The LAUE project for broadband gamma-ray focusing lenses

We present the LAUE project devoted to develop an advanced technology for building a high focal length Laue lens for soft gamma--ray astronomy (80-600 keV). The final goal is to develop a focusing optics that can improve the current sensitivity in the above energy band by 2 orders of magnitude.Comment: 7 pages, 6 figures, presented at the SPIE conference on "Optics for EUV, X-ray, and Gamma-ray Astronomy". To be published in the Proceedings of SPIE, vol.8147, 201

Comparison of Algorithms for the AI-Based Fault Diagnostic of Cable Joints in MV Networks

Abstract Electrical utilities and system operators (SOs) are constantly looking for solutions to problems in the management and control of the power network. For this purpose, SOs are exploring new research fields, which might bring contributions to the power system environment. A clear example is the field of computer science, within which artificial intelligence (AI) has been developed and is being applied to many fields. In power systems, AI could support the fault prediction of cable joints. Despite the availability of many legacy methods described in the literature, fault prediction is still critical, and it needs new solutions. For this purpose, in this paper, the authors made a further step in the evaluation of machine learning methods (ML) for cable joint health assessment. Six ML algorithms have been compared and assessed on a consolidated test scenario. It simulates a distributed measurement system which collects measurements from medium-voltage (MV) cable joints. Typical metrics have been applied to compare the performance of the algorithms. The analysis is then completed considering the actual in-field conditions and the SOs’ requirements. The results demonstrate: (i) the pros and cons of each algorithm; (ii) the best-performing algorithm; (iii) the possible benefits from the implementation of ML algorithms

Therapeutic potential of endothelial colony‐forming cells in ischemic disease: Strategies to improve their regenerative efficacy

Cardiovascular disease (CVD) comprises a range of major clinical cardiac and circulatory diseases, which produce immense health and economic burdens worldwide. Currently, vascular regenerative surgery represents the most employed therapeutic option to treat ischemic disorders, even though not all the patients are amenable to surgical revascularization. Therefore, more efficient therapeutic approaches are urgently required to promote neovascularization. Therapeutic angiogenesis represents an emerging strategy that aims at reconstructing the damaged vascular network by stimulating local angiogenesis and/or promoting de novo blood vessel formation according to a process known as vasculogenesis. In turn, circulating endothelial colony‐forming cells (ECFCs) represent truly endothelial precursors, which display high clonogenic potential and have the documented ability to originate de novo blood vessels in vivo. Therefore, ECFCs are regarded as the most promising cellular candidate to promote therapeutic angiogenesis in patients suffering from CVD. The current briefly summarizes the available information about the origin and characterization of ECFCs and then widely illustrates the preclinical studies that assessed their regenerative efficacy in a variety of ischemic disorders, including acute myocardial infarction, peripheral artery disease, ischemic brain disease, and retinopathy. Then, we describe the most common pharmacological, genetic, and epigenetic strategies employed to enhance the vasoreparative potential of autologous ECFCs by manipulating crucial pro‐angiogenic signaling pathways, e.g., extracellular‐signal regulated kinase/Akt, phosphoinositide 3‐kinase, and Ca2+ signaling. We conclude by discussing the possibility of targeting circulating ECFCs to rescue their dysfunctional phenotype and promote neovascularization in the presence of CVD

The WINPack 1 a novel wearable system for heart rate and vital signs monitoring

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