Pavement testing by integrated geophysical methods: Feasibility, resolution and diagnostic potential

This work is focused on the assessment of the diagnostic potential of several geophysical methods when applied to the investigation of a rigid airport pavement. The potential and limit of each technique are evaluated as well as the added value deriving from their integration. Firstly, we reconstruct a high-resolution image of the pavement by a large electromagnetic and georadar screening. An advanced processing of georadar data, implemented through the picking of the arrival times of reflections for each profile, provides a quantitative estimation of the deviation between the design and the as-built thickness of layers. Additionally, electrical tomography has been applied to unequivocally identify the anomalous zones, where higher values of resistivity would be associated to porous zones that are prone to degradation and failure. The seismic tomographic survey had the additional purpose to recover the mechanical properties of the pavement in terms of both P- and S-waves and consequently of elastic constants (Poisson's ratio), whose values were consistent with those recovered in literature. The anomalies detected by each technique are consistent in their indications and they can be correlated to failure phenomena occurring at layer interfaces within the pavement structure or to unexpected variations of the layer thicknesses. The cost-effective geophysical campaign has validated the four-layered system deduced from the original design and has been used to reconstruct a high-resolution map of the pavement in order to discriminate fractures, crack-prone areas or areas where the as-built differs from the original design

Induced Pluripotent Stem Cells: Advances in the Quest for Genetic Stability during Reprogramming Process.

Evaluation of the extent and nature of induced pluripotent stem cell (iPSC) genetic instability is important for both basic research and future clinical use. As previously demonstrated regarding embryonic stem cells, such DNA aberrations might affect the differentiation capacity of the cells and increase their tumorigenicity. Here, we first focus on the contribution of multiple DNA damage response pathways during cellular reprogramming. We then discuss the origin and mechanisms responsible for the modification of genetic material in iPSCs (pre-existing variations in somatic cells, mutations induced by reprogramming factors, and mutations induced by culture expansion) and deepen the possible functional consequences of genetic variations in these cells. Lastly, we present some recent improvements of iPSC generation methods aimed at obtaining cells with fewer genetic variations

User Localization for Rescue Operations Exploiting the Cross-Cross-Correlations of Signals from Multiple Sensors

Delay estimation of incoming signals in passive systems is still nowadays at the base of many signal processing applications ranging from passive radars to underwater acoustics, indoor acoustic positioning, and others. This paper aims at improving the estimation of the delays with respect to multiple sensing nodes for user localization for rescue operations under the unavailability of the base stations in the area of interest. To this end, it suitably exploits a method grounded on the computation of the cross-correlation between the cross-correlation estimates (say cross-cross-correlation) of the received signals. The estimation problem is formulated as a least squares (LS) optimization problem. As a consequence, the proposed method inherits an important feature of the LS approach, namely that is independent of the underlying data distributions. The performance assessment is conducted in comparison with its classic counterpart

Sensor Failure Detection for TDOA-based Localization Systems

This paper outlines a strategy for identifying sensors in a passive locating system that are not functioning properly. The framework is based on the information extracted from delay estimation errors, obtained from solving a system of equations in which the cross- and cross-cross-correlation methods are both used. Hence, we remove equations with the highest errors and use a statistical test to identify which sensor is experiencing failure. Our approach is analyzed through numerical simulations and real-recorded data, and compared to heuristic and conventional methods to prove its advantages

An IMEX-DG solver for atmospheric dynamics simulations with adaptive mesh refinement

We present an accurate and efficient solver for atmospheric dynamics simulations that allows for non-conforming mesh refinement. The model equations are the conservative Euler equations for compressible flows. The numerical method is based on an $h-$adaptive Discontinuous Galerkin spatial discretization and on a second order Additive Runge Kutta IMEX method for time discretization, especially designed for low Mach regimes. The solver is implemented in the framework of the $deal.II$ library, whose mesh refinement capabilities are employed to enhance efficiency. A number of numerical experiments based on classical benchmarks for atmosphere dynamics demonstrate the properties and advantages of the proposed method

Healing environment in pediatric dentistry: strategies adopted by “Sapienza” University of Rome

Children’s dental anxiety has been of great worry for many years and it is still a barrier for dental care. According to recent guidelines for oral health prevention in childhood, additional strategies for a preventive care should be applied for pediatric patients. So it’s important to encourage pediatric dentists to develop a “child-friendly” environment for treating children. Environmental elements that produce positive feelings can reduce anxiety. The analysis of environmental design and features applied in Pediatric Dentistry Unit, Department of Oral and Maxillo-facial sciences, Sapienza University of Rome, highlighted special attention to the aspects supporting sensory conditions (colors, light, spatial organization); reassurance strategies (decorations, dental team attire, drawings); anxiety control strategies (playing area, TV, comics, toys); behavioral management strategies (positive reinforcement, modeling); in-formation (brochures, posters)

An efficient IMEX-DG solver for the compressible Navier-Stokes equations for non-ideal gases

We propose an efficient, accurate and robust IMEX solver for the compressible Navier-Stokes equation describing non-ideal gases with general equations of state. The method, which is based on an $h-$adaptive Discontinuos Galerkin spatial discretization and on an Additive Runge Kutta IMEX method for time discretization, is tailored for low Mach number applications and allows to simulate low Mach regimes at a significantly reduced computational cost, while maintaining full second order accuracy also for higher Mach number regimes. The method has been implemented in the framework of the $deal.II$ numerical library, whose adaptive mesh refinement capabilities are employed to enhance efficiency. Refinement indicators appropriate for real gas phenomena have been introduced. A number of numerical experiments on classical benchmarks for compressible flows and their extension to real gases demonstrate the properties of the proposed method