Designs and model effects definitions in the initial stage of a plant breeding program

The objective of this work was to compare the relative efficiency of initial selection and genetic parameter estimation, using augmented blocks design (ABD), augmented blocks twice replicated design (DABD) and group of randomised block design experiments with common treatments (ERBCT), by simulations, considering fixed effect model and mixed model with regular treatment effects as random. For the simulations, eight different conditions (scenarios) were considered. From the 600 simulations in each scenario, the mean percentage selection coincidence, the Pearsons´s correlation estimates between adjusted means for the fixed effects model, and the heritability estimates for the mixed model were evaluated. DABD and ERBCT were very similar in their comparisons and slightly superior to ABD. Considering the initial stages of selection in a plant breeding program, ABD is a good alternative for selecting superior genotypes, although none of the designs had been effective to estimate heritability in all the different scenarios evaluated.

Muscle moment-arms: a key element in muscle-force estimation.

A clear and rigorous definition of muscle moment-arms in the context of musculoskeletal systems modelling is presented, using classical mechanics and screw theory. The definition provides an alternative to the tendon excursion method, which can lead to incorrect moment-arms if used inappropriately due to its dependency on the choice of joint coordinates. The definition of moment-arms, and the presented construction method, apply to musculoskeletal models in which the bones are modelled as rigid bodies, the joints are modelled as ideal mechanical joints and the muscles are modelled as massless, frictionless cables wrapping over the bony protrusions, approximated using geometric surfaces. In this context, the definition is independent of any coordinate choice. It is then used to solve a muscle-force estimation problem for a simple 2D conceptual model and compared with an incorrect application of the tendon excursion method. The relative errors between the two solutions vary between 0% and 100%.

Grade and Cross Slope Estimation from LIDAR-based Surface Models, 2003

Many transportation agencies maintain grade as an attribute in roadway inventory databases; however, the information is often in an aggregated format. Cross slope is rarely included in large roadway inventories. Accurate methods available to collect grade and cross slope include global positioning systems, traditional surveying, and mobile mapping systems. However, most agencies do not have the resources to utilize these methods to collect grade and cross slope on a large scale. This report discusses the use of LIDAR to extract roadway grade and cross slope for large-scale inventories. Current data collection methods and their advantages and disadvantages are discussed. A pilot study to extract grade and cross slope from a LIDAR data set, including methodology, results, and conclusions, is presented. This report describes the regression methodology used to extract and evaluate the accuracy of grade and cross slope from three dimensional surfaces created from LIDAR data. The use of LIDAR data to extract grade and cross slope on tangent highway segments was evaluated and compared against grade and cross slope collected using an automatic level for 10 test segments along Iowa Highway 1. Grade and cross slope were measured from a surface model created from LIDAR data points collected for the study area. While grade could be estimated to within 1%, study results indicate that cross slope cannot practically be estimated using a LIDAR derived surface model.

A Framework for Building Hypercubes Using MapReduce

The European Space Agency's Gaia mission will create the largest and most precise three dimensional chart of our galaxy (the Milky Way), by providing unprecedented position, parallax, proper motion, and radial velocity measurements for about one billion stars. The resulting catalogue will be made available to the scientific community and will be analyzed in many different ways, including the production of a variety of statistics. The latter will often entail the generation of multidimensional histograms and hypercubes as part of the precomputed statistics for each data release, or for scientific analysis involving either the final data products or the raw data coming from the satellite instruments. In this paper we present and analyze a generic framework that allows the hypercube generation to be easily done within a MapReduce infrastructure, providing all the advantages of the new Big Data analysis paradigmbut without dealing with any specific interface to the lower level distributed system implementation (Hadoop). Furthermore, we show how executing the framework for different data storage model configurations (i.e. row or column oriented) and compression techniques can considerably improve the response time of this type of workload for the currently available simulated data of the mission. In addition, we put forward the advantages and shortcomings of the deployment of the framework on a public cloud provider, benchmark against other popular solutions available (that are not always the best for such ad-hoc applications), and describe some user experiences with the framework, which was employed for a number of dedicated astronomical data analysis techniques workshops.

A Framework for Building Hypercubes Using MapReduce

The European Space Agency's Gaia mission will create the largest and most precise three dimensional chart of our galaxy (the Milky Way), by providing unprecedented position, parallax, proper motion, and radial velocity measurements for about one billion stars. The resulting catalogue will be made available to the scientific community and will be analyzed in many different ways, including the production of a variety of statistics. The latter will often entail the generation of multidimensional histograms and hypercubes as part of the precomputed statistics for each data release, or for scientific analysis involving either the final data products or the raw data coming from the satellite instruments. In this paper we present and analyze a generic framework that allows the hypercube generation to be easily done within a MapReduce infrastructure, providing all the advantages of the new Big Data analysis paradigmbut without dealing with any specific interface to the lower level distributed system implementation (Hadoop). Furthermore, we show how executing the framework for different data storage model configurations (i.e. row or column oriented) and compression techniques can considerably improve the response time of this type of workload for the currently available simulated data of the mission. In addition, we put forward the advantages and shortcomings of the deployment of the framework on a public cloud provider, benchmark against other popular solutions available (that are not always the best for such ad-hoc applications), and describe some user experiences with the framework, which was employed for a number of dedicated astronomical data analysis techniques workshops.

Demand-based structural change and balanced economic growth

[eng] We analyze the equilibrium of a multi-sector exogenous growth model where the introduction of minimum consumption requirements drives structural change. We show that equilibrium dynamics simultaneously exhibt structural change and balanced growth of aggregate variables as is observed in US when the initial intensity of minimum consumption requirements is sufficiently small. This intensity is measured by the ratio between the aggregate value of the minimum consumption requirements and GDP and, therefore, it is inversely related with the level of economic development. Initially rich economies benefit from an initially low intensity of the minimum consumption requirements and, as a consequence, these economies end up exhibiting balanced growth of aggregate variables, while there is structural change. In contrast, initially poor economies suffer from an initially large intensity of the minimum consumption requirements, which makes the growth of the aggregate variables unbalanced during a very large period. These economies may never exhibit simultaneously balanced growth of aggregate variables and structural change.

Confirmatory factor analysis of an integrated model of psycopathology assessed with MMPI-2-RF and the MCMI-III

We presented an integrated hierarchical model of psychopathology that more accurately captures empirical patterns of comorbidity between clinical syndromes and personality disorders.In order to verify the structural validity of the model proposed, this study aimed to analyze the convergence between the Restructured Clinical (RC) scales and Personality scales (PSY-5) of the MMPI-2-RF and the Clinical Syndrome and Personality Disorder scales of the MCMI-III.The MMPI-2-RF and MCMI-III were administered to a clinical sample of 377 outpatients (167 men and 210 women).The structural hypothesiswas assessed by using a Confirmatory Factor Analytic design with four common superordinate factors. An independent-cluster-basis solution was proposed based on maximum likelihood estimation and the application of several fit indices.The fit of the proposed model can be considered as good and more so if we take into account its complexity.

Software for interpolation of vegetative growth of yerba mate plants in 3D

The objective of this work was to build mock-ups of complete yerba mate plants in several stages of development, using the InterpolMate software, and to compute photosynthesis on the interpolated structure. The mock-ups of yerba-mate were first built in the VPlants software for three growth stages. Male and female plants grown in two contrasting environments (monoculture and forest understory) were considered. To model the dynamic 3D architecture of yerba-mate plants during the biennial growth interval between two subsequent prunings, data sets of branch development collected in 38 dates were used. The estimated values obtained from the mock-ups, including leaf photosynthesis and sexual dimorphism, are very close to those observed in the field. However, this similarity was limited to reconstructions that included growth units from original data sets. The modeling of growth dynamics enables the estimation of photosynthesis for the entire yerba mate plant, which is not easily measurable in the field. The InterpolMate software is efficient for building yerba mate mock-ups.

Combining digital elevation model analysis and run-out modeling to characterize hazard posed by a potentially unstable rock slope at Turtle Mountain, Alberta, Canada

Turtle Mountain in Alberta, Canada has become an important field laboratory for testing different techniques related to the characterization and monitoring of large slope mass movements as the stability of large portions of the eastern face of the mountain is still questionable. In order to better quantify the volumes potentially unstable and the most probable failure mechanisms and potential consequences, structural analysis and runout modeling were preformed. The structural features of the eastern face were investigated using a high resolution digital elevation model (HRDEM). According to displacement datasets and structural observations, potential failure mechanisms affecting different portions of the mountain have been assessed. The volumes of the different potentially unstable blocks have been calculated using the Sloping Local Base Level (SLBL) method. Based on the volume estimation, two and three dimensional dynamic runout analyses have been performed. Calibration of this analysis is based on the experience from the adjacent Frank Slide and other similar rock avalanches. The results will be used to improve the contingency plans within the hazard area.

Multimodal Investment Analysis Methodology, Phase One: The Conceptual Model, 1998

The purpose of this project is to develop an investment analysis model that integrates the capabilities of four types of analysis for use in evaluating interurban transportation system improvements. The project will also explore the use of new data warehousing and mining techniques to design the types of databases required for supporting such a comprehensive transportation model. The project consists of four phases. The first phase, which is documented in this report, involves development of the conceptual foundation for the model. Prior research is reviewed in Chapter 1, which is composed of three major sections providing demand modeling background information for passenger transportation, transportation of freight (manufactured products and supplies), and transportation of natural resources and agricultural commodities. Material from the literature on geographic information systems makes up Chapter 2. Database models for the national and regional economies and for the transportation and logistics network are conceptualized in Chapter 3. Demand forecasting of transportation service requirements is introduced in Chapter 4, with separate sections for passenger transportation, freight transportation, and transportation of natural resources and commodities. Characteristics and capacities of the different modes, modal choices, and route assignments are discussed in Chapter 5. Chapter 6 concludes with a general discussion of the economic impacts and feedback of multimodal transportation activities and facilities.

Prepupal Building Behavior in Drosophila melanogaster and Its Evolution under Resource and Time Constraints.

Structures built by animals are a widespread and ecologically important 'extended phenotype'. While its taxonomic diversity has been well described, factors affecting short-term evolution of building behavior within a species have received little experimental attention. Here we describe how, given the opportunity, wandering Drosophila melanogaster larvae often build long tunnels in agar substrates and embed their pupae within them. These embedded larvae are characterized by a longer egg-to-pupariation developmental time than larvae that pupate on the surface. Assuming that such building behaviors are likely to be energetically costly and/or time consuming, we hypothesized that they should evolve to be less pronounced under resource or time limitation. In accord with this prediction, larvae from populations evolved for 160 generations under a regime that combines larval malnutrition with limited developmental time dug shorter tunnels than larvae from control unselected populations. However, the proportion of larvae that embedded before pupation did not differ between the malnutrition-adapted and control populations, suggesting that tunnel length and likelihood of embedding before pupation are controlled by different genetic loci. The behaviors exhibited by wandering larvae of Drosophila melanogaster prior to pupation offer a model system to study evolution of animal building behaviors because the tunneling and embedding phenotypes are simple, facultative and highly variable.

Modeling and mitigation of supply-demand mismatches

In this thesis, I develop analytical models to price the value of supply chain investments under demand uncer¬tainty. This thesis includes three self-contained papers. In the first paper, we investigate the value of lead-time reduction under the risk of sudden and abnormal changes in demand forecasts. We first consider the risk of a complete and permanent loss of demand. We then provide a more general jump-diffusion model, where we add a compound Poisson process to a constant-volatility demand process to explore the impact of sudden changes in demand forecasts on the value of lead-time reduction. We use an Edgeworth series expansion to divide the lead-time cost into that arising from constant instantaneous volatility, and that arising from the risk of jumps. We show that the value of lead-time reduction increases substantially in the intensity and/or the magnitude of jumps. In the second paper, we analyze the value of quantity flexibility in the presence of supply-chain dis- intermediation problems. We use the multiplicative martingale model and the "contracts as reference points" theory to capture both positive and negative effects of quantity flexibility for the downstream level in a supply chain. We show that lead-time reduction reduces both supply-chain disintermediation problems and supply- demand mismatches. We furthermore analyze the impact of the supplier's cost structure on the profitability of quantity-flexibility contracts. When the supplier's initial investment cost is relatively low, supply-chain disin¬termediation risk becomes less important, and hence the contract becomes more profitable for the retailer. We also find that the supply-chain efficiency increases substantially with the supplier's ability to disintermediate the chain when the initial investment cost is relatively high. In the third paper, we investigate the value of dual sourcing for the products with heavy-tailed demand distributions. We apply extreme-value theory and analyze the effects of tail heaviness of demand distribution on the optimal dual-sourcing strategy. We find that the effects of tail heaviness depend on the characteristics of demand and profit parameters. When both the profit margin of the product and the cost differential between the suppliers are relatively high, it is optimal to buffer the mismatch risk by increasing both the inventory level and the responsive capacity as demand uncertainty increases. In that case, however, both the optimal inventory level and the optimal responsive capacity decrease as the tail of demand becomes heavier. When the profit margin of the product is relatively high, and the cost differential between the suppliers is relatively low, it is optimal to buffer the mismatch risk by increasing the responsive capacity and reducing the inventory level as the demand uncertainty increases. In that case, how¬ever, it is optimal to buffer with more inventory and less capacity as the tail of demand becomes heavier. We also show that the optimal responsive capacity is higher for the products with heavier tails when the fill rate is extremely high.

Rice yield estimation based on weather conditions and on technological level of production systems in Brazil

The objective of this work was to evaluate an estimation system for rice yield in Brazil, based on simple agrometeorological models and on the technological level of production systems. This estimation system incorporates the conceptual basis proposed by Doorenbos & Kassam for potential and attainable yields with empirical adjusts for maximum yield and crop sensitivity to water deficit, considering five categories of rice yield. Rice yield was estimated from 2000/2001 to 2007/2008, and compared to IBGE yield data. Regression analyses between model estimates and data from IBGE surveys resulted in significant coefficients of determination, with less dispersion in the South than in the North and Northeast regions of the country. Index of model efficiency (E1') ranged from 0.01 in the lower yield classes to 0.45 in higher ones, and mean absolute error ranged from 58 to 250 kg ha‑1, respectively.

Towards a dynamic model of e-commerce: environmental, technological and organisational drivers of B2C along time

Despite the important benefits for firms of commercial initiatives on the Internet, e-commerce is still an emerging distribution channel, even in developed countries. Thus, more needs to be known about the mechanisms affecting its development. A large number of works have studied firms¿ e-commerce adoption from technological, intraorganizational, institutional, or other specific perspectives, but there is a need for adequately tested integrative frameworks. Hence, this work proposes and tests a model of firms¿ business-to-consumer (called B2C) e-commerce adoption that is founded on a holistic vision of the phenomenon. With this integrative approach, the authors analyze the joint influence of environmental, technological, and organizational factors; moreover, they evaluate this effect over time. Using various representative Spanish data sets covering the period 1996-2005, the findings demonstrate the suitability of the holistic framework. Likewise, some lessons are learned from the analysis of the key building blocks. In particular, the current study provides evidence for the debate about the effect of competitive pressure, since the findings show that competitive pressure disincentivizes e-commerce adoption in the long term. The results also show that the development or enrichment of the consumers¿ consumption patterns, the technological readiness of the market forces, the firm¿s global scope, and its competences in innovation continuously favor e-commerce adoption.

Secure Dynamic MANET On-demand (SEDYMO) Routing Protocol

This paper describes the state of the art of secure ad hoc routing protocols and presents SEDYMO, a mechanism to secure a dynamic multihop ad hoc routing protocol. The proposed solution defeats internal and external attacks usinga trustworthiness model based on a distributed certification authority. Digital signatures and hash chains are used to ensure the correctness of the protocol. The protocol is compared with other alternatives in terms of security strength, energy efficiency and time delay. Both computational and transmission costs are considered and it is shown that the secure protocol overhead is not a critical factor compared to the high network interface cost.