Structures in superconducting YBa2Cu3O7−δ thin films investigated by magneto-optic technique

Using a reflection magneto-optic technique we have investigated natural inhomogeneities and artificial structures in YBCO thin films exposed to an external magnetic field. The artificial structures were mechanically scratched by scanning a diamond tip with different loading over the film surface. Alternatively planar structures with reduced oxygen content could be patterned by heating the YBCO film with a focused laser beam in nitrogen atmosphere. Depending on the laser annealing parameters different screening properties concerning the applied magnetic field could be achieved.As a magneto-optically active layer we used EuS films evaporated on glass as well as bismuth- and gallium-doped lutetium-iron-garnet films grown onto (111) oriented gadolinium-gal lium-gar net substrates by liquid phase epitaxy. In contrast to measurements with EuS films that show only weak faraday rotation for temperatures higher than 20 K the magneto-optic studies have been expanded to about 60 K by using the garnet films.     

Rheumatic heart disease in India

A cross-sectional study was carried out in rural areas of Jawan Block, District Aligarh, Uttar Pradesh, India, covering a total population of 3760 drawn from 11 villages. The total number of confirmed cases of rheumatic heart disease was 24 with a prevalence rate of 6.4 per 1000 of the general rural population. The prevalence of rheumatic heart disease increased with age until the age of 25 years. Females were more prone to rheumatic heart disease compared to males. Socio-economic class had a direct impact on the occurrence of rheumatic heart disease.     

Cost and sensitivity analysis for photovoltaic station in Kuwait

A full analysis is shown in this paper for the cost of kWh generated from photovoltaic station located in Kuwait. By using a 21 years weather data for Kuwait, the yearly generated energy was found by proposing the PV station capacity with known panels tilt angle. The cost of kWh generated from PV station was compared with the kWh generated from conventional units in the country. A sensitivity analysis was done to some factors; capital cost per installed PV peak watt, discount rate, and operating peak hours, which affect the cost of kWh production from both PV and conventional units. If the PV station is proposed to be installed in Kuwait, the capital cost per PV installed peak watt must be less than today's prices.     

Study of Lateral Spread of Ions Emitted from 2.3 kJ Plasma Focus with Hydrogen and Nitrogen Gases

The characteristics of ion beams of hydrogen and nitrogen with different filling pressures emitted from the plasma focus device of 2.3 kJ energy are investigated. CR-39 SSNTDs are employed for the registration of tracks of ions. The exposed detectors are etched in 6N NaOH solution at 70°C and then examined with an optical microscope. The ion flux is estimated to be of the order of 10^5–6 tracks/cm². The flux with the radial position does not exhibit any regular pattern of variation.     

On the application of Harris hawks optimization (HHO) algorithm to the design of microchannel heat sinks

Engineering with Computers - A novel Harris hawks optimization algorithm is applied to microchannel heat sinks for the minimization of entropy generation. In the formulation of the heat transfer...     

Automatic Channel Detection Using DNN on 2D Seismic Data

Geologists interpret seismic data to understand subsurface properties and subsequently to locate underground hydrocarbon resources. Channels are among the most important geological features interpreters analyze to locate petroleum reservoirs. However, manual channel picking is both time consuming and tedious. Moreover, similar to any other process dependent on human intervention, manual channel picking is error prone and inconsistent. To address these issues, automatic channel detection is both necessary and important for efficient and accurate seismic interpretation. Modern systems make use of real-time image processing techniques for different tasks. Automatic channel detection is a combination of different mathematical methods in digital image processing that can identify streaks within the images called channels that are important to the oil companies. In this paper, we propose an innovative automatic channel detection algorithm based on machine learning techniques. The new algorithm can identify channels in seismic data/images fully automatically and tremendously increases the efficiency and accuracy of the interpretation process. The algorithm uses deep neural network to train the classifier with both the channel and non-channel patches. We provide a field data example to demonstrate the performance of the new algorithm. The training phase gave a maximum accuracy of 84.6% for the classifier and it performed even better in the testing phase, giving a maximum accuracy of 90%.