A system for the exposure of small laboratory animals to a 25-mT60-Hz alternating or traveling magnetic field

A versatile exposure system which can be used to investigate the effects of a 60-Hz alternating magnetic field or traveling magnetic field on small laboratory animals is described. Special attention was given to the design of the electric circuit to simplify the supply requirements and to keep the overall current to a minimum. A magnetic field having a flux density up to 30 mT (300 G) can be generated, and a traveling magnetic field is obtained by reconnecting the coils to a three-phase supply. The total magnetic field due to the currents in the three coils used in the exposure system is analyzed. A computer program was written to evaluate the magnetic field in the region where the animals are located. The difference observed between measured and computed values is attributed to the representation of the multiturn, multilayer coils by equivalent single-turn coils     

A 2D quadrangular pyramid photoelectric autocollimator with extended angle measurement range

A photoelectric autocollimator with high accuracy and extended measurement range based on the quadrangular pyramid is proposed, and the corresponding algorithms are also deduced. A new image processing algorithm has been proposed to improve the accuracy, and the corresponding errors are also estimated, the error does not exceed half a pixel when the distance between the marks more than two radii. The experimental results have verified that the measurement range of the proposed two-dimensional (2D) quadrangular pyramid photoelectric autocollimator can be increased times than that of the flat mirror photoelectric autocollimator from 10′ to 15′. The accuracy is better than 1″ when the deflection is less than 15′.     

Identification of reduced-order thermal therapy models using thermal MR images: theory and validation

In this paper, we develop and validate a method to identify computationally efficient site- and patient-specific models of ultrasound thermal therapies from MR thermal images. The models of the specific absorption rate of the transduced energy and the temperature response of the therapy target are identified in the reduced basis of proper orthogonal decomposition of thermal images, acquired in response to a mild thermal test excitation. The method permits dynamic reidentification of the treatment models during the therapy by recursively utilizing newly acquired images. Such adaptation is particularly important during high-temperature therapies, which are known to substantially and rapidly change tissue properties and blood perfusion. The developed theory was validated for the case of focused ultrasound heating of a tissue phantom. The experimental and computational results indicate that the developed approach produces accurate low-dimensional treatment models despite temporal and spatial noises in MR images and slow image acquisition rate.     

Efficient Output Mode Converter for 30 GHz Gyroklystron at IAP

An output mode converter for Ka-band multi-MW gyroklystron in the Institute of Applied Physics (IAP) operating in the TE₅₃ mode is suggested. Two variants of the converter, aimed for different applications, are presented: the TE₅₃ to TE₀₁ mode converter with power output along the device axis and the TE₅₃ mode to Gaussian wavebeam quasi-optical converter with a visor. The suggested designs include the built-in electron beam collector. The converters were designed using a new synthesis algorithm, which implies iterative improvement of the waveguide wall shape in order to achieve high efficiency. The calculation results were proven by HFSS simulation and low-power tests of one version of the converter.     

Structured Output SVM for Remote Sensing Image Classification

Traditional kernel classifiers assume independence among the classification outputs. As a consequence, each misclassification receives the same weight in the loss function. Moreover, the kernel function only takes into account the similarity between input values and ignores possible relationships between the classes to be predicted. These assumptions are not consistent for most of real-life problems. In the particular case of remote sensing data, this is not a good assumption either. Segmentation of images acquired by airborne or satellite sensors is a very active field of research in which one tries to classify a pixel into a predefined set of classes of interest (e.g. water, grass, trees, etc.). In this situation, the classes share strong relationships, e.g. a tree is naturally (and spectrally) more similar to grass than to water. In this paper, we propose a first approach to remote sensing image classification using structured output learning. In our approach, the output space structure is encoded using a hierarchical tree, and these relations are added to the model in both the kernel and the loss function. The methodology gives rise to a set of new tools for structured classification, and generalizes the traditional non-structured classification methods. Comparison to standard SVM is done numerically, statistically and by visual inspection of the obtained classification maps. Good results are obtained in the challenging case of a multispectral image of very high spatial resolution acquired with QuickBird over a urban area.     

Interpenetrated Gel Polymer Binder for High‐Performance Silicon Anodes in Lithium‐ion Batteries

Silicon has attracted ever‐increasing attention as a high‐capacity anode material in Li‐ion batteries owing to its extremely high theoretical capacity. However, practical application of silicon anodes is seriously hindered by its fast capacity fading as a result of huge volume changes during the charge/discharge process. Here, an interpenetrated gel polymer binder for high‐performance silicon anodes is created through in‐situ crosslinking of water‐soluble poly(acrylic acid) (PAA) and polyvinyl alcohol (PVA) precursors. This gel polymer binder with deformable polymer network and strong adhesion on silicon particles can effectively accommodate the large volume change of silicon anodes upon lithiation/delithiation, leading to an excellent cycling stability and high Coulombic efficiency even at high current densities. Moreover, high areal capacity of ～4.3 mAh/cm² is achieved based on the silicon anode using the gel PAA–PVA polymer binder with a high mass loading. In view of simplicity in using the water soluble gel polymer binder, it is believed that this novel binder has a great potential to be used for high capacity silicon anodes in next generation Li‐ion batteries, as well as for other electrode materials with large volume change during cycling.     

Determination of the average channel temperature of GaN MOSHFETs under continuous wave and periodic-pulsed RF operational conditions

We present a method to determine the average device channel temperature of AlGaN/GaN metal–oxide–semiconductor heterostructure field effect transistors (MOSHFETs) in the time domain under continuous wave (CW) and periodic-pulsed RF (radiation frequency) operational conditions. The temporal profiles of microwave output power densities of GaN MOSHFETs were measured at 2 GHz under such conditions and used for determination of the average channel temperature. The measurement technique in this work is also being utilized to determine the thermal time constant of the devices. Analytical temporal solutions of temperature profile in MOSHFETs are provided to support the method. The analytical solutions can also apply to generic field effect transistors (FETs) with an arbitrary form of time-dependent heat input at the top surface of the wafer. It is found that the average channel temperature of GaN MOSHFETs on a 300 μm sapphire substrate with the output power of 10 W/mm can be over 400 °C in the CW mode while the average channel temperature of GaN MOSHFETs on a SiC substrate with the same thickness only reaches 50 °C under the same condition. The highest average channel temperature in a pulsed RF mode will vary with respect to the duty cycle of the pulse and type of the substrate.     

Flash Lamps as Ignition and Initiation Sources of the VS-2 Pyrotechnic Composition

In the present work it is found that the pyrotechnic composition VS-2 can be initiated with flash lamps IFC-500 and EVIS. VS-2 pyrotechnic composition contains 90% of mercury（Ⅱ） 5-hydrazinotetrazolate perchlorate and 10% of optically transparent copolymer of 2-methyl-5-vinyltetrazole and methacrylic acid （PVMT）. We have found that the flash lamps make it possible to initiate combustion of VS-2 composition with its transition to detonation both in cylindrical charges placed in brass caps of 5 mm diameter and 2 mm high， and film charges with 10 mm×80 mm in size and surface weights of 60 mg·cm^-2 and 90 mg·cm^-2， showing ignition delay times 10 μs and 3 μs， respectively. We also measured detonation velocities for VS-2 composition film charges， which were 4375-4505 m·s^-1 （of the charge being surface mass 60 mg·cm^-2） and 4221-4281 m·s^-1 （of the charge being surface mass 90 mg·cm^-2） and their blasting action on the aluminum plate. The depths of the normal shock wave imprints at the charge-barrier interface were 0.6-0.7 mm （for surface mass of the film charges 60 mg·cm^-2） and 1.2-1.3 mm （for surface mass of the film charges 90 mg·cm^-2）.     

Ascertaining the importance of neurons to develop better brain-machine interfaces

In the design of brain-machine interface (BMI) algorithms, the activity of hundreds of chronically recorded neurons is used to reconstruct a variety of kinematic variables. A significant problem introduced with the use of neural ensemble inputs for model building is the explosion in the number of free parameters. Large models not only affect model generalization but also put a computational burden on computing an optimal solution especially when the goal is to implement the BMI in low-power, portable hardware. In this paper, three methods are presented to quantitatively rate the importance of neurons in neural to motor mapping, using single neuron correlation analysis, sensitivity analysis through a vector linear model, and a model-independent cellular directional tuning analysis for comparisons purpose. Although, the rankings are not identical, up to sixty percent of the top 10 ranking cells were in common. This set can then be used to determine a reduced-order model whose performance is similar to that of the ensemble. It is further shown that by pruning the initial ensemble neural input with the ranked importance of cells, a reduced sets of cells (between 40 and 80, depending upon the methods) can be found that exceed the BMI performance levels of the full ensemble.