Re: "Endothelitis in COVID-19-positive patients after extremity amputation for acute thrombotic events"

Ilonzo et al reported, in their recent and interesting article, their clinical experience in 4 patients affected by COVID-19 and undergoing major limb amputation secondary to acute irreversible ischemia. On histological examination with hematoxylin/eosin they found inflammatory cells associated with endothelium/apoptotic bodies, mononuclear cells, small vessel congestion, and lymphocytic endotheliitis and concluded that the findings in these patients is more likely an infectious angiitis due to COVID-19. In our experience we have observed numerous cases of venous and arterial thromboembolism not only in the acute phase of COVID-19, but (even more interestingly) even after recovery. Whether SARS-CoV-2 is able to directly attack vascular endothelial cells expressing high levels of ACE2, and then lead to abnormal coagulation and sepsis, still needs to be explored

Detection of a two-phonon mode in a cuprate superconductor via polarimetric RIXS

Recent improvements in the energy resolution of resonant inelastic x-ray scattering experiments (RIXS) at the Cu-L$_3$ edge have enabled the study of lattice, spin, and charge excitations. Here, we report on the detection of a low intensity signal at 140meV, twice the energy of the bond-stretching (BS) phonon mode, in the cuprate superconductor $\textrm{Bi}_2\textrm{Sr}_2\textrm{Ca}\textrm{Cu}_2\textrm{O}_{8+x}$ (Bi-2212). Ultra-high resolution polarimetric RIXS measurements allow us to resolve the outgoing polarization of the signal and identify this feature as a two-phonon excitation. Further, we study the connection between the two-phonon mode and the BS one-phonon mode by constructing a joint density of states toy model that reproduces the key features of the data

Improving the reliability of 3D people tracking system by means of deep-learning

People tracking is a crucial task in most computer vision applications aimed at analyzing specific behaviors in the sensed area. Practical applications include vision analytics, people counting, etc. In order to properly follow the actions of a single subject, a people tracking framework needs to robustly recognize it from the rest of the surrounding environment, thus allowing proper management of changing positions, occlusions and so on. The recent widespread diffusion of deep learning techniques on almost any kind of computer vision application provides a powerful methodology to address recognition. On the other hand, a large amount of data is required to train state-of-the-art Convolutional Neural Networks (CNN) and this problem is solved, when possible, by means of transfer learning. In this paper, we propose a novel dataset made of nearly 26 thousand samples acquired with a custom stereo camera providing depth according to a fast and accurate stereo algorithm. The dataset includes sequences acquired in different environments with more than 20 different people moving across the sensed area. Once labeled the 26 K images and depth maps of the dataset, we train a head detection module based on state-of-the-art deep network on a portion of the dataset and validate it a different sequence. Finally, we include the head detection module within an existing 3D tracking framework showing that the proposed approach notably improves people detection and tracking accuracy

Covid-19 emergency management and preparedness in cross-border territories. Collection of experiences, needs and public health strategies in the framework of interreg GESTI.S.CO. project

Background and aim: The Covid-19 pandemic highlighted management difficulties in neighboring territories. The aim of the paper is to report the needs of different stakeholders during, before and after Covid-19 emergency with specific regard to challenges faced by public administrators in confined territories. Methods: In the framework of Interreg GESTI.S.CO. project the study has been designed with two methodological steps: i) a co-design workshop and ii) a web-based survey. The workshop includes both an audience interaction session and focus groups. Then, starting from the focus group results, the survey has been designed with 30 questions and submitted to the 227 municipalities located between Italy and Switzerland to understand the implementation of Public Health strategies in local emergency planning. Results: The interactive session highlighted that most of the critical issues are related to the lack of communication and planning in Public Health policies. The survey highlighted that the local emergency plans rarely integrate a section on health emergencies (30% Italy and 50% Switzerland). Only 20% of the respondents dedicated a section for Covid-19 emergency management. Most of them did not activate initiatives to support mental health. 90% of the municipalities did not cooperate with the neighboring country, but half of them think that it would have been much more useful. The 55% of the Italian respondents are currently updating their emergency plan and will implement it with some Public Health input. Conclusions: The study provides insights that can support policy makers in improving their strategy in responding to future pandemic. (www.actabiomedica.it)