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In order to explore the spatial pesticide spraying deposition distribution, the downwash flow field characteristics for unmanned aerial vehicle (UAV) pesticide application with accurate flight height and velocity and the relationship of these two aspects, a novel measurement method was proposed in this paper. A model '3WQF80-10' single-rotor diesel UAV was tested using this method in wheat field and the effects of flight direction, flight parameters and crosswind on the distribution of spatial spraying deposition quality balance (SSDQB) and the downwash flow field distribution were researched. A cuboid aluminum sampling frame of spatial spraying deposition quality balance (SFSSDQB) with monofilament wires was made for collecting the droplets in four directions, and a set of multi-channel micro-meteorology measurement system (MMMS) was applied for measuring the downwash wind speed in three directions. Besides, BeiDou Navigation Satellite System (BNSS) was used for controlling and recording the working height, velocity and track of this model of single-rotor UAV. The results showed the distribution of the spatial spray deposition and the downwash flow field of UAV could be measured effectively at exact flight height and velocity via this method. When the average wind speed was 0.9 m/s, the average temperature was 31.5°C and the average relative humidity was 34.1%, and the average distribution ratios of spraying deposition for model '3WQF80-10' UAV on the upwind part, the top part, the downwind part and the bottom part were 4.4%, 2.3%, 50.4% and 43.7%, respectively. The flight directions of forward and backward had an impact on droplet deposition distribution and the working effect of flying backwards, with 60% of deposition ratio of the bottom part of the SFSSDQB, was better than flying forward. There was a linear negative correlation between the coefficient of variation (CV) of the bottom part and the flight height and the coefficient of determination was 0.9178, which means that the deposition distribution becomes more uniform with the increase of height. Additionally, there was a linear positive correlation between weighted mean deposition rate and crosswind speed and the coefficient of determination was 0.9684, which shows the deposition distribution gets more concentrated towards the downwind part with the rise of crosswind speed. Therefore, according to the results of tests of downwash airflow speed, it is shown that regardless of the flight direction and height and the crosswind, all these factors influence the droplet deposition distribution via weakening the intensity of the downwash airflow field in the direction perpendicular to the ground. The results can provide valuable information for the research of UAV pesticide application techniques and the establishment of the standard of spraying deposition and drift tests of UAV in crop field.

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We developed a GPU-based analytical method, named as SHEsisEpi, which purely focuses on risk epistasis in a genome-wide association study (GWAS) of complex traits, excluding the contamination of marginal effects caused by single-locus association. We analyzed the Wellcome Trust Case Control Consortium's (WTCCC) GWAS data of bipolar disorder (BPD) with 500K SNPs. Our algorithm only used 27 h to finish the exhaustive scan and was more than 300 times faster than the CPUbased analysis on our system. Furthermore, by genotyping the top finding that met our criteria (P = 5.37 × 10 −12

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Sclerosing mesenteritis is a rare, benign, and chronic fibrosing inflammation disease with unknown etiology that affects the mesentery of small bowel and colon. The disease has two well-established histological types: the acute or subacute form known as mesenteric panniculitis and the chronic form known as retractile or sclerosing mesenteritis. Because the sclerosing mesenteritis is lack of special clinical manifestation and typical signs, so the patients are very easy to be misdiagnosed. The correct diagnosis of sclerosing mesenteritis depends on pathological examination and exploratory laparotomy. We report a case of sclerosing mesenteritis in a 52-year-old male who presented with chronic abdominal pain and intraabdominal mass. This patient had a long-term and heavy drinking history. He was misdiagnosed as celiac teratoma by CT examination and then underwent an exploratory laparotomy at March 2 2004. A mass, its diameter being about 5 cm, was detected in mesentery of distal ileum. Although a few small intestines tightly adhered on the mass, the involved intestine had no obstruction. The intraoperative biopsy indicated that it was an inflammatory mass. The mass and adhered intestines were removed. He was diagnosed with sclerosing mesenteritis by histopathological examination of paraffin section. After operation, this patient went well and lives without recrudescence at the time we wrote this paper.

Recently, lip image analysis has received much attention because its visual information is shown to provide improvement for speech recognition and speaker authentication. Lip image segmentation plays an important role in lip image analysis. In this paper, a new fuzzy clustering method for lip image segmentation is presented. This clustering method takes both the color information and the spatial distance into account while most of the current clustering methods only deal with the former. In this method, a new dissimilarity measure, which integrates the color dissimilarity and the spatial distance in terms of an elliptic shape function, is introduced. Because of the presence of the elliptic shape function, the new measure is able to differentiate the pixels having similar color information but located in different regions. A new iterative algorithm for the determination of the membership and centroid for each class is derived, which is shown to provide good differentiation between the lip region and the nonlip region. Experimental results show that the new algorithm yields better membership distribution and lip shape than the standard fuzzy c-means algorithm and four other methods investigated in the paper.

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