Calcifications are products of mineralization whose presence is usually associated with pathological conditions. The minerals mostly seen in several diseases are calcium oxalate (CaCO), calcium carbonate (CaCO) and hydroxyapatite (HAp). Up to date, there is no in vivo method that could discriminate between minerals. To this aim, a dual energy x-ray method was developed in the present study. An analytical model was implemented for the determination of the Calcium/Phosphorus mass ratio ([Formula: see text]). The simulation was carried out using monoenergetic and polyenergetic x-rays and various calcification thicknesses (100-1000 [Formula: see text]) and types (CaCO, CaCO, HAp). The experimental evaluation of the method was performed using the optimized irradiation conditions obtained from the simulation study. X-ray tubes, combined with energy dispersive and energy integrating (imaging) detectors, were used for the determination of the [Formula: see text] in phantoms of different mineral types and thicknesses. Based on the results of the experimental procedure, statistical significant difference was observed between the different types of minerals when calcification thicknesses were 300 [Formula: see text] or higher.
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http://dx.doi.org/10.1088/1361-6560/aa8445 | DOI Listing |
J Virol
January 2025
SA MRC Antibody Immunity Research Unit, School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Parktown, Johannesburg, South Africa.
The Antibody Mediated Prevention (AMP) trials showed that passively infused VRC01, a broadly neutralizing antibody (bNAb) targeting the CD4 binding site (CD4bs) on the HIV-1 envelope protein (Env), protected against neutralization-sensitive viruses. We identified six individuals from the VRC01 treatment arm with multi-lineage breakthrough HIV-1 infections from HVTN703, where one variant was sensitive to VRC01 (IC < 25 ug/mL) but another was resistant. By comparing Env sequences of resistant and sensitive clones from each participant, we identified sites predicted to affect VRC01 neutralization and assessed the effect of their reversion in the VRC01-resistant clone on neutralization sensitivity.
View Article and Find Full Text PDFPhilos Trans A Math Phys Eng Sci
January 2025
Microsystems Group, School of Engineering, Newcastle University, Newcastle upon Tyne NE1 7RU, UK.
The increasing demand for processing large volumes of data for machine learning (ML) models has pushed data bandwidth requirements beyond the capability of traditional von Neumann architecture. In-memory computing (IMC) has recently emerged as a promising solution to address this gap by enabling distributed data storage and processing at the micro-architectural level, significantly reducing both latency and energy. In this article, we present In-Memory comPuting architecture based on Y-FlAsh technology for Coalesced Tsetlin machine inference (IMPACT), underpinned on a cutting-edge memory device, Y-Flash, fabricated on a 180 nm complementary metal oxide semiconductor (CMOS) process.
View Article and Find Full Text PDFSci Rep
January 2025
Computational Physics Key Laboratory of Sichuan Province, Yibin University, Yibin, China.
The potential energy curves, dipole moments and transition dipole moments of the 14 Λ-S states and 30 Ω states of TlBr cation were performed using the multi-reference configuration interaction method. The Davidson correction and spin-orbit coupling effects were also considered. The spectroscopic properties and transition properties of TlBr cation were reported at the first time.
View Article and Find Full Text PDFSci Rep
January 2025
Laboratory for Artificial Intelligence, Institute for Computational Science and Artificial Intelligence, Van Lang University, Ho Chi Minh City, Vietnam.
Compliant mechanism has some advantages and has been widely applied in many accurate positioning systems. However, modeling the compliant mechanism behavior has suffered from many challenges, such as unstable results, and the limitation of training data set. In the field of compliant mechanism modeling, there has been no research interested in applying meta-heuristics optimization algorithms to optimize the weights and biases of the neural network globally.
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January 2025
College of Intelligent Systems Science and Engineering, Hubei Minzu University, Enshi, 445000, China.
This paper addresses the low level of intelligence in tea processing equipment in Enshi Prefecture by designing an intelligent withering control system based on the STMicroelectronics 32-bit Microcontroller (STM32). This control system can achieve real-time monitoring of the withering environment and automate the control of heating and ventilation dehumidification modules. By integrating IoT technology, relevant users can view the tea production process via mobile devices, enabling intelligent and remote production operations.
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