Université du Québec à Chicoutimi

Aluminium alloys suffer from a serious backlash of low formability, hindering their implementation in the automobile sector, where demand has been skyrocketing for decades. However, warm forming techniques have been reported to bear the ability to curb this problem using a forming temperature below the recrystallization point, owing to the direct contribution of the activated non-octahedral slip systems. This calls for an investigation on the onset of secondary slip systems along with an estimation of microstructural characterization and analysis of crystallographic texture since both are expected to have a staggering influence on the mechanical properties at elevated temperatures. Hence, the present investigation deals with thorough microstructural analysis derived from the Electron Back Scattered Diffraction (EBSD) maps and analysis of crystallographic texture through Orientation Distribution Function maps of EN AW 6061 samples deformed through tension both at room and elevated temperature (250 °C). Furthermore, Visco Plastic Self Consistent (VPSC) modelling along with the Finite element (FE) method has also been incorporated with an aim to verify the crystallographic texture and deformation behaviour, respectively. These extensive characterization methodologies provided compelling evidences of the formation of deformation substructures at elevated tempaerature along with distinct represtation of work hardening behaviour of the material. The texture analysis further elaborated on the influence of high temperature on the reduction of unidirectional defects at high temperature, allowing it to regain its symmetry.

This study investigated the effect of pre-friction surfacing heat treatment of consumable rods and heat input during friction surfacing on the microstructure, mechanical properties, and wear resistance of hypereutectic Al-Si alloy deposited on a commercially pure aluminum substrate. The results show that regardless of the consumable rod’s heat treatment conditions, the coating’s efficiency has increased with the increase in heat input, so the coating efficiency increases by 20% and 30% in the solid solution-treated rod and the artificially aged rod, respectively. By increasing the heat input, the average grain size in the coating fabricated by solid solution-treated rod and artificially aged rod increased from 0.1 to 0.9 µm and from 0.2 to 1.3 µm, respectively. At constant heat input, the average hardness and wear resistance of the coating created in the solid solution-treated rod are lower than those of the artificially aged rod. By decreasing heat input, the wear loss in the coating fabricated by solid solution-treated rod and artificially aged rod decreased by 10% and 20%, respectively, reaching 0.1 and 0.03 µg/m.

Physics-informed machine learning (PIML) seeks to integrate scientific knowledge into conventional machine learning models to mitigate the black-box nature of the latter and prevent them from producing physically inconsistent results. Recently, Adombi et al. (2024) [a causal physics-informed deep learning formulation for groundwater flow modeling and climate change effect analysis] have shown that incorporating scientific knowledge into machine learning models is not enough to make them obey certain fundamental principles of physics, such as causality. They then derived certain constraints, called causal relationship constraints (CRC), to force PIML to obey the principle of causality. However, in some situations, CRC constraints in PIML prioritize the satisfaction of the principle of causality to the detriment of performance. In this study, we propose new CRC conditions and a new architecture for PIML, with the aim of testing the hypothesis that these conditions improve the performance of PIML models without transgressing the principle of causality. The models were tasked with simulating groundwater levels in six piezometers located in Quebec, Canada. A conventional machine learning model (convolutional neural network, 1D-CNN), a PIML model based on Adombi et al. (2024) (H-Lin) and a PIML model based on the architecture proposed in this work (H-LinC) were trained and subsequently compared. The results show that 1D-CNN outperforms H-LinC, which in turn outperforms H-Lin in terms of accuracy, with median NSE and KGE of 0.76 and 0.87 for 1D-CNN, 0.68 and 0.76 fir H-LinC, and 0.53 and 0.59 fir H-Lin. However, only H-LinC and H-Lin satisfy the principle of causality.

We introduce families of quasi-rectifiable vector fields and study their geometric and algebraic aspects. Then, we analyse their applications to systems of partial differential equations. Our results explain, in a simple manner, the properties of families of vector fields describing hydrodynamic-type equations by means of k-waves. Facts concerning families of quasi-rectifiable vector fields, their relation to Hamiltonian systems, and practical procedures for studying such families are developed. We introduce and analyse quasi-rectifiable Lie algebras, which are motivated by geometric and practical reasons. We classify different types of quasi-rectifiable Lie algebras, e.g. indecomposable ones up to dimension five. New methods for solving systems of hydrodynamic-type equations are established to illustrate our results. In particular, we study hydrodynamic-type systems admitting Riemann k-wave solutions through quasi-rectifiable Lie algebras of vector fields. We develop techniques for obtaining the submanifolds related to quasi-rectifiable Lie algebras of vector fields and systems of partial differential equations admitting a nonlinear superposition rule: the PDE Lie systems.

In this work, a long surface wave plasma column is generated using high power pulse-modulated microwave power in argon at atmospheric pressure. The temporal evolutions of the electron density and temperature are diagnosed by optical emission spectroscopy. It is found that the emission intensity peaks correspond to the nodes of standing surface waves where the local electric field is reduced, rather than the antinodes, which is in contrast with that in low pressure discharges. The reasons for this behavior are discussed by considering the excitation balance of the excited levels of Ar I in the plasma. A standing surface wave pattern propagating with the movement of the ionization front in the plasma column, which plays the role of a discontinuity, is observed by means of microsecond time-resolved imaging. Another standing wave at the location of the launcher is also described which indicates that the region below the gap also acts as a discontinuity for the wave propagation. The formation of the propagating standing wave is discussed with respect to the wave propagation characteristics by using an electromagnetic (EM) model based on the propagation of the surface wave. This study underlines the fundamental differences in the EM wave/plasma interactions between continuous and pulsed surface wave discharges and provides new insights into the importance of the microwave applicator segment for a complete description of the plasma column formation.

This study evaluates the impact of Big Data Analytics (BDA) on firm sustainable performance (FSP). BDA is conceptualized as a dual construct comprising predictive and prescriptive analytics, while FSP is considered from a triple bottom line (TBL) perspective comprising the economic, social, and environmental lines of firm performance. The study relies exclusively on independent third-party BDA and FSP data pertaining to 522 firms from the US S&P500 Index and the Canadian S&P500/TSX60 Index. The data is analyzed with ordinary least squares (OLS) regression, and the findings reveal, on aggregate, that BDA has a direct, positive, and significant effect on overall FSP. The results of the piecemeal analysis show that BDA is positively related to the economic, social, and environmental dimensions. Furthermore, our distinction between predictive and prescriptive analytics suggests that prescriptive analytics outperforms the FSP results obtained with predictive analytics moderately. The study insights provide strategic knowledge for firms seeking to leverage digitalization for enhanced corporate citizenship while boosting their digital capabilities. The impact of technology, especially Big Data, on sustainability, has gained traction in the literature, yet this is the first study to delve deeper into the detailed relationships between both constructs by deciphering and quantifying the impact of BDA components on the TBL.

Mitochondria are crucial for cellular metabolism and signalling. Mitochondrial activity is modulated by mitochondrial fission and fusion, which are required to properly balance metabolic functions, transfer material between mitochondria, and remove defective mitochondria. Mitochondrial fission occurs at mitochondria-endoplasmic reticulum (ER) contact sites, and requires the formation of actin filaments that drive mitochondrial constriction and the recruitment of the fission protein DRP1. The role of actin in mitochondrial fusion remains entirely unexplored. Here we show that preventing actin polymerisation on either mitochondria or the ER disrupts both fission and fusion. We show that fusion but not fission is dependent on Arp2/3, whereas both fission and fusion require INF2 formin-dependent actin polymerization. We also show that mitochondria-associated actin marks fusion sites prior to the fusion protein MFN2. Together, our work introduces a method for perturbing organelle-associated actin and demonstrates a previously unknown role for actin in mitochondrial fusion.

Under climate warming, earlier spring phenology has heightened the risk of late spring frost (LSF) damage. However, the intricate interplay among LSF, spring phenology and photosynthetic carbon uptake remains poorly understood. Using 286,000 ground phenological records involving 870 tree species and remote-sensing data across the Northern Hemisphere, we show that LSF occurrence in a given year reduces photosynthetic productivity by 13.6%, resulting in a delay in spring phenology by ~7.0 days in the subsequent year. Our experimental evidence, along with simulations using modified process-based phenology models, further supports this finding. This frost-induced delay in spring phenology subsequently leads to a decrease in photosynthetic productivity during the next year following an LSF event. Therefore, it is essential to integrate this frost-induced delay in spring phenology into current Earth system models to ensure accurate predictions of the impacts of climate extremes on terrestrial carbon cycling under future climate change.

Several groundwater quality investigations have been conducted in coastal regions that are commonly exposed to multiple anthropogenic stressors. Nonetheless, such studies remain challenging because they require focused-diagnostic approaches for a comprehensive understanding of groundwater contamination. Therefore, this study integrates a multi-tracer approach to acquire comprehensive information allowing for an improved under standing of the origins of groundwater contamination, the relative contribution of contaminants, and their biogeochemical cycling within a coastal groundwater system. This multi-tracer approach, focusing on nitrate (NO3) and sulfate (SO4) groundwater contamination, is applied to a Mediterranean coastal aquifer underlying an important economically strategic agricultural area. Dissolved NO3 in groundwater has concentrations up to 89 mg/L, whereas SO4 concentrations in groundwater are up to 458 mg/L. By integrating isotope tracers (i.e., δ15NNO3, δ18ONO3, δ11B, δ34SSO4, and δ18OSO4), NO3 and SO4 in the groundwater are found to have originated from multiple anthropogenic and natural sources including synthetic fertilizers, manure, sewage, atmospheric deposition, and marine evaporites. Chemical and isotopic data are coupled to identify the dominant hydro(geo) logic processes and the major subsurface biogeochemical reactions that govern the NO3 and SO4 occurrences. Nitrate and SO4 concentrations are identified to be respectively controlled by nitrification/denitrification and by bacterial dissimilatory SO4 reduction. Identifying these subsurface biogeochemical processes constrained the Bayesian isotope MixSIAR model, that is used for apportioning the relative contributions of the identified groundwater contamination sources, by informed site-specific isotopic fractionation effects. Results from SIAR indicate that manure is distinguished as the predominant source for NO3 (61 %), whereas SO4 in groundwater is mostly supplied from two sources (i.e., synthetic fertilizers and soil-derived sulfate) identified with similar contributions (30 %). This study particularly demonstrates the utility of initially describing the subsurface processes, not only to predict the fate of NO3 and SO4 concentrations within the groundwater system, but also to constrain the MixSIAR model with justified site-specific isotopic fractionation effects for subsurface transformation processes affecting NO3 and SO4.

This study introduces a highly sensitive one-dimensional (1D) photonic crystal (PC)-based biosensor for detecting urea concentrations using a defect layer approach. The sensor is designed with alternating layers of BaF₂ and TiO₂, featuring a central defect layer filled with urea samples. Using the transfer matrix method (TMM), the transmission spectra were analyzed to detect urea concentrations ranging from 50 to 800 mM. This study examines the effects of varying layer thicknesses on key performance parameters, including sensitivity, Q-factor, FWHM, FoM, and LoD, successfully optimizing the sensor design. The results demonstrate a redshift in the defect mode wavelength with increasing urea concentrations, achieving sensitivities as high as 212.75 nm/RIU. Unlike conventional methods that require extensive sample preparation and lengthy analysis times, this sensor provides a rapid, cost-effective, and scalable solution. Its capability to operate near the pathophysiological range of urea in human blood makes it particularly suitable for medical diagnostics.

Voluntary counseling and testing (VCT) services have been set up in most Districts in Kenya due to the rising surge of HIV/AIDS. However, the use of these services among married persons has not been fully explored. In Kissi, the issue of VCT is pressing as the rate of HIV prevalence is close to 3%. In 2006, about 20 000 clients came for VCT services in Kenya yet only 165 of these were married persons. In the Keumbu sub-district hospital, of the more than 1000 clients that came for VCT services, approximately 29% were married persons. This paper therefore aims at determining the utilization of VCT services by married persons in the study area. The qualitative data was obtained principally through two focus group discussions (FGDs) in which the respondents were asked to comment on their use of VCT services while the quantitative data was obtained from interviews with 245 respondents. The qualitative data was analyzed through verbatim transcription while for the quantitative data; the responses were coded and populated into SPSS from which the frequencies and percentages were calculated. The results show that actual use of the VCT services is low (28.1%) but slightly higher among female respondents than males. The low usage may be attributed to (a) fear of results, (b) death anxiety, (c) lack of confidentiality and lastly, (d) fear of stigmatization. Female respondents were found to have a greater awareness of VCT and thus its potential use.

Dating violence victimization (DVV) is a prevalent public health problem with harmful consequences among adolescents. Pornography use has been identified among the factors associated with DVV. However, most studies have relied on cross-sectional designs, limiting the ability to determine temporal relationships between these variables. The present study assessed bidirectional longitudinal associations between pornography use and DVV (psychological, physical, and sexual), also examining cross-sectional associations and gender differences. Participants’ self-report data from two assessments of a longitudinal study were used. The sample consisted of 1,556 teenagers ( M age = 14.55 years, SD age = .630; 51.5% were girls) having reported an intimate relationship in the past year at the first and/or second time point (T1/T2). Whereas some cross-sectional associations between pornography use and DVV were observed at T1, results from the autoregressive cross-lagged model revealed no significant longitudinal association between pornography use and the three forms of DVV, regardless of gender. Thus, pornography use may not represent a significant risk factor over time for DVV in adolescents. These findings provide additional insights concerning the associations between pornography use and DVV and suggest that emphasis should perhaps be placed on other variables in the study of risk factors for DVV. Still, although modest, transversal links support the importance of interventions that promote healthy intimate relationships in adolescence and education about pornography use.

In temperate and boreal ecosystems, trees undergo dormancy to avoid cold temperatures during the unfavorable season. This phase includes changes in frost hardiness, which is minimal during the growing season and reaches its maximum in winter. Quantifying frost hardiness is important to assess the frost risk and shifts of species distribution under a changing climate. We investigate the effect of local conditions and intra-specific variation on frost hardiness in sugar maple (Acer saccharum Marsh.). Seedlings belonging to seven provenances from the northern area of the species’ range were planted at two sites in Quebec, Canada. LT50, i.e., the lethal temperature for 50% of the cells, was measured monthly with the Relative Electrolyte Leakage (REL) method on branches and buds from September 2021 to July 2022. LT50 varied between −4 °C in summer (July) and − 68 °C in winter (February). Autumnal acclimation rates (September to early December) and mid-winter frost hardiness (December to early March) were similar in both sites. Samples in the southern site deacclimated faster than in the northern site between March and July, because of a warmer and earlier spring. No difference in frost hardiness was detected between provenances. Our results suggest that the frost hardiness trait is similar within the northern part of the sugar maple distribution, with local weather conditions having a greater influence than provenance. We demonstrate that LT50 in sugar maple can exceed −55 °C, far below the minimum temperatures occurring in winter at the northern limit of the species. In order to minimize the risk of damage from extreme frost events exceeding tree frost hardiness, a careful evaluation of site characteristics is more important than provenance selection. Other factors should also be considered within the context of changing climate, in particular the phenology of maple and avoidance of late frost in spring.

This paper analyzes the dimensions underlying the management practices of public managers when they areimplementing their organizational objectives. This study also shows, in relation to our conceptual framework ofthe five dimensions of strategy execution, the necessary behaviours and attitudes that public managers ought todeploy in performing their missions of public benefit. To that end we conducted a factor analysis, subsequent toa survey of service managers in public administration, which allowed to assess and to emphasize thesignificance of each of the five dimensions of strategy execution.

Detecting falls presents a significant challenge for researchers, given the risk of serious injuries like femoral neck fractures, brain hemorrhages, or burns, which result in significant pain and, in some cases, worsen over time, leading to end-of-life complications or even fatalities. One approach to addressing this challenge involves promptly alerting caregivers, such as nurses, upon detecting a fall. In our work, we present a technique to detect falls within a 40-square-meter apartment by collecting data from three ultra-wideband radars. The presented technique combines a vision transformer and a residual neural network for fall identification, a binary classification task distinguishing between fall and non-fall events. To train and test the presented technique, we use data reflecting various fall types simulated by 10 participants across three locations in the apartment. We evaluated the performance of the presented technique in comparison with some base models by using the leave-one-subject-out strategy to demonstrate the generalization of experiment results in practical scenarios with new subjects. We also report our results by applying cross-validation to select a validation set, which highlights the effectiveness of the presented technique during the training phase and demonstrates the confidence of the obtained results in the testing phase. Consistently, the results illustrate the superior performance of the presented technique compared to the based models. Encouragingly, our results indicate nearly 99% accuracy in fall detection, demonstrating promising potential for real-world application.

In this study, a numerical model that employs smoothed particle hydrodynamics (SPH) is presented to simulate the temperature distribution and measure the weld pool surface area of disk laser-welded overlap aluminum sheets. This simulation technique is well suited for performing three-dimensional calculations with high spatial resolution while keeping low computational costs. This simulation models laser welding of AA6061-T6 aluminum sheets, a well-known commercial alloy used in various transportation industries, predicting temperature distribution and the fusion zone surface area. The first approach dictates a comparison of the numerically calculated temperature distribution during laser welding over experimental tests instrumented with thermocouples. The second validation method involves a comparison between numerical simulations of the top surface melt pool area with the experimental measurements extracted from high-speed camera images. The most remarkable results of comparisons between simulated and experimental temperature distributions reveal significant agreement, highlighting the ability of the simulation model to accurately reproduce the thermal phenomena observed in experiments. The effect of laser welding speed and power on the dimensions of the fusion zone was analyzed and highlighted that the higher the welding speed, the narrower the weld pool is. This behavior reflects a reduction in the width and length of the weld pool, resulting in a contraction of its upper surface. The effect of welding parameters on cooling rates and melt zone volume is also discussed. This study will serve as a reference for identifying the main parameters, such as top surface dimensions and melt volume, as well as temperature distribution during laser welding, which could eventually enable a hot cracking criterion to be determined using numerical simulations. Graphical Abstract