Simon Fraser University
  • Burnaby, British Columbia, Canada
Recent publications
The COVID-19 pandemic has caused a great “reset” and has challenged many assumptions about work and life in general. Our focus in this paper is on the future of global work in the context of multinational enterprises (MNEs). We take a phenomenon-based approach to describe the important trends and challenges affecting the where, who, how and why of global work. As we highlight implications for organizations and individuals, we offer a set of research questions to guide future research and inform IHRM practitioners.
Background: Collectivism has been identified as a protective factor against COVID-19 - perhaps due to increased conformity with social norms regarding prevention behaviors. Other studies have also found that individualism can inspire uptake of preventative behaviors as a means of personal protection. It is possible that these cultural orientations may promote different patterns of prevention (e.g. mask wearing vs. social distancing). Furthermore, existing studies examining the role of individualism and collectivism during the COVID-19 pandemic have frequently failed to account for other psychological processes, including differences in personality, which could help provide a better understanding of the psychological process underlying prevention behavior. Methods: Participants were recruited using social media advertisements. The Cultural Orientations Scale measured individualism-collectivism and hierarchism-egalitarianism. The Ten Item Personality Inventory measured the five factor model of personality. Multivariable models, dominance analyses and structural equation mediation tests were used to identify the most important predictors of COVID-19 prevention behavior (i.e. mask-wearing, hand-washing, reducing social interactions, physical distancing, staying at home and social bubbling), controlling for demographic and situational factors. Results: Among 774 participants, most (i.e. 60-80%) reported uptake of COVID-19 prevention behaviors. Higher vertical (hierarchical) collectivism was associated with staying at home and higher horizontal (egalitarian) individualism was associated with mask-wearing and reducing social interactions. Neither Vertical Collectivism nor Horizontal Collectivism were significantly associated with any of the prevention behaviors when controlling for personality traits and confounding variables. Agreeableness was identified as a key mediator of the correlation between these cultural orientations on general uptake of COVID-19 prevention behaviors. Conclusions: Cultural orientations (e.g. collectivism-individualism, hierarchism-egalitarianism) and personality traits (e.g. Agreeableness) are salient correlates of COVID-19 prevention behaviors and therefore should be accounted for in the development, design and delivery of health promotion messages aiming to increase uptake of these behaviors.
In this study, based on inspiration drawn from origami and the suction mechanism of leeches, a dry electrode is developed for reliable blood pressure (BP) monitoring. The leech-inspired suction mechanism generated a local soft vacuum facilitating appropriate contact with the human skin. Subsequently, an electrocardiogram (ECG) sensor, termed a leech-inspired origami (LIO) sensor, was constructed using the developed dry electrode. The LIO with a sensing robot system ensures reliable ECG signals with a signal-to-noise ratio of 21.7 ± 0.56 dB. From the paired detection of ECG and photoplethysmography (PPG) through human–robot interaction, BP monitoring was demonstrated. The average difference of the systolic BP between that estimated by the sensing robot and that monitored by the sphygmomanometer was 0.03 mmHg, indicating the reliable BP monitoring ability of the sensing robot. The LIO sensing system inspired by origami and leech behaviors makes BP sensing tools feasible, which in turn would further the development of a remote healthcare monitoring robotic system.
The accurate simulation of additional interactions at the ATLAS experiment for the analysis of proton–proton collisions delivered by the Large Hadron Collider presents a significant challenge to the computing resources. During the LHC Run 2 (2015–2018), there were up to 70 inelastic interactions per bunch crossing, which need to be accounted for in Monte Carlo (MC) production. In this document, a new method to account for these additional interactions in the simulation chain is described. Instead of sampling the inelastic interactions and adding their energy deposits to a hard-scatter interaction one-by-one, the inelastic interactions are presampled, independent of the hard scatter, and stored as combined events. Consequently, for each hard-scatter interaction, only one such presampled event needs to be added as part of the simulation chain. For the Run 2 simulation chain, with an average of 35 interactions per bunch crossing, this new method provides a substantial reduction in MC production CPU needs of around 20%, while reproducing the properties of the reconstructed quantities relevant for physics analyses with good accuracy.
Muons are particles with a spin of ½ that can be implanted into a wide range of condensed matter materials to act as a local probe of the surrounding atomic environment. Measurement of the muon’s precession and relaxation provides an insight into how it interacts with its local environment. From this, unique information is obtained about the static and dynamic properties of the material of interest. This has enabled muon spin spectroscopy, more commonly known as muon spin rotation/relaxation/resonance (μSR), to develop into a powerful tool to investigate material properties such as fundamental magnetism, superconductivity and functional materials. Alongside this, μSR may be used to study, for example, energy storage materials, ionic diffusion in potential batteries, the dynamics of soft matter, free radical chemistry, reaction kinetics, semiconductors, advanced manufacturing and cultural artefacts. This Primer is intended as an introductory article and introduces the μSR technique, the typical results obtained and some recent advances across various fields. Data reproducibility and limitations are also discussed, before highlighting promising future developments. Muon spin spectroscopy examines how muons interact with their local environment through measurement of the muon’s precession and relaxation. This provides unique information about the static and dynamic properties of a material. This Primer gives an introductory overview to muon spin spectroscopy, describing how muons are produced and used experimentally in various applications.
Background Changes in the diversity of herbivore communities can strongly influence the functioning of northern ecosystems. Different herbivores have different impacts on ecosystems because of differences in their diets, behaviour and energy requirements. The combined effects of different herbivores can in some cases compensate each other but lead to stronger directional changes elsewhere. However, the diversity of herbivore assemblages has until recently been a largely overlooked dimension of plant–herbivore interactions. Given the ongoing environmental changes in tundra ecosystems, with increased influx of boreal species and changes in the distribution and abundance of arctic herbivores, a better understanding of the consequences of changes in the diversity of herbivore assemblages is needed. This protocol presents the methodology that will be used in a systematic review on the effects of herbivore diversity on different processes, functions and properties of tundra ecosystems. Methods This systematic review builds on an earlier systematic map on herbivory studies in the Arctic that identified a relatively large number of studies assessing the effects of multiple herbivores. The systematic review will include primary field studies retrieved from databases, search engines and specialist websites, that compare responses of tundra ecosystems to different levels of herbivore diversity, including both vertebrate and invertebrate herbivores. We will use species richness of herbivores or the richness of functional groups of herbivores as a measure of the diversity of the herbivore assemblages. Studies will be screened in three stages: title, abstract and full text, and inclusion will follow clearly identified eligibility criteria, based on their target population, exposure, comparator and study design. The review will cover terrestrial Arctic ecosystems including the forest-tundra ecotone. Potential outcomes will include multiple processes, functions and properties of tundra ecosystems related to primary productivity, nutrient cycling, accumulation and dynamics of nutrient pools, as well as the impacts of herbivores on other organisms. Studies will be critically appraised for validity, and where studies report similar outcomes, meta-analysis will be performed.
Background The Coronavirus Disease-2019 (COVID-19) pandemic has created a spectrum of adversities that have affected older adults disproportionately. This paper examines older adults with multimorbidity using longitudinal data to ascertain why some of these vulnerable individuals coped with pandemic-induced risk and stressors better than others – termed multimorbidity resilience. We investigate pre-pandemic levels of functional, social and psychological forms of resilience among this sub-population of at-risk individuals on two outcomes – self-reported comprehensive pandemic impact and personal worry. Methods This study was conducted using Follow-up 1 data from the Canadian Longitudinal Study on Aging (CLSA), and the Baseline and Exit COVID-19 study, conducted between April and December in 2020. A final sub-group of 9211 older adults with two or more chronic health conditions were selected for analyses. Logistic regression and Generalized Linear Mixed Models were employed to test hypotheses between a multimorbidity resilience index and its three sub-indices measured using pre-pandemic Follow-up 1 data and the outcomes, including covariates. Results The multimorbidity resilience index was inversely associated with pandemic comprehensive impact at both COVID-19 Baseline wave (OR = 0.83, p < 0.001, 95% CI: [0.80,0.86]), and Exit wave (OR = 0.84, p < 0.001, 95% CI: [0.81,0.87]); and for personal worry at Exit (OR = 0.89, p < 0.001, 95% CI: [0.86,0.93]), in the final models with all covariates. The full index was also associated with comprehensive impact between the COVID waves (estimate = − 0.19, p < 0.001, 95% CI: [− 0.22, − 0.16]). Only the psychological resilience sub-index was inversely associated with comprehensive impact at both Baseline (OR = 0.89, p < 0.001, 95% CI: [0.87,0.91]) and Exit waves (OR = 0.89, p < 0.001, 95% CI: [0.87,0.91]), in the final model; and between these COVID waves (estimate = − 0.11, p < 0.001, 95% CI: [− 0.13, − 0.10]). The social resilience sub-index exhibited a weak positive association (OR = 1.04, p < 0.05, 95% CI: [1.01,1.07]) with personal worry, and the functional resilience measure was not associated with either outcome. Conclusions The findings show that psychological resilience is most pronounced in protecting against pandemic comprehensive impact and personal worry. In addition, several covariates were also associated with the outcomes. The findings are discussed in terms of developing or retrofitting innovative approaches to proactive coping among multimorbid older adults during both pre-pandemic and peri-pandemic periods.
Humoral responses to COVID-19 vaccines in people living with HIV (PLWH) remain incompletely characterized. We measured circulating antibodies against the SARS-CoV-2 spike protein receptor-binding domain (RBD), ACE2 displacement and viral neutralization activities one month following the first and second COVID-19 vaccine doses, and again 3 months following the second dose, in 100 adult PLWH and 152 controls. All PLWH were receiving suppressive antiretroviral therapy, with median CD4+ T-cell counts of 710 (IQR 525–935) cells/mm ³ , though nadir CD4+ T-cell counts ranged as low as <10 cells/mm ³ . After adjustment for sociodemographic, health and vaccine-related variables, HIV infection was associated with lower anti-RBD antibody concentrations and ACE2 displacement activity after one vaccine dose. Following two doses however, HIV was not significantly associated with the magnitude of any humoral response after multivariable adjustment. Rather, older age, a higher burden of chronic health conditions, and dual ChAdOx1 vaccination were associated with lower responses after two vaccine doses. No significant correlation was observed between recent or nadir CD4+ T-cell counts and responses to two vaccine doses in PLWH. These results indicate that PLWH with well-controlled viral loads and CD4+ T-cell counts in a healthy range generally mount strong initial humoral responses to dual COVID-19 vaccination. Factors including age, co-morbidities, vaccine brand, response durability and the rise of new SARS-CoV-2 variants will influence when PLWH will benefit from additional doses. Further studies of PLWH who are not receiving antiretroviral treatment or who have low CD4+ T-cell counts are needed, as are longer-term assessments of response durability.
The ATLAS experiment at the Large Hadron Collider has a broad physics programme ranging from precision measurements to direct searches for new particles and new interactions, requiring ever larger and ever more accurate datasets of simulated Monte Carlo events. Detector simulation with Geant4 is accurate but requires significant CPU resources. Over the past decade, ATLAS has developed and utilized tools that replace the most CPU-intensive component of the simulation—the calorimeter shower simulation—with faster simulation methods. Here, AtlFast3, the next generation of high-accuracy fast simulation in ATLAS, is introduced. AtlFast3 combines parameterized approaches with machine-learning techniques and is deployed to meet current and future computing challenges, and simulation needs of the ATLAS experiment. With highly accurate performance and significantly improved modelling of substructure within jets, AtlFast3 can simulate large numbers of events for a wide range of physics processes.
Unintentional overdose deaths, most involving opioids, have eclipsed all other causes of US deaths for individuals less than 50 years of age. An estimated 2.4 to 5 million individuals have opioid use disorder (OUD) yet a minority receive treatment in a given year. Medications for OUD (MOUD) are the gold standard treatment for OUD however early dropout remains a major challenge for improving clinical outcomes. A Cascade of Care (CoC) framework, first popularized as a public health accountability strategy to stem the spread of HIV, has been adapted specifically for OUD. The CoC framework has been promoted by the NIH and several states and jurisdictions for organizing quality improvement efforts through clinical, policy, and administrative levers to improve OUD treatment initiation and retention. This roadmap details CoC design domains based on available data and potential linkages as individual state agencies and health systems typically rely on limited datasets subject to diverse legal and regulatory requirements constraining options for evaluations. Both graphical decision trees and catalogued studies are provided to help guide efforts by state agencies and health systems to improve data collection and monitoring efforts under the OUD CoC framework.
Plain English summary Involving patients and families as partners in planning, conducting, and sharing results of health research, referred to as patient engagement, is becoming more common and recognized as important part of the research process. However, guidelines and examples of how to do this well are limited. In this article, we describe the development and features of the Ottawa Patient Engagement in Research Model at The Ottawa Hospital (TOH) and the Ottawa Hospital Research Institute (OHRI). Key pieces of the model include: a Patient and Family Engagement Program, which recruits, educates, and supports patients and families to engage in clinical care, decision making, and research; the Ottawa Methods Centre, which leads studies to understand the best methods to conduct research, and provides support to researchers for patient engagement; and the Office of Patient Engagement in Research Activities, which connects patients, researchers, clinicians, and other stakeholders. Early success of this model may be a result of shared priorities between TOH, OHRI and patients, the creation of a patient engagement policy, ongoing support provided to patients, family members and researchers, and creative methods for recruitment, tracking and evaluation procedures. Ongoing challenges and next steps include promoting diversity among patient partners, setting up a fair and transparent policy for compensating patient partners, and engaging patients across a variety of roles and research areas. This model represents a unique effort of patients, clinicians, researchers, and policymakers across disciplines and institutions to produce one strategy for meaningful teamwork with patients and families in health research.
In an ideal risk-informed approach to safety analysis, all possible operational states of the system and all sources of uncertainty would be factored. Brute force approaches are cost-prohibitive if high-fidelity multiphysics simulation systems are used. To address this barrier, we present a first attempt to develop emulators for coupled neutronics/thermalhydraulics simulations of large break loss-of-coolant accidents in a generic pressurized heavy water reactor. The emulators are based on a linear mean function coupled with a locally approximate Gaussian process model. The emulators are capable of predicting the power pulse amplitude and the maximum bundle enthalpy within mean absolute relative errors of 0.75 and 0.36%, and mean relative margins of error of 1.9 and 1.0%, respectively. In relation to the simulator, the evaluation time is reduced by a factor of nearly 1800. The paper covers the simulation system, training data generation framework, statistical models and uncertainties, and results.
Academic dishonesty (AD) continues to threaten the integrity of post-secondary institutions around the world with new scandals publicized every year. While AD has received considerable research attention, most of these studies have focused on quantifying the characteristics of cheaters and cheating behaviour, primarily at the undergraduate level. In the present study, we used a mix-methods approach to explore student attitudes towards AD among business students at both graduate and undergraduate levels at a North American university. We found that the perceived prevalence of AD was higher among undergraduates, who regarded cheating scenarios to be less wrong when compared to graduates. When asked how AD impacted other students, the undergraduate respondents highlighted the consequences of artificially inflating the normalized grading distribution, while the graduate respondents focused on the erosion of cohort dynamics and professional networks. Both groups of students shared that they faced increasing competition and other pressures that motivated them to engage in AD. These factors propagated cheating behaviour through complex positive feedback loop mechanisms, which we termed the Vicious Cycles of Cheating. Based on these factors, we proposed recommendations that are directly informed by students and designed to break these cycles.
Brand love is an often ignored, yet important dimension in consumer-brand relationships. Especially consumer-brand relationships with masstige brands that are hedonic and symbolic in nature. Using an experimental design (n = 465), this study investigated the interplay between brand love and brand loyalty, and its impact on brand equity. Contrary to current literature, the findings indicate that consumers can develop brand love without being loyal to a brand and can exhibit high brand love without purchasing from the brand. Brand love had a greater impact on brand equity than brand loyalty, and both brand love and brand equity diminished when consumers experienced brand betrayal. The brand love-loyalty matrix shows the interplay between these constructs for masstige brand relationships and can be used to increase market share. Finally, a decision tree is provided to guide the growth decisions of luxury brands who want to embark on a masstige strategy.
Oceans are increasingly looked toward for their contribution to addressing climate change. These so-called ocean-based climate “solutions” often fall under the umbrella of the “blue economy,” a term used to refer to new ways of organizing ocean economies to provide equitable economic and environmental benefits. Yet, thus far the literature exploring blue economies and blue economy governance has largely overlooked or downplayed its equity and justice roots and implications, including how blue economies are embedded in multiple scales of environmental injustices. This is particularly important when blue economies include offshore oil production. The purpose of this paper is to both emphasize the need and provide an approach to incorporate justice and equity—specifically climate justice—into blue economy planning and scholarship. We build on conceptualizations of blue economies as assemblages to draw attention to the global reach of climate impacts associated with oil that are often overlooked or ignored at sites of production and through regional governance. We argue that greenhouse gas emissions from the life cycle of oil should be included in policies and planning (including blue economy planning) at sites of production, but that this must also incorporate underlying power structures that lead to uneven impacts and climate injustice. We look at environmental assessments as a regional governance tool that could be used to shape opportunities and openings to organize blue economies differently. To illustrate these points, we look at how environmental assessments are playing (and could play) a role in enacting and shaping Newfoundland and Labrador's blue economy.
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13,190 members
Ralph A Pantophlet
  • Faculty of Health Sciences
Nicole Pernat
  • Department of Philosophy
Ray Jennings
  • Laboratory for Logic and Experimental Philosophy
Alireza Saffarzadeh
  • Department of Physics
Mark R Blair
  • Department of Psychology
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