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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).

Although past studies have identified predictors related to child injuries with developmental disorders, national-level research in Asia is limited. The objective of this study was to explore the risk factors for child injuries with developmental disorders in Taiwan using a national-level integrated database for the period between 2004–2015 (The Maternal and Child Health Database, National Health Insurance Research Database, Census Registry, and Indigenous Household Registration). Children younger than 12 years old who had records of visiting the ER or being hospitalized due to injury or without injury were included in this study. A 1:1 nested case-control study (injury vs. noninjury) to examine the risk factors for child injury with developmental disorder was performed. A total of 2,167,930 children were enrolled. The risk factors were associated with repeated ER visits or hospitalization: being indigenous (adjusted odds ratio [AOR]: 1.51; CI: 1.45–1.57); having a developmental disorder (AOR: 1.74; CI: 1.70–1.78); and having parents with illicit drug use (AOR: 1.48; CI: 1.32–1.66), alcohol abuse (AOR: 1.21; CI: 1.07–1.37), or a history of mental illness (AOR: 1.43; CI: 1.41–1.46). Being indigenous, having developmental disorders, and having parents with history of illicit drug use, alcohol abuse, or mental illness were predictors related to injuries in children.

The transverse momentum distribution of charged particles formed in AuAu collisions at Beam Energy Scan (BES) ($\sqrt{S_{NN}}=$ 7.7, 11.5, 19.6, 27, 39 $\hspace{0.05cm} GeV$) is investigated. In addition, $ P_{T}$ spectra of $\Lambda$ particle at $\sqrt{S_{NN}}$=62.4 $\hspace{0.03cm} GeV$ was examined. Tsallis distribution is used to extract the temperature, volume and the entropic index from the experimental results at mid-rapidity and zero chemical potential. We measure some particle ratios like $ \frac{k^{+}}{\pi^{+}} $ and $ \frac{\Lambda}{\pi^{-}} $ which are puzzling horn in the experiment and in the thermal model. We conclude that the horn vanished when we used Tsallis distribution, but this does not confirm a solution to the puzzle, which is primarily visible in the experimental results.

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.

Objectives: Over half of pedestrians killed and seriously injured in Great Britain in 2015 were involved in crashes at junctions. This study investigates the nature of these crashes.Methods: A study was conducted into pedestrian casualty crashes at priority controlled junctions, roundabouts and signalised junctions in England between 2005 and 2015 using information from the UK STATS19 accident database, the UK National Travel Survey and the UK National Census. Consideration was given to coding frequencies of contributory factors, exposure (in terms of miles walked or driven) as well as age, gender and the resident deprivation index of the road users involved.Results and Conclusions: In terms of indicative blame, the coding frequencies of subjectively determined pedestrian actions and behaviour factors which might have contributed to pedestrian casualty crashes were found to be between 1.6 and 2.8 times the frequencies of driver actions and behavioural factors. Substantial social gradients were found in pedestrian casualty rates per miles walked and in the driver involvement rates per mile driven with those from the most deprived quintile having higher rates. In addition, it was found that female pedestrians, aged 60 years and over, had higher pedestrian casualty rates, per billion miles walked, for all three junction types, when compared with males and females under the age of 60 years, apart from male pedestrians aged 16 years and younger at priority controlled junctions.

This paper examines pedestrian anatomical injuries and crash characteristics in back-to-traffic and facing-traffic crashes. Pedestrian crashes involving pedestrians walking along streets (i.e. with their backs to traffic or facing traffic) have been overlooked in literature. Although this is not the most frequent type of crash, the crash consequence to pedestrians is a safety concern. Combining Taiwan A1A2 police-reported accident data and data from the National Health Insurance Database from years 2003–2013, this paper examines anatomical injuries and crash characteristics in back-to-traffic and facing-traffic crashes. There were a total of 830 and 2267 pedestrian casualties in back-to-traffic and facing-traffic crashes respectively. The injuries sustained by pedestrians and crash characteristics of these two crash types were compared with those of other crossing types of crashes (nearside crash, nearside dart-out crash, offside crash, and offside dart-out crash). Odds of various injuries to body regions were estimated using logistic regressions. Key findings include that the percentage of fatalities in back-to-traffic crashes is the highest; logistic models reveal that pedestrians in back-to-traffic crashes sustained more head, neck, and spinal injuries than did pedestrians in other crash types, and unlit darkness and non-built-up roadways were associated with an increased risk of pedestrian head injuries. Several crash features (e.g. unlit darkness, overtaking manoeuvres, phone use by pedestrians and drivers, and intoxicated drivers) are more frequently evident in back-to-traffic crashes than in other types of crashes. The current research suggests that in terms of crash consequence, facing traffic is safer than back to traffic.