Chun Sha^1,*, Chaohui Yue², Wenchen Wang³

Structural Durability & Health Monitoring, Vol.17, No.5, pp. 369-381, 2023, DOI:10.32604/sdhm.2023.027948

Abstract Convolution neural networks in deep learning can solve the problem of damage identification based on vibration acceleration. By combining multiple 1D DenseNet submodels, a new ensemble learning method is proposed to improve identification accuracy. 1D DenseNet is built using standard 1D CNN and DenseNet basic blocks, and the acceleration data obtained from multiple sampling points is brought into the 1D DenseNet training to generate submodels after offset sampling. When using submodels for damage identification, the voting method ideas in ensemble learning are used to vote on the results of each submodel, and then vote centrally. Finally, the cantilever damage problem… More >

Zhuyou Hu¹, Ping Lin^2,3, He Guo^2,3, Yumei Zhang^2,3, Zhihai Xiang^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.1, pp. 1-2, 2023, DOI:10.32604/icces.2023.09475

Abstract In recent years, the vehicle scanning method for bridge inspection has drawn much attention by researchers because of its simple operation and high efficiency [1]. Besides the natural frequency, modal modes and other information of bridges, damage can also be detected in this way [2]. For example, we proposed the passive tap-scan damage detection method [3], which scans the bridge with the tapping force generated by a toothed wheel, mimicking the hunting behavior of woodpeckers. In this talk, we will discuss two critical aspects related to the mechanism of this method. One is the quantitative relationship between the vehicle acceleration… More >

Nizar Faisal Alkayem¹, Maosen Cao^2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.4, pp. 1-1, 2023, DOI:10.32604/icces.2023.09367

Abstract Structural damage identification is a key engineering technique that attempts to ensure structural reliability. In this regard, one of the major intelligent approaches is the inverse analysis of structural damage using metaheuristics. By considering the recent achievements, an efficient hybrid objective function that combines the modal kinetic energy and modal strain energy is developed. The objective function aims to extract maximum modal information from the structure and overcome noisy conditions. Moreover, the original methods are usually vulnerable to the associated high multimodality and uncertainty of the inverse problem. Therefore, the particle swarm algorithm (PSO) mechanism is combined with another newly… More >

Mingliang Jiang¹, Zhujiang Wang^2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.08949

Abstract This work deals with the parameter identification of invariant-based hyperelastic materials using the virtual fields method (VFM). Combined with the full-field deformation data obtained from the digital image correlation (DIC), VFM has been utilized to characterize the mechanical properties of hyperelastic materials [1]. In the conventional formulation of the VFM, the calculation of the internal virtual work (IVW) needs to obtain the stress and conjugate virtual strains, which requires a lot of calculation and derivation work. In this paper, the VFM is reformulated by calculating the IVW through the variation of elastic energy, which is more concise and easier to… More >

Zhuyou Hu¹, Ping Lin^2,3, He Guo^2,3, Yumei Zhang^2,3, Zhihai Xiang^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.1, pp. 1-2, 2023, DOI:10.32604/icces.2023.09475

Abstract In recent years, the vehicle scanning method for bridge inspection has drawn much attention by researchers because of its simple operation and high efficiency [1]. Besides the natural frequency, modal modes and other information of bridges, damage can also be detected in this way [2]. For example, we proposed the passive tap-scan damage detection method [3], which scans the bridge with the tapping force generated by a toothed wheel, mimicking the hunting behavior of woodpeckers. In this talk, we will discuss two critical aspects related to the mechanism of this method. One is the quantitative relationship between the vehicle acceleration… More >

Taotao Yuan¹, Haitian Yang¹, Yiqian He^1,2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.4, pp. 1-1, 2023, DOI:10.32604/icces.2023.09275

Abstract Computational modeling can provide insight into understanding the damage mechanisms of soft biological tissues, and identification of constitutive parameters is key issues in the computational modeling. On the other hand, although it is thought that computational model should be non-local for soft tissues based on the existence of intrinsic length scales, there is very few work for the identification of the parameters of nonlocal damage models of soft tissues. Firstly, we use the gradient-enhanced damage model presented in our previous publication showing advantages in considering the internal length scales and in satisfying mesh independence for simulating damage [1]. Secondly, the… More >

WAYEZ NAQVI, ANANYA SINGH, PREKSHI GARG, PRACHI SRIVASTAVA^*

BIOCELL, Vol.47, No.8, pp. 1675-1687, 2023, DOI:10.32604/biocell.2023.029624

Abstract Biological entities are involved in complicated and complex connections; hence, discovering biological information using network biology ideas is critical. In the past few years, network biology has emerged as an integrative and systems-level approach for understanding and interpreting these complex interactions. Biological network analysis is one method for reducing enormous data sets to clinically useful knowledge for disease diagnosis, prognosis, and treatment. The network of biological entities can help us predict drug targets for several diseases. The drug targets identified through the systems biology approach help in targeting the essential biological pathways that contribute to the progression and development of… More >

Zhixian Qi^1,2,*, Shuohe Wang^1,2, Qiang Xue^1,2, Haiting Mi³, Jian Wang^1,2

Energy Engineering, Vol.120, No.9, pp. 2059-2077, 2023, DOI:10.32604/ee.2023.028595

Abstract A current identification method based on optimized variational mode decomposition (VMD) and sample entropy (SampEn) is proposed in order to solve the problem that the main protection of the urban rail transit DC feeder cannot distinguish between train charging current and remote short circuit current. This method uses the principle of energy difference to optimize the optimal mode decomposition number k of VMD; the optimal VMD for DC feeder current is decomposed into the intrinsic modal function (IMF) of different frequency bands. The sample entropy algorithm is used to perform feature extraction of each IMF, and then the eigenvalues of… More >

Long Zhao, Xudong Lu, Xinbo Huang^*, Hao Yang, Guoze Feng

Structural Durability & Health Monitoring, Vol.17, No.4, pp. 283-297, 2023, DOI:10.32604/sdhm.2023.025977

Abstract In the harsh environment, the structural health of the anti-vibration hammer, which suffers from the coupled effects of corrosion and fatigue damage, is significantly reduced. As part of the conductor structure, the anti-vibration hammer is rigidly attached to the conductor, effectively suppressing conductor vibration. The conductor’s breeze vibration law and natural modal frequency are altered damage to the anti-vibration hammer structure. Through built a vibration experiment platform to simulate multiple faults such as anti-vibration hammer head drop off and position slippage, which to obtained the vibration acceleration signal of the conductor. The acceleration vibration signal is processed and analyzed in… More >

ZIYU LIU^1,2, AKIKO OKANO^3,4, EMIKO SANADA^1,3,4, YUSHI FUTAMURA^3,4, TOSHIHIKO NOGAWA^3,5, KOSUKE ISHIKAWA⁶, KENTARO SEMBA^7,8, JIANG LI⁹, XIAOMENG LI¹⁰, HIROYUKI OSADA^3,4,11,*, NOBUMOTO WATANABE^1,2,4,*

Oncology Research, Vol.31, No.5, pp. 655-666, 2023, DOI:10.32604/or.2023.030248

Abstract

Myc belongs to a family of proto-oncogenes that encode transcription factors. The overexpression of c-Myc causes many types of cancers. Recently, we established a system for screening c-Myc inhibitors and identified antimycin A by screening the RIKEN NPDepo chemical library. The specific mechanism of promoting tumor cell metastasis by high c-Myc expression remains to be explained. In this study, we screened approximately 5,600 microbial extracts using this system and identified a broth prepared from Streptomyces sp. RK19-A0402 strongly inhibits c-Myc transcriptional activity. After purification of the hit broth, we identified compounds closely related to the aglycone of cytovaricin and had… More > Graphic Abstract