Lakehead University Knowledge Commons

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Trauma, ableism, and the CODA experience in educational contexts
(2026) McLetchie, Ashley; Mastrangelo, Sonia; Narine, Caroline; Lovell-Johnston, Meridith; Snodden, Kristin
This qualitative phenomenological study explored how ableist societal structures influence the identity development, lived experiences, and well-being of Children of Deaf Adults (CODA), with particular attention to educational contexts. Guided by Critical Disability Theory and Stuart Shanker’s Self-Regulation Framework, the study examined how systemic barriers contribute to both hardship and resilience among CODAs and how educational systems can better recognize and support them. Eight adult CODAs between the ages of 20 and 34 participated in semi-structured interviews and completed a demographic questionnaire. This study contributes to the limited body of research on CODAs by centering their voices and lived experiences. It recommends recognizing CODAs as Multiple Language Learners (MLLs), improving educator knowledge of Deaf culture and bilingual language development, ensuring accessible communication for Deaf parents, increasing Deaf and CODA representation within curricula, and expanding culturally responsive mental health supports. Ultimately, the findings call for educational and social systems that move beyond accommodation toward equity, cultural validation, and meaningful inclusion for CODAs and their families.
A comparative structural workflow for investigating structural features associated with immunoglobulin E cross-reactivity between cow’s milk and respiratory lipocalin allergens
(2026) Peter, Ikebek S.; Floriano, Wely
Background: Cow’s milk allergy and allergic asthma can occur in the same individuals, but it is not well understood at the molecular level. Bovine β-lactoglobulin (Bos d 5) is a major cow’s milk allergen and a member of the lipocalin protein family. Several clinically important respiratory allergens are lipocalins. Their shared fold provides a basis for comparing surfaces that may be relevant to IgE recognition. Objective: To develop a structural workflow for comparing Bos d 5 IgE-binding regions with corresponding regions in milk, respiratory and human lipocalins. Methods: Literature-reported linear IgE-binding regions of Bos d 5 and the conformational epitope defined from the Bos d 5 IgE–Fab complex were mapped onto homologous lipocalin structures using structural alignment. In parallel, comparative Fab–query allergen models were generated by positioning each query structure in the binding orientation defined by the Bos d 5 IgE–Fab complex. Structural and physicochemical descriptors were calculated after standardized preparation without additional energy minimization (RAW) and with minimization (MIN). Similarity to Bos d 5 was assessed using principal component analysis (PCA), Euclidean distance-based ranking, and group comparisons using permutation tests. Results: The dataset comprised the Bos d 5 reference structure (n = 1), respiratory allergens (n = 23), human lipocalins (n = 18), and β-lactoglobulin (βLG) homologs (n = 17 Across mapped linear IgE-binding regions, non-bovine ruminant βLGs most frequently ranked closest to Bos d 5, occupying the top rank in 8 of 12 analyses under the RAW protocol and 7 of 12 analyses under the MIN protocol. For the mapped conformational epitope region, non-bovine ruminant βLGs showed the smallest median distance to Bos d 5 under both protocols (RAW: 0.82; MIN: 1.10). The comparison with respiratory allergens was significant under RAW (p = 0.0311), but not under MIN (p = 0.0774). In the MIN composite analysis, median distances were 1.60 for non-bovine ruminant β-lactoglobulins, 4.46 for respiratory allergens and 4.51 for human lipocalins. Several respiratory lipocalins, including Fel d 4, Can f 4, Mus m 1, Fel d 7, and Cav p 1, repeatedly appeared among nearer neighbors in selected descriptor sets; however, this pattern was not consistent across all descriptor sets. Conclusion: This study developed a reproducible structural comparison workflow for evaluating IgE-binding surface similarity across homologous lipocalins. Application to Bos d 5 consistently recovered close similarity among non-bovine ruminant βLGs, as expected from their close evolutionary and structural relationship. A subset of respiratory lipocalins showed partial structural similarity in selected analyses, but this pattern was not consistent across all comparisons. The workflow therefore provides a way to prioritize candidate proteins and surface regions for experimental testing of IgE binding and possible cross-reactivity.
Trustworthy aerial edge computing with robust, priority-aware, and learning-based optimization for 6G networks
(2026) Butt, Muhammad Omair; Ejaz, Waleed; Aujla, Gagangeet; Ikki, Salama; Yassine, Abdulsalam
Aerial edge computing serves remote and disaster-affected regions where terrestrial coverage is sparse or unavailable. Trust in these deployments reflects the consistency with which an uncrewed aerial vehicle (UAV) fulfills the tasks it accepts. The existing literature generally develops trust measures without explicitly connecting them to the admission of Internet of things (IoT) devices. These measures typically associate trust with regions, data contributions, or device populations. IoT device admission meanwhile focuses on UAV resources such as coverage, residual energy, and computing capacity. This resource-oriented view describes what a UAV can offer rather than what it has reliably delivered. Offloading commits each device to the service the selected UAV provides, which makes trust an important consideration in aerial edge computing. This thesis proposes a trust-aware aerial edge computing framework that delivers trustworthy mobile edge computing (MEC) from UAVs to IoT devices. The framework evaluates each UAV through multiple trust dimensions and admits an IoT device only when the selected UAV meets the trust requirement of its task. We formulate joint UAV deployment, device association, and resource allocation as a multi-criteria mixed-integer nonlinear program (MINLP) balancing connectivity, trust, cost, and task latency. A penalty-guided optimization (PGO) algorithm based on sequential quadratic programming (SQP) solves the resulting problem and achieves near-optimal connectivity relative to branch-and-bound at substantially lower computational cost. We extend the framework to uncertain IoT device states, differentiated task requirements, and device mobility. Uncertainty in residual energy and device location enters the IoT-UAV association decision as an explicit input. Task priority accompanies trust within the same association decision and captures the deadline-sensitive requirements of individual tasks. IoT mobility follows a Gauss-Markov process within the extended problem formulation. UAV deployment and the associated decision-making proceed under centralized, hybrid, and fully distributed control schemes. Connectivity remains near the optimal benchmark under both device-state uncertainty and task heterogeneity. Mobile settings reveal a trade-off between accumulated reward and trust assurance across the three control strategies. Trust therefore functions as a decision criterion that complements resource availability, task requirements, and network dynamics in aerial edge computing.
Effects of wood ash amendments on greenhouse gas production and soil solute dynamics in hydromorphic forest soils of Northwestern Ontario
(2026) Huth, Adelaide; Basiliko, Nathan; Pendea, Florin; Emilson, Erik; Morris, Dave; Venier, Lisa
Wood ash recycling can return nutrients to forest soils, but responses in hydromorphic settings remain poorly characterized. This study examined how ash type and application rate affect pH and dissolved base cations, whether riparian and upland soils differ in methane (CH₄) concentrations, and how gas responses change during anaerobic incubation. Two boiler ashes (PB3 and PB6) were applied at nominal rates of 0, 5, 10, 20 and 50 t ha⁻¹ to five soil composites from northwestern Ontario: two riparian, two upland and one buffer source. Laboratory microcosms were incubated under N₂-flushed conditions for 60 days. Headspace CH₄ and carbon dioxide (CO₂) were measured on Days 10 and 34, and filtered-water chemistry was assessed on Day 60. Ash-amended pH values exceeded the corresponding untreated controls in all five soils by 0.78–2.53 units, including at the lowest rate, supporting the expectation that ash reduces acidity. Dissolved base-cation responses depended on the element, soil and ash: sodium increased in many amended treatments, while calcium and magnesium varied among soils and rates. The hypothesis of higher riparian CH₄ concentrations was partly supported: both riparian sources exceeded their paired upland sources at Day 10, but Black Spruce upland exceeded Black Spruce riparian at Day 34. Temporal gas responses varied among soils and treatments, consistent with the third hypothesis; CO₂ also increased in untreated jars, and neither gas showed a uniform response to increasing ash rate. Exploratory mercury measurements often showed lower filtered-water total mercury (THg) in amended samples, but methylmercury was not measured. Limited field replication and chemistry coverage, together with departures from gas-model assumptions, constrain inference. The findings identify soil- and ash-specific responses for field testing and water-quality monitoring, without establishing an operational application rate.
Secure routing protocol for lossy, congested, and attack-prone Flying Ad Hoc Networks
(2026) Yusuf, Shaji; El-Ocla, Hosam; Tan, Xing; Rathore, M. Mazhar
Flying Ad Hoc Networks (FANETs) provide flexible and rapidly deployable wireless communication among unmanned aerial vehicles (UAVs) without relying on fixed infrastructure. These networks are useful in applications such as disaster response, surveillance, environmental monitoring, military communication, and emergency coordination, where timely and reliable packet delivery is important. However, FANET communication is difficult to maintain because UAV nodes move rapidly in three-dimensional space, causing frequent topology changes, link breakage, route instability, queue buildup, packet retransmissions, and energy consumption. In addition to these normal wireless and mobility-related challenges, FANETs are also vulnerable to low-rate Denial-of-Service (LDoS) attacks. Such attacks are difficult to detect because they do not necessarily generate a continuously high traffic volume. Instead, FB-Shrew-like attackers transmit short bursts of relatively small packets at carefully selected intervals, occupying buffer space and forcing legitimate TCP packets to experience delay, retransmission, or loss. This thesis proposes a secure multipath routing protocol called AOMDV-GAD to improve communication resilience in lossy, congested, and attack-prone FANET environments. The proposed protocol integrates lightweight sender-side packet-loss classification with Genetic Algorithm-based route optimization. Traffic characteristics that are unavailable at the source are measured at the receiving node and conveyed to the source through ICMP feedback, after which the source distinguishes packet loss caused by random wireless conditions, ordinary congestion, and low-rate DoS activity. This distinction is important because these three events require different network responses. Random loss should not automatically cause a route to be treated as malicious, congestion should encourage the selection of routes with better queue availability, and LDoS activity should cause routes containing suspected nodes to be avoided. The routing component of AOMDV-GAD extends the multipath capability of Ad hoc On-Demand Multipath Distance Vector (AOMDV) routing. AOMDV first discovers multiple candidate routes between a source and destination. The proposed DoS detection output is then used as a mandatory route-screening condition. Routes containing a DoS-suspected UAV are removed from the candidate route set before fitness evaluation. Only the remaining safe routes are evaluated using queue availability and residual-energy information. The queue factor reduces the selection of heavily loaded intermediate UAVs, while the residual-energy factor reduces repeated dependence on weak or energy-depleted nodes. A Genetic Algorithm is then applied to the safe route population using selection, crossover, mutation, and survivor selection to identify an efficient forwarding route. In this design, route security is separated from route-performance optimization, preventing an attack-affected route from being selected simply because it has favourable congestion or energy values at a particular instant. The proposed protocol was implemented and evaluated using NS-3.35 in a three-dimensional FANET simulation environment. The evaluation considered variations in the number of UAV nodes, percentage of malicious nodes, UAV mobility speed, and simulation duration. AOMDV-GAD was compared with AOMDV, AOMDV-FG, HWSCS-HDL, CLUN-LSR, and JRP-LA using throughput, Packet Delivery Ratio (PDR), end-to-end delay, routing overhead, and energy consumption. The simulation results show that AOMDV-GAD improves packet delivery and throughput while reducing delay, routing overhead, and energy consumption under dense, mobile, and attack-prone conditions. For example, at 150 UAVs, AOMDV-GAD achieved approximately 2.28 Mbps throughput and 83.07% PDR, compared with approximately 1.06 Mbps throughput and 46.23% PDR for AOMDV. Similar improvements were observed when the malicious-node percentage reached 40%, the UAV speed reached 40 m/s, and the simulation duration reached 100 s. The results demonstrate that combining packet-loss classification, DoS-based route screening, congestion-aware evaluation, residual-energy-aware selection, and GA-based route optimization provides a more resilient routing mechanism for highly dynamic FANETs. The proposed approach reduces the probability of repeatedly forwarding packets through compromised, congested, or energy-weak routes and improves the ability of the network to maintain useful communication under adverse conditions.