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This document reports the results of the different computational analyses performed on the data collected in the project. After a brief introduction, the document includes several sections devoted to different kinds of analysis. In each section, we have first an introduction on the objectives of the analysis presented in the context of the Diamond project, then it offers a description of the methodology, and the presentation of the results obtained, organized by use case. Finally, a last section is devoted to discussion and general conclusions. The computational methods employed for the data analysis include: Analysis of structured open data to define indicators that characterize the area surrounding each urban railway station (use case I) or docking station (Use case III) along socio-demographic, territory and mobility aspects, and to select relevant stations for the subsequent steps of the analysis (Section 2). Analysis of observations, to characterize the selected urban railways infrastructures (Use case I) and docking stations (Use case III) (Section 3). Analysis of experimental sessions in a simulator laboratory setting, to validate the impact of autonomous vehicles driving experience and passengers’ emotional appraisal, considering gender and other relevant intersectional variables (Use case II), combined with the analysis of user satisfaction surveys for Use case II (Section 4). Analysis of social media data collected from Twitter, to get insights on the concerns of men and women regarding topics related to Use case I, II and III (Section 5) Analysis of user satisfaction surveys on service provisions (Use cases I and III) and employment conditions (Use case IV), exploring and assessing differences in user satisfaction according to their socio-demographic characteristics, by means of statistical tests, regression analysis, factor analysis (Section 6). Analysis of users and employees' priorities from Dynamic Augmentative Delphi surveys, employing Analytic Hierarchy Processes to assess the ranking between priorities for different groups of respondents (Section 7). Bayesian network analysis to obtain a weighted hierarchy of fairness characteristics, based on open and proprietary structured data, observations and UESI questionnaires, and a statistical assessment of significant differences between users along socio-demographic variables (Section 8). While the document is structured along the different kinds of analysis performed, the final conclusions present a summary of the main results, organized per use case (Section 9).

OBJECTIVE: To elucidate the clinical values of anti-M3R in Sjögren’s syndrome (SS) in the largest cohort for an anti-M3R study. METHODS: The plasma of 361 subjects (156 primary-SS[pSS], 62 non-SS-sicca[SICCA], 40 systemic lupus erythematosus [SLE], 50 rheumatoid arthritis[RA], and 53 healthy controls[HC]) was screened using our modified On-Cell-Western assay. Saliva from pSS (n=37) compared to SICCA (n=26) was also analyzed. The sensitivity/specificity of anti-M3R and its association with comprehensive clinical/laboratory features were determined. RESULTS: Plasma-anti-M3R was higher in pSS compared to other groups, differentiating pSS with good-to-excellent diagnostic power with a specificity of 85% and a sensitivity between 75% and 98%. pSS plasma-anti-M3R was positively correlated with ocular staining scores, anti-Ro/SSA, IgG, β2-microglobulin, ESR, and ESSDAI. It was negatively correlated with WBC, C4, and salivary scintigraphic indices. Saliva-anti-M3R was 3.59 times higher in pSS than in SICCA. Interestingly, the positivity of plasma-anti-M3R with or without anti-Ro/SSA was higher in those who did not undergo a lip biopsy than in individuals with a biopsy (100% vs. 88.6%, p=0.013, and 90.6% vs. 75%, p=0.023, respectively). The agreement between the 2002 American-European-Consensus-Group criteria and the criteria substituted with plasma-anti-M3R for the lip biopsy reached 92% with a significant kappa of 0.824. CONCLUSION: Anti-M3R enhances sensitivity and specificity for SS diagnosis, correlating with ocular dryness and glandular hypofunction, and the hematological/biological domains of the ESSDAI. Our findings also underscore anti-M3R in SS diagnosis, where clinical assessments by multi-disciplinary specialists, such as lip biopsy, sialometry, or ocular evaluation, are limited.

At non-signalized marked crosswalks, pedestrian priority is neither well-defined nor well acknowledged by drivers. This paper presents the findings of an investigation on both driver and pedestrian behavior at non-signalized marked crosswalks located on channelized right-turn lanes at intersections in the State of Qatar. Five crosswalks in Doha city were video recorded from discrete locations on a typical working day. The results from the data analysis of 1620 pedestrians&rsquo, behavior indicated that waiting behavior, gap acceptance, and crossing speed are complex phenomena and depend upon both pedestrians&rsquo, characteristics as well as their crossing characteristics. The drivers&rsquo, yielding behavior was mainly linked to pedestrians&rsquo, gender and adjacent land use. Low driver yielding rates indicated that significant improvements are required to enhance pedestrian safety. Among pedestrian attributes, gender had the most significant effect on crossing behavior followed by distractions, crossing in a group or alone, and dressing style. Findings of this research will be useful for planners when designing crosswalks at new intersections and during simulations of pedestrian and driver behavior at marked crosswalks on exclusive right-turn lanes. The results of this study will also be directly applicable to the Arabian Gulf countries as they exhibit similar conditions as the State of Qatar.