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Acute lung injury (ALI) is a severe form of respiratory failure characterized by altered lung mechanics and refractory hypoxemia. Globally, the condition presents a serious threat to human health. Morin is a potential active monomer that has beneficial therapeutic effects in ALI; however, its mechanism of action remains unclear. Herein, we found significant elevation of inflammation and pyroptosis in the lung tissue of mice with lipopolysaccharide-induced ALI. Additionally, morin blocked the activation of the TLR4/TRAF6/NF-κB pathway and synergically inhibited the entry of p65 into the nucleus by downregulating the expression of Kruppel-like factor 5. Morin also inhibited caspase-1 activation and protected the GSDMD protein from cleavage. These findings are evidence that morin alleviates ALI by blocking the NF-κB pathway, reducing inflammation, and inhibiting macrophage pyroptosis.

Autism spectrum disorder (ASD) is a prevalent neurodevelopmental disorder characterized by atypical patterns of social interaction and communication as well as restrictive and repetitive behaviors. Additionally, ASD often presents with sleep disturbances. Delta (δ) catenin protein 2 (CTNND2) encodes δ-catenin protein, a neuron-specific catenin implicated in many complex neuropsychiatric diseases. Our previous study had exhibited deletion of Ctnnd2 in mice lead to autism-like behaviors. However, to our knowledge, no studies have investigated the effects of Ctnnd2 deletion in sleep of mice. In this study, we investigated whether knockout (KO) of exon 2 of the Ctnnd2 gene could induce sleep-wake disorders in mice and identify the effects of oral melatonin (MT) supplementation on KO mice. Our results demonstrated that KO mice exhibited ASD-like behaviors and sleep-wake disorders and they were attenuated, in part, by MT supplementation. Moreover, we further proved the correlation between autism-like behaviors and sleep-wake disorders in KO mice. MT may improve ASD-like behaviors by attenuating sleep-wake dysfunction. Overall, our current study was the first to identify that knockdown of Ctnnd2 gene could induce sleep-wake disorders in mice and had a correlation between sleep and phenotypes of ASD in Ctnnd2 KO mice. Our findings suggest that treatment of sleep-wake disturbances benefits on Ctnnd2 gene-deletion caused autism-like behaviors.

Background To review our long-term clinical experience, analyze the failure patterns, and give suggestions for target volume delineation of carcinoma showing thymus-like differentiation (CASTLE) treated with intensity-modulated radiotherapy (IMRT). Methods From April 2008 to May 2019, 30 patients with CASTLE treated by postoperative or radical IMRT in our center were retrospectively reviewed. A total dose of 56-60 Gy in 28–30 fractions was prescribed to patients without residual disease and 66 Gy in 33 fractions for patients with residual or unresectable disease. Survival rates were calculated using the Kaplan-Meier method. Treatment-related toxicities were graded by National Cancer Institute Common Toxicity Criteria (NCI-CTC) version 4.0. Results Among the 30 patients, 12 (40%) received partial resection or biopsy. Lateral lymph node metastasis was observed in 7 (23.3%) patients. During follow-up, regional lymph node recurrence occurred in 2 patients and distant metastasis in 5 patients. With a median follow-up time of 63.5 months, the 5-year local recurrence-free survival (LRFS), regional recurrence-free survival (RRFS), distant metastasis-free survival (DMFS), overall survival (OS) and progression-free survival (PFS) rates were 100, 88.9, 78.9, 93.1 and 78.9%, respectively. For patients with no lateral neck node metastasis, prophylactic radiotherapy for lateral neck nodal regions failed to improve RRFS (p = 0.381) and OS (p = 0.153). Conclusion Distant metastasis was the major failure pattern for CASTLE after surgery and IMRT. For patients with no lateral neck node metastasis, the omission of irradiation for lateral neck nodal regions seems to be safe and feasible.

Rice plays a crucial role in food production worldwide as one of the most important cereal crops. Breeding blast disease resistant varieties is a long-term aim for sustainable rice production. II-32B is an elite maintainer line of II-32A which has been widely used as a hybrid rice parent in China. However, it is significantly susceptible to rice blast. In this study, multiple alleles, Pi-2 and Pi-9, and the chromosomal segment of blast resistance genes, Pi-1 and Pi-kh, were introgressed to receptor parents II-32B by marker-assisted backcross breeding. Eleven near-isogenic lines (NILs) with single Pi-gene and 12 pyramid lines containing double or three homozygous resistance genes were obtained. These improved lines were identified by inoculating Magnaporthe oryzae isolates in the field/greenhouses; the result showed that the resistance of pyramid lines containing three resistance genes was stronger than the lines with double or single gene, whereas the lines with double genes were stronger than the one with single-gene. Additionally, pyramiding of different Pi-genes was effective in obtaining the durable blast resistance in rice. This implies that gene pyramiding in rice can increase spectrum and strength of resistance to blast. Furthermore, three-line retention of sixteen improved NILs was kept well and the agronomic traits were consistence with II-32B. We conclude that gene pyramiding is an effective breeding approach for the improvement of rice varieties with durable resistance to blast in the future.

Melt shear flow behavior and melt shear viscosity are important characterization of processing properties for polymeric materials. The effects of microencapsulated red phosphorus (MRP) content and experimental conditions on the melt shear flow behavior of the polypropylene (PP) composites were investigated using a torque rheometer. It was found that the melt shear viscosity, the torque, and energy consumption at balance state of the composites increased nonlinearly with increasing MRP weight fraction while decreased slightly with increasing temperature, the maximum torque increased with increasing the roller speed, and the dependence of the melt shear viscosity and the energy consumption at balance state on temperature roughly obeyed the Arrhenius equation. These findings would provide useful data for processing these flame-retardant PP composites.

According to reliable survey data, the number of domestic electricity companies in China has exceeded 20,000. All provinces in the country are actively preparing for the reform of the spot market. In 2019 and 2020, the spot market in Guangdong, Zhejiang and other provinces will land. At that time, the profitability and load forecasting ability of each power supply company are the important links that must be considered in pushing the power supply company to the market. Power supply company's contract strategy, quotation strategy, transaction strategy and economic calculation of individual customers are very important, which will affect the vital interests of the power supply company. Especially for a single customer with huge power consumption, it is necessary to have a precise contract scheme to meet the needs of large customers. Therefore, it is not right to carry out user-level load forecasting. The forecast of the transformation and upgrading of the electricity market is forward-looking and urgent. With the basic data of electricity customers having a certain foundation, data analysis based on power data has a necessary foundation for accurate calculation and prediction of user-level load.

Starting from the description of big data value, this article firstly introduced the main sources and the chief characteristics of power big data, secondly elicited the background, present status and primary requirements of open sharing for power big data, and thirdly elaborated the key technologies which were involved in the open sharing pattern of power big data. Then, based on the analysis of open sharing and the technologies, the overall framework and technical route for the open sharing pattern of massive power big data were designed. Then, the open sharing pattern of power big data were designed in detail from the following three aspects: the way of metadata management, the mode of user access control for data open sharing, and the route of sharing service gateway generation, and then, this article gave the complete process which describes the steps of an open sharing service building, and all of these can help to achieve open sharing of massive power big data. Finally this article analyzed the effectiveness of open sharing for power big data in data mining and data transaction, summarized the open sharing pattern of massive power big data, and gave the prospects for the next step of data open sharing work.

The power load curve is describing the behavior of electricity consumption by customers. The curve characteristic information is obtained by mining and analyzing the power load curve, which can be used as the classification basis for power customers. Based on the massive characteristics of power load curve, the K-means clustering algorithm and Spark-based parallelization method are studied firstly, and on the basis of this, the parallel transformation of k-means algorithm is carried out. Then the preprocessing steps of the power load curve data and the detailed flow of the mining analysis are proposed, and the R parallelization algorithm is applied to the mining analysis of the actual power load curve data, through which the classification of electricity customers are achieved and verified. Finally, the R-based parallel clustering algorithm is briefly summarized.

An iris location method based on mathematical morphology and improved Hough transform is proposed in this paper. When locating the iris inner boundary, an iris inner boundary method based on mathematical morphology and circle fitting is proposed. The iris image is first preprocessed to get a binary image by the gray stretch transform or the circular region mean filter, and then the type of the connected region selected as the iris inner boundary in the binary image is determined by the ratio of the width to the length. On the foundation, the different method is used to extract the parameters of the connected region and the iris inner boundary is obtained. When locating the iris outer boundary, an iris outer boundary method based on the improved Hough transform is put forward. First, the Gaussian filter is used to deal with the iris image, the filtered image is reduced, Canny operator is employed for edge detection, an annular region centered at the center of the iris inner boundary of the reduced image is cropped to explore a circle by Hough transform, and the center and the radius of the iris outer boundary are worked out. The experimental results reveal that this proposed method has the advantages of fast speed, high accuracy, strong robustness and practicability.

The traveling-salesman problem can be regarded as an NP-hard problem. To better solve the best solution, many heuristic algorithms, such as simulated annealing, ant-colony optimization, tabu search, and genetic algorithm, were used. However, these algorithms either are easy to fall into local optimization or have low or poor convergence performance. This paper proposes a new algorithm based on simulated annealing and gene-expression programming to better solve the problem. In the algorithm, we use simulated annealing to increase the diversity of the Gene Expression Programming (GEP) population and improve the ability of global search. The comparative experiments results, using six benchmark instances, show that the proposed algorithm outperforms other well-known heuristic algorithms in terms of the best solution, the worst solution, the running time of the algorithm, the rate of difference between the best solution and the known optimal solution, and the convergent speed of algorithms.

The closest iterative point algorithm (ICP) is widely used in medical image registration. But there exist some problems in the following aspects. First, due to its heavily computational load, it has a time-consuming process and a low registration efficiency. Second, due to the fact that it heavily depends on whether the initial rotation and translation matrices of the floating point set can be exactly extracted, it often traps in the local optimum and even fails to register images. In addition, due to the complexity of medical images, it is difficult to automatically extract the salutary feature points. In this paper, by computing the coordinate inertia matrices of the reference and floating images, the rotation angles are obtained and referred to as the initial rotation parameters of ICP for image registration. The edges of the reference and floating images are detected by the edge convolution kernel so-called B-spline gradient operator (BSGO) and then the binarization images involving the feature points are acquired. The experimental results reveal that, this proposed method has a fairly simple implementation, a low computational load, a fast registration and good alignment accuracy. Also, It can efficiently avoid trapping in the local optimum and cater to both mono-modality and multi-modality image registrations.