Making motorcycle rides safer by advanced technology is an ongoing challenge in the context of developing driving assistant systems and safety infrastructure. Determining which section of a road and which driving behaviour is "safe" or "unsafe" is rarely possible due to the individual differences in driving experience, driving style, fitness and potentially available assistant systems. This study investigates the feasibility of a new approach to quantify motorcycle riding risk for an experimental sample of bikers by collecting motorcycle-specific dynamic data of several riders on selected road sections. Comparing clustered dynamics with the observed dynamic data at known risk spots, we provide a method to represent individual risk estimates in a single risk map for the investigated road section. This yields a map of potential risk spots, based on an aggregation of individual risk estimates. The risk map is optimized to include most of the previous accident sites, while keeping the overall area classified as risky small. As such, with data collected on a large scale, the presented methodology could guide safety inspections at the highlighted areas of a risk map and be the basis of further studies into the safety relevant differences in driving styles.
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http://dx.doi.org/10.1016/j.aap.2021.106297 | DOI Listing |
BMC Med
January 2025
Department of Public Health, Erasmus MC University Medical Center, Rotterdam, the Netherlands.
Background: Over the past decades, the prevalence of obesity among adults has rapidly increased, particularly in socioeconomically deprived urban neighbourhoods. To better understand the complex mechanisms behind this trend, we created a system map exposing the underlying system driving obesity prevalence in socioeconomically deprived urban neighbourhoods over the last three decades in the Netherlands.
Methods: We conducted Group Model Building (GMB) sessions with a group of thirteen interdisciplinary experts to develop a Causal Loop Diagram (CLD) of the obesogenic system.
J Trauma Stress
January 2025
Department of Psychology, Harvard University, Cambridge, Massachusetts, USA.
Research suggests a bidirectional association between sleep disturbances and posttraumatic stress disorder (PTSD) symptoms. However, most studies have been conducted with group-level data, which do not necessarily capture the associations between PTSD symptoms and sleep within an individual over time. This study aimed to add to the literature concerning the association between sleep and PTSD and extend these findings to investigate the effect of sleep disturbances on positive affect.
View Article and Find Full Text PDFFunct Integr Genomics
January 2025
Intelligent OMICS Limited, Nottingham, United Kingdom.
Gene‒gene interactions play pivotal roles in disease pathogenesis and are fundamental in the development of targeted therapeutics, particularly through the elucidation of oncogenic gene drivers in cancer. The systematic analysis of pathways and gene interactions is critical in the drug discovery process for various cancer subtypes. SPAG5, known for its role in spindle formation during cell division, has been identified as an oncogene in several cancers, although its specific impact on AML remains underexplored.
View Article and Find Full Text PDFSurg Today
January 2025
Department of Endocrine Surgery, Nippon Medical School Hospital, 1-1-5 Sendagi, Bunkyo-ku, Tokyo, 113-8603, Japan.
Purpose: Tumor/node/metastasis staging and prognostic index (PI) are used to predict prognosis and guide treatment for anaplastic thyroid carcinoma (ATC). With the advent of treatments, such as BRAF/MEK inhibitors and immune checkpoint inhibitors, dynamic markers to assess disease status and treatment efficacy are needed. This study examined the utility of PI as a dynamic marker for ATC treatment.
View Article and Find Full Text PDFSci Rep
January 2025
School of BioSciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, 632014, India.
The proliferation-specific oncogenic transcription factor, FOXM1 is overexpressed in primary and recurrent breast tumors across all breast cancer (BC) subtypes. Intriguingly, FOXM1 overexpression was found to be highest in Triple-negative breast cancer (TNBC), the most aggressive BC with the worst prognosis. However, FOXM1-mediated TNBC pathogenesis is not completely elucidated.
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