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For many cyber-physical systems, e.g., IoT systems and autonomous vehicles, offloading workload to auxiliary processing units has become crucial. However, since this approach highly depends on network connectivity and responsiveness, typically only non-critical tasks are offloaded, which have less strict timing requirements than critical tasks. In this work, we provide two protocols allowing to offload critical and non-critical tasks likewise, while providing different service levels for non-critical tasks in the event of an unsuccessful offloading operation, depending on the respective system requirements. We analyze the worst-case timing behavior of the local cyber-physical system and, based on these analyses, we provide a sufficient schedulability test for each of the proposed protocols. In the course of comprehensive experiments, we show that our protocols have reasonable acceptance ratios under the provided schedulability tests. Moreover, we demonstrate that the system behavior under our proposed protocols is strongly dependent on probability of unsuccessful offloading operations, the percentage of critical tasks in the system, and the amount of offloaded workload.

A Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Master of Applied Science in Software Systems Engineering, University of Regina. xii, 126 p. Connected Autonomous Vehicles (CAV) industry is expected to grow rapidly in the upcoming years. Many enterprises will need to adapt new techniques to be able to participate in CAV growth. Although some manufacturers promise high level of automation by 2025, the needed infrastructure investment will take longer time due to the huge investments’ capital and the time needed for constructions. CAV will need to continuously communicate with their surroundings in order to guarantee efficient and safe trips. One of the main communicating methods is Vehicle to Infrastructure, which mainly depends on Roadside Equipment in North America. There’s a need to give decision makers best possible information to help them make investment decisions and define risks. Profit and Loss analysis is not enough because it doesn’t cover operational design, value creation, or value exchange in the business ecosystem. A sound knowledge of business operations through business modeling will allow business owners to take proper investment decisions and perform proper risk identification and consequently, choose the appropriate risk management strategies. Traditional business modeling techniques are insufficient to cope with elements of CAV and investment decisions. Supply Chain Operating Reference (SCOR), Value Network Analysis (VNA), Value Reference Model (VRM), and e3Value were all specific business modeling techniques which targeted supply chain or economic values. The Value Management Modeling Language (VDML) is a superior approach because it addressed value creation and value exchange in the ecosystem and provided deep understanding of business operations. Road owners need VDML business modeling to study the possibility of making their roads ready for Connected Autonomous Vehicles (CAV) operations. No previous modeling attempts were made for this purpose. Also, to reduce service development risks, business owners will need to guarantee alignment and reduce service development time and cost. In this research a methodology has been suggested to use the VDML based Value Management Platform (VMP) to assist the road owners in their decision and allow them to perform risk identification and take investment decisions. The model was validated against previous years’ financial data of 407ETR as an example of a road owner and was projected to four years of operations. Using the Unified Modeling Language (UML) for service development achieves intracompany alignment which reduces service development risks. The VMP tool did not produce UML use case diagrams, therefore, a tool has been developed to supply VMP-based UML use case diagrams Student yes

Objectives: To describe the baseline characteristics of SLE patients requiring biologic therapy in the UK and to explore short term efficacy and infection rates associated with rituximab (RTX) use.\ud \ud \ud \ud Methods: Patients commencing biologic therapy for refractory SLE and who consented to join BILAG-BR were analysed. Baseline characteristics, disease activity (BILAG 2004/SLEDAI-2K) and rates of infection over follow-up were analysed. Response was defined as loss of all A and B BILAG scores to ⩽ 1 B score with no new A/B scores in other organ systems at 6 months.\ud \ud \ud \ud Results: Two hundred and seventy SLE patients commenced biologic therapy from September 2010 to September 2015, most commonly RTX (n = 261). Two hundred and fifty (93%) patients were taking glucocorticoids at baseline at a median [interquartile range (IQR)] oral dose of 10 mg (5–20 mg) daily. Response rates at 6 months were available for 68% of patients. The median (IQR) BILAG score was 15 (10–23) at baseline and 3 (2–12) at 6 months (P < 0.0001). The median (IQR) SLEDAI-2K reduced from 8 (5–12) to 4 (0–7) (P < 0.001). Response was achieved in 49% of patients. There was also a reduction in glucocorticoid use to a median (IQR) dose of 7.5 mg (5–12 mg) at 6 months (P < 0.001). Serious infections occurred in 26 (10%) patients, being more frequent in the first 3 months post-RTX therapy. A higher proportion of early infections were non-respiratory (odds ratio = 1.98, 95% CI: 0.99, 3.9; P = 0.049).\ud \ud \ud \ud Conclusion: RTX is safe and is associated with improvement in disease activity in refractory SLE patients with concomitant reductions in glucocorticoid use. Early vigilance for infection post-infusion is important to further improve treatment risks and benefits.

Background:\ud \ud The inhibitory CTLA-4 molecule is a crucial regulator of immune responses and a target for therapeutic intervention in both autoimmunity and cancer. In particular, CTLA-4 is important in controlling antigen-specific immunity, including responses to autoantigens associated with autoimmune disease. Here, we investigate cytokine responses to a range of lupus-associated autoantigens and assess whether the alternatively spliced isoform of CTLA-4, soluble CTLA-4 (sCTLA-4), contributes to immune regulation of autoantigen-specific immunity in systemic lupus erythematosus (SLE).\ud Methods:\ud \ud The cell culture supernatant production of sCTLA-4 as well as the cytokines IL-10, IFN-γ, and IL-17 from peripheral blood mononuclear cells (PBMC) from lupus patients and age- and sex-matched healthy volunteer donors were measured in response to previously identified histone and small nuclear ribonucleoprotein (snRNP) autoantigen-derived peptides (H391-105, H471-93, and U170K131-151) by ELISA. We also examined the functional contribution of sCTLA-4 to immune regulation in the context of these autoantigenic peptides following blockade of sCTLA-4 with a selective anti-sCTLA-4 monoclonal antibody, JMW-3B3.\ud Results:\ud \ud We identified responses to autoantigenic peptides, which revealed qualitative differences in cytokine (IL-10, IL-17, and IFN-γ) profiles between SLE patients and healthy donors. PBMC from healthy donors responded to each of the lupus peptides by secreting IFN-γ and IL-17, but PBMC from SLE patients produced IL-10. Although we did not observe differences in the levels of serum or PBMC culture supernatant sCTLA-4 in either cohort, blockade of sCTLA-4 in PBMC cultures responding to antigen enhanced the cytokine profiles associated with each group.\ud Conclusion:\ud \ud The results show that lupus autoantigen-derived peptides display varied immunogenicity in lupus versus healthy volunteer donors, while sCTLA-4 acts to regulate the T-cell activity independently of response profile.

Full analysis of individual patient and donor peptide response datasets used to generate the summary data presented in Fig. 3. (DOCX 495 kb)