98%
921
2 minutes
20
This work aims at revealing and optimizing the mechanism, to promote the design of phosphorus-based flame retardants (PFRs) for controlling the spread of fire risk caused by the continuous spread of polymers. Herein, we synthesized about 10 nm TiO grown in situ on the surface of BP through a simple hydrothermal procedure to introduce it into epoxy (EP/BP-TiO). In the first place, EP/BP-TiO2.0 nanocomposite achieves a reduction of 58.96% and 50.35% in PHRR and THR, respectively. Secondly, the pyrolysis of BP from P to P, P and P is revealed. As a guide, P is established as a characteristic product of the analytical model for evaluating the effects in the gas phase for BP-based hybrids. Finally, this work clarifies the enhancement path for BP-TiO is optimized for the capturing of OH· and H· radicals by P(PO). Crucially, this study reveals and controls the mechanism of the BP-based hybrids at the molecular level, which is expected to provide a promising analytical model for broad market PFRs design to address the risks and challenges of casualties and ecology caused by composites fire.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.chemosphere.2022.135504 | DOI Listing |
Bariatric surgery is an effective treatment for morbid obesity, but patient outcomes differ greatly because of a variety of phenotypes, comorbidities, and postoperative adherence. In bariatric care, artificial intelligence (AI) and machine learning (ML) are becoming revolutionary tools because traditional predictive models based on BMI and demographic variables are unable to account for these complexities. To put it simply, AI is a branch of computer science that enables machines to perform tasks that typically require human intelligence.
View Article and Find Full Text PDFJ Gen Intern Med
September 2025
UCSF Benioff Homelessness and Housing Initiative, University of California, San Francisco, CA, USA.
Background: Older homeless-experienced adults are at higher risk of loneliness than general older adults. Loneliness is associated with multiple adverse health and mental health outcomes. Less is known about factors contributing to loneliness among older adults who experience homelessness.
View Article and Find Full Text PDFRen Fail
December 2025
Department of Critical Care Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, China.
This study aimed to develop a predictive model and construct a graded nomogram to estimate the risk of severe acute kidney injury (AKI) in patients without preexisting kidney dysfunction undergoing liver transplantation (LT). Patients undergoing LT between January 2022 and June 2023 were prospectively screened. Severe AKI was defined as Kidney Disease: Improving Global Outcomes stage 3.
View Article and Find Full Text PDFSci Justice
September 2025
Department of Forensic Science, People's Public Security University of China, Beijing 100038, China. Electronic address:
As a critical frontier in forensic science, the profiling of physical evidence characteristics has garnered substantial attention. This study employed gas chromatography-mass spectrometry (GC-MS) to investigate age-related differences in sebaceous fingermark fatty acid compositions. Fingermark samples from 80 volunteers were analyzed to characterize fatty acid profiles across different age groups.
View Article and Find Full Text PDFJ Safety Res
September 2025
Department of Civil Engineering, College of Engineering, Qassim University, 51452, Saudi Arabia. Electronic address:
Introduction: The recent rise in e-scooter usage has reshaped urban mobility but has also led to a significant increase in e-scooter-related injuries, raising critical safety concerns. While existing research has primarily focused on post-crash medical outcomes and general risk comparisons, substantial gaps remain in identifying specific risk factors associated with e-scooter crashes and utilizing interpretable analytical approaches.
Method: This study addresses these gaps by analyzing 2,400 e-scooter crash records from the UK STATS19 database using advanced machine learning models to predict injury severity.