Comparison between two artificial intelligence models to discriminate cancerous cell nuclei based on confocal fluorescence imaging in hepatocellular carcinoma.

Background: Hepatocellular carcinoma (HCC) exhibits an exceptional intratumoral heterogeneity that might influence diagnosis and outcome. Advances in digital microscopy and artificial intelligence (AI) may improve the HCC identification of liver cancer cells.

Aim: Two AI algorithms were designed to perform computer-assisted discrimination of tumour from non-tumour nuclei in HCC.

Neural network analysis for predicting metrics of fragmented laminar artifacts: a case study from MPPNB sites in the Southern Levant.

This study was aimed at introducing a new method for predicting the original metrics of fragmented standardized artifacts, specifically of flint blades from the Middle Pre-Pottery Neolithic B (10,200/100-9,500/400 cal B.P.) in the Southern Levant.

Efficient Integration of Ultra-low Power Techniques and Energy Harvesting in Self-Sufficient Devices: A Comprehensive Overview of Current Progress and Future Directions.

Compact, energy-efficient, and autonomous wireless sensor nodes offer incredible versatility for various applications across different environments. Although these devices transmit and receive real-time data, efficient energy storage (ES) is crucial for their operation, especially in remote or hard-to-reach locations. Rechargeable batteries are commonly used, although they often have limited storage capacity.

Controlling On-Surface Photoactivity: The Impact of π-Conjugation in Anhydride-Functionalized Molecules on a Semiconductor Surface.

On-surface synthesis has become a prominent method for growing low-dimensional carbon-based nanomaterials on metal surfaces. However, the necessity of decoupling organic nanostructures from metal substrates to exploit their properties requires either transfer methods or new strategies to perform reactions directly on inert surfaces. The use of on-surface light-induced reactions directly on semiconductor/insulating surfaces represents an alternative approach to address these challenges.

Affine diffractive beam dividers.

Diffractive optical elements that divide an input beam into a set of replicas are used in many optical applications ranging from image processing to communications. Their design requires time-consuming optimization processes, which, for a given number of generated beams, are to be separately treated for one-dimensional and two-dimensional cases because the corresponding optimal efficiencies may be different. After generalizing their Fourier treatment, we prove that, once a particular divider has been designed, its transmission function can be used to generate numberless other dividers through affine transforms that preserve the efficiency of the original element without requiring any further optimization.