In this study, fog simulations were conducted using the Fifth-Generation NCAR/Penn State Mesoscale Model (MM5) in and around the Yodo River Basin, Japan. The purpose is to investigate the MM5 performance of fog simulation for long-term periods. The simulations were performed for January, February, March, and July, 2005 with a coarse 3-km and a nested fine 1-km grid domains. Results of the simulations were compared with data from ten meteorological observatories, fog sampling site in Mt. Rokko, and visibility measurement sites along the Second Meishin Expressway. At the meteorological observatories, the MM5 predictions agreed well with the observed temperature and specific humidity. In the Mt. Rokko region, MM5 generally reproduced the occurrence of relatively thick fog events but tended to overestimate liquid water content (LWC) of fog (by factors of 2.2-3.3 in terms of monthly mean LWC). In the Second Meishin Expressway region, while MM5 identified the specific sites at which fog either frequently or seldom occurs, the model underestimated the monthly fog frequencies by factors of more than 1.5. Overall, MM5 reproduced the general trend of fog events, and the model performance may be improved by using more adequate land surface data and suitable physics options for our study.
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http://dx.doi.org/10.1016/s1001-0742(08)62135-x | DOI Listing |
Cureus
December 2024
Trauma and Orthopedics, Lister Hospital, Stevenage, GBR.
Introduction The internet age has broadened the horizons of modern medicine, and the ever-increasing scope of artificial intelligence (AI) has made information about healthcare, common pathologies, and available treatment options much more accessible to the wider population. Patient autonomy relies on clear, accurate, and user-friendly information to give informed consent to an intervention. Our paper aims to outline the quality, readability, and accuracy of readily available information produced by AI relating to common foot and ankle procedures.
View Article and Find Full Text PDFJ Med Syst
January 2025
Department of Ophthalmology, The First Affiliated Hospital of Nanyang Medical College, Nanyang, China.
With the rise of AI platforms, patients increasingly use them for information, relying on advanced language models like ChatGPT for answers and advice. However, the effectiveness of ChatGPT in educating thyroid cancer patients remains unclear. We designed 50 questions covering key areas of thyroid cancer management and generated corresponding responses under four different prompt strategies.
View Article and Find Full Text PDFContraception
January 2025
Collaborative for Reproductive Equity, Department of Obstetrics and Gynecology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, 1300 University Avenue, Medical Sciences Center 4245 Madison, WI 53706 USA. Electronic address:
In 2022, the United States' Supreme Court ruling in Dobbs v. Jackson Women's Health Organization overturned Roe v. Wade and federal protections for abortion.
View Article and Find Full Text PDFJ Hazard Mater
January 2025
Center for Disease Control and Prevention of People's Liberation Army, Beijing 100071, China.
Peracetic acid (PAA) is an emerging disinfectant known to be highly effective against various microorganisms. However, the capability of PAA to eliminate spores under different conditions and its application in liquid and gaseous forms remain unclear. Here, we aimed to develop a stabilized single-composite PAA and evaluate its disinfection efficacy in both liquid and gaseous form against suspended or surface-coated spores under varying temperature and humidity conditions.
View Article and Find Full Text PDFWorld Psychiatry
February 2025
Department of Psychiatry, University of Campania "L. Vanvitelli", Naples, Italy.
This is the first bottom-up review of the lived experience of postpartum depression and psychosis in women. The study has been co-designed, co-conducted and co-written by experts by experience and academics, drawing on first-person accounts within and outside the medical field. The material initially identified was shared with all participants in a cloud-based system, discussed across the research team, and enriched by phenomenological insights.
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