The number of data sources and models in the mobility and transport domain strongly proliferated in the last decade. Most formats have been created to enable specific and innovative applications. On the other hand, the available data models present a certain degree of complexity in terms of their integration and management due to partial overlaps, and in most cases, they could be exploited alternatively to implement the same smart and latest innovative solutions. This paper offers an overview of data models, standards and their relationships. A second contribution highlights any possible exploitation of data models for implementing operational processes for city transportation management and for the feeding of simulation and optimization processes that produce other data results in other data models. The final goal in most cases is the monitoring and control of city transport conditions, as well as the tactic and strategic planning of city infrastructure. This work was developed in the context of the CN MOST, a national center of sustainable mobility in Italy, and it is based on exploiting the Snap4City platform.
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http://dx.doi.org/10.3390/s24020441 | DOI Listing |
Ecotoxicol Environ Saf
January 2025
West China Center of Excellence for Pancreatitis, Institute of Integrated Traditional Chinese and Western Medicine, West China Hospital, Sichuan University, Chengdu 610041, China; Regenerative Medicine Research Center, Sichuan University West China Hospital, Chengdu, Sichuan 610041, China. Electronic address:
Dichlorvos (DDVP) is an organophosphorus pesticide commonly utilized in agricultural production. Recent epidemiological studies suggest that exposure to DDVP correlates with an increased incidence of liver disease. However, data regarding the hepatotoxicity of DDVP remain limited.
View Article and Find Full Text PDFComput Med Imaging Graph
January 2025
CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China; National Key Laboratory of Kidney Diseases, Beijing 100853, China. Electronic address:
In clinical optical molecular imaging, the need for real-time high frame rates and low excitation doses to ensure patient safety inherently increases susceptibility to detection noise. Faced with the challenge of image degradation caused by severe noise, image denoising is essential for mitigating the trade-off between acquisition cost and image quality. However, prevailing deep learning methods exhibit uncontrollable and suboptimal performance with limited interpretability, primarily due to neglecting underlying physical model and frequency information.
View Article and Find Full Text PDFObjective: The oxidative balance score (OBS) has emerged as a novel marker for assessing oxidative stress status. This study aimed to investigate the association of OBS with systolic blood pressure (SBP), diastolic blood pressure (DBP), all-cause, and cardiovascular disease mortality in hypertensive patients.
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JMIR Res Protoc
January 2025
Université de Sherbrooke, Sherbrooke, QC, Canada.
Background: The centralization of decision-making power in the public health care system has a negative impact on the practice of professionals and the quality of home care services (HCS) for seniors. To improve HCS, decentralized management could be a particularly promising approach. To be effective, strategies designed to incorporate this management approach require attention to 3 elements: autonomy of local stakeholders, individual and organizational capacities, and accountability for actions and decisions.
View Article and Find Full Text PDFJ Neurosurg
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1Department of Neurosurgery, St. Olav's University Hospital, Trondheim, Norway.
Objective: The extent of resection (EOR) and postoperative residual tumor (RT) volume are prognostic factors in glioblastoma. Calculations of EOR and RT rely on accurate tumor segmentations. Raidionics is an open-access software that enables automatic segmentation of preoperative and early postoperative glioblastoma using pretrained deep learning models.
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