Numerical simulation of buried pipeline subjected to blast seismic waves

Numerical studies were carried out to investigate the vibration of buried pipeline subjected to blast seismic waves. The numerical model contains a 5 tons of explosive, an X70 buried pipeline and different kinds of soils. The stress and the vibration velocity of the pipeline were acquired during the simulation. The influence of buried depth on vibration velocity was also revealed in the paper

Spatio-Temporal Adaptive Embedding Makes Vanilla Transformer SOTA for Traffic Forecasting

With the rapid development of the Intelligent Transportation System (ITS), accurate traffic forecasting has emerged as a critical challenge. The key bottleneck lies in capturing the intricate spatio-temporal traffic patterns. In recent years, numerous neural networks with complicated architectures have been proposed to address this issue. However, the advancements in network architectures have encountered diminishing performance gains. In this study, we present a novel component called spatio-temporal adaptive embedding that can yield outstanding results with vanilla transformers. Our proposed Spatio-Temporal Adaptive Embedding transformer (STAEformer) achieves state-of-the-art performance on five real-world traffic forecasting datasets. Further experiments demonstrate that spatio-temporal adaptive embedding plays a crucial role in traffic forecasting by effectively capturing intrinsic spatio-temporal relations and chronological information in traffic time series.Comment: Accepted as CIKM2023 Short Pape

MegaCRN: Meta-Graph Convolutional Recurrent Network for Spatio-Temporal Modeling

Spatio-temporal modeling as a canonical task of multivariate time series forecasting has been a significant research topic in AI community. To address the underlying heterogeneity and non-stationarity implied in the graph streams, in this study, we propose Spatio-Temporal Meta-Graph Learning as a novel Graph Structure Learning mechanism on spatio-temporal data. Specifically, we implement this idea into Meta-Graph Convolutional Recurrent Network (MegaCRN) by plugging the Meta-Graph Learner powered by a Meta-Node Bank into GCRN encoder-decoder. We conduct a comprehensive evaluation on two benchmark datasets (METR-LA and PEMS-BAY) and a large-scale spatio-temporal dataset that contains a variaty of non-stationary phenomena. Our model outperformed the state-of-the-arts to a large degree on all three datasets (over 27% MAE and 34% RMSE). Besides, through a series of qualitative evaluations, we demonstrate that our model can explicitly disentangle locations and time slots with different patterns and be robustly adaptive to different anomalous situations. Codes and datasets are available at https://github.com/deepkashiwa20/MegaCRN.Comment: Preprint submitted to Artificial Intelligence. arXiv admin note: substantial text overlap with arXiv:2211.1470

Plasmid parB contributes to uropathogenic Escherichia coli colonization in vivo by acting on biofilm formation and global gene regulation

The endogenous plasmid pUTI89 harbored by the uropathogenic Escherichia coli (UPEC) strain UTI89 plays an important role in the acute stage of infection. The partitioning gene parB is important for stable inheritance of pUTI89. However, the function of partitioning genes located on the plasmid in pathogenesis of UPEC still needs to be further investigated. In the present study, we observed that disruption of the parB gene leads to a deficiency in biofilm formation in vitro. Moreover, in a mixed infection with the wild type strain and the parB mutant, in an ascending UTI mouse model, the mutant displayed a lower bacterial burden in the bladder and kidneys, not only at the acute infection stage but also extending to 72 hours post infection. However, in the single infection test, the reduced colonization ability of the parB mutant was only observed at six hpi in the bladder, but not in the kidneys. The colonization capacity in vivo of the parB-complemented strain was recovered. qRT-PCR assay suggested that ParB could be a global regulator, influencing the expression of genes located on both the endogenous plasmid and chromosome, while the gene parA or the operon parAB could not. Our study demonstrates that parB contributes to the virulence of UPEC by influencing biofilm formation and proposes that the parB gene of the endogenous plasmid could regulate gene expression globally

Case Report: Sequential Chemotherapy and Immunotherapy Produce Sustained Response in Osteosarcoma With High Tumor Mutational Burden

BackgroundImmunotherapy has provided an effective method for the treatment of many cancers. However, its efficacy in osteosarcoma is not satisfactory so far.Case PresentationHere, we presented a case of osteosarcoma treated with sequential chemotherapy and immunotherapy and showed promising therapeutic potential. The 29-year-old female patient presented 9th rib osteosarcoma with suspected right lung lower lobe metastasis. Surgery was performed to remove the primary lesion, and a series of chemotherapies were given afterward in consideration of the response and tolerance. The right lung lower lobe metastasis was under control first but progressed (PD) 9 months after the initiation of therapy. The lesion was surgically removed and subsequent chemotherapy was implemented. The patient had good tolerance with chemotherapy and maintained well for approximately 11 months before the discovery of 11th rib and right lung upper lobe metastases. Surgery was then performed on both lesions and achieved complete response. Post-surgical brief chemotherapy and subsequent long-term immunotherapy (pembrolizumab) maintained continuous remission for 33 months. The patient survived for 60 months with well-controlled disease from the time of confirmed diagnosis. Genetic alterations of all primary and metastatic lesions were investigated by whole-exome sequencing (WES). Substantial similarity in mutational landscape between the primary lesion and 11th rib metastasis and between the two lung metastases were revealed, while substantial heterogeneity was found between the rib lesions and lung metastases. The tumor mutational burden (TMB) for the 9th rib primary lesion, the metastatic 11th rib lesion, and the metastatic right upper and lower lobe nodule tissues was 8.02, 2.38, 4.61, and 0.14 mutations/Mb, respectively. The primary lesion exhibited the most diverse copy number variation (CNV) changes among all lesions. Furthermore, pathway enrichment analysis also suggested significant heterogeneity among the lesions.ConclusionsSurgery with sequential chemotherapy and maintenance immunotherapy was shown to have good response for the first time on osteosarcoma patient who had high TMB tumor lesions and good tolerance for chemotherapy and immunotherapy

Sensors for Robotics 2015

Robot is currently one of the exciting and fast developing technologies changing the life of human being. It has been widely applied in lots of areas such as industry, agriculture, medicine, transportation, social service, military, space exploration, and undersea exploiting. Increasing attention by robot researchers has been paid to the robot sensor, as a key component of the robot. During the last decade, much effort has been done to develop robot sensors for robot perception, robot control, autonomous robot, human-robot interaction, and so forth. In spite of the large and increasing interest and promising applications, robot sensor design is a significant challenging, which is involved in not only sensor materials, structure design, manufacturing process, and calibration technique, but also signal processing, data fusion, and pattern recognition. For instance, remarkable examples of tactile sensors and systems have been proposed; however, their ability to address specific applications and their extension to other fields such as medical instrumentation, prosthetic devices, and biomechanics test is questionable. This special issue aims at exhibiting the latest research achievements, ideas, and advances in robot sensors

Sensors for robotics

Robots are currently widely applied in lots of areas such as industry, agriculture, medicine, transportation, social service, military, space exploration, and undersea exploiting. The robot sensor, as a key component of the robot, has been paid increasing attention by robot researchers. Furthermore, sensor based human-robot interaction is currently the frontier of robot research. Robot sensing technology has been an evolving research field involving a strong interdisciplinary effort from researchers in different fields, namely, electronics, mechanics, material science, measurement and control, signal processing, bioengineering, and so forth. During the last decade, much effort has been done to develop robot sensors for robot control, robot perception, robot navigation, human-robot interaction, teleoperational robot, and so forth. In spite of the large and increasing interest and promising applications, robot sensor design is a significant challenge, which is involved in not only chemical sensors, biosensors, optical sensors, and physical sensors but also signal processing, data fusion, and pattern recognition. For instance, remarkable examples of tactile sensors and systems have been proposed; however, their capability to address specific applications and their extension to other fields such as medical instrumentation, prosthetic devices, and augmented reality are questionable