Haojie Lian¹, Jiaqi Wang¹, Leilei Chen^2,*, Shengze Li³, Ruochen Cao⁴, Qingyuan Hu⁵, Peiyun Zhao¹

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 1143-1163, 2024, DOI:10.32604/cmes.2024.048549

Abstract This paper presents a novel framework aimed at quantifying uncertainties associated with the 3D reconstruction of smoke from 2D images. This approach reconstructs color and density fields from 2D images using Neural Radiance Field (NeRF) and improves image quality using frequency regularization. The NeRF model is obtained via joint training of multiple artificial neural networks, whereby the expectation and standard deviation of density fields and RGB values can be evaluated for each pixel. In addition, customized physics-informed neural network (PINN) with residual blocks and two-layer activation functions are utilized to input the density fields of the NeRF into Navier-Stokes equations… More >

SAIFEI XIE^1,2,4, HUI XIE^2,*, JINCAI GUO³, JIN TAN⁴, YULIN YU¹, MINYI ZHANG¹, SHANG WEN¹

BIOCELL, Vol.48, No.4, pp. 591-599, 2024, DOI:10.32604/biocell.2024.046691

Abstract Background: Puerarin (Pue) has been reported to be a natural active ingredient with multiple antifibrotic properties. This work aimed at exploring the function of Pue in oral submucous fibrosis (OSF) treatment. Methods: Human oral mucosa fibroblasts (hOMF) were induced with transforming growth factor beta1 (TGF-β1) and intervened with Pue. Expressions of fibrosis-related markers were analyzed by Western blot and IF staining. Cell viability was characterized by the CCK-8 assay. Expressions of miR-30 family members were quantified by qRT-PCR. The correlation between fibroblast activation protein (FAP) and miR-30 family expression was evaluated by the Pearson correlation coefficient. Bioinformatics prediction and dual-luciferase… More > Graphic Abstract

Sureka Sivavelu, Venkatesh Palanisamy^*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3469-3487, 2024, DOI:10.32604/cmc.2024.047407

Abstract The development of defect prediction plays a significant role in improving software quality. Such predictions are used to identify defective modules before the testing and to minimize the time and cost. The software with defects negatively impacts operational costs and finally affects customer satisfaction. Numerous approaches exist to predict software defects. However, the timely and accurate software bugs are the major challenging issues. To improve the timely and accurate software defect prediction, a novel technique called Nonparametric Statistical feature scaled QuAdratic regressive convolution Deep nEural Network (SQADEN) is introduced. The proposed SQADEN technique mainly includes two major processes namely metric… More >

HYUNG SUN KIM^1,#, YUN SUN LEE^2,#, SEUNG MYUNG DONG³, HYO JUNG KIM¹, DA EUN LEE², HYEON WOONG KANG², MYEONG JIN KIM², JOON SEONG PARK^1,*

Oncology Research, Vol.32, No.4, pp. 615-624, 2024, DOI:10.32604/or.2024.044029

Abstract Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive solid malignancies. A specific mechanism of its metastasis has not been established. In this study, we investigated whether Neural Wiskott-Aldrich syndrome protein (N-WASP) plays a role in distant metastasis of PDAC. We found that N-WASP is markedly expressed in clinical patients with PDAC. Clinical analysis showed a notably more distant metastatic pattern in the N-WASP-high group compared to the N-WASP-low group. N-WASP was noted to be a novel mediator of epithelial-mesenchymal transition (EMT) via gene expression profile studies. Knockdown of N-WASP in pancreatic cancer cells significantly inhibited cell invasion, migration,… More > Graphic Abstract

Youming Guo, Qinmu Wu^*

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1489-1514, 2023, DOI:10.32604/cmc.2023.042313

Abstract Permanent magnet synchronous motor (PMSM) is widely used in various production processes because of its high efficiency, fast reaction time, and high power density. With the continuous promotion of new energy vehicles, timely detection of PMSM faults can significantly reduce the accident rate of new energy vehicles, further enhance consumers’ trust in their safety, and thus promote their popularity. Existing fault diagnosis methods based on deep learning can only distinguish different PMSM faults and cannot interpret and analyze them. Convolutional neural networks (CNN) show remarkable accuracy in image data analysis. However, due to the “black box” problem in deep learning… More >

SAYAKA IMATSUJI^1,#, YUKIKO UJIE^1,#, HIROYUKI ODAKE¹, MASAYA IMOTO^1,2, SUSUMU ITOH³, ETSU TASHIRO^1,3,*

Oncology Research, Vol.32, No.1, pp. 139-150, 2024, DOI:10.32604/or.2023.030190

Abstract Growing evidence suggests an association between epithelial-mesenchymal transition (EMT), a hallmark of tumor malignancy, and chemoresistance to a number of anti-cancer drugs. However, the mechanism of EMT induction in the process of acquiring anti-cancer drug resistance remains unclear. To address this issue, we obtained a number of cisplatin-resistant clones from LoVo cells and found that almost all of them lost cell-cell contacts. In these clones, the epithelial marker E-cadherin was downregulated, whereas the mesenchymal marker N-cadherin was upregulated. Moreover, the expression of EMT-related transcription factors, including Slug, was elevated. On the other hand, the upregulation of other mesenchymal marker Vimentin… More >

Chia-Wei Jan¹, Yu-Jhih Chiu¹, Kuan-Lin Chen², Ting-Chun Yao³, Ping-Huan Kuo^1,4,*

Computer Systems Science and Engineering, Vol.47, No.3, pp. 2989-3010, 2023, DOI:10.32604/csse.2023.042078

Abstract Pneumonia is a common lung disease that is more prone to affect the elderly and those with weaker respiratory systems. However, hospital medical resources are limited, and sometimes the workload of physicians is too high, which can affect their judgment. Therefore, a good medical assistance system is of great significance for improving the quality of medical care. This study proposed an integrated system by combining transfer learning and gradient-weighted class activation mapping (Grad-CAM). Pneumonia is a common lung disease that is generally diagnosed using X-rays. However, in areas with limited medical resources, a shortage of medical personnel may result in… More >

Premanand S., Sathiya Narayanan^*

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 25-45, 2023, DOI:10.32604/cmc.2023.042590

Abstract Machine Learning (ML) and Deep Learning (DL) technologies are revolutionizing the medical domain, especially with Electrocardiogram (ECG), by providing new tools and techniques for diagnosing, treating, and preventing diseases. However, DL architectures are computationally more demanding. In recent years, researchers have focused on combining the computationally less intensive portion of the DL architectures with ML approaches, say for example, combining the convolutional layer blocks of Convolution Neural Networks (CNNs) into ML algorithms such as Extreme Gradient Boosting (XGBoost) and K-Nearest Neighbor (KNN) resulting in CNN-XGBoost and CNN-KNN, respectively. However, these approaches are homogenous in the sense that they use a… More >

Hamdi Hachicha^1,2, Mamadou Dia², Hassine Bouafif², Ahmed Koubaa¹, Mohamed Khlif³, Flavia Lega Braghiroli^1,*

Journal of Renewable Materials, Vol.11, No.11, pp. 3807-3829, 2023, DOI:10.32604/jrm.2023.029454

Abstract Reconstituted wood panels have several advantages in terms of ease of manufacturing, but their shorter life span results in a huge amount of reconstituted wood panels being discarded in sorting centers yearly. Currently, the most common approach for dealing with this waste is incineration. In this study, reconstituted wood panels were converted into activated biochar through a two-step thermochemical process: (i) biochar production using pilot scale fast pyrolysis at 250 kg/h and 450°C; and (ii) a physical activation at three temperatures (750°C, 850°C and 950°C) using an in-house activation furnace (1 kg/h). Results showed that the first stage removed about… More > Graphic Abstract

Xiaojie Jiang¹, Xin Li¹, Yining Xu¹, Dong Sun¹, Julien S. Baker², Yaodong Gu^1,3,*

Molecular & Cellular Biomechanics, Vol.20, No.2, pp. 67-79, 2023, DOI:10.32604/mcb.2023.042910

Abstract

The aim of this study was to investigate whether kinematic data during a countermovement jump (CMJ) could explain the post-activation performance enhancement (PAPE) effects following acute resistance exercise. Twenty-four male participants with resistance training and jumping experience were recruited and randomly assigned to either the experimental group (PAPE-stimulus) (n = 12) or the control group (n = 12). In the experimental group, participants performed 5 reps of squats at 80% 1RM to induce PAPE, while the control group received no intervention. Both groups performed three CMJ tests before (PRE) and at immediate (POST0), 4 (POST4), 8 (POST8), and 12 (POST12)… More > Graphic Abstract