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Case-crossover designs have been widely applied to epidemiological and medical investigations of associations between short-term exposures and risk of acute adverse health events. Much effort has been made in literature on understanding source of confounding and reducing systematic bias by reference-select strategies. In this paper, we explored the nature of bias in the ambi-directional and time-stratified case-crossover designs via simulation using actual air pollution data from urban Edmonton, Alberta, Canada. We further proposed a calibration approach for eliminating systematic bias in estimates (coefficient estimate, 95% confident interval, and p-value). Bias check for coefficient estimation, size check and power check for significance test were done via simulation experiments to show advantages of the calibrated case-crossover studies over the ones without calibration. An application was done to investigate associations between air pollutants and acute myocardial infarction hospitalizations in urban Edmonton. In conclusion, systematic bias in a case-crossover design is often unavoidable, leading to an obvious bias in the estimated effect and an unreliable p value in the significance test. The proposed calibration technique provides an efficient approach to eliminating systematic bias in a case-crossover study. [ABSTRACT FROM AUTHOR]

Aim: This paper outlines the transformation of youth mental health services in Edmonton, Alberta, a large city in Western Canada. We describe the processes and challenges involved in restructuring how services and care are delivered to youth (11‐25 years old) with mental health needs based on the objectives of the pan‐Canadian ACCESS Open Minds network. Methods: We provide a narrative review of how youth mental health services have developed since our engagement with the ACCESS Open Minds initiative, based on its five central objectives of early identification, rapid access, appropriate care, continuity of care, and youth and family engagement. Results: Building on an initial community mapping exercise, a service network has been developed; teams that were previously age‐oriented have been integrated together to seamlessly cover the age 11 to 25 range; early identification has thus far focused on high‐school populations; and an actual drop‐in space facilitates rapid access and linkages to appropriate care within the 30‐day benchmark. Conclusions: Initial aspects of the transformation have relied on restructuring and partnerships that have generated early successes. However, further transformation over the longer term will depend on data demonstrating how this has impacted clinical outcomes and service utilization. Ultimately, sustainability in a large urban centre will likely involve scaling up to a network of similar services to cover the entire population of the city. [ABSTRACT FROM AUTHOR]

This paper examines the demand for hockey game trips among metropolitan and nonmetropolitan residents of Alberta, Canada. Using data on both revealed and stated preference game-trip behavior from a telephone survey conducted throughout Alberta, we estimate the effect of ticket prices, team quality, arena amenities, and capacity on the latent demand for National Hockey League hockey games. We find that lower ticket prices, higher team quality, and additional capacity encourage attendance. In the status quo scenario, consumer surplus per game is $50 for those who had attended hockey games and about 50% less for those who had not attended games. Exploiting the stated preference data, we develop a number of other consumer surplus estimates. We also include travel costs in the estimation of the demand function and estimate the full value of the game trip considering both ticket prices and travel costs. Sold-out arenas in Calgary and Edmonton generate annual consumption benefits of $40 and $35 million when only ticket prices are used to calculate consumer surplus (i.e., excluding travel costs). Considering the full-price consumer surplus for the Calgary Flames of $103 per game trip, the annual consumption benefits may be as high as $82 million. [ABSTRACT FROM AUTHOR]

This paper reviews the factors and criteria for the design of new and the retrofitting of existing dry detention ponds to enhance removal of total suspended solids (TSS) from stormwater. Detention time is discussed as the most important factor affecting TSS removal. Two-stage facilities and multi-level outlet design are important means of enhancing TSS removal in dry ponds. Two dry ponds within the city of Edmonton were selected to evaluate their TSS removal. The level of expected TSS removal is low owing to the relatively short detention times for both ponds. Methods for retrofitting the dry ponds to enhance TSS removal are discussed.Key words: dry pond, stormwater, TSS removal, detention time, retrofitting.Cet article passe en revue les facteurs et critères de conception de nouveaux étangs de rétention, et de modification de ceux déjà existants, avec pour but d'améliorer la capacité d'enlèvement des substances solides totales en suspension (SST) contenues dans les eaux de ruissellement. Le temps de rétention est examiné en tant que facteur principal affectant l'enlèvement des SST. Les installations à deux étages et la conception de sorties multi-niveaux sont des procédés importants qui améliorent l'enlèvement des SST dans les étangs. Deux étangs de la Ville d'Edmonton ont été sélectionnés et leur capacité de rétention a été évaluée. Le niveau d'enlèvement des SST escompté est bas compte-tenu des temps de rétention relativement courts de ces deux étangs. Les méthodes de modification des étangs visant à améliorer l'enlèvement des SST sont examinées.Mots clés : étang, eaux de ruissellement, enlèvement des SST, temps de rétention, réajustement.[Traduit par la Rédaction] [ABSTRACT FROM AUTHOR]

Provides summaries of several papers presented on Department of Medicine Research Day at the University of Alberta in May 2001. `Survey of Perioperative Care by Canadian General Internists,' by T.H. Taher et al; `Implications of Antinuclear Antibody Positivity in Healthy Individuals,' by S.O. Myckatyn et al; `Prevalence and Prediction of Metabolic Bone Disease in Chronic Liver Disease,' by J.C. McDermid et al.

This paper examines the precipitous drop in crime rates in Edmonton reported over the past two years. Previous analysis shows that the major reasons for changes in crime rates include: reduction in the numbers of the at-risk population: deterioration in the social and economic climate: changes in laws; alterations in access to police; and changes in the proactive nature of policing. The results of analysis of data drawn from official files and community surveys from one city indicate that the drop in crime rates are a function of declines in property crime reporting: administrative decisions taken to alter the access to police resources for the public; and a shift towards community policing with an emphasis on problem solving and crime prevention. [ABSTRACT FROM AUTHOR]

The article focuses on the program for the annual meeting of the Phycological Society of America. The meeting will be held at the University of Alberta, Edmonton, Alberta, in Canada, from June 20-24, 1971. The chairmen of the program will be Harold C. Bold and Louis Druehl. All sessions of the program at which contributed papers, lectures and the symposium are presented are scheduled as joint sessions of the Phycological Society of America, the Phycological Section of the Canadian Botanical Association and the Phycological Section of the Botanical Society of America.

Announces the 95th annual meeting of the Poultry Science Association, Inc. slated in July 16 to 19, 2006 at Alberta, Edmonton, Canada. Program chairmen; Papers and Presentation; Participants.

In the past few years, artificial neural networks (ANNs) have been used in describing and modelling wastewater treatment processes. Artificial neural network models can be identified without a detailed knowledge of the kinetics of the system to be modelled. Also, ANN models can potentially contain a great deal of information about the system itself, including the same type of information contained in conventional deterministic models. The fact that these models can be continuously updated with minimal resource requirements makes them very attractive for application in a real-time control scenario. In the current paper, applications of ANNs in the field of wastewater treatment performance prediction are reviewed. In addition, this paper presents a case study that reports some comprehensive modelling work to develop nonlinear neural network prediction models for the Gold Bar Wastewater Treatment Plant (GBWWTP), the largest sewage treatment facility in Edmonton, Alberta. [ABSTRACT FROM AUTHOR]

Artificial neural network (ANN) technology has evolved from the experimental stage into actual industrial applications. To achieve this significant transition, careful planning and adjustment are required. This paper illustrates such an example in the water treatment industry. The project objective is to upgrade the ANN models from a previous research project and install the system on-line in the Rossdale Water Treatment Plant in Edmonton, Alberta, Canada, to forecast raw water colour one day ahead. The article discusses the important issues and techniques to upgrade the neural network model to the actual application. Furthermore, sufficient communication is also required between the designers and the users to address the applicability and user friendly issues in model implementation. Failure in communication can render the whole process ineffective. Possible improvements are also recommended for the future on-line applications. [ABSTRACT FROM AUTHOR]

This paper examines the application of the artificial neural network (ANN) modeling technique to model a lime softening process at a full-scale drinking water treatment facility. The modeling was done for the Rossdale Water Treatment Plant (WTP) operated by EPCOR Water Services Inc. in Edmonton, Alberta. It was determined that ANN can model a lime clarifier accurately and with superior performance to other modeling methods. During the development stage, a prediction of alum clarifier pH also becomes necessary, and a very accurate inferential (virtual) sensor for pH was developed using ANN. The ANN models were also integrated with the Supervisory Control and Data Acquisition (SCADA) system of the plant so that real-time predictions of lime doses and effluent total hardness could be monitored. It was shown that the performance of the ANN models that were developed using average daily values for the parameters also work well when they are executed in real time. [ABSTRACT FROM AUTHOR]

This paper reports on the application of artificial neural network (ANN) techniques for predicting the concentration of trihalomethanes (THMs) in finished water at the E.L. Smith Water Treatment Plant (WTP) in Edmonton, Alberta, Canada. The formation of THMs in finished water involves many complex chemical reactions and interactions that are difficult to model using conventional methods. The formation of THMs has been found to be correlated to raw and treated water quality characteristics such as colour, pH, and temperature and chemical addition such as chlorine, alum, and powder activated carbon (PAC). Three models were derived using raw water, post clarification water, and a combination of raw and post clarification water parameter inputs. The model that most successfully predicted the concentration of THMs in finished water is the model that uses clarifier effluent parameter inputs. This model can be used at the E.L. Smith WTP for early detection of potentially high THM concentrations in finished water and gives plant operators enough advanced warning to reduce THM precursors. With an adequate understanding of water treatment plant processes and THM formation potential it will be fairly easy for any water treatment facility, which has a few years of historical plant data, to develop its own ANN model for predicting the formation of THM in finished water. [ABSTRACT FROM AUTHOR]