On a New Problem of High-speed Landslides

This paper has discussed the problem proposed about multiple stroke of high-speed landslides its multiple strokes 1 change of energy, and overstepping gas billows spattered with mud

Mapping the tail fiber as the receptor binding protein responsible for differential host specificity of Pseudomonas aeruginosa bacteriophages PaP1 and JG004.

The first step in bacteriophage infection is recognition and binding to the host receptor, which is mediated by the phage receptor binding protein (RBP). Different RBPs can lead to differential host specificity. In many bacteriophages, such as Escherichia coli and Lactococcal phages, RBPs have been identified as the tail fiber or protruding baseplate proteins. However, the tail fiber-dependent host specificity in Pseudomonas aeruginosa phages has not been well studied. This study aimed to identify and investigate the binding specificity of the RBP of P. aeruginosa phages PaP1 and JG004. These two phages share high DNA sequence homology but exhibit different host specificities. A spontaneous mutant phage was isolated and exhibited broader host range compared with the parental phage JG004. Sequencing of its putative tail fiber and baseplate region indicated a single point mutation in ORF84 (a putative tail fiber gene), which resulted in the replacement of a positively charged lysine (K) by an uncharged asparagine (N). We further demonstrated that the replacement of the tail fiber gene (ORF69) of PaP1 with the corresponding gene from phage JG004 resulted in a recombinant phage that displayed altered host specificity. Our study revealed the tail fiber-dependent host specificity in P. aeruginosa phages and provided an effective tool for its alteration. These contributions may have potential value in phage therapy

Localization Transformation of Five Coordinate Milling Machine

AbstractAs five coordinates gantry milling machine is not able to meet the requirements of the parts of precision and efficient processing, for the machine tool's electrical function degradation, mechanical part aging, CNC system backward, now it needs to upgrade the whole electrification and fix the mechanical part by Huangzhong, HNC - 848 c/M bus type numerical control system. Though the machine localization reformation, the precision and efficiency of the machine tool are improved, thus the application of domestic CNC system and functional components in the machine tool are promoted

Applications for Drowning Identification by Planktonic Diatom Test on Rats in Forensic Medicine

AbstractWe established a model of drowning, and by investigating diatoms in lung, liver, kidney, and long bone marrow of rats at different time to discuss the cause of death. The organs of 35 rats were extracted 0.5h, 1h, 6h, 12h, 24h and 48h after drowning and the organs of sham-drowning group killed by mechanical asphyxia were extracted 1h after body immersed in water. The organs were digested by acid, and the diatoms were analyzed by statistics. Results shown the detection rate was 100% in lung, and the positive rate of all the extracted organs was 100% 6hours after drowning except the sham-drowning group. No diatoms were detected in the liver, kidney and bone marrow of the sham-drowning group, just only one case was positive in the lung. So it is concluded that the detection rate of diatoms could be considered as important evidence in drowning determination

Multiobjective Transmission Network Planning considering the Uncertainty and Correlation of Wind Power

In order to consider the uncertainty and correlation of wind power in multiobjective transmission network expansion planning (TNEP), this paper presents an extended point-estimation method to calculate the probabilistic power flow, based on which the correlative power outputs of wind farm are sampled and the uncertain multiobjective transmission network planning model is transformed into a solvable deterministic model. A modified epsilon multiobjective evolutionary algorithm is used to solve the above model and a well-distributed Pareto front is achieved, and then the final planning scheme can be obtained from the set of nondominated solutions by a fuzzy satisfied method. The proposed method only needs the first four statistical moments and correlation coefficients of the output power of wind farms as input information; the modeling of wind power is more precise by considering the correlation between wind farms, and it can be easily combined with the multiobjective transmission network planning model. Besides, as the self-adaptive probabilities of crossover and mutation are adopted, the global search capabilities of the proposed algorithm can be significantly improved while the probability of being stuck in the local optimum is effectively reduced. The accuracy and efficiency of the proposed method are validated by IEEE 24 as well as a real system

MS-DCANet: A Novel Segmentation Network For Multi-Modality COVID-19 Medical Images

The Coronavirus Disease 2019 (COVID-19) pandemic has increased the public health burden and brought profound disaster to humans. For the particularity of the COVID-19 medical images with blurred boundaries, low contrast and different sizes of infection sites, some researchers have improved the segmentation accuracy by adding model complexity. However, this approach has severe limitations. Increasing the computational complexity and the number of parameters is unfavorable for model transfer from laboratory to clinic. Meanwhile, the current COVID-19 infections segmentation DCNN-based methods only apply to a single modality. To solve the above issues, this paper proposes a symmetric Encoder-Decoder segmentation framework named MS-DCANet. We introduce Tokenized MLP block, a novel attention scheme that uses a shift-window mechanism similar to the Transformer to acquire self-attention and achieve local-to-global semantic dependency. MS-DCANet also uses several Dual Channel blocks and a Res-ASPP block to expand the receptive field and extract multi-scale features. On multi-modality COVID-19 tasks, MS-DCANet achieved state-of-the-art performance compared with other U-shape models. It can well trade off the accuracy and complexity. To prove the strong generalization ability of our proposed model, we apply it to other tasks (ISIC 2018 and BAA) and achieve satisfactory results