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Paired associative stimulation has been used in stroke patients as an innovative recovery treatment. However, the mechanisms underlying the therapeutic effectiveness of paired associative stimulation on neurological function remain unclear. In this study, rats were randomly divided into middle cerebral occlusion model (MCAO) and paired associated magnetic stimulation (PAMS) groups. The MCAO rat model was produced by middle cerebral artery embolization. The PAMS group received PAMS on days 3 to 20 post MCAO. The MCAO group received sham stimulation, three times every week. Within 18 days after ischemia, rats were subjected to behavioral experiments-the foot-fault test, the balance beam walking test, and the ladder walking test. Balance ability was improved on days 15 and 17, and the foot-fault rate was less in their affected limb on day 15 in the PAMS group compared with the MCAO group. Western blot assay showed that the expression levels of brain derived neurotrophic factor, glutamate receptor 2/3, postsynaptic density protein 95 and synapsin-1 were significantly increased in the PAMS group compared with the MCAO group in the ipsilateral sensorimotor cortex on day 21. Resting-state functional magnetic resonance imaging revealed that regional brain activities in the sensorimotor cortex were increased in the ipsilateral hemisphere, but decreased in the contralateral hemisphere on day 20. By finite element simulation, the electric field distribution showed a higher intensity, of approximately 0.4 A/m2, in the ischemic cortex compared with the contralateral cortex in the template. Together, our findings show that PAMS upregulates neuroplasticity-related proteins, increases regional brain activity, and promotes functional recovery in the affected sensorimotor cortex in the rat MCAO model. The experiments were approved by the Institutional Animal Care and Use Committee of Fudan University, China (approval No. 201802173S) on March 3, 2018.

Natural gas exists in considerable quantities in tight reservoirs. Tight formations are rocks with very tiny or poorly connected pors that make flow through them very difficult, i.e., the permeability is very low. The mixed finite element method (MFEM), which is locally conservative, is suitable to simulate the flow in porous media. This paper is devoted to developing a mixed finite element (MFE) technique to simulate the gas transport in low permeability reservoirs. The mathematical model, which describes gas transport in low permeability formations, contains slippage effect, as well as adsorption and diffusion mechanisms. The apparent permeability is employed to represent the slippage effect in low-permeability formations. The gas adsorption on the pore surface has been described by Langmuir isotherm model, while the Peng-Robinson equation of state is used in the thermodynamic calculations. Important compatibility conditions must hold to guarantee the stability of the mixed method by adding additional constraints to the numerical discretization. The stability conditions of the MFE scheme has been provided. A theorem and three lemmas on the stability analysis of the mixed finite element method (MFEM) have been established and proven. A semi-implicit scheme is developed to solve the governing equations. Numerical experiments are carried out under various values of the physical parameters.

The combination of magnetoresistive (MR) element and magnetic flux concentrators (MFCs) offers highly sensitive magnetic field sensors. To maximize the effect of MFC, the geometrical design between the MR element and MFCs is critical. In this paper, we present simulation and experimental studies on the effect of the geometrical relationship between current-in-plane giant magnetoresistive (GMR) element and MFCs made of a NiFeCuMo film. Finite element method (FEM) simulations showed that although an overlap between the MFCs and GMR element enhances their magneto-static coupling, it can lead to a loss of magnetoresistance ratio due to a magnetic shielding effect by the MFCs. Therefore, we propose a comb-shaped GMR element with alternate notches and fins. The FEM simulations showed that the fins of the comb-shaped GMR element provide a strong magneto-static coupling with the MFCs, whereas the electric current is confined within the main body of the comb-shaped GMR element, resulting in improved sensitivity. We experimentally demonstrated a higher sensitivity of the comb-shaped GMR sensor (36.5 %/mT) than that of a conventional rectangular GMR sensor (28 %/mT).

NRC publication: Yes

This paper describes a newly-developed damage-based fatigue life model for the longterm reliability assessment of drawn steel wires and wire ropes. The methodology is based on the computed local stress field in the critical trellis contact zone of a stranded wire rope by FE simulations and the estimated fretting damage of the drawn wire material. A case study using a single strand (1x7) steel wire rope with 5.43 mm-dia. drawn wires is employed to demonstrate the damage-based fatigue life prediction procedures. Under applied tensile loading with peak stress corresponding to 50%MBL (DP = 145 kN, R = 0.1), the von Mises stress cycles in-phase and with an identical stress ratio to the applied axial load. The damage initiation life at the trellis contact along the core wire is No = 673 cycles with an additional 589 load cycles to reach the first separation of the material point. The threshold load cycle for the fretting fatigue damage is predicted to be 12.3%MBL. An improved data set of the damage model parameters of the drawn steel wires is indispensable in achieving an accurate and validated life prediction model.

The miniaturization trend leads to the development of a graphene based nanoelectromechanical (NEM) switch to fulfill the high demand in low power device applications. In this article, we highlight the finite element (FEM) simulation of the graphene-based NEM switches of fixed-fixed ends design with beam structures which are perforated and intact. Pull-in and pull-out characteristics are analyzed by using the FEM approach provided by IntelliSuite software, version 8.8.5.1. The FEM results are consistent with the published experimental data. This analysis shows the possibility of achieving a low pull-in voltage that is below 2 V for a ratio below 15:0.03:0.7 value for the graphene beam length, thickness, and air gap thickness, respectively. The introduction of perforation in the graphene beam-based NEM switch further achieved the pull-in voltage as low as 1.5 V for a 250 nm hole length, 100 nm distance between each hole, and 12-number of hole column. Then, a von Mises stress analysis is conducted to investigate the mechanical stability of the intact and perforated graphene-based NEM switch. This analysis shows that a longer and thinner graphene beam reduced the von Mises stress. The introduction of perforation concept further reduced the von Mises stress at the graphene beam end and the beam center by approximately ~20–35% and ~10–20%, respectively. These theoretical results, performed by FEM simulation, are expected to expedite improvements in the working parameter and dimension for low voltage and better mechanical stability operation of graphene-based NEM switch device fabrication.

In the present paper, finite element analysis of the knee joint is performed for stress and strain estimation of the knee joint for osteoarthritis patients. Osteoarthritis (OA), called the wear and tear arthritis is commonly occurring arthritis wherein a gradual loss of cartilage from the joints are observed. This leads to the joint bones rubbing quite close against one another with less amount of shock-absorbing done by the cartilage causing pain, stiffness, swelling, decreased movability and bone spur formation can be observed. It is mostly observed in patients above 45 years old, but weight and gender are also some of the factors forcing a quick onset of the disease. Using modelling software Blender, a solid model is made of the bone component, namely tibia, fibula, femur and patella as well as Ligaments and cartilages. Using finite element simulation software, analysis is done to determine the level of stress under various forces on the joint. The knee joint experiences a maximum stress and strain of 2.352 MPa and 0.02454 respectively which are within safe static condition. The study can be further extended to predict the danger of failure for the patients having osteoarthritis conditions which in turn will help to take a preventive measure for the knee joint.

Deformation studies at grain level have been performed in order to model how individual crystals in a polycrystalline material deform. The experiment was carried out by plane-strain compression of a high-purity polycrystalline aluminium with columnar grain structure with near 〈100〉 fibre texture parallel to the constrained direction in the channel die. This structure was chosen to allow a fully three-dimensional characterization of the grain structure. The grain orientations were mapped by orientation image microscopy, as the directionally solidified material was deformed in steps of 10% to a total height reduction of 40%. The grains were found either to show nearly uniform rotations or to split into two types of deformation bands, either with repeating orientation fields or with non-repeating orientation fields. The Taylor model and the finite-element method (FEM) were, as usual, quite successful in predicting the average deformation texture, but the Taylor model failed totally to predict the rotation of individual grains. The FEM was more successful in predicting the individual grain rotations but did not, as in a previous study, predict the morphology of the deformation bands. The significant discovery, made here, was that it appeared possible to model the local deformation at a grain scale, from the observed individual deviations of the grain rotations from those predicted if each grain underwent just the plane-strain conditions imposed on the sample. Plastic work rates were computed allowing four shears (two shears in each of the two contact planes) that are compatible with the channel-die geometry. It was found that in all the 'hard' grains (those with high Taylor factors), the additional shears (in type and magnitude) that minimized the plastic energy dissipation rate were the same shears that were needed to match the observed grain rotations. Adjacent Taylor 'soft' grains were found to have been subjected to the additional shears imposed by their neighbouring hard grains. This was true even when these shears raised the plastic work of the soft grains. This effect was most marked when the soft grains were small in size. These additional shears found by this plastic work analysis were consistent with the observed additional shear seen in the overall shape change of the sample. The grains forming non-repeating orientation fields had low initial Taylor factors and were surrounded by high-Taylor-factor grains, usually of larger size, but which had adopted somewhat different extra shears. The grains showing repeating orientation fields were found to have an orientation, near 'cube', (001) 〈100〉, which was initially unstable, leading to a break-up into different orientation fields when deformed. These differing deformation bands in the cube grains followed different strain paths, which also minimized their plastic work.

Towards the characterization of viscoelasticity of the soft tissue, which is an important biomarker, this study aims to investigate the effectiveness of the Harmonic Shear Wave Elastography (HSWE) framework by analyzing the frequency-dependent phase velocity maps, using a 3D Finite-Element-based simulation framework. Here, we developed and verified a 3D finite-element framework to accurately model the tissue displacement under a multi-frequency HSWE setting. The HSWE results were compared using both simulation and phantom experiments against those from the Pulsed Shear Wave Elastography (PSWE) method which is widely used in shear wave elastography problems. Particularly, we analyzed the group and frequency-dependent phase velocities, focusing on the frequency range of 300 to 800 Hz. Additionally, we conducted parametric studies to examine the effects of inclusion size, stiffness, and viscosity. The HSWE framework provided accurate measurements of group and phase velocities, comparable to those obtained using the PSWE method. The median differences between HSWE and PSWE results were 5.21 % and 9.14 % for group and phase velocities, respectively, in simulations, and 13.98 % and 22.32 % for group and phase velocities, respectively, in phantom experiments. Parametric studies showed that the HSWE framework is effective in accurately characterizing the location, size, stiffness and viscoelastic properties of tissue inclusions, with notable improvements over PSWE, particularly for smaller inclusions at lower frequencies. Future work will focus on optimizing the HSWE framework for clinical use and developing inverse models to estimate the underlying viscoelastic shear moduli of the tissue to enhance its diagnostic capabilities.

The human heart is enclosed in the pericardial cavity. The pericardium consists of a layered thin sac and is separated from the myocardium by a thin film of fluid. It provides a fixture in space and frictionless sliding of the myocardium. The influence of the pericardium is essential for predictive mechanical simulations of the heart. However, there is no consensus on physiologically correct and computationally tractable pericardial boundary conditions. Here, we propose to model the pericardial influence as a parallel spring and dashpot acting in normal direction to the epicardium. Using a four-chamber geometry, we compare a model with pericardial boundary conditions to a model with fixated apex. The influence of pericardial stiffness is demonstrated in a parametric study. Comparing simulation results to measurements from cine magnetic resonance imaging reveals that adding pericardial boundary conditions yields a better approximation with respect to atrioventricular plane displacement, atrial filling, and overall spatial approximation error. We demonstrate that this simple model of pericardial–myocardial interaction can correctly predict the pumping mechanisms of the heart as previously assessed in clinical studies. Utilizing a pericardial model not only can provide much more realistic cardiac mechanics simulations but also allows new insights into pericardial–myocardial interaction which cannot be assessed in clinical measurements yet.