NetCausality: A time-delayed neural network tool for causality detection and analysis

The analysis of causality between systems is still an important research activity, which finds application in several fields of science. The software presented is a new tool for causality detection and analysis between time series. The proposed technique is based on time-delayed neural networks (TDNN). The tool is developed in MATLAB and it comprises three main functions. The first one returns the total causality between two or more systems of equations. The second tool is used to find the ‘‘time horizon’’, id est the time delay at which the influence between the systems occurs. The last function is a causality feature detection to determine the time intervals, in which the mutual coupling is sufficiently strong to have a real influence on the target

An alternative SNR-based weighted-LSM algorithm to classify and measure the concentration of Biological Agents from Laser-Induced Fluorescence

Optical spectroscopic techniques, such as Laser-Induced Breakdown Spectroscopy (LIBS) or Laser-Induced Fluorescence (LIF), have already been used to study and detect Biological Agents (BAs). Unfortunately, BAs usually share similar-shaped emitted spectra and low-signal intensities, making their detection and classification difficult to assess. Least-Square Minimisation (LSM) based algorithms are usually deployed to measure the concentration of agents from spectra. Recently, it has been shown how the use of ad hoc weights can help in improving the performance of the concentration evaluation. More specifically, it has been observed that the “weight matrix” should be modelled as a function of the boundary conditions of the problem. This work proposes a new weight matrix that is based on the Signal-to-Noise Ratio (SNR) of the measurements. The idea is based on the fact that more noisy data are less reliable and therefore weight should be lowered. The paper, after a brief introduction and review of the LSM applied to spectra, will show the new methodology. A systematic analysis of the new algorithm is done and the comparison with the other LSM algorithms is presented. The results clearly show that there is a range of parameters for which the new algorithm performs better

Targeting lipid rafts as a strategy against coronavirus

Lipid rafts are functional membrane microdomains containing sphingolipids, including gangliosides, and cholesterol. These regions are characterized by highly ordered and tightly packed lipid molecules. Several studies revealed that lipid rafts are involved in life cycle of different viruses, including coronaviruses. Among these recently emerged the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). The main receptor for SARS-CoV-2 is represented by the angiotensin-converting enzyme-2 (ACE-2), although it also binds to sialic acids linked to host cell surface gangliosides. A new type of ganglioside-binding domain within the N-terminal portion of the SARS-CoV-2 spike protein was identified. Lipid rafts provide a suitable platform able to concentrate ACE-2 receptor on host cell membranes where they may interact with the spike protein on viral envelope. This review is focused on selective targeting lipid rafts components as a strategy against coronavirus. Indeed, cholesterol-binding agents, including statins or methyl-β-cyclodextrin (MβCD), can affect cholesterol, causing disruption of lipid rafts, consequently impairing coronavirus adhesion and binding. Moreover, these compounds can block downstream key molecules in virus infectivity, reducing the levels of proinflammatory molecules [tumor necrosis factor alpha (TNF-α), interleukin (IL)-6], and/or affecting the autophagic process involved in both viral replication and clearance. Furthermore, cyclodextrins can assemble into complexes with various drugs to form host–guest inclusions and may be used as pharmaceutical excipients of antiviral compounds, such as lopinavir and remdesivir, by improving bioavailability and solubility. In conclusion, the role of lipid rafts-affecting drugs in the process of coronavirus entry into the host cells prompts to introduce a new potential task in the pharmacological approach against coronavirus

Performance Characterization of ESA's Tropospheric Delay Calibration System for Advanced Radio Science Experiments

Media propagation noises are amongst the main error sources of radiometric observables for deep space missions, with fluctuations of the tropospheric excess path length representing a relevant contributor to the Doppler noise budget. Microwave radiometers currently represent the most accurate instruments for the estimation of the tropospheric delay and delay rate along a slant direction. A prototype of a tropospheric delay calibration system (TDCS), using a 14 channel Ka/V band microwave radiometer, has been developed under a European Space Agency contract and installed at the deep space ground station in Malargüe, Argentina, in February 2019. After its commissioning, the TDCS has been involved in an extensive testbed campaign by recording a total of 44 tracking passes of the Gaia spacecraft, which were used to perform an orbit determination analysis. This work presents the first statistical characterization of the end-to-end performance of the TDCS prototype in an operational scenario. The results show that using TDCS-based calibrations instead of the standard GNSS-based calibrations leads to a significant reduction of the residual Doppler noise and instability

Eribulin vs. Eribulin + Bevacizumab in advanced-line treatment of Her-2 negative metastatic breast cancer

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Enhancing Radiation Detection by Drones through Numerical Fluid Dynamics Simulations

This study addresses the optimization of the location of a radioactive-particle sensor on a drone. Based on the analysis of the physical process and of the boundary conditions introduced in the model, computational fluid dynamics simulations were performed to analyze how the turbulence caused by drone propellers may influence the response of the sensors. Our initial focus was the detection of a small amount of radioactivity, such as that associated with a release of medical waste. Drones equipped with selective low-cost sensors could be quickly sent to dangerous areas that first responders might not have access to and be able to assess the level of danger in a few seconds, providing details about the source terms to Radiological-Nuclear (RN) advisors and decision-makers. Our ultimate application is the simulation of complex scenarios where fluid-dynamic instabilities are combined with elevated levels of radioactivity, as was the case during the Chernobyl and Fukushima nuclear power plant accidents. In similar circumstances, accurate mapping of the radioactive plume would provide invaluable input-data for the mathematical models that can predict the dispersion of radioactivity in time and space. This information could be used as input for predictive models and decision support systems (DSS) to get a full situational awareness. In particular, these models may be used either to guide the safe intervention of first responders or the later need to evacuate affected regions

Sialoendoscopy: state of the art, challenges and further perspectives. Round Table, 101st SIO National Congress, Catania 2014

This draft of the Official Round Table held during the 101st SIO National Congress is an updated review on sialoendoscopy, a technique used for diagnosis and treatment of obstructive pathologies of salivary glands in a minimally invasive fashion. This review treats many aspects of salivary gland endoscopy, starting from anatomy to deal with the more advanced surgical techniques and analyses the main decisional algorithms proposed in the literature. In addition, particular attention was directed to the current limitations of this technique and to the potential developments that sialoendoscopy could have in the near future

Theory of decoherence in a matter wave Talbot-Lau interferometer

We present a theoretical framework to describe the effects of decoherence on matter waves in Talbot-Lau interferometry. Using a Wigner description of the stationary beam the loss of interference contrast can be calculated in closed form. The formulation includes both the decohering coupling to the environment and the coherent interaction with the grating walls. It facilitates the quantitative distinction of genuine quantum interference from the expectations of classical mechanics. We provide realistic microscopic descriptions of the experimentally relevant interactions in terms of the bulk properties of the particles and show that the treatment is equivalent to solving the corresponding master equation in paraxial approximation.Comment: 20 pages, 4 figures (minor corrections; now in two-column format

Enhancing radiation detection by drones through numerical fluid dynamics simulations

This study addresses the optimization of the location of a radioactive-particle sensor on a drone. Based on the analysis of the physical process and of the boundary conditions introduced in the model, computational fluid dynamics simulations were performed to analyze how the turbulence caused by drone propellers may influence the response of the sensors. Our initial focus was the detection of a small amount of radioactivity, such as that associated with a release of medical waste. Drones equipped with selective low-cost sensors could be quickly sent to dangerous areas that first responders might not have access to and be able to assess the level of danger in a few seconds, providing details about the source terms to Radiological-Nuclear (RN) advisors and decision-makers. Our ultimate application is the simulation of complex scenarios where fluid-dynamic instabilities are combined with elevated levels of radioactivity, as was the case during the Chernobyl and Fukushima nuclear power plant accidents. In similar circumstances, accurate mapping of the radioactive plume would provide invaluable input-data for the mathematical models that can predict the dispersion of radioactivity in time and space. This information could be used as input for predictive models and decision support systems (DSS) to get a full situational awareness. In particular, these models may be used either to guide the safe intervention of first responders or the later need to evacuate affected regions

Tobacco vs. electronic cigarettes: absence of harm reduction after six years of follow-up

OBJECTIVE: Information on the long-term safety of electronic cigarettes (e-cig) is still limited. We report the results after six years of follow-up of the first observational study assessing e-cig long-term effectiveness and safety. PATIENTS AND METHODS: Participants were adults who smoked ≥1 tobacco cigarette/day (tobacco smokers); or used any type of e-cig inhaling ≥50 puffs weekly (e-cig users); or used both (dual users). Participants were contacted directly or by phone and/or internet interviews. Hospital discharge abstract data and carbon monoxide level tests were also used. RESULTS: Data were available for 228 e-cig users (all ex-smokers), 469 tobacco smokers, 215 dual users. A possibly smoking-related disease (PSRD) was recorded in 90 subjects (9.9%); 11 deceased (1.2%). No differences were observed across groups in PSRD rates, with minor changes in self-reported health. Among e-cig users, 64.0% remained tobacco abstinent. Dual users and tobacco smokers did not significantly differ in the rate of cessation of tobacco (38.6% vs. 33.9%, respectively) and all products (23.7% vs. 26.4%). A comparable decrease in daily cigarettes was also observed. 39.5% of the sample switched at least once (tobacco smokers: 15.1%; dual users: 83.3%). CONCLUSIONS: After six years, no evidence of harm reduction was found among e-cig or dual users. The complete switch to e-cig might support tobacco quitters remain abstinent, but the use of e-cig in addition to tobacco did not improve smoking cessation or reduction