Zhuo Chen^1,*, Ningning Wang², Wenbo Jin³, Dui Li¹

Energy Engineering, Vol.121, No.4, pp. 1007-1026, 2024, DOI:10.32604/ee.2023.045270

Abstract A hard problem that hinders the movement of waxy crude oil is wax deposition in oil pipelines. To ensure the safe operation of crude oil pipelines, an accurate model must be developed to predict the rate of wax deposition in crude oil pipelines. Aiming at the shortcomings of the ENN prediction model, which easily falls into the local minimum value and weak generalization ability in the implementation process, an optimized ENN prediction model based on the IRSA is proposed. The validity of the new model was confirmed by the accurate prediction of two sets of experimental data on wax deposition… More > Graphic Abstract

Fu Guan^1,*, Matthias Gass², Florian Berger², Heiko Schneider¹, Firat Duru^1,3, Thomas Wolber^1,3,*

Congenital Heart Disease, Vol.19, No.1, pp. 85-92, 2024, DOI:10.32604/chd.2024.047266

Abstract Aims: Although the application of ultrasound-guided vascular puncture and Z-stitch hemostasis to manage femoral access has been widely utilized, there is limited data on this combined application in adult congenital heart disease (ACHD) patients undergoing electrophysiological (EP) procedures. We sought to evaluate the safety and efficacy of ultrasound-guided puncture and postprocedural Z-stitch hemostasis for ACHD patients undergoing EP procedures. Methods and Results: The population of ACHD patients undergoing transfemoral EP procedures at the University of Zurich Heart Center between January 2019 and December 2022 was observed and analyzed. During the study period, femoral access (left/right, arterial/venous) was performed under real-time… More >

XINFENG ZHANG^1,2,#, SHUANG LI^2,#, MEIRU SONG^1,2, YUE CHEN³, LIANGZHENG CHANG³, ZHERUI LIU⁴, HONGYUAN DAI³, YUTAO WANG⁴, GANGQI YANG³, YUN JIANG^5,6,*, YINYING LU^1,2,*

Oncology Research, Vol.32, No.4, pp. 679-690, 2024, DOI:10.32604/or.2024.046231

Abstract Liver cancer is a prevalent malignant cancer, ranking third in terms of mortality rate. Metastasis and recurrence primarily contribute to the high mortality rate of liver cancer. Hepatocellular carcinoma (HCC) has low expression of focal adhesion kinase (FAK), which increases the risk of metastasis and recurrence. Nevertheless, the efficacy of FAK phosphorylation inhibitors is currently limited. Thus, investigating the mechanisms by which FAK affects HCC metastasis to develop targeted therapies for FAK may present a novel strategy to inhibit HCC metastasis. This study examined the correlation between FAK expression and the prognosis of HCC. Additionally, we explored the impact of… More >

LU ZHANG^*, JINGUO CHU^*, YUSHAN YU

Oncology Research, Vol.32, No.4, pp. 703-716, 2024, DOI:10.32604/or.2023.030988

Abstract Background: Limited research has been conducted on the influence of autophagy-associated long non-coding RNAs (ARLncRNAs) on the prognosis of hepatocellular carcinoma (HCC). Methods: We analyzed 371 HCC samples from TCGA, identifying expression networks of ARLncRNAs using autophagy-related genes. Screening for prognostically relevant ARLncRNAs involved univariate Cox regression, Lasso regression, and multivariate Cox regression. A Nomogram was further employed to assess the reliability of Riskscore, calculated from the signatures of screened ARLncRNAs, in predicting outcomes. Additionally, we compared drug sensitivities in patient groups with differing risk levels and investigated potential biological pathways through enrichment analysis, using consensus clustering to identify subgroups… More >

Yaohua Zhang^a,*, Yoshio Utaka^b

Frontiers in Heat and Mass Transfer, Vol.3, No.1, pp. 1-12, 2012, DOI:10.5098/hmt.v3.1.3003

Abstract This paper reviews recent research on microlayer formed by confined vapor bubbles during boiling in mini/microchannels. Experimental measurements, simulations and theoretical studies are described and compared. As a reference to clarify the mechanism for the formation of a microlayer, Taylor flow (i.e. elongated bubble flow in mini/micro circular tubes under adiabatic conditions and at Re << 1) and elongated bubble flow at high velocity, with consideration of the influence of inertia, are also reviewed. Compared to the steady adiabatic conditions, one of the distinct points for the boiling condition is that the bubble grows exponentially due to rapid evaporation of… More >

Mohammad Mehedi Hassan^1,*, Salman A. AlQahtani², Mabrook S. AlRakhami¹, Ahmed Zohier Elhendi³

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3101-3123, 2024, DOI:10.32604/cmes.2024.047940

Abstract In the current landscape of the COVID-19 pandemic, the utilization of deep learning in medical imaging, especially in chest computed tomography (CT) scan analysis for virus detection, has become increasingly significant. Despite its potential, deep learning’s “black box” nature has been a major impediment to its broader acceptance in clinical environments, where transparency in decision-making is imperative. To bridge this gap, our research integrates Explainable AI (XAI) techniques, specifically the Local Interpretable Model-Agnostic Explanations (LIME) method, with advanced deep learning models. This integration forms a sophisticated and transparent framework for COVID-19 identification, enhancing the capability of standard Convolutional Neural Network… More >

Fatemeh Hassani Khorshidi¹, Saeed Kazemi Najafi¹, Farhood Najafi^2,*, Antonio Pizzi^3,*, Dick Sandberg⁴, Rabi Behrooz¹

Journal of Renewable Materials, Vol.12, No.2, pp. 305-323, 2024, DOI:10.32604/jrm.2023.043953

Abstract The purpose of this research study was to investigate the properties of polyurethane coatings based on lignin nano-particles. For this purpose, the prepared coatings were applied to pine wood surfaces and weathered artificially. Subsequently, color and gloss of the coatings were measured before and after the weathering test. Field emission scanning electron microscopy (FE-SEM) micrographs prepared from the coatings showed that the average size of nano-particles in the polyurethane substrate was approximately 500 nm. Nuclear magnetic resonance (¹³C-NMR) spectroscopy showed that strong urethane bonds were formed in the nano-lignin-based polyurethane. Differential calorimetric analysis (DSC) test revealed that the glass-transition temperature… More > Graphic Abstract

Flavia Oliveira Monteiro da Silva Abreu^1,2,*, Taysse Holanda¹, Joice Farias do Nascimento¹, Henety Nascimento Pinheiro¹, Rachel Menezes Castelo¹, Hélcio Silva dos Santos³, Thais Benincá⁴, Patrícia da Silva Malheiros⁴, Júlio César Sousa Prado⁵, Raquel de Oliveira Fontenelle⁵, Maria Madalena de Camargo Forte²

Journal of Renewable Materials, Vol.12, No.2, pp. 285-304, 2024, DOI:10.32604/jrm.2023.043919

Abstract With the increase in antimicrobial resistance, it has become necessary to explore alternative approaches for combating and preventing diseases. DB-cinnamaldehyde (CNM) and Benzyl4-amino (B4AM) are bioactive compounds derived from chalcones but with restricted solubility in aqueous media. Nanoemulsions can enhance the solubility of compounds and can be a promising alternative in the development of novel antimicrobials, with reduced side effects and prolonged release. The objective of this study was to evaluate the stability of oil-in-water nanoemulsions loaded with two distinct types of chalcones at two different dosages, to propose a stable formulation with antimicrobial properties. Results showed that nanoemulsions presented… More > Graphic Abstract

Saba Awan^1,*, Zahid Mehmood^2,*

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2535-2555, 2024, DOI:10.32604/cmc.2024.047337

Abstract Highway safety researchers focus on crash injury severity, utilizing deep learning—specifically, deep neural networks (DNN), deep convolutional neural networks (D-CNN), and deep recurrent neural networks (D-RNN)—as the preferred method for modeling accident severity. Deep learning’s strength lies in handling intricate relationships within extensive datasets, making it popular for accident severity level (ASL) prediction and classification. Despite prior success, there is a need for an efficient system recognizing ASL in diverse road conditions. To address this, we present an innovative Accident Severity Level Prediction Deep Learning (ASLP-DL) framework, incorporating DNN, D-CNN, and D-RNN models fine-tuned through iterative hyperparameter selection with Stochastic… More >

Xiao Feng^1,2,3,*, Zheng Yuan¹

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1881-1895, 2024, DOI:10.32604/cmc.2023.047243

Abstract First, we propose a cross-domain authentication architecture based on trust evaluation mechanism, including registration, certificate issuance, and cross-domain authentication processes. A direct trust evaluation mechanism based on the time decay factor is proposed, taking into account the influence of historical interaction records. We weight the time attenuation factor to each historical interaction record for updating and got the new historical record data. We refer to the beta distribution to enhance the flexibility and adaptability of the direct trust assessment model to better capture time trends in the historical record. Then we propose an autoencoder-based trust clustering algorithm. We perform feature… More >