964 resultados para variance component models
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Ensembles of extended Atmospheric Model Intercomparison Project (AMIP) runs from the general circulation models of the National Centers for Environmental Prediction (formerly the National Meteorological Center) and the Max-Planck Institute (Hamburg, Germany) are used to estimate the potential predictability (PP) of an index of the Pacific–North America (PNA) mode of climate change. The PP of this pattern in “perfect” prediction experiments is 20%–25% of the index’s variance. The models, particularly that from MPI, capture virtually all of this variance in their hindcasts of the winter PNA for the period 1970–93. The high levels of internally generated model noise in the PNA simulations reconfirm the need for an ensemble averaging approach to climate prediction. This means that the forecasts ought to be expressed in a probabilistic manner. It is shown that the models’ skills are higher by about 50% during strong SST events in the tropical Pacific, so the probabilistic forecasts need to be conditional on the tropical SST. Taken together with earlier studies, the present results suggest that the original set of AMIP integrations (single 10-yr runs) is not adequate to reliably test the participating models’ simulations of interannual climate variability in the midlatitudes.
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Dados de 4.959 lactações de 2.414 vacas da raça Pardo-Suíça, filhas de 70 reprodutores, distribuídos em 51 rebanhos, foram utilizados para se estimar o componente de variância para a interação reprodutor x rebanho das produções de leite e de gordura e verificar o efeito desta interação sobre a avaliação genética dos reprodutores, por meio de modelos que diferiam na presença e ausência do termo de interação. As produções de leite e de gordura foram ajustadas para duas ordenhas diárias, 305 dias de lactação e idade adulta da vaca. O teste da razão de verossimilhança foi utilizado na verificação da efetividade da inclusão da interação no modelo. As médias das produções de leite e de gordura foram 6085,79 ± 1629,73 kg e 225,61 ± 60,44 kg, respectivamente. A proporção da variância total decorrente da interação reprodutor x rebanho foi 0,4%, para a produção de leite, e 1%, para a produção de gordura. A estimativa de herdabilidade foi 0,38, para a produção de leite, utilizando-se ambos os modelos, e reduziu de 0,40 para 0,39, para a produção de gordura, quando o modelo com interação foi considerado. A função de verossimilhança aumentou significativamente com a inclusão da interação no modelo. A correlação de Spearman foi próxima de um para ambas as características, quando todos os reprodutores foram considerados. Houve redução de 1% na estimativa de acurácia dos valores genéticos preditos para ambas as características, porém, a correlação de Pearson estimada entre as acurácias obtidas para cada modelo estudado foi próxima à unidade. A interaçãoreprodutor x rebanho não afetou as estimativas de componentes de variâncias genética e residual e a ordem de classificação dos reprodutores para ambas as características.
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Foram simuladas estruturas de dados em modelos mistos representando o teste de 100 reprodutores, sendo cada reprodutor acasalado com 10 matrizes (total de 1000 matrizes), originando em cada acasalamento 2 proles, totalizando 2000 proles (vinte proles por reprodutor). De cada combinação reprodutor e matriz, dez proles tiveram seu fenótipo expresso no ambiente de baixa produção (Estrato 1) e, a outra metade, no ambiente de alta produção (Estrato 2). A simulação foi realizada de forma a representar diferentes situações de presença de heterogeneidade de variâncias, combinando-se as origens da heterogeneidade, de natureza genética e ambiental. Na presença de heterogeneidade residual, o valor estimado para o componente de variância residual, considerando homogeneidade de variâncias se aproximou do valor médio das variâncias entre os estratos. Houve superestimação, também, do componente de variância genético aditivo. Ao simular heterogeneidade de variância de origem genética, observou-se que a estimação desse componente situou-se em valor intermediário aos simulados. Nessa situação, o componente de variância residual estimado foi próximo do valor simulado, indicando que a heterogeneidade de variâncias quando proveniente de fatores genéticos, não interfere, substancialmente, sobre e estimação do componente de variância residual. Na simulação de dados com presença de heterogeneidade tanto de origem genética quanto ambiental (estrutura de dados 4), conduziu a estimação de componentes de variâncias intermediários aos valores simulados em cada estrato. Assim, observa-se que, mesmo quando os reprodutores apresentam proles bem distribuídas em ambos os estratos, a heterogeneidade de variância proveniente de fatores não genético provoca distorções sobre a estimação da variância genética aditiva. Mas por outro lado, quando a heterogeneidade de variância é decorrente de fatores genéticos, não há grande interferência sobre a estimativa da variância residual, tal comportamento pode ser explicado pela incorporação da matriz de parentesco na estimação do componente de variância genético aditivo, possibilitando discriminar melhor a origem da diferenças entre variâncias. Na estrutura onde a variância residual foi heterogênea a estimativa de herdabilidade foi menor em relação à estrutura de homogeneidade de variâncias. Por outro lado, quando somente a variância genética aditiva foi heterogênea, a estimativa de herdabilidade, considerando-se apenas o estrato de alta variabilidade genética, foi inflacionada pela superestimação da variância genética aditiva. No entanto, a estimativa de herdabilidade obtida, desconsiderando essa fonte de heterogeneidade de variância, foi próxima à situação de homogeneidade de variância, indicando que, quando os reprodutores possuem boa distribuição de proles em diferentes ambientes, as estimativas relacionadas ao efeito genético são ponderadas pelo desempenho dos animais em cada ambiente. As correlações de Spearman e de Pearson entre os valores genéticos preditos dos reprodutores, para todas as situações, foram maiores que 0,90. O resultado indica que, mesmo havendo presença de heterogeneidade de variância genética e/ou ambiental, se os reprodutores possuem proles bem distribuídas entre os ambientes (estratos heterogêneos) a classificação do mérito genético não se altera, o que era esperado, pois em análises unicarácter, quando ocorre uma fonte de viés na avaliação genética, ela é comum a todos os indivíduos. Na situação em que foi imposta a estrutura de dados à presença de heterogeneidade de variância residual com número de número desigual de proles por reprodutor nos estratos, provocou superestimação dos componentes de variância. Porém mesmo havendo alteração na magnitude dos valores genéticos preditos para os reprodutores, a heterogeneidade de variância não alterou a classificação entre os reprodutores todas as correlações de ordem foram próximas à unidade. O efeito da heterogeneidade de variância, oriunda de fatores ambientais, ocasiona em maiores distorções sobre a avaliação genética animal, em relação, quando a mesma é proveniente de causas genéticas. A conexidade genética entre diferentes ambientes, dilui o efeito da heterogeneidade de variância, tanto de origem genética, quanto ambiental, na predição de valores genéticos dos reprodutores.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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O objetivo dessa pesquisa foi avaliar aspectos genéticos que relacionados à produção in vitro de embriões na raça Guzerá. O primeiro estudo focou na estimação de (co) variâncias genéticas e fenotípicas em características relacionadas a produção de embriões e na detecção de possível associação com a idade ao primeiro parto (AFC). Foi detectada baixa e média herdabilidade para características relacionadas à produção de oócitos e embriões. Houve fraca associação genética entre características ligadas a reprodução artificial e a idade ao primeiro parto. O segundo estudo avaliou tendências genéticas e de endogamia em uma população Guzerá no Brasil. Doadoras e embriões produzidos in vitro foram considerados como duas subpopulações de forma a realizar comparações acerca das diferenças de variação anual genética e do coeficiente de endogamia. A tendência anual do coeficiente de endogamia (F) foi superior para a população geral, sendo detectado efeito quadrático. No entanto, a média de F para a sub- população de embriões foi maior do que na população geral e das doadoras. Foi observado ganho genético anual superior para a idade ao primeiro parto e para a produção de leite (305 dias) entre embriões produzidos in vitro do que entre doadoras ou entre a população geral. O terceiro estudo examinou os efeitos do coeficiente de endogamia da doadora, do reprodutor (usado na fertilização in vitro) e dos embriões sobre resultados de produção in vitro de embriões na raça Guzerá. Foi detectado efeito da endogamia da doadora e dos embriões sobre as características estudadas. O quarto (e último) estudo foi elaborado para comparar a adequação de modelos mistos lineares e generalizados sob método de Máxima Verossimilhança Restrita (REML) e sua adequação a variáveis discretas. Quatro modelos hierárquicos assumindo diferentes distribuições para dados de contagem encontrados no banco. Inferência foi realizada com base em diagnósticos de resíduo e comparação de razões entre componentes de variância para os modelos em cada variável. Modelos Poisson superaram tanto o modelo linear (com e sem transformação da variável) quanto binomial negativo à qualidade do ajuste e capacidade preditiva, apesar de claras diferenças observadas na distribuição das variáveis. Entre os modelos testados, a pior qualidade de ajuste foi obtida para o modelo linear mediante transformação logarítmica (Log10 X +1) da variável resposta.
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Component-based development (CBD) has become an important emerging topic in the software engineering field. It promises long-sought-after benefits such as increased software reuse, reduced development time to market and, hence, reduced software production cost. Despite the huge potential, the lack of reasoning support and development environment of component modeling and verification may hinder its development. Methods and tools that can support component model analysis are highly appreciated by industry. Such a tool support should be fully automated as well as efficient. At the same time, the reasoning tool should scale up well as it may need to handle hundreds or even thousands of components that a modern software system may have. Furthermore, a distributed environment that can effectively manage and compose components is also desirable. In this paper, we present an approach to the modeling and verification of a newly proposed component model using Semantic Web languages and their reasoning tools. We use the Web Ontology Language and the Semantic Web Rule Language to precisely capture the inter-relationships and constraints among the entities in a component model. Semantic Web reasoning tools are deployed to perform automated analysis support of the component models. Moreover, we also proposed a service-oriented architecture (SOA)-based semantic web environment for CBD. The adoption of Semantic Web services and SOA make our component environment more reusable, scalable, dynamic and adaptive.
Epidemiology and genetic architecture of blood pressure: a family based study of Generation Scotland
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Hypertension is a major risk factor for cardiovascular disease and mortality, and a growing global public health concern, with up to one-third of the world’s population affected. Despite the vast amount of evidence for the benefits of blood pressure (BP) lowering accumulated to date, elevated BP is still the leading risk factor for disease and disability worldwide. It is well established that hypertension and BP are common complex traits, where multiple genetic and environmental factors contribute to BP variation. Furthermore, family and twin studies confirmed the genetic component of BP, with a heritability estimate in the range of 30-50%. Contemporary genomic tools enabling the genotyping of millions of genetic variants across the human genome in an efficient, reliable, and cost-effective manner, has transformed hypertension genetics research. This is accompanied by the presence of international consortia that have offered unprecedentedly large sample sizes for genome-wide association studies (GWASs). While GWAS for hypertension and BP have identified more than 60 loci, variants in these loci are associated with modest effects on BP and in aggregate can explain less than 3% of the variance in BP. The aims of this thesis are to study the genetic and environmental factors that influence BP and hypertension traits in the Scottish population, by performing several genetic epidemiological analyses. In the first part of this thesis, it aims to study the burden of hypertension in the Scottish population, along with assessing the familial aggregation and heritialbity of BP and hypertension traits. In the second part, it aims to validate the association of common SNPs reported in the large GWAS and to estimate the variance explained by these variants. In this thesis, comprehensive genetic epidemiology analyses were performed on Generation Scotland: Scottish Family Health Study (GS:SFHS), one of the largest population-based family design studies. The availability of clinical, biological samples, self-reported information, and medical records for study participants has allowed several assessments to be performed to evaluate factors that influence BP variation in the Scottish population. Of the 20,753 subjects genotyped in the study, a total of 18,470 individuals (grouped into 7,025 extended families) passed the stringent quality control (QC) criteria and were available for all subsequent analysis. Based on the BP-lowering treatment exposure sources, subjects were further classified into two groups. First, subjects with both a self-reported medications (SRMs) history and electronic-prescription records (EPRs; n =12,347); second, all the subjects with at least one medication history source (n =18,470). In the first group, the analysis showed a good concordance between SRMs and EPRs (kappa =71%), indicating that SRMs can be used as a surrogate to assess the exposure to BP-lowering medication in GS:SFHS participants. Although both sources suffer from some limitations, SRMs can be considered the best available source to estimate the drug exposure history in those without EPRs. The prevalence of hypertension was 40.8% with higher prevalence in men (46.3%) compared to women (35.8%). The prevalence of awareness, treatment and controlled hypertension as defined by the study definition were 25.3%, 31.2%, and 54.3%, respectively. These findings are lower than similar reported studies in other populations, with the exception of controlled hypertension prevalence, which can be considered better than other populations. Odds of hypertension were higher in men, obese or overweight individuals, people with a parental history of hypertension, and those living in the most deprived area of Scotland. On the other hand, deprivation was associated with higher odds of treatment, awareness and controlled hypertension, suggesting that people living in the most deprived area may have been receiving better quality of care, or have higher comorbidity levels requiring greater engagement with doctors. These findings highlight the need for further work to improve hypertension management in Scotland. The family design of GS:SFHS has allowed family-based analysis to be performed to assess the familial aggregation and heritability of BP and hypertension traits. The familial correlation of BP traits ranged from 0.07 to 0.20, and from 0.18 to 0.34 for parent-offspring pairs and sibling pairs, respectively. A higher correlation of BP traits was observed among first-degree relatives than other types of relative pairs. A variance-component model that was adjusted for sex, body mass index (BMI), age, and age-squared was used to estimate heritability of BP traits, which ranged from 24% to 32% with pulse pressure (PP) having the lowest estimates. The genetic correlation between BP traits showed a high correlation between systolic (SBP), diastolic (DBP) and mean arterial pressure (MAP) (G: 81% to 94%), but lower correlations with PP (G: 22% to 78%). The sibling recurrence risk ratio (λS) for hypertension and treatment were calculated as 1.60 and 2.04 respectively. These findings confirm the genetic components of BP traits in GS:SFHS, and justify further work to investigate genetic determinants of BP. Genetic variants reported in the recent large GWAS of BP traits were selected for genotyping in GS:SFHS using a custom designed TaqMan® OpenArray®. The genotyping plate included 44 single nucleotide polymorphisms (SNPs) that have been previously reported to be associated with BP or hypertension at genome-wide significance level. A linear mixed model that is adjusted for age, age-squared, sex, and BMI was used to test for the association between the genetic variants and BP traits. Of the 43 variants that passed the QC, 11 variants showed statistically significant association with at least one BP trait. The phenotypic variance explained by these variant for the four BP traits were 1.4%, 1.5%, 1.6%, and 0.8% for SBP, DBP, MAP, and PP, respectively. The association of genetic risk score (GRS) that were constructed from selected variants has showed a positive association with BP level and hypertension prevalence, with an average effect of one mmHg increase with each 0.80 unit increases in the GRS across the different BP traits. The impact of BP-lowering medication on the genetic association study for BP traits has been established, with typical practice of adding a fixed value (i.e. 15/10 mmHg) to the measured BP values to adjust for BP treatment. Using the subset of participants with the two treatment exposure sources (i.e. SRMs and EPRs), the influence of using either source to justify the addition of fixed values in SNP association signal was analysed. BP phenotypes derived from EPRs were considered the true phenotypes, and those derived from SRMs were considered less accurate, with some phenotypic noise. Comparing SNPs association signals between the four BP traits in the two model derived from the different adjustments showed that MAP was the least impacted by the phenotypic noise. This was suggested by identifying the same overlapped significant SNPs for the two models in the case of MAP, while other BP traits had some discrepancy between the two sources
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O objetivo do estudo foi apresentar a fração da variância intrapessoal para ajuste da distribuição de nutrientes de adultos e idosos. Utilizaram-se dados de inquérito populacional com amostra representativa (n = 511) de indivíduos com 19 anos ou mais do município de São Paulo, SP, em 2007. A fração da variância intrapessoal foi obtida pelo método proposto pela Iowa State University. Observaram-se diferenças nas frações das variâncias intrapessoais de nutrientes segundo sexo. Esses valores devem ser utilizados para ajustar a distribuição da ingestão de nutrientes, pois sua não utilização pode resultar em viés na análise e interpretação de dados.
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Background: The heritability of cardiovascular risk factors is expected to differ between populations because of the different distribution of environmental risk factors, as well as the genetic make-up of different human populations. Methods: The purpose of this analysis was to evaluate genetic and environmental influences on cardiovascular risk factor traits, using a variance component approach, by estimating the heritability of these traits in a sample of 1,666 individuals in 81 families ascertained randomly from a highly admixed population of a city in a rural area in Brazil. Results: Before adjustment for sex, age, age(2), and age x sex interaction, polygenic heritability of systolic (SBP) and diastolic (DBP) blood pressure were 15.0% and 16.4%, waist circumference 26.1%, triglycerides 25.7%, fasting glucose 32.8%, HDL-c 31.2%, total cholesterol 28.6%, LDL-c 26.3%, BMI 39.1%. Adjustment for covariates increased polygenic heritability estimates for all traits mainly systolic and diastolic blood pressure (25.9 and 26.2%, respectively), waist circumference (40.1%), and BMI (51.0%). Conclusion: Heritability estimates for cardiovascular traits in the Brazilian population are high and not significantly different from other studied worldwide populations. Mapping efforts to identify genetic loci associated with variability of these traits are warranted.
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This research presents the development and implementation in a computational routine of algorithms for fault location in multiterminal transmission lines. These algorithms are part of a fault-location system, which is capable of correctly identifying the fault point based on voltage and current phasor quantities, calculated by using measurements of voltage and current signals from intelligent electronic devices, located on the transmission-line terminals. The algorithms have access to the electrical parameters of the transmission lines and to information about the transformers loading and their connection type. This paper also presents the development of phase component models for the power system elements used by the fault-location algorithms.
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The magnitude of genotype-by-management (G x M) interactions for grain yield and grain protein concentration was examined in a multi-environment trial (MET) involving a diverse set of 272 advanced breeding lines from the Queensland wheat breeding program. The MET was structured as a series of management-regimes imposed at 3 sites for 2 years. The management-regimes were generated at each site-year as separate trials in which planting time, N fertiliser application rate, cropping history, and irrigation were manipulated. irrigation was used to simulate different rainfall regimes. From the combined analysis of variance, the G x M interaction variance components were found to be the largest source of G x E interaction variation for both grain yield (0.117 +/- 0.005 t(2) ha(-2); 49% of total G x E 0.238 +/- 0.028 t(2) ha(-2)) and grain protein concentration (0.445 +/- 0.020%(2); 82% of total G x E 0.546 +/- 0.057%(2)), and in both cases this source of variation was larger than the genotypic variance component (grain yield 0.068 +/- 0.014 t(2) ha(-2) and grain protein 0.203 +/- 0.026%(2)). The genotypic correlation between the traits varied considerably with management-regime, ranging from -0.98 to -0.31, with an estimate of 0.0 for one trial. Pattern analysis identified advanced breeding lines with improved grain yield and grain protein concentration relative to the cultivars Hartog, Sunco and Meteor. It is likely that a large component of the previously documented G x E interactions for grain yield of wheat in the northern grains region are in part a result of G x M interactions. The implications of the strong influence of G x M interactions for the conduct of wheat breeding METs in the northern region are discussed. (C) 2001 Elsevier Science B.V. All rights reserved.
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For the improvement of genetic material suitable for on farm use under low-input conditions, participatory and formal plant breeding strategies are frequently presented as competing options. A common frame of reference to phrase mechanisms and purposes related to breeding strategies will facilitate clearer descriptions of similarities and differences between participatory plant breeding and formal plant breeding. In this paper an attempt is made to develop such a common framework by means of a statistically inspired language that acknowledges the importance of both on farm trials and research centre trials as sources of information for on farm genetic improvement. Key concepts are the genetic correlation between environments, and the heterogeneity of phenotypic and genetic variance over environments. Classic selection response theory is taken as the starting point for the comparison of selection trials (on farm and research centre) with respect to the expected genetic improvement in a target environment (low-input farms). The variance-covariance parameters that form the input for selection response comparisons traditionally come from a mixed model fit to multi-environment trial data. In this paper we propose a recently developed class of mixed models, namely multiplicative mixed models, also called factor-analytic models, for modelling genetic variances and covariances (correlations). Mixed multiplicative models allow genetic variances and covariances to be dependent on quantitative descriptors of the environment, and confer a high flexibility in the choice of variance-covariance structure, without requiring the estimation of a prohibitively high number of parameters. As a result detailed considerations regarding selection response comparisons are facilitated. ne statistical machinery involved is illustrated on an example data set consisting of barley trials from the International Center for Agricultural Research in the Dry Areas (ICARDA). Analysis of the example data showed that participatory plant breeding and formal plant breeding are better interpreted as providing complementary rather than competing information.
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Submitted in partial fulfillment for the Requirements for the Degree of PhD in Mathematics, in the Speciality of Statistics in the Faculdade de Ciências e Tecnologia
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Sorption is commonly agreed to be the major process underlying the transport and fate of polycyclic aromatic hydrocarbons (PAHs) in soils. However, there is still a scarcity of studies focusing on spatial variability at the field scale in particular. In order to investigate the variation in the field of phenanthrene sorption, bulk topsoil samples were taken in a 15 × 15-m grid from the plough layer in two sandy loam fields with different texture and organic carbon (OC) contents (140 samples in total). Batch experiments were performed using the adsorption method. Values for the partition coefficient K d (L kg−1) and the organic carbon partition coefficient K OC (L kg−1) agreed with the most frequently used models for PAH partitioning, as OC revealed a higher affinity for sorption. More complex models using different OC compartments, such as non-complexed organic carbon (NCOC) and complexed organic carbon (COC) separately, performed better than single K OC models, particularly for a subset including samples with Dexter n < 10 and OC <0.04 kg kg−1. The selected threshold revealed that K OC-based models proved to be applicable for more organic fields, while two-component models proved to be more accurate for the prediction of K d and retardation factor (R) for less organic soils. Moreover, OC did not fully reflect the changes in phenanthrene retardation in the field with lower OC content (Faardrup). Bulk density and available water content influenced the phenanthrene transport mechanism phenomenon.
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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.