DMD: A Large-Scale Multi-Modal Driver Monitoring Dataset for Attention and Alertness Analysis

Vision is the richest and most cost-effective technology for Driver Monitoring Systems (DMS), especially after the recent success of Deep Learning (DL) methods. The lack of sufficiently large and comprehensive datasets is currently a bottleneck for the progress of DMS development, crucial for the transition of automated driving from SAE Level-2 to SAE Level-3. In this paper, we introduce the Driver Monitoring Dataset (DMD), an extensive dataset which includes real and simulated driving scenarios: distraction, gaze allocation, drowsiness, hands-wheel interaction and context data, in 41 hours of RGB, depth and IR videos from 3 cameras capturing face, body and hands of 37 drivers. A comparison with existing similar datasets is included, which shows the DMD is more extensive, diverse, and multi-purpose. The usage of the DMD is illustrated by extracting a subset of it, the dBehaviourMD dataset, containing 13 distraction activities, prepared to be used in DL training processes. Furthermore, we propose a robust and real-time driver behaviour recognition system targeting a real-world application that can run on cost-efficient CPU-only platforms, based on the dBehaviourMD. Its performance is evaluated with different types of fusion strategies, which all reach enhanced accuracy still providing real-time response.Comment: Accepted to ECCV 2020 workshop - Assistive Computer Vision and Robotic

Lessons learned — resolving the enigma of genetic factors in IBS

IBS is the most prevalent functional gastrointestinal disorder and phenotypically characterized by chronic abdominal discomfort, pain and altered defecation patterns. The pathophysiology of IBS is multifactorial, albeit with a substantial genetic component. To date, studies using various methodologies, ranging from family and twin studies to candidate gene approaches and genome-wide association studies, have identified several genetic variants in the context of IBS. Yet, despite enlarged sample sizes, increased statistical power and meta-analyses in the past 7 years, positive associations are still scarce and/or have not been reproduced. In addition, epigenetic and pharmacogenetic approaches remain in their infancy. A major hurdle is the lack of large homogenized case-control cohorts recruited according to standardized and harmonized criteria. The COST Action BM1106 GENIEUR (GENes in Irritable Bowel Syndrome Research Network EURope) has been established to address these obstacles. In this Review, the (epi)genetic working group of GENIEUR reports on the current state-of-the-art in the field, highlights fundamental flaws and pitfalls in current IBS (epi) genetic research and provides a vision on how to address and improve (epi) genetic approaches in this complex disorder in the future.Peer-reviewed manuscript: [https://imagine.imgge.bg.ac.rs/handle/123456789/1625

The Impact of Prenatal Exposure to Dexamethasone on Gastrointestinal Function in Rats

Antenatal treatment with synthetic glucocorticoids is commonly used in pregnant women at risk of preterm delivery to accelerate tissue maturation. Exposure to glucocorticoids during development has been hypothesized to underlie different functional gastrointestinal (GI) and motility disorders. Herein, we investigated the impact of in utero exposure to synthetic glucocorticoids (iuGC) on GI function of adult rats. Wistar male rats, born from pregnant dams treated with dexamethasone (DEX), were studied at different ages. Length, histologic analysis, proliferation and apoptosis assays, GI transit, permeability and serotonin (5-HT) content of GI tract were measured. iuGC treatment decreased small intestine size and decreased gut transit. However, iuGC had no impact on intestinal permeability. iuGC differentially impacts the structure and function of the GI tract, which leads to long-lasting alterations in the small intestine that may predispose subjects prone to disorders of the GI tract.PortugueseFoundation for Science and Technology (FCT) forproviding a fellowship to Fátima Ramalhosa (SFRH/BD/52058/2012) and Carina Soares-Cunha (SFRH/BD/51992/201