Geospatial dashboards for intelligent multimodal traffic management

This paper presents the current status and future outlook of Traffic Management as a Service (TMaaS). TMaaS is an innovative web platform that provides a cloud-based vendor-neutral multimodal traffic management solution for small and medium-sized cities. Urban mobility data from several stakeholders and public service providers is integrated and visualized in a clean, intuitive and customizable interface for traffic operators and citizens

TMaaS, a new cloud-based, vendor-neutral multimodal traffic management solution

Traffic Management as a Service (TMaaS) is an innovative collaboration between eight public and private partner organisations, including the City of Ghent (main urban authority). This consortium has spent the past three years researching and developing a web application that provides a cloud-based, vendor-neutral multimodal traffic management solution for small and medium-sized cities. Urban mobility data from several stakeholders and public service providers are integrated and visualized in a clean, intuitive and customizable interface for traffic operators and citizens. TMaaS is a European project co-funded by the Urban Innovative Actions initiativ

How Virtual Agents Can Learn to Synchronize: an Adaptive Joint Decision-Making Model of Psychotherapy

Joint decision-making can be seen as the synchronization of actions and emotions, usually via nonverbal interaction between people while they show empathy. The aim of the current paper was (1) to develop an adaptive computational model for the type of synchrony that can occur in joint decision-making for two persons modeled as agents, and (2) to visualize the two persons by avatars as virtual agents during their decision-making. How to model joint decision-making computationally while taking into account adaptivity is rarely addressed, although such models based on psychological literature have a lot of future applications like online coaching and therapeutics. We used an adaptive network-oriented modelling approach to build an adaptive joint decision-making model in an agent-based manner and simulated multiple scenarios of such joint decision-making processes using a dedicated software environment that was implemented in MATLAB. Programming in the Unity 3D engine was done to virtualize this process as nonverbal interaction between virtual agents, their internal and external states, and the scenario. Although our adaptive joint decision model has general application areas, we have selected a therapeutic session as example scenario to visualize and interpret the example simulations

Exploring label dynamics of velocity-selective arterial spin labeling in the kidney

Purpose: Velocity-selective arterial spin labeling (VSASL) has been proposed for renal perfusion imaging to mitigate planning challenges and effects of arterial transit time (ATT) uncertainties. In VSASL, label generation may shift in the vascular tree as a function of cutoff velocity. Here, we investigate label dynamics and especially the ATT of renal VSASL and compared it with a spatially selective pulsed arterial spin labeling technique, flow alternating inversion recovery (FAIR). Methods: Arterial spin labeling data were acquired in 7 subjects, using free-breathing dual VSASL and FAIR with five postlabeling delays: 400, 800, 1200, 2000, and 2600 ms. The VSASL measurements were acquired with cutoff velocities of 5, 10, and 15 cm/s, with anterior–posterior velocity-encoding direction. Cortical perfusion-weighted signal, temporal SNR, quantified renal blood flow, and arterial transit time were reported. Results: In contrast to FAIR, renal VSASL already showed fairly high signal at the earliest postlabeling delays, for all cutoff velocities. The highest VSASL signal and temporal SNR was obtained with a cutoff velocity of 10 cm/s at postlabeling delay = 800 ms, which was earlier than for FAIR at 1200 ms. Fitted ATT on VSASL was ≤ 0 ms, indicating ATT insensitivity, which was shorter than for FAIR (189 ± 79 ms, P .05) with good correlations on subject level. Conclusion: Velocity-selective arterial spin labeling in the kidney reduces ATT sensitivity compared with the recommended pulsed arterial spin labeling method, as well as if cutoff velocity is increased to reduce spurious labeling due to motion. Thus, VSASL has potential as a method for time-efficient, single-time-point, free-breathing renal perfusion measurements, despite lower tSNR than FAIR

Risk factors for Coronavirus disease 2019 (Covid-19) death in a population cohort study from the Western Cape province, South Africa

Risk factors for coronavirus disease 2019 (COVID-19) death in sub-Saharan Africa and the effects of human immunodeficiency virus (HIV) and tuberculosis on COVID-19 outcomes are unknown. We conducted a population cohort study using linked data from adults attending public-sector health facilities in the Western Cape, South Africa. We used Cox proportional hazards models, adjusted for age, sex, location, and comorbidities, to examine the associations between HIV, tuberculosis, and COVID-19 death from 1 March to 9 June 2020 among (1) public-sector “active patients” (≥1 visit in the 3 years before March 2020); (2) laboratory-diagnosed COVID-19 cases; and (3) hospitalized COVID-19 cases. We calculated the standardized mortality ratio (SMR) for COVID-19, comparing adults living with and without HIV using modeled population estimates.Among 3 460 932 patients (16% living with HIV), 22 308 were diagnosed with COVID-19, of whom 625 died. COVID19 death was associated with male sex, increasing age, diabetes, hypertension, and chronic kidney disease. HIV was associated with COVID-19 mortality (adjusted hazard ratio [aHR], 2.14; 95% confidence interval [CI], 1.70–2.70), with similar risks across strata of viral loads and immunosuppression. Current and previous diagnoses of tuberculosis were associated with COVID-19 death (aHR, 2.70 [95% CI, 1.81–4.04] and 1.51 [95% CI, 1.18–1.93], respectively). The SMR for COVID-19 death associated with HIV was 2.39 (95% CI, 1.96–2.86); population attributable fraction 8.5% (95% CI, 6.1–11.1)

Traffic management as a service

This paper presents Traffic Management as a Service (TMaaS), a neutral traffic management framework for urban mobility aimed at small and medium-sized cities. It accepts and connects multimodal data and services from different parties for monitoring, analysis and management and allows flexible adaptation and on-demand use of the system. TMaaS is an open urban traffic management marketplace that enables third parties to generate innovative solutions and business models and encourages citizen participation and co-creation in urban mobility. TMaaS is currently being demonstrated in real-use cases for the City of Ghent, a medium-sized city in Belgium. Selected replicator cities will be included in 2020

Traffic Management as a Service

This paper presents Traffic Management as a Service (TMaaS), a neutral traffic management framework for urban mobility aimed at small and medium-sized cities. It accepts and connects multimodal data and services from different parties for monitoring, analysis and management and allows flexible adaptation and on-demand use of the system. TMaaS is an open urban traffic management marketplace that enables third parties to generate innovative solutions and business models and encourages citizen participation and co-creation in urban mobility. TMaaS is currently being demonstrated in real-use cases for the City of Ghent, a medium-sized city in Belgium. Selected replicator cities will be included in 2020

Switching In and Out of Sync:A Controlled Adaptive Network Model of Transition Dynamics in the Effects of Interpersonal Synchrony on Affiliation

Interpersonal synchrony is associated with better interpersonal affiliation. No matter how well-affiliated people are, interruptions or transitions in synchrony rebound to occur. One might intuitively expect that transitions in synchrony negatively affect affiliation or liking. Empirical evidence, however, suggests that time periods with interruptions in synchrony may favor affiliation or liking even more than time periods without interruptions in synchrony. This paper introduces a controlled adaptive network model to explain how persons’ affiliation might benefit from transitions in synchrony over and above mean levels of synchrony. The adaptive network model was evaluated in a series of simulation experiments for two persons with a setup in which a number of scenarios were encountered in different (time) episodes. Our controlled adaptive network model may serve as a foundation for more realistic virtual agents with regard to synchrony transitions and their role in affiliation.</p