Power calculation for gravitational radiation: oversimplification and the importance of time scale

A simplified formula for gravitational-radiation power is examined. It is shown to give completely erroneous answers in three situations, making it useless even for rough estimates. It is emphasized that short timescales, as well as fast speeds, make classical approximations to relativistic calculations untenable.Comment: Three pages, no figures, accepted for publication in Astronomische Nachrichte

Mesoscopic continuous and discrete channels for quantum information transfer

We study the possibility of realizing perfect quantum state transfer in mesoscopic devices. We discuss the case of the Fano-Anderson model extended to two impurities. For a channel with an infinite number of degrees of freedom, we obtain coherent behavior in the case of strong coupling or in weak coupling off-resonance. For a finite number of degrees of freedom, coherent behavior is associated to weak coupling and resonance conditions

A NEURAL NETWORK APPROACH TO ANALYSE CAVITATING FLOW REGIME IN AN INTERNAL ORIFICE

none3The identification of the water cavitation regime is an important issue in a wide range of machines, as hydraulic machines and internal combustion engine. In the present work several experiments on a water cavitating flow were conducted in order to investigate the influence of pressures and temperature on flow regime transition. In some cases, as the injection of hot fluid or the cryogenic cavitation, the thermal effects could be important. The cavitating flow pattern was analyzed by the images acquired by the high-speed camera and by the pressure signals. Four water cavitation regimes were individuated by the visualizations: no-cavitation, developing, super and jet cavitation. As by image analysis, also by the frequency analysis of the pressure signals, different flow behaviours were identified at the different operating conditions. A useful approach to predict and on-line monitoring the cavitating flow and to investigate the influence of the different parameters on the phenomenon is the application of Artificial Neural Network (ANN). In the present study a three-layer Elman neural network was designed, using as inputs the power spectral density distributions of dynamic differential pressure fluctuations, recorded downstream and upstream the restricted area of the orifice. Results show that the designed neural networks predict the cavitation patterns successfully comparing with the cavitation pattern by visual observation. The Artificial Neural Network underlines also the impact that each input has in the training process, so it is possible to identify the frequency ranges that more influence the different cavitation regimes and the impact of the temperature. A theoretical analysis has been also performed to justify the results of the experimental observations. In this approach the nonlinear dynamics of the bubbles growth have been used on an homogenous vapor - liquid mixture model, so to couple the effects of the internal dynamic bubble with the other flow parameters.Paper ESDA2012-82205M.G. De Giorgi; D. Bello; A.FicarellaDE GIORGI, Maria Grazia; Bello, Daniela; Ficarella, Antoni

Exploring Prognostic and Diagnostic Techniques for Jet Engine Health Monitoring: A Review of Degradation Mechanisms and Advanced Prediction Strategies

Maintenance is crucial for aircraft engines because of the demanding conditions to which they are exposed during operation. A proper maintenance plan is essential for ensuring safe flights and prolonging the life of the engines. It also plays a major role in managing costs for aeronautical companies. Various forms of degradation can affect different engine components. To optimize cost management, modern maintenance plans utilize diagnostic and prognostic techniques, such as Engine Health Monitoring (EHM), which assesses the health of the engine based on monitored parameters. In recent years, various EHM systems have been developed utilizing computational techniques. These algorithms are often enhanced by utilizing data reduction and noise filtering tools, which help to minimize computational time and efforts, and to improve performance by reducing noise from sensor data. This paper discusses the various mechanisms that lead to the degradation of aircraft engine components and the impact on engine performance. Additionally, it provides an overview of the most commonly used data reduction and diagnostic and prognostic techniques

FDG-PET in the management of germ cell tumor

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Experimental Detection of Entanglement with Polarized Photons

We report on the first experimental realization of the entanglement witness for polarization entangled photons. It represents a recently discovered significant quantum information protocol which is based on few local measurements. The present demonstration has been applied to the so-called Werner states, a family of ''mixed'' quantum states that include both entangled and non entangled states. These states have been generated by a novel high brilliance source of entanglement which allows to continuously tune the degree of mixedness

Pharmacokinetics and antinociceptive effects of tramadol and its metabolite O-desmethyltramadol following intravenous administration in sheep

Although sheep are widely used as an experimental model for various surgical procedures there is a paucity of data on the pharmacokinetics and efficacy of analgesic drugs in this species. The aims of this study were to investigate the pharmacokinetics of intravenously (IV) administered tramadol and its active metabolite O-desmethyltramadol (M1) and to assess the mechanical antinociceptive effects in sheep. In a prospective, randomized, blinded study, six healthy adult sheep were given 4 and 6\u2009mg/kg tramadol and saline IV in a cross-over design with a 2-week wash-out period. At predetermined time points blood samples were collected and physiological parameters and mechanical nociceptive threshold (MNT) values were recorded. The analytical determination of tramadol and M1 was performed using high performance liquid chromatography. Pharmacokinetic parameters fitted a two- and a non-compartmental model for tramadol and M1, respectively. Normally distributed data were analysed by a repeated mixed linear model. Plasma concentration vs. time profiles of tramadol and M1 were similar after the two doses. Tramadol and M1 plasma levels decreased rapidly in the systemic circulation, with both undetectable after 6\u2009h following drug administration. Physiological parameters did not differ between groups; MNT values were not statistically significant between groups at any time point. It was concluded that although tramadol and M1 concentrations in plasma were above the human minimum analgesic concentration after both treatments, no mechanical antinociceptive effects of tramadol were reported. Further studies are warranted to assess the analgesic efficacy of tramadol in sheep