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Using the example of an industrial site in Edmonton, Alberta, this paper argues that industrial ruins represent instantiations of abstract abandonment, a kind of real abstraction that directly articulates to the logic of capital. Drawing from excavations of the industrial ruins of Mill Creek Ravine, one of the first industrial areas in Edmonton, this paper reveals how sites of abstract abandonment congeal critical histories of both abandonment and its afterlives. The history of these ruins, and the communities that emerged after they were abandoned materialize the failures of capitalist fantasies, as well as the sprouts that grow in its cracks. [ABSTRACT FROM AUTHOR]

Although road surface friction is considered the most effective performance measure for maintenance operations, it is not commonly used due to the high cost of collection. As a result, most jurisdictions use subjective visual indicators that qualitatively describe the state of the road surface, even though they create measurement inconsistencies and offer less detailed maintenance tracking. For maintenance personnel to transition into using friction, the collection cost must be reduced. This paper attempts to do so by proposing a low-cost, machine learning-based method for predicting road surface friction using dash camera imagery and demonstrates its feasibility through a case study. The dataset used for this project was collected in the City of Edmonton, AB, Canada during its 2021/2022 winter season. Three models were developed using tree-based algorithms, where all three displayed high performance with an average root mean squared error of 0.0796 or 79.3% accuracy based on RMSPE. [ABSTRACT FROM AUTHOR]

Reinforced concrete is a commonly used material for constructing basements in low-rise buildings or residential houses in Canada, and as the use of cross-laminated timber (CLT) advances, the door to think of an alternative basement material to offset greenhouse gas emissions associated with reinforced concrete is open. However, the evaluation of CLT durability in below-grade environments, specifically concerning moisture and mould development, remains an unexplored field in research. Hence, this paper aims to analyze CLT's moisture response and mould growth risk in below-grade environments using field and laboratory experiments. A laboratory experiment was carried out to test a waterproofing membrane solution selected to compose the wall assembly in the field experiment. A large-scale experimental CLT basement was built at a cohesive soil site in Edmonton, Canada. The field experiment involved monitoring the relative humidity, temperature, and soil volumetric water content of the CLT panels, which measure 3 m by 6 m in plan and 2 m deep. Data was collected for an extended period from June 2022 to July 2023. The VVT model, developed by Hukka and Viitanen (1999) and updated by Viitanen et al., 2011 to estimate the mould growth level, was used to predict the risk of mould growth. The laboratory experiment showed that the waterproofing membrane is suitable for protection against moisture in a still-water setup. Field experiment results suggested that the primary moisture source was below the basement floor when the floor was finished inadequately. The moisture content of CLT walls was significantly increased by floor flooding and decreased by heating the basement interior. The acceptable mould index of three was surpassed during periods of abundant water below the basement floor due to flood events, showing that the CLT panels were at risk of mould growth development. • CLT use inbasements is in research stage. This paper contains insights for developing future research on this subject. • CLT in basement construction requires robust envelope with waterproofing membranes that perform well below grade. • Elevated moisture levels could pose structural and biological risks to the CLT basement and its occupants. • CLT basement walls take time to dry, and during this period, the walls may be exposed to risky levels of mould growth. [ABSTRACT FROM AUTHOR]

The great increase in car ownership has led to the daily recurrence of traffic congestion. Thus, traffic mobility, safety and emission concerns have become the most serious challenges for transportation researchers. To mitigate traffic congestion, a variety of proactive traffic-control strategies, such as ramp metering (RM), have been intensively investigated and deployed. With the aim of improving freeway traffic conditions, RM regulates the on-ramp flows dynamically in response to dynamic road conditions. However, most early RM strategies focus on optimising the traffic from one single aspect. This paper presents an RM control algorithm that predicts and evaluates the RM-controlled future traffic states. The impact of RM control was evaluated using a macroscopic traffic-flow model. The designed RM control algorithm possesses a multi-objective optimisation module, which improves the traffic network from the aspects of mobility, safety and emissions. The designed algorithm is evaluated through simulation and calibrated using field data collected over an 11 km major freeway stretch in Edmonton, Alberta, Canada. The comparison of the proposed algorithm-controlled scenario and the uncontrolled scenario shows that the proposed RM control algorithm can effectively relieve traffic congestion, improve safety and reduce carbon emissions concurrently. [ABSTRACT FROM AUTHOR]

Background: Ongoing legal and social discrimination, and stigmatization of people with lived experience of drug use (PWLE) continues to contribute to overdose-related deaths in Canada. The involvement of PWLE working in harm reduction services has proven effective in decreasing drug-related harms among PWLE; however, there exist unintended negative impacts. PWLE working in harm reduction services risk overextending themselves beyond employment parameters (e.g., emotional labor) with few systems in place (e.g., employment advocacy) for support. While meaningful participation of PWLE in harm reduction programs is critical to addressing the overdose crisis, their labor in Canada's overdose response commands further investigation and recognition. This paper examines some of the benefits and negative aspects of working in harm reduction among PWLE. Methods: Fifty qualitative surveys were completed by PWLE working in harm reduction services from across Canada at the National 2018 Stimulus conference held in Edmonton, Alberta. The surveys focused on the benefits and negatives of 'peer' employment and recommendations for organizational transformation through short answer written sections. Surveys were analyzed thematically using NVivo, informed by critical perspectives on substance use, with attention to key re-occurring themes on employment equity. Results: While participants described multiple benefits of working in harm reduction services, such as the valuing of their expertise by fellow 'peers,' growing skill sets, countering stigma, and preventing overdose deaths, issues of workplace equity were significantly identified. Stigma, tokenism, workplace discrimination, including power and pay inequities, as well as lack of worker compensation and benefits were identified as key factors persisting in the everyday experiences of participants. Conclusion: Continued exposure to stigma, workplace discrimination, and/or power imbalances, combined with the impact of high stakes employment (e.g., dealing with overdose deaths), can have significant consequences for PWLE working in harm reduction, including burn out. Policy recommendations include large-scale structural changes that address inequities of hierarchical 'peer' employment for PWLE, including increased leadership roles for diverse PWLE, pay equity and benefits, unionization, as well as more supportive working environments attentive to the intersecting social-structural factors (poverty, criminalization, racism, gendered violence) impacting the everyday lives of PWLE working in harm reduction. [ABSTRACT FROM AUTHOR]

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]

Waste collection management plays a crucial role in controlling pandemic outbreaks. Electric waste collection systems and vehicles can improve the efficiency and effectiveness of sanitary processes in municipalities worldwide. The waste collection routing optimization involves designing routes to serve all customers with the least number of vehicles, total traveling distance, and time considering the vehicle capacity. This paper proposes a dynamic location-arc routing optimization model for electric waste collection vehicles. The proposed model suggests an optimal routing plan for the waste collection vehicles and determines the optimal locations of the charging stations, dynamic charging arcs, and waste collection centers. A genetic algorithm and grey wolf optimizer are used to solve the large-sized random generated NP-hard location-arc routing problems. We present a case study for the city of Edmonton in Canada and show the grey wolf optimizer outperforms the genetic algorithm. We further demonstrate the total number of waste collection centers, charging stations, and arcs for dynamic charging needed to ensure a minimum required service for electric vehicles throughout Edmonton's entire waste collection system. [Display omitted] • The waste collection routing optimization optimizes routes serving customers. • Optimized routes use minimum vehicles, distance, and time with capacitated vehicles. • A dynamic location-arc routing optimization is proposed for electric waste collection vehicles. • Genetic algorithms and grey wolf algorithms solve the large NP-hard problem. • A case study in Canada shows grey wolf algorithm outperforms the genetic algorithm. [ABSTRACT FROM AUTHOR]

This paper applies urban and environmental sociological theory to survey data on self-reported sustainable consumption practices, using a matched sample of central city and suburban residents in Edmonton, Alberta. We use cluster analysis to create an ordinal typology of four types of consumers, conduct an analysis of variance to characterize the resultant clusters, and perform logistic regression to predict the net effect of urban and neighbourhood context on sustainable consumption practices. We find that neighbourhood and environmental attitude are the strongest predictors of sustainable consumption practices. We conclude by arguing many sustainable activities are more difficult to incorporate into daily routine when residing in the suburban neighbourhood. While suburban residents may feel strongly that they should consume less, their geographic location appears to significantly constrain their ability to meaningfully reduce their own consumption. This urban Canadian case study has implications for middle class environmental practices in other North American urban and suburban settings. [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 explores the changing settlement patterns of Aboriginal peoples in Winnipeg, Manitoba and Edmonton, Alberta, between 1971 and 2001. The objective is to compare these residential patterns to the traditional model for immigrant settlement put forward by the Chicago school model and supported by other researchers. We recognize that Aboriginal people are not immigrants. Immigrant models have often been employed to interpret Aboriginal peoples settlement patterns in cities, though, and we attempt to evaluate the applicability of these models to the Aboriginal experience, and to explore variations between these two cities. Our results suggest that the classical model of immigrant settlement patterns does not describe the urban Aboriginal experience very well. They also show that patterns vary substantially between cities. Interviews with key informants in the two cities suggest that much of this variation is related to differences in the spatial distribution of low-cost housing in Edmonton and Winnipeg. [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]

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]

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 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]