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Vat photopolymerization (VPP) is an additive manufacturing method that requires the design of photocurable resins to act as feedstock and binder for the printing of parts, both monolithic and composite. The design of a suitable photoresin is costly and time-consuming. The development of one formulation requires the consumption of kilograms of costly materials, weeks of printing and performance testing, as well as the need to have developers with the expertise and knowledge of the materials used, making the development process cost thousands.
View Article and Find Full Text PDFParametric Studies of Polyacrylamide Adsorption on Calcite Using Molecular Dynamics Simulation.
Molecules
January 2025
Department of Chemical Engineering, Imperial College London, London SW7 2AZ, UK.
This study investigates the efficacy of polyacrylamide-based polymers, specifically hydrolysed polyacrylamide (HPAM), in reducing solids production within carbonate reservoirs. Building on our earlier simulation approach, molecular simulations were conducted to examine how these polymers adsorb onto calcite, the main mineral found in carbonate formations. The adsorption process was affected by several factors, including polymer molecular weight, charge density, temperature, and salinity.
View Article and Find Full Text PDFMice with 16p11.2 Deletion and Duplication Show Alterations in Biological Processes Associated with White Matter.
Int J Mol Sci
January 2025
Neuroscience and Mental Health Innovation Institute, Cardiff University, Hadyn Ellis Building, Cardiff CF24 4HQ, UK.
Deletion and duplication in the human 16p11.2 chromosomal region are closely linked to neurodevelopmental disorders, specifically autism spectrum disorder. Data from neuroimaging studies suggest white matter microstructure aberrations across these conditions.
View Article and Find Full Text PDFExplainable AI in Diagnostic Radiology for Neurological Disorders: A Systematic Review, and What Doctors Think About It.
Diagnostics (Basel)
January 2025
Aerospace Engineering Department and Interdisciplinary Research Center for Smart Mobility and Logistics, and Interdisciplinary Research Center Aviation and Space Exploration, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia.
Artificial intelligence (AI) has recently made unprecedented contributions in every walk of life, but it has not been able to work its way into diagnostic medicine and standard clinical practice yet. Although data scientists, researchers, and medical experts have been working in the direction of designing and developing computer aided diagnosis (CAD) tools to serve as assistants to doctors, their large-scale adoption and integration into the healthcare system still seems far-fetched. Diagnostic radiology is no exception.
View Article and Find Full Text PDFSymbolic regression for strength prediction of eccentrically loaded concrete-filled steel tubular columns.
Sci Rep
January 2025
Department of Structural Engineering, Mansoura University, PO BOX 35516, Mansoura, Egypt.
Concrete-filled steel tube (CFST) columns are widely employed in high-rise buildings, long-span bridges, and seismic-resistant structures due to their superior load-bearing capacity, structural efficiency, and resilience under extreme loading conditions. This study uses symbolic regression with structural design code provisions to predict the eccentric strength of concrete filled-steel tubular columns with circular shape (CCFST) and rectangular shape (RCFST). Previous studies have used two distinct approaches for estimating eccentric strength: explainable models based on theoretical derivations and black-box models derived from machine learning (ML) methods.
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