Organizational capacity and knowledge transfer : a qualitative case study of the 2007 Canada Winter Games host society

Understanding and managing the knowledge transfer process in sport organizations is an essential component to enhance organizational capacity. Very little research on either capacity or knowledge transfer within a sport organization exists. Consequently, the purpos e of this qualitative case study was to, examine the transfer of knowledge process within a major games host society. Specifically, two research goals guided the study: 1) To develop a model to explain a knowledge t r ans f e r process in a non-profit ma jor games hos t organization and 2) To examine the relevance of the model to a Canada Games Hos t Society. Data we r e collected from interviews with middle and senior level volunteers as well as senior s t a f f members (n= 27), document s and observations. The findings indicated three barriers to knowledge transfer: structural, systemic, and cultural. As a result of the findings a revised model for knowledge transfer wa s proposed that included modifications related to the direction of knowledge flow, timing of the knowledge transfer process, and group inter-relations. Implications identified the importance of intuition managers, time and organizational levels for successful knowledge transfer. Recommendations for future host societies and the Canada Games Council are presented.

Oxygen exchange in galls of Eurosta solidaginis (Diptera: Tephritidae)

Hypoxia in plant tissue should affect animals living within. Gallmakers stimulate their plant hosts to produce the gall they inhabit and feed on, and also influence the gall phenotype for other adaptations, such as defense against predators. The potential for hypoxia in galls of Eurosta solidaginis was studied in the context of potential adaptations to gall oxygen level, using a combination of direct measurement, mathematical modelling, and respirometry on both gallmakers and hosts. Modelling results suggested mild hypoxia tolerable to the larva persists for most of the growth season, whereas more severe hypoxia may occur earlier in fully-grown young galls. Field data from one of the two years studied showed hypoxia more severe than expected, and coincided with adverse weather conditions and high larval mortality. The hypoxia may be related to host response to adverse weather. Whether hypoxia directly caused larval mortality requires further study.

Variability in the Insect and Plant Adhesins, Mad1 and Mad2, within the Fungal Genus Metarhizium Suggest Plant Adaptation as an Evolutionary Force

Several species of the insect pathogenic fungus Metarhizium are associated with certain plant types and genome analyses suggested a bifunctional lifestyle; as an insect pathogen and as a plant symbiont. Here we wanted to explore whether there was more variation in genes devoted to plant association (Mad2) or to insect association (Mad1) overall in the genus Metarhizium. Greater divergence within the genus Metarhizium in one of these genes may provide evidence for whether host insect or plant is a driving force in adaptation and evolution in the genus Metarhizium. We compared differences in variation in the insect adhesin gene, Mad1, which enables attachment to insect cuticle, and the plant adhesin gene, Mad2, which enables attachment to plants. Overall variation for the Mad1 promoter region (7.1%), Mad1 open reading frame (6.7%), and Mad2 open reading frame (7.4%) were similar, while it was higher in the Mad2 promoter region (9.9%). Analysis of the transcriptional elements within the Mad2 promoter region revealed variable STRE, PDS, degenerative TATA box, and TATA box-like regions, while this level of variation was not found for Mad1. Sequences were also phylogenetically compared to EF-1a, which is used for species identification, in 14 isolates representing 7 different species in the genus Metarhizium. Phylogenetic analysis demonstrated that the Mad2 phylogeny is more congruent with 59 EF-1a than Mad1. This would suggest that Mad2 has diverged among Metarhizium lineages, contributing to clade- and species-specific variation, while it appears that Mad1 has been largely conserved. While other abiotic and biotic factors cannot be excluded in contributing to divergence, these results suggest that plant relationships, rather than insect host, have been a major driving factor in the divergence of the genus Metarhizium.

Cognitive Behavior Therapy for Obsessive-Compulsive Behavior in Children with Autism Spectrum Disorder: A Comparison of Hierarchical Linear Modelling and Visual Analysis

Behavioral researchers commonly use single subject designs to evaluate the effects of a given treatment. Several different methods of data analysis are used, each with their own set of methodological strengths and limitations. Visual inspection is commonly used as a method of analyzing data which assesses the variability, level, and trend both within and between conditions (Cooper, Heron, & Heward, 2007). In an attempt to quantify treatment outcomes, researchers developed two methods for analysing data called Percentage of Non-overlapping Data Points (PND) and Percentage of Data Points Exceeding the Median (PEM). The purpose of the present study is to compare and contrast the use of Hierarchical Linear Modelling (HLM), PND and PEM in single subject research. The present study used 39 behaviours, across 17 participants to compare treatment outcomes of a group cognitive behavioural therapy program, using PND, PEM, and HLM on three response classes of Obsessive Compulsive Behaviour in children with Autism Spectrum Disorder. Findings suggest that PEM and HLM complement each other and both add invaluable information to the overall treatment results. Future research should consider using both PEM and HLM when analysing single subject designs, specifically grouped data with variability.

Variability in the Insect and Plant Adhesins, Mad1 and Mad2, within the Fungal Genus Metarhizium Suggest Plant Adaptation as an Evolutionary Force

Several species of the insect pathogenic fungus Metarhizium are associated with certain plant types and genome analyses suggested a bifunctional lifestyle; as an insect pathogen and as a plant symbiont. Here we wanted to explore whether there was more variation in genes devoted to plant association (Mad2) or to insect association (Mad1) overall in the genus Metarhizium. Greater divergence within the genus Metarhizium in one of these genes may provide evidence for whether host insect or plant is a driving force in adaptation and evolution in the genus Metarhizium. We compared differences in variation in the insect adhesin gene, Mad1, which enables attachment to insect cuticle, and the plant adhesin gene, Mad2, which enables attachment to plants. Overall variation for the Mad1 promoter region (7.1%), Mad1 open reading frame (6.7%), and Mad2 open reading frame (7.4%) were similar, while it was higher in the Mad2 promoter region (9.9%). Analysis of the transcriptional elements within the Mad2 promoter region revealed variable STRE, PDS, degenerative TATA box, and TATA box-like regions, while this level of variation was not found for Mad1. Sequences were also phylogenetically compared to EF-1a, which is used for species identification, in 14 isolates representing 7 different species in the genus Metarhizium. Phylogenetic analysis demonstrated that the Mad2 phylogeny is more congruent with 59 EF-1a than Mad1. This would suggest that Mad2 has diverged among Metarhizium lineages, contributing to clade- and species-specific variation, while it appears that Mad1 has been largely conserved. While other abiotic and biotic factors cannot be excluded in contributing to divergence, these results suggest that plant relationships, rather than insect host, have been a major driving factor in the divergence of the genus Metarhizium.

Mathematical modelling in mathematics education and instruction

This paper aims at giving a concise survey of the present state-of-the-art of mathematical modelling in mathematics education and instruction. It will consist of four parts. In part 1, some basic concepts relevant to the topic will be clarified and, in particular, mathematical modelling will be defined in a broad, comprehensive sense. Part 2 will review arguments for the inclusion of modelling in mathematics teaching at schools and universities, and identify certain schools of thought within mathematics education. Part 3 will describe the role of modelling in present mathematics curricula and in everyday teaching practice. Some obstacles for mathematical modelling in the classroom will be analysed, as well as the opportunities and risks of computer usage. In part 4, selected materials and resources for teaching mathematical modelling, developed in the last few years in America, Australia and Europe, will be presented. The examples will demonstrate many promising directions of development.

Enterprise Modelling Approach based on Maturity and Business Scope perspectives

This paper introduces a framework that supports users to implement enterprise modelling within collaborative companies. These enterprise models are the basis for a holistic interoperability measurement and management methodology which will be presented in the second part of the paper. The discipline of enterprise modelling aims at capturing all dimensions of an enterprise in a simplified model. Thus enterprise models are the appropriate basis for managing collaborative enterprise as they reduce the complexity of interoperability problems. Therefore, a first objective of this paper is to present an approach that enables companies to get the most effect out of enterprise modelling in a collaborative environment based on the maturity of their organisation relative to modelling. Within this first step, the user will get recommendations e.g. for the correct modelling language as well as the right level of detail.

Modelling structural zeros in compositional data

This analysis was stimulated by the real data analysis problem of household expenditure data. The full dataset contains expenditure data for a sample of 1224 households. The expenditure is broken down at 2 hierarchical levels: 9 major levels (e.g. housing, food, utilities etc.) and 92 minor levels. There are also 5 factors and 5 covariates at the household level. Not surprisingly, there are a small number of zeros at the major level, but many zeros at the minor level. The question is how best to model the zeros. Clearly, models that try to add a small amount to the zero terms are not appropriate in general as at least some of the zeros are clearly structural, e.g. alcohol/tobacco for households that are teetotal. The key question then is how to build suitable conditional models. For example, is the sub-composition of spending excluding alcohol/tobacco similar for teetotal and non-teetotal households? In other words, we are looking for sub-compositional independence. Also, what determines whether a household is teetotal? Can we assume that it is independent of the composition? In general, whether teetotal will clearly depend on the household level variables, so we need to be able to model this dependence. The other tricky question is that with zeros on more than one component, we need to be able to model dependence and independence of zeros on the different components. Lastly, while some zeros are structural, others may not be, for example, for expenditure on durables, it may be chance as to whether a particular household spends money on durables within the sample period. This would clearly be distinguishable if we had longitudinal data, but may still be distinguishable by looking at the distribution, on the assumption that random zeros will usually be for situations where any non-zero expenditure is not small. While this analysis is based on around economic data, the ideas carry over to many other situations, including geological data, where minerals may be missing for structural reasons (similar to alcohol), or missing because they occur only in random regions which may be missed in a sample (similar to the durables)

Knowledge integration within an applied mobile robot summer course

This paper presents the use of a mobile robot platform as an innovative educational tool in order to promote and integrate different curriculum knowledge. Hence, it is presented the acquired experience within a summer course named ldquoapplied mobile roboticsrdquo. The main aim of the course is to integrate different subjects as electronics, programming, architecture, perception systems, communications, control and trajectory planning by using the educational open mobile robot platform PRIM. The summer course is addressed to a wide range of student profiles. However, it is of special interests to the students of electrical and computer engineering around their final academic year. The summer course consists of the theoretical and laboratory sessions, related to the following topics: design & programming of electronic devices, modelling and control systems, trajectory planning and control, and computer vision systems. Therefore, the clues for achieving a renewed path of progress in robotics are the integration of several knowledgeable fields, such as computing, communications, and control sciences, in order to perform a higher level reasoning and use decision tools with strong theoretical base

Stock return comovements and integration within the Latin American integrated market

Financial integration has been pursued aggressively across the globe in the last fifty years; however, there is no conclusive evidence on the diversification gains (or losses) of such efforts. These gains (or losses) are related to the degree of comovements and synchronization among increasingly integrated global markets. We quantify the degree of comovements within the integrated Latin American market (MILA). We use dynamic correlation models to quantify comovements across securities as well as a direct integration measure. Our results show an increase in comovements when we look at the country indexes, however, the increase in the trend of correlation is previous to the institutional efforts to establish an integrated market in the region. On the other hand, when we look at sector indexes and an integration measure, we find a decreased in comovements among a representative sample of securities form the integrated market.

Stochastic modelling of rainfall from satellite data

Satellite-based rainfall monitoring is widely used for climatological studies because of its full global coverage but it is also of great importance for operational purposes especially in areas such as Africa where there is a lack of ground-based rainfall data. Satellite rainfall estimates have enormous potential benefits as input to hydrological and agricultural models because of their real time availability, low cost and full spatial coverage. One issue that needs to be addressed is the uncertainty on these estimates. This is particularly important in assessing the likely errors on the output from non-linear models (rainfall-runoff or crop yield) which make use of the rainfall estimates, aggregated over an area, as input. Correct assessment of the uncertainty on the rainfall is non-trivial as it must take account of • the difference in spatial support of the satellite information and independent data used for calibration • uncertainties on the independent calibration data • the non-Gaussian distribution of rainfall amount • the spatial intermittency of rainfall • the spatial correlation of the rainfall field This paper describes a method for estimating the uncertainty on satellite-based rainfall values taking account of these factors. The method involves firstly a stochastic calibration which completely describes the probability of rainfall occurrence and the pdf of rainfall amount for a given satellite value, and secondly the generation of ensemble of rainfall fields based on the stochastic calibration but with the correct spatial correlation structure within each ensemble member. This is achieved by the use of geostatistical sequential simulation. The ensemble generated in this way may be used to estimate uncertainty at larger spatial scales. A case study of daily rainfall monitoring in the Gambia, west Africa for the purpose of crop yield forecasting is presented to illustrate the method.

Introduction. Stochastic physics and climate modelling

Finite computing resources limit the spatial resolution of state-of-the-art global climate simulations to hundreds of kilometres. In neither the atmosphere nor the ocean are small-scale processes such as convection, clouds and ocean eddies properly represented. Climate simulations are known to depend, sometimes quite strongly, on the resulting bulk-formula representation of unresolved processes. Stochastic physics schemes within weather and climate models have the potential to represent the dynamical effects of unresolved scales in ways which conventional bulk-formula representations are incapable of so doing. The application of stochastic physics to climate modelling is a rapidly advancing, important and innovative topic. The latest research findings are gathered together in the Theme Issue for which this paper serves as the introduction.

Development and illustrative outputs of the Community Integrated Assessment System (CIAS), a multi-institutional modular integrated assessment approach for modelling climate change.

This paper describes the development and first results of the “Community Integrated Assessment System” (CIAS), a unique multi-institutional modular and flexible integrated assessment system for modelling climate change. Key to this development is the supporting software infrastructure, SoftIAM. Through it, CIAS is distributed between the community of institutions which has each contributed modules to the CIAS system. At the heart of SoftIAM is the Bespoke Framework Generator (BFG) which enables flexibility in the assembly and composition of individual modules from a pool to form coupled models within CIAS, and flexibility in their deployment onto the available software and hardware resources. Such flexibility greatly enhances modellers’ ability to re-configure the CIAS coupled models to answer different questions, thus tracking evolving policy needs. It also allows rigorous testing of the robustness of IA modelling results to the use of different component modules representing the same processes (for example, the economy). Such processes are often modelled in very different ways, using different paradigms, at the participating institutions. An illustrative application to the study of the relationship between the economy and the earth’s climate system is provided.

Assessing nitrogen dynamics in European ecosystems, integrating measurement and modelling: conclusions

This contribution closes this special issue of Hydrology and Earth System Sciences concerning the assessment of nitrogen dynamics in catchments across Europe within a semi-distributed Integrated Nitrogen model for multiple source assessment in Catchments (INCA). New developments in the understanding of the factors and processes determining the concentrations and loads of nitrogen are outlined. The ability of the INCA model to simulate the hydrological and nitrogen dynamics of different European ecosystems is assessed and the results of the first scenario analyses investigating the impacts of deposition, climatic and land-use change on the nitrogen dynamics are summarised. Consideration is given as to how well the model has performed as a generic too] for describing the nitrogen dynamics of European ecosystems across Arctic, Maritime. Continental and Mediterranean climates, its role in new research initiatives and future research requirements.

Transport and distribution of lindane and simazine in a riverine environment: measurements in bed sediments and modelling

Aquatic sediments often remove hydrophobic contaminants from fresh waters. The subsequent distribution and concentration of contaminants in bed sediments determines their effect on benthic organisms and the risk of re-entry into the water and/or leaching to groundwater. This study examines the transport of simazine and lindane in aquatic bed sediments with the aim of understanding the processes that determine their depth distribution. Experiments in flume channels (water flow of 10 cm s(-1)) determined the persistence of the compounds in the absence of sediment with (a) de-ionised water and (b) a solution that had been in contact with river sediment. In further experiments with river bed sediments in light and dark conditions, measurements were made of the concentration of the compounds in the overlying water and the development of bacterial/algal biofilms and bioturbation activity. At the end of the experiments, concentrations in sediments and associated pore waters were determined in sections of the sediment at 1 mm resolution down to 5 mm and then at 10 mm resolution to 50 mm depth and these distributions analysed using a sorption-diffusion-degradation model. The fine resolution in the depth profile permitted the detection of a maximum in the concentration of the compounds in the pore water near the surface, whereas concentrations in the sediment increased to a maximum at the surface itself. Experimental distribution coefficients determined from the pore water and sediment concentrations indicated a gradient with depth that was partly explained by an increase in organic matter content and specific surface area of the solids near the interface. The modelling showed that degradation of lindane within the sediment was necessary to explain the concentration profiles, with the optimum agreement between the measured and theoretical profiles obtained with differential degradation in the oxic and anoxic zones. The compounds penetrated to a depth of 40-50 rum over a period of 42 days. (C) 2004 Society of Chemical Industry.