The impact of the Geometric Correction Scheme on MEG functional topology at rest

Spontaneous activity is correlated across brain regions in large scale networks (RSN) closely resembling those recruited during several behavioral tasks and characterized by functional specialization and dynamic integration. Specifically, MEG studies revealed a set of central regions (dynamic core) possibly facilitating communication among differently specialized brain systems. However, source projected MEG signals, due to the fundamentally ill-posed inverse problem, are affected by spatial leakage, leading to the estimation of spurious, blurred connections that may affect the topological properties of brain networks and their integration. To reduce leakage effects, several correction schemes have been proposed including the Geometric Correction Scheme (GCS) whose theory, simulations and empirical results on topography of a few RSNs were already presented. However, its impact on the estimation of fundamental graph measures used to describe the architecture of interactions among brain regions has not been investigated yet. Here, we estimated dense, MEG band-limited power connectomes in theta, alpha, beta, and gamma bands from 13 healthy subjects (all young adults). We compared the connectivity and topology of MEG uncorrected and GCS-corrected connectomes. The use of GCS considerably reorganized the topology of connectivity, reducing the local, within-hemisphere interactions mainly in the beta and gamma bands and increasing across-hemisphere interactions mainly in the alpha and beta bands. Moreover, the number of hubs decreased in the alpha and beta bands, but the centrality of some fundamental regions such as the Posterior Cingulate Cortex (PCC), Supplementary Motor Area (SMA) and Middle Prefrontal Cortex (MPFC) remained strong in all bands, associated to an increase of the Global Efficiency and a decrease of Modularity. As a comparison, we applied orthogonalization on connectomes and ran the same topological analyses. The correlation values were considerably reduced, and orthogonalization mainly decreased local within-hemisphere interactions in all bands, similarly to GCS. Notably, the centrality of the PCC, SMA and MPFC was preserved in all bands, as for GCS, together with other hubs in the posterior parietal regions. Overall, leakage correction removes spurious local connections, but confirms the role of dynamic hub regions, specifically the anterior and posterior cingulate, in integrating information in the brain at rest

Exploiting the Hierarchical Morphology of Single-Walled and Multi-Walled Carbon Nanotube Films for Highly Hydrophobic Coatings

Self-assembled hierarchical solid surfaces are very interesting for wetting phenomena, as observed in a variety of natural and artificial surfaces. Here, we report single-walled (SWCNT) and multi-walled carbon nanotube (MWCNT) thin films realized by a simple, rapid, reproducible, and inexpensive filtration process from an aqueous dispersion, that was deposited at room temperature by a dry-transfer printing method on glass. Furthermore, the investigation of carbon nanotube films through scanning electron microscopy (SEM) reveals the multi-scale hierarchical morphology of the self-assembled carbon nanotube random networks. Moreover, contact angle measurements show that hierarchical SWCNT/MWCNT composite surfaces exhibit a higher hydrophobicity (contact angles of up to 137{\deg}) than bare SWCNT (110{\deg}) and MWCNT (97{\deg}) coatings, thereby confirming the enhancement produced by the surface hierarchical morphology.Comment: 7 pages, 5 figures, This article is part of the Thematic Series "Self-assembly of nanostructures and nanomaterials

Super-Hydrophobic Multi-Walled Carbon Nanotube Coatings for Stainless Steel

We have taken advantage of the native surface roughness and the iron content of AISI 316 stainless steel to direct grow multi-walled carbon nanotube (MWCNT) random networks by chemical vapor deposition (CVD) at low-temperature ($< 1000^{\circ}$C), without the addition of any external catalysts or time-consuming pre-treatments. In this way, super-hydrophobic MWCNT films on stainless steel sheets were obtained, exhibiting high contact angle values ($154^{\circ}$) and high adhesion force (high contact angle hysteresis). Furthermore, the investigation of MWCNT films at scanning electron microscopy (SEM) reveals a two-fold hierarchical morphology of the MWCNT random networks made of hydrophilic carbonaceous nanostructures on the tip of hydrophobic MWCNTs. Owing to the Salvinia effect, the hydrophobic and hydrophilic composite surface of the MWCNT films supplies a stationary super-hydrophobic coating for conductive stainless steel. This biomimetical inspired surface not only may prevent corrosion and fouling but also could provide low-friction and drag-reduction.Comment: 6 pages, 3 figure

A Multiscale Thermo-Fluid Computational Model for a Two-Phase Cooling System

In this paper, we describe a mathematical model and a numerical simulation method for the condenser component of a novel two-phase thermosyphon cooling system for power electronics applications. The condenser consists of a set of roll-bonded vertically mounted fins among which air flows by either natural or forced convection. In order to deepen the understanding of the mechanisms that determine the performance of the condenser and to facilitate the further optimization of its industrial design, a multiscale approach is developed to reduce as much as possible the complexity of the simulation code while maintaining reasonable predictive accuracy. To this end, heat diffusion in the fins and its convective transport in air are modeled as 2D processes while the flow of the two-phase coolant within the fins is modeled as a 1D network of pipes. For the numerical solution of the resulting equations, a Dual Mixed-Finite Volume scheme with Exponential Fitting stabilization is used for 2D heat diffusion and convection while a Primal Mixed Finite Element discretization method with upwind stabilization is used for the 1D coolant flow. The mathematical model and the numerical method are validated through extensive simulations of realistic device structures which prove to be in excellent agreement with available experimental data

Optimal design of the ideal grounded tuned mass damper inerter for comfort performances improvement in footbridges with practical implementation considerations

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High-spectral-purity laser system for the AURIGA detector optical readout

We describe a low-frequency-noise laser system conceived for the readout of small mechanical vibrations. The system consists of a Nd:YAG source stabilized to a high-finesse Fabry–Perot cavity and achieves the best performance in the range 1–10 kHz with a minimum residual noise of 4×10-3 Hz/Hz. We perform an extended characterization of the frequency stability by means of an independent optical cavity and we also measure the residual fluctuations after transmission through an optical fiber. Our apparatus is optimized for use in an optical readout for the gravitational wave detector AURIGA, where a laser system with the characteristics reported here will allow an improvement of one order of magnitude in the detector sensitivity

An Application of the Harmony-Search Multi-Objective (HSMO) Optimization Algorithm for the Solution of Pump Scheduling Problem☆

Abstract In hydraulic systems, water is often pumped to reach higher elevations, so as to ensure the minimum required pressure and guarantee adequate service level. However, pumps cannot be instantly activated and people do not consume the resource in uniform mode throughout the day. To avoid direct pumping, water can be stored in tanks at a higher elevation, so that it can be supplied whenever there is a higher demand. Because of the significant costs required for pumping, energy-saving in water supply systems is one of the most challenging issues to ensure optimal management of water systems. Careful scheduling of pumping operations may lead not only to energy savings, but alsoto prevent damages, as consequence of reduction of operation times and switches. By means of computer simulation, an optimal schedule of pumps can be achieved using optimization algorithms. In this paper, a harmony-search multi-objective (HSMO) optimization approach is adapted to the pump scheduling problem. The model interfaces with the popular hydraulic solver, EPANET 2.0, to check the hydraulic constraints and to evaluate the performances of the selected schedules. Penalties are introduced in the objective function in case of violation of the hydraulic constraints. The model is applied to a case study, showing that the results are comparable with those of competitive meta-heuristic algorithms (e.g. Genetic Algorithms) and pointing out the suitability of the HSMO algorithm for pumping optimization

Direct pulp capping with an adhesive system in management of a complicated incisor fracture: a three-year follow-up case report

Summary Objectives This article describes a direct pulp capping with an adhesive system and an immediate reattachment of the intact fractured tooth fragment after an impact trauma to the maxillary lateral incisor that caused a complicated crown fracture and pulpal exposure. Materials and methods In this case, a simple reattachment technique was performed without additional preparation. A hybridization of the exposed dentin with an adhesive system was chosen to protect the pulp-dentin interface and bonding the tooth fragment as precisely as possible. A resin composite was used to fill the discontinuity between the fragment and the tooth. The clinical procedure can be considered safe and simple. Results and conclusions After three years, the tooth had satisfying esthetics and excellent function and pulp was still vital with no signs or symptoms of inflammation. Clinician should be updated with the current methods and techniques for the management of complicated tooth fracture

A Model Driven Approach to Water Resource Analysis based on Formal Methods and Model Transformation

AbstractSeveral frameworks have been proposed in literature in order to cope with critical infrastructure modelling issues, and almost all rely on simulation techniques. Anyway simulation is not enough for critical systems, where any problem may lead to consistent loss in money and even human lives. Formal methods are widely used in order to enact exhaustive analyses of these systems, but their complexity grows with system dimension and heterogeneity. In addition, experts in application domains could not be familiar with formal modelling techniques. A way to manage complexity of analysis is the use of Model Based Transformation techniques: analysts can express their models in the way they use to do and automatic algorithms translate original models into analysable ones, reducing analysis complexity in a completely transparent way.In this work we describe an automatic transformation algorithm generating hybrid automata for the analysis of a natural water supply system. We use real system located in the South of Italy as case study