Mosapride combined with probiotics on gastrointestinal function and growth in premature infants.

The aim of this study was to investigate the effects of mosapride combined with probiotics on gastrointestinal function and growth and development in premature infants. A total of 240 premature infants treated at Weifang People's Hospital between June 2012 and May 2015 who matched our criteria were randomly divided into three groups of 80 cases each. Group A received routine treatment, group B received routine treatment combined with live B. subtilis and E. faecium granules with multivitamins (Medilac-Vita), and group C received routine treatment and Saccharomyces boulardii sachets (Bioflor). Mosapride was administered to patients in groups B and C to promote intestinal peristalsis. Gastrin and bilirubin levels, as well as jaundice fade time, were recorded. Growth and development condition (i.e., head circumference and weight), duration and incidence of feeding intolerance (FI), as well as other symptoms were also analyzed. By day 14, gastrin concentrations in groups B and C were significantly higher than those in group A (P<0.05). Serum bilirubin levels in groups B and C showed a progressive decline from day 7 to day 14, and jaundice duration in group A was significantly longer (P<0.05). Furthermore, at 2 weeks, the average weight growth rate and head circumference were significantly greater in groups B and C, weight loss recovery time was shorter, and EUGR incidence was lower (P<0.05). The incidence rate of gastric retention and FI were lower in groups B and C than group A (P<0.05), and neonatal hyperbilirubinemia, parenteral nutrition-associated cholestasis, necrotizing enterocolitis, and neonatal sepsis incidence was significantly lower in groups B and C (P<0.05). Mosapride combined with probiotics can effectively reduce FI incidence in premature infants, shorten enteral feeding time, promote the absorption of required nutrients, and promote the development and recovery of early physiological weight loss in preterm infants.

[Evaluation of high-resolution images application for wild medicinal plants macro monitoring: a case of Apocynum].

To investigate the resources of medicinal plant, such as wild Apocynum, supervised classification based on Principal Component Analysis (PCA) and texture feature were used to monitor wild medicinal plants from image captured by ZY-3 and World-view-2 and compare which satellite Image are more appropriate to monitor the wild medicinal plants. The research results shows that: for more complex growth conditions wild medicinal plants Apocynum, high-resolution images Worldview-2 is more suitable for its remote identification, the low-resolution satellite ZY-3 can only recognizes the wild medicinal plants which distributed intensively. If the study target distribution is more intensive and larger scale, and cultivated type medicinal plants, the use of satellite ZY-3 in low resolution remote sensing data to identify the target can be a good choice, it is not necessary to buy high-resolution data, in order to avoid waste of expenditure, for the scattered distribution, the high-resolution satellite imagery data may be indispensable to identify targets.

[Measurement of sown area of safflower based on PCA and texture features classification and remote sensing imagery].

To improve accuracy of estimation in planted safflower acreage,we selected agricultural area in Yumin County, Xinjiang as the study area. There safflower was concentrated planted. Supervised classification based on Principal Component Analysis (PCA) and texture feature were used to obtain the safflower acreage from image captured by ZY-3. The classification result was compared with only spectral feature and spectral feature with texture feature. The research result shows that this method can effectively solve the problem of low accuracy and fracture classification result in single data source classification. The overall accuracy is 87.519 1%, which increases by 7.117 2% compared with single data source classification. Therefore, the classification method based on PCA and texture features can be adapted to RS image classification and estimate the acreage of safflower. This study provides a feasible solution for estimation of planted safflower acreage by image captured by ZY-3 satellite.