RECONSTRUCTION OF PART OF AN ACTUAL BLAST-WAVE FLOW FIELD TO AGREE WITH EXPERIMENTAL DATA BY USING NUMERICAL METHOD WITH HIGH IDENTIFICATION

In this paper, on the basis of experimental data of two kinds of chemical explosions, the piston-pushing model of spherical blast-waves and the second-order Godunov-type scheme of finite difference methods with high identification to discontinuity are used to the numerical reconstruction of part of an actual hemispherical blast-wave flow field by properly adjusting the moving bounary conditions of a piston. This method is simple and reliable. It is suitable to the evaluation of effects of the blast-wave flow field away from the explosion center.

High frequencies of HGV and TTV infections in blood donors in Hangzhou

AIM: To determine the frequencies of HGV and TTV infections in blood donors in Hangzhou. METHODS: RT-nested PCR for HGV RNA detection and semi-nested PCR for TTV DNA detection in the sera from 203 blood donors, and nucleotide sequence analysis were performed. RESULTS: Thirty-two (15.8%) and 30 (14.8%) of the 203 serum samples were positive for HGV RNA and TTV DNA, respectively. And 5 (2.5%) of the 203 serum samples were detectable for both HGV RNA and TTV DNA. Homology of the nucleotide sequences of HGV RT-nested PCR products and TTV semi-nested PCR products from 3 serum samples compared with the reported HGV and TTV sequences was 89.36%, 87.94%, 88.65% and 63.51%, 65.77% and 67.12%, respectively. CONCLUSION: The infection rates of HGV and/or TTV in blood donors are relatively high, and to establish HGV and TTV examinations to screen blood donors is needed for transfusion security. The genomic heterogeneity of TTV or HGV is present in the isolates from different areas.

Intensify standardized therapy for esophageal and stomach cancer in tumor hospitals

INTRODUCTIONCancer treatment situation in tumor hospitals inChina has its own unique characteristics which arenot found in other parts of the world. Because ofthe huge population and high incidence rates ofesophageal and stomach cancer[1-5], the number ofcancer patients waiting for admission isinconceivably large.

Interobserver variation in histopathological assessment of Helicobacter pylori gastritis

AIM:Because the presence or absence of H pylori infection has important implications for therapeutic decisions based on histological assessment,the reproducibility of Sydney system is important.The study was designed to test the reproducibility of features of Helicobacter pylori gastritis, using the updated Sydney classification. METHODS:Gastric biopsies of 40 randomly selected cases of H pylori gastritis were scored semiquantitatively by three pathologists.Variables analysed induded chronic inflammation, inflammatory activity,atrophy,intestinal metaplasia,H pylori, surface epithelial damage.κ values below 0.5 represented poor,those between 0.5 and 0.75 good and values over 0.75 excellent interobserver agreement. RESULTS:The best interobserver agreement(κ=0.62)was present for intestinal metaplasia.The agreement was the poorest for evaluating atrophy(κ=0.31). CONCLUSION:Although the results of this study were in accordance with some previous studies,an excellent agreement could not be reached for any features of H pylori gastritis.This low degree of concordance is assumed to be due to the personal evaluation differences in grading the features,the lack of standardized diagnostic criteria,and the ignorance to reach a consensus about the methods to be used in grading the features of H pylori gastritis before initiating the study.

Healthy ranges of serum alanine aminotransferase levels in Iranian blood donors

AIM: The healthy ranges for serum alanine aminotransferase(ALT) levels are less well studied. The aim of this study was to define the upper limit of normal (ULN) for serum ALT levels, and to assess factors associated with serum ALT activity in apparently healthy blood donors. METHODS: A total of 1 939 blood donors were included.ALT measurements were performed for all cases using the same laboratory method. Healthy ranges for ALT levels werecomputed from the population at the lowest risk for liver disease. Univariate and multivariate analyses were performed to evaluate associations between clinical factors and ALT levels.RESULTS: Serum ALT activity was independently associated with body mass index (BMI) and male gender, but not associated with age. Association of ALT with BMI was more prominent in males than in females. Upper limit of normal for non-overweight women (BMI of less than 25) was 34 U/L,and for non-overweight men was 40 U/L.CONCLUSION: Serum ALT is strongly associated with sex and BMI. The normal range of ALT should be defined for male and female separately.

Significant factors associated with fatal outcome in emergency open surgery for perforated peptic ulcer

AIM:To evaluate the main factors associated with mortality in patients undergoing surgery for perforated peptic ulcer referred to an academic department of general surgery in a large southern Italian city. METHODS:One hundred and forty-nine consecutive patients (M:F ratio=110:39,mean age 52 yrs,range 16-95) with peptic ulcer disease were investigated for clinical history (including age,sex,previous history of peptic ulcer,associated diseases,delayed abdominal surgery,ulcer site,operation type,shock on admission,postoperative general complications, and intra-abdominal and/or wound infections),serum analyses and radiological findings. RESULTS:The overall mortality rate was 4.0%.Among all factors,an age above 65 years,one or more associated diseases,delayed abdominal surgery,shock on admission, postoperative abdominal complications and/or wound infections,were significantly associated (x^2) with increased mortality in patients undergoing surgery (0.0001<P<0.03). CONCLUSION:Factors such as concomitant diseases,shock on admission,delayed surgery,and postoperative abdominal and wound infections are significantly associated with fatal outcomes and need careful evaluation within the general workup of patients admitted for perforated peptic ulcer.

Gastric malignancies in Northern Jordan with special emphasis on descriptive epidemiology

AIM:To study the epidemiology of gastric malignancies in Jordan as a model for Middle East countries where such data is scarce. METHODS:Pertinent epidemiological and clinicopathological data for 201 patients with gastric malignancy in north of Jordan between 1991 and 2001 were analyzed. RESULTS:Male:female ratio was 1.8:1.The mean age was 61.2 years,and 8.5% of the patients were younger than 40 years of age.The overall age-adjusted incidence was 5.82/100 000 population/year.The age specific incidence for males raised from 1.48 in those aged 30-39 years to 72.4 in those aged 70-79 years.Adenocarcinomas, gastric lymphomas,malignant stromal tumors,and carcinoids were found in 87.5%,8%,2.5%,and 2% respectively.There was an average of 10.1-month delay between the initial symptoms and the diagnosis.Only 82 patients underwent“curative”gastrectomy.Among adenocarcinoma groups,Lauren intestinal type was the commonest(72.2%)and the distal third was the most common localization(48.9%).The mean follow up for patients with gastric adenocarcinoma was 25.1 mo(range 1-132mo).The 5-year survival rates for stages Ⅰ(n=15), Ⅱ(n=41),Ⅲ(n=59),and Ⅳ(n=53) were 67.3%,41.3%, 5.7%,and 0% respectively(P=0.0001).The overall 5 year survival was 21.1%. CONCLUSION:Despite low inddence,some epidemiological features of gastric cancer in Jordan mimic those of high- risk areas.Patients are detected and treated after a relatively long delay.No justification in favor of a possible gastric cancer screening effort in Jordan is supported by our study;rather,the need of an earlier diagnosis and subsequent better care.

Development of practical postprocessor for 5-axis machine tool with non-orthogonal rotary axes

In order to develop a practical postprocessor for 5-axis machine tool,the general equations of numerically controlled(NC) data for 5-axis configurations with non-orthogonal rotary axes were exactly expressed by the inverse kinematics,and a windows-based postprocessor written with Visual Basic was developed according to the proposed algorithm.The developed postprocessor is a general system suitable for all kinds of 5-axis machines with orthogonal and non-orthogonal rotary axes.Through implementation of the developed postprocessor and verification by a cutting simulation and machining experiment,the effectiveness of the proposed algorithm is confirmed.Compatibility is improved by allowing exchange of data formats such as rotational total center position(RTCP) controlled NC data,vector post NC data,and program object file(POF) cutter location(CL) data,and convenience is increased by adding the function of work-piece origin offset.Consequently,a practical post-processor for 5-axis machining is developed.

CORRECTION OF ASYMMETRIC STRENGTHENING OF QUIKSCAT WIND FIELD AND ASSIMILATION APPLICATION IN TYPHOON SIMULATION

As an approach to the technological problem that the wind data of QuikSCAT scatterometer cannot accurately describe the zone of typhoon-level strong wind speed, some objective factors such as the typhoon moving speed, direction and friction are introduced in this study to construct the asymmetric strengthening of the QuikSCAT wind field. Then by adopting a technology of four-dimensional data assimilation, an experiment that includes both the assimilation and forecasting phases is designed to simulate Typhoon Rananim numerically. The results show that with model constraints and adjustment, this technology can incorporate the QuikSCAT wind data to the entire column of the model atmosphere, improve greatly the simulating effects of the whole-column wind, pressure field and the track as well as the simulated typhoon intensity covered by the forecast phase, and work positively for the forecasting of landfall locations.

Estimation of transition redshift based on Reinsch splines

Many schemes have been proposed to define a model-independent con- straint on cosmological dynamics, such as the nonparametric dark energy equation of state ω（z） or the deceleration parameter q（z）. These methods usually contain deriva- tives with respect to observational data with noise. However, there can be large un- certainties when one estimates values with numerical differentiation, especially when noise is significant. We introduce a global numerical differentiation method, first for- mulated by Reinsch, which is smoothed by cubic spline functions, and apply it to the estimation of the transition redshift zt with a simulated expansion rate E（z） based on observational Hubble parameter data. We also discuss some deficiencies and limita-tions of this method.

Evaluation of a Micro-scale Wind Model's Performance over Realistic Building Clusters Using Wind Tunnel Experiments

The simulation performance over complex building clusters of a wind simulation model（Wind Information Field Fast Analysis model, WIFFA） in a micro-scale air pollutant dispersion model system（Urban Microscale Air Pollution dispersion Simulation model, UMAPS） is evaluated using various wind tunnel experimental data including the CEDVAL（Compilation of Experimental Data for Validation of Micro-Scale Dispersion Models） wind tunnel experiment data and the NJU-FZ experiment data（Nanjing University-Fang Zhuang neighborhood wind tunnel experiment data）. The results show that the wind model can reproduce the vortexes triggered by urban buildings well, and the flow patterns in urban street canyons and building clusters can also be represented. Due to the complex shapes of buildings and their distributions, the simulation deviations/discrepancies from the measurements are usually caused by the simplification of the building shapes and the determination of the key zone sizes. The computational efficiencies of different cases are also discussed in this paper. The model has a high computational efficiency compared to traditional numerical models that solve the Navier–Stokes equations, and can produce very high-resolution（1–5 m） wind fields of a complex neighborhood scale urban building canopy（～ 1 km ×1km） in less than 3 min when run on a personal computer.

Performance analysis of parallel gravitational N-body codes on large GPU clusters

We compare the performance of two very different parallel gravitational N-body codes for astrophysical simulations on large Graphics Processing Unit（GPU） clusters, both of which are pioneers in their own fields as well as on certain mutual scales- NBODY6＋＋ and Bonsai. We carry out benchmarks of the two codes by analyzing their performance, accuracy and efficiency through the modeling of structure decomposition and timing measurements. We find that both codes are heavily optimized to leverage the computational potential of GPUs as their performance has approached half of the maximum single precision performance of the underlying GPU cards. With such performance we predict that a speed-up of200- 300 can be achieved when up to 1k processors and GPUs are employed simultaneously. We discuss the quantitative information about comparisons of the two codes, finding that in the same cases Bonsai adopts larger time steps as well as larger relative energy errors than NBODY6＋＋, typically ranging from10- 50 times larger, depending on the chosen parameters of the codes. Although the two codes are built for different astrophysical applications, in specified conditions they may overlap in performance at certain physical scales, thus allowing the user to choose either one by fine-tuning parameters accordingly.

Fast compression and reconstruction of astronomical images based on compressed sensing

With the fast increase in the resolution of astronomical images, the question of how to process and transfer such large images has become a key issue in astronomy. We propose a new real-time compression and fast reconstruction algorithm for astronomical images based on compressive sensing techniques. We first reconstruct tile Original signal with fewer measurements, according to its compressibility. Then, based on the characteristics of astronomical images, we apply Daubechies orthogonal wavelets to obtain a sparse representation. A matrix representing a random Fourier ensembleis used to obtain a sparse representation in a lower dimensional space. For reconstructing the image, we propose a novel minimum total variation with block addptive sensing to balance the accuracy and eomputation time. Our experimental results show that the proposed algorithm can efficiently reconstruct colorful astronomicai images with high resolution and improve the applicability of compressed sensing.

A novel pure data-selection framework for day-ahead wind power forecasting

Numerical weather prediction(NWP)data possess internal inaccuracies,such as low NWP wind speed corresponding to high actual wind power generation.This study is intended to reduce the negative effects of such inaccuracies by proposing a pure data-selection framework(PDF)to choose useful data prior to modeling,thus improving the accuracy of day-ahead wind power forecasting.Briefly,we convert an entire NWP training dataset into many small subsets and then select the best subset combination via a validation set to build a forecasting model.Although a small subset can increase selection flexibility,it can also produce billions of subset combinations,resulting in computational issues.To address this problem,we incorporated metamodeling and optimization steps into PDF.We then proposed a design and analysis of the computer experiments-based metamodeling algorithm and heuristic-exhaustive search optimization algorithm,respectively.Experimental results demonstrate that(1)it is necessary to select data before constructing a forecasting model;(2)using a smaller subset will likely increase selection flexibility,leading to a more accurate forecasting model;(3)PDF can generate a better training dataset than similarity-based data selection methods(e.g.,K-means and support vector classification);and(4)choosing data before building a forecasting model produces a more accurate forecasting model compared with using a machine learning method to construct a model directly.

Developments of the Three-Dimensional Variational Data Assimilation System for the Nonhydrostatic GRAPES

Based on the original GRAPES（Global/Regional Assimilation and PrEdiction System）3DVAR（p3DAR）, which is defined on isobaric surface,a new three-dimensional variational data assimilation system（m3DVAR） is constructed and used exclusively with the nonhydrostatic GRAPES model in order to reduce the errors caused by spatial interpolation and variable transformation,and to improve the quality of the initial value for operational weather forecasts.Analytical variables of the m3DVAR are fully consistent with predictands of the GRADES model in terms of spatial staggering and physical definition.A different vertical coordinate and the nonhydrostatic condition are taken into account,and a new scheme for solving the dynamical constraint equations is designed for the m3DVAR.To deal with the diffculties in solving the nonlinear balance equation atσlevels,dynamical balance constraints between mass and wind fields are reformulated,and an effective mathematical scheme is implemented under the terrain-following coordinate.Meanwhile,new observation operators are developed for routine observational data,and the background error covariance is also obtained.Currently,the m3DVAR system can assimilate all routine observational data. Multi-variable idealized experiments with single point observations are performed to validate the m3DVAR system.The results show that the system can describe correctly the multi-variable analysis and the relationship of the physical constraints.The difference of innovation and the analysis residual forπalso show that the analysis error of the m3DVAR is smaller than that of the p3DVAR.The T s scores of precipitation forecasts in August 2006 indicate that the m3DVAR system provides reduced errors in the model initial value than the p3DVAR system.Therefore,the m3DVAR system can improve the analysis quality and initial value for numerical weather predictions.

A CLUSTERING ALGORITHM FOR MIXED NUMERIC AND CATEGORICAL DATA

Most of the earlier work on clustering mainly focused on numeric data whoseinherent geometric properties can be exploited to naturally define distance functions between datapoints. However, data mining applications frequently involve many datasets that also consists ofmixed numeric and categorical attributes. In this paper we present a clustering algorithm which isbased on the k-means algorithm. The algorithm clusters objects with numeric and categoricalattributes in a way similar to k-means. The object similarity measure is derived from both numericand categorical attributes. When applied to numeric data, the algorithm is identical to the k-means.The main result of this paper is to provide a method to update the 'cluster centers' of clusteringobjects described by mixed numeric and categorical attributes in the clustering process to minimizethe clustering cost function. The clustering performance of the algorithm is demonstrated with thetwo well known data sets, namely credit approval and abalone databases.