A portable sample viewing and alignment system is described which provides fast and reliable motion positioning for fixed target arrays at synchrotrons and free-electron laser sources.

X-ray optics, based on a double-crystal deflection scheme, that enable reflectivity measurements from liquid surfaces/interfaces have been designed, built and commissioned on beamline I07 at Diamond Light Source. This system is able to deflect the beam onto a fixed sample position located at the centre of a five-circle diffractometer. Thus the incident angle can be easily varied without moving the sample, and the reflected beam is tracked either by a moving Pilatus 100K detector mounted on the diffractometer arm or by a stationary Pilatus 2M detector positioned appropriately for small-angle scattering. Thus the system can easily combine measurements of the reflectivity from liquid interfaces (Q(z) > 1 Å(-1)) with off-specular data collection, both in the form of grazing-incidence small-angle X-ray scattering (GISAXS) or wider-angle grazing-incidence X-ray diffraction (GIXD). The device allows operation over the energy range 10-28 keV.

Purpose: Through the last three decades, functional magnetic resonance imaging (fMRI) has provided immense quantities of information about the dynamics of the brain, functional brain mapping, and resting-state brain networks. Despite providing such rich functional information, fMRI is still not a commonly used clinical technique due to inaccuracy involved in analysis of extremely noisy data. However, ongoing developments in deep learning techniques suggest potential improvements and better performance in many different domains. Our main purpose is to utilize the potentials of deep learning techniques for fMRI data for clinical use. Approach: We present one such synergy of fMRI and deep learning, where we apply a simplified yet accurate method using a modified 3D convolutional neural networks (CNN) to resting-state fMRI data for feature extraction and classification of Alzheimer's disease (AD). The CNN is designed in such a way that it uses the fMRI data with much less preprocessing, preserving both spatial and temporal information. Results: Once trained, the network is successfully able to classify between fMRI data from healthy controls and AD subjects, including subjects in the mild cognitive impairment (MCI) stage. We have also extracted spatiotemporal features useful for classification. Conclusion: This CNN can detect and differentiate between the earlier and later stages of MCI and AD and hence, it may have potential clinical applications in both early detection and better diagnosis of Alzheimer's disease.

A scanning four-bounce monochromator that offers an unprecedented level of stability in the incident beam energy resolution and calibration has been developed for a flagship spectroscopy beamline at Diamond Light Source.

The I21 beamline at Diamond Light Source is dedicated to advanced resonant inelastic X-ray scattering (RIXS) for probing charge, orbital, spin and lattice excitations in materials across condensed matter physics, applied sciences and chemistry. Both the beamline and the RIXS spectrometer employ divergent variable-line-spacing gratings covering a broad energy range of 280–3000 eV. A combined energy resolution of ∼35 meV (16 meV) is readily achieved at 930 eV (530 eV) owing to the optimized optics and the mechanics. Considerable efforts have been paid to the design of the entire beamline, particularly the implementation of the collection mirrors, to maximize the X-ray photon throughput. The continuous rotation of the spectrometer over 150° under ultra high vacuum and a cryogenic manipulator with six degrees of freedom allow accurate mappings of low-energy excitations from solid state materials in momentum space. Most importantly, the facility features a unique combination of the high energy resolution and the high photon throughput vital for advanced RIXS applications. Together with its stability and user friendliness, I21 has become one of the most sought after RIXS beamlines in the world.