Flowmeter for large-scale pipes

AbstractThis paper studied a new type of flowmeter, the bypass flowmeter. It is suitable for large-scale pipes. The principle of bypass flowmeter is studied by analyzing flowing in parallel pipes and carrying out experiments at a modified performance test system for centrifugal pumps. The study results showed that the flowrate ratio between the main pipe and the bypass pipe is determined by the geometric structures of pipes and the flowing states in the pipes. The flowrate ratio varies greatly when the Reynolds numbers are relatively lower both in the main pipe and the bypass pipe. The flowrate ratio keeps constant when the Reynolds number in the main pipe is larger than 120000. The head loss becomes smaller when the bypass pipe is connected to the main pipe. The percentage of head loss decrease is from 7.64% to 9.34%. The results indicate that bypass flowmeter is suitable for flowrate measuring in large scale pipes. It will not cause additional head loss to the flow

Inverse Projection Representation and Category Contribution Rate for Robust Tumor Recognition

Sparse representation based classification (SRC) methods have achieved remarkable results. SRC, however, still suffer from requiring enough training samples, insufficient use of test samples and instability of representation. In this paper, a stable inverse projection representation based classification (IPRC) is presented to tackle these problems by effectively using test samples. An IPR is firstly proposed and its feasibility and stability are analyzed. A classification criterion named category contribution rate is constructed to match the IPR and complete classification. Moreover, a statistical measure is introduced to quantify the stability of representation-based classification methods. Based on the IPRC technique, a robust tumor recognition framework is presented by interpreting microarray gene expression data, where a two-stage hybrid gene selection method is introduced to select informative genes. Finally, the functional analysis of candidate's pathogenicity-related genes is given. Extensive experiments on six public tumor microarray gene expression datasets demonstrate the proposed technique is competitive with state-of-the-art methods.Comment: 14 pages, 19 figures, 10 table

Main factors influencing the gut microbiota of Datong yaks in mixed group

The Datong yak (Bos grunniens) is the first artificial breed of yaks in the world and has played an important role in the improvement of domestic yak quality on the Qinghai-Tibet Plateau. The Datong yak breeding farm in the Qinghai province of China is the main place for the breeding and feeding of Datong yaks. It hosts domestic Datong yaks and wild male yaks, mainly in mixed groups. Different managements have different effects on livestock. The gut microbiota is closely related to the health and immunity of Datong yaks, and mixed grouping can affect the composition and diversity of the gut microbiota of Datong yaks. To reveal the effects of mixed grouping on the gut microbiota of Datong yaks and wild yaks and identify the main dominant factors, we compared the gut microbial diversities of domestic males and females and wild males based on 16S rRNA V3–V4 regions using fresh fecal samples. The data showed significant differences in the gut microbial diversity of these three groups, and the α-diversity was the highest in wild males. Different factors influence the gut microbiota, and the main influencing factors were different in different groups, including sex differences, host genetics, and physical interactions. We also compared ecological assembly processes in the three groups. The results showed that mixed grouping contributed to the improvement of gut microbial diversity in domestic females. Our study provides effective and feasible suggestions for the feeding and management of the Datong yaks

Future Changes in Mean and Extreme Monsoon Precipitation in the Middle and Lower Yangtze River Basin, China, in the CMIP5 Models

In this study, the potential future changes of mean and extreme precipitation in the middle and lower Yangtze River basin (MLYRB), eastern China, are assessed using the models of phase 5 of the Coupled Model Intercomparison Project (CMIP5). Historical model simulations are first compared with observations in order to evaluate model performance. In general, the models simulate the precipitation mean and frequency better than the precipitation intensity and extremes, but still have difficulty capturing precipitation patterns over complex terrains. They tend to overestimate precipitation mean, frequency, and intensity while underestimating the extremes. After correcting for model biases, the spatial variation of mean precipitation projected by the multimodel ensemble mean (MME) is improved, so the MME after the bias correction is used to project changes for the years 2021–50 and 2071–2100 relative to 1971–2000 under two emission scenarios: RCP4.5 and RCP8.5. Results show that with global warming, precipitation will become less frequent but more intense over the MLYRB. Relative changes in extremes generally exceed those in mean precipitation. Moreover, increased precipitation extremes are also expected even in places where mean precipitation is projected to decrease in 2021–50. The overall increase in extreme precipitation could potentially lead to more frequent floods in this already flood-prone region