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Abstract Lepus oiostolus (L. oiostolus) is a species endemic to the Qinghai-Tibet Plateau. However, the absence of a reference genome limits genetic studies. Here, we reported a high-quality L. oiostolus genome assembly, with scaffolds anchored to 24 chromosomes and a total assembled length of 2.80 Gb (contig N50 = 64.25 Mb). Genomic annotation uncovered 22,295 protein-coding genes and identified 49.84% of the sequences as transposable elements. Long interspersed nuclear elements (LINEs) constitute a high proportion of the genome. Our study is at the first time to report the chromosome-scale genome for the species of the L. oiostolus. It provides a valuable genomic resource for future research on the evolution of the Leporidae.

Microbial resistance has now become a global public health concern, and the spread of multidrug-resistant bacteria also threatens human health. Antimicrobial peptides (AMPs) are a class of small peptides with antibacterial, anti-inflammatory, anti-infective, anti-oxidation, anti-tumor, antiviral functions and immune regulation activities. Due to the small sizes, their structures are easily studied by nuclear magnetic resonance (NMR) techniques. Compared to traditional antibiotics, AMPs have specific antibacterial mechanisms, and do not easily result in the production of drug-resistant strains. Thus, the development of new antimicrobial peptides and their wide use instead of chemical antibiotics are of great significance to human health. In this review, we first summarized the relationship between the structures and functions of antimicrobial peptides. Then, we focused on examples, cathelicidins, a group of cationic antimicrobial peptides with multiple biological activities. Especially, cathelicidin BF30 or BF34, composed of 30 or 34 amino acids, were from the venom glands of the Bungarus fasciatus snake and were considered to be the most active antibacterial peptides among different cathelicidin members. Their solution structures determined by NMR are α-helixes, which are useful in designing new and stable peptides with similar framework, including stapple peptides by inducing chemical modifications in the sidechains of some residues, as well as cyclic peptides by inducing disulfide bond between cysteines in the sequences.

In applications of software testing, the cause–effect graph method is an approach often used to design test cases by analyzing various combinations of inputs with a graphical approach. However, not all inputs have equal impacts on the results, and approaches based on exhaustive testing are generally time-consuming and laborious. As a statute-based software-testing method, combinatorial testing aims to select a small but effective number of test cases from the large space of all possible combinations of the input values for the software to be tested, and to generate a set of test cases with a high degree of coverage and high error detection capability. In this paper, the reduced ordered binary decision diagram is utilized to simplify the cause–effect graph so as to reduce the numbers of both the inputs and test cases, thereby saving the testing cost. In addition, an improved particle swarm optimization algorithm is proposed to significantly reduce the computation time needed to generate test cases. Experiments on several systems show that the proposed method can generate excellent results for test case generation.

ObjectiveThis paper aims to study the application effects of heterogeneous supercomputing platforms based on domestic processors in the field of ship hydrodynamics.MethodsThe direct numerical simulation of the flow around a 3D finite square cylinder with Re = 250 using the Sunway Taihu Light supercomputer is implemented, in which the maximum number of grids is 245.76 million ( t = 600 s, dt = 0.001), and the simulation results are analyzed and verified. The parallel programming method of MPI+Threads is used with a maximum parallel size of 133 120 cores.ResultsAccording to the statistics, the calculation can be completed in a few days under the current parallel scale using 245.76 million grids. In addition, the simulation results show that the vortex shedding is synchronous in different cross-sections of a 3D finite square cylinder. When the characteristics of flow around the finite square cylinder with slenderness ratios of 2, 3 and 4 are compared, it is found that when the slenderness ratio is 2, the wake vortex structure of the wake is a long straight streamwise vortex secondary structure, or else it is an antisymmetric Karman vortex.ConclusionThese results indicate that multilevel parallel computing using the Sunway Taihu Light supercomputer can effectively reduce the time-consumption caused by grid scale increase in small-scale grids, which has broad application prospects in the field of ship hydrodynamics.

Hemorrhagic transformation (HT) is one of the common complications in patients with acute ischemic stroke (AIS). This study aims to investigate the value of different thresholds of Tmax generated from perfusion-weighted MR imaging (PWI) and the apparent diffusion coefficient (ADC) value in the prediction of HT in AIS. A total of 156 AIS patients were enrolled in this study, with 55 patients in the HT group and 101 patients in non-HT group. The clinical baseline data and multi-parametric MRI findings were compared between HT and non-HT groups to identify indicators related to HT. The optimal parameters for predicting HT and the corresponding cutoff values were obtained using the receiver operating characteristic curve analysis of the volumes of ADC < 620 × 10−6 mm2/s and Tmax > 6 s, 8 s, and 10 s. The results showed that the volumes of ADC < 620 × 10−6 mm2/s and Tmax > 6 s, 8 s, and 10 s in the HT group were all significantly larger than that in the non-HT group and were all independent risk factors for HT. Early measurement of the volume of Tmax > 10 s had the highest value, with a cutoff lesion volume of 10.5 mL.

Due to various uncontrollable factors (such as random faulty acquisition equipment and data distortion), urban traffic flow data inevitably suffers from some form of data loss. Finding an effective filling method to estimate the missing data is of great help to the study of transportation networks. Traffic flow during a day are likely to have its regular peak period and off-peak period. For most regions of the urban road network, normally there is a certain trend in the traffic flow data. In this paper, we propose a data imputation method that employs a tensor decomposition approach, which fully considers the characteristics of the traffic flow in both time and space. The proposed method is based on high order singular value decomposition with soft thresholding core. In this method, traffic data are divided into its main trend part and the residual part, which is called detrending. And tensor decomposition is performed on these two parts separately. For each part, dynamic rank method is used to adjust the rank of tensor decomposition. With the actual 214 anonymous road segments with 10 minutes interval data in Guangdong, China, the highway data with 15 minutes interval in Madrid, Spain, and the traffic flow data from PeMS with 5 minutes interval in California, USA. The results of the different models are discussed in the case of continuous data missing and random data missing by different time intervals. In addition, by comparing with other data imputation methods, our method can fill the missing data with better performance.

Well-child health care services are essential for maintaining optimum child health and development. This study's aim was to evaluate the quality of such services and identify factors affecting service quality from the perspective of well-child health care providers located in China's Hunan Province. To achieve this, a qualitative descriptive method was employed, with 22 well-child health care providers being recruited, using purposive sampling, from among the provinces' government community health centers. The participants completed individual semi-structured interviews lasting approximately 25-30 minutes that were designed to obtain their views on well-child health care administration in the province. Then, the interview transcripts were analyzed thematically. The main finding was that participants felt that the delivery of well-child health care services in Hunan Province is insufficient. Factors they mentioned as negatively affecting the delivery of such services included the region's fragmented primary health care system, inadequate attention to this issue from parents and community health care center managers, and a lack of specialized well-child care knowledge. Thus, currently, well-child health care is not being successfully implemented in Hunan Province; consequently, in order to successfully implement well-child health care in this region, community health care centers should invest more resources and funding, particularly into education programs for well-child health care providers.