Research on self-cross transformer model of point cloud change detecter

With the vigorous development of the urban construction industry, engineering deformation or changes often occur during the construction process. To combat this phenomenon, it is necessary to detect changes in order to detect construction loopholes in time, ensure the integrity of the project and reduce labor costs. Or the inconvenience and injuriousness of the road. In the study of change detection in 3D point clouds, researchers have published various research methods on 3D point clouds. Directly based on but mostly based ontraditional threshold distance methods (C2C, M3C2, M3C2-EP), and some are to convert 3D point clouds into DSM, which loses a lot of original information. Although deep learning is used in remote sensing methods, in terms of change detection of 3D point clouds, it is more converted into two-dimensional patches, and neural networks are rarely applied directly. We prefer that the network is given at the level of pixels or points. Variety. Therefore, in this article, our network builds a network for 3D point cloud change detection, and proposes a new module Cross transformer suitable for change detection. Simultaneously simulate tunneling data for change detection, and do test experiments with our network

GIS-Based Analysis of the Spatial Distribution and Influencing Factors of Traditional Villages in Hebei Province, China

Traditional villages are a valuable cultural asset that occupy an important position in Chinese traditional culture. This study focuses on 206 traditional villages in Hebei Province, and aims to explore their spatial distribution characteristics and influencing factors using ArcGIS spatial analysis. The analysis shows that traditional villages in Hebei Province were distributed in clus-ters during different historical periods, and eventually formed three core clusters in Shijiazhuang, Zhangjiakou and Xingtai-Handan after different historical periods. Moreover, the overall dis-tribution of traditional villages in Hebei Province is very uneven, with clear regional differences, and most of them are concentrated in the eastern foothills of the Taihang Mountains. To identify the factors influencing traditional villages, natural environmental factors, socio-economic factors, and historical and cultural factors are considered. The study finds that socio-economic and nat-ural environmental factors alternate in the spatial distribution of traditional villages in Hebei Province. The influence of the interaction of these factors increases significantly, and so-cio-economic factors have a stronger influence on the spatial distribution. Specifically, the spatial distribution of traditional villages in Hebei Province is influenced by natural environmental fac-tors, while socio-economic factors act as drivers of spatial distribution. Historical and cultural factors act as catalysts of spatial distribution, and policy directions are external forces of spatial distribution. Overall, this study provides valuable insights into the spatial distribution charac-teristics and influencing factors of traditional villages in Hebei Province, which can be used to develop effective strategies for rural revitalisation in China

Overall PSD and Fractal Characteristics of Tight Oil Reservoirs: A Case Study of Lucaogou Formation in Junggar Basin, China

Lucaogou tight oil reservoir, located in the Junggar Basin, Northwest of China, is one of the typical tight oil reservoirs. Complex lithology leads to a wide pore size distribution (PSD), ranging from several nanometers to hundreds of micrometers. To better understand PSD and fractal features of Lucaogou tight oil reservoir, the experiment methods including scanning electron microscope (SEM), rate-controlled mercury injection (RMI) and pressure-controlled mercury injection (PMI) were performed on the six samples with different lithology. The results indicate that four types of pores exist in Lucaogou tight oil reservoir, including dissolution pores, clay dominated pores, microfractures and inter-granular pores. A combination of PMI and RMI was proposed to calculate the overall PSD of tight oil reservoirs, the overall pore radius of Lucaogou tight oil reservoir ranges from 3.6 nm to 500µm. The fractal analysis was carried out based on the PMI data. Fractal dimension (Fd) values varied between 2.843 and 2.913 with a mean value of 2.88. Fd increases with a decrease of quartz content and an increase of clay mineral content. Samples from tight oil reservoirs with smaller average pore radius have stronger complexity of pore structure. Fractal dimension shows negative correlations with porosity and permeability. In addition, fractal characteristics of different tight reservoirs were compared and analyzed

Exploring coupled images fusion based on joint tensor decomposition

Data fusion has always been a hot research topic in human-centric computing and extended with the development of artificial intelligence. Generally, the coupled data fusion algorithm usually utilizes the information from one data set to improve the estimation accuracy and explain related latent variables of other coupled datasets. This paper proposes several kinds of coupled images decomposition algorithms based on the coupled matrix and tensor factorization-optimization (CMTF-OPT) algorithm and the flexible coupling algorithm, which are termed the coupled images factorization-optimization(CIF-OPT) algorithm and the modified flexible coupling algorithm respectively. The theory and experiments show that the effect of the CIF-OPT algorithm is robust under the influence of different noises. Particularly, the CIF-OPT algorithm can accurately restore an image with missing some data elements. Moreover, the flexible coupling model has better estimation performance than a hard coupling. For high-dimensional images, this paper adopts the compressed data decomposition algorithm that not only works better than uncoupled ALS algorithm as the image noise level increases, but saves time and cost compared to the uncompressed algorithm

Case Report: Metagenomic next-generation sequencing assists in dynamic pathogen monitoring: powerful tool for progressing severe pneumonia

BackgroundSevere community-acquired pneumonia (sCAP) is life-threatening and characterized by intensive care unit (ICU) admission and high mortality. And they are vulnerable to hospital-acquired infection. In such a severe condition, metagenomic next-generation sequencing (mNGS) outperforms for short turnaround time and broad detection spectrum.Case presentationA 15-year-old male with severe influenza and methicillin-resistant Staphylococcus aureus (MRSA) pneumonia progressed rapidly, initially misdiagnosed as influenza co-infected with Aspergillus for misleading bronchoscopy manifestations. The turnaround time of mNGS is 13 h, which has the potential to expedite the clinical medication process. With the powerful support of mNGS and extracorporeal membrane oxygenation (ECMO), anti-infective therapy was adjusted accordingly, and vital signs gradually stabilized. After tortuous treatment and unremitting efforts, the patient recovered well.ConclusionsRapid mNGS applications, timely medication adjustments, strong ECMO support and active family compliance contribute to this miracle of life. False-negative or false-positive results are alarming, anti-infective medications should be adjusted after a comprehensive review of physical status and other indicators

Induction of polyploid tillered onion using colchicine and pendimethalin

The shoot tip explants of the tillered onion line Z-018 were used as experimental materials. The effects of colchicine and pendimethalin on the induction of polyploid tillered onion were studied in vitro with different concentrations and treatment time. Treatment with 250 μmol/L colchicine for 4 days caused a variant rate of 42.22% and a mortality rate of 36.67%, whereas treatment with 30 μmol/L pendimethalin for 6 days caused a variant rate of 41.11% and a mortality rate of 24.44%. Subsequent cytological identification showed that tetraploid plants were successfully induced by both mutagens. Compared with the diploid plants, the tetraploid plants exhibited slower growth, thicker leaves, stems and roots, larger stomatal apparatus and increased number of chloroplasts. In addition, the obtained tetraploid plants have thicker tubular leaves, decreased number of tillers, larger bulbs and increased yield of the products. This provides the basis for future research on tillered onion germplasm resources

Chemical Vapor Deposition of High-Quality Large-Sized MoS2 Crystals on Silicon Dioxide Substrates

Large???sized MoS2 crystals can be grown on SiO2/Si substrates via a two???stage chemical vapor deposition method. The maximum size of MoS2 crystals can be up to about 305 ??m. The growth method can be used to grow other transition metal dichalcogenide crystals and lateral heterojunctions. The electron mobility of the MoS2 crystals can reach ???30 cm2 V???1 s???1, which is comparable to those of exfoliated flakes.ope

Advances in molecular biological research of Angelica sinensis

Angelica sinensis (Oliv.) Diels belongs to the Apiaceae family. The root of A. sinensis, is used in traditional Chinese medicine for its antioxidant and immune regulation properties. The main active compounds in A. sinensis include organic acids, phthalides and coumarins, and their biosynthetic pathways are the focus of international attention. A. sinensis is prone to early flowering and bolting, which negatively impacts production for several reasons, including germplasm degradation and quality instability in artificial cultivation. The identification of top-geoherbalism of A. sinensis has also become the focus of recent research, as it would allow selection for breeds with excellent medicinal quality and remarkable curative effects. Advances in sequencing technology and bioinformatic methodologies have enabled extensive molecular and genetic studies in A. sinensis. In this review, we summarize the latest molecular research advances related to A. sinensis, including biosynthetic pathways and regulation of active compounds, and molecular underpinnings of early bolting and flowering and top-geoherbalism. We discuss limitations of the current research and propose prospective topics in need of further exploration

Modelling, optimisation and decision support using the grid

Modelling, Optimisation and Decision Support tools are vital in most areas of engineering. As part of the Distributed Aircraft Maintenance Environment (DAME) e-Science project, a virtual “work-bench” has been developed that can aid the engineer in solving engineering design problems. While the problem that motivated the development of these tools was taken from the aerospace industry, this sort of approach has broader application in areas such as automotive and marine engineering, as well as in the medical industry