Mean sensitivity (MS) of tree ring is a key index representing the sensitivity of tree rings to climate. Understanding the variation of MS and its influencing factors at a large area is helpful to understand the interaction between tree growth and climate. We used 573 tree-ring width chronologies in Asia from the International Tree Ring Date Bank (ITRDB) to examine the variation of tree-ring sensitivity and potential influencing factors. The results showed that the MS of trees was high in the arid regions and cold regions. Precipitation was more important than temperature in diriving MS. Consistent with the pattern of up-down-up for precipitation, MS showed a down-up-down fluctuation with increasing altitude, indicating that precipitation affected by altitude was a key climate factor for the MS. MS had great difference due to different physiological traits among tree species. Light-adapted species, such as Juniperus przewalskii and Pinus gerardiana, had high MS due to drought tole-rance. Shade-adapted species, such as Picea and Abies, had low MS. Old trees may have high MS.
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http://dx.doi.org/10.13287/j.1001-9332.201903.003 | DOI Listing |
Int J Med Inform
March 2025
Department of Military Health Statistics, Naval Medical University, Shanghai, China. Electronic address:
Background: Timely and accurate outcome prediction is essential for clinical decision-making for ischemic stroke patients in the intensive care unit (ICU). However, the interpretation and translation of predictive models into clinical applications are equally crucial. This study aims to develop an interpretable machine learning (IML) model that effectively predicts in-hospital mortality for ischemic stroke patients.
View Article and Find Full Text PDFPLoS One
March 2025
Medical Physics and Radiation Sciences Program, School of Physics, Universiti Sains MalaysiaPenang, Malaysia.
In this research, nineteen (19) samples were collected and analyzed with the following objectives: to evaluate the activity concentration of radionuclides, assess gamma absorption, determine indoor radon concentration, and evaluate the public health impact of building materials used in Katsina State, Nigeria. The study aimed to provide critical data that would inform safe construction practices and regulatory compliance. Samples were sourced locally from various quarry sites, while materials such as cement, paint, tiles, and ceiling materials were purchased from local markets.
View Article and Find Full Text PDFPhytopathology
March 2025
Michigan State University, Dept. Plant, Soil and Microbial Sciences, 105 CIPS, East Lansing, Michigan, United States, 48910;
Oak wilt, caused by the fungal pathogen , spreads via root grafts and insect vectors, threating oaks ( spp.) and chestnuts ( spp.) in the United States.
View Article and Find Full Text PDFFront Artif Intell
February 2025
Department of Surgery, College of Medicine and Health Science, University of Gondar, Gondar, Ethiopia.
Heart disease is a leading cause of mortality worldwide, making accurate early detection essential for effective treatment and management. This study introduces a novel hybrid machine-learning approach that combines transfer learning using the VGG16 convolutional neural network (CNN) with various machine-learning classifiers for heart disease detection. A conditional tabular generative adversarial network (CTGAN) was employed to generate synthetic data samples from actual datasets; these were evaluated using statistical metrics, correlation analysis, and domain expert assessments to ensure the quality of the synthetic datasets.
View Article and Find Full Text PDFBMC Med
March 2025
Health Economics and Policy Evaluation Research (HEPER) Group, Centre for Medicine Use and Safety, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Melbourne, Australia.
Background: Long-term cost-effectiveness analyses of health behaviour interventions to effectively manage type 2 diabetes mellitus (T2DM) in low-income countries are crucial for minimising economic burden and optimising resource allocation. Therefore, this study aimed to estimate the long-term cost-effectiveness of implementing a health behaviour intervention to manage T2DM in Nepal.
Methods: A Markov model in combination with a decision tree was developed to compare the costs and outcomes of the health behaviour intervention against usual care among 481 (238-intervention and 243-control) participants from healthcare system and societal perspectives.
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