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Coherent Rayleigh scattering‐based distributed fibre optic sensing technology enables real‐time acquisition of vibration and acoustic information along the optical fibres. However, the complexity of monitoring environments often leads to false alarms and missed detections during the process of information source identification with distributed acoustic sensing (DAS). Therefore, it becomes crucial to effectively extract meaningful signal features and perform accurate pattern recognition in the presence of external noise disturbance. The authors provide a comprehensive review of signal feature extraction and pattern recognition techniques applied in DAS technology. After introducing the fundamentals of DAS, specific applications are considered, and the following techniques have been analysed and compared: feature extraction algorithms based on wavelet decomposition, feature extraction schemes utilising other decomposition models, traditional recognition classifiers, and neural network‐based recognition classifiers using deep learning. The advantages and limitations of each scheme are discussed, along with their potential applications in various scenarios. The aim is to provide insights into the latest technologies in signal processing and pattern recognition for DAS, fostering further advancements in this field. [ABSTRACT FROM AUTHOR]

The Covid-19 pandemic of 2019 was a global public health emergency, resulting in millions of deaths worldwide. The origin of pandemic was in China, where the disease was first reported in 2019 and in 2020, it became a global pandemic. Because of the economic and social effects caused by COVID-19, changes were made to China's economic model. The Chinese government wanted to protect their economy and people from the virus, so they invested a lot of money into combating the pandemic. Economic development is when a country's economy becomes more advanced than other countries. If it has good infrastructure and employment opportunities, it will become richer (McBryde et al., 2020). An economy can advance quickly through technological advancement, education, and increasing demand for goods and services. When China first experienced the pandemic, it had a rich economy and grew quickly. China was rapidly developing in terms of technology, education, and infrastructure. China's economic model took a turn for the worse when the COVID-19 pandemic hit it. The virus spread quickly, causing millions of deaths in China (Dhar, 2020). The Chinese government was forced to invest billions of RMB into research and to treat those affected by the virus. After COVID-19, China's economy fell into a slight recession. This could have been caused by a drop in exports, an increased mortality rate, and the government spending billions on stopping the pandemic. This paper will first give an overview of previous economic models that China used, then it will discuss how the COVID-19 pandemic changed China's economic model, and finally, this paper will look at the impact that COVID-19 had on China's economy.

Simple Summary: The cotton mealybug, Phenacoccus solenopsis, native to the USA, is a globally invasive quarantine pest. This pest has now spread to more than 43 countries and covered all continents except Antarctica, posing a serious threat to agricultural and forestry production, as well as biosecurity. The niche conservatism hypothesis states a tendency for species to maintain their original ecological niches in time and space and has been widely debated. In this study, based on the multidimensional hypervolume analysis and species distribution model, we identified the niche dynamics of this pest and further assessed its global invasion risk. The results indicated that the niche hypervolume in invasive ranges was significantly larger than that in native ranges, with 99.45% of the niche differentiation contributed by niche expansion rather than spatial replacement. Niche expansion was especially evident in Oceania and Eurasia. Compared to 2017, the current area of suitable habitats had increased significantly and this pest would expand northwards from the south in future climate change scenarios. The invasion risk in North Africa, northern China, areas along the Mediterranean, and northern Europe should not be ignored. As a globally invasive quarantine pest, the cotton mealybug, Phenacoccus solenopsis, is spreading rapidly, posing serious threats against agricultural and forestry production and biosecurity. In recent years, the niche conservatism hypothesis has been widely debated, which is particularly evident in invasive biology research. Identifying the niche dynamics of P. solenopsis, as well as assessing its global invasion risk, is of both theoretical and practical importance. Based on 462 occurrence points and 19 bioclimatic variables, we used n-dimensional hypervolume analysis to quantify the multidimensional climatic niche of this pest in both its native and invasive ranges. We examined niche conservatism and further optimized the MaxEnt model parameters to predict the global invasion risk of P. solenopsis under both current and future climate conditions. Our findings indicated that the niche hypervolume of this pest in invasive ranges was significantly larger than that in its native ranges, with 99.45% of the niche differentiation contributed by niche expansion, with the remaining less than 1% explained by space replacement. Niche expansion was most evident in Oceania and Eurasia. The area under the receiver operating characteristic curve (0.83) and true skill statistic (0.62) indicated the model's robust performance. The areas of suitable habitats for P. solenopsis are increasing significantly and the northward spread is obvious in future climate change scenarios. North Africa, northern China, Mediterranean regions, and northern Europe had an increased invasion risk of P. solenopsis. This study provided scientific support for the early warning and control of P. solenopsis. [ABSTRACT FROM AUTHOR]

Carbon Nanotubes (CNTs) filled with metals can be used in capacitors, sensors, rechargeable batteries, and so on. Atomic arrangement of the metals has an important role in the function of the composites. The tips of CNTs were opened, and then nickel was filled by means of hydrothermal oxidation/ultrasonic vibration method. The tests of TEM, HREM, and EDX (energy-dispersive X-ray spectroscopy) analysis showed that Ni was filled in CNTs successfully. The atomic arrangement of nickel filled into single wall carbon nanotubes was investigated by molecular dynamics simulation. The radial distribution function and bond orientation order were established to analyze the atomic arrangement of nickel filled in carbon nanotubes during the cooling process. The results show that nickel atoms became in order gradually and preferably crystallized on the inner wall of carbon nanotubes when the temperature decreased from 1600 K. After it cooled to 100 K, the arrangement of nickel atoms in outermost circle was regular and dense, but there were many defects far from the wall of CNTs. According to the calculation of bond orientation order parameters Q6 and its visualization, the structure of nickel is Face-centered cube (f.c.c). (1,1,1)Ni was close on the inner surface of carbon nanotubes. Radial direction of CNTs was [1,1,1] crystal orientation. Axial direction of CNTs, namely, filling direction, was [1, 1 ,2] crystal orientation. [ABSTRACT FROM AUTHOR]

A Gram-stain-negative, facultatively aerobic, motile and ovoid- to rod-shaped bacterium, designated as FT324 T , was isolated from a surface mangrove sediment sample from Shenzhen, PR China. The taxonomic position of strain FT324 T was determined by a combination of phylogenetic, physiological, biochemical and chemotaxonomic analyses. Strain FT324 T grew at 20-40 °C (optimum, 30-37 °C), pH 5.0-9.0 (optimum, pH 8.0) and in the presence of 0-3 % (w/v) NaCl (optimum, 1 %). Its full-length 16S rRNA gene sequence was the most similar to Frigidibacter oleivorans XJ4 T (97.4 %), followed by Defluviimonas denitrificans DSM 18921 T (96.62 %), Pseudothioclava arenosa CAU 1312 T (96.54 %) and Defluviimonas nitratireducens DL5-4 T (96.47 %). The major fatty acids (>10 %) of FT324 T were C 19 : 0 cyclo ω 8 c (51.9 %) and summed feature 8(29.6 %). The predominant respiratory quinone was Q-10. Its polar lipid profile contained phosphatidylethanolamine, phosphatidylmethylethanolamine, phosphatidylglycerol, diphosphatidylglycerol, one unidentified aminolipid, one unidentified lipid and two unidentified phospholipids. Its estimated genome size was 4 294 115 bp and the genomic DNA G+C content was 69.6 mol%. Based on its distinct phenotypic, chemotaxonomic and phylogenetic characteristics, strain FT324 T should represent a novel species of the genus Defluviimonas , for which the name Defluviimonas sediminis sp. nov. is proposed (=MCCC 1K07685 T =KCTC 92477 T ).