With the development of digital and intelligent technologies, the intelligence level in the field of railway engineering construction is also constantly improving. Establishing a unified high-speed railway intelligent...With the development of digital and intelligent technologies, the intelligence level in the field of railway engineering construction is also constantly improving. Establishing a unified high-speed railway intelligent building standard system has become a key factor to further improve the intelligent building level. By focusing on the field of intelligent building under the intelligent high-speed railway, the paper analyzes the formulation of engineering construction standards at home and abroad as well as the application and standard formulation status of the intelligent building technology, discusses the requirements for the preparation of high-speed railway intelligent building standard system, carries out structural analysis on the high-speed railway intelligent building standard system, proposes the architecture of high-speed railway intelligent building standard system and further clarifies the standard system framework and the formulation content of each part, which provides guidance for the formulation and revision of railway intelligent building standards.展开更多
The existing Low-Earth-Orbit(LEO)positioning performance cannot meet the requirements of Unmanned Aerial Vehicle(UAV)clusters for high-precision real-time positioning in the Global Navigation Satellite System(GNSS)den...The existing Low-Earth-Orbit(LEO)positioning performance cannot meet the requirements of Unmanned Aerial Vehicle(UAV)clusters for high-precision real-time positioning in the Global Navigation Satellite System(GNSS)denial conditions.Therefore,this paper proposes a UAV Clusters Information Geometry Fusion Positioning(UC-IGFP)method using pseudoranges from the LEO satellites.A novel graph model for linking and computing between the UAV clusters and LEO satellites was established.By utilizing probability to describe the positional states of UAVs and sensor errors,the distributed multivariate Probability Fusion Cooperative Positioning(PF-CP)algorithm is proposed to achieve high-precision cooperative positioning and integration of the cluster.Criteria to select the centroid of the cluster were set.A new Kalman filter algorithm that is suitable for UAV clusters was designed based on the global benchmark and Riemann information geometry theory,which overcomes the discontinuity problem caused by the change of cluster centroids.Finally,the UC-IGFP method achieves the LEO continuous highprecision positioning of UAV clusters.The proposed method effectively addresses the positioning challenges caused by the strong direction of signal beams from LEO satellites and the insufficient constraint quantity of information sources at the edge nodes of the cluster.It significantly improves the accuracy and reliability of LEO-UAV cluster positioning.The results of comprehensive simulation experiments show that the proposed method has a 30.5%improvement in performance over the mainstream positioning methods,with a positioning error of 14.267 m.展开更多
A modified mixed/hybrid finite element method, which is no longer required to satisfy the Babuska-Brezzi condition, is referred to as a stabilized method Based on the duality of vanational principles in solid mechanic...A modified mixed/hybrid finite element method, which is no longer required to satisfy the Babuska-Brezzi condition, is referred to as a stabilized method Based on the duality of vanational principles in solid mechanics, a new type of stabilized method, called the combinatorially stabilized mixed/hybrid finite element method, is presented by weight-averaging both the primal and the dual "saddle-point" schemes. Through a general analysis of stability and convergence under an abstract framework, it is shown that for the methods only an inf-sup inequality much weaker than Babuska-Brezzi condition needs to be satisfied. As a concrete application, it is concluded that the combinatorially stabilized Raviart and Thomas mixed methods permit the C -elements to replace the H(div; Ω)-elements.展开更多
Hepatocellular carcinoma (HCC) is common and one of the most aggressive of all human cancers. Recent studies have indicated that miRNAs, a class of small noncoding RNAs that regulate gene expression post-transcription...Hepatocellular carcinoma (HCC) is common and one of the most aggressive of all human cancers. Recent studies have indicated that miRNAs, a class of small noncoding RNAs that regulate gene expression post-transcriptionally, directly contribute to HCC by targeting many critical regulatory genes. Several miRNAs are involved in hepatitis B or hepatitis C virus replication and virus-induced changes, whereas others participate in multiple intracellular signaling pathways that modulate apoptosis, cell cycle checkpoints, and growth-factor-stimulated responses. When disturbed, these pathways appear to result in malignant transformation and ultimately HCC development. Recently, miRNAs circulating in the blood have acted as possible early diagnostic markers for HCC. These miRNA also could serve as indicators with respect to drug efficacy and be prognostic in HCC patients. Such biomarkers would assist stratification of HCC patients and help direct personalized therapy. Here, we summarize recent advances regarding the role of miRNAs in HCC development and progression. Our expectation is that these and ongoing studies will contribute to the understanding of the multiple roles of these small noncoding RNAs in liver tumorigenesis.展开更多
The superresolution(SR)method based on generative adversarial networks(GANs)cannot adequately capture enough diversity from training data,resulting in misalignment between input low resolution(LR)images and output hig...The superresolution(SR)method based on generative adversarial networks(GANs)cannot adequately capture enough diversity from training data,resulting in misalignment between input low resolution(LR)images and output high resolution(HR)images.GAN training has difficulty converging.Based on this,an advanced GAN-based image SR reconstructionmethod is presented.First,the dense connection residual block and attention mechanism are integrated into the GAN generator to improve high-frequency feature extraction.Meanwhile,an added discriminator is added into the GAN discriminant network,which forms a dual discriminator to ensure that the process of training is stable.Second,the more robust Charbonnier loss is used instead of the mean square error(MSE)loss to compare similarities between the obtained image and actual image,and the total variation(TV)loss is employed to smooth the training results.Finally,the experimental results indicate that global structures can be better reconstructed using the method of this paper and texture details of images compared with other SOTA methods.The peak signal-to-noise ratio(PSNR)values by the method of this paper are improved by an average of 2.24 dB,and the structural similarity index measure(SSIM)values are improved by an average of 0.07.展开更多
文摘With the development of digital and intelligent technologies, the intelligence level in the field of railway engineering construction is also constantly improving. Establishing a unified high-speed railway intelligent building standard system has become a key factor to further improve the intelligent building level. By focusing on the field of intelligent building under the intelligent high-speed railway, the paper analyzes the formulation of engineering construction standards at home and abroad as well as the application and standard formulation status of the intelligent building technology, discusses the requirements for the preparation of high-speed railway intelligent building standard system, carries out structural analysis on the high-speed railway intelligent building standard system, proposes the architecture of high-speed railway intelligent building standard system and further clarifies the standard system framework and the formulation content of each part, which provides guidance for the formulation and revision of railway intelligent building standards.
基金supported in part by the National Natural Science Foundation of China(Nos.62171375,62271397,62001392,62101458,62173276,61803310 and 61801394)the Shenzhen Science and Technology Innovation ProgramChina(No.JCYJ20220530161615033)。
文摘The existing Low-Earth-Orbit(LEO)positioning performance cannot meet the requirements of Unmanned Aerial Vehicle(UAV)clusters for high-precision real-time positioning in the Global Navigation Satellite System(GNSS)denial conditions.Therefore,this paper proposes a UAV Clusters Information Geometry Fusion Positioning(UC-IGFP)method using pseudoranges from the LEO satellites.A novel graph model for linking and computing between the UAV clusters and LEO satellites was established.By utilizing probability to describe the positional states of UAVs and sensor errors,the distributed multivariate Probability Fusion Cooperative Positioning(PF-CP)algorithm is proposed to achieve high-precision cooperative positioning and integration of the cluster.Criteria to select the centroid of the cluster were set.A new Kalman filter algorithm that is suitable for UAV clusters was designed based on the global benchmark and Riemann information geometry theory,which overcomes the discontinuity problem caused by the change of cluster centroids.Finally,the UC-IGFP method achieves the LEO continuous highprecision positioning of UAV clusters.The proposed method effectively addresses the positioning challenges caused by the strong direction of signal beams from LEO satellites and the insufficient constraint quantity of information sources at the edge nodes of the cluster.It significantly improves the accuracy and reliability of LEO-UAV cluster positioning.The results of comprehensive simulation experiments show that the proposed method has a 30.5%improvement in performance over the mainstream positioning methods,with a positioning error of 14.267 m.
文摘A modified mixed/hybrid finite element method, which is no longer required to satisfy the Babuska-Brezzi condition, is referred to as a stabilized method Based on the duality of vanational principles in solid mechanics, a new type of stabilized method, called the combinatorially stabilized mixed/hybrid finite element method, is presented by weight-averaging both the primal and the dual "saddle-point" schemes. Through a general analysis of stability and convergence under an abstract framework, it is shown that for the methods only an inf-sup inequality much weaker than Babuska-Brezzi condition needs to be satisfied. As a concrete application, it is concluded that the combinatorially stabilized Raviart and Thomas mixed methods permit the C -elements to replace the H(div; Ω)-elements.
基金supported by the National Natural Science Foundation of China(Grant Nos.30970623 and 31071137)International Science and Technology Cooperation Projects(Grant Nos.2010DFA31840 and 2010DFB33720)+1 种基金Program for New Century Excellent Talents in University(Grant No.NCET-11-0288)Beijing Natural Science Foundation(Grant No.5112030)
文摘Hepatocellular carcinoma (HCC) is common and one of the most aggressive of all human cancers. Recent studies have indicated that miRNAs, a class of small noncoding RNAs that regulate gene expression post-transcriptionally, directly contribute to HCC by targeting many critical regulatory genes. Several miRNAs are involved in hepatitis B or hepatitis C virus replication and virus-induced changes, whereas others participate in multiple intracellular signaling pathways that modulate apoptosis, cell cycle checkpoints, and growth-factor-stimulated responses. When disturbed, these pathways appear to result in malignant transformation and ultimately HCC development. Recently, miRNAs circulating in the blood have acted as possible early diagnostic markers for HCC. These miRNA also could serve as indicators with respect to drug efficacy and be prognostic in HCC patients. Such biomarkers would assist stratification of HCC patients and help direct personalized therapy. Here, we summarize recent advances regarding the role of miRNAs in HCC development and progression. Our expectation is that these and ongoing studies will contribute to the understanding of the multiple roles of these small noncoding RNAs in liver tumorigenesis.
基金supported in part by the Basic Scientific Research Project of Liaoning Provincial Department of Education under Grant No.LJKQZ2021152in part by the National Science Foundation of China (NSFC)under Grant No.61602226in part by the PhD Startup Foundation of Liaoning Technical University of China under Grant No.18-1021.
文摘The superresolution(SR)method based on generative adversarial networks(GANs)cannot adequately capture enough diversity from training data,resulting in misalignment between input low resolution(LR)images and output high resolution(HR)images.GAN training has difficulty converging.Based on this,an advanced GAN-based image SR reconstructionmethod is presented.First,the dense connection residual block and attention mechanism are integrated into the GAN generator to improve high-frequency feature extraction.Meanwhile,an added discriminator is added into the GAN discriminant network,which forms a dual discriminator to ensure that the process of training is stable.Second,the more robust Charbonnier loss is used instead of the mean square error(MSE)loss to compare similarities between the obtained image and actual image,and the total variation(TV)loss is employed to smooth the training results.Finally,the experimental results indicate that global structures can be better reconstructed using the method of this paper and texture details of images compared with other SOTA methods.The peak signal-to-noise ratio(PSNR)values by the method of this paper are improved by an average of 2.24 dB,and the structural similarity index measure(SSIM)values are improved by an average of 0.07.
