Plan S and Open Access (OA) in Quebec: What does the revised FRQ OA policy mean for researchers?

Objective: Our article examines the effects of Quebec’s provincial funding agency (FRQ)’s revised 2022 OA policy on researchers. Following FRQ’s participation as a cOAlition S funding agency, which involves endorsing Plan S principles, we provide an overview of the OA options for researchers. We examine these options under the FRQ 2019 and FRQ 2022 policy years, account for the effect of transformative agreements (TA) on OA publishing options, as well as the financial implications for researchers under the revised policy. Methods: The researchers extracted a list of FRQ-funded publications from years 2020 to 2022 using the DOI registration agency Crossref. Using this sample set, we, the researchers, quantitatively analyzed OA options under the previous policy and the revised one, comparing the two. To determine the effect of transformative agreements (TAs)s, we reviewed current agreements offered through Canada’s national licensing agency Canadian Research Knowledge Network (CRKN). Results: We found that the self-archiving method for open access (OA) is reduced under the revised 2022 policy. Our results lead us to anticipate the pressure felt by authors who will be required to pay article processing charges (APCs) to meet grant requirements. Conclusion: The current publishing patterns of FRQ-funded researchers are primarily concentrated in hybrid journals not covered by transformative agreements. As such, researchers will face additional financial costs should these publishing patterns continue. Concerted efforts among all stakeholders (researchers, universities, libraries, and funders) are needed to sustainably transition to immediate OA

Men’s Experiences of Paternity Leaves in Accounting Firms

Accounting researchers and practitioners have made strides in addressing persistent gender inequalities in the accounting profession. However, these efforts have largely sidestepped men and masculinities. Our study considers the role of men and masculinities in gender inequalities by exploring how men in accounting experience paternity leaves. We conduct interviews with thirteen men in audit firms in France. We find that fathers are reluctant to take leaves which they view as vacation periods incompatible with their professional work. They see audit firms as offering less support to fathers than mothers, with support for fathers growing but still marginal. Finally, they experience a variety of emotions, including positive emotions around fatherhood and negative emotions around difficulties in reconciling fatherhood with professional responsibilities and paternity leaves. Practically, our findings imply that to address gender inequalities further, accounting firms need to change the norms around care work, including paternity leaves

Summoning Black Beach

Summoning Black Beach is the culmination of a material research completed over the course of the MFA program. The exhibition text is structured as a series of short stories that tells of the artists' personal experiences and encounters with key materials important in the exhibition. Also included are photo documentation of the thesis show (of the same name) held at Centre d'art et de diffusion CLARK

Solidarity in Isolation: Shared Pandemic Experiences of Medical and Academic Middle Manager Librarians

In this chapter, five librarians in leadership and middle management roles (most hired or promoted not long before the COVID-19 pandemic) share their experiences

The Use of High-Velocity Air Fuel for Solid-State Additive Manufacturing

Ti-6Al-4V components used extensively in aero engines are prone to damage. When a part is damaged, it can be repaired or replaced. Compared to replacing, repairing methods such as solid-state additive manufacturing processes are more cost-efficient. Among solid-state additive manufacturing methods, cold spray (CS) is more promising because it fabricates samples at high deposition rates without oxidation or phase transformation. Using CS, it is possible to manufacture samples with low porosity levels; however, the existing pores that result from insufficient deformation of the solid-state particles adversely affect the mechanical properties. To enhance sample density, particle deformation should be increased by thermally softening them during deposition. As cold spray cannot deposit particles at elevated temperatures, this thesis proposes using high-velocity air-fuel (HVAF) as a solid-state additive manufacturing technology. The numerical analysis reveals that through the thermal softening effect, particle deformation will increase by elevating the deposited particle temperature. This allows a denser structure to be fabricated. Nevertheless, the increase in particle deformation does not necessarily indicate better particle adhesion to the substrate. In order for the particle and substrate to adhere better, both the particle and the substrate oxide layer need to be broken and ejected. Particle and substrate oxide layer failures depend on particle velocity and temperature and particle velocity and substrate temperature, respectively. The inner-diameter HVAF process (ID-HVAF) has been used as a solid-state deposition technique. Results showed that increasing nozzle length and air/fuel pressure enhanced the velocity of in-flight particles and the density of as-sprayed Ti-6Al-4V coatings. Using the spraying conditions that produced the densest coating, the ID-HVAF process was used to fabricate four-mm thick Ti-6Al-4V samples. Heat treatment was required to enhance the mechanical properties of the samples by transforming the brittle α-Ti phase into the more deformable β-Ti phase. Applying heat treatment decreased porosity from 1.18% to 0.98%. Lastly, the results show vanadium oxide presence in both as-fabricated and heat-treated samples. Oxygen content measurements revealed 1.6 wt% oxygen in both samples. This acts as an α-phase stabilizer and negatively affects the hardness of heat-treated samples

System-Level Analysis and Design of Safety-Critical Cyber Physical Systems

The reduction in size and cost of hardware together with the accelerating innovation and advancement in sensor and computational technologies have opened the door for cyber physical systems into all types of applications. While most early systems involved varying degrees of human involvement, the various success stories are encouraging designers to develop cyber physical systems for autonomous control. The trustworthiness of a cyber-physical system is essential for it to be qualified for utilization in most real-life deployments. This is especially critical for systems that deal with precious human lives. which can be engaged directly as in biomedical systems or indirectly as in automotive systems. Although use-cases for biomedical and automotive systems are considered, the proposed generalized framework can be used to analyze the safety of various cyber-physical systems. These safety-critical systems can be investigated using both experimental testing and model-based verification. Accurate models have the potential to permit investigating the system behavior under abnormal scenarios. Also, appropriate modeling can speed-up the development process by evaluating candidate designs at an early stage of the design cycle. Model-based verification can be conducted using the less-exhaustive simulation testing or the resources-greedy model checking. As a trade-off, statistical model checking bears a feasible approach where statistical guarantees can be examined with a specific level of confidence. This research addresses the problem of utilizing accurate system-level models to analyze and design safety-critical cyber-physical systems. The behavioral descriptions of cyber physical systems are modelled by constructing equivalent formal models. These system-level models are used to conduct statistical model checking to verify properties written using metric interval temporal logic and to provide statistical guarantees on the system safety. This approach is applied on biomedical and automotive systems to verify their safety with consideration for some distortions resulting from unintentional or intentional sources. The proposed verification approach enlightens the development process by providing feedback that can help elect the designs. Moreover, new robust and safe control techniques are proposed to enhance the safety of a closed-loop glucose controller system. Also, a systematic approach is proposed for safety analysis of cyber physical systems. This approach processes systems described using SysML diagrams and applies a new proposed automatic algorithm to construct equivalent formal models. This research work is a step towards bridging the gap between system-level models and formal models so that analysis can be conducted efficiently to enhance the safety and robustness of cyber-physical systems

The Authenticity Factor: Understanding the Impact of User-Generated Content Sponsorship on Consumer Behaviour for Value-Expressive Products

In a world where social media has transformed the way consumers make purchasing decisions, user-generated content (UGC) has become a powerful tool for marketers to reach and engage with their target audience. This study examines the impact of UGC sponsorship on consumer behaviour, focusing on the mediating role of perceived authenticity and the moderating impact of source familiarity, specifically in the context of value-expressive products within the fashion industry. A quantitative research design was employed, utilizing two online questionnaires to gather data. The findings demonstrate that non-sponsored UGC is perceived as more authentic than sponsored UGC and has a stronger influence on consumer intentions to search, share, and purchase. On the other hand, source familiarity was found to have no significant impact on these effects. Given the limited research on this topic, the findings of this study will provide valuable insights into the factors that determine the effectiveness of sponsored and non-sponsored UGC. The study will also contribute to the existing literature on UGC and offer practical implications for marketers in effectively managing user-generated marketing messages and a better understanding of the importance of perceived authenticity in shaping consumer intentions. Keywords: User-Generated Content (UGC), Perceived Authenticity, Consumer Behaviour, Value-Expressive Products, Source Familiarity, Sponsorship, Marketing Strateg

New Signal Priority Strategies to Improve Public Transit Operations

Rapid urbanization is causing severe congestion on road transport networks around the world. Improving service and attracting more travellers could be part of the solution. In urban areas, improving public transportation efficiency and reliability can reduce traffic congestion and improve transportation system performance. By facilitating public buses' movement through traffic signal-controlled intersections, a Transit Signal Priority (TSP) strategy can contribute to the reduction of queuing time at intersections. In the last decade, studies have focused on TSP systems to help public transportation organizations attract more travellers. However, the traditional TSP also has a significant downside; it is detrimental to non-prioritized movements and other transport modes. This research proposes new TSP strategies that account for the number of passengers on board as well as the real-time adherence of buses to their present schedules. Two methods have been proposed. First, buses are prioritized based on their load and their adherence to their schedules, while in the second method, the person delay at an intersection is optimized. The optimization approach in the first method uses a specific priority for public transit, while additional parameters are considered in the second method, like residual queue and arrival rate at the intersection. One of this research's main contributions is providing insight into the benefits of these new TSP methods along a corridor and on an isolated signalized intersection. The proposed methods need real-time information on transit operations, traffic signals status and vehicular flows. The lack of readily available infrastructure to provide all these data is compensated by using a traffic simulator, VISSIM, for an isolated intersection and an arterial corridor. The study area simulation results indicated that the new TSP methods performed better than the conventional TSP. For the investigated study area, it was shown that the second method performed better in an isolated signalized intersection, while the first method reduced traffic and environmental indices when used for an arterial corridor. Future research can investigate the effects of the proposed methodology on the urban network by using macrosimulation to see the effects of the proposed TSP on the network. Also, considering conflicting TSP requests in these methodologies could be another area for further research

Integrated Optimization of Location, Design, and Operation of Renewable Energy Systems for Urban Microgrids

The building sector of urban areas plays a crucial role in carbon emissions and climate change. Distributed generation using clean energies could help to reduce emissions. Furthermore, urban microgrids increase the reliability of power supply since most of the power outages are created in the grid distribution system and transmission lines. However, a cost-effective design and operation of an urban microgrid poses challenges, such as limited space for installing the renewable components, especially in populated areas, the uncertainty of renewable resources, and the resiliency of the designed microgrid in case of not having access to the central grid. Therefore, this thesis was initiated with the objective of developing a comprehensive method for the efficient design of an urban microgrid. The developed framework consists of three main modules. The first module aims at designing an energy system for a community microgrid by sizing and finding the optimum configuration of the energy system. To resolve the spatial issue problem in urban areas, regional renewable generation is proposed in this research where clean energy is produced outside of the populated area as a virtual power plant in relation to the microgrid. A mapping model is also developed to select the best location for installing components outside the microgrid. The mapping model is connected with the optimization model to automatically generate the best configuration and location of regional generation based on several aspects of each zone. The second module deals with renewable resources and electrical load demand uncertainties and tries to reduce them by forecasting strategies. Since renewable resources such as solar irradiance and wind speed are not predictable using just historical data, hybridized numeric weather prediction (NWP) and deep learning models are offered to tackle the drawback. The last module proposes a solution to ensure resilience against power supply failures in electricity grids caused by extreme weather conditions, unavailability of generation capacities, and transmission components problems. The discussed models were applied to one of Concordia University's largest buildings in downtown Montreal, Canada. The results show a significant improvement in the environmental aspect of the regional generation if the existing gas boiler would be substituted by electric boilers and heat pumps (using generated renewable electricity outside of microgrid), preventing emissions of about 4233 tons CO2 and 5.3 tons NOX per year. Using a proposed tariff structure beneficial to both the customer and utility, the resulting levelized cost of energy is about 5.3 Cents per kilowatt hour, i.e., lower than the current rate of about 6 Cents per kWh. Using the second module’s proposed hybrid models for renewable resources and electrical load demand prediction of the case study was also helpful by considerably bringing down the error. Finally, operation dispatch scenarios are developed to reinforce the system’s resiliency in severe conditions for the case study in the third module. A mixed-integer linear programming (MILP) approach is employed to identify global optimum dispatch solutions based on the next 48 h plans for different seasons to formulate a whole-year operational model. The results show that the loss of power supply probability (LPSP), as an indicator of resiliency, could be lowered to near zero while minimizing operational cost using the proposed optimal load (derived from critical load)

Efficient Computational Methodologies for Multi-Objective Optimization of Distributed Energy Resources (DER) Inverters

The paralleling of power converters connected to the grid for power-sharing is a widely used technique. In this context, the design framework for a low-cost, lightweight, compact, and high-performance optimum configuration is an open research problem. This thesis proposes an innovative Multi-Objective Hierarchical Optimization Design Framework (MO-HO-DF) for an Alternating Current (AC) grid interface with N interleaved H-bridges, each with M parallel ``to-be-determined'' switches, connected through coupling inductances (Lf). A total of eight Figures of Merit (FOMs) were identified for the design framework optimization. A rigorous model of the power electronic system is presented. Next, a highly computationally efficient algorithm for the estimation of the required frequency modulation ratio (mf) to meet current harmonic performance requirements for any given configuration is proposed. Then, the concept and implementation of the algorithm are presented for the MO-HO-DF. The effectiveness of the design optimization framework is demonstrated by comparing it to a base case solution. Finally, the design calculations are validated via Piecewise Linear Electrical Circuit Simulation (PLECS) software with manufacturer-provided Three-Dimensional (3D) power semiconductor models that include thermal modelling. In particular, when an H-bridge is interfaced with a single-phase grid, it requires controllers to regulate the voltages and currents in the system. In this context, the static optimization of controllers responsible for Direct Current (DC) bus voltage regulation and AC regulation, considering time-domain and frequency-domain behaviours, is an open research problem. Firstly, this thesis proposes a method to obtain FOMs with the use of inbuilt functions in MATLAB software. Then for the Type-II Proportional+Integral (PI) controller, a single-variable two-objective convex optimization is proposed. Next, for the Proportional+Multi-Resonant (PMR) controller, three-variable five-objective convex optimization is proposed. The design of the PMR controller is a multi-variable problem that can inherit the principles of a hierarchical framework and leverage the effect of a design variable on the final optimization result. Thus, the work on PMR controller design optimization is extended to a three-level hierarchical design framework and evaluates all six possible paths for optimization. Finally, enhanced macro-model-based MATLAB simulation results are provided to verify the performance of controller designs and generate statistical insights