Hydrological daily rainfall-runoff simulation with BTOPMC model and comparison with Xin'anjiang model

A grid-based distributed hydrological model, the Block-wise use of TOPMODEL （BTOPMC）, which was developed from the original TOPMODEL, was used for hydrological daily rainfall-runoff simulation. In the BTOPMC model, the runoff is explicitly calculated on a cell-by-cell basis, and the Muskingum-Cunge flow concentration method is used. In order to test the model＇s applicability, the BTOPMC model and the Xin＇anjiang model were applied to the simulation of a humid watershed and a semi-humid to semi-arid watershed in China. The model parameters were optimized with the Shuffle Complex Evolution （SCE-UA） method. Results show that both models can effectively simulate the daily hydrograph in humid watersheds, but that the BTOPMC model performs poorly in semi-humid to semi-arid watersheds. The excess-infiltration mechanism should be incorporated into the BTOPMC model to broaden the model＇s applicability.

Bone marrow mesenchymal stem cell therapy regulates gut microbiota to improve post-stroke neurological function recovery in rats

BACKGROUND As a cellular mode of therapy,bone marrow mesenchymal stem cells(BMSCs)are used to treat stroke.However,their mechanisms in stroke treatment have not been established.Recent evidence suggests that regulation of dysregulated gut flora after stroke affects stroke outcomes.AIM To investigate the effects of BMSCs on gut microbiota after ischemic stroke.METHODS A total of 30 Sprague-Dawley rats were randomly divided into three groups,including sham operation control group,transient middle cerebral artery occlusion(MCAO)group,and MCAO with BMSC treatment group.The modified Neurological Severity Score(mNSS),beam walking test,and Morris water maze test were used to evaluate neurological function recovery after BMSC transplantation.Nissl staining was performed to elucidate on the pathology of nerve cells in the hippocampus.Feces from each group of rats were collected and analyzed by 16s rDNA sequencing.RESULTS BMSC transplantation significantly reduced mNSS(P<0.01).Rats performed better in the beam walking test in the BMSC group than in the MCAO group(P<0.01).The Morris water maze test revealed that the BMSC treatment group exhibited a significant improvement in learning and memory.Nissl staining for neuronal damage assessment after stroke showed that in the BMSC group,cells were orderly arranged with significantly reduced necrosis.Moreover,BMSCs regulated microbial structure composition.In rats treated with BMSCs,the abundance of potential short-chain fatty acid producing bacteria and Lactobacillus was increased.CONCLUSION BMSC transplantation is a potential therapeutic option for ischemic stroke,and it promotes neurological functions by regulating gut microbiota dysbiosis.

Hydraulic model with roughness coefficient updating method based on Kalman filter for channel flood forecast

A real-time channel flood forecast model was developed to simulate channel flow in plain rivers based on the dynamic wave theory. Taking into consideration channel shape differences along the channel, a roughness updating technique was developed using the Kalman filter method to update Manning＇s roughness coefficient at each time step of the calculation processes. Channel shapes were simplified as rectangles, triangles, and parabolas, and the relationships between hydraulic radius and water depth were developed for plain rivers. Based on the relationship between the Froude number and the inertia terms of the momentum equation in the Saint-Venant equations, the relationship between Manning＇s roughness coefficient and water depth was obtained. Using the channel of the Huaihe River from Wangjiaba to Lutaizi stations as a case, to test the performance and rationality of the present flood routing model, the original hydraulic model was compared with the developed model. Results show that the stage hydrographs calculated by the developed flood routing model with the updated Manning＇s roughness coefficient have a good agreement with the observed stage hydrographs. This model performs better than the original hydraulic model.

A multistandard and resource-efficient Viterbi decoder for a multimode communication system

We present a novel standard convolutional symbols generator(SCSG)block for a multi-parameter reconfigurable Viterbi decoder to optimize resource consumption and adaption of multiple parameters.The SCSG block generates all the states and calculates all the possible standard convolutional symbols corresponding to the states using an iterative approach.The architecture of the Viterbi decoder based on the SCSG reduces resource consumption for recalculating the branch metrics and rearranging the correspondence between branch metrics and transition paths.The proposed architecture supports constraint lengths from 3 to 9,code rates of 1/2,1/3,and 1/4,and fully optional polynomials.The proposed Viterbi decoder has been implemented on the Xilinx XC7VX485T device with a high throughput of about 200 Mbps and a low resource consumption of 162k logic gates.