Iowa Communications Network Performance Report, FY2010

Agency Performance Report

Iowa Communications Network Performance Report, FY2011

Agency Performance Report

Iowa Communications Network Performance Report, FY2011

Agency Performance Report

Iowa Communications Network Performance Plan, FY 2013

Agency Performance Plan, Iowa Communications Network

Iowa Communications Network Performance Plan, FY2014

Agency Performance Plan, Iowa Communications Network

Iowa Communications Network, Strategic Plan, 2012

This report outlines the strategic plan for Iowa Communications Network, goals and mission.

La cohorte sepsis lausannoise: une opportunité de développer la recherche dans le Réseau latin de médecine intensive [Lausanne Cohort of septic patients as an opportunity to develop multidisciplinary research within the Swiss Latin Network of Intensive Care Medicine]

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.

Survey of Users of the USGS Stream-Gaging Network in Iowa, 1996, HR-383, 1996

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.

Firm's network capability and innovation performance: evidences from China hi-tech industry

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.

Social network architecture and the maintenance of deleterious cultural traits.

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.

Light intensity modulates the regulatory network of the shade avoidance response in Arabidopsis.

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.

Management of adenoid cystic carcinoma of the breast: a Rare Cancer Network study.

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.

ConnectomeViewer - Multi-Modal Multi-Level Network Visualization and Analysis.

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.

Generation of biological association networks: A novel strategy to detect new targets in cancer therapy

The aim of this work was to design a novel strategy to detect new targets for anticancer treatments. The rationale was to build Biological Association Networks from differentially expressed genes in drug-resistant cells to identify important nodes within the Networks. These nodes may represent putative targets to attack in cancer therapy, as a way to destabilize the gene network developed by the resistant cells to escape from the drug pressure. As a model we used cells resistant to methotrexate (MTX), an inhibitor of DHFR. Selected node-genes were analyzed at the transcriptional level and from a genotypic point of view. In colon cancer cells, DHFR, the AKR1 family, PKC¿, S100A4, DKK1, and CAV1 were overexpressed while E-cadherin was lost. In breast cancer cells, the UGT1A family was overexpressed, whereas EEF1A1 was overexpressed in pancreatic cells. Interference RNAs directed against these targets sensitized cells towards MTX.

Occurrence of patulin in organic and conventional apple juice. Risk assessment

Organic foods are promoted as environmentally friendly and its consumption has become increasingly popular. Nevertheless,organic farming practices could produce commodities more susceptible to fungal attack and as a result, food with higher levels of mycotoxins. Patulin is a mycotoxin mainly present in apples and apple-based products. In this paper, we report our recent results and an update of the patulin occurrence and their risk in conventional and organic apple juices around Europe.