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Driver distraction in school zones: A roadside observational study in Canada
No full textDistracted and impatient driving are top contributors to road crashes and fatalities. However, we lack sufficient data on the prevalence of dangerous behaviours and quantities of active transportation users integrated with motorized traffic in school zones – urbanized areas that exhibit higher rates of vulnerable road users. This study fills this gap by investigating the prevalence of driver distraction and impatient driving at seven locations in school zones in the city of Windsor, Ontario in Canada. Roadside observations were conducted during the Fall of 2024 and Winter of 2025 at peak activity periods during both the morning drop-off and afternoon pick-up times. Dangerous behaviours were measured as a factor of environmental factors (weather, season), time of the day (AM vs PM), and vehicle characteristics. Results showed an increased presence of dangerous driving in warmer months, with no significant differences being found between morning and afternoon. Approximately 20% of all drivers were engaged in distracting or impatient driving, with one in ten drivers being engaged in unlawful behaviours involving the use of handheld devices while driving. Drivers of larger vehicles also exhibited more dangerous driving. Our study adds to the distracted and impatient driving literature, and offers valuable information for road safety practitioners and regulators that can be used to implement more targeted road safety solutions
Greenhouse electrification via transactive energy management strategy
No full textDistributed energy resources have grown significantly in Canada and the world over the past decade, particularly in the agricultural sector. As P2P (peer-to-peer) energy trading plays a fundamental role in renewable energy uptake and system flexibility for the low-carbon energy transition, this paper provides an overview of this approach from a techno-economic standpoint for two greenhouses located in Leamington, Ontario. The real-time site solar irradiation, ambient temperature, and load demand over 8760 h have been utilized to drive the designs. In this investigation, two cases are assessed for pepper greenhouse: Case I: energy purchase from the grid and Case II: energy purchase from excess energy of neighbor which is cucumber-tomato greenhouse. The integration of 50 kW PV/1 kWh battery/35 kW converter achieves the feasibility criteria by recording net present cost (NPC) and cost of energy (COE), which are 0.044/kWh, respectively
Comparative numerical modelling of the behaviour of CFRP composites under hypervelocity impact
No full textMicro-meteoroids and orbital debris (MMOD) travelling at orbital speeds (>7 km/s) at low Earth orbit pose a prevalent threat to the operational integrity of satellites through hypervelocity impacts (HVIs). Damage to these structures can be quantified through the economic expenses related to loss of operation and replacement. Facesheets, usually fabricated from metals like aluminum, and, more recently, advanced composite materials such as carbon fiber-reinforced plastics (CFRPs), are generally the first line of defense against incoming debris. However, the deformation and damage that these materials undergo, especially CFRPs, in these situations needs to be better understood to improve design capabilities. Physical testing provides the best avenue for exploring material behaviour, however it is often associated with high economic and time expenses. A commonly accepted alternative relies on using numerical modelling of HVI shielding structures. Numerical studies regarding these impacts generally rely on either the traditional implementation of the finite element method (FEM, which is well-suited to modelling delamination between ply layers) or the smoothed particles hydrodynamics method (SPH, well-suited for modelling fragmentation and extreme deformations), neither of which fully captures the complete scope of failure. An adaptive FEM-SPH method is considered within this study to more comprehensively model the simultaneously occurring damage mechanisms. 16-ply composites under HVI by three different projectile materials, namely steel (high-density), aluminum (medium-density), and nylon (low-density), are modelled within this study. Crater size and delaminated area reported the numerical simulations were compared with results observed in experimental studies and were used as metrics to determine the accuracy of the numerical models
Women participating in sport: tensions rising from negotiations of aging, gender norms, and personal responsibility for health in later life
No full textIntroduction Older women have typically faced systemic exclusion from sport, often a result of intersecting age- and gender-based norms and/or constraints. This study investigated how 22 women (mean age 61 years) participating in recreational or competitive sport understood and experienced their participation in relation to societal expectations of aging, gender, and maintaining health and wellbeing. Methods The women, aged 52–77 years, each participated in a semi-structured interview to explore their perspectives on aging, disability, societal perceptions, and sport engagement. Interviews were audio-recorded, transcribed, anonymized, and analyzed using reflexive thematic analysis, emphasizing researcher subjectivity and iterative theme development. Results The women framed their sport involvement as a moral and disciplined practice, aligning with neoliberal ideals of personal responsibility and self-management for health in later life. However, their narratives also highlighted systemic barriers, such as professional demands, caregiving responsibilities, and gendered norms, that constrained their participation. This “double barrier” of age and gender norms produced a tension between perceived agency and structural exclusion. Discussion While older women actively asserted responsibility for their health and engagement, their experiences revealed that structural inequities related to age and gender expectations, not personal failings, often limited participation. Conclusion These findings challenge responsibility-centred narratives and call for inclusive sport policies that account for the socio-cultural and institutional barriers shaping older women's experiences in sport and exercise contexts
Estimating Snow-Related Daily Change Events in the Canadian Winter Season: A Deep Learning-Based Approach
No full textSnow water equivalent (SWE), an essential parameter of snow, is largely studied to understand the impact of climate regime effects on snowmelt patterns. This study developed a Siamese Attention U-Net (Si-Att-UNet) model to detect daily change events in the winter season. The daily SWE change event detection task is treated as an image content comparison problem in which the Si-Att-UNet compares a pair of SWE maps sampled at two temporal windows. The model detected SWE similarity and dissimilarity with an F1 score of 99.3% at a 50% confidence threshold. The change events were derived from the model’s prediction of SWE similarity using the 50% threshold. Daily SWE change events increased between 1979 and 2018. However, the SWE change events were significant in March and April, with a positive Mann–Kendall test statistic (tau = 0.25 and 0.38, respectively). The highest frequency of zero-change events occurred in February. A comparison of the SWE change events and mean change segments with those of the northern hemisphere’s climate anomalies revealed that low temperature and low precipitation anomalies reduced the frequency of SWE change events. The findings highlight the influence of climate variables on daily changes in snow-related water storage in March and April
Exploring the role of volume energy density in altering microstructure and corrosion behavior of nitinol alloys produced by laser powder bed fusion
No full textIn the realm of materials science and engineering, the pursuit of advanced materials with tailored properties has been a driving goal behind technological progress. Scientific interest in laser powder bed fusion (L-PBF) fabricated NiTi alloy has in recent times seen an upsurge of activity. In this study, we investigate the impact of varying volume energy density (VED) during L-PBF on the microstructure and corrosion behaviour of NiTi alloys in both scan (XY) and built (XZ) planes. The microstructural evolution in both planes was characterized by electron backscatter diffraction and phase change temperatures were characterized using differential scanning calorimeter measurements. Electrochemical experiments were carried out to compare the specimens produced at high laser energy density and low laser energy density. The results indicate that employing high laser energy density in the production of NiTi alloy induces discontinuous dynamic recrystallization, contributing to grain refinement. This in turn enhances the corrosion resistance of the specimen. X-ray photoelectron spectroscopy was employed to examine the type of oxide layer that developed on the samples. The increased resistance to corrosion in a high laser energy density sample can be associated with the formation of a stable and homogeneous passive layer with enriched TiO2 as opposed to Ti2O3. This exploration has unravelled the intricate relationship between VED, the microstructure, and the corrosion properties of L-PBF fabricated NiTi alloys, offering valuable insights into their performance for diverse applications
Machine Learning-Based Smartphone Grip Posture Image Recognition and Classification
No full textUncomfortable smartphone grip postures resulting from inappropriate user interface design can degrade smartphone usability. This study aims to develop a classification model for smartphone grip postures by detecting the positions of the hand and fingers on smartphones using machine learning techniques. Seventy participants (35 males and 35 females with an average of 38.5 ± 12.2 years) with varying hand sizes participated in the smartphone grip posture experiment. The participants performed four tasks (making calls, listening to music, sending text messages, and web browsing) using nine smartphone mock-ups of different sizes, while cameras positioned above and below their hands recorded their usage. A total of 3278 grip posture images were extracted from the recorded videos and were preprocessed using a skin color and hand contour detection model. The grip postures were categorized into seven types, and three models (MobileNetV2, Inception V3, and ResNet-50), along with an ensemble model, were used for classification. The ensemble-based classification model achieved an accuracy of 95.9%, demonstrating higher accuracy than the individual models: MobileNetV2 (90.6%), ResNet-50 (94.2%), and Inception V3 (85.9%). The classification model developed in this study can efficiently analyze grip postures, thereby improving usability in the development of smartphones and other electronic devices
