Håvard Bjerkeseth Solvin^1,2,5,*, Simone Goa Diab^1,4, Ole Jakob Elle^2,3, Henrik Holmstrøm^1,4, Henrik Brun^2,4,*

Congenital Heart Disease, Vol.18, No.5, pp. 551-559, 2023, DOI:10.32604/chd.2023.031537

Abstract Background: The management of suspected critical congenital heart defects (CCHD) relies on timely echocardiographic diagnosis. The availability of experienced echocardiographers is limited or even non-existent in many hospitals with obstetric units. This study evaluates remote-mentored echocardiography performed by physicians without experience in imaging of congenital heart defects (CHD). Methods: The setup included a pediatric cardiologist in a separate room, guiding a physician without experience in echocardiographic imaging of CHD in the examination of a symptomatic newborn. This remote-mentoring pair was blinded to the diagnosis of the newborn and presented with a simplified patient history. The echocardiographic images were streamed to… More > Graphic Abstract

Yanli Liu^1,2, Fengzhen Han², Jian Zhuang⁴, Yanqiu Ou⁴, Yanji Qu⁵, Yanyan Lin², Weina Zhang², Haiping Wang^3,*, Liping Huang^1,*

Congenital Heart Disease, Vol.18, No.5, pp. 561-570, 2023, DOI:10.32604/chd.2023.030511

Abstract Background: Research on fetal congenital heart defect (CHD) mostly focuses on etiology and mechanisms. However, studies on maternal complications or pathophysiology are limited. Our objective was to determine whether vascular dysfunction exists in pregnant women carrying a fetus with congenital heart defects. Methods: We conducted a case-control study. 27 cases of pregnant women carrying a fetus with major CHD admitted to our hospital for delivery between April 2021 and August 2022 were selected. Every case was matched with about 2 pregnant complication-free controls without fetal abnormalities. The proangiogenic and anti-angiogenic factors and pregnancy outcomes were compared. Results: The proangiogenic factors… More > Graphic Abstract

Yongzhi Min^1,2,*, Jiafeng Li³, Yaxing Li¹

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 941-962, 2023, DOI:10.32604/cmc.2023.041182

Abstract To guarantee the safety of railway operations, the swift detection of rail surface defects becomes imperative. Traditional methods of manual inspection and conventional nondestructive testing prove inefficient, especially when scaling to extensive railway networks. Moreover, the unpredictable and intricate nature of defect edge shapes further complicates detection efforts. Addressing these challenges, this paper introduces an enhanced Unified Perceptual Parsing for Scene Understanding Network (UPerNet) tailored for rail surface defect detection. Notably, the Swin Transformer Tiny version (Swin-T) network, underpinned by the Transformer architecture, is employed for adept feature extraction. This approach capitalizes on the global information present in the image… More >

Umut Hanoglu^1,2,*, Božidar Šarler^1,2

The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.09610

Abstract In this research, a rolling simulation system based on a novel meshless solution procedure is upgraded considering casting defects in the material model. The improved model can predict the final stage of the defects after multi-pass rolling. The casted steel billet that enters the rolling mill arrives with casting defects. Those defects may be porosity due to the shrinkage and cavity or micro-cracks near the surface due to hot tearing. In this work, porosity is considered the main defect source since it can easily be determined experimentally. The damage theory develops a damaged stiffness matrix with a scalar damage value.… More >

Rongzhuang Song^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.09608

Abstract Kink defects in nanocellulose are ubiquitous yet associated questions remain open regarding the unclear microstructure-mechanical property relationship. Various kink patterns without molecular-scale resolution result in bemusements of how nanocellulose forms different kinks and what the fundamental mechanisms of reversible and irreversible kinks are. In our atomic force microscopy images of mechanically treated cellulose nanofibrils, bent nanofibrils usually exhibit small curvatures while kinked nanofibrils feature sharp bends, in which kinks are conspicuous due to their promiscuous configurations. To identify the nanomechanics of incipient kink defects formed in nanocellulose, molecular dynamics simulations of cellulose nanocrystals (CNCs) under curvature-dependent bending are subsequently carried… More >

Huitian Wang¹, Junjie You¹, Sha Yin^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.010417

Abstract Strong and tough mechanical metamaterials are highly demanded in engineering application. Nature inspired dual-phase metamaterial composites was developed and examined, by employing architectured lattice materials with different mechanical properties respectively as the constituent matrix and reinforcement phases. Then, the reinforcement phase was incorporated into the matrix phase with specific patterning. The composite metamaterials were simply fabricated using additive manufacturing. From quasistatic compression tests, the strength and toughness could be simultaneously enhanced after the addition of reinforcement phase grains. Through simulation modeling, effects of dual-phase distribution, elementary architecture, parent material and defects on mechanical properties of dual-phase mechanical metamaterials were investigated.… More >

Xu Yang^1,2, Jing Zhang^1,2, Chuanxian Luo^1,2, Qinqing Huang^1,2, Hui Xu^1,2, Guozhi Zhang^1,2,*

Energy Engineering, Vol.120, No.9, pp. 2115-2132, 2023, DOI:10.32604/ee.2023.027198

Abstract In response to the problem of frequent leakage and false alarm of partial discharge insulation defects in GIS, this paper conducts experimental research on intermittent discharge characteristics of common solid insulation defects in GIS. Using true GIS to build a multi-source testing platform for intermittent discharge of solid insulation defects, and using pulse current method, ultra-high frequency method, ultrasonic method, and gas characteristic component detection method to study the variation law of intermittent discharge characteristics of solid insulation defects. The results show that: the intermittent discharge state of metal fouling defects on the solid insulation surface decreases with the extension… More >

Ahmed Silik^1,2,7, Xiaodong Wang³, Chenyue Mei³, Xiaolei Jin³, Xudong Zhou⁴, Wei Zhou⁴, Congning Chen⁴, Weixing Hong^1,2, Jiawei Li^1,2, Mingjie Mao^1,2, Yuhan Liu^1,2, Mohammad Noori^5,6,*, Wael A. Altabey^8,*

Structural Durability & Health Monitoring, Vol.17, No.4, pp. 257-281, 2023, DOI:10.32604/sdhm.2023.023617

Abstract Damage detection is an important area with growing interest in mechanical and structural engineering. One of the critical issues in damage detection is how to determine indices sensitive to the structural damage and insensitive to the surrounding environmental variations. Current damage identification indices commonly focus on structural dynamic characteristics such as natural frequencies, mode shapes, and frequency responses. This study aimed at developing a technique based on energy Curvature Difference, power spectrum density, correlation-based index, load distribution factor, and neutral axis shift to assess the bridge deck condition. In addition to tracking energy and frequency over time using wavelet packet… More > Graphic Abstract

Xiaoxue Zhou¹, Tingyang Yang², Ye Zhang¹, Yanping Ruan¹, Jiancheng Han¹, Xiaowei Liu¹, Ying Zhao¹, Xiaoyan Gu¹, Tingting Liu¹, Hairui Wang¹, Yihua He^1,*

Congenital Heart Disease, Vol.18, No.3, pp. 387-397, 2023, DOI:10.32604/chd.2023.029060

Abstract Background: Atrioventricular septal defects (AVSDs) are screened and diagnosed usually rely on the imaging characteristics of fetal echocardiography (FE). However, diagnosis on images is heavily depended on sonographers’ experience and the quantitative data are rarely studied. Objective: This study aimed to realize the prenatal diagnosis of AVSDs by analyzing the quantitative data on FE. Methods: One hundred and thirteen cardiac quantitative data was analyzed in 370 normal and 49 AVSDs fetuses retrospectively. The top six with the highest diagnostic accuracy rate were acquired according to the area under the curve (AUC), and the diagnostic value of six variables was analyzed.… More >

Nadeem Jabbar Chaudhry^1,*, M. Bilal Khan², M. Javaid Iqbal¹, Siddiqui Muhammad Yasir³

Journal on Artificial Intelligence, Vol.4, No.4, pp. 245-259, 2022, DOI:10.32604/jai.2022.038875

Abstract Recently, outstanding identification rates in image classification tasks were achieved by convolutional neural networks (CNNs). to use such skills, selective CNNs trained on a dataset of well-known images of metal surface defects captured with an RGB camera. Defects must be detected early to take timely corrective action due to production concerns. For image classification up till now, a model-based method has been utilized, which indicated the predicted reflection characteristics of surface defects in comparison to flaw-free surfaces. The problem of detecting steel surface defects has grown in importance as a result of the vast range of steel applications in end-product… More >