Zero sequence blocking transformers for multi-pulse rectifier in aerospace applications

The second session of the 109th Congress may well face decisions regarding the preparation of U.S. military forces for stability missions, a broad doctrinal term of which a major subset is peace operations. A November 28, 2005, Department of Defense (DOD) directive that designates stability operations as “core missions” of the U.S. military marks a major shift on the future necessity of performing peacekeeping and related stability operations (also known as stabilization and reconstruction operations)

Decision table for classifying point sources based on FIRST and 2MASS databases

With the availability of multiwavelength, multiscale and multiepoch astronomical catalogues, the number of features to describe astronomical objects has increases. The better features we select to classify objects, the higher the classification accuracy is. In this paper, we have used data sets of stars and quasars from near infrared band and radio band. Then best-first search method was applied to select features. For the data with selected features, the algorithm of decision table was implemented. The classification accuracy is more than 95.9%. As a result, the feature selection method improves the effectiveness and efficiency of the classification method. Moreover the result shows that decision table is robust and effective for discrimination of celestial objects and used for preselecting quasar candidates for large survey projects.Comment: 10 pages. accepted by Advances in Space Researc

Simulation of action potential propagation based on the ghost structure method

In this paper, a ghost structure (GS) method is proposed to simulate the monodomain model in irregular computational domains using finite difference without regenerating body-fitted grids. In order to verify the validity of the GS method, it is first used to solve the Fitzhugh-Nagumo monodomain model in rectangular and circular regions at different states (the stationary and moving states). Then, the GS method is used to simulate the propagation of the action potential (AP) in transverse and longitudinal sections of a healthy human heart, and with left bundle branch block (LBBB). Finally, we analyze the AP and calcium concentration under healthy and LBBB conditions. Our numerical results show that the GS method can accurately simulate AP propagation with different computational domains either stationary or moving, and we also find that LBBB will cause the left ventricle to contract later than the right ventricle, which in turn affects synchronized contraction of the two ventricles

Presynaptic regulation of the inhibitory transmission by GluR5-containing kainate receptors in spinal substantia gelatinosa

GluR5-containing kainate receptors (KARs) are known to be involved in nociceptive transmission. Our previous work has shown that the activation of presynaptic KARs regulates GABAergic and glycinergic synaptic transmission in cultured dorsal horn neurons. However, the role of GluR5-containing KARs in the modulation of inhibitory transmission in the spinal substantia gelatinosa (SG) in slices remains unknown. In the present study, pharmacological, electrophysiological and genetic methods were used to show that presynaptic GluR5 KARs are involved in the modulation of inhibitory transmission in the SG of spinal slices in vitro. The GluR5 selective agonist, ATPA, facilitated the frequency but not amplitude of spontaneous inhibitory postsynaptic currents (sIPSCs) in SG neurons. ATPA increased sIPSC frequency in all neurons with different firing patterns as delayed, tonic, initial and single spike patterns. The frequency of either GABAergic or glycinergic sIPSCs was significantly increased by ATPA. ATPA could also induce inward currents in all SG neurons recorded. The frequency, but not amplitude, of action potential-independent miniature IPSCs (mIPSCs) was also facilitated by ATPA in a concentration-dependent manner. However, the effect of ATPA on the frequency of either sIPSCs or mIPSCs was abolished in GluR5(-/- )mice. Deletion of the GluR5 subunit gene had no effect on the frequency or amplitude of mIPSCs in SG neurons. However, GluR5 antagonist LY293558 reversibly inhibited sIPSC and mIPSC frequencies in spinal SG neurons. Taken together, these results suggest that GluR5 KARs, which may be located at presynaptic terminals, contribute to the modulation of inhibitory transmission in the SG. GluR5-containing KARs are thus important for spinal sensory transmission/modulation in the spinal cord

Surrogate models based on machine learning methods for parameter estimation of left ventricular myocardium

A long-standing problem at the frontier of biomechanical studies is to develop fast methods capable of estimating material properties from clinical data. In this paper, we have studied three surrogate models based on machine learning (ML) methods for fast parameter estimation of left ventricular (LV) myocardium. We use three ML methods named K-nearest neighbour (KNN), XGBoost and multi-layer perceptron (MLP) to emulate the relationships between pressure and volume strains during the diastolic filling. Firstly, to train the surrogate models, a forward finite-element simulator of LV diastolic filling is used. Then the training data are projected in a low-dimensional parametrized space. Next, three ML models are trained to learn the relationships of pressure–volume and pressure–strain. Finally, an inverse parameter estimation problem is formulated by using those trained surrogate models. Our results show that the three ML models can learn the relationships of pressure–volume and pressure–strain very well, and the parameter inference using the surrogate models can be carried out in minutes. Estimated parameters from both the XGBoost and MLP models have much less uncertainties compared with the KNN model. Our results further suggest that the XGBoost model is better for predicting the LV diastolic dynamics and estimating passive parameters than other two surrogate models. Further studies are warranted to investigate how XGBoost can be used for emulating cardiac pump function in a multi-physics and multi-scale framework