Dynamics of the atmosphere of Jupiter

Atmospheric jets and vortices on Jupiter persist for decades in the presence of vigorous turbulence which might be expected to destroy organized flows. The penetration depth of the jets into the planet has been a major question, and new data from the NASA Galileo entry probe suggest that they are not shallow atmospheric phenomena. Numerical simulations and Galileo orbiter data promise further progress in the near future.     

Geometrical effects in microfluidic-based microarrays for rapid, efficient single-cell capture of mammalian stem cells and plant cells

In this paper, a detailed numerical and experimental investigation into the optimisation of hydrodynamic micro-trapping arrays for high-throughput capture of single polystyrene (PS) microparticles and three different types of live cells at trapping times of 30 min or less is described. Four different trap geometries (triangular, square, conical, and elliptical) were investigated within three different device generations, in which device architecture, channel geometry, inter-trap spacing, trap size, and trap density were varied. Numerical simulation confirmed that (1) the calculated device dimensions permitted partitioned flow between the main channel and the trap channel, and further, preferential flow through the trap channel in the absence of any obstruction; (2) different trap shapes, all having the same dimensional parameters in terms of depth, trapping channel lengths and widths, main channel lengths and widths, produce contrasting streamline plots and that the interaction of the fluid with the different geometries can produce areas of stagnated flow or distorted field lines; and (3) that once trapped, any motion of the trapped particle or cell or a shift in its configuration within the trap can result in significant increases in pressures on the cell surface and variations in the shear stress distribution across the cell’s surface. Numerical outcomes were then validated experimentally in terms of the impact of these variations in device design elements on the percent occupancy of the trapping array (with one or more particles or cells) within these targeted short timeframes. Limitations on obtaining high trap occupancies in the devices were shown to be primarily a result of particle aggregation, channel clogging and the trap aperture size. These limitations could be overcome somewhat by optimisation of these device design elements and other operational variables, such as the average carrier fluid velocity. For example, for the 20 μm polystyrene microparticles, the number of filled traps increased from 32% to 42% during 5–10 min experiments in devices with smaller apertures. Similarly, a 40%–60% reduction in trapping channel size resulted in an increase in the amount of filled traps, from 0% to almost 90% in 10 min, for the human bone marrow derived mesenchymal stem cells, and 15%–85% in 15 min for the human embryonic stem cells. Last, a reduction of the average carrier fluid velocity by 50% resulted in an increase from 80% to 92% occupancy of single algae cells in traps. Interestingly, changes in the physical properties of the species being trapped also had a substantial impact, as regardless of the trap shape, higher percent occupancies were observed with cells compared to single PS microparticles in the same device, even though they are of approximately the same size. This investigation showed that in microfluidic single cell capture arrays, the trap shape that maximizes cell viability is not necessarily the most efficient for high-speed single cell capture. However, high-speed trapping configurations for delicate mammalian cells are possible but must be optimised for each cell type and designed principally in accordance with the trap size to cell size ratio.     

Design and performance analysis of PID controller for an automatic voltage regulator system using simplified particle swarm optimization

This paper presents the design and performance analysis of Proportional Integral Derivate (PID) controller for an Automatic Voltage Regulator (AVR) system using recently proposed simplified Particle Swarm Optimization (PSO) also called Many Optimizing Liaisons (MOL) algorithm. MOL simplifies the original PSO by randomly choosing the particle to update, instead of iterating over the entire swarm thus eliminating the particles best known position and making it easier to tune the behavioral parameters. The design problem of the proposed PID controller is formulated as an optimization problem and MOL algorithm is employed to search for the optimal controller parameters. For the performance analysis, different analysis methods such as transient response analysis, root locus analysis and bode analysis are performed. The superiority of the proposed approach is shown by comparing the results with some recently published modern heuristic optimization algorithms such as Artificial Bee Colony (ABC) algorithm, Particle Swarm Optimization (PSO) algorithm and Differential Evolution (DE) algorithm. Further, robustness analysis of the AVR system tuned by MOL algorithm is performed by varying the time constants of amplifier, exciter, generator and sensor in the range of ?50% to +50% in steps of 25%. The analysis results reveal that the proposed MOL based PID controller for the AVR system performs better than the other similar recently reported population based optimization algorithms.