Traditional scenic route planning only considers the shortest path, which ignores the information of scenic road conditions. As the most effective direct search method to solve the shortest path in static road network, A* algorithm can plan the optimal scenic route by comprehensively evaluating the weights of each expanded node in the gridded scenic area. However, A* algorithm has the problem of traversing more nodes and ignoring the cost of road in the route planning. In order to bring better travel experience to the travelers, the above factors are taken into account. This paper presents a path planning method based on the improved A* algorithm. Firstly, the heuristic function of the A* algorithm is weighted by exponential decay to improve the calculation efficiency of the algorithm. Secondly, in order to increase the practicality of the A* algorithm, the impact factors that road conditions is introduced to the evaluation function. Finally, the feasibility of the improved A* algorithm is verified through simulation experiments. Experimental results show that the improved A* algorithm can effectively reduce the calculation time and road cost.
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http://dx.doi.org/10.1038/s41598-022-05386-6 | DOI Listing |
JAMA Netw Open
January 2025
HealthPartners Institute, Bloomington, Minnesota.
Importance: Medication adherence is important for managing blood pressure (BP), low-density lipoprotein cholesterol (LDL-C), and hemoglobin A1c (HbA1c). Interventions to improve medication adherence are needed.
Objective: To examine the effectiveness of an intervention using algorithmic identification of low medication adherence, clinical decision support to physicians, and pharmacist outreach to patients to improve cardiometabolic medication adherence and BP, LDL-C, and HbA1c control.
Anal Bioanal Chem
January 2025
Department of Plant and Environmental Science, University of Copenhagen, Thorvaldsensvej 40, DK-1871, Frederiksberg, Denmark.
Liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) is commonly used for identification of compounds in complex samples due to the high chromatographic and mass spectral resolution provided. In subsequent data processing workflows, it is imperative to preserve this resolution to fully exploit the data. "Region of interest" (ROI) algorithms were introduced as a better alternative to equidistant binning for compressing HRMS data because they better preserve the mass spectral resolution.
View Article and Find Full Text PDFAnn Neurol
January 2025
Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY.
Objective: Isolated rapid eye movement (REM) sleep behavior disorder (iRBD) is, in most cases, an early stage of Parkinson's disease or related disorders. Diagnosis requires an overnight video-polysomnogram (vPSG), however, even for sleep experts, interpreting vPSG data is challenging. Using a 3D camera, automated analysis of movements has yielded high accuracy.
View Article and Find Full Text PDFBackground: Clinical diagnosis of frontotemporal dementia (FTD) can be challenging, requiring an accurate tool dedicated to this diagnostic hurdle. Since FTD exhibits distinct regional atrophy patterns on magnetic resonance imaging (MRI), AI-aided automated brain volume analysis could enhance the clinical diagnostic assessment of FTD, including the detection of the disease and the classification of subtypes, which encompass behavioral variant (BV), semantic variant (SV), and progressive non-fluent aphasia (PNFA). In this study, we leverage automated brain volumetry software to approach both FTD detection and the differential diagnosis among its subtypes.
View Article and Find Full Text PDFBackground: Current tools for Alzheimer's disease screening and staging used in clinical research (e.g. ACE-3, ADAS-Cog) require substantial face-to-face time with trained professionals, and may be affected by subjectivity, "white coat syndrome" and other biases.
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