A Novel Particle/Photon Detector Based on a Superconducting Proximity Array of Nanodots

The current frontiers in the investigation of high-energy particles demand for new detection methods. Higher sensitivity to low-energy deposition, high-energy resolution to identify events and improve the background rejection, and large detector masses have to be developed to detect even an individual particle that weakly interacts with ordinary matter. Here, we will describe the concept and the layout of a novel superconducting proximity array which show dynamic vortex Mott insulator to metal transitions, as an ultra-sensitive compact radiation-particle detector.     

Self-Organising Maps: A new way to screen the level of satisfaction of dialysis patients

Evaluation of patient satisfaction has become an important indicator for assessing health care quality. Fresenius Medical Care (FME) as a global provider of dialysis services through its NephroCare network has a strong interest in monitoring patient satisfaction.The aim of the paper is to test and validate a methodology for detecting a residual area of low satisfaction in dialysis patients.The FME Patient Satisfaction Programme questionnaire was distributed to haemodialysis (HD) patients treated in 335 centers of its network. It contained 79 questions covering various satisfaction aspects regarding Dialysis Unit, Dialysis Arrangement, Nurses, Doctors, etc.To analyse the data provided by the questionnaire, the Self-Organising Map (SOM) method was used. SOM is a neural network model for clustering and projecting high-dimensional data into a low-dimensional space, preserving topological relationships of original high-dimensional data spaces.10,632 HD patients completed the questionnaire. Mean age was 63.05 ± 14.93 years with 56.69% males. Response rate was 66%. Overall level of satisfaction was 1.99 (range from ?3 to +3). On average patients were very satisfied with all issues. Nevertheless, a group of patients, around 60 years old, balanced gender ratio, whose level of satisfaction was lower than 1, were highlighted.In the NephroCare clinics patient satisfaction with service is rather high. While traditional analysis usually stops here, the SOM method allows identification of areas of potential improvement for specific patient groups.     

Effectiveness of Semi-Supervised Active Learning in Automated Wound Image Segmentation

Appropriate wound management shortens the healing times and reduces the management costs, benefiting the patient in physical terms and potentially reducing the healthcare system’s economic burden. Among the instrumental measurement methods, the image analysis of a wound area is becoming one of the cornerstones of chronic ulcer management. Our study aim is to develop a solid AI method based on a convolutional neural network to segment the wounds efficiently to make the work of the physician more efficient, and subsequently, to lay the foundations for the further development of more in-depth analyses of ulcer characteristics. In this work, we introduce a fully automated model for identifying and segmenting wound areas which can completely automatize the clinical wound severity assessment starting from images acquired from smartphones. This method is based on an active semi-supervised learning training of a convolutional neural network model. In our work, we tested the robustness of our method against a wide range of natural images acquired in different light conditions and image expositions. We collected the images using an ad hoc developed app and saved them in a database which we then used for AI training. We then tested different CNN architectures to develop a balanced model, which we finally validated with a public dataset. We used a dataset of images acquired during clinical practice and built an annotated wound image dataset consisting of 1564 ulcer images from 474 patients. Only a small part of this large amount of data was manually annotated by experts (ground truth). A multi-step, active, semi-supervised training procedure was applied to improve the segmentation performances of the model. The developed training strategy mimics a continuous learning approach and provides a viable alternative for further medical applications. We tested the efficiency of our model against other public datasets, proving its robustness. The efficiency of the transfer learning showed that after less than 50 epochs, the model achieved a stable DSC that was greater than 0.95. The proposed active semi-supervised learning strategy could allow us to obtain an efficient segmentation method, thereby facilitating the work of the clinician by reducing their working times to achieve the measurements. Finally, the robustness of our pipeline confirms its possible usage in clinical practice as a reliable decision support system for clinicians.     

A new high-brightness stepped-crystal diffractor for X-ray microanalysis

An electron-probe X-ray microanalyzers, the characteristic X-ray radiation is generated within a small volume of sample and the emitting surface area is on the order of 1 μm². For a distance to analyzer of approximately 0.5 m, this small emitting area can be considered as a point source. Practical implementations of the electron-probe X-ray microanalysis (EPMA) require a high spectral resolution and sufficient intensity.     

Cycling reliability of RF-MEMS switches with Gold–Platinum multilayers as contact material

Microsystem Technologies - Contact resistance is the main parameter used for assessing the high cycling reliability of RF microelectromechanical (RF-MEMS) switches. In this paper the use of a...     

Coherent and incoherent components of a synchrotron radiation spot produced by separate capillaries

We discuss soft-x-ray focusing properties of separate capillaries. It is shown that a nonnegligible fraction of the synchrotron radiation beam transmitted by the capillary is modal. Experimental and theoretical data are discussed to explain the superposition pattern of x rays in the focal plane due to the interference phenomena of electromagnetic radiation propagating through separate capillaries.     

Single-reflection regime of X rays that travel into a monocapillary

We present an analysis of the transmission of x rays through a single monocapillary under the single-reflection regime. Because ray tracing does not provide an explanation for experimental data, we give a qualitative interpretation of the observed behavior within the framework of wave theory.     

Reliability of RF MEMS switches due to charging effects and their circuital modelling

The reliability of RF MEMS switches is typically reduced by charging effects occurring in the dielectrics. The aim of this paper is to discuss these effects, and to propose analytical and equivalent circuit models which account for most of the physical contributions present in the structure.