An Unsplit, Cell-Centered Godunov Method for Ideal MHD

We present a second-order Godunov algorithm for multidimensional, ideal MHD. Our algorithm is based on the unsplit formulation of Colella (J. Comput. Phys. vol. 87, 1990), with all of the primary dependent variables centered at the same location. To properly represent the divergence-free condition of the magnetic fields, we apply a discrete projection to the intermediate values of the field at cell faces, and apply a filter to the primary dependent variables at the end of each time step. We test the method against a suite of linear and nonlinear tests to ascertain accuracy and stability of the scheme under a variety of conditions. The test suite includes rotated planar linear waves, MHD shock tube problems, low-beta flux tubes, and a magnetized rotor problem. For all of these cases, we observe that the algorithm is second-order accurate for smooth solutions, converges to the correct weak solution for problems involving shocks, and exhibits no evidence of instability or loss of accuracy due to the possible presence of non-solenoidal fields.Comment: 37 Pages, 9 Figures, submitted to Journal of Computational Physic

Predictive methods of electricity price: An application to the Italian electricity market

Price forecasting is a crucial element for the members of the electricity markets and business decision making to maximize their profits. The electricity prices have an impact on the behavior of market participants, and thus, predicting prices for generation companies, and consumers is essential for both the short-term profits in the Day-Ahead, Intra-Day and Ancillary markets, and the long-term benefits in the future planning, investment, and risk management. Therefore, participants in the electricity market need to accurately and effectively predict the price signal to manage market risk. In this paper, different forecasting models have been compared, and the most promising ones have been employed to forecast the short term Italian electricity market clearing price for achieving forecasting accuracy. In particular, simulations are performed for four principal regression methods, including Support Vector Machine, Gaussian Processes Regression, Regression Trees, and Multi-Layer Perceptron. The performance of predicted models is compared through several performance metrics, including MAE, RMSE, R, and the total number of percentage error anomalies. The results indicate the SVM is the best choice for forecasting the electricity market price on the Italian case study

“Influence of the Therapy with Dorzolamide on the Corneal Structures: Analysis by Confocal Microscopy (CS3)”

Purpose: To value, in vivo, with the confocal microscopy(CS3) the corneal microscopic changes in a group of patients in therapy with Dorzolamide 2% eyedrops. Methods:Thirty patients (sixty eyes) with monocular hypertension (IOP21 mmHg) and no previous ipotonic therapy were recruited. The hypertensive eye (HE)was treated with Dorzolamine 2% eyedrops three times daily, the normal tension eye (NE) was used as the control eye. At the time of recruitment, one and three months after the beginning of treatment were performed: applanation tonometry, ultrasound pachimetry (USP), and a CS examination. Results: Mean age was 41,13±10,515 year, at the recruitment time: mean IOP was 16,50±2.34 mmHg in the NE and 22,06±0.68 mmHg in the HE, USP was 542,50±31,18 µ in the NE and 536,63±38,08 in the HE, endothelial cell density was (cell/mm2) 2473,37±339,58 in the NE and 2386,94±284,16 in the HE, stromal reflectivity was 0.36±0.06 in the NE and 0.36±0.05 in the HE. At each control time the IOP was statistically reduced in the treated eyes of a mean of 7,25 mmHg (p<0.01), all the corneal data didn’t show a statistically significant change during the follow–up period, only the stromal reflectivity seemed to be increased in the last control of 0,1 (p<0.005). Conclusions: The CS3 examination allowed us to value the microscopic corneal structure and to show that no clinically significant changes were produced by dorzolamide local therapy

Proof of Presence: Novel Vehicle Detection System

The detection of vehicle presence in parking slots is a fundamental part of smart parking systems. The problem is commonly approached with devices composed of specific sensors, which usually are either magnetic or infrared. The sensor is continuously sampled by an onboard microcontroller capable of determining the slot status (available or occupied) and sending the information to a central collection and gathering system by means of a wireless technology. Nevertheless, cost and power consumption are still an issue. Based on the consideration that the vehicle slot status is only a single bit of information, in this article an alternative low-power and cost-effective approach is proposed. Specifically, two novel vehicle presence detectors, one battery-powered and based on 868 MHz LoRa technology and one solar-cell-powered and adopting BAP 866 MHz UHF RFID technology, are presented, designed, realized, and tested. The obtained results demonstrate the appropriateness of the proposed approach since the same functionalities of conventional devices at lower cost and lower consumption are reached

Effect of irrigation regimes and artificial mycorrhization on insect pest infestations and yield in tomato crop

A 2-year field experiment was carried out to test the effect of root symbionts treatments in combination with different watering levels on tomato yield and pest infestation rates. A split-plot experimental design was followed, where the main treatments were three irrigation regimes, and the subplot factor was the mycorrhizal treatment (two mycorrhizal treatments [M1 and M2] and the control). The M1 treatment consisted in the use of a commercial preparation (Micosat F; CCS Aosta, Italy) containing a mixture of vesicular-arbuscular mycorrhizae (VAM), bacteria of the rhizosphere and saprophytic fungi, while M2 treatment used only arbuscular mycorrhizal fungi. Insect pests sampled in the field during the 2 years of experiment were all sap-feeders (Trialeurodes vaporariorum, Macrosiphum euphorbiae, Frankliniella occidentalis and an unidentified species of leafhopper). Results did not show any impact of root symbionts on pests, whereas water deficit significantly reduced plant infestation rates. Both mycorrhization treatments and water supply resulted in a significantly positive effect on crop yield

Self-consistent solutions of canonical proper self-gravitating quantum systems

Generic self-gravitating quantum solutions that are not critically dependent on the specifics of microscopic interactions are presented. The solutions incorporate curvature effects, are consistent with the universality of gravity, and have appropriate correspondence with Newtonian gravitation. The results are consistent with known experimental results that indicate the maintenance of the quantum coherence of gravitating systems, as expected through the equivalence principle.Comment: 13 pages, 7 figure

Cosmological Adaptive Mesh Refinement

We describe a grid-based numerical method for 3D hydrodynamic cosmological simulations which is adaptive in space and time and combines the best features of higher order--accurate Godunov schemes for Eulerian hydrodynamics with adaptive particle--mesh methods for collisionless particles. The basis for our method is the structured adaptive mesh refinement (AMR) algorithm of Berger & Collela (1989), which we have extended to cosmological hydro + N-body simulations. The resulting multiscale hybrid method is a powerful alternative to particle-based methods in current use. The choices we have made in constructing this algorithm are discussed, and its performance on the Zeldovich pancake test problem is given. We present a sample application of our method to the problem of first structure formation. We have achieved a spatial dynamic range $L_{box}/\Delta x > 250,000$ in a 3D multispecies gas + dark matter calculation, which is sufficient to resolve the formation of primordial protostellar cloud cores starting from linear matter fluctuations in an expanding FRW universe.Comment: 14 pages, 3 figures (incl. one large color PS) to appear in "Numerical Astrophysics 1998", eds. S. Miyama & K. Tomisaka, Tokyo, March 10-13, 199

Mass-loaded spherical accretion flows

We have calculated the evolution of spherical accretion flows undergoing mass-loading from embedded clouds through either conduction or hydrodynamical ablation. We have observed the effect of varying the ratios of the mass-loading timescale and the cooling timescale to the ballistic crossing timescale through the mass-loading region. We have also varied the ratio of the potential energy of a particle injected into the flow near the outer region of mass-loading to the temperature at which a minimum occurs in the cooling curve. The two types of mass-loading produce qualitatively different types of behaviour in the accretion flow, since mass-loading through conduction requires the ambient gas to be hot, whereas mass ablation from clumps occurs throughout the flow. Higher ratios of injected to accreted mass typically occur with hydrodynamical ablation, in agreement with previous work on wind-blown bubbles and supernova remnants. We find that mass-loading damps the radiative overstability of such flows, in agreement with our earlier work. If the mass-loading is high enough it can stabilize the accretion shock at a constant radius, yielding an almost isothermal subsonic post-shock flow. Such solutions may be relevant to cooling flows onto massive galaxies. Mass-loading can also lead to the formation of isolated shells of high temperature material, separated by gas at cooler temperatures

A Fuzzy Inference System for the Assessment of Indoor Air Quality in an Operating Room to Prevent Surgical Site Infection

Indoor air quality in hospital operating rooms is of great concern for the prevention of surgical site infections (SSI). A wide range of relevant medical and engineering literature has shown that the reduction in air contamination can be achieved by introducing a more efficient set of controls of HVAC systems and exploiting alarms and monitoring systems that allow having a clear report of the internal air status level. In this paper, an operating room air quality monitoring system based on a fuzzy decision support system has been proposed in order to help hospital staff responsible to guarantee a safe environment. The goal of the work is to reduce the airborne contamination in order to optimize the surgical environment, thus preventing the occurrence of SSI and reducing the related mortality rate. The advantage of FIS is that the evaluation of the air quality is based on easy-to-find input data established on the best combination of parameters and level of alert. Compared to other literature works, the proposed approach based on the FIS has been designed to take into account also the movement of clinicians in the operating room in order to monitor unauthorized paths. The test of the proposed strategy has been executed by exploiting data collected by ad-hoc sensors placed inside a real operating block during the experimental activities of the “Bacterial Infections Post Surgery” Project (BIPS). Results show that the system is capable to return risk values with extreme precision