Hypokalaemia following nebulized salbutamol in children with acute attack of bronchial asthma

OBJECTIVE: To determine whether use of nebulized salbutamol therapy for treatment of an acute attack of asthma in children is associated with hypokalaemia and if so what is its frequency, severity and effect on recovery. METHODOLOGY: Forty-six children, aged 10 months to 12 years (mean 7.9 +/- 1.5 years) with acute attack of bronchial asthma, treated initially with three doses of nebulized salbutamol 0.15-0.3 mg/kg, every 30 min participated in the study. Blood for serum potassium was obtained at the beginning and after three doses of nebulized salbutamol therapy, before administering other drugs. RESULTS: The mean +/- SD serum potassium level decreased marginally from 3.9 +/- 0.5 mEq/L to 3.7 +/- 0.5 mEq/L (P < 0.05). A decrease in serum potassium concentration was noted in 26 (56.5%) and hypokalaemia (serum potassium < 3.5 mg/L) in 17 (39%) patients. It was more frequent in patients who had received oral salbutamol for the preceding 7 days. The average time taken for recovery was longer in patients who had hypokalaemia than those who had normal serum potassium concentration (8.6 +/- 2.7 h vs 6.5 +/- 2.7 h; P < 0.005). CONCLUSIONS: Hypokalaemia may occur in about one-third of patients treated with three doses of nebulized salbutamol therapy, especially those on prior oral salbutamol therapy. The monitoring of serum potassium concentration may be warranted in such patients.     

Performance evaluation of the augmented data vortex switch fabric: An all-optical packet switched interconnection network

Modern high-performance computing systems require networks with high capacity, extremely high throughput and low latency in order to pass messages between thousands of processors and memory elements. Optical Interconnection Networks (OIN) offer a potentially viable solution to this requirement. An all-optical packet switched interconnection network called a Data Vortex (DV) switch has already been proposed by Yang et al. for the purpose of large scale photonic interconnections. For any interconnection network, fault tolerance and reliability are crucial issues, evaluation of which lacked attention for the case of the DV switch. In our earlier work we therefore presented the results for fault tolerance and reliability analysis of the primary DV switch. We also proposed a new Augmented Data Vortex (ADV) switch fabric, to improve the fault tolerance of the primary DV switch. The performance as regards fault tolerance of the ADV switch was computed and detailed results were obtained. In this paper, performance of ADV is investigated with reference to parameters such as latency and injection ratio (throughput) by means of numerical simulations. A uniform random traffic model has been used for the performance evaluation. The results obtained are compared with the results reported for the DV switch. The results show that the ADV switch with enhanced fault tolerance also improves the performance regarding latency. For same switch sizes (i.e. the same number of angles A, and height H) the injection ratios (throughput) for the DV and the ADV switches are comparable. Hence it can serve as a suitable candidate for high performance computing.     

A New Technique for Forecasting Surface Wind Field From Scatterometer Observations: A Case Study for the Arabian Sea

The possibility of predicting ocean-surface wind field a few days ahead from satellite scatterometer observations in the Arabian Sea has been explored in this paper. The prediction technique is based on a combination of empirical orthogonal function (EOF) analysis and genetic algorithm (GA). The space-time distributed satellite data (zonal or meridional wind field) have been decomposed into a set of spatial eigenmodes ranked by their temporal variance. The associated temporal amplitude functions have been used by the GA for carrying out forecasts with lead times varying from one to five days. The GA finds the analytical equations that best describe the behavior of the different temporal amplitude functions in the EOF decomposition. Later, the predicted wind field has been generated as a linear combination of the dominant spatial modes weighted by the corresponding predicted amplitudes. The technique has been tested using independent validation data sets. It has been further tested by comparing the forecast fields with buoy data. The performance of GA is comparable to that of persistence forecast for the first two days of forecast, while it is better than that of persistence for three- to five-day-ahead forecasts     

Erratum to: First-Principles Investigation of Electronic Properties of GaAsxSb1 – x Ternary Alloys

Semiconductors - erratum     

Analytical modeling of flicker and thermal noise in n-channel DG FinFETs

A compact physics-based thermal and flicker noise model has been developed for n-channel Double Gate FinFETs with varying structural parameters. The effects of mobility degradation due to velocity saturation, carrier heating and channel length modulation have been incorporated for an accurate modeling of noise. The mobility fluctuations dependent on the inversion carrier density have been considered and a characteristic of the flicker noise different from that of Bulk MOSFETs was observed. This has been validated by the experimental results. Based on the proposed thermal and flicker noise model, a compact expression of the corner frequency has been derived and the effects of the structural parameters such as the length and the thickness of the channel have been analyzed. Finally, the model has been applied for p-channel devices and noise behavior in accordance with experimental data has been obtained.     

Segregated targeting for multiple resource networks using decomposition algorithm

A generalized decomposition technique is presented for determining optimal resource usage in segregated targeting problems with single quality index (e.g., concentration, temperature, etc.) through pinch analysis. The latter problems are concerned with determining minimal resource requirements of process networks characterized by the existence of multiple zones, each consisting of a set of demands and using a unique external resource. However, all the zones share a common set of internal sources. The decomposition algorithm allows the problem to be decomposed into a sequence of subproblems, each of which can in turn be solved using any established graphical or algebraic targeting methodology to determine the minimum requirement of respective resource. This article presents a rigorous mathematical proof of the decomposition algorithm, and then demonstrates its potential applications with case studies on carbon‐constrained energy sector planning, interplant water integration, and emergy‐based multisector fuel allocation. © 2009 American Institute of Chemical Engineers AIChE J, 2010