Carleton University

About: Carleton University is a education organization based out in Ottawa, Ontario, Canada. It is known for research contribution in the topics: Population & Large Hadron Collider. The organization has 15852 authors who have published 39650 publications receiving 1106610 citations.

A critical evaluation of the specificity of aniline blue induced fluorescence

Abstract: Commercial aniline blue dyes are heterogeneous and variable. We have isolated and purified the fluorochrome from water soluble aniline blue. This fluorochrome fluoresces weakly with a maximum emission around 455 nm but the fluorescence is shifted to longer wavelengths (500–506 nm) when complexed with isolated β-1,3-glucans, cellulose or mixed-linked glucans. A similar intense fluorescence is observed in sieve plates, new cell walls and around pitfields in the presence of the fluorochrome. The fluorescence induced by the aniline blue fluorochrome does not specifically indicate the presence of β-1,3-glucans. Indeed most wall features are induced to fluoresce to some extent by the fluorochrome. However, fluorescence is modified by lignins and phenolics. Furthermore the intense fluorescence induced in the traditional “callose” sites, sieve plates, around pitfields and in new cell walls is probably related to localized differences in the structural packing of wall polymers.

A comprehensive evaluation of capture-recapture models for estimating software defect content

Abstract: An important requirement to control the inspection of software artifacts is to be able to decide, based on more objective information, whether the inspection can stop or whether it should continue to achieve a suitable level of artifact quality. A prediction of the number of remaining defects in an inspected artifact can be used for decision making. Several studies in software engineering have considered capture-recapture models to make a prediction. However, few studies compare the actual number of remaining defects to the one predicted by a capture-recapture model on real software engineering artifacts. The authors focus on traditional inspections and estimate, based on actual inspections data, the degree of accuracy of relevant state-of-the-art capture-recapture models for which statistical estimators exist. In order to assess their robustness, we look at the impact of the number of inspectors and the number of actual defects on the estimators' accuracy based on actual inspection data. Our results show that models are strongly affected by the number of inspectors, and therefore one must consider this factor before using capture-recapture models. When the number of inspectors is too small, no model is sufficiently accurate and underestimation may be substantial. In addition, some models perform better than others in a large number of conditions and plausible reasons are discussed. Based on our analyses, we recommend using a model taking into account that defects have different probabilities of being detected and the corresponding Jackknife Estimator. Furthermore, we calibrate the prediction models based on their relative error, as previously computed on other inspections. We identified theoretical limitations to this approach which were then confirmed by the data.

Managing correctional treatment for reduced recidivism: A meta-analytic review of programme integrity

Abstract: Purpose. Although issues surrounding programme integrity and implementation seem intuitively appealing as important contributors to effective correctional programming, they have been relatively ignored within the extant literature. The present meta-analysis provided the first systematic examination of these issues by exploring their impact on recidivism reduction in correctional treatment programmes.Methods. A meta-analysis was conducted on 273 tests of the effectiveness of correctional treatment programmes that were extracted from various human service programmes. Indicators of programme integrity reviewed included several management variables (i.e. selection, training and clinical supervision of service deliverers), evaluator involvement, presence of training manuals, monitoring of treatment delivery, and using a small sample of clients.Results. Overall, the meta-analyses revealed that programme integrity provided an independent source of enhanced programme effectiveness, even when controls were introduced for other variables (e.g. involved evaluator and sample size).Conclusions. Consistent with previous research, the present study demonstrated that the positive contributions of programme integrity were limited to the enhancement of the effects of human service programmes consistent with the principles of risk, need, and general responsivity. However, the relatively poor reporting of programme integrity indicators within primary studies necessitates that evaluators and programme deliverers alike ensure that this information is included in future evaluations to provide an even greater understanding of the influences of integrity. Language: en

Technology Entrepreneurship: Overview, Definition, and Distinctive Aspects

Abstract: Technology entrepreneurship lies at the heart of many important debates, including those around launching and growing firms, regional economic development, selecting the appropriate stakeholders to take ideas to markets, and educating managers, engineers, and scientists. Unless a generally accepted definition of technology entrepreneurship is established, however, these debates lose their focus. The purpose of this article is to identify the themes that dominate the technology entrepreneurship literature, provide a definition of technology entrepreneurship, and identify its distinguishing aspects relative to economics, entrepreneurship, and management. The author argues that technology entrepreneurship is an investment in a project that assembles and deploys specialized individuals and heterogeneous assets to create and capture value for the firm. What distinguishes technology entrepreneurship from other entrepreneurship types (e.g., social entrepreneurship, small business management, and self-employment) is the collaborative experimentation and production of new products, assets, and their attributes, which are intricately related to advances in scientific and technological knowledge and the firm’s asset ownership rights. Don’t let the noise of other’s opinions drown out your own inner voice. And most importantly, have the courage to follow your heart and intuition. They somehow already know what you truly want to become. Everything else is secondary. Steve Jobs (1955–2011) Co-founder of Apple and Pixar