Enhanced critical magnetization currents of hot-pressed YBa2Cu3O6+x through partial melting post-oxygenation

Bulk YBa₂Cu₃O_6+x superconductor was synthesized using the hot-pressing technique combined with various oxygen-annealing cycles. Pressed samples, with theirab-planes perpendicular to the pressing axis, annealed in oxygen at the partial melting point of approximately 1000°C and slowly cooled at different rates in the temperature ranges 975–935 and 935–450°C showed enhanced magnetization hysteresis loops with a weak field dependence. Due to oxygen-deficient regions in these materials, anomalous magnetization hysteresis loops with a butterfly contour were observed at temperatures above 50 K. This indicates that these regions act as effective flux-pinning centres at high temperatures. The critical magnetization current density (J _c) calculated using the Bean model and the average grain dimension was of the order of 10⁴ A cm^–2 at 75 K up to 1 T. Because of a shorter period of oxygenation and a weak field dependence ofJ _c s, the synthesis process reported here is very promising and further optimization of the period in various annealing temperature ranges to limit the weak links caused by excessive grain growth becomes necessary. The observations are also correlated with the morphology and the crystal orientation studied by scanning electron microscopy and X-ray diffractometry, respectively.     

Synthesis of high aspect-ratio carbon nanotube "flying carpets" from nanostructured flake substrates

We present a robust method for synthesis of aligned, single-walled carbon nanotube (CNT) "flying carpets" from nanostructured alumina flakes. Roll-to-roll e-beam deposition is utilized to produce the flakes, and hot filament chemical vapor deposition is utilized to grow dense, aligned carbon nanotubes from the flakes with remarkably high CNT yields. The flakes are captured inside a mesh cage and freely suspended in the gas flow during growth. Optical characterization indicates the presence of high quality, small diameter single-walled carbon nanotubes.     

An empirical study for software change prediction using imbalanced data

Software change prediction is crucial in order to efficiently plan resource allocation during testing and maintenance phases of a software. Moreover, correct identification of change-prone classes in the early phases of software development life cycle helps in developing cost-effective, good quality and maintainable software. An effective software change prediction model should equally recognize change-prone and not change-prone classes with high accuracy. However, this is not the case as software practitioners often have to deal with imbalanced data sets where instances of one type of class is much higher than the other type. In such a scenario, the minority classes are not predicted with much accuracy leading to strategic losses. This study evaluates a number of techniques for handling imbalanced data sets using various data sampling methods and MetaCost learners on six open-source data sets. The results of the study advocate the use of resample with replacement sampling method for effective imbalanced learning.     

Cyclophospholipids Increase Protocellular Stability to Metal Ions

Model protocells have long been constructed with fatty acids, because these lipids are prebiotically plausible and can, at least theoretically, support a protocell life cycle. However, fatty acid protocells are stable only within a narrow range of pH and metal ion concentration. This instability is particularly problematic as the early Earth would have had a range of conditions, and extant life is completely reliant on metal ions for catalysis and the folding and activity of biological polymers. Here, prebiotically plausible monoacyl cyclophospholipids are shown to form robust vesicles that survive a broad range of pH and high concentrations of Mg²⁺, Ca²⁺, and Na⁺. Importantly, stability to Mg²⁺ and Ca²⁺ is improved by the presence of environmental concentrations of Na⁺. These results suggest that cyclophospholipids, or lipids with similar characteristics, may have played a central role during the emergence of Darwinian evolution.     

An integrated converter model and enhanced control approach for torque ripple minimisation of switched reluctance motor: a CMFG-RNN technique

ABSTRACT

In this paper, a control mechanism for speed control of switched reluctance motor (SRM) with torque ripple reduction utilising moth flame optimisation algorithm and genetic algorithm with recurrent neural network (CMFG-RNN) is presented. The control mechanism comprises of FOPID speed controller in the external loop and current controller in the internal loop along with control of turn-on and turn-off angles for the SRM. The issue of getting the ideal estimations of proportional, integral and derivative gains for both speed and current controller along with the turn-on and turn-off angles is considered as a multi-objective optimisation problem with the goals of limiting the Integral Squared Error of speed and torque ripple. Simulations of CMFG-RNN-based control of SRM are done utilising SIMULINK/MATLAB software. With a specific end goal to assess the strong execution of CMFG-RNN, the comparison of current, speed, flux and torque under different techniques are considered. The outcomes got by CMFG-RNN are contrasted and validated with ALO and NSGA-II techniques. The outcomes uncover that CMFG-RNN-based controllers give better execution as far as lesser torque ripple and quick settling time because of its systematic random search capabilities, thereby enhancing the dynamic execution of SRM drive.     

Iodine positive-column oscillation associated with cathode instability

A positive-column oscillation in low-pressure iodine vapour with frequency about 100 kc/s has been found to be associated with oscillations of small corona-type protuberances of the cathode glow. Two ways are described for suppressing the oscillations.     

Separation of Nitrogenous Residues from Deproteinated Whey for Lactose Crystallization

The influence of heat treatment, pH adjustment, and total solids content on the effectiveness of secondary protein removal (clarification) from heat-acid deproteinated whey was studied. Lowering pH and increasing total solids content before clarification decreased residual protein (nitrogen × 6.38) in clarified whey. Lowest nitrogen was obtained by concentrating deproteinated whey to 55% total solids, adjusting pH to 3.5, heating to 90 C, and filtering. Thread-like aggregates formed during concentration of the heat-acid deproteinated whey at pH 4.5 in a rotary film evaporator. Analytical studies indicated that the aggregates were composed predominantly of proteose-peptone component 5.