool for both clinical researchers and neuroscientists to support investigations of such connectome data has grown. Methods: We developed the ConnectomeViewer, a powerful, extensible software tool for visualization and analysis in connectomic research. It uses the novel defined container-like Connectome File Format, specifying networks (GraphML), surfaces (Gifti), volumes (Nifti), track data (TrackVis) and metadata. Usage of Python as programming language allows it to by cross-platform and have access to a multitude of scientific libraries. Results: Using a flexible plugin architecture, it is possible to enhance functionality for specific purposes easily. Following features are already implemented: * Ready usage of libraries, e.g. for complex network analysis (NetworkX) and data plotting (Matplotlib). More brain connectivity measures will be implemented in a future release (Rubinov et al, 2009). * 3D View of networks with node positioning based on corresponding ROI surface patch. Other layouts possible. * Picking functionality to select nodes, select edges, get more node information (ConnectomeWiki), toggle surface representations * Interactive thresholding and modality selection of edge properties using filters * Arbitrary metadata can be stored for networks, thereby allowing e.g. group-based analysis or meta-analysis. * Python Shell for scripting. Application data is exposed and can be modified or used for further post-processing. * Visualization pipelines using filters and modules can be composed with Mayavi (Ramachandran et al, 2008). * Interface to TrackVis to visualize track data. Selected nodes are converted to ROIs for fiber filtering The Connectome Mapping Pipeline (Hagmann et al, 2008) processed 20 healthy subjects into an average Connectome dataset. The Figures show the ConnectomeViewer user interface using this dataset. Connections are shown that occur in all 20 subjects. The dataset is freely available from the homepage (connectomeviewer.org). Conclusions: The ConnectomeViewer is a cross-platform, open-source software tool that provides extensive visualization and analysis capabilities for connectomic research. It has a modular architecture, integrates relevant datatypes and is completely scriptable. Visit www.connectomics.org to get involved as user or developer.
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Highway maintenance engineers and administrators are often confronted with a number of problems related to highway maintenance work programs. One of these problems is concerned with determining the optimum number and locations of highway maintenance garages in a given area. Serious decline in highway revenues and a high inflation rate have made it necessary to examine existing maintenance practices and to allocate reduced financial resources more effectively and efficiently. Searching for and providing of reasonable solutions to these problems is the focus of this research project. The methodology used is to identify and modify for use (if necessary) those models which have already been developed. Models which could give optimum number and locations of highway maintenance garages were found to be too theoretical and/or practically infeasible. Consequently, research focus was shifted from these models to other models that could compare alternatives and select the best among these alternatives. Three such models -- the Alabama model, California model, and Louisiana model, were identified and studied.