Iowa Communications Network - Fiscal Year 2012 Annual Report

The Iowa Communications Network (ICN) is the country’s premier distance learning and state government Network, committed to providing Iowans with convenient, equal access to education, government and healthcare. The Network makes it possible for Iowans, physically separated by location, to interact in an efficient, creative, and cost-effective manner. ICN provides high-speed Internet, data, video conferencing, and voice (phone) services to authorized users, under Code of Iowa, which includes: K-12 schools, higher education, hospitals, state and federal government, National Guard armories, and libraries.

Measuring conduct and cost parameters in the Spanish air transport market

This paper estimates a model of airline competition for the Spanish air transport market. I test the explanatory power of alternative oligopoly models with capacity constraints. In addition, I analyse the degree of density economies. Results show that Spanish airlines conduct follows a price-leadership scheme so that it is less competitive than the Cournot solution. I also find evidence that thin routes can be considered as natural monopolies

Dispersal routes reconstruction and the minimum cost arborescence problem.

We show that the dispersal routes reconstruction problem can be stated as an instance of a graph theoretical problem known as the minimum cost arborescence problem, for which there exist efficient algorithms. Furthermore, we derive some theoretical results, in a simplified setting, on the possible optimal values that can be obtained for this problem. With this, we place the dispersal routes reconstruction problem on solid theoretical grounds, establishing it as a tractable problem that also lends itself to formal mathematical and computational analysis. Finally, we present an insightful example of how this framework can be applied to real data. We propose that our computational method can be used to define the most parsimonious dispersal (or invasion) scenarios, which can then be tested using complementary methods such as genetic analysis.

Cost-effectiveness analysis of a European primary-care physician training in smoking cessation counseling.

BACKGROUND: Physician training in smoking cessation counseling has been shown to be effective as a means to increase quit success. We assessed the cost-effectiveness ratio of a smoking cessation counseling training programme. Its effectiveness was previously demonstrated in a cluster randomized, control trial performed in two Swiss university outpatients clinics, in which residents were randomized to receive training in smoking interventions or a control educational intervention. DESIGN AND METHODS: We used a Markov simulation model for effectiveness analysis. This model incorporates the intervention efficacy, the natural quit rate, and the lifetime probability of relapse after 1-year abstinence. We used previously published results in addition to hospital service and outpatient clinic cost data. The time horizon was 1 year, and we opted for a third-party payer perspective. RESULTS: The incremental cost of the intervention amounted to US$2.58 per consultation by a smoker, translating into a cost per life-year saved of US$25.4 for men and 35.2 for women. One-way sensitivity analyses yielded a range of US$4.0-107.1 in men and US$9.7-148.6 in women. Variations in the quit rate of the control intervention, the length of training effectiveness, and the discount rate yielded moderately large effects on the outcome. Variations in the natural cessation rate, the lifetime probability of relapse, the cost of physician training, the counseling time, the cost per hour of physician time, and the cost of the booklets had little effect on the cost-effectiveness ratio. CONCLUSIONS: Training residents in smoking cessation counseling is a very cost-effective intervention and may be more efficient than currently accepted tobacco control interventions.

Iowa Plan for Brain Injury, 2007-2010

Traumatic Brain Injury (TBI) impacts the lives of thousands of Iowans every year. TBI has been described as the “Silent Epidemic” because so often the scars are not visible to others. The affects of brain injury are cognitive, emotional, social, and can result in physical disability. In addition to the overwhelming challenges individuals with brain injury experience, families also face many difficulties in dealing with their loved one’s injury, and in navigating a service delivery system that can be confusing and frustrating. In 1998, the Iowa Department of Public Health (IDPH) conducted a comprehensive statewide needs assessment of brain injury in Iowa. This assessment led to the development of the first Iowa Plan for Brain Injury, “Coming Into Focus.” An updated state plan, the Iowa Plan for Brain Injuries 2002 – 2005, was developed, which reported on progress of the previous state plan, and outlined gaps in service delivery in Iowa. Four areas of focus were identified by the State Plan for Brain Injuries Task Force that included: 1) Expanding the Iowa Brain Injury Resource Network (IBIRN); 2) Promoting a Legislative and Policy Agenda, While Increasing Legislative Strength; 3) Enhancing Data Collection; and, 4) Increasing Funding. The IDPH utilized “Coming Into Focus” as the framework for an application to the federal TBI State Grant Program, which has resulted in more than $900,000 for plan implementation. Iowa continues to receive grant dollars through the TBI State Grant Program, which focuses on increasing capacity to serve Iowans with brain injury and their families. Highlighting the success of this grant project, in 2007 the IDPH received the federal TBI Program’s “Impacting Systems Change” Award. The Iowa Brain Injury Resource Network (IBIRN) is the product of nine years of TBI State Grant Program funding. The IBIRN was developed to ensure that Iowans got the information and support they needed after a loved one sustained a TBI. It consists of a hospital and service provider pre-discharge information and service linkage process, a resource facilitation program, a peer-to-peer volunteer support network, and a service provider training and technical assistance program. Currently over 90 public and private partners work with the IDPH and the Brain Injury Association of Iowa (BIA-IA) to administer the IBIRN system and ensure that families have a relevant and reliable location to turn for information and support. Further success was accomplished in 2006 when the Iowa legislature created the Brain Injury Services Program within the IDPH. This program consists of four components focusing on increasing access to services and improving the effectiveness of services available to individuals with TBI and their families, including: 1) HCBS Brain Injury Waiver-Eligible Component; 2) Cost Share Component; 3) Neuro-Resource Facilitation; and, 4) Enhanced Training. The Iowa legislature appropriated $2.4 million to the Brain Injury Services Program in state fiscal year (SFY) 2007, and increased that amount to $3.9 million in SFY 2008. The Cost Share Component models the HCBS Brain Injury Waiver menu of services but is available for Iowans who do not qualify functionally or financially for the Waiver. In addition, the Neuro-Resource Facilitation program links individuals with brain injury and their families to needed supports and services. The Iowa Plan for Brain Injury highlights the continued need for serving individuals with brain injury and their families. Additionally, the Plan outlines the paths of prevention and services, which will expand the current system and direct efforts into the future.

Monitoring network optimisation for spatial data classification using support vector machines

The paper presents a novel method for monitoring network optimisation, based on a recent machine learning technique known as support vector machine. It is problem-oriented in the sense that it directly answers the question of whether the advised spatial location is important for the classification model. The method can be used to increase the accuracy of classification models by taking a small number of additional measurements. Traditionally, network optimisation is performed by means of the analysis of the kriging variances. The comparison of the method with the traditional approach is presented on a real case study with climate data.

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.

Stochastic models and numerical algorithms for a class of regulatory gene networks.

Regulatory gene networks contain generic modules, like those involving feedback loops, which are essential for the regulation of many biological functions (Guido et al. in Nature 439:856-860, 2006). We consider a class of self-regulated genes which are the building blocks of many regulatory gene networks, and study the steady-state distribution of the associated Gillespie algorithm by providing efficient numerical algorithms. We also study a regulatory gene network of interest in gene therapy, using mean-field models with time delays. Convergence of the related time-nonhomogeneous Markov chain is established for a class of linear catalytic networks with feedback loops.

On the tractability of the piecewise-linear approximation for general discrete-choice network revenue management

The choice network revenue management (RM) model incorporates customer purchase behavioras customers purchasing products with certain probabilities that are a function of the offeredassortment of products, and is the appropriate model for airline and hotel network revenuemanagement, dynamic sales of bundles, and dynamic assortment optimization. The underlyingstochastic dynamic program is intractable and even its certainty-equivalence approximation, inthe form of a linear program called Choice Deterministic Linear Program (CDLP) is difficultto solve in most cases. The separation problem for CDLP is NP-complete for MNL with justtwo segments when their consideration sets overlap; the affine approximation of the dynamicprogram is NP-complete for even a single-segment MNL. This is in contrast to the independentclass(perfect-segmentation) case where even the piecewise-linear approximation has been shownto be tractable. In this paper we investigate the piecewise-linear approximation for network RMunder a general discrete-choice model of demand. We show that the gap between the CDLP andthe piecewise-linear bounds is within a factor of at most 2. We then show that the piecewiselinearapproximation is polynomially-time solvable for a fixed consideration set size, bringing itinto the realm of tractability for small consideration sets; small consideration sets are a reasonablemodeling tradeoff in many practical applications. Our solution relies on showing that forany discrete-choice model the separation problem for the linear program of the piecewise-linearapproximation can be solved exactly by a Lagrangian relaxation. We give modeling extensionsand show by numerical experiments the improvements from using piecewise-linear approximationfunctions.

Estabilitzador de tensió, a partir d'una reactància de nucli saturable

Actualment hi ha una gran varietat de marques i models d'estabilitzadors de tensió, tot i que tots estan dissenyats i construïts amb el mateix propòsit, entregar una tensió estable a la sortida del dispositiu. La raó per la que es fabriquen estabilitzadors de tensió, es basa en el fet que, tot i amb els avenços tècnics i millores dels serveis de l'àrea energètica, no s'han pogut eliminar les freqüents caigudes o pujades de tensió en les xarxes d'alimentació d'energia elèctrica, fet que pot ocasionar errors en el funcionament dels equips electrònics. És per això que la majoria d'usuaris d'equips electrònics interposen un estabilitzador de tensió entre la línea d'alimentació dels seus aparells. L'objectiu del treball és realitzar la construcció d'un dispositiu de tres bobines amb un nucli ferromagnètic per a dur a terme la funció d'estabilitzador de tensió alterna. Mitjançant la tècnica de reluctància de nucli saturable i aplicant-la en aquest cas pràctic, es vol aconseguir desenvolupar un estabilitzador de tensió fiable i econòmic. Aquest treball ha d'aportar una solució en entorns de treball, entre altres, on s'utilitzen màquines d'alimentació alternes que siguin molt sensibles a les variacions de tensió de la xarxa i que, a més a més, no suposi una despesa molt elevada.

Information sharing and social network dynamics : a coevolutionary approach

The capacity to interact socially and share information underlies the success of many animal species, humans included. Researchers of many fields have emphasized the evo¬lutionary significance of how patterns of connections between individuals, or the social networks, and learning abilities affect the information obtained by animal societies. To date, studies have focused on the dynamics either of social networks, or of the spread of information. The present work aims to study them together. We make use of mathematical and computational models to study the dynamics of networks, where social learning and information sharing affect the structure of the population the individuals belong to. The number and strength of the relationships between individuals, in turn, impact the accessibility and the diffusion of the shared information. Moreover, we inves¬tigate how different strategies in the evaluation and choice of interacting partners impact the processes of knowledge acquisition and social structure rearrangement. First, we look at how different evaluations of social interactions affect the availability of the information and the network topology. We compare a first case, where individuals evaluate social exchanges by the amount of information that can be shared by the partner, with a second case, where they evaluate interactions by considering their partners' social status. We show that, even if both strategies take into account the knowledge endowments of the partners, they have very different effects on the system. In particular, we find that the first case generally enables individuals to accumulate higher amounts of information, thanks to the more efficient patterns of social connections they are able to build. Then, we study the effects that homophily, or the tendency to interact with similar partners, has on knowledge accumulation and social structure. We compare the case where individuals who know the same information are more likely to learn socially from each other, to the opposite case, where individuals who know different information are instead more likely to learn socially from each other. We find that it is not trivial to claim which strategy is better than the other. Depending on the possibility of forgetting information, the way new social partners can be chosen, and the population size, we delineate the conditions for which each strategy allows accumulating more information, or in a faster way For these conditions, we also discuss the topological characteristics of the resulting social structure, relating them to the information dynamics outcome. In conclusion, this work paves the road for modeling the joint dynamics of the spread of information among individuals and their social interactions. It also provides a formal framework to study jointly the effects of different strategies in the choice of partners on social structure, and how they favor the accumulation of knowledge in the population. - La capacité d'interagir socialement et de partager des informations est à la base de la réussite de nombreuses espèces animales, y compris les humains. Les chercheurs de nombreux domaines ont souligné l'importance évolutive de la façon dont les modes de connexions entre individus, ou réseaux sociaux et les capacités d'apprentissage affectent les informations obtenues par les sociétés animales. À ce jour, les études se sont concentrées sur la dynamique soit des réseaux sociaux, soit de la diffusion de l'information. Le présent travail a pour but de les étudier ensemble. Nous utilisons des modèles mathématiques et informatiques pour étudier la dynamique des réseaux, où l'apprentissage social et le partage d'information affectent la structure de la population à laquelle les individus appartiennent. Le nombre et la solidité des relations entre les individus ont à leurs tours un impact sur l'accessibilité et la diffusion de l'informa¬tion partagée. Par ailleurs, nous étudions comment les différentes stratégies d'évaluation et de choix des partenaires d'interaction ont une incidence sur les processus d'acquisition des connaissances ainsi que le réarrangement de la structure sociale. Tout d'abord, nous examinons comment des évaluations différentes des interactions sociales influent sur la disponibilité de l'information ainsi que sur la topologie du réseau. Nous comparons un premier cas, où les individus évaluent les échanges sociaux par la quantité d'information qui peut être partagée par le partenaire, avec un second cas, où ils évaluent les interactions en tenant compte du statut social de leurs partenaires. Nous montrons que, même si les deux stratégies prennent en compte le montant de connaissances des partenaires, elles ont des effets très différents sur le système. En particulier, nous constatons que le premier cas permet généralement aux individus d'accumuler de plus grandes quantités d'information, grâce à des modèles de connexions sociales plus efficaces qu'ils sont capables de construire. Ensuite, nous étudions les effets que l'homophilie, ou la tendance à interagir avec des partenaires similaires, a sur l'accumulation des connaissances et la structure sociale. Nous comparons le cas où des personnes qui connaissent les mêmes informations sont plus sus¬ceptibles d'apprendre socialement l'une de l'autre, au cas où les individus qui connaissent des informations différentes sont au contraire plus susceptibles d'apprendre socialement l'un de l'autre. Nous constatons qu'il n'est pas trivial de déterminer quelle stratégie est meilleure que l'autre. En fonction de la possibilité d'oublier l'information, la façon dont les nouveaux partenaires sociaux peuvent être choisis, et la taille de la population, nous déterminons les conditions pour lesquelles chaque stratégie permet d'accumuler plus d'in¬formations, ou d'une manière plus rapide. Pour ces conditions, nous discutons également les caractéristiques topologiques de la structure sociale qui en résulte, les reliant au résultat de la dynamique de l'information. En conclusion, ce travail ouvre la route pour la modélisation de la dynamique conjointe de la diffusion de l'information entre les individus et leurs interactions sociales. Il fournit également un cadre formel pour étudier conjointement les effets de différentes stratégies de choix des partenaires sur la structure sociale et comment elles favorisent l'accumulation de connaissances dans la population.

Using niche-based models to improve the sampling of rare species

Because data on rare species usually are sparse, it is important to have efficient ways to sample additional data. Traditional sampling approaches are of limited value for rare species because a very large proportion of randomly chosen sampling sites are unlikely to shelter the species. For these species, spatial predictions from niche-based distribution models can be used to stratify the sampling and increase sampling efficiency. New data sampled are then used to improve the initial model. Applying this approach repeatedly is an adaptive process that may allow increasing the number of new occurrences found. We illustrate the approach with a case study of a rare and endangered plant species in Switzerland and a simulation experiment. Our field survey confirmed that the method helps in the discovery of new populations of the target species in remote areas where the predicted habitat suitability is high. In our simulations the model-based approach provided a significant improvement (by a factor of 1.8 to 4 times, depending on the measure) over simple random sampling. In terms of cost this approach may save up to 70% of the time spent in the field.

Family history of cancer and the risk of cancer: a network of case-control studies.

BACKGROUND: The risk of many cancers is higher in subjects with a family history (FH) of cancer at a concordant site. However, few studies investigated FH of cancer at discordant sites. PATIENTS AND METHODS: This study is based on a network of Italian and Swiss case-control studies on 13 cancer sites conducted between 1991 and 2009, and including more than 12 000 cases and 11 000 controls. We collected information on history of any cancer in first degree relatives, and age at diagnosis. Odds ratios (ORs) for FH were calculated by multiple logistic regression models, adjusted for major confounding factors. RESULTS: All sites showed an excess risk in relation to FH of cancer at the same site. Increased risks were also found for oral and pharyngeal cancer and FH of laryngeal cancer (OR = 3.3), esophageal cancer and FH of oral and pharyngeal cancer (OR = 4.1), breast cancer and FH of colorectal cancer (OR = 1.5) and of hemolymphopoietic cancers (OR = 1.7), ovarian cancer and FH of breast cancer (OR = 2.3), and prostate cancer and FH of bladder cancer (OR = 3.4). For most cancer sites, the association with FH was stronger when the proband was affected at age <60 years. CONCLUSIONS: Our results point to several potential cancer syndromes that appear among close relatives and may indicate the presence of genetic factors influencing multiple cancer sites.

Total Cost of Transportation Analysis of Road and Highway Issues, HR-388, 2002

In the administration, planning, design, and maintenance of road systems, transportation professionals often need to choose between alternatives, justify decisions, evaluate tradeoffs, determine how much to spend, set priorities, assess how well the network meets traveler needs, and communicate the basis for their actions to others. A variety of technical guidelines, tools, and methods have been developed to help with these activities. Such work aids include design criteria guidelines, design exception analysis methods, needs studies, revenue allocation schemes, regional planning guides, designation of minimum standards, sufficiency ratings, management systems, point based systems to determine eligibility for paving, functional classification, and bridge ratings. While such tools play valuable roles, they also manifest a number of deficiencies and are poorly integrated. Design guides tell what solutions MAY be used, they aren't oriented towards helping find which one SHOULD be used. Design exception methods help justify deviation from design guide requirements but omit consideration of important factors. Resource distribution is too often based on dividing up what's available rather than helping determine how much should be spent. Point systems serve well as procedural tools but are employed primarily to justify decisions that have already been made. In addition, the tools aren't very scalable: a system level method of analysis seldom works at the project level and vice versa. In conjunction with the issues cited above, the operation and financing of the road and highway system is often the subject of criticisms that raise fundamental questions: What is the best way to determine how much money should be spent on a city or a county's road network? Is the size and quality of the rural road system appropriate? Is too much or too little money spent on road work? What parts of the system should be upgraded and in what sequence? Do truckers receive a hidden subsidy from other motorists? Do transportation professions evaluate road situations from too narrow of a perspective? In considering the issues and questions the author concluded that it would be of value if one could identify and develop a new method that would overcome the shortcomings of existing methods, be scalable, be capable of being understood by the general public, and utilize a broad viewpoint. After trying out a number of concepts, it appeared that a good approach would be to view the road network as a sub-component of a much larger system that also includes vehicles, people, goods-in-transit, and all the ancillary items needed to make the system function. Highway investment decisions could then be made on the basis of how they affect the total cost of operating the total system. A concept, named the "Total Cost of Transportation" method, was then developed and tested. The concept rests on four key principles: 1) that roads are but one sub-system of a much larger 'Road Based Transportation System', 2) that the size and activity level of the overall system are determined by market forces, 3) that the sum of everything expended, consumed, given up, or permanently reserved in building the system and generating the activity that results from the market forces represents the total cost of transportation, and 4) that the economic purpose of making road improvements is to minimize that total cost. To test the practical value of the theory, a special database and spreadsheet model of Iowa's county road network was developed. This involved creating a physical model to represent the size, characteristics, activity levels, and the rates at which the activities take place, developing a companion economic cost model, then using the two in tandem to explore a variety of issues. Ultimately, the theory and model proved capable of being used in full system, partial system, single segment, project, and general design guide levels of analysis. The method appeared to be capable of remedying many of the existing work method defects and to answer society's transportation questions from a new perspective.