Agency Fact Sheet, Iowa Communication Network, FY2004

This document produced by the Iowa Department of Administrative Services has been developed to provide a multitude of information about executive branch agencies/department on a single sheet of paper. The facts provides general information, contact information, workforce data, leave and benefits information and affirmative action data.

Agency Fact Sheet, Iowa Communications Network , FY2005

This document produced by the Iowa Department of Administrative Services has been developed to provide a multitude of information about executive branch agencies/department on a single sheet of paper. The facts provides general information, contact information, workforce data, leave and benefits information and affirmative action data.

Agency Fact Sheet, Iowa Commutations Network, FY2006

This document produced by the Iowa Department of Administrative Services has been developed to provide a multitude of information about executive branch agencies/department on a single sheet of paper. The facts provides general information, contact information, workforce data, leave and benefits information and affirmative action data.

Early stage primary bone lymphoma - a retrospective, multicenter rare cancer network (rcn) study

Purpose: Primary bone lymphoma (PBL) accounts for less than 1% of all malignant lymphomas, and 4-5% of all extra-nodal lymphomas. In this study, the disease profile, outcome, and prognostic factors were assessed in patients with stage I and II PBL.Patients and Methods: Thirteen Rare Cancer Network (RCN) institutions enrolled 116 consecutive patients with PBL treated between 1987 and 2008 in this study. Inclusion criteria were age > 16 years, stage I and II, minimum 6 months follow-up and a biopsy-proven confirmation of non-Hodgkin's lymphoma (NHL). Eighty-seven patients underwent chemoradiotherapy (CXRT), 15 radiotherapy (RT) without (13) or with (2) surgery, 14 chemotherapy (CXT) without (9) or with (5) surgery. Median RT dose was 40 Gy (range: 4-60). The median number of CXT cycles was 6 (range: 2-8). Median follow-up was 41 months (range: 6-242).Results: The overall response rate at the end of treatment was 91% (CR 74%, PR 17%). Local recurrence or progression was observed in 12 (10%) patients, and systemic recurrence in 17 (15%). Causes of death included disease progression in 21, unrelated in 5, CXT-related toxicity in 1, and second primary cancer in 2 patients. The 5-yr overall survival (OS), lymphoma-specific survival (LSS), and local control (LC) were 76%, 78% and 92%, respectively. In univariate analyses (log-rank test), favorable prognostic factors for OS were age <50 years (P=0.008), international prognostic index (IPI) score ≤1 (P=0.009), high grade histology (P=0.04), CXRT (P=0.05), CXT (P=0,0004), complete response (CR) (P<0.0001), number of CXT cycles ( ≥6 ) (P=0.01), and RT dose > 40 Gy (P=0.005). All above-mentioned parameters were also significant for LSS except for age and number of chemotherapy cycles. For LC, only CR and stage I were favorable factors. In multivariate analysis, IPI score, RT dose, complete response, and chemotherapy were independently influencing the outcome (OS and LSS). Complete response at the end of treatment was the only predicting factor for LC. Six patients developed grade 3 or more toxicities, according to Common Terminology Criteria for Adverse Events (CTCAE) V3.0.Conclusion: This large multicenter study confirms the relatively good prognosis of early stage PBL treated with combined CXRT. Local control was excellent, while systemic failures were rare. An adequate dose of RT (40 Gy or more) and complete CXT regime (≥ 6 cycles) were associated with better outcome.

Multitask learning of environmental spatial data

The present research deals with an application of artificial neural networks for multitask learning from spatial environmental data. The real case study (sediments contamination of Geneva Lake) consists of 8 pollutants. There are different relationships between these variables, from linear correlations to strong nonlinear dependencies. The main idea is to construct a subsets of pollutants which can be efficiently modeled together within the multitask framework. The proposed two-step approach is based on: 1) the criterion of nonlinear predictability of each variable ?k? by analyzing all possible models composed from the rest of the variables by using a General Regression Neural Network (GRNN) as a model; 2) a multitask learning of the best model using multilayer perceptron and spatial predictions. The results of the study are analyzed using both machine learning and geostatistical tools.

Optimal network topologies for local search with congestion

The problem of searchability in decentralized complex networks is of great importance in computer science, economy, and sociology. We present a formalism that is able to cope simultaneously with the problem of search and the congestion effects that arise when parallel searches are performed, and we obtain expressions for the average search cost both in the presence and the absence of congestion. This formalism is used to obtain optimal network structures for a system using a local search algorithm. It is found that only two classes of networks can be optimal: starlike configurations, when the number of parallel searches is small, and homogeneous-isotropic configurations, when it is large.

Comparing the artificial neural network with parcial least squares for prediction of soil organic carbon and pH at different moisture content levels using visible and near-infrared spectroscopy

Visible and near infrared (vis-NIR) spectroscopy is widely used to detect soil properties. The objective of this study is to evaluate the combined effect of moisture content (MC) and the modeling algorithm on prediction of soil organic carbon (SOC) and pH. Partial least squares (PLS) and the Artificial neural network (ANN) for modeling of SOC and pH at different MC levels were compared in terms of efficiency in prediction of regression. A total of 270 soil samples were used. Before spectral measurement, dry soil samples were weighed to determine the amount of water to be added by weight to achieve the specified gravimetric MC levels of 5, 10, 15, 20, and 25 %. A fiber-optic vis-NIR spectrophotometer (350-2500 nm) was used to measure spectra of soil samples in the diffuse reflectance mode. Spectra preprocessing and PLS regression were carried using Unscrambler® software. Statistica® software was used for ANN modeling. The best prediction result for SOC was obtained using the ANN (RMSEP = 0.82 % and RPD = 4.23) for soil samples with 25 % MC. The best prediction results for pH were obtained with PLS for dry soil samples (RMSEP = 0.65 % and RPD = 1.68) and soil samples with 10 % MC (RMSEP = 0.61 % and RPD = 1.71). Whereas the ANN showed better performance for SOC prediction at all MC levels, PLS showed better predictive accuracy of pH at all MC levels except for 25 % MC. Therefore, based on the data set used in the current study, the ANN is recommended for the analyses of SOC at all MC levels, whereas PLS is recommended for the analysis of pH at MC levels below 20 %.

Self-similar community structure in a network of human interactions

We propose a procedure for analyzing and characterizing complex networks. We apply this to the social network as constructed from email communications within a medium sized university with about 1700 employees. Email networks provide an accurate and nonintrusive description of the flow of information within human organizations. Our results reveal the self-organization of the network into a state where the distribution of community sizes is self-similar. This suggests that a universal mechanism, responsible for emergence of scaling in other self-organized complex systems, as, for instance, river networks, could also be the underlying driving force in the formation and evolution of social networks.

Hierarchical neural network with high storage capacity

A recent method used to optimize biased neural networks with low levels of activity is applied to a hierarchical model. As a consequence, the performance of the system is strongly enhanced. The steps to achieve optimization are analyzed in detail.

Modelling diffusion of innovations in a social network

A simple model of diffusion of innovations in a social network with upgrading costs is introduced. Agents are characterized by a single real variable, their technological level. According to local information, agents decide whether to upgrade their level or not, balancing their possible benefit with the upgrading cost. A critical point where technological avalanches display a power-law behavior is also found. This critical point is characterized by a macroscopic observable that turns out to optimize technological growth in the stationary state. Analytical results supporting our findings are found for the globally coupled case.

Exact long-time behavior of a network of oscillators under random fields

We present an exact solution for the order parameters that characterize the stationary behavior of a population of Kuramotos phase oscillators under random external fields [Y. Kuramoto, in International Symposium on Mathematical Problems in Theoretical Physics, Lecture Notes in Physics, Vol. 39 (Springer, Berlin, 1975), p. 420]. From these results it is possible to generate the phase diagram of models with an arbitrary distribution of random frequencies and random fields.

Remote Synchronization Reveals Network Symmetries and Functional Modules

We study a Kuramoto model in which the oscillators are associated with the nodes of a complex network and the interactions include a phase frustration, thus preventing full synchronization. The system organizes into a regime of remote synchronization where pairs of nodes with the same network symmetry are fully synchronized, despite their distance on the graph. We provide analytical arguments to explain this result, and we show how the frustration parameter affects the distribution of phases. An application to brain networks suggests that anatomical symmetry plays a role in neural synchronization by determining correlated functional modules across distant locations.

Midwest Transportation Consortium Annual Report, 2004-2005

The Midwest Transportation Consortium (MTC) recently completed its sixth year of operation. The MTC has become an established portion of the research and educational programs at ISU and its partner universities. The MTC continues to emphasize its primary focus of developing human capital. For example, this semester, Fall, 2005, ISU has graduate scholars in its educational program. However, we also recognize that the federal grant is an opportunity to build programs at our respective universities that continue after the U.S. DOT UTCP may end. An example of building a long lasting program is the University of Missouri – St. Louis’ (UMSL) and its development of a transportation Ph.D. program in their business college. Admittedly, this program could have been started regardless, but Dr. Ray Mundy, Director of UMSL’s Transportation Scholars Program, believes that the MTC support of the transportation educational program at UMSL was the essential component in establishing a Ph.D. program. At ISU, the MTC has been instrumental in establishing two research and outreach programs, and both have themes that are related to the MTC’s theme of “Transportation System Management and Operation.” The Center for Weather Impacts on Mobility and Safety (C-WIMS) was recently established, and the Center for Road Infrastructure Management and Operations (RIMO) is in the process of being established. The MTC has a critical role in establishing each of these two programs. As part of the on-going MTC program, we have established an effective network that promotes the education of future transportation professionals and the development of new knowledge on how to manage transportation infrastructure and services in a more sustainable manner. The MTC has a track record of developing outstanding students; these students are now becoming leaders in the private sector, government, and academia. The MTC has also supported the development of an extensive research portfolio related to sustainable transportation asset management. More research projects are in the pipeline. Finally, the MTC has dedicated itself to the dissemination of asset management research results through an ongoing technology transfer program. This document provides a progress for the latest fiscal year of operation of the MTC, which ran from October 2004 through September 2005.