다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

An overview of transmission/reflection-based methods for the electromagnetic characterisation of materials is presented. The paper initially describes the most popular approaches for the characterisation of bulk materials in terms of dielectric permittivity and magnetic permeability. Subsequently, the limitations and the methods aimed at removing the ambiguities deriving from the application of the classical Nicolson–Ross–Weir direct inversion are discussed. The second part of the paper is focused on the characterisation of partially conductive thin sheets in terms of surface impedance via waveguide setups. All the presented measurement techniques are applicable to conventional transmission reflection devices such as coaxial cables or waveguides.

Electromagnetic Characterisation of Materials by Using Transmission/Reflection (T/R) Devices

The main risks associated with magnetic resonance imaging (MRI) have been extensively reported and studied; for example, everyday objects may turn into projectiles, energy deposition can cause burns, varying fields can induce nerve stimulation, and loud noises can lead to auditory loss. The present review article is geared toward providing intuition about the physical mechanisms that give rise to these risks. On the one hand, excellent literature already exists on the practical aspect of risk management, with clinical workflow and recommendations. On the other hand, excellent technical articles also exist that explain these risks from basic principles of electromagnetism. We felt that an underserved niche might be found between the two, ie, somewhere between basic science and practical advice, to help develop intuition about electromagnetism that might prove of practical value when working around MR scanners. Following a wide-ranging introduction, risks originating from the main magnetic field, the excitation RF electromagnetic field, and switching of the imaging gradients will be presented in turn.

Level of Evidence: 5

Technical Efficacy: 1

J. Magn. Reson. Imaging 2018;47:28–43.

The physics of MRI safety

Understanding human brain function, brain development and brain dysfunction is one of the great challenges of the twentyfirst century. Biomedical imaging has now run up against a number of technical constraints that are exposing limits to its potential. In order to overcome the current limits to high-field magnetic resonance cerebral imaging (MRI) and unleash its fullest potential, the CEA has built NeuroSpin, an ultra-high-field neuroimaging facility at its Saclay centre (in the Essonne). NeuroSpin already boasts three fully operational MRI systems. The first is a 3-tesla high-field system and the second is a very-high-field 7-tesla system, both of which are dedicated to clinical studies and investigations in humans, while the third is an ultra-high-field 17.65-tesla system designed for studies on small animals. In 2011, NeuroSpin will be commissioning an 11.7-tesla ultra-high-field system of unprecedented power that is designed for research on human subjects. The level of the magnetic field and the scale required will make this joint French-German project to build the magnet a breakthrough in the international arena. Ultra-high-field magnetic resonance imaging

Ultra-High Field Magnetic Resonance Imaging

To determine whether microwave (MW) radiation induces neural cell apoptosis, differentiated PC12 cells and Wistar rats were exposed to 2.856GHz for 5min and 15min, respectively, at an average power density of 30 mW/cm 2 . JC-1 and TUNEL staining detected significant apoptotic events, such as the loss of mitochondria membrane potential and DNA fragmentation, respectively. Transmission electron microscopy and Hoechst staining were used to observe chromatin ultrastructure and apoptotic body formation. Annexin V-FITC/PI double staining was used to quantify the level of apoptosis. The expressions of Bax, Bcl-2, cytochrome c, cleaved caspase-3 and PARP were examined by immunoblotting or immunocytochemistry. Caspase-3 activity was measured using an enzyme-linked immunosorbent assay. The results showed chromatin condensation and apoptotic body formation in neural cells 6h after microwave exposure. Moreover, the mitochondria membrane potential decreased, DNA fragmentation increased, leading to an increase in the apoptotic cell percentage. Furthermore, the ratio of Bax/Bcl-2, expression of cytochrome c, cleaved caspase-3 and PARP all increased. In conclusion, microwave radiation induced neural cell apoptosis via the classical mitochondria-dependent caspase-3 pathway. This study may provide the experimental basis for further investigation of the mechanism of the neurological effects induced by microwave radiation.

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Neural cell apoptosis induced by microwave exposure through mitochondria-dependent caspase-3 pathway.

The production of mitotic spindle disturbances and activation of the apoptosis pathway in V79 Chinese hamster cells by continuous 2.45 GHz microwaves exposure were studied, in order to investigate possible non-thermal cell damage. We demonstrated that microwave (MW) exposure at the water resonance frequency was able to induce alteration of the mitotic apparatus and apoptosis as a function of the applied power densities (5 and 10mW/cm(2)), together with a moderate reduction in the rate of cell division. After an exposure time of 15 min the proportion of aberrant spindles and of apoptotic cells was significantly increased, while the mitotic index decreased as well, as compared to the untreated V79 cells. Additionally, in order to understand if the observed effects were due to RF exposure per se or to a thermal effect, V79 cells were also treated in thermostatic bath mimicking the same temperature increase recorded during microwave emission. The effect of temperature on the correct assembly of mitotic spindles was negligible up to 41°C, while apoptosis was induced only when the medium temperature achieved 40°C, thus exceeding the maximum value registered during MW exposure. We hypothesise that short-time MW exposures at the water resonance frequency cause, in V79 cells, reversible alterations of the mitotic spindle, this representing, in turn, a pro-apoptotic signal for the cell line.

Non-thermal effects of 2.45 GHz microwaves on spindle assembly, mitotic cells and viability of Chinese hamster V-79 cells.

The computational cost of topology optimization based on the binary particle swarm optimization is greatly reduced by the use of deep neural networks (DNNs). A first convolutional neural network (CNN) is trained with data coming from finite-element analysis (FEA) with the aim of correctly estimating the output quantity (a motor torque in the proposed case study). A second CNN is trained to give as output the boundary conditions [(BCs), expressed in terms of fields or potentials] to be used as BC of a reduced finite-element method (FEM) model, created in order to still be able to give the correct value of the output quantity. In the optimization phase, the torque properties are evaluated by the trained CNN, and only a reduced percentage of cases are reevaluated by either the full FEM model or the reduced FEM model. The overall computational time of the optimization procedure is significantly reduced.

Deep Learning and Reduced Models for Fast Optimization in Electromagnetics

Spiral resonators (SRs) are one of the most common typologies of resonant magnetic unit cell for the realization of metamaterials. The precise knowledge of their lumped electric properties ( RLC parameters) is of crucial importance in the metamaterial design. Thus, an accurate and unambiguous procedure for estimating the value of the RLC lumped parameters of compact SRs is introduced. The proposed procedure relies on a rigorous approach allowing a complete characterization of SRs also in terms of $Q$ -factor. The method is general and valid for other shapes of resonators. The estimations have been finally verified by performing measurements on fabricated SRs through a magnetic probe.

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Accurate Extraction of Equivalent Circuit Parameters of Spiral Resonators for the Design of Metamaterials

In this work, a topology optimization procedure is proposed and applied to the TEAM 25 problem, i.e., a model of a die press with an electromagnet for orientation of magnetic powder. The shape of the press is described as a free discretized profile, and its relation to the flux density in the cavity is simulated by finite element analysis (FEA) and learned by a deep neural network (DNN) model. The DNN is used as a surrogate model for optimization, aiming to obtain a desired flux density distribution in the cavity. Results are promising, as better accuracy is obtained with respect to the full FEA-based optimization approach with the reduced time cost. Once trained, the surrogate model can be used to efficiently solve a whole family of problems where a different target field distribution is defined.

A Deep Learning Surrogate Model for Topology Optimization

In this article, we introduce a general analytical procedure to unambiguously characterize a metasurface through its lumped circuital equivalent in resonant inductive Wireless Power Transfer (WPT) applications. The proposed model incorporates the finite extent of the slab, as well as the WPT near field operative regime and the presence of the particular driving/receiving coils arrangement, providing quantitative and easy-to-handle parameters which can be manipulated to achieve WPT performance enhancement. We first develop the theoretical background aimed at the lumped parameters extraction, which reveals, for WPT applications, more accurate and robust with respect to the conventional sub-wavelength homogenization theories based on infinite slab extent and impinging plane wave hypotheses. We provide some general guidelines for the design of metasurfaces for WPT performance enhancement based on the derived circuit model; afterwards, we numerically design a test-case consisting of two resonant coils (driver and receiver, respectively) with an interposed passive metasurface to verify the developed theory. Finally, we show some measurements performed on a fabricated prototype, that present an overall excellent agreement with both the lumped model and the numerical simulations.

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Nunzia Fontana

Papers

Non-thermal effects of 2.45 GHz microwaves on spindle assembly, mitotic cells and viability of Chinese hamster V-79 cells.

Deep Learning and Reduced Models for Fast Optimization in Electromagnetics

Accurate Extraction of Equivalent Circuit Parameters of Spiral Resonators for the Design of Metamaterials

A Deep Learning Surrogate Model for Topology Optimization

An Accurate Equivalent Circuit Model of Metasurface-Based Wireless Power Transfer Systems