Search

Microbial-induced calcium carbonate precipitation (MICP) is an emerging in situ grouting technology for sand ground improvement, slope stability, and subgrade reinforcement, featuring rapid implementation and low energy consumption. The precipitated calcium carbonate crystals can rapidly fill and cement sand particles so as to form a new soil structure that effectively reduces liquefaction sensitivity and dynamic damage. The centrifuge shake table test is an effective method for simulating liquefaction of sandy soil layers under shear wave excitation. Many studies have been conducted on this topic in recent years. However, the study on dynamic response, especially the liquefaction resistance of MICP-cemented sands by centrifuge shake table tests, is rare. In order to investigate the cementation effect of microbial treatment, centrifuge shake table tests were performed on two models, i.e., untreated and MICP cemented sand model. The test results indicated that, compared with untreated sand model, the liquefaction resistance of the MICP model was significantly improved in terms of acceleration response, shear stiffness, stress–strain relationship, and ground surface settlement. This study contributes to a better understanding of the mechanical law in the liquefaction process and enriches the engineering application of microbial grouting treatment of sand foundation prone to liquefaction. [ABSTRACT FROM AUTHOR]

The proliferation of shared electric scooters (E-scooters) has brought convenience to urban transportation but has also introduced challenges such as disorderly parking and an imbalance between supply and demand. Given the current inconsistent quantity and spatial distribution of shared E-scooters, coupled with inadequate research on deployment stations selection, we propose a novel maximal covering location problem (MCLP) based on distance tolerance. The model aims to maximize the coverage of user demand while minimizing the sum of distances from users to deployment stations. A deep reinforcement learning (DRL) was devised to address this optimization model. An experiment was conducted focusing on areas with high concentrations of shared E-scooter trips in Chicago. The solutions of location selection were obtained by DRL, the Gurobi solver, and the genetic algorithm (GA). The experimental results demonstrated the effectiveness of the proposed model in optimizing the layout of shared E-scooter deployment stations. This study provides valuable insights into facility location selection for urban shared transportation tools, and showcases the efficiency of DRL in addressing facility location problems (FLPs). [ABSTRACT FROM AUTHOR]

Emerging pollutants, nitro-polycyclic aromatic hydrocarbons (NPAHs), and halogenated PAHs (HPAHs), in atmospheric fine particulate matter (PM2.5) in four cities (Taiyuan, Yangquan, Changzhi, and Jincheng) during the non-heating and heating periods of Shanxi province, China, in 2020, were monitored to investigate their pollution characteristics and potential health risk. The exposure levels of PM2.5-bound ∑16PAHs, ∑13NPAHs, ∑6ClPAHs, and ∑7BrPAHs during the heating period ascended compared to the non-heating period. 2N-Nap, 1N-Nap, 2N-Fle, and 9N-Phe were primary monomers in NPAHs with higher concentrations, while higher levels of 2Br-Fle, 2Cl-Ant, and 9Cl-Phe were in HPAHs. Toxic equivalency quotients (TEQs), incremental lifetime cancer risk (ILCR), and loss of life expectancy (LLE) results suggested that PM2.5-bound PAHs during the heating periods posed a potential carcinogenic risk. The ILCR and loss of life expectancy (LLE) values of PM2.5-bound PAHs showed a similar decreasing trend with an order: adults (age 30–70) > toddler >adults (age 18–30) > teenagers > children >baby. The TEQ and ILCR values of ∑13NPAHs and ∑13HPAHs in PM2.5 were far below the safety threshold, indicating no obvious cancer risks. The pollution of PM2.5-bound PAHs, NPAHs, and HPAHs and potential health risks in Yangquan and Changzhi was more serious compared to Taiyuan and Jincheng. [ABSTRACT FROM AUTHOR]

In the automated modeling generated by oblique photography, various terrains cannot be physically distinguished individually within the triangulated irregular network (TIN). To utilize the data representing individual features, such as a single building, a process of building monomer construction is required to identify and extract these distinct parts. This approach aids subsequent analyses by focusing on specific entities, mitigating interference from complex scenes. A deep convolutional neural network is constructed, combining U-Net and ResNeXt architectures. The network takes as input both digital orthophoto map (DOM) and oblique photography data, effectively extracting the polygonal footprints of buildings. Extraction accuracy among different algorithms is compared, with results indicating that the ResNeXt-based network achieves the highest intersection over union (IOU) for building segmentation, reaching 0.8255. The proposed "dynamic virtual monomer" technique binds the extracted vector footprints dynamically to the original oblique photography surface through rendering. This enables the selective representation and querying of individual buildings. Empirical evidence demonstrates the effectiveness of this technique in interactive queries and spatial analysis. The high level of automation and excellent accuracy of this method can further advance the application of oblique photography data in 3D urban modeling and geographic information system (GIS) analysis. [ABSTRACT FROM AUTHOR]

A geographic information system (GIS) is a technical system which is supported by computer software and hardware systems. It focuses on the geographical information related to the whole or part of the earth's surface. It is used for collecting, storing, managing, calculating, analyzing, displaying, and describing geographical information. It has inherent advantages in processing geographic data and plays an indispensable role in the sustainable detection of natural resources, natural disaster risk management, urban sustainable development planning, etc. With the continuous development of technology, the integration of GIS with emerging technologies such as big data, cloud services, and artificial intelligence creates new geographic information systems and entirely new development directions. The GIS architecture is of great value for the efficient execution of GIS systems. In this process, as the organizational form of GIS systems, the GIS architecture is also constantly evolving with the intersection and integration of GIS and other technologies. This research reviews a large amount of literature on component technologies, 3D technologies, cloud computing, big data, artificial intelligence, and so on, at home and abroad and analyzes and elaborates on the current development status and trends of GIS software architecture. It discusses in detail the characteristics and future development directions of different GIS software architectures in different periods and makes delicate descriptions of their hierarchical features. This study aims to summarize the advantages and disadvantages of architectures in different stages, the interactivity from the user's perspective. On this basis, it studies the development trends of GIS integrated with big data and artificial intelligence, summarizes the laws and experience of the evolution of its system architecture, and analyzes the technological drivers of each evolution and their impact on GIS applications. Reviewing the evolution history of GIS frameworks is expected to provide guiding references for more efficient GIS system architecture research in the future. [ABSTRACT FROM AUTHOR]

Fine particulate matter (PM2.5) is a common pollutant, and its health risk has attracted much attention. Studies have shown that PM2.5 exposure is associated with liver disease. The composition of PM2.5 is complex, and its hepatotoxic effects and lipid metabolism process are not well understood. In this study, we detected the concentrations of PM2.5 and its components (metals and polycyclic aromatic hydrocarbon (PAHs)) in the winter in Taiyuan, Shanxi Province, China, from 2017 to 2020 and then assessed the health risks. We also investigated the effects of different components (whole particles (WP), water-soluble particles (WSP), organic particles (OP)) of PM2.5 on the cytotoxicity and lipid metabolism in human liver cell line (HepG2) after 24 h of treatment. The changes in cytotoxicity indexes (LDH, IL-6, reactive oxygen species (ROS)) and lipids (triglyceride (TG), free fatty acid (FFA)) were measured after 24 h. The mRNA expression of lipid metabolism-related factors (SREBP1, CD36, MTTP) was determined by real-time quantitative RT-qPCR. Finally, the correlation between metals and PAHs with higher PM2.5 content in 4 years and biomarkers was analyzed. The results showed that: (1) The PM2.5 pollution was severe in Taiyuan during winter in 2017 and the subsequent four years. The calculation results of the metal enrichment factor (EF) value and PAHs characteristic ratio of PM2.5 showed that PM2.5 pollution sources differed in different years. (2) Exposure to metals and PAHs in PM2.5 did not cause a non-carcinogenic risk. Metals had no cancer risk, while PAHs inhaled in PM2.5 in 2017 and 2018 had a potential cancer risk. The atmospheric PM2.5 pollution in Taiyuan has had a downward trend, but the PAHs in the PM2.5 of 2017–18, when the pollution is relatively serious, have a potential carcinogenic risk. (3) WP, OP and WSP inhibited cell survival rate from 2017 to 2020, and OP had higher cytotoxicity at the same concentration. (4) WP, OP and WSP increased the levels of LDH, IL-6, TNF-α, ROS, MDA, TG and FFA, and inhibited SOD activity in a dose-effect relationship. The organic components in PM2.5 are more toxic to HepG2 cells and affect the expression of lipid metabolism-related factors at the transcriptional level. (5) The mRNA expressions of factors related to lipid synthesis, uptake, oxidation and output were up-regulated after treatment with PM2.5 and its components, suggesting a lipid metabolism disorder. (6) The biomarkers were associated with certain metals (Zn, Pb, Cu and Cr) and PAHs in PM2.5. These suggested that PM2.5- and PM2.5-bound organic matter caused HepG2 cytotoxicity and affected lipid metabolism. [ABSTRACT FROM AUTHOR]

MicroRNAs (miRNAs) are important post-transcriptional regulators of gene expression in many physiological and pathological processes. Previous studies have reported the role of miR-139-3p in cancer. However, its specific roles and functions in the heart undergoing hypertrophy have yet to be fully elucidated. In the present study, a significant upregulation of miR-139-3p expression was demonstrated in the left ventricular myocardium of two-kidney one-clip (2K1C) hypertensive rats using microarray and quantitative real-time PCR (qRT-PCR). Based on computational analysis, we observed that miR-139-3p can control the expression of mitogen-activated protein kinase 1 (MAPK1) as a target gene, which is essential for the induction of cardiac hypertrophy and cardiomyocyte apoptosis. This study provides first information that the highly expressed miR-139-3p might be closely involved in MAPK1-mediated cardiac hypertrophy and cardiomyocyte apoptotic processes in 2K1C rat.