Parallel multilevel fast multipole method for solving large-scale problems

The Multilevel Fast Multipole Method (FMM) is a well-established method and can be applied to solve electromagnetic (EM) scattering problems. Compared with other traditional methods, it requires less computational time and memory. However, constrained by a single processor's speed and memory limitations, the problem size that can be solved by serial implementation is still relatively small. For a million-unknown target, the computational time on a single processor is intolerable, and memory could be easily exhausted. Parallel-computing technology, which can utilize multiprocessors, provides an efficient way to solve electrically large-scale EM problems. This paper will focus on discussing the parallel methodologies applied to a multilevel FMM code, as well as demonstrating the computational efficiency of the parallel approach.     

Computational performance of a parallelized three-dimensional high-order spectral element toolbox

In this paper, a comprehensive performance review of an MPI-based high-order three-dimensional spectral element method C++ toolbox is presented. The focus is put on the performance evaluation of several aspects with a particular emphasis on the parallel efficiency. The performance evaluation is analyzed with the help of a time prediction model based on a parameterization of the application and the hardware resources. Two tailor-made benchmark cases in computational fluid dynamics (CFD) are introduced and used to carry out this review, stressing the particular interest for clusters with up to thousands of cores. Some problems in the parallel implementation have been detected and corrected. The theoretical complexities with respect to the number of elements, to the polynomial degree, and to communication needs are correctly reproduced. It is concluded that this type of code has a nearly perfect speedup on machines with thousands of cores, and is ready to make the step to next-generation petaFLOP machines.     

Improving Flood Forecasting in a Developing Country: A Comparative Study of Stepwise Multiple Linear Regression and Artificial Neural Network

Due to limited data sources, practical situations in most developing countries favor black-box models in real time operations. In a simple and robust approach, this study examines performances of stepwise multiple linear regression (SMLR) and artificial neural network (ANN) models, as tools for multi-step forecasting Chindwin River floods in northern Myanmar. Future river stages are modeled using past water levels and rainfall at the forecasting station as well as at the hydrologically connected upstream station. The developed models are calibrated with flood season data from 1990 to 2007 and validated with data from 2008 to 2011. Model performances are compared for 1- to 5-day ahead forecasts. With a high accuracy, both candidate models performed well for forecasting the full range of flood levels. The ANN models were superior to the SMLR models, particularly in predicting the extreme floods. Correlation analysis was found to be useful for determining the initial input variables. Contribution of upstream data to both models could improve the forecasting performance with higher R ² values and lower errors. Considering the commonly available data in the region as primary predictors, the results would be useful for real time flood forecasting, avoiding the complexity of physical processes.     

Estimating forest canopy density of tropical mixed deciduous vegetation using Landsat data: a comparison of three classification approaches

Although a number of image classification approaches are available to estimate forest canopy density (FCD) using satellite data, assessment of their relative performances with tropical mixed deciduous vegetation is lacking. This study compared three image classification approaches – maximum likelihood classification (MLC), multiple linear regression (MLR) and FCD Mapper – in estimating the FCD of mixed deciduous forest in Myanmar. The application of MLC and MLR was based on spectral reflectance of vegetation, whereas FCD Mapper was operated on integrating the biophysical indices derived from the reflectance of the vegetation. The FCD was classified into four categories: closed canopy forest (CCF; FCD ≥ 70%), medium canopy forest (MCF; 40% ≥ FCD < 70%), open canopy forest (OCF; 10% ≥ FCD < 40%) and non-forest (NF; FCD < 10%). In the three classification approaches, producer's and user's accuracies were higher for more homogeneous vegetation such as NF and CCF than for heterogeneous vegetation density (VD) such as OCF and MCF. FCD Mapper produced the best overall accuracy and kappa coefficient. This study revealed that only spectral reflectance is not enough to get good results in estimating FCD in tropical mixed deciduous vegetation. This study indicates that FCD Mapper, an inexpensive approach because it requires only validation data and thus saves time, can be applied to monitor tropical mixed deciduous vegetation over time at lower cost than alternative methods.     

Emission of polycyclic aromatic hydrocarbons, toxicity, and mutagenicity from domestic cooking using sawdust briquettes, wood, and kerosene

Smoke samples, in both gas and particulate matter (PM) phases, of the three domestic stoves were collected using U.S. EPA modified method 5 and were analyzed for 17 PAH (HPLC-UV), acute toxicity (Microtox test), and mutagenicity (Amestest). The gas phase of smoke contributed > or = 95% of 17 PAH, > or = 96% of toxicity, and > or = 60% of mutagenicity. The highest emission factor of 17 PAH was from sawdust briquettes (260 mg/kg), but the highest emission of 11 genotoxic PAH was from kerosene (28 mg/kg). PM samples of kerosene smoke were not toxic. The total toxicity emission factor was the highest from sawdust, followed by kerosene and wood fuel. Smoke samples from the kerosene stove were not mutagenic. TA98 indicated the presence of both direct and indirect mutagenic activities in PM samples of sawdust and wood fuel but only direct mutagenic activities in the gas phase. TA100 detected only direct mutagenic activities in both PM and gas-phase samples. The higher mutagenicity emission factor was from wood fuel, 12 x 10(6) revertants/kg (TA100-S9) and 3.5 x 10(6) (TA98-S9), and lower from sawdust, 2.9 x 10(6) (TA100-S9) and 2.8 x 10(6) (TA98-S9). The low burning rate and high efficiency of a kerosene stove have resulted in the lowest PAH, toxicity, and mutagenicity emissions from daily cooking activities. The bioassays produced toxicity and mutagenicity results in correspondence with the PAH content of samples. The tests could be used for a quick assessment of potential health risks.     

Transmission of hepatitis C virus to infants of human immunodeficiency virus-negative intravenous drug-using mothers: rate of infection and assessment of risk factors for transmission

The acute effects of a newly synthesized thromboxane dual blocker (KDI-792), a combined thromboxane synthase inhibitor and receptor antagonist, on lower limb circulation were examined using two-dimensional color and pulse Doppler ultrasonography and laser Doppler flowmetry. A randomized single-masked, placebo-controlled trial was performed on 36 type 2 diabetic patients with minimally impaired baseline flow. The anatomical cross-sectional area (CSA), maximum flow velocity (MFV) and flow volume index (FVI) in the right dorsal pedis artery (DPA) and right femoral artery (FA) were determined by Doppler ultrasonography before and 45 and 90 minutes after the administration of either 100 or 200 mg of KDI-792 to the dose groups or placebo to the control group. Periflux blood flow (PBF) in the right foot was determined simultaneously by laser Doppler flowmetry. Both CSA and MFV in the dose groups were significantly increased in both the FA and DPA. FVI was markedly increased from 21.4 +/- 3.7 to 68.3 +/- 26.8 in the DPA (M +/- SD, P < 0.01) and from 365.4 +/- 35.3 to 771.7 +/- 75.7 in the FA (P < 0.01) in the 200 mg dose group. In the 100 mg dose group, FVI was markedly increased from 20.0 +/- 8.7 to 68.3 +/- 26.8 (P < 0.01) in the DPA and from 372.5 +/- 130.0 to 677.5 +/- 187.8 (P < 0.01) in the FA. PBF was also increased in both dose groups (from 4.15 +/- 1.4 to 7.0 +/- 4.0 ml/min/100 g tissue in the 200 mg dose group, P < 0.01), whereas there were no significant changes in either measurement in the control group. There were no significant changes in pulse rate or blood pressure after administration in either the dosage group or the placebo group. These and previous findings indicate that a single administration of KDI-792 markedly increases lower limb blood flow and might have a more potent vasodilating effect than that of prostaglandin I2 derivatives.     

Risk factors in dengue shock syndrome

Despite a growing body of evidence predominantly, but not exclusively, from Thailand suggesting that the risk of developing dengue shock syndrome (DSS) is greatest following an anamnestic dengue infection, particularly if the most recent infection was with dengue 2 virus, there continues to be debate about the justification for these claims. This report describes a five-year, prospective study in two townships (suburbs) in Yangon (Rangoon) Myanmar (Burma) in which attempts were made to confirm the data from an earlier prospective study in Thailand and to address some of the criticism of earlier studies. This investigation found the incidence of anamnestic dengue infections in DSS patients to be significantly higher than in the community from which they were drawn and a significantly higher risk of developing DSS following an anamnestic infection (particularly with dengue 2 virus) than following a primary infection with any serotype.