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Although burnout is often discussed as 'present' or 'not-present', the conceptual framework of an engagement-burnout continuum is more accurate and useful. Recognition of individuals' transitional states of burnout also allows for earlier detection of issues and tailored interventions to address the full burnout spectrum.Previously reported Maslach Burnout Inventory-Human Services Scale (MBI-HSS) data from a 2017 national survey of 1272 veterinarians across Canada were re-analysed using a latent profile analysis to classify individuals along the engagement-burnout continuum.Four clusters were identified: engaged (10.8%), ineffective (18.9%), overextended (29.6%) and burnout (40.7%). These results indicate that most participants (89.2%) had one, or a combination, of high exhaustion, high depersonalisation and low professional efficacy.This cross-sectional study represents data from one point in time and may be subject to response bias.We discuss strategies-particularly long-term, organisational-level interventions-to promote engagement and help address workplace issues contributing to inefficacy, overextension and burnout in the veterinary profession. We also recommend MBI data be analysed via latent profiles to provide a more nuanced view of burnout, allow for earlier recognition of workplace issues and facilitate more meaningful interventions and comparisons across populations.

Amidst unprecedented variability and change in climate across the Circumpolar North, increasing attention has been directed towards integrated environment and health monitoring systems to inform responses to climate change impacts on Inuit health. Yet, existing monitoring systems are often not designed to consider Inuit-identified conceptualizations of wellbeing that can help identify, monitor, and respond to the more intangible losses and damages from climate change. This study—conducted in partnership with the Inuit community of Rigolet, Nunatsiavut, Canada—aimed to characterize what Inuit value and want monitored to develop a conceptual framework for an Inuit-led integrated monitoring system. Using community-led research approaches, data were drawn from in-depth, semi-structured interviews with 31 individuals including community members (n = 13), government representatives (n = 14), and healthcare professionals (n = 4) in Nunatsiavut between 2015 and 2016. Thematic analysis of these data was guided by a constant-comparative process. Interviewees described how monitoring climatic and environmental conditions was grounded in land-attachment, reciprocity, knowledge sharing, and self-determination. Findings enhance understandings of how Inuit-led monitoring in the North can guide climate change adaptation that considers intangible losses and damages to wellbeing and ways of living. Further, these findings illustrate how localized perspectives on climate change can contribute to place-based public health research and policy that reflect what matters most to communities.

Successful mitigation of emerging infectious disease requires that the public adopt recommended behaviours, which is directly influenced by effective crisis communication. Social media has become an important communication channel during COVID-19 where official actors, influencers, and the public are co-creating crisis messages. Our research examined COVID-19-related crisis messages across Canadian influencer accounts within news media, politicians, public health and government, science communicators, and brand influencer and celebrities, posted on Instagram between December 2019 and March 2021 for Health Belief Model and Extended Parallel Processing Model constructs and the corresponding public comment sentiment and engagement. Thirty-three influencer accounts resulted in a total of 2,642 Instagram posts collected, along with 461,436 comments, which showed overall low use of constructs in both captions and images. Further, most posts used no combinations (n = 0 or 1 construct per post) of constructs in captions and images and very infrequently used captions that combined threat (severity and susceptibility) with cues to action and efficacy. Brand influencers and celebrities, politicians, and science communicators had above average post engagement while public health and government and news media had lower. Finally, most influencers saw the largest proportion of neutral sentiment comments. Crisis messages must be designed to include combinations of constructs that increase message acceptance and influence risk perception and efficacy to increase the adoption of recommended and mandated behaviours.

Substantial global data show that many taxa are shifting their phenologies in response to climate change. For birds, migration arrival dates in breeding regions have been shifting earlier, and there is evidence that both evolutionary adaptation and behavioural flexibility influence these shifts. As more efficient flyers may be able to demonstrate more flexibility to respond to changing conditions during migratory flight, we hypothesize that differences among passerine species in flight efficiency, as reflected by morphology, may be associated with the magnitude of shifts in arrival date in response to climate warming. We applied a logistic model to 18 years of eBird data to estimate mean arrival date for 44 common passerines migrating to northeast North America. We then used linear mixed-effects models to estimate changes in mean arrival date and compared these changes to morphological proxies for flight efficiency and migratory distance using phylogenetic generalized least squares models. On average, passerine species shifted their arrival dates 0.120 days earlier each year, with 27 of the 44 species shifting to significantly earlier arrival times, and two shifting to significantly later ones. Of the 15 species with non-significant shifts, 13 trended toward earlier arrivals. Longer migration distances and higher wing aspect ratios were associated with greater shifts toward earlier arrivals. Migration distance and aspect ratio were also significantly correlated to each other. This suggests that changes in arrival date are affected by factors pertaining to migratory flight over long distances namely, flight efficiency and migration distance. These traits may be able predict the magnitude of arrival date shift, and by extension identify species that are most at risk to climate change due to inflexible arrival timing.

DNA barcoding has greatly accelerated the pace of specimen identification to the species level, as well as species delineation. Whereas the application of DNA barcoding to the matching of unknown specimens to known species is straightforward, its use for species delimitation is more controversial, as species discovery hinges critically on present levels of haplotype diversity, as well as patterning of standing genetic variation that exists within and between species. Typical sample sizes for molecular biodiversity assessment using DNA barcodes range from 5 to 10 individuals per species. However, required levels that are necessary to fully gauge haplotype variation at the species level are presumed to be strongly taxon‐specific. Importantly, little attention has been paid to determining appropriate specimen sample sizes that are necessary to reveal the majority of intraspecific haplotype variation within any one species. In this paper, we present a brief outline of the current literature and methods on intraspecific sample size estimation for the assessment of COI DNA barcode haplotype sampling completeness. The importance of adequate sample sizes for studies of molecular biodiversity is stressed, with application to a variety of metazoan taxa, through reviewing foundational statistical and population genetic models, with specific application to ray‐finned fishes (Chordata: Actinopterygii). Finally, promising avenues for further research in this area are highlighted.

Climate change impacts on population health and wellbeing are spatially and socially distributed, and shape place-based capacities, constraints, and priorities for climate change adaptation. Inuit across the Circumpolar North have called for public health monitoring and response systems that integrate environmental and human health data, and provide localized information to support place-based adaptation strategies. The goal of this research was to qualitatively characterize how Inuit in Rigolet, Nunatsiavut, Labrador, Canada, identify, interpret, and use environmental and climatic observations to make decisions that will protect and promote their health and wellbeing in the context of climate change. Inuit community research leads conducted in-depth, semi-structured interviews with Rigolet Inuit to identify and contextualize environmental and climatic observations that were important for monitoring. Under the direction of community research leads, qualitative data from interviews were analyzed by the core research team using constant-comparative thematic analysis methods to ensure emergent findings were grounded in the voices and perspectives of Rigolet Inuit. Rigolet Inuit considered all climatic and environmental observations to be connected and emphasized the importance of collective, intergenerational knowledge in understanding and adapting to current and future climate change. The ways that Rigolet Inuit interpreted and used these observations for making decisions depended on perceived relevance and importance of observations, trustworthiness of information, and personal thresholds for risks. Knowledge shared by Rigolet Inuit demonstrated the nuanced, relational nature of how climatic and environmental observations are identified, interpreted, and used in decision-making for place-based climate change adaptation. It is important to prioritize these place-based and locally validated ways of knowing and learning about the land in the development of integrated monitoring systems to inform adaptation strategies that are based on a community’s existing resilience and creativity, and premised on relationships among people and places. In so doing, we can identify entry points for improving the ways in which monitoring systems function to link environment and health data, and inform robust, evidence-based adaptation strategies and policies.

UNSTRUCTURED The emergence of COVID-19 spurred the formation of myriad teams to tackle every conceivable aspect of the virus and thwart its spread. Enabled by global digital connectedness, collaboration has become a constant theme throughout the pandemic, resulting in the expedition of the scientific process (including vaccine development), rapid consolidation of global outbreak data and statistics, and experimentation with novel partnerships. To document the evolution of these collaborative efforts, the authors collected illustrative examples as the pandemic unfolded, supplemented with publications from the JMIR COVID-19 Special Issue. Over 60 projects rooted in collaboration are categorized into five main themes: knowledge dissemination, data propagation, crowdsourcing, artificial intelligence, and hardware design and development. They highlight the numerous ways that citizens, industry professionals, researchers, and academics have come together worldwide to consolidate information and produce products to combat the COVID-19 pandemic. Initially, researchers and citizen scientists scrambled to access quality data within an overwhelming quantity of information. As global curated data sets emerged, derivative works such as visualizations or models were developed that depended on consistent data and would fail when there were unanticipated changes. Crowdsourcing was used to collect and analyze data, aid in contact tracing, and produce personal protective equipment by sharing open designs for 3D printing. An international consortium of entrepreneurs and researchers created a ventilator based on an open-source design. A coalition of nongovernmental organizations and governmental organizations, led by the White House Office of Science and Technology Policy, created a shared open resource of over 200,000 research publications about COVID-19 and subsequently offered cash prizes for the best solutions to 17 key questions involving artificial intelligence. A thread of collaboration weaved throughout the pandemic response, which will shape future efforts. Novel partnerships will cross boundaries to create better processes, products, and solutions to consequential societal challenges.

The emergence of COVID-19 spurred the formation of myriad teams to tackle every conceivable aspect of the virus and thwart its spread. Enabled by global digital connectedness, collaboration has become a constant theme throughout the pandemic, resulting in the expedition of the scientific process (including vaccine development), rapid consolidation of global outbreak data and statistics, and experimentation with novel partnerships. To document the evolution of these collaborative efforts, the authors collected illustrative examples as the pandemic unfolded, supplemented with publications from the JMIR COVID-19 Special Issue. Over 60 projects rooted in collaboration are categorized into five main themes: knowledge dissemination, data propagation, crowdsourcing, artificial intelligence, and hardware design and development. They highlight the numerous ways that citizens, industry professionals, researchers, and academics have come together worldwide to consolidate information and produce products to combat the COVID-19 pandemic. Initially, researchers and citizen scientists scrambled to access quality data within an overwhelming quantity of information. As global curated data sets emerged, derivative works such as visualizations or models were developed that depended on consistent data and would fail when there were unanticipated changes. Crowdsourcing was used to collect and analyze data, aid in contact tracing, and produce personal protective equipment by sharing open designs for 3D printing. An international consortium of entrepreneurs and researchers created a ventilator based on an open-source design. A coalition of nongovernmental organizations and governmental organizations, led by the White House Office of Science and Technology Policy, created a shared open resource of over 200,000 research publications about COVID-19 and subsequently offered cash prizes for the best solutions to 17 key questions involving artificial intelligence. A thread of collaboration weaved throughout the pandemic response, which will shape future efforts. Novel partnerships will cross boundaries to create better processes, products, and solutions to consequential societal challenges.

Cloud computing services such as file storage and big data analytics offer cost-effective, secure, flexible, and sustainable services to their users. Despite their benefits, the adoption of many cloud services is still limited, and many organizations are hesitant to adopt cloud technologies for several reasons. Researchers have used innovation adoption theories to explore the factors influencing users’ decisions toward accepting and using a new information system. This study presents a systematic review of the factors influencing organizational decisions concerning the acceptance of cloud-based technologies using the technology-organization-environment (TOE) framework. We analyze, integrate, and classify these factors and show that much of the literature has emphasized the technical aspects of technology adoption, such as cloud security. We further show factors like top management support, relative advantage, cloud complexity, and competitive pressure are the most critical factors affecting organizational attitude toward cloud technology adoption.

Rising COVID-19 cases in Canada in early 2021, coupled with pervasive mis- and disinformation, demonstrate the critical relationship between effective crisis communication, trust, and risk protective measure adherence by the public. Trust in crisis communication is affected by the communication’s characteristics including transparency, timeliness, empathy, and clarity, as well as the source and communication channels used. Crisis communication occurs in a rhetorical arena where various actors, including public health, news media, and the public, are co-producing and responding to messages. Rhetorical arenas must be monitored to assess the acceptance of messaging. The quality and content of Canadian public health and news media crisis communication on Facebook were evaluated to understand the use of key guiding principles of effective crisis communication, the focus of the communication, and subsequent public emotional response to included posts. Four hundred and thirty-eight posts and 26,774 anonymized comments were collected and analyzed. Overall, the guiding principles for effective crisis communication were inconsistently applied and combined. A limited combination of guiding principles, especially those that demonstrate trustworthiness, was likely driving the negative sentiment uncovered in the comments. Public health and news media should use the guiding principles consistently to increase positive sentiment and build trust among followers.

International Maritime Organization’s Marine Fuel Rule, or IMO 2020, is just around the corner. Few refineries are ready for the change to bunker fuel specifications caused by IMO 2020 where marine bunker fuel sulfur content will be reduced to 0.5 wt% from current 3.5 wt%. Many refineries around the world, who currently produce about 4 million barrels per day of high sulfur bunker fuel stocks, still need to invest in upgrading technologies. In the past Visbreaking was used to make Residue Fuel Oil (RFO) as it reduces the viscosity of the resid by thermally cracking the heavy molecules, thereby minimzing cutter stocks. It also has a relatively low capital and operating costs compared to other residue upgrading technologies. However, it concentrates contaminants (sulfur, nitrogen, and Conradson Carbon Residue (CCR)) in the product. As a result, it is not considered a viable solution for RFO sulfur reduction. Fortunately, there are several technologies available to upgrade the high sulfur residuum oil to high value products or low sulfur fuel oil as shown in Figure 1. The benefits and features of each of these options is discussed in this paper to provide an understanding of the various processes’ merits. Case studies are also provided to provide indications of which technologies are best suited depending on the specific scenario.

In this paper, we investigate the impact that human mobility and social interactions have on data replication schemes in mobile ad hoc networks (MANETs), and how they can be used to improve content availability. Since nodes in MANETs are free to move around, network partitions can result in disconnections between nodes which store content and those accessing it. In this work we investigate some of the metrics that are typically used to evaluate storage schemes. We discuss several different data storage and replication methods designed for MANETs, and under which circumstance one may be a better choice than another. We also investigate human mobility models and how social interactions are leveraged by the storage schemes might be leveraged to improve content availability in MANETs.

Universities today possess large volumes of structured and unstructured data, generated from several educational and administrative processes and systems. This data forms what is known today as big data. The common challenge many universities face today is to find the most effective way to harness this data, visualize it and then optimize it for its purposes of continuously delivering enhanced education. While big data technologies require costly infrastructure and expertise for its life cycle management, there has been overwhelming success using Big Data Analytics (BDA) in the business sector for cost reduction and effectiveness. This provides the motivation to explore the use of BDA in the education sector to understand the opportunities it might provide to higher education. In this paper, we explore how data and analytics have been used so far in the higher education sector for enhanced learning or to support decisions, what opportunities and challenges surround BDA in this sector.

We developed a continuous, nonlinear model (FLOG-CN) linking carbon mineralization and nitrogen mineralization–immobilization with respect to time that successfully reproduced the complex CO 2 -C and SMN dynamics for a collection of 70 paired C and N soil datasets. Application of the model to diverse C and N datasets showed that incorporating latency into the model of C mineralization, and using C to drive N dynamics, allows heterogeneous data from many different soil amendments to be described by the same model. We successfully modeled complex CO 2 -C and SMN dynamics of widely different shapes and from a variety of soil amendments containing plant and animal residues. The re-interpretation of these datasets with the FLOG-CN models improved the quantitative analysis of C and N dynamics, yielding new insights into how amendment characteristics and experimental conditions influence the timing and quantity of C and N mineralized. Model parameters were responsive to varying soil characteristics (pH, C, N, C:N), amendment N:C, amendment rate, incubation temperature, and N additions. Stepwise regression was used to predict model parameters using metadata available for 56 of these datasets. Significant relationships were developed to estimate model parameters independently using measured system properties or other model parameters that could be independently estimated. Estimates of C and N dynamics both fell along a 1:1 line indicating that the model parameters could be adequately described by the measured properties, but the available metadata was not able to describe C dynamics with high precision. Nitrogen mineralization–immobilization was strongly related to amendment N:C, and switched between the two processes at an amendment N:C between 0.077 and 0.085 (C:N between 11.7 and 12.9). We believe that the modeling approach described here will allow quantitative and objective comparisons of diverse C and N datasets that have been hindered by subjective descriptions of the past.

Lake whitefish (Coregonus clupeaformis) are an ecologically, economically, and culturally important species to the native and non-native fishers of Lake Huron, Canada. Studying the effects of anthropogenic activity on lake whitefish is of utmost importance to ensure this species remains viable in its environment for sustainable harvest. One analysis tool that is frequently used for ecological population risk assessments are agent-based models (ABMs), in which the population is represented as a network of heterogeneous individual agents that interact with one another and their environment. However, in an ABM that incorporates a high level of biological detail to model a large population moving within a spatial environment over time, significant computation is required to manage, manipulate, and store the relevant data for each agent over successive time iterations. We introduce a new approach to ABMs known as environmental ABMs (enviro-ABMs) to reduce this computational expense and simulation runtime. Specifically, we divide the environment into a collection of spatially indexed cells and treat each of these as a single agent, allowing fish to move from one contiguous cell to another. This reduces the computational requirements to a limited number of active cells. In addition to more predictable computational requirements, this method keeps all fish sorted by age and location for efficient mortality, spawning, and harvest operations, and reduces the amount of computational overhead needed. Applying the enviro-ABM to our case study in Lake Huron, we demonstrate how it can be used to model anthropogenic activities and stressors that may affect lake whitefish, and how the model can be used to facilitate fisheries management decision making. While the model is applied specifically to the case of whitefish in Lake Huron, it can be generalized to conduct risk assessment for other species in a variety of habitats.

Anti-Mullerian hormone (AMH) is expressed by both male and female fetuses during mammalian development, with males expressing AMH earlier and at significantly higher concentration. The aim of the current study was to explore the potential impact of pregnancy and fetal sex on maternal AMH and to determine if plasma (Pl) AMH or placenta intercotyledonary membrane and cotyledonary AMH receptor 2 (AMHR2) mRNA expression differ in pregnant cows carrying male vs. female fetuses. AMH levels in blood were measured using a bovine optimized ELISA kit. Cows pregnant with a male fetus were observed to have a significantly greater difference in Pl AMH between day 35 and 135 of gestation. Average fetal AMH level between 54 and 220days of gestation was also observed to be significantly higher in male vs. female fetuses. Intercotyledonary membranes and cotyledons were found to express AMHR2 between days 38 and 80 of gestation at similar levels in both fetal sexes. These findings support the hypothesis that fetal sex alters maternal Pl AMH during pregnancy in cattle.

This paper suggests using mobile touchscreen devices to assist students with vision loss in working with data. It presents an integrated approach that combines current sonification methods with interactive multi-touch gesture-based exploration of data, designed to aid students in mental visualization and comprehension of data and function plots. This approach aims to help students with vision loss study independently of support centres, collaborate with their peers, and participate in group studies. Initial user study evaluating this approach and demonstrating its feasibility is presented; further research pathways are also discussed.

The hypothalamic-pituitary-adrenal (HPA) axis is a major part of the neuroendocrine system in animal responses to stress. It is known that the HPA axis is attenuated at parturition to prevent detrimental effects of glucocorticoid secretion including inhibition of lactation and maternal responsiveness. Luman/CREB3 recruitment factor (LRF) was identified as a negative regulator of CREB3 which is involved in the endoplasmic reticulum stress response. Here, we report a LRF gene knockout mouse line that has a severe maternal behavioral defect. LRF(-/-) females lacked the instinct to tend pups; 80% of their litters died within 24 h, while most pups survived if cross-fostered. Prolactin levels were significantly repressed in lactating LRF(-/-) dams, with glucocorticoid receptor (GR) signaling markedly augmented. In cell culture, LRF repressed transcriptional activity of GR and promoted its protein degradation. LRF was found to colocalize with the known GR repressor, RIP140/NRIP1, which inhibits the activity by GR within specific nuclear punctates that are similar to LRF nuclear bodies. Furthermore, administration of prolactin or the GR antagonist RU486 restored maternal responses in mutant females. We thus postulate that LRF plays a critical role in the attenuation of the HPA axis through repression of glucocorticoid stress signaling during parturition and the postpartum period.

PIWI proteins and their associated piRNAs have been the focus of intensive research in the past decade; therefore, their participation in the maintenance of genomic integrity during spermatogenesis has been well established. Recent studies have suggested important roles for the PIWI/piRNA system outside of gametogenesis, based on the presence of piRNAs and PIWI proteins in several somatic tissues, cancers, and the early embryo. Here, we investigated the small RNA complement present in bovine gonads, gametes, and embryos through next-generation sequencing. A distinct piRNA population was present in the testis as expected. However, we also found a large population of slightly shorter, 24–27 nt piRNA-like RNA (pilRNAs) in pools of oocytes and zygotes. These oocyte and embryo pilRNAs exhibited many of the canonical characteristics of piRNAs including a 1U bias, the presence of a ‘ping-pong’ signature, genomic clustering, and transposable element targeting. Some of the major transposons targeted by oocyte and zygote pilRNA were from the LINE RTE and ERV1 classes. We also identified pools of pilRNA potentially derived from, or targeted at, specific mRNA sequences. We compared the frequency of these gene-associated pilRNAs to the fold change in the expression of respective mRNAs from two previously reported transcriptome datasets. We observed significant negative correlations between the number of pilRNAs targeting mRNAs, and their fold change in expression between the 4–8 cell and 8–16 cell stages. Together, these results represent one of the first characterizations of the PIWI/piRNA pathway in the translational bovine model, and in the novel context of embryogenesis.

The biological effects of exposure to radioactive fluorodeoxyglucose (18F-FDG) were investigated in the lymphocytes of patients undergoing positron emission tomography (PET) procedures. Low-dose, radiation-induced cellular responses were measured using 3 different end points: (1) apoptosis; (2) chromosome aberrations; and (3) γH2AX foci formation. The results showed no significant change in lymphocyte apoptosis, or chromosome aberrations, as a result of in vivo 18F-FDG exposure, and there was no evidence the PET scan modified the apoptotic response of lymphocytes to a subsequent 2 Gy in vitro challenge irradiation. However, lymphocytes sampled from patients following a PET scan showed an average of 22.86% fewer chromosome breaks and 39.16% fewer dicentrics after a subsequent 2 Gy in vitro challenge irradiation. The effect of 18F-FDG exposure on phosphorylation of histone H2AX (γH2AX) in lymphocytes of patients showed a varied response between individuals. The relationship between γH2AX foci formation and increasing activity of 18F-FDG was not directly proportional to dose. This variation is most likely attributed to differences in the factors that combine to constitute an individual’s radiation response. In summary, the results of this study indicate18F-FDG PET scans may not be detrimental but can elicit variable responses between individuals and can modify cellular response to subsequent radiation exposures.

The purpose of this study is to assess the effect of topical amitriptyline, ketamine, and lidocaine (AKL) on alleviation of neuropathic pain from radiation dermatitis and the feasibility of a randomized trial.Eligible subjects had radiation dermatitis with dry or moist desquamation with neuropathic pain and were intolerant or allergic to standard intervention. AKL was applied to painful sites three times a day daily until 2 weeks post-radiotherapy. Subjects were monitored every 2-5 days during radiotherapy and at 2 and 6 weeks after completion of radiotherapy. The University of Washington Neuropathic Pain Scale was used to grade the neuropathic pain before and after use of the interventional gel. Compliance was assessed by asking subjects at each visit how frequently they were using the interventional gel.Over a 14-month period, 16 subjects met eligibility criteria. Eighty-two percent of subjects used the AKL as directed. Five subjects (32%) reported fatigue, and three subjects (19%) reported site irritation from the interventional gel. AKL was shown to significantly reduce (p0.05) pain intensity, sharpness, burning, sensitivity, itchiness, unpleasantness, deepness, and surfaceness levels on a short-term basis (i.e., between pre-treatment and 30 min post-treatment). AKL was shown to significantly reduce (p0.05) burning levels on a long-term basis (i.e., between pre-treatment and 2 weeks post-treatment).AKL was a safe intervention to use with minimal toxicity and good compliance. It significantly reduced several measures of neuropathic pain associated with radiation dermatitis. A larger-scale study would require recruitment from multiple centers.