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Non-linear relationship between built environment and non-motorized travel efficiency under the traffic micro-circulation model.
PLoS One
January 2025
School of Architecture and Urban Planning, Lanzhou Jiaotong University, Gansu, Lanzhou, China.
The built environment is an important determinant of travel demand and mode choice. Studying the relationship between the built environment and transportation usage can support and assist traffic policy interventions. Previous studies often assumed that this relationship is linear; however, the impact of the built environment on non-motorized travel efficiency may be more complex than the typically modeled linear relationships.
View Article and Find Full Text PDFThe effect of pregnancy vitamin D supplementation on maternal blood pressure: real-world data analysis within the MAVIDOS randomised placebo-controlled trial.
Arch Gynecol Obstet
January 2025
MRC Lifecourse Epidemiology Centre, University of Southampton, Southampton General Hospital, Tremona Road, Southampton, SO16 6YD, UK.
Purpose: Observational studies have suggested negative associations between maternal 25-hydroxyvitamin D (25(OH)D) status and risk of hypertensive disorders of pregnancy [pregnancy-induced hypertension (PIH) and preeclampsia (PET)]. Data from intervention studies are limited. We hypothesised that vitamin D supplementation would lower maternal blood pressure (BP) during pregnancy and reduce the incidence of hypertensive disorders of pregnancy.
View Article and Find Full Text PDFRisk quantification based Adaptive Cruise control and its application in approaching behavior at signalized intersections.
Accid Anal Prev
January 2025
School of Transportation, Southeast University, Nanjing, Jiangsu Province 211189, PR China; Institute on Internet of Mobility, Southeast University and University of Wisconsin-Madison, Southeast University, Nanjing, Jiangsu Province 211189, PR China.
Traffic signals, while reducing conflicts within intersections, often lead to stop-and-go behaviors in approaching vehicles, negatively impacting traffic flow in terms of safety, efficiency, and fuel consumption. Aimed at minimizing the traffic oscillations caused by traffic signals through Connected and Autonomous Vehicles (CAVs) and meeting real-time operational needs, this paper proposes a Risk-Based Adaptive Cruise Control (RACC). RACC designs the constraints of approaching a signalized intersection as expected risks, enabling compliance with all constraints while being adaptable to basic road scenarios.
View Article and Find Full Text PDFAddressing residual and recurrent aneurysms post-Woven EndoBridge device embolization: a systematic review and meta-analysis.
J Neurointerv Surg
January 2025
Department of Neurosurgery, University at Buffalo Jacobs School of Medicine and Biomedical Sciences, Buffalo, New York, USA
Background: Early literature on the Woven EndoBridge (WEB) device reported 80-90% adequate aneurysm occlusion but low complete occlusion (40-55%). It is uncertain whether residual or recurrent aneurysms require re-treatment to prevent future rupture.
Objective: To systematically review the literature to meta-analyze occlusion and complication rates after re-treatment of these aneurysms.
PSMA PET/CT based multimodal deep learning model for accurate prediction of pelvic lymph-node metastases in prostate cancer patients identified as candidates for extended pelvic lymph node dissection by preoperative nomograms.
Eur J Nucl Med Mol Imaging
January 2025
Department of Nuclear Medicine, Xiangya Hospital, Central South University, No. 87 Xiangya Road, Changsha, Hunan, 410008, P.R. China.
Purpose: To develop and validate a prostate-specific membrane antigen (PSMA) PET/CT based multimodal deep learning model for predicting pathological lymph node invasion (LNI) in prostate cancer (PCa) patients identified as candidates for extended pelvic lymph node dissection (ePLND) by preoperative nomograms.
Methods: [Ga]Ga-PSMA-617 PET/CT scan of 116 eligible PCa patients (82 in the training cohort and 34 in the test cohort) who underwent radical prostatectomy with ePLND were analyzed in our study. The Med3D deep learning network was utilized to extract discriminative features from the entire prostate volume of interest on the PET/CT images.
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