Treatment with lipid therapy to resuscitate a patient suffering from toxicity due to local anesthetics

Recently, although without a universal recognition, the use of lipid emulsions as a rescue therapy for the bupivacaine cardiac toxicity has been proposed. In this article we report a successful resuscitation of a patient after the injection of bupivacaine in emergency room and a commented review of the related literature. The patient is a 73 years old man that, after a subcutaneous injection of bupivacaine (0.5%, i.e. 0.5 mL/h), developed circulatory arrest. After the failure of the initial treatment based on the advanced life support protocol, we have successfully performed a therapy with lipid emulsion. The bupivacaine intravascular injection, together with its interaction with amitriptyline and carbamazepine, could lead to cardiac depression, severe arrhythmias, hypotension, and/or cardiac arrest. In the case of failure of traditional life support treatment, intravenous lipid emulsion proves to be the best therapy to treat bupivacaine systemic toxicity

Terahertz gas sensor based on absorption-induced transparency

A system for the detection of spectral signatures of gases at the Terahertz regime is presented. The system consists in an initially opaque holey metal film whereby the introduction of a gas provokes the appearance of spectral features in transmission and reflection, due to the phenomenom of absorption-induced transparency (AIT). The peaks in transmission and dips in reflection observed in AIT occur close to the absorption energies of the molecules, hence its name. The presence of the gas would be thus revealed as a strong drop in reflectivity measurements at one (or several) of the gas absorption resonances. As a proof of principle, we theoretically demonstrate how the AIT-based sensor would serve to detect tiny amounts of hydrocyanic acid

A strange case of Evans syndrome

Evans syndrome is a rare autoimmune disease presenting hemolytic anemia, thrombocytopenia and/or neutropenia. It may be associated with other autoimmune or lymphoproliferative diseases. It can have an extremely serious disease course and, in rare cases, this can even be life-threatening. First-line treatment consists of steroids and/or immunoglobulin. Further therapy with rituximab, vincristine, cyclophosphamide and other immunosuppressive drugs can be considered in unresponsive patients. We report a case of Evans syndrome in a 54-year old woman admitted to the Emergency Department (ED) for asthenia. Etiopathogenic, clinical, therapeutic and evolutive aspects are discussed. In contrast to many cases described in the literature, our patient had a satisfactory response to corticoids. We also discuss how to make a specific diagnosis, even in a suburban ED with limited resources, in order to admit patients to the appropriate hospital department and allow the correct therapy to be started as early as possible

DAG-Net: Double Attentive Graph Neural Network for Trajectory Forecasting

Understanding human motion behaviour is a critical task for several possible applications like self-driving cars or social robots, and in general for all those settings where an autonomous agent has to navigate inside a human-centric environment. This is non-trivial because human motion is inherently multi-modal: given a history of human motion paths, there are many plausible ways by which people could move in the future. Additionally, people activities are often driven by goals, e.g. reaching particular locations or interacting with the environment. We address the aforementioned aspects by proposing a new recurrent generative model that considers both single agents' future goals and interactions between different agents. The model exploits a double attention-based graph neural network to collect information about the mutual influences among different agents and to integrate it with data about agents' possible future objectives. Our proposal is general enough to be applied to different scenarios: the model achieves state-of-the-art results in both urban environments and also in sports applications

Optical Scattering Cancellation through Arrays of Plasmonic Nanoparticles: A Review

In this contribution, we review and discuss our recent results on the design of optical scattering cancellation devices based on an array of plasmonic nanoparticles. Starting from two different analytical models available to describe its electromagnetic behavior, we show that a properly designed array of plasmonic nanoparticles behaves both as an epsilon-near-zero metamaterial and as a reactive metasurface and, therefore, can be successfully used to reduce the optical scattering of a subwavelength object. Three different typologies of nanoparticle arrays are analyzed: spherical, core-shell, and ellipsoidal nanoparticles. We prove, both theoretically and through full-wave simulations, that such nanostructures can be successfully used as a cloaking device at ultraviolet and optical frequencies

A Nonparametric Estimator for Coherent Change Detection: The Permutational Change Detection

Nowadays, synthetic aperture radar (SAR) is widely used in heterogeneous fields with aims strictly dependent on the objectives of the application. One of the most common is the exploitation of the interferometric-SAR (InSAR) to measure millimeter movements on the Earth's surface, aiming to monitor failures (e.g., landslides) or to measure the health state of infrastructures (e.g., mining assets, bridges, and buildings). In this article, developing algorithms to detect temporal and spatial changes in the radar targets becomes very important. This article focuses on the temporal change detection framework, proposing a nonparametric coherent change detection (CCD) algorithm called permutational change detection (PCD), a purely statistical algorithm whose core is the permutational test. The PCD estimates the temporal change points (CPs) of a radar target recognizing blocks structure in the coherence matrix, namely, new radar objects. The algorithm has been fine-tuned for small SAR datasets, with the specific aim of prioritizing the analysis of the latest changes. A rigorous mathematical derivation of the algorithm is carried out, explaining how some limits have been addressed. Then, the performance analysis on the simulated data is deeply accomplished, carried out for the stand-alone PCD and the PCD compared with a parametric CCD algorithm based on the generalized likelihood ratio test (GLRT), and with the Omnibus and REACTIV detectors. The comparison with these other algorithms and the stand-alone performance analysis point out the robustness of the PCD in dealing with very noisy environments, even in the case of a single block. Finally, the PCD is validated by processing two Sentinel I data stacks, ascending and descending geometries, of the 2016 Central Italy earthquake