A transport beamline solution to control optically accelerated proton beams

Laser-target interaction represents a very promising field for several potential applications,
from the nuclear physics to the radiobiology. However optically accelerated particle beams are
characterized by some extreme features, not suitable for many applications. Therefore, beyond
the improvements at the laser-target interaction level, many researchers are spending their efforts
for the development of specific beam transport devices in order to obtain controlled and
reproducible output beams.In this background, the ELIMED (ELI-Beamlines MEDical applications)
project was born. Within 2017, a dedicated transport beam-line coupled with dosimetric
systems, named ELIMED, will be installed at the Extreme Light Infrastructure Beamlines
(ELI-Beamlines) facility in Prague (CZ),as a part of the ELIMAIA (ELI Multidisciplinary Applications
of laserâA ¸SIon Acceleration) beamline

Laser-Driven Ion Accelerators: State of the Art and Applications

Laser-plasma based accelerators of protons and heavier ions are a source of potential interest for several applications, including in the biomedical area. While the potential future use in cancer hadrontherapy acts as a strong aspirational motivation for this research field, radiobiology employing laser-driven ion bursts is alreadyan active field of research. Here we give a summary of the state of the art in laser driven ion acceleration, of the main challenges currently faced by the research inthis field and of some of the current and future strategies for overcoming them.

Proposing the deep dynamic Bayesian network as a future computer based medical system

The development of new learning models has been of great importance throughout recent years, with a focus on creating advances in the area of deep learning. Deep learning was first noted in 2006, and has since become a major area of research in a number of disciplines. This paper will delve into the area of deep learning to present its current limitations and provide a new idea for a fully integrated deep and dynamic probabilistic system. The new model will be applicable to a vast number of areas initially focusing on applications into medical image analysis with an overall goal of utilising this approach for prediction purposes in computer based medical systems.