The cool-season (May to October) rainfall decline in southwestern Australia deepened during 2001-2020 to become 20.5% less than the 1901-1960 reference period average, with a complete absence of very wet years (i.e., rainfall > 90th percentile). CMIP5 and CMIP6 climate model simulations suggest that approximately 43% of the observed multi-decadal decline was externally-forced. However, the observed 20-year rainfall anomaly in 2001-2020 is outside the range of both preindustrial control and historical simulations of almost all climate models used in this study. This, and the fact that the models generally appear to simulate realistic levels of decadal variability, suggests that 43% might be an underestimate. A large ensemble from one model exhibits drying similar to the observations in 10% of simulations and suggests that the external forcing contribution is indeed larger (66%). The majority of models project further drying over the twenty-first century, even under strong cuts to greenhouse gas emissions. Under the two warmest scenarios, over 70% of the late twenty-first century years are projected to be drier than the driest year simulated during the 1901-1960 period. Our results suggest that few, if any, very wet years will occur during 2023-2100, even if strong cuts to global emissions are made.
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http://dx.doi.org/10.1038/s41598-023-48877-w | DOI Listing |
ACS Appl Mater Interfaces
January 2025
School of Precision Instrument and Optoelectronics Engineering, Tianjin University, 92 Weijin Road, Tianjin 300072, China.
Traditional tactile sensors are single-function, and it is difficult to meet the needs of applications in complex environments. This paper describes the development and applications of flexible tactile sensors with cilia based on magnetoelectric composites made of neodymium iron boron (NdFeB) microparticles with a silver (Ag) nanoshell in polydimethylsiloxane (PDMS). These sensors adopt the inherent magnetism of NdFeB microparticles and the excellent conductivity of the Ag coating.
View Article and Find Full Text PDFBMC Oral Health
January 2025
Faculty of Dentistry, Department of Endodontics, Ondokuz Mayis University, Samsun, Kurupelit, 55139, Turkey.
Background: The aim was to evaluate the stresses in teeth, with external root resorption (ERR) restored with different materials using finite element analysis (FEA).
Methods: In this study, a Micro-CT scan was conducted on a prepared maxillary central tooth. DICOM-compatible images obtained from the sections were converted into stereolithography format using Ctan software.
J Environ Manage
January 2025
School of Economy and Management, Shandong Agricultural University, Taian, 271018, PR China. Electronic address:
Agricultural products are essential for nutrition and food security, particularly in China where agricultural production capacity is growing steadily. Despite the benefits of Ecological Agricultural (EA) products, including environmental protection and enhanced consumer utility, their widespread adoption and maximization of value are impeded by various factors. This study explores the intricate tripartite relationship - government, agribusiness, and consumer, in the value realization of EA products in China by establishing an evolutionary game model.
View Article and Find Full Text PDFAm J Transl Res
December 2024
School of Physical Education, Nanchang University Nanchang, Jiangxi, China.
Objective: To investigate the protective effects of ankle braces in patients with functional ankle instability.
Methods: This retrospective study involved 30 participants recruited from January 2023 to December 2023 at School of Physical Education, Nanchang University. These participants were divided into an ankle brace group wearing braces and a control group without braces.
Cureus
January 2025
General Practice, Wad Medani Hospital, Wad Medani, SDN.
To enhance patient outcomes in pediatric cancer, a better understanding of the medical and biological risk variables is required. With the growing amount of data accessible to research in pediatric cancer, machine learning (ML) is a form of algorithmic inference from sophisticated statistical techniques. In addition to highlighting developments and prospects in the field, the objective of this systematic study was to methodically describe the state of ML in pediatric oncology.
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