ON MARGINALIZED MULTILEVEL MODELS AND THEIR COMPUTATION

Clustered data analysis is characterized by the need to describe both systematic variation in a mean model and cluster-dependent random variation in an association model. Marginalized multilevel models embrace the robustness and interpretations of a marginal mean model, while retaining the likelihood inference capabilities and flexible dependence structures of a conditional association model. Although there has been increasing recognition of the attractiveness of marginalized multilevel models, there has been a gap in their practical application arising from a lack of readily available estimation procedures. We extend the marginalized multilevel model to allow for nonlinear functions in both the mean and association aspects. We then formulate marginal models through conditional specifications to facilitate estimation with mixed model computational solutions already in place. We illustrate this approach on a cerebrovascular deficiency crossover trial.

RANDOM EFFECTS MODELS IN A META-ANALYSIS OF THE ACCURACY OF DIAGNOSTIC TESTS WITHIN A GOLD STANDARD IN THE PRESENCE OF MISSING DATA

In evaluating the accuracy of diagnosis tests, it is common to apply two imperfect tests jointly or sequentially to a study population. In a recent meta-analysis of the accuracy of microsatellite instability testing (MSI) and traditional mutation analysis (MUT) in predicting germline mutations of the mismatch repair (MMR) genes, a Bayesian approach (Chen, Watson, and Parmigiani 2005) was proposed to handle missing data resulting from partial testing and the lack of a gold standard. In this paper, we demonstrate an improved estimation of the sensitivities and specificities of MSI and MUT by using a nonlinear mixed model and a Bayesian hierarchical model, both of which account for the heterogeneity across studies through study-specific random effects. The methods can be used to estimate the accuracy of two imperfect diagnostic tests in other meta-analyses when the prevalence of disease, the sensitivities and/or the specificities of diagnostic tests are heterogeneous among studies. Furthermore, simulation studies have demonstrated the importance of carefully selecting appropriate random effects on the estimation of diagnostic accuracy measurements in this scenario.

Mixed inheritance of equine recurrent airway obstruction

BACKGROUND: Mode of inheritance of equine recurrent airway obstruction (RAO) is unknown. HYPOTHESIS: Major genes are responsible for RAO. ANIMALS: Direct offspring of 2 RAO-affected Warmblood stallions (n = 197; n = 163) and a representative sample of Swiss Warmbloods (n = 401). METHODS: One environmental and 4 genetic models (general, mixed inheritance, major gene, and polygene) were tested for Horse Owner Assessed Respiratory Signs Index (1-4, unaffected to severely affected) by segregation analyses of the 2 half-sib sire families, both combined and separately, using prevalences estimated in a representative sample. RESULTS: In all data sets the mixed inheritance model was most likely to explain the pattern of inheritance. In all 3 datasets the mixed inheritance model did not differ significantly from the general model (P= .62, P= 1.00, and P= .27) but was always better than the major gene model (P < .01) and the polygene model (P < .01). The frequency of the deleterious allele differed considerably between the 2 sire families (P= .23 and P= .06). In both sire families the displacement was large (t= 17.52 and t= 12.24) and the heritability extremely large (h(2)= 1). CONCLUSIONS AND CLINICAL RELEVANCE: Segregation analyses clearly reveal the presence of a major gene playing a role in RAO. In 1 family, the mode of inheritance was autosomal dominant, whereas in the other family it was autosomal recessive. Although the expression of RAO is influenced by exposure to hay, these findings suggest a strong, complex genetic background for RAO.

Decision Support Models for Composing and Navigating through e-Learning Objects

Libraries of learning objects may serve as basis for deriving course offerings that are customized to the needs of different learning communities or even individuals. Several ways of organizing this course composition process are discussed. Course composition needs a clear understanding of the dependencies between the learning objects. Therefore we discuss the metadata for object relationships proposed in different standardization projects and especially those suggested in the Dublin Core Metadata Initiative. Based on these metadata we construct adjacency matrices and graphs. We show how Gozinto-type computations can be used to determine direct and indirect prerequisites for certain learning objects. The metadata may also be used to define integer programming models which can be applied to support the instructor in formulating his specifications for selecting objects or which allow a computer agent to automatically select learning objects. Such decision models could also be helpful for a learner navigating through a library of learning objects. We also sketch a graph-based procedure for manual or automatic sequencing of the learning objects.

VIS-NIR reflectance of water ice/regolith analogue mixtures and implications for the detectability of ice mixed within planetary regoliths

Permanently shadowed regions at the poles of the Moon and Mercury have been pointed out as candidates for hosting water ice at their surface. We have measured in the laboratory the visible and near infrared spectral range (VIS-NIR) bidirectional reflectance of intimate mixtures of water ice and the JSC-1AF lunar simulant for different ice concentrations, particle sizes, and measurement geometries. The nonlinearity between the measured reflectance and the amount of ice in the mixture can be reproduced to some extent by the mixing formulas of standard reflectance models, in particular, those of Hapke and Hiroi, which are tested here. Estimating ice concentrations from reflectance data without knowledge of the mixing coefficientsstrongly dependent on the size/shape of the grainscan result in large errors. According to our results, it is possible that considerable amounts of water ice might be intimately mixed in the regolith of the Moon and Mercury without producing noticeable photometric signatures.

Performance Evaluation of the New Connecticut Leading Employment Index Using Lead Profiles and BVAR Models

Dua and Miller (1996) created leading and coincident employment indexes for the state of Connecticut, following Moore's (1981) work at the national level. The performance of the Dua-Miller indexes following the recession of the early 1990s fell short of expectations. This paper performs two tasks. First, it describes the process of revising the Connecticut Coincident and Leading Employment Indexes. Second, it analyzes the statistical properties and performance of the new indexes by comparing the lead profiles of the new and old indexes as well as their out-of-sample forecasting performance, using the Bayesian Vector Autoregressive (BVAR) method. The new indexes show improved performance in dating employment cycle chronologies. The lead profile test demonstrates that superiority in a rigorous, non-parametric statistic fashion. The mixed evidence on the BVAR forecasting experiments illustrates the truth in the Granger and Newbold (1986) caution that leading indexes properly predict cycle turning points and do not necessarily provide accurate forecasts except at turning points, a view that our results support.

Age models of ODP Sites 117-722 and 117-728

Pliocene and Pleistocene sediments of the Oman margin and Owen Ridge are characterized by continuous alternation of light and dark layers of nannofossil ooze and marly nannofossil ooze and cyclic variation of wet-bulk density. Origin of the wet-bulk density and color cycles was examined at Ocean Drilling Program Site 722 on the Owen Ridge and Site 728 on the Oman margin using 3.4-m.y.-long GRAPE (gamma ray attenuation) wet-bulk density records and records of sediment color represented as changes in gray level on black-and-white core photographs. At Sites 722 and 728 sediments display a weak correlation of decreasing wet-bulk density with increasing darkness of sediment color. Wet-bulk density is inversely related to organic carbon concentration and displays little relation to calcium carbonate concentration, which varies inversely with the abundance of terrigenous sediment components. Sediment color darkens with increasing terrigenous sediment abundance (decreasing carbonate content) and with increasing organic carbon concentration. Upper Pleistocene sediments at Site 722 display a regular pattern of dark colored intervals coinciding with glacial periods, whereas at Site 728 the pattern of color variation is more irregular. There is not a consistent relationship between the dark intervals and their relative wet-bulk density in the upper Pleistocene sections at Sites 722 and 728, suggesting that dominance of organic matter or terrigenous sediment as primary coloring agents varies. Spectra of wet-bulk density and optical density time series display concentration of variance at orbital periodicities of 100, 41, 23, and 19 k.y. A strong 41-k.y. periodicity characterizes wet-bulk density and optical density variation at both sites throughout most of the past 3.4 m.y. Cyclicity at the 41-k.y. periodicity is characterized by a lack of coherence between wet-bulk density and optical density suggesting that the bulk density and color cycles reflect the mixed influence of varying abundance of terrigenous sediments and organic matter. The 23-k.y. periodicity in wet-bulk density and sediment color cycles is generally characterized by significant coherence between wet-bulk density and optical density, which reflects an inverse relationship between these parameters. Varying organic matter abundance, associated with changes in productivity or preservation, is inferred to more strongly influence changes in wet-bulk density and sediment color at this periodicity.

Using ecological niche models to support tree species selection for forest restoration planning in largely deforested regions

Species selection for forest restoration is often supported by expert knowledge on local distribution patterns of native tree species. This approach is not applicable to largely deforested regions unless enough data on pre-human tree species distribution is available. In such regions, ecological niche models may provide essential information to support species selection in the framework of forest restoration planning. In this study we used ecological niche models to predict habitat suitability for native tree species in "Tierra de Campos" region, an almost totally deforested area of the Duero Basin (Spain). Previously available models provide habitat suitability predictions for dominant native tree species, but including non-dominant tree species in the forest restoration planning may be desirable to promote biodiversity, specially in largely deforested areas were near seed sources are not expected. We used the Forest Map of Spain as species occurrence data source to maximize the number of modeled tree species. Penalized logistic regression was used to train models using climate and lithological predictors. Using model predictions a set of tools were developed to support species selection in forest restoration planning. Model predictions were used to build ordered lists of suitable species for each cell of the study area. The suitable species lists were summarized drawing maps that showed the two most suitable species for each cell. Additionally, potential distribution maps of the suitable species for the study area were drawn. For a scenario with two dominant species, the models predicted a mixed forest (Quercus ilex and a coniferous tree species) for almost one half of the study area. According to the models, 22 non-dominant native tree species are suitable for the study area, with up to six suitable species per cell. The model predictions pointed to Crataegus monogyna, Juniperus communis, J.oxycedrus and J.phoenicea as the most suitable non-dominant native tree species in the study area. Our results encourage further use of ecological niche models for forest restoration planning in largely deforested regions.

Two Novel Methods For The Determination Of The Number Of Components In Independent Components Analysis Models

Independent Components Analysis is a Blind Source Separation method that aims to find the pure source signals mixed together in unknown proportions in the observed signals under study. It does this by searching for factors which are mutually statistically independent. It can thus be classified among the latent-variable based methods. Like other methods based on latent variables, a careful investigation has to be carried out to find out which factors are significant and which are not. Therefore, it is important to dispose of a validation procedure to decide on the optimal number of independent components to include in the final model. This can be made complicated by the fact that two consecutive models may differ in the order and signs of similarly-indexed ICs. As well, the structure of the extracted sources can change as a function of the number of factors calculated. Two methods for determining the optimal number of ICs are proposed in this article and applied to simulated and real datasets to demonstrate their performance.

Some past decision theory models for euro construction model codes and for road drainage in Spain, and modest hints with multi-criteria methods for agro and environmental assurance

The authors are from UPM and are relatively grouped, and all have intervened in different academic or real cases on the subject, at different times as being of different age. With precedent from E. Torroja and A. Páez in Madrid Spain Safety Probabilistic models for concrete about 1957, now in ICOSSAR conferences, author J.M. Antón involved since autumn 1967 for euro-steel construction in CECM produced a math model for independent load superposition reductions, and using it a load coefficient pattern for codes in Rome Feb. 1969, practically adopted for European constructions, giving in JCSS Lisbon Feb. 1974 suggestion of union for concrete-steel-al.. That model uses model for loads like Gumbel type I, for 50 years for one type of load, reduced to 1 year to be added to other independent loads, the sum set in Gumbel theories to 50 years return period, there are parallel models. A complete reliability system was produced, including non linear effects as from buckling, phenomena considered somehow in actual Construction Eurocodes produced from Model Codes. The system was considered by author in CEB in presence of Hydraulic effects from rivers, floods, sea, in reference with actual practice. When redacting a Road Drainage Norm in MOPU Spain an optimization model was realized by authors giving a way to determine the figure of Return Period, 10 to 50 years, for the cases of hydraulic flows to be considered in road drainage. Satisfactory examples were a stream in SE of Spain with Gumbel Type I model and a paper of Ven Te Chow with Mississippi in Keokuk using Gumbel type II, and the model can be modernized with more varied extreme laws. In fact in the MOPU drainage norm the redacting commission acted also as expert to set a table of return periods for elements of road drainage, in fact as a multi-criteria complex decision system. These precedent ideas were used e.g. in wide Codes, indicated in symposia or meetings, but not published in journals in English, and a condensate of contributions of authors is presented. The authors are somehow involved in optimization for hydraulic and agro planning, and give modest hints of intended applications in presence of agro and environment planning as a selection of the criteria and utility functions involved in bayesian, multi-criteria or mixed decision systems. Modest consideration is made of changing in climate, and on the production and commercial systems, and on others as social and financial.

An empirical mixed model to quantify climate influence on the growth of Pinus halepensis Mill. stands in South-Eastern Spain

The influence of climate on forest stand composition, development and growth is undeniable. Many studies have tried to quantify the effect of climatic variables on forest growth and yield. These works become especially important because there is a need to predict the effects of climate change on the development of forest ecosystems. One of the ways of facing this problem is the inclusion of climatic variables into the classic empirical growth models. The work has a double objective: (i) to identify the indicators which best describe the effect of climate on Pinus halepensis growth and (ii) to quantify such effect in several scenarios of rainfall decrease which are likely to occur in the Mediterranean area. A growth mixed model for P. halepensis including climatic variables is presented in this work. Growth estimates are based on data from the Spanish National Forest Inventory (SNFI). The best results are obtained for the indices including rainfall, or rainfall and temperature together, with annual precipitation, precipitation effectiveness, Emberger?s index or free bioclimatic intensity standing out among them. The final model includes Emberger?s index, free bioclimatic intensity and interactions between competition and climate indices. The results obtained show that a rainfall decrease about 5% leads to a decrease in volume growth of 5.5?7.5% depending on site quality.

News in engineering education in Spain effective from 2010 in presence of external changes and mixed crisis, looking mostly to agro and civil engineers.

The engineering careers models were diverse in Europe, and are adopting now in Spain the Bolonia process for European Universities. Separated from older Universities, that are in part technically active, Civil Engineering (Caminos, Canales y Puertos) started at end of 18th century in Spain adopting the French models of Upper Schools for state civil servants with exam at entry. After 1800 intense wars, to conserve forest regions Ingenieros de Montes appeared as Upper School, and in 1855 also the Ingenieros Agrónomos to push up related techniques and practices. Other Engineers appeared as Upper Schools but more towards private factories. These ES got all adapted Lower Schools of Ingeniero Tecnico. Recently both grew much in number and evolved, linked also to recognized Professions. Spanish society, into European Community, evolved across year 2000, in part highly well, but with severe discordances, that caused severe youth unemployment with 2008-2011 crisis. With Bolonia process high formal changes step in from 2010-11, accepted with intense adaptation. The Lower Schools are changing towards the Upper Schools, and both that have shifted since 2010-11 various 4-years careers (Grado), some included into the precedent Professions, and diverse Masters. Acceptation of them to get students has started relatively well, and will evolve, and acceptation of new grades for employment in Spain, Europe or outside will be essential. Each Grado has now quite rigid curricula and programs, MOODLE was introduced to connect pupils, some specific uses of Personal Computers are taught in each subject. Escuela de Agronomos centre, reorganized with its old name in its precedent buildings at entrance of Campus Moncloa, offers Grados of Agronomic Engineering and Science for various public and private activities for agriculture, Alimentary Engineering for alimentary activities and control, Agro-Environmental Engineering more related to environment activities, and in part Biotechnology also in laboratories in Campus Monte-Gancedo for Biotechnology of Plants and Computational Biotechnology. Curricula include Basics, Engineering, Practices, Visits, English, ?project of end of career?, Stays. Some masters will conduce to specific professional diploma, list includes now Agro-Engineering, Agro-Forestal Biotechnology, Agro and Natural Resources Economy, Complex Physical Systems, Gardening and Landscaping, Rural Genie, Phytogenetic Resources, Plant Genetic Resources, Environmental Technology for Sustainable Agriculture, Technology for Human Development and Cooperation.

Towards model-driven engineering for mixed-criticality systems: multiPARTES approach

Mixed criticality systems emerges as a suitable solution for dealing with the complexity, performance and costs of future embedded and dependable systems. However, this paradigm adds additional complexity to their development. This paper proposes an approach for dealing with this scenario that relies on hardware virtualization and Model-Driven Engineering (MDE). Hardware virtualization ensures isolation between subsystems with different criticality levels. MDE is intended to bridge the gap between design issues and partitioning concerns. MDE tooling will enhance the functional models by annotating partitioning and extra-functional properties. System partitioning and subsystems allocation will be generated with a high degree of automation. System configuration will be validated for ensuring that the resources assigned to a partition are sufficient for executing the allocated software components and that time requirements are met.

Radar track segmentation with cubic splines for collision risk models in high density terminal areas

This paper presents a method to segment airplane radar tracks in high density terminal areas where the air traffic follows trajectories with several changes in heading, speed and altitude. The radar tracks are modelled with different types of segments, straight lines, cubic spline function and shape preserving cubic function. The longitudinal, lateral and vertical deviations are calculated for terminal manoeuvring area scenarios. The most promising model of the radar tracks resulted from a mixed interpolation using straight lines for linear segments and spline cubic functions for curved segments. A sensitivity analysis is used to optimise the size of the window for the segmentation process.

Analyzing size-symmetric vs. size-asymmetric and intra-vs. inter-specific competition in beech (Fagus sylvatica L.) mixed stands

In mixed stands, inter-specific competition can be lower than intra-specific competition when niche complementarity and/or facilitation between species prevail. These positive interactions can take place at belowground and/or aboveground levels. Belowground competition tends to be size symmetric while the aboveground competition is usually for light and almost always size-asymmetric. Interactions between forest tree species can be explored analyzing growth at tree level by comparing intra and inter-specific competition. At the same time, possible causes of niche complementarity can be inferred relating intra and inter-specific competition with the mode of competition, i.e. size-symmetric or sizeasymmetric. The aim of this paper is to further our understanding of the interactions between species and to detect possible causes of competition reduction in mixed stands of beech (Fagus sylvatica L.) with other species: pine?beech, oak?beech and fir?beech. To test whether species growth is better explained by size-symmetric and/or size-asymmetric competition, five different competition structures where included in basal area growth models fitted using data from the Spanish National Forest Inventory for the Pyrenees. These models considered either size-symmetry only (Reineke?s stand density index, SDI), size-asymmetry only (SDI of large trees or SDI of small trees), or both combined. In order to assess the influence of the admixture, these indices were introduced in two different ways, one of which was to consider that trees of all species compete in a similar way, and the other was to split the stand density indices into intra- and inter-specific competition components. The results showed that in pine?beech mixtures, there is a slightly negative effect of beech on pine basal area growth while beech benefitted from the admixture of Scots pine; this positive effect being greater as the proportion of pine trees in larger size classes increases. In oak?beech mixtures, beech growth was also positively influenced by the presence of oaks that were larger than the beech trees. The growth of oak, however, decreased when the proportion of beech in SDI increased, although the presence of beech in larger size classes promoted oak growth. Finally, in fir?beech mixtures, neither fir nor beech basal area growth were influenced by the presence of the other species. The results indicate that size-asymmetric is stronger than size-symmetric competition in these mixtures, highlighting the importance of light in competition. Positive species interactions in size-asymmetric competition involved a reduction of asymmetry in tree size-growth relationships.