949 resultados para African Development
Resumo:
In this paper, we provide specific examples of the educational promises and problems that arise as multiliteracies pedagogical initiatives encounter conventional institutional beliefs and practices in mainstream schooling. This paper documents and characterizes the ways in which two specific digital learning initiatives were played out in two distinctive traditional schooling contexts, as experienced by two different student groups: one comprising an elite mainstream and the other an excluded minority. By learning from the instructive complications that arose out of attempts by innovative and well-meaning educators to provide students with more relevant learning experiences than currently exist in mainstream schooling, this paper contributes fresh perspectives and more nuanced understandings of how diverse learners and their teachers negotiate the opportunities and challenges of the New London Group's vision of a multiliteracies approach to literacy and learning. We conclude by arguing that, where multiliteracies are understood as “garnish” to the “pedagogical roast” of traditional code-based and print-based academic literacies, they will continue to work on the sidelines of mainstream schooling and be seen only as either useful extensions or helpful interventions for high-performing and at-risk students respectively.
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It has previously been found that complexes comprised of vitronectin and growth factors (VN:GF) enhance keratinocyte protein synthesis and migration. More specifically, these complexes have been shown to significantly enhance the migration of dermal keratinocytes derived from human skin. In view of this, it was thought that these complexes may hold potential as a novel therapy for healing chronic wounds. However, there was no evidence indicating that the VN:GF complexes would retain their effect on keratinocytes in the presence of chronic wound fluid. The studies in this thesis demonstrate for the first time that the VN:GF complexes not only stimulate proliferation and migration of keratinocytes, but also these effects are maintained in the presence of chronic wound fluid in a 2-dimensional (2-D) cell culture model. Whilst the 2-D culture system provided insights into how the cells might respond to the VN:GF complexes, this investigative approach is not ideal as skin is a 3-dimensional (3-D) tissue. In view of this, a 3-D human skin equivalent (HSE) model, which reflects more closely the in vivo environment, was used to test the VN:GF complexes on epidermopoiesis. These studies revealed that the VN:GF complexes enable keratinocytes to migrate, proliferate and differentiate on a de-epidermalised dermis (DED), ultimately forming a fully stratified epidermis. In addition, fibroblasts were seeded on DED and shown to migrate into the DED in the presence of the VN:GF complexes and hyaluronic acid, another important biological factor in the wound healing cascade. This HSE model was then further developed to enable studies examining the potential of the VN:GF complexes in epidermal wound healing. Specifically, a reproducible partial-thickness HSE wound model was created in fully-defined media and monitored as it healed. In this situation, the VN:GF complexes were shown to significantly enhance keratinocyte migration and proliferation, as well as differentiation. This model was also subsequently utilized to assess the wound healing potential of a synthetic fibrin-like gel that had previously been demonstrated to bind growth factors. Of note, keratinocyte re-epitheliasation was shown to be markedly improved in the presence of this 3-D matrix, highlighting its future potential for use as a delivery vehicle for the VN:GF complexes. Furthermore, this synthetic fibrin-like gel was injected into a 4 mm diameter full-thickness wound created in the HSE, both keratinocytes and fibroblasts were shown to migrate into this gel, as revealed by immunofluorescence. Interestingly, keratinocyte migration into this matrix was found to be dependent upon the presence of the fibroblasts. Taken together, these data indicate that reproducible wounds, as created in the HSEs, provide a relevant ex vivo tool to assess potential wound healing therapies. Moreover, the models will decrease our reliance on animals for scientific experimentation. Additionally, it is clear that these models will significantly assist in the development of novel treatments, such as the VN:GF complexes and the synthetic fibrin-like gel described herein, ultimately facilitating their clinical trial in the treatment of chronic wounds.
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Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This final report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.
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This is a review of the book titled 'Rebuilding Native Nations. Strategies Governance and Development', edited by Miriam Jorgensen.
Resumo:
Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This Industry focused report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.
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The Co-operative Research Centre for Construction Innovation (CRC-CI) is funding a project known as Value Alignment Process for Project Delivery. The project consists of a study of best practice project delivery and the development of a suite of products, resources and services to guide project teams towards the best procurement approach for a specific project or group of projects. These resources will be focused on promoting the principles that underlie best practice project delivery rather than simply identifying an off-the-shelf procurement system. This project builds on earlier work by Sidwell, Kennedy and Chan (2002), on re-engineering the construction delivery process, which developed a procurement framework in the form of a Decision Matrix
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Construction sector application of Lead Indicators generally and Positive Performance Indicators (PPIs) particularly, are largely seen by the sector as not providing generalizable indicators of safety effectiveness. Similarly, safety culture is often cited as an essential factor in improving safety performance, yet there is no known reliable way of measuring safety culture. This paper proposes that the accurate measurement of safety effectiveness and safety culture is a requirement for assessing safe behaviours, safety knowledge, effective communication and safety performance. Currently there are no standard national or international safety effectiveness indicators (SEIs) that are accepted by the construction industry. The challenge is that quantitative survey instruments developed for measuring safety culture and/ or safety climate are inherently flawed methodologically and do not produce reliable and representative data concerning attitudes to safety. Measures that combine quantitative and qualitative components are needed to provide a clear utility for safety effectiveness indicators.
Resumo:
The aim of this project is to develop a systematic investment decision-making framework for infrastructure asset management by incorporation economic justification, social and environmental consideration in the decision-making process. This project assesses the factors that are expected to provide significant impacts on the variability of expenditures. A procedure for assessing risk and reliability for project investment appraisals will be developed. The project investigates public perception, social and environmental impacts on road infrastructure investment. This research will contribute to the debate about how important social and environmental issues should be incorporated into the investment decision-making process for infrastructure asset management.
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Objectives The objectives of this project were two-fold: • Assess the ease with which current architectural CAD systems supported the use ofparametric descriptions in defining building shape, engineering system performance and cost at the early stages of building design; • Assess the feasibility of implementing a software decision support system that allowed designers to trade-off the characteristics and configuration of various engineering systems to move towards a “global optimum” rather than considering each system in isolation and expecting humans to weigh up all of the costs and benefits. The first stage of the project consisted of using four different CAD systems to define building shells (envelopes) with different usages. These models were then exported into a shared database using the IFC information exchange specifications. The second stage involved the implementation of small computer programs that were able to estimate relevant system parameters based on performance requirements and the constraints imposed by the other systems. These are presented in a unified user interface that extracts the appropriate building shape parameters from the shared database Note that the term parametric in this context refers to the relationships among and between all elements of the building model - not just geometric associations - which will enable the desired coordination.
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Belonging to an online community offers teachers the opportunity to exchange ideas, make connections with a wider peer group and form collaborative networks. The increasing popularity of teacher professional communities means that we need to understand how they work and determine the role they may play in teacher professional development. This chapter will map data from a doctoral study to a recentlydeveloped model of professional development to offer a new perspective of how online communities can add to a teacher’s personal and professional growth and, in so doing, add to the small number of studies in this field. This chapter will conclude with a call for a revision of the way we approach professional development in the 21st century and suggest that old models and metaphors are hindering the adoption of more effective means of professional development for teachers.
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- This paper presents a validation proposal for development of diagnostic and prognostic algorithms for SF6 puffer circuit-breakers reproduced from actual site waveforms. The re-ignition/restriking rates are duplicated in given circuits and the cumulative energy dissipated in interrupters by the restriking currents. The targeted objective is to provide a simulated database for diagnosis of re-ignition/restrikes relating to the phase to earth voltage and the number of re-ignition/restrikes as well as estimating the remaining life of SF6 circuit-breakers. The model-based diagnosis of a tool will be useful in monitoring re-ignition/restrikes as well as predicting a nozzle’s lifetime. This will help ATP users with practical study cases and component data compilation for shunt reactor switching and capacitor switching. This method can be easily applied with different data for the different dielectric curves of circuit breakers and networks. This paper presents modelling details and some of the available cases, required project support, the validation proposal, the specific plan for implementation and the propsed main contributions.
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Principal Topic Small and micro-enterprises are believed to play a significant part in economic growth and poverty allevition in developing countries. However, there are a range of issues that arise when looking at the support required for local enterprise development, the role of micro finance and sustainability. This paper explores the issues associated with the establishment and resourcing of micro-enterprise develoment and proposes a model of sustainable support of enterprise development in very poor developing economies, particularly in Africa. The purpose of this paper is to identify and address the range of issues raised by the literature and empirical research in Africa, regarding micro-finance and small business support, and to develop a model for sustainable support for enterprise development within a particular cultural and economic context. Micro-finance has become big business with a range of models - from those that operate on a strictly business basis to those that come from a philanthropic base. The models used grow from a range of philosophical and cultural perspectives. Entrepreneurship training is provided around the world. Success is often measured by the number involved and the repayment rates - which are very high, largely because of the lending models used. This paper will explore the range of options available and propose a model that can be implemented and evaluated in rapidly changing developing economies. Methodology/Key Propositions The research draws on entrepreneurial and micro-finance literature and empirical research undertaken in Mozambique, which lies along the Indian ocean sea border of Southern Africa. As a result of war and natural disasters over a prolonged period, there is little industry, primary industries are primitive and there is virtually no infrastructure. Mozambique is ranked as one of the poorest countries in the world. The conditions in Mozambique, though not identical, reflect conditions in many other parts of Africa. A numebr of key elements in the development of enterprises in poor countries are explored including: Impact of micro-finance Sustainable models of micro-finance Education and training Capacity building Support mechanisms Impact on poverty, families and the local economy Survival entrepreneurship versus growth entrepreneurship Transitions to the formal sector. Results and Implications The result of this study is the development of a model for providing intellectual and financial resources to micro-entrepreneurs in poor developing countries in a sustainable way. The model provides a base for ongoing research into the process of entrepreneurial growth in African developing economies. The research raises a numeber of issues regarding sustainability including the nature of the donor/recipient relationship, access to affordable resources, the impact of individual entrepreneurial activity on the local economny and the need for ongoing research to understand the whole process and its impact, intended and unintended.