Showing papers by "Memorial University of Newfoundland published in 2022"
TL;DR: A detailed report on the impact analysis of EV integration on the component and system levels is presented and techniques employed to effectively model the mobile nature of EV load and distributed EVs potential to provide ancillary solutions are explained.
Abstract: Electric vehicles (EVs) have remarkably emerged as an alternative for internal combustion engines. With high penetration levels of the EVs, its addition to the existing distribution line infrastructure affects the power quality and grid stability. Additionally, EV charging loads are characteristically different as they are mobile compared to other fixed node-connected loads. Proposing solutions without considering these factors may result in grid congestion and subsequent over/under compensations. Another emerging dynamics co-occurring in the distribution system is high penetration levels of renewable energy in the utility grid. Although these dynamics pose challenges in stable grid operation, it also gives opportunities for solving some of the grid integration issues of EV loads. Thus, the effect of adding EV charging load to the existing low voltage distribution system must be analyzed by considering different criteria such as grid impact with different EV chargers, mobile nature of EV load, power quality, voltage profile, and spread/peak demand of load curve. This paper presents a detailed report on the impact analysis of EV integration on the component and system levels. For analyzing the effect on power quality (component level), grid pollution contributed by EV chargers along with possible solutions is elucidated. Detailed discussion on the significance of EV load location, existing load distribution, and nature of EV charging load distribution is presented by considering different feeders and different load curves. These discussions are supported with simulated case studies followed by a review of existing literature for enhanced understanding. Finally, techniques employed to effectively model the mobile nature of EV load and distributed EVs potential to provide ancillary solutions are also explained.
51 citations
TL;DR: In this paper, the effects of roasting temperature and time on aldehyde formation derived from lipid oxidation in scallop, and the deterrent effect of natural antioxidants extracted from bamboo leaves (AOB) were investigated.
25 citations
TL;DR: In this paper, the authors tried to establish a new theoretical circumvention strategy to reduce the abortion risk of synthetic musks to pregnant women by designing the supplementary diet plan and environmentally friendly SMs derivatives using molecular docking and three-dimensional quantitative structure-activity relationship (3D-QSAR) models.
24 citations
TL;DR: In this paper , the authors tried to establish a new theoretical circumvention strategy to reduce the abortion risk of synthetic musks to pregnant women by designing the supplementary diet plan and environmentally friendly SMs derivatives using molecular docking and three-dimensional quantitative structure-activity relationship (3D-QSAR) models.
24 citations
TL;DR: Wang et al. as discussed by the authors analyzed the current status and challenges of university laboratory safety in China and presented future directions to reduce accidents using engineering and administrative controls, and performed a descriptive statistical analysis of 110 publicly reported university laboratory accidents in mainland China since 2000.
Abstract: The past two decades have seen a rise in university laboratory accidents in China. Although there is a growing awareness due to higher reporting and media coverage, the evaluation and understanding of common hazards and deficiencies in university laboratories remains to be addressed. Aiming to enhance safety in laboratory-related activities, this study analyzed the current status and challenges of university laboratory safety in China and presented future directions to reduce accidents using engineering and administrative controls. A descriptive statistical analysis of 110 publicly reported university laboratory accidents in mainland China since 2000 was performed to investigate the proximate causes of the accidents, and further, to identify potential deficiencies existing in the current safety management of laboratories. It was found that human factors were the most contributing cause and the training element was a vulnerable competency in laboratory safety management. Based on the results, a comparative analysis between the underlying reasons for the poor safety situation and the efforts that have been made has brought the challenges and possible solutions for safety improvements in university laboratories. By suggesting top-down and bottom-up approaches, the present study provides valuable insights and serves as a reference for universities and relevant authorities to enhance safety in university laboratories.
21 citations
TL;DR: In this article , a dominant supplier manufacturing differentiated products in determining the best online mode under different distribution strategies was investigated, and the optimal commission rate to maximize the win-win region was shown to be highly dependent upon the substitution intensity across the differentiated products.
19 citations
TL;DR: In this article, a novel vulnerability model called the "fire and explosion synergistic effect model" (FESEM) is proposed to model equipment vulnerability under the spatial-temporal synergistic of heat radiation and overpressure.
19 citations
TL;DR: In this paper , a crystal plasticity-based constitutive model is developed to describe the thermomechanical behavior of pseudoelastic NiTi single crystal, which includes all inelastic mechanisms influencing the fatigue behavior of NiTi SMAs in a finite strain framework.
16 citations
TL;DR: In this article, a crystal plasticity-based constitutive model is developed to describe the thermomechanical behavior of pseudoelastic NiTi single crystal, which includes all inelastic mechanisms influencing the fatigue behavior of NiTi SMAs in a finite strain framework.
16 citations
TL;DR: In this paper , a structural causal model was built to estimate the strength of causal links among salinity, dispersant addition, cell abundance, biosurfactant productivity and oil biodegradation.
16 citations
TL;DR: In this article, a dynamic risk analysis model for analyzing domino effects in RTHM based on Dynamic Bayesian Network is proposed, which can simulate the domino-driven effects in terms of both consequences and probability escalation and dealing with the parameter and model uncertainties.
Abstract: Rail transport of hazardous material (RTHM) plays a vital role in the supply chain of raw materials and products. However, RTHM can pose severe risks due to the large quantities of flammable and explosive chemicals transported over rail tracks crossing residential and industrial areas and possible human and technical failures. Among the potential safety issues, the domino effect is one of the most feared events, which can have devastating consequences despite its relatively low probability. As the first study, the present investigation develops a dynamic risk analysis model for analyzing domino effects in RTHM based on Dynamic Bayesian Network. Accident scenarios such as pool fire, flash fire, fire ball, vapor cloud explosion, and BLEVE are considered to analyze domino effects. The model performance is tested on a real RTHM (i.e., gasoline transportation), demonstrating the effectiveness of the proposed model in simulating the domino-driven effects in terms of both consequences and probability escalation and in dealing with the parameter and model uncertainties.
TL;DR: In this paper , the authors investigated the MODA formation mechanism and its impact on oil dispersion during marine oil spill response, and they found that MODA reduced oil dispersal effectiveness under different mixing energy levels.
TL;DR: The Future of Walkability Measures Workshop as discussed by the authors discussed and proposed a conceptual definition of walkability and related concepts, and suggested that the term Active Living Environments (ALEs) is more appropriate.
Abstract: Walkability is a popular term used to describe aspects of the built and social environment that have important population-level impacts on physical activity, energy balance, and health. Although the term is widely used by researchers, practitioners, and the general public, and multiple operational definitions and walkability measurement tools exist, there are is no agreed-upon conceptual definition of walkability.To address this gap, researchers from Memorial University of Newfoundland hosted "The Future of Walkability Measures Workshop" in association with researchers from the Canadian Urban Environmental Health Research Consortium (CANUE) in November 2017. During the workshop, trainees, researchers, and practitioners worked together in small groups to iteratively develop and reach consensus about a conceptual definition and name for walkability. The objective of this paper was to discuss and propose a conceptual definition of walkability and related concepts.In discussions during the workshop, it became clear that the term walkability leads to a narrow conception of the environmental features associated with health as it inherently focuses on walking. As a result, we suggest that the term Active Living Environments, as has been previously proposed in the literature, are more appropriate. We define Active Living Environments (ALEs) as the emergent natural, built, and social properties of neighbourhoods that promote physical activity and health and allow for equitable access to health-enhancing resources.We believe that this broader conceptualization allows for a more comprehensive understanding of how built, natural, and social environments can contribute to improved health for all members of the population.
TL;DR: In this paper , the effects of changing fire regimes on some important recovery processes have been considered, the consequences for the dispersal of propagules (plant seeds and fungal spores) in forest communities have not.
Abstract: Abstract Many forest species are adapted to long-interval, high-severity fires, but the intervals between severe fires are decreasing with changes in climate, land use, and biological invasions. Although the effects of changing fire regimes on some important recovery processes have previously been considered, the consequences for the dispersal of propagules (plant seeds and fungal spores) in forest communities have not. We characterize three mechanisms by which changing fire regimes disrupt propagule dispersal in mesic temperate, boreal, and high-elevation forests: reduced abundance and altered spatial distributions of propagule source populations, less effective dispersal of propagules by wind, and altered behavior of animal dispersers and propagule predators. We consider how disruptions to propagule dispersal may interact with other factors that are also influenced by fire regime change, potentially increasing risk of forest conversion. Finally, we highlight urgent research topics regarding how dispersal limitation may shape twenty-first century forest recovery after stand-replacing fire.
TL;DR: In this article , the authors investigated the relationship between pressure change, velocity change, and temperature of crude oil through a pipeline and presented a method of using a regression supervised machine learning (ML) algorithm to detect faults.
Abstract: This study investigates the relationship between pressure change, velocity change, and temperature of crude oil through a pipeline and presents a method of using a regression supervised machine learning (ML) algorithm to detect faults. A representative dataset of crude oil flow is generated by computational fluid dynamics (CFD) and used to train the algorithm to develop a model of fluid behavior under normal pipeline operations over a range of typical flow rates and temperatures. CFD data are then collected under several simulated fault conditions: leaks of 10% and 20%, and a 50% restriction to flow, by nominal pipe cross-sectional area. This study demonstrates that the ML algorithm can be trained to model the system under normal conditions, thereby successfully recognizing a fault condition as non-conforming and indicative of a statistically significant change in pipeline operation. It is further able to identify the fault type based on the pattern observed in the new data. It is shown that ML may be a safe, low-cost, and accurate method of monitoring a subsea pipeline for optimal performance and fault detection without the need to introduce special equipment to a subsea pipeline network, providing an avenue for enhanced process safety and protection of ocean environments. This paper demonstrates that the application of ML to the monitoring of pipeline networks could provide valuable contributions to the industry in terms of safety, cost, and environmental protection.
TL;DR: In this paper, the authors summarized recent research progress in developing effective and environmentally friendly dispersants by using green, food grade, and biological surfactants and additives and highlighted the future research needs to promote the application of these new formulas in marine oil spill incidents.
Abstract: The dispersant application has been recognized as an effective marine oil spill response option. Sustainable dispersants are continuously formulated to minimize potential ecological concerns. This review summarized recent research progress in developing effective and environmentally friendly dispersants by using green, food grade, and biological surfactants and additives. The oil dispersion efficiency and toxicity of these newly generated dispersants have also been discussed. We ended this review by highlighting the future research needs to promote the application of these new formulas in marine oil spill incidents.
TL;DR: In this paper, the authors proposed applying the Object-Oriented Bayesian Network (OOBN) to capture the risk influencing factors of the capsizing accident scenario under different operating conditions for a small fishing trawler, a sub-class of fishing vessels.
TL;DR: In this article , the authors summarized recent research progress in developing effective and environmentally friendly dispersants by using green, food grade, and biological surfactants and additives and highlighted the future research needs to promote the application of these new formulas in marine oil spill incidents.
Abstract: The dispersant application has been recognized as an effective marine oil spill response option. Sustainable dispersants are continuously formulated to minimize potential ecological concerns. This review summarized recent research progress in developing effective and environmentally friendly dispersants by using green, food grade, and biological surfactants and additives. The oil dispersion efficiency and toxicity of these newly generated dispersants have also been discussed. We ended this review by highlighting the future research needs to promote the application of these new formulas in marine oil spill incidents.
TL;DR: In this article, the authors developed a statistical approach to index starvation-induced mortality by estimating the proportion of individuals experiencing severe emaciation in a fish population, and found a positive association between rates of natural mortality estimated by an integrated population model and the index of mortality derived from proportions of cod in poor condition.
TL;DR: A time-varying risk assessment method that takes into consideration the population dynamism and the two-stage robust optimization approach is employed to formulate two mixed-integer programming models, namely the basic and expanded unit commitment models, for managing a reliable emergency response system.
TL;DR: In this paper, a Computational Fluid Dynamics (CFD) model for the inclined well section is used to investigate the cuttings transport efficiency (CTE), and an Eulerian-Eulerian multiphase flow model is proposed and validated with lab scale experimental data.
TL;DR: In this article, a robust neural network-based method called generalized structure of group method of data handling (GS-GMDH) was proposed to simulate the horizontal and vertical subgouge soil deformation profiles in clay.
TL;DR: In this paper, the status of air quality during the 8th phase of unlocking of COVID-19 lockdown (January 2021) at three locations of North India was evaluated, and the results showed that the levels of PM2.5 showed a significant increase of 525.2%, 281.2, and 185.0% at sites S1, S2 and S3, respectively in the unlock 8, in comparison to its concentration in the lockdown phase.
TL;DR: In this paper , a robust neural network-based method called generalized structure of group method of data handling (GS-GMDH) was proposed to simulate the horizontal and vertical subgouge soil deformation profiles in clay.
TL;DR: In this paper , the authors describe patterns in monthly migraine days (MMD) and tablet utilization, and estimate health-related quality of life (HRQoL) measures in patients treated as needed (PRN) with rimegepant 75 mg over 52-weeks.
Abstract: The objective of this study was to describe patterns in monthly migraine days (MMD) and tablet utilization, and to estimate health-related quality of life (HRQoL) measures in patients treated as needed (PRN) with rimegepant 75 mg over 52-weeks.Eligible subjects were adults with ≥1 year history of migraine and ≥ 6 MMD at baseline, who used rimegepant 75 mg up to once daily PRN (at their discretion) for up to 52-weeks in an open-label safety study (BHV3000-201; NCT03266588). Mean MMD were calculated at each 4-week period, along with mean monthly tablets taken. Migraine-specific quality of life (MSQv2) data were mapped to EQ-5D utilities and used to characterize HRQoL over time. A published network meta-analysis was used to characterize pain hours as well as time periods spent migraine free.One thousand forty four subjects were included in this post-hoc analysis. Overall mean MMD were 10.9 at baseline and decreased to 8.9 by week 52. Tablet use remained stable over the follow-up period. A total of 0.08 incremental QALYs were associated with rimegepant use.For subjects with 6 or more MMD, acute treatment of migraine attacks with rimegepant 75 mg on a PRN basis over one-year of follow-up was found to be associated with reduced MMD frequency without an increase in monthly tablet utilization, and improved HRQoL. There was no evidence of medication-related increases in MMDs when rimegepant 75 mg was used as needed for the acute treatment of migraine over 52-weeks.ClinicalTrials.gov identifier NCT03266588 .
TL;DR: In this article , a thermal non-uniformity factor was used to quantitatively characterize the nonuniform distribution of thermal resistance and capacitance in an exterior wall built with superthermal aerogel insulating panels.
TL;DR: In this paper , support vector regression (SVR) was proposed as an improved approach for generating smooth continuous estimates of discharge rate and compared the fit characteristics of SVR to traditionally used methods, including Hanning window filtering and polynomial regression.
Abstract: Objective. Successive improvements in high density surface electromyography and decomposition techniques have facilitated an increasing yield in decomposed motor unit (MU) spike times. Though these advancements enhance the generalizability of findings and promote the application of MU discharge characteristics to inform the neural control of motor output, limitations remain. Specifically, (1) common approaches for generating smooth estimates of MU discharge rates introduce artifacts in quantification, which may bias findings, and (2) discharge characteristics of large MU populations are often difficult to visualize.Approach. In the present study, we propose support vector regression (SVR) as an improved approach for generating smooth continuous estimates of discharge rate and compare the fit characteristics of SVR to traditionally used methods, including Hanning window filtering and polynomial regression. Furthermore, we introduce ensembles as a method to visualize the discharge characteristics of large MU populations. We define ensembles as the average discharge profile of a subpopulation of MUs, composed of a time normalized ensemble average of all units within this subpopulation. Analysis was conducted with MUs decomposed from the tibialis anterior (N= 2128), medial gastrocnemius (N= 2673), and soleus (N= 1190) during isometric plantarflexion and dorsiflexion contractions.Main result. Compared to traditional approaches, we found SVR to alleviate commonly observed inaccuracies and produce significantly less absolute fit error in the initial phase of MU discharge and throughout the entire duration of discharge. Additionally, we found the visualization of MU populations as ensembles to intuitively represent population discharge characteristics with appropriate accuracy for visualization.Significance. The results and methods outlined here provide an improved method for generating estimates of MU discharge rate with SVR and present a unique approach to visualizing MU populations with ensembles. In combination, the use of SVR and generation of ensembles represent an efficient method for rendering population discharge characteristics.
TL;DR: In this paper , the authors apply Faure & Fang's (2008) framework to unravel the paradox inherent and changes to Russian cultural values over time, and find that underlying paradoxical values that traditionally coexisted in Russian culture during the Communist regime have been further reinforced as a consequence of Russia's interactions with the rest of the world.
TL;DR: In this paper , the authors developed a framework to analyze the dynamics of a finite-dimensional quantum system and showed that the reduced system evolution is Markovian for all times, and that the decay of the reservoir correlation function only needs to be polynomial in time, improving on the previously required exponential decay.
Abstract: We develop a framework to analyze the dynamics of a finite-dimensional quantum systemS R S R S R t ≥ 0 S R S R S R N
TL;DR: In this paper , the authors explored the many attributes that influence purchase decisions for dried leaf cannabis, including price, quality, packaging and warnings, source of the cannabis, and social influences.
Abstract: Cannabis was legalized in Canada for non-medical use in 2018. The goal of legalization was to improve health and safety by creating access to regulated products, with accurate product labels and warnings and no risk of contamination. However, more than 2 years post-legalization, a large proportion of purchases are still suspected to be through unlicensed retailers. This study sought to identify the factors that influenced the purchase decisions of cannabis consumers in Newfoundland and Labrador (NL).Semi-structured focus groups and interviews were conducted in NL with individuals who were > 19 and had purchased cannabis within the last 12 months. All sessions were conducted virtually, audio-recorded, and transcribed. A thematic analysis was conducted, and two members of the research team coded the data using NVivo. A combination of deductive and inductive coding was carried out, themes from the literature were identified, and new themes from the transcripts were discovered. A final coding template of the data was agreed upon by the team through discussion and consensus.A total of 23 individuals (30% women) participated, with 83% coming from urban areas. While all cannabis product types were discussed, the conversation naturally focused on dried flower products. Participants discussed a variety of considerations when making purchase decisions categorized around five broad themes: 1) price, 2) quality, 3) packaging and warnings, 4) the source of the cannabis, and 5) social influences. The price difference between licensed and un-licensed sources was commonly discussed as a factor that influenced purchase decisions. Product quality characteristics (e.g. size, color, moisture content) and social influences were also considered in purchase decisions. Participants were generally indifferent to packaging and warning labels but expressed concern about the excessive packaging required for regulated products.This study explores the many attributes that influence purchase decisions for dried leaf cannabis. Understanding the drivers of purchase decisions can help inform policy reforms to make regulated cannabis products more appealing to consumers. Further research is needed to measure the effect of each attribute on cannabis purchase decisions.