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Access to resources can take many forms: digital access via an onsite network, through an external site, website, etc., or physical access to labs, machines, information repositories, etc. Whether access to resources is digital or physical, it must be allowed, denied, revoked, or disabled using robust and coherent access control (AC) models. What makes the process of AC more complicated is the emergence of digital transformation technologies and pervasive systems such as the internet of things (IoT) and industry 4.0 systems, especially with the growing demand for transparency in users' interaction with various applications and services. Controlling access and ensuring security and cybersecurity in IoT and industry 4.0 environments is a challenging task. This is due to the increasing distribution of resources and the massive presence of cyber-threats and cyber-attacks. To ensure the security and privacy of users in industry sectors, we need an advanced AC metamodel that defines all the required components and attributes to derive various instances of AC models and follow the new and increasing demand for AC requirements due to continuous technology upgrades. Due to the several limitations in the existing metamodels and their inability to answer the current AC requirements, we have developed a Hierarchical, Extensible, Advanced, Dynamic (HEAD) AC metamodel with significant features that overcome the existing metamodels' limitations. In this paper, the HEAD metamodel is employed to specify the needed AC policies for two case studies inspired by the computing environment of Institut Technologique de Maintenance Industrielle (ITMI)-Sept-Îles, QC, Canada; the first is for ITMI's local (non-IoT) environment and the second for ITMI's IoT environment. For each case study, the required AC model is derived using the domain-specific language (DSL) of HEAD metamodel, then Xtend notation (an expressive dialect of Java) is utilized to generate the needed Java code which represents the concrete instance of the derived AC model. At the system level, to get the needed AC rules, Cypher statements are generated and then injected into the Neo4j database to represent the Next Generation Access Control (NGAC) policy as a graph. NGAC framework is used as an enforcement point for the rules generated by each case study. The results show that the HEAD metamodel can be adapted and integrated into various local and distributed environments. It can serve as a unified framework, answer current AC requirements and follow policy upgrades. To demonstrate that the HEAD metamodel can be implemented on other platforms, we implement an administrator panel using VB.NET and SQL. [ABSTRACT FROM AUTHOR]

This paper presented a two-dimensional, well-balanced hydrodynamic and sediment transport model based on the solutions of variable-density shallow-water equations (VDSWEs) and the Exner equation for bed change for simulating sediment transport in unsteady flows. Those equations are solved in a coupled way by the first-order Godunov-type finite volume method. The Harten–Lax–van Leer–Contact (HLLC) Riemann solver is extended to find the local Riemann fluxes to maintain the exact balance between the momentum term and the bed slope term. A well-balanced scheme is superior to an unbalanced scheme to minimize numerical dispersion as demonstrated by the synthetic standing contact-discontinuity test case. Following this, the model is employed to simulate two laboratory experiments and a field case, the 1996 Lake Ha! Ha! flood event in Canada. The results of water surface elevations and bed surface profiles agree well with the measurements. The accuracy and robustness of the numerical schemes make the model a good candidate for practical engineering applications. [ABSTRACT FROM AUTHOR]

The labour market for care professionals has experienced significant changes, resulting in critical shortages globally. Nurses represent the largest share of health workers worldwide; nonetheless, an estimated 13 million more nurses will be needed over the next 10 years. Prior to the pandemic, the domestic supply of nurses in Canada had not kept pace with the ever-increasing demand for services. Pre-pandemic age- and needs-based forecasting models have estimated shortages in an excess of 100,000 nurses nationwide by 2030. While COVID-19 has accelerated the demand for and complexity of service requirements, it has also resulted in losses of healthcare professionals due to an increased sick leave, unprecedented burnout and retirements. This paper examines key factors that have contributed to nursing supply issues in Canada over time and provides examples of policy responses to the present shortage facing the healthcare system. To provide adequate care, the nursing workforce must be stabilized and—more importantly—recognized as critical to the health of the population. [ABSTRACT FROM AUTHOR]

Heating, ventilation, and air conditioning (HVAC) systems play a crucial role in either increasing or decreasing the risk of airborne disease transmission. High ventilation, for instance, is a common method used to control and reduce the infection risk of airborne diseases such as COVID-19. On the other hand, high ventilation will increase energy consumption and cost. This paper proposes an optimal HVAC controller to assess the trade-off between energy consumption and indoor infection risk of COVID-19. To achieve this goal, a nonlinear model predictive controller (NMPC) is designed to control the HVAC systems of a university building to minimize the risk of COVID-19 transmission while reducing building energy consumption. The NMPC controller uses dynamic models to predict future outputs while meeting system constraints. To this end, a set of dynamic physics-based models are created to capture heat transfer and conservation of mass, which are used in the NMPC controller. Then, the developed models are experimentally validated by conducting experiments in the ETLC building at the University of Alberta, Canada. A classroom in the building is equipped with a number of sensors to measure indoor and outdoor environmental parameters such as temperature, relative humidity, and CO 2 concentration. The validation results show that the model can predict room temperature and CO 2 concentration by 0.8%, and 2.4% mean absolute average errors, respectively. Based on the validated models, the NMPC controller is designed to calculate the optimal airflow and supply air temperature for every 15 min. The results for real case studies show that the NMPC controller can reduce the infection risk of COVID-19 transmission below 1% while reducing energy consumption by 55% when compared to the existing building controller. [ABSTRACT FROM AUTHOR]

Pluvial flooding in urban areas is one of the most significant drivers of disaster loss in Canada. Damages during pluvial flood events are associated with overwhelmed urban drainage (stormwater and wastewater) systems. During the period from 2013 to 2021, Canadian property and casualty insurers reported approximately CAD 2 billion in personal property (residential) pluvial sewer backup claims during flood catastrophes. There has been growing interest in managing pluvial urban flood risk, notably through newly funded national programs focused on climate change adaptation. These programs have included the development of new guidelines and standards focused on managing the underlying factors contributing to urban and basement flooding. Inflow and infiltration (I/I) has received limited attention in the pluvial flood literature, however. Informed by significant engagement with practitioners in Canada, this paper provides a review of the issue of I/I into wastewater systems and its relation to pluvial flooding. The paper will address concerns related to private property engagement in I/I and urban pluvial flood reduction programs. Both improved technical standards and administrative support are needed to ensure that wastewater infrastructure is less susceptible to I/I over its lifecycle. [ABSTRACT FROM AUTHOR]

In recent years, sustainable community development has gained traction for addressing local environmental, social, and economic issues. Cities worldwide are committed to implementing sustainable community plans (SCPs) in their efforts to achieve sustainable development, and more recently, to localize the United Nations' Sustainable Development Goals (SDGs). Although there are over 1000 plans in Canada, a gap exists between creating these plans and implementing them. Integrating market-based instruments (MBIs) with traditional policy tools would help to diversify revenue generation and thus mitigate these constraints. This paper presents a new and comprehensive categorization of MBIs that aligns the locally applicable ones with the environmental aims of both SCPs and SDGs. The categorization framework has been tested through focus groups with key municipal staff from two Canadian communities. The new categorization framework aligned over 50 locally applicable MBIs with 8 different environmental topics and 12 SDGs. The paper presents a useful tool for implementing SCPs and SDGs and contributes to the understanding of MBIs for enabling local progress in sustainable development. [ABSTRACT FROM AUTHOR]

Since individual neural networks have limited deep expressiveness and effectiveness, many learning frameworks face difficulties in the availability and balance of sample selection. As a result, in change detection, it is difficult to upgrade the hit rate of a high-performance model on both positive and negative pixels. Therefore, supposing that the sacrificed components coincide perfectly with the important evaluation objectives, such as positives, it would lose more than gain. To address this issue, in this paper, we propose a multi-visual collaborative deep network (MV-CDN) served by three collaborative network members that consists of three subdivision approaches, the CDN with one collaborator (CDN-C), CDN with two collaborators (CDN-2C), and CDN with three collaborators (CDN-3C). The purpose of the collaborator is to re-evaluate the feature elements in the network transmission, and thus to translate the group-thinking into a more robust field of vision. We use three sets of public double-temporal hyperspectral images taken by the AVIRIS and HYPERION sensors to show the feasibility of the proposed schema. The comparison results have confirmed that our proposed schema outperforms the existing state-of-the-art algorithms on the three tested datasets, which demonstrates the broad adaptability and progressiveness of the proposal. [ABSTRACT FROM AUTHOR]

The American lobster (Homarus americanus) is the most valuable seafood on Canada's Atlantic coast, generating over CAD 800 million in export revenue alone for New Brunswick. However, labor shortages plague the lobster industry, and lobsters must be processed quickly to maintain food safety and quality assurance standards. This paper proposes a lobster estimation orientation approach using a convolutional neural network model, with the aim of guiding the FANUC LR Mate 200 iD robotic arm for lobster manipulation. To validate this technique, four state-of-the-art object detection algorithms were evaluated on an American lobster images dataset: YOLOv7, YOLOv7-tiny, YOLOV4, and YOLOv3. In comparison to other versions, YOLOv7 demonstrated a superior performance with an F1-score of 95.2%, a mean average precision (mAP) of 95.3%, a recall rate of 95.1%, and 111 frames per second (fps). Object detection models were deployed on the NVIDIA Jetson Xavier NX, with YOLOv7-tiny achieving the highest fps rate of 25.6 on this platform. Due to its outstanding performance, YOLOv7 was selected for developing lobster orientation estimation. This approach has the potential to improve efficiency in lobster processing and address the challenges faced by the industry, including labor shortages and compliance with food safety and quality standards. [ABSTRACT FROM AUTHOR]

When there is direct competition for a position of power (promotion, elected office, etc.), competitors are tempted to cheat to increase their chances of winning. If they do so successfully, then how they rationalize their cheating can determine how they treat the losers of the competition. In this paper, we explore how the winners of a promotion tournament treat the losers, using a two stage laboratory experiment run in Canada and the United Arab Emirates. In the first stage, subjects compete to earn the role of the dictator in a dictator game, which takes place in the second stage. We vary whether or not subjects can cheat during the competition. The results of the experiment can be summarized as follows: (1) cheating significantly increases altruism in some tournament winners, (2) winners who cheat the most are significantly less altruistic than winners who cheated only a little, (3) there are significant differences in cheating behavior across the two populations, and (4) cheating behavior can be at least partially attributed to differences in intelligence and beliefs across the two populations. [ABSTRACT FROM AUTHOR]

The import demand for energy resources, including liquefied natural gas (LNG), has been steadily increasing in the Asia-Pacific region. Australia, the Middle East (Qatar), the Russian Federation, and the U.S. are the major players who compete strategically to capture this ever-growing market for LNG. The objective of this paper is to examine the potential for Canada's entry into this market as another LNG exporter and what impact that can have on the existing suppliers. Using a game-theoretic LNG export competition model, we explore the conditions under which Canada can make a profitable entry. We also investigate the effect of Canada's entry on the profitability of the four incumbent exporters. Employing a multi-leader Stackelberg model, we found that Canada's entry could be a Pareto superior outcome under certain conditions because it benefits all competing firms and consumers. Further, Canada's entry into the LNG export market always helps the low-cost incumbent firms by increasing their output and profit. However, the high-cost incumbent firms' output falls, while their profit may increase or decrease depending on the unit cost and market size parameters. With differential export costs between Canada and the U.S., the latter has an incentive to act strategically to affect the entrance of the former. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to provide evidence-based guidance on the management of a positive human papilloma virus (HPV) test and to provide guidance around screening and HPV testing for specific patient populations. The guideline was developed by a working group in collaboration with the Gynecologic Oncology Society of Canada (GOC), Society of Colposcopists of Canada (SCC), and the Canadian Partnership Against Cancer. The literature informing these guidelines was obtained through a systematic review of relevant literature by a multi-step search process led by an information specialist. The literature was reviewed up to July 2021 with manual searches of relevant national guidelines and more recent publications. The quality of the evidence and strength of recommendations were developed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) framework. The intended users of this guideline include primary care providers, gynecologists, colposcopists, screening programs, and healthcare facilities. The implementation of the recommendations will ensure an optimum implementation of HPV testing with a focus on the management of positive results. Recommendations for appropriate care for underserved and marginalized groups are made. [ABSTRACT FROM AUTHOR]

The admission of people suffering from psychiatric and neurocognitive disorders to euthanasia and physician-assisted suicide (E/PAS) in some European and non-European countries represents a controversial issue. In some countries, the initial limitation of E/PAS to cases of severe physical illness with poor prognosis in the short term has been overcome, as it was considered discriminatory; thus, E/PAS has also been made available to subjects suffering from mental disorders. This decision has raised significant ethical questions regarding the capacity and freedom of self-determination; the family, social, and economic contexts; the social consideration of the sense of dignity and the pressure on the judgment of one's personal value; the contextual therapeutic possibilities; the identification of figures involved in the validation and application; as well as the epistemological definitions of the clinical conditions in question. To these issues must be added the situation of legislative vacuum peculiar to different countries and the widespread lack of effective evaluation and control systems. Nonetheless, pessimistic indicators on global health status, availability of care and assistance, aging demographics, and socioeconomic levels suggest that there may be further pressure toward the expansion of such requests. The present paper aims to trace an international overview with the aim of providing ethical support to the debate on the matter. Precisely, the goal is the delimitation of foundations for clinical practice in the complex field of psychiatry between the recognition of the irreversibility of the disease, assessment of the state of physical and mental suffering, as well as the possibility of adopting free and informed choices. [ABSTRACT FROM AUTHOR]

In August 2021, the United States withdrew from Afghanistan after 20 years. The fall of the Afghan government to the Taliban resulted in the displacement of some Afghans. Canada committed to welcoming thousands of refugees. Research suggests that refugees tend to have higher rates of post-traumatic stress, and Afghan refugees, in particular, have among the highest rates. Another body of literature suggests that religious coping has positive effects. This paper presents qualitative data from interviews with 11 Afghan refugees who arrived in Ontario after August 2021 with the intent to combine these two findings. In so doing, we sought to understand how Afghan refugees described their experiences of displacement and the extent to which those experiences were traumatic, but also how they relied on Islam to cope with the traumatic effects of displacement. The interviews we conducted suggested that our participants experienced exposure to death, exposure to threat of death and/or injury, and described some of symptoms of the criteria for PTSD. The interviews also suggested that the participants coped using Islamic concepts, beliefs, and rituals. The qualitative data we present provide rich descriptions of the experiences of trauma in the face of displacement and religious coping. [ABSTRACT FROM AUTHOR]

Practices of creativity and compliance intersect in interaction when directing local dances remotely for people living with dementia and their carers in institutional settings. This ethnomethodological study focused on how artistic mechanisms are understood and structured by participants in response to on-screen instruction. Video data were collected from two long-term care facilities in Canada and Finland in a pilot study of a dance program that extended internationally from Canada to Finland at the onset of COVID-19. Fourteen hours of video data were analyzed using multimodal conversation analysis of initiation–response sequences. In this paper, we identify how creative instructed actions are produced in compliance with multimodal directives in interaction when mediated by technology and facilitated by copresent facilitators. We provide examples of how participants' variably compliant responses in relation to dance instruction, from following a lead to coordinating with others, produce different creative actions from embellishing to improvising. Our findings suggest that cocreativity may be realized at intersections of compliance and creativity toward reciprocity. This research contributes to interdisciplinary discussions about the potential of arts-based practices in social inclusion, health, and well-being by studying how dance instruction is understood and realized remotely and in copresence in embodied instructed action and interaction. [ABSTRACT FROM AUTHOR]

Remote community initiatives for renewable energy are rapidly emerging across Canada but with varying numbers, success rates, and strategies. To meet low-carbon transition goals, the need to coordinate technology deployment and long-term policy to guide the adoption is critical. Renewable resources such as wind, solar, hydro, and biomass can provide energy at a subsidized cost, create sustainable infrastructure, and provide new economic viability in social value integration. The renewable energy transition is crucial to Canada in sustaining remote and indigenous communities by providing local, clean, and low-carbon-emission energy for heat, power, and possibly transportation. This paper identified 635 renewable resources projects deployed to improve and increase electricity supply. To an extent, balancing demand within the remote and indigenous communities of Canada and highlighting sustainable renewable energy development through ownership participation within the communities is achievable before 2050 and beyond through energy efficiency and the social value of energy. The article identifies clean energy targets as mandated by the different provinces in Canada to reach net-zero GHG emissions. [ABSTRACT FROM AUTHOR]

Using microdata from Statistics Canada's Labour Force Survey (LFS) and Population Census, this paper explores how spatial characteristics are correlated with temporary employment outcomes for Canada's immigrant population. Results from ordinary least square regression models suggest that census metropolitan areas and census agglomerations (CMAs/CAs) characterized by a high share of racialized immigrants, immigrants in low-income, young, aged immigrants, unemployed immigrants, and immigrants employed in health and service occupations were positively associated with an increase in temporary employment for immigrants. Furthermore, findings from principal component regression models revealed that a combination of spatial characteristics, namely CMAs/CAs characterized by both a high share of unemployed immigrants and immigrants in poverty, had a greater likelihood of immigrants being employed temporarily. The significance of this study lies in the spatial conceptualization of temporary employment for immigrants that could better inform spatially targeted employment policies, especially in the wake of the structural shift in the nature of work brought about by the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

What would it look like to honour differences in eating disorder recovery? Recoveries from eating disorders and eating distress are enacted in relation to discursive, material, and affective flows that open and constrain different possibilities for differently embodied people. Yet, the pull toward establishing consensus on "what recovery is" continues to dominate the landscape of both qualitative and quantitative eating disorder recovery work. While researchers from a variety of perspectives, disciplines, and methodological traditions have sought to establish consensus on what recovery "is", a singular definition remains elusive. Indeed, when researchers continue to adopt the same methodologies—which largely emphasize establishing patterns of sameness—the opportunity to dig into contradictions and tensions that enliven recoveries is missed. In this paper, we reflect on our experiences conducting creative, collaborative, generative research to re-write, re-design, re-draw, and otherwise re-imagine recoveries. The knowledge generated in our research is co-constructed with people with living experience of disordered/distressed eating/eating disorders who spoke back to mainstream recovery discourses (e.g., the idea that recovery is about perfection, that recovery is linear, that one is either recovered or not, that the word "recovered" encapsulates the experience, etc.). We engaged with 12 participants: four in an online group workshop and eight in individual online sessions. Participants held a variety of experiences and backgrounds from Canada, the United States, and Aotearoa New Zealand. We explored their journeys into this conversation with us, the meaning of recovery, and their thoughts on what makes recovery im/possible. Participants were offered several options for creative engagement and took up the idea of "creativity" in ways as different as the stories they shared. Participants created collages, short stories, poems, drawings, and told stories about their experiences. Here, we discuss methodological insights gained from asking participants to lead the creative process. We also explore how this project potentially enables different ways of thinking about and doing eating disorder recovery. Delving into the differences in both method and content opens up opportunities to take seriously the different relational, material, and affective constellations of participants' living experiences of eating distress/disorder "recovery". [ABSTRACT FROM AUTHOR]

The conventional manufacturing methods for fabricating orthotic and prosthetic (O&P) devices have been in practice for a very long time. Recently, O&P service providers have started exploring different advanced manufacturing techniques. The objective of this paper is to perform a mini review on recent progress in the use of polymer-based additive manufacturing (AM) for O&P devices and to gather insights from the O&P professionals on the current practices and technologies and on the prospect of using AM techniques in this field. In our study, first, scientific articles on AM for O&P devices were studied. Then, twenty-two (22) interviews were conducted with O&P professionals from Canada. The primary focus was on five key areas: cost, material, design and fabrication efficiency, structural strength, functionality, and patient satisfaction. The cost of manufacturing the O&P devices using AM techniques is lower as compared to the conventional methods. O&P professionals expressed their concern over the materials and structural strength of the 3D-printed prosthetic devices. Published articles report comparable functionality and patient satisfaction for both O&P devices. AM also greatly improves design and fabrication efficiency. However, due to a lack of qualification standards for 3D printed O&P devices, 3D printing is being embraced more slowly in the O&P business than in other industries. [ABSTRACT FROM AUTHOR]

In this paper, taking Block G in Canada as an example, combined with the data of the working area, the Pearson–MIC comprehensive evaluation method was adopted to optimize the key parameters of productivity. Based on the analytic hierarchy process, the weight of each parameter was calculated, the grade of evaluation index of the "sweet spot" was divided, the standard of the sweet spot was established, and the distribution of the superimposed sweet spot was finally depicted. The results show that lateral length, number of stages, volume of fluid, and amount of proppant are the key engineering parameters of horizontal well, and lateral length is an independent key engineering parameter. The cumulative gas production in the first two years was normalized on the lateral length to eliminate the engineering influence, and the total organic carbon (TOC) was finally determined as the key geological parameter, whereas porosity and water saturation were the secondary key parameters. The area of Type I sweet spots accounts for 24.2% in the Series Upper and 23.1% in the Series Lower. This study proposed a new sweet spot prediction idea based on the influence of geological factors on productivity, and its results also laid a foundation for the subsequent placement of horizontal wells in Block G. [ABSTRACT FROM AUTHOR]

Countries are drastically impacted by financial and fiscal crises. Financial crises have the worst impact on not only society, but also the economy. The Canadian economy underwent financial crises and recessions several times during the last century. In this paper, daily closing stock prices of five large Canadian banks were studied during the last five crisis periods. It is aimed to determine the most effective or dominant index prices on the daily closing stock price of the banks during the crisis periods. The five periods were selected from secondary data from January 1975 to December 2020 by using the graphs and the crises in the literature. Multiple linear regression was performed to analyze the impact of price indexes during crisis periods. Findings show that "price index—financials" had a positive impact on the daily closing price of banks during the last five economic crises in Canada. Since the banks have different investment tools in their portfolio, the impacts of price indexes on the daily closing prices depend on these portfolios, which ultimately could have led to the economic crises. [ABSTRACT FROM AUTHOR]

This paper analyzes the role of Canadian online news media in framing travel during the pandemic. The article applies Altheide's concept of the problem frame to reflect how news media contribute to the emergence of a highly rationalized problem that, in turn, generates a discourse of fear. While the impacts of COVID-19 on tourism have been extensively examined within tourism scholarship, less attention has been devoted to the impact of news media. Because travel and the pandemic are heavily intertwined, discourse analysis can help process media narratives, furthering our understanding of their role in influencing perceived risk of travel. A critical discourse analysis of over 100 online news articles was conducted using thematic analysis to uncover themes in Canadian media sources and to explore how the media have framed travel during the pandemic. The role of online news media in promoting fear was communicated through the themes of anxiety, antitrust, avoidance, and animosity. The role of the media in producing the problem frame in the context of travel was examined as well as its implications for perceived travel risk and tourism demand. The power dynamics between media, government, and the citizens it serves are also discussed. [ABSTRACT FROM AUTHOR]

Skilled immigrants are critical assets to the social and economic dynamism of Canada. However, they are less likely to find employment matching their skillset due to a lack of inclusive post-immigration professional integration policies and support. They generally earn less and often live below the low-income cutoff relative to their Canadian-born counterparts. This paper aims to review the current situation of low job market integration (LJMI) of skilled immigrants in Canada and its implications on their social integration and mental well-being. Skilled immigrants continue to face disparities in getting desired jobs, despite having sufficient skills and credentials similar if not superior to that of Canadian-borns. Based on the existing literature, this study demonstrates that low job market integration limits skilled immigrants' productivity, and they experience a lower level of social integration and deteriorated mental well-being. Therefore, initiatives from multidisciplinary and multisector stakeholders are necessary to improve skilled immigrants' mental well-being by providing equal opportunities devoid of social exclusion and marginalization. [ABSTRACT FROM AUTHOR]

The paper describes a system and experimental procedure that use integrating passive detectors, such as thermoluminescent dosimeters (TLDs), for the measurement of ultra-low-level ambient dose equivalent rate values at the underground SNOLAB facility located in Sudbury, Ontario, Canada. Because these detectors are passive and can be exposed for relatively long periods of time, they can provide better sensitivity for measuring ultra-low activity levels. The final characterization of ultra-low-level ambient dose around water shielding for ongoing direct dark matter search experiments in Cube Hall at SNOLAB underground laboratory is given. The conclusion is that TLDs provide reliable results in the measurement of the ultra-low-level environmental radiation background. [ABSTRACT FROM AUTHOR]

Climate warming at high latitudes has contributed to the growing interest in shrub tree-ring analysis. Shrub architecture presents new challenges for dendrochronology, such as the seemingly lower and inconsistent climatic sensitivity of stems vs. root collars. Shrub stems may thus be considered as sub-optimal to study climate–growth relationships. In this paper, we propose that the lower climatic sensitivity of stems could be caused by the use of unsuitable detrending methods for chronologies spanning decades rather than centuries. We hypothesize that the conversion of the ring width (RW) to basal area increment (BAI) is better suited than traditional detrending methods to removing age/size-related trends without removing multi-decadal climate signals. Using stem and root collar samples collected from three sites in the forest–tundra ecotone of eastern Canada, we compared the climate–growth relationships of these two approaches for stems and root collars using mixed-effects models. The climate sensitivity was, on average, 4.9 and 2.7 times higher with BAI than with detrended (mean-centered) RW chronologies for stems and root collars, respectively. The climatic drivers of radial growth were identical for stems and root collars when using BAI (July temperature and March precipitation), but were inconsistent when using detrended RW series (root collars: July temperature and March precipitation at all sites; stems: April and June temperature, depending on the site). Although the use of BAI showed promising results for studying long-term climate signals in shrub growth chronologies, further studies focusing on different species and locations are needed before the use of BAI can become broadly used in shrub dendrochronology. [ABSTRACT FROM AUTHOR]

The increasing amount of operational data in buildings opens up new methods for improving building performance through advanced controls. Although predictive control has been widely investigated in the literature, field demonstrations still remain rare. Alternatively, model-based controls can provide similar improvement while being easier to implement in real buildings. This paper investigates three data-driven model-based control strategies to improve the cooling performance of commercial and institutional buildings: (a) chiller sequencing, (b) free cooling, and (c) supply air temperature reset. These energy efficiency measures are applied to an existing commercial building in Canada with data from summer 2020 and 2021. The impact of each measure is individually assessed, as well as their combined effects. The results show that all three of the measures together reduce building cooling energy by 12% and cooling system electric energy by 33%. [ABSTRACT FROM AUTHOR]

Simple Summary: This paper looks at changes in weight, physical activity, and food/dietary intake during the first year of the COVID-19 pandemic in undergraduate students enrolled in a Canadian university. The investigation used an online survey format to collect data at the end of the two lockdown periods over one year. Participants were recruited from universities across Canada. The results show a modest weight gain accompanied by a decrease in physical activity and an unhealthy change in diet. Specifically, students reported that their engagement in specific physical activities and overall activity levels decreased during the lockdowns. The number of calories also decreased over time, while the foods consumed decreased in nutritional value. Thus, the modest weight gain observed may have resulted from the decrease in physical activity and diet quality. In conclusion, Canadian food and physical activity recommendations were not met during the lockdowns caused by the pandemic, which highlights the physical and nutritional implications of confinement. This study examined changes in body mass and body mass index (BMI), physical activity, and dietary intake in Canadian university students during the first year of the COVID-19 pandemic. Two self-reported recall surveys were conducted: after the first lockdown in September 2020 (T1) and following the second lockdown in March 2021 (T2). Eligible participants were full-time undergraduate students attending a Canadian university and residing in Canada during the first year of the pandemic. At T1, 510 students (99 male, 411 female) completed the survey, and of those, 135 (32 males, 103 females) completed the survey at T2 (73% attrition). At both T1 and T2, most participants were 18–24 years of age (93% and 90%, respectively), Caucasian (73% and 78%, respectively), and resided in the province of Ontario (79% and 80%, respectively). Body mass increased from T1 to T2 (+0.91 ± 3.89 kg t(132) = −2.7, p = 0.008). BMI also increased from T1 to T2 (+0.30 ± 1.33 kg/m2 [t(130) = −2.5, p = 0.012), with a greater number of participants within the overweight range (19.8% versus 24.4%, respectively). At T1, 38% of the participants reported a decrease in physical activity, while the number of students reporting a decrease in activity increased to 56% at T2. Dietary energy intake decreased from 1678 ± 958 kcal/day at T1 to 1565 ± 842 kcal/day at T2 [c2(1) = 7.2, p = 0.007]. Diet quality also decreased, with participants not meeting the recommended daily allowance for essential macro and micronutrients. A decrease was observed in daily servings of fruits (−27%, p < 0.001), vegetables (−72%, p < 0.001), and grains (−68%, p < 0.001). In conclusion, despite a small decrease in dietary energy intake, a modest weight gain occurred during the first year of the COVID-19 pandemic in this cohort of Canadian university students, which was potentially related to decreased physical activity and diet quality. [ABSTRACT FROM AUTHOR]

This paper formulates and solves a new problem of the double model following adaptive control (MFAC) of nodes and links in a complex dynamical network (CDN). This is different from most existing studies on CDN and MFAC. Inspired by the concept of composite systems, the CDN with dynamic links is regarded as an interconnected system composed of an interconnected node group (NG) and link group (LG). Guided by the above-mentioned new idea of viewing a CDN from the perspective of composite systems, by means of Lyapunov theory and proposed related mathematical preliminaries, a new adaptive control scheme is proposed for NG. In addition, to remove the restriction that the states of links in a CDN are unavailable due to physical constraints, technical restraints, and expensive measurement costs, we synthesize the coupling term in LG with the proposed adaptive control scheme for NG, such that the problem of double MFAC of nodes and links in CDN is solved. Finally, a simulation example is presented to verify the theoretical results. [ABSTRACT FROM AUTHOR]

There is a large amount of drilling core data in the Mackay River oil sands block in Canada, and the accurate identification of facies from the cores is important and necessary for the understanding of the subsurface reservoir. The traditional recognition method of facies from cores is by human work and is very time consuming. Furthermore, the results are different according to different geologists because of the subjective judgment criterion. An efficient and objective method is important to solve the above problem. In this paper, the deep learning image-recognition algorithm is used to automatically and intelligently recognize the facies type from the core image. Through a series of high-reliability preprocessing operations, such as cropping, segmentation, rotation transformation, and noise removal of the original core image, that have been manually identified, the key feature information in the images is extracted based on the ResNet50 convolutional neural network. On the dataset of about 200 core images from 13 facies, an intelligent identification system of facies from core images is constructed, which realizes automatic facies identification from core images. Comparing this method with traditional convolutional neural networks and support vector machines (SVM), the results show that the recognition accuracy of this model is as high as 91.12%, which is higher than the other two models. It is also shown that for a relatively special dataset, such as core images, it is necessary to rely on their global features in order to classify them, and, with a large similarity between some of the categories, it is extremely difficult to classify them. The selection of a suitable neural network model can have a great impact on the accuracy of recognition results. Then, the recognized facies are input as hard data to construct the three-dimensional facies model, which reveals the complex heterogeneity and distribution of the subsurface reservoir for further exploration and development. [ABSTRACT FROM AUTHOR]

Low-sloped roofs such as commercial and high-rise buildings in a dense urban area provide vast "unused" surfaces that can be used to manage storm-water and mitigate urban flooding. Storm-water Detention Assembly (SDA) known as "blue roof" exerts advanced drainage technologies and operational strategies to store-and-release storm-water during and after heavy rainfall events. SDA can reduce peak flow and decrease storm-water run-off volume. However, the SDA application is limited due to the lack of science-based regulatory requirements. This paper introduces SDA, summarizes the benefits and challenges of this system, reviews the existing code specifications on roofing drain systems, and documents the criteria to design and construct SDA. With this systematic approach, the missing links are identified that shall form code change request for possible inclusion in the National Building Code of Canada (NBCC) and National Plumping Code of Canada (NPC). In addition, a road map is stated to calculate and benchmark the drain requirements on low-sloped roofs for a given design climatic load. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic led to unprecedented changes in the U.S. price of softwood lumber by more than 300% between 2020 and 2022. The increased volatility of lumber prices after the COVID-19 outbreak remains unexplained. In this paper, we examine how a calibrated random walk can induce similar price volatility through the development of a stochastic process. As a preferred approach, we employ an event model to estimate the impact of COVID-19 and other key events on the price of softwood lumber. The econometric model serves to provide evidence that the price volatility of softwood lumber is not completely random, and we can instead attribute part of the variation to recent regional and global events. We found that, while COVID-19 did result in a price jump, it was smaller than a rainfall event that restricted imports from Canada, while import duties and other trade actions had no discernible impact on U.S. lumber prices. [ABSTRACT FROM AUTHOR]

In boreal forests in Canada, broadleaf stands are characterized by generally well-drained soils and a humus-rich layer. In contrast, spruce-moss stands are often characterized by more poorly drained soils and acidic humus layer. However, presence of these two forest types in various degrees of mixture in stands can be beneficial to spruce seedlings productivity. It was hypothesized that leaf litter and humus from pure spruces-moss stands, pure broadleaf stands, and mixed stand may influence Black spruce (Picea mariana (Mill.) BSP) seedling growth and development differently. A greenhouse experiment was carried out to evaluate the effect of different leaf litter and different humus on spruces seedlings. Our results suggest better development for seedlings grown in humus from mixed stands and pure broadleaf stands compared to humus from pure B. spruce or standard forest nursery substrate. Furthermore, leaf litter from broadleaf trees species, such as species Speckle alder (Alnus rugosa (Du Roi) R.T. Clausen), T. aspen (Populus tremuloides Michx), Willows (Salix spp.) and Paper birch (Betula papyrifera Marsh.), has shown distinct results in the growth and development of B. spruce seedlings in greenhouse. Furthermore, promotion of mixed stand can increase B. spruce productivity by improving the physicochemical composition of the forest floor. [ABSTRACT FROM AUTHOR]

This paper proposes an improved model-based forest height inversion method for airborne L-band dual-baseline repeat-pass polarimetric synthetic aperture radar interferometry (PolInSAR) collections. A two-layer physical model with various volumetric scattering attenuation and dynamic motion properties is first designed based on the traditional Random Motion over Ground (RMoG) model. Related PolInSAR coherence functions with both volumetric and temporal decorrelations incorporated are derived, where the impacts of homogenous and heterogeneous attenuation and dynamic motion properties on the performance of forest height inversion were investigated by the Linear Volume Attenuation (LVA), Quadratic Volume Attenuation (QVA), Linear Volume Motion (LVM), and Quadratic Volume Motion (QVM) depictions in the volume layer. Dual-baseline PolInSAR data were acquired to increase the degree of freedom (DOF) of the coherence observations and thereby provide extra constraints on the forest parameters to address the underdetermined problem. The experiments were carried out on a boreal forest in Canada and a tropical one in Gabon, where physical models with LVA + QVM (RMSE: 3.56 m) and QVA + LVM (RMSE: 6.83 m) exhibited better performances on the forest height inversion over the boreal and tropical forest sites, respectively. To leverage the advantages of LVA, QVA, LVM, and QVM, a pixel-wise optimization strategy was used to obtain the best forest height inversion performance for the range of attenuation and motion profiles considered. This pixel-wise optimization surpasses the best-performing single model and achieves forest height inversion results with an RMSE of 3.21 m in the boreal forest site and an RMSE of 6.48 m in the tropical forest site. [ABSTRACT FROM AUTHOR]

Specialized products can be needed to help meet the nutrition requirements of vulnerable populations, including infants and young children, those who are ill, and older adults. Laws and regulations delineate distinct categories for such products including medical foods or formulated liquid diets, foods for special dietary use (FSDUs), infant formulas, and natural health products (NHPs). Yet, the literature is limited regarding the role and importance of functional and sustainable packaging for specialized products. This perspective review describes these unique product categories and the role of packaging as well as regulatory considerations. Furthermore, reviewed are how waste reduction strategies and emerging legislative/regulatory policies in the United States and Canada may not adequately address the functional packaging requirements for specialized products. The paper concludes by offering perspectives for emerging innovations and policy development for sustainability. [ABSTRACT FROM AUTHOR]

The Thompson River valley is one of the most important transportation corridors in western Canada as it hosts two important railways. This valley has experienced several historical landslide events, many of them along a 10 km section south of the town of Ashcroft. Six of these landslides, showing varying states of activity, were selected for analysis in this paper, as these have the potential for the biggest impact on the railways. The subsurface interpretation of these landslides is combined with satellite InSAR data from May 2015 to May 2017 to enhance the current understanding of the landslide kinematics. Two InSAR orientations are combined geometrically with the assumption that the horizontal component of landslide movement is parallel to the slope azimuth, which provides a practicable approach to approximate landslide displacement vectors. The results classify these landslides as very slow-moving. The maximum velocities recorded are 29, 35, 26, 64, 18, and 52 mm/year for the Goddard, North, South, South extension, Barnard, and Redhill landslides, respectively. All landslides except the Redhill landslide show near-horizontal movements near the toe, with increasing vertical components as measurements approach the back scarp. This confirms that kinematics include rotational and compound mechanisms. [ABSTRACT FROM AUTHOR]

Forecasting the aggregate charging load of a fleet of electric vehicles (EVs) plays an important role in the energy management of the future power system. Therefore, accurate charging load forecasting is necessary for reliable and efficient power system operation. A hybrid method that is a combination of the similar day (SD) selection, complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), and deep neural networks is proposed and explored in this paper. For the SD selection, an extreme gradient boosting (XGB)-based weighted k-means method is chosen and applied to evaluate the similarity between the prediction and historical days. The CEEMDAN algorithm, which is an advanced method of empirical mode decomposition (EMD), is used to decompose original data, to acquire intrinsic mode functions (IMFs) and residuals, and to improve the noise reduction effect. Three popular deep neural networks that have been utilized for load predictions are gated recurrent units (GRUs), long short-term memory (LSTM), and bidirectional long short-term memory (BiLSTM). The developed models were assessed on a real-life charging load dataset that was collected from 1000 EVs in nine provinces in Canada from 2017 to 2019. The obtained numerical results of six predictive combination models show that the proposed hybrid SD-CEEMDAN-BiLSTM model outperformed the single and other hybrid models with the smallest forecasting mean absolute percentage error (MAPE) of 2.63% Canada-wide. [ABSTRACT FROM AUTHOR]

This paper explores the manners in which Indigenous and allied non-Indigenous researchers, medical directors, and knowledge-keepers (among others) extend the ethical precepts and social justice commitments that are inherent in community-based participatory research (CBPR) approaches to genomics. By means of a genealogical analysis of bioethical discourses, I examine the problem in which genomic science claims to offer potentially beneficial genetic screening tools to Indigenous and racialized peoples who have and continue to struggle with historical health inequity, exploitation, and exclusion by the very biomedical institutions which would be charged with the task of ethically introducing these biomedical tools. This investigation focuses on Indigenous data sovereignty (IDS) as an approach established by Indigenous communities and scientists to gain access to the benefits of genomic health which, if the field's promises are true, aims to counter the historical neglect or exploitation by biomedical researchers and institutions. I chart the role of CBPR principals as it pertains to collective efforts by both Indigenous communities and non-Indigenous allies to create the social, biomedical, and institutional conditions to improve Indigenous health equity in the context of genomic science in two specific studies: the Silent Genome initiative (British Columbia) and the Aotearoa Variome (Aotearoa/New Zealand). This investigation contributes insights to social science literatures in health equity for racialized communities, biomedical ethics, Indigenous Science and Technology Studies, and decolonial biomedical and technoscience histories. [ABSTRACT FROM AUTHOR]

The authors report findings from a 15-month project that focused on the experiences of sex workers who live and work in an Eastern Canadian province. As part of a larger multi-phased study, 15 adults who identified as women, transgender, or non-binary, and received money or goods for sexual services, participated in photo-elicitation interviews. Drawing on a critical framing analysis, findings indicated supports—as identified and experienced by sex workers—encompassed three categories of care: self, community, and collective. These categories are described, with a particular focus on the latter two. Continuing with the care-based framework, recommendations to structure interventions draw on the role of accountability care in identifying how best to operationalize policies that promote health, well-being, and dignity of Canadian sex workers. The paper begins with a brief overview of the Canadian context and the role of supports. It follows with a discussion on the materials and methods and the results. It concludes with recommendations, limitations, and future considerations. [ABSTRACT FROM AUTHOR]

"Short-term load forecasting (STLF)" is increasingly significant because of the extensive use of distributed energy resources, the incorporation of intermitted RES, and the implementation of DSM. This paper provides a novel ensemble forecasting model with wavelet transform for the STLF depending on the decomposition principle of load profiles. The model can effectively capture the portion of daily load profiles caused by seasonal variations. The results indicate that it is possible to improve STLF accuracy with the proposed method. The proposed approach is tested with the data taken from Ontario's electricity market in Canada. The results show that the proposed technique performs well in-terms of prediction when compared to existing traditional and cutting-edge methods. The performance of the model was validated with different datasets. Moreover, this approach can provide accurate load forecasting using ensemble models. Therefore, utilities and smart grid operators can use this approach as an additional decision-making tool to improve their real-time decisions. [ABSTRACT FROM AUTHOR]

Fire activity in 288 areas (2.5° N × 10° E) in the Arctic region (50°–70° N, 0°–360° E) was analyzed using about 4.4 million satellite hotspot (HS) data from 2002 to 2021. A total of 21 high fire density areas from eastern Europe to western Canada were selected, and their fire–weather conditions during each active fire period were analyzed using about 1820 various weather maps at the upper and the lower air level. Analysis results showed that the active fires in the Arctic region occurred under the fire–weather conditions associated with the northward movement of cut-off high (COH) and warm air masses detached from the south caused by large westerly meandering (LWM). LWM is a sign of the beginning of an active fire period. Very active fires on HS peak days occurred several days after the start of the northward movement of COHs and under mainly high-pressure conditions in the upper air and strong wind conditions in the lower air. The time lag of these several days suggests that we may be prepared for very active fires. The fire–weather analysis approach described in this paper has shown that future large-scale fire outbreaks are predictable. [ABSTRACT FROM AUTHOR]

Antimicrobial resistance (AMR) is continuing to grow across the world. Though often thought of as a mostly public health issue, AMR is also a major agricultural and environmental problem. As such, many researchers refer to it as the preeminent One Health issue. Aerial transport of antimicrobial-resistant bacteria via bioaerosols is still poorly understood. Recent work has highlighted the presence of antibiotic resistance genes in bioaerosols. Emissions of AMR bacteria and genes have been detected from various sources, including wastewater treatment plants, hospitals, and agricultural practices; however, their impacts on the broader environment are poorly understood. Contextualizing the roles of bioaerosols in the dissemination of AMR necessitates a multidisciplinary approach. Environmental factors, industrial and medical practices, as well as ecological principles influence the aerial dissemination of resistant bacteria. This article introduces an ongoing project assessing the presence and fate of AMR in bioaerosols across Canada. Its various sub-studies include the assessment of the emissions of antibiotic resistance genes from many agricultural practices, their long-distance transport, new integrative methods of assessment, and the creation of dissemination models over short and long distances. Results from sub-studies are beginning to be published. Consequently, this paper explains the background behind the development of the various sub-studies and highlight their shared aspects. [ABSTRACT FROM AUTHOR]

The fuzzy logic technique is one of the effective approaches for evaluating flexible and rigid pavement distress. The process of classifying pavement distress is usually performed by visual inspection of the pavement surface or using data collected by automated distress measurement equipment. Fuzzy mathematics provides a convenient tool for incorporating subjective analysis, uncertainty in pavement condition index, and maintenance-needs assessment, and can greatly improve consistency and reduce subjectivity in this process. This paper aims to develop a fuzzy logic-based system of pavement condition index and maintenance-needs evaluation for a pavement road network by utilizing pavement distress data from the U.S. and Canada. Considering rutting, fatigue cracking, block cracking, longitudinal cracking, transverse cracking, potholes, patching, bleeding, and raveling as input variables, the variables were fuzzified into fuzzy subsets. The fuzzy subsets of the variables were considered to have triangular membership functions. The relationships between nine pavement distress parameters and PCI were represented by a set of fuzzy rules. The fuzzy rules relating input variables to the output variable of sediment discharge were laid out in the IF–THEN format. The commonly used weighted average method was employed for the defuzzification procedure. The coefficient of determination ( R 2 ), root mean squared error (RMSE), and mean absolute error (MAE) were used as the performance indicator metrics to evaluate the performance of analytical models. [ABSTRACT FROM AUTHOR]

The present paper is a contribution to the study of a new Modern Greek variety that is spoken in Canada by first-generation immigrants who arrived in this country between 1945 and 1975. This variety displays features originating from: (a) A Common Modern Greek spoken in Greece around the middle of the 20th century, (b) mutually intelligible characteristics of the immigrants' native dialectal varieties, mainly from the Peloponnese, (c) contact with English, (d) Standard Modern Greek. We present, discuss, and analyze data collected within the framework of the project "ImmiGrec: Stories of Greek immigration in Canada." We focus on linguistic elements that could be considered indicative features of a Greek-Canadian Koiné, more particularly by investigating the borrowing and integration of English nouns and the variation in the use of the unstressed syllabic augment /e-/ and two different imperfective past suffixes. [ABSTRACT FROM AUTHOR]

Crop identification and classification are of great significance to agricultural land use management. The physically constrained general model-based decomposition (PCGMD) has proven to be a promising method in comparison with the typical four-component decomposition methods in scattering mechanism interpretation and identifying vegetation types. However, the robustness of PCGMD requires further investigation from the perspective of final applications. This paper aims to validate the efficiency of the PCGMD method on crop classification for the first time. Seven C-band time-series RADARSAT-2 images were exploited, covering the entire growing season over an agricultural region near London, Ontario, Canada. Firstly, the response and temporal evolution of the four scattering components obtained by PCGMD were analyzed. Then, a forward selection approach was applied to achieve the highest classification accuracy by searching an optimum combination of multi-temporal SAR data with the random forest (RF) algorithm. For comparison, the general model-based decomposition method (GMD), the original and its three improved Yamaguchi four-component decomposition approaches (Y4O, Y4R, S4R, G4U), were used in all tests. The results reveal that the PCGMD method is highly sensitive to seasonal crop changes and matches well with the real physical characteristics of the crops. Among all test methods used, the PCGMD method using six images obtained the optimum classification performance, reaching an overall accuracy of 91.83%. [ABSTRACT FROM AUTHOR]

Recently, tools developed for detecting human activities have been quite prominent in contributing to health issue prevention and long-term healthcare. For this occasion, the current study aimed to evaluate the performance of eye-movement complexity features (from multi-scale entropy analysis) compared to eye-movement conventional features (from basic statistical measurements) on detecting daily computer activities, comprising reading an English scientific paper, watching an English movie-trailer video, and typing English sentences. A total of 150 students participated in these computer activities. The participants' eye movements were captured using a desktop eye-tracker (GP3 HD Gazepoint™ Canada) while performing the experimental tasks. The collected eye-movement data were then processed to obtain 56 conventional and 550 complexity features of eye movement. A statistic test, analysis of variance (ANOVA), was performed to screen these features, which resulted in 45 conventional and 379 complexity features. These eye-movement features with four combinations were used to build 12 AI models using Support Vector Machine, Decision Tree, and Random Forest (RF). The comparisons of the models showed the superiority of complexity features (85.34% of accuracy) compared to conventional features (66.98% of accuracy). Furthermore, screening eye-movement features using ANOVA enhances 2.29% of recognition accuracy. This study proves the superiority of eye-movement complexity features. [ABSTRACT FROM AUTHOR]

Assessing the energy performance of existing residential buildings (ERB) has been identified as key to improving building energy efficiency and reducing associated greenhouse gas emissions in Canada. However, identifying optimal retrofit packages requires a significant amount of knowledge of building energy modelling, and it is a time-consuming and laborious process. This paper proposed a data-driven framework that combines machine learning, multi-objective optimization, and multi-criteria decision-making techniques to evaluate the energy performance of ERB and thereby formulate optimal retrofit plans. First, an artificial neural network (ANN) was developed to predict the energy performance of a wide range of retrofit packages. A genetic algorithm was employed to determine the best structure and hyperparameters of the ANN model. Then, the energy consumption results were integrated with environmental and economic impact data to evaluate the environmental and economic performance of retrofit packages and thereby identify Pareto optimal solutions. Finally, a multi-criteria decision-making method was used to select the best retrofit packages among the optimal solutions. The proposed framework was validated using data on a typical residential building in British Columbia, Canada. The results indicated that this framework could effectively predict building energy performance and help decision-makers to make an optimal decision when choosing retrofit packages. [ABSTRACT FROM AUTHOR]

In Canada, many mines have adopted the sublevel stoping method, such a blasthole stoping (BHS), to extract steeply deposited minerals. Sill pillars are usually kept in place in this mining method to support the weight of the overburden in underground mining. To prolong the mine's life, sill pillars will be recovered, and sill pillar recovery could cause failures, fatality, and equipment loss in the stopes. In this paper, three sill pillar recovery schemes—SBS, SS1, and SS2—were proposed and conducted to assess the feasibility of recovering two sill pillars in a hard rock mine by developing a full-sized three-dimensional (3D) analysis model employing the finite element method (FEM). The numerical model was calibrated by comparing the model computed ground settlement with the in situ monitored ground settlement data. The rockburst tendency of the stope accesses caused by the sill pillar recovery was assessed by employing the tangential stress (Ts) criterion and burst potential index (BPI) criterion. All three proposed sill pillar recovery schemes were feasible and safe to recover the sill pillars in this hard rock mine, and the scheme SBS was the optimum one among the three schemes. [ABSTRACT FROM AUTHOR]

Joseph Kerski has identified five converging global trends—geo-awareness, geo-enablement, geotechnologies, citizen science, and storytelling—which contribute to the increased relevance of geography for education and society. While these trends are discussed by Kerski in the context of the proliferating significance of geography in teaching and education, they also provide a useful lens for considering the increasing ubiquity of critical approaches to cartography both in general and in the context of teaching and education, where mapping can include participatory collaborations with individuals from a variety of knowledge communities and extend to the mapping of experiences, emotions, and Indigenous perspectives. In this paper, we consider these trends and related ideas such as Kerski's "geoliteracy" and metaliteracy in light of some relatively current examples and in light of the evolution of research and teaching linked with a series of interrelated map-based projects and courses that take a multidimensional approach to teaching and learning about the Residential Schools Legacy in Canada. [ABSTRACT FROM AUTHOR]

A major hurdle in pediatric formulation development is the lack of safety and toxicity data on some of the commonly used excipients. While the maximum oral safe dose for several kinds of excipients is known in the adult population, the doses in pediatric patients, including preterm neonates, are not established yet due to the lack of evidence-based data. This paper consists of four parts: (1) country-specific perspectives in different parts of the world (current state, challenges in excipients, and ongoing efforts) for ensuring the use of safe excipients, (2) comparing and contrasting the country-specific perspectives, (3) past and ongoing collaborative efforts, and (4) future perspectives on excipients for pediatric formulation. The regulatory process for pharmaceutical excipients has been developed. However, there are gaps between each region where a lack of information and an insufficient regulation process was found. Ongoing efforts include raising issues on excipient exposure, building a region-specific database, and improving excipient regulation; however, there is a lack of evidence-based information on safety for the pediatric population. More progress on clear safety limits, quantitative information on excipients of concern in the pediatric population, and international harmonization of excipients' regulatory processes for the pediatric population are required. [ABSTRACT FROM AUTHOR]

Research has historically exploited Indigenous communities, particularly in the medical and health sciences, due to the dominance of discriminatory colonial systems. In many regions across Canada and worldwide, historical and continued injustices have worsened health among Indigenous Peoples. Global health crises such as climate change are most adversely impacting Indigenous communities, as their strong connection to the land means that even subtle changes in the environment can disproportionately affect local food and health systems. As we explore strategies for climate change preparedness and adaptation, Indigenous Peoples have a wealth of Traditional Knowledge to tackle specific climate and related health issues. If combined with digital citizen science, data collection by citizens within a community could provide relevant and timely information about specific jurisdictions. Digital devices such as smartphones, which have widespread ownership, can enable equitable participation in citizen science projects to obtain big data for mitigating and managing climate change impacts. Informed by a Two-Eyed Seeing approach, a decolonized lens to digital citizen science can advance climate change adaptation and preparedness efforts. This paper describes the 'Bridge Framework' for decolonizing digital citizen science using a case study with a subarctic Indigenous community in Saskatchewan, Canada. [ABSTRACT FROM AUTHOR]

Unexpected observations of strong radiowave scatter at a ~85–90 km altitude with very high frequency radars were explained in the early 1990s, when it was demonstrated that these were due to special turbulent and small-scale scatterers with high Schmidt number. Studies of these phenomena have primarily been concentrated in polar regions, and the events seem most prominent in regions of very cold air (below 140 K). Such radar echoes are referred to as polar mesosphere summer echoes (PMSE), and are rare at lower latitudes. In this paper we report observations of similar scatterers at sites below 50° latitude. The nature of these scatterers is discussed and results are compared to observations at the polar site of Eureka, Canada. Mid-latitude observations at frequencies of 48.92 and 45.47 MHz were made, respectively, at Abitibi Canyon (49.9° N latitude) and Markstay (46.5° N latitude) in Ontario, Canada. In particular, we look at the relationship of these scatterers to geophysical parameters, especially the Ap index. Our results suggest that mesospheric air with temperatures less than 140 K now exists below 50° latitude. This may be an indication of an equator-ward creep of global mesospheric cooling (which is associated with the well-known tropospheric global warming), but the scatterers at lower latitudes also demonstrate correlation with the Ap index. On the other hand, the polar scatterers at Eureka demonstrated no correlation of any significance with Ap. The importance of these results in regard to the global distribution of mesospheric temperatures is discussed, and comparisons to other measurements are made. [ABSTRACT FROM AUTHOR]