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Severe fever with thrombocytopenia syndrome virus (SFTSV) is spreading rapidly in Asia. This virus is transmitted by the Asian longhorned tick (Haemaphysalis longicornis), which has parthenogenetically and sexually reproducing populations. Parthenogenetic populations were found in ≥15 provinces in China and strongly correlated with the distribution of severe fever with thrombocytopenia syndrome cases. However, distribution of these cases was poorly correlated with the distribution of populations of bisexual ticks. Phylogeographic analysis suggested that the parthenogenetic population spread much faster than bisexual population because colonization is independent of sexual reproduction. A higher proportion of parthenogenetic ticks was collected from migratory birds captured at an SFTSV-endemic area, implicating the contribution to the long-range movement of these ticks in China. The SFTSV susceptibility of parthenogenetic females was similar to that of bisexual females under laboratory conditions. These results suggest that parthenogenetic Asian longhorned ticks, probably transported by migratory birds, play a major role in the rapid spread of SFTSV.

Introduction of vacancies is a promising route to enhance the performance of electrocatalysts by tuning the electronic structure and bonding energy. Here, the influence of ultrasound treatment on the O vacancies formation and interlayer spacing in NiFe layered double hydroxide (LDH) was investigated. It is found that the strong ultrasound treatment results in rich O vacancies on the surface of NiFe LDH, which affect the electrocatalysis performance. Besides, the ultrasound treated NiFe LDH electrocatalysts had a reduced thickness with a hexagonal nanosheet morphology and expanded interlayer distance, which could promote the diffusion of reactant and generated gas. When the obtained defect-rich NiFe LDH electrocatalyst prepared by a 10-min ultrasonic treatment was applied to catalyze oxygen evolution reaction (OER), only 194 mV of overpotential was needed to maintain a current density of 10 mA·cm−2.

To address the problems of high cost of new ammunition experiment, few data of field test and low accuracy of consumption prediction, this article proposes a Bayesian estimation method of ammunition consumption based on normal-inverse gamma distribution, and estimates the hyperparameters in the prior distribution through the prior information from the consumption of ammunition under different damage degrees of point targets, based on the normal distribution phenomenon of ammunition consumption at each damage degree. It is to establish a Bayesian estimation model for ammunition consumption under different damage degrees according to field test data based on Bayesian formula and solve for its posterior distribution. The example proves that the estimation results of ammunition consumption for point target with different damage degrees based on this method is more scientific and reasonable according to various prior information.

Micro/nanofibers have been widely applied to mimic the fibrillary structure of collagen type I from a bionic point of view, however, the wavy structure of collagen fibers in biological tissues such as arteries and ligaments has hardly been fabricated. In this study, a universal method was developed to fabricate the crimped fibers of different biopolymers by controlling the relaxation of residual stress, allowing the resulting scaffold a stable nonlinear elasticity. The effects of the processing conditions such as pre-strain, temperature of plasticizer, and fixed contraction length on the crimped fiber structure have been investigated. The results suggested that an engineered nonlinear elasticity of the scaffolds can be tailored by tuning the crimped structure. Human umbilical vein endothelial cells (HUVECs) cultured on the mat with crimped fibers showed promoted cell adhesion and cell spreading. Crimped fibers might have a great potential for repairing tendons and soft connective tissue and for constructing of tissue-engineering vascular grafts.

Metal organic frameworks (MOFs) show excellent electrochemical performances due to their ultrahigh porosity, large specific surface area, and easy functionalization. These characteristics make it fascinating electrode materials with excellent electrochemical performance for the currently dominated lithium-based batteries (e.g., Li-ion batteries, Li-S batteries, Li-O2 batteries). Hence, this review summarizes the recent advances of MOFs-based materials as an electrode for high-performance lithium-ion storage. Firstly, we briefly describe the development history, principle, and mechanism of the lithium-based batteries. Then, the recent advances of MOFs/MOFs composite and MOF-derived materials employed as electrode materials for Lithium-ion batteries, Li-S batteries, and Li-O2 batteries are reviewed with their electrochemical performances. Finally, we conclude and point out the future direction of MOFs-related materials for lithium-based batteries.

Functional hydrogels with properties that mimic the structure of extracellular matrix (ECM) and regulate cell behaviors have drawn much attention in biomedical applications. Herein, gelatin-based hydrogels were designed and loaded with chondroitin sulfate (CS) to endow biological regulation on the angiogenesis behaviors of endothelial cells (ECs). Manufactured hydrogels containing various amounts of CS were characterized via methods including mechanical tests, cytocompatibility, hemolysis, and angiogenesis assays. The results showed that the prepared hydrogels exhibited excellent mechanical stability, cytocompatibility, and hemocompatibility. Additionally, the angiogenesis behaviors of ECs were obviously promoted. However, excessive loading of CS would weaken the effect due to a higher proportion of occupation on the cell membrane. In conclusion, this investigation highlights the great potential of these hydrogels in treating ischemic diseases and accelerating tissue regeneration in terms of regulating the angiogenesis process via CS release.

At present, pointer meters are still widely used because of their mechanical stability and electromagnetic immunity, and it is the main trend to use a computer vision-based automatic reading system to replace inefficient manual inspection. Many correction and recognition algorithms have been proposed for the problems of skew, distortion, and uneven illumination in the field-collected meter images. However, the current algorithms generally suffer from poor robustness, enormous training cost, inadequate compensation correction, and poor reading accuracy. This paper first designs a meter image skew-correction algorithm based on binary mask and improved Mask-RCNN for different types of pointer meters, which achieves high accuracy ellipse fitting and reduces the training cost by transfer learning. Furthermore, the low-light enhancement fusion algorithm based on improved Retinex and Fast Adaptive Bilateral Filtering (RBF) is proposed. Finally, the improved ResNet101 is proposed to extract needle features and perform directional regression to achieve fast and high-accuracy readings. The experimental results show that the proposed system in this paper has higher efficiency and better robustness in the image correction process in a complex environment and higher accuracy in the meter reading process.