Cheryl Dickson^1,2,4, Danielle Osborn¹, David Baker^1,4, Judith Fethney³, David S. Celermajer^1,4, Rachael Cordina^1,4,*

Congenital Heart Disease, Vol.19, No.1, pp. 49-63, 2024, DOI:10.32604/chd.2023.044874

Abstract Background: Much has been written about the loss to follow-up in the transition between pediatric and adult Congenital Heart Disease (CHD) care centers. Much less is understood about the loss to follow-up (LTF) after a successful transition. This is critical too, as patients lost to specialised care are more likely to experience morbidity and premature mortality. Aims: To understand the prevalence and reasons for loss to follow-up (LTF) at a large Australian Adult Congenital Heart Disease (ACHD) centre. Methods: Patients with moderate or highly complex CHD and gaps in care of >3 years (defined as LTF) were identified from a… 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 >

Morteza Eslamian^*

Frontiers in Heat and Mass Transfer, Vol.2, No.4, pp. 1-20, 2011, DOI:10.5098/hmt.v2.4.3001

Abstract Recent advances in thermodiffusion (Soret effect) in binary and higher multicomponent liquid mixtures are reviewed. The mixtures studied include the hydrocarbon, associating, molten metal and semiconductor, polymer, and DNA mixtures. The emphasis is placed on the theoretical works, particularly models based on the nonequilibrium thermodynamics, although other approaches such as the statistical, kinetic and hydrodynamic approaches are discussed as well. For each mixture, the major theoretical and experimental works are discussed and the research trends and challenges are addressed. Some of the challenges include a need for combining various methods to develop a comprehensive theoretical model or at least to… More >

HAO LV¹, BO ZHU^1,2, DEGAO CHEN^1,2,*

BIOCELL, Vol.48, No.3, pp. 363-378, 2024, DOI:10.32604/biocell.2023.046367

Abstract Tumor-associated macrophages (TAMs) are emerging as targets for tumor therapy because of their primary role in promoting tumor progression. Several studies have been conducted to target TAMs by reducing their infiltration, depleting their numbers, and reversing their phenotypes to suppress tumor progression, leading to the development of drugs in preclinical and clinical trials. However, the heterogeneous characteristics of TAMs, including their ontogenetic and functional heterogeneity, limit their targeting. Therefore, in-depth exploration of the heterogeneity of TAMs, combined with immune checkpoint therapy or other therapeutic modalities could improve the efficiency of tumor treatment. This review focuses on the heterogeneous ontogeny and… More >

Irfan Haider¹, Muhammad Attique Khan^1,*, Muhammad Nazir¹, Taerang Kim², Jae-Hyuk Cha²

Computer Systems Science and Engineering, Vol.48, No.2, pp. 529-554, 2024, DOI:10.32604/csse.2023.042080

Abstract Fruit infections have an impact on both the yield and the quality of the crop. As a result, an automated recognition system for fruit leaf diseases is important. In artificial intelligence (AI) applications, especially in agriculture, deep learning shows promising disease detection and classification results. The recent AI-based techniques have a few challenges for fruit disease recognition, such as low-resolution images, small datasets for learning models, and irrelevant feature extraction. This work proposed a new fruit leaf leaf leaf disease recognition framework using deep learning features and improved pathfinder optimization. Three fruit types have been employed in this work for… More >

Nasser Alshammari¹, Shumaila Shahzadi², Saad Awadh Alanazi^1,*, Shahid Naseem³, Muhammad Anwar³, Madallah Alruwaili⁴, Muhammad Rizwan Abid⁵, Omar Alruwaili⁴, Ahmed Alsayat¹, Fahad Ahmad^6,7

Computer Systems Science and Engineering, Vol.48, No.2, pp. 363-394, 2024, DOI:10.32604/csse.2023.040721

Abstract Software Defined Network (SDN) and Network Function Virtualization (NFV) technology promote several benefits to network operators, including reduced maintenance costs, increased network operational performance, simplified network lifecycle, and policies management. Network vulnerabilities try to modify services provided by Network Function Virtualization MANagement and Orchestration (NFV MANO), and malicious attacks in different scenarios disrupt the NFV Orchestrator (NFVO) and Virtualized Infrastructure Manager (VIM) lifecycle management related to network services or individual Virtualized Network Function (VNF). This paper proposes an anomaly detection mechanism that monitors threats in NFV MANO and manages promptly and adaptively to implement and handle security functions in order… More >

Frontiers in Heat and Mass Transfer, Vol.3, No.1, pp. 1-3, 2012, DOI:10.5098/hmt.v3.1.1001

Abstract This article has no abstract. More >

Carlo Cattani¹, Haci Mehmet Baskonus^2,*, Armando Ciancio³

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2261-2264, 2024, DOI:10.32604/cmes.2024.050209

Abstract This article has no abstract. More >

Yizhao Wang^*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3029-3045, 2024, DOI:10.32604/cmes.2024.046270

Abstract Near-fault impulsive ground-shaking is highly destructive to engineering structures, so its accurate identification ground-shaking is a top priority in the engineering field. However, due to the lack of a comprehensive consideration of the ground-shaking characteristics in traditional methods, the generalization and accuracy of the identification process are low. To address these problems, an impulsive ground-shaking identification method combined with deep learning named PCA-LSTM is proposed. Firstly, ground-shaking characteristics were analyzed and ground-shaking the data was annotated using Baker’s method. Secondly, the Principal Component Analysis (PCA) method was used to extract the most relevant features related to impulsive ground-shaking. Thirdly, a… More >

Weiliang Gao¹, Shixu Jia², Tingting Zhao^2,3,*, Zhiyong Wang²

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3495-3511, 2024, DOI:10.32604/cmes.2023.046188

Abstract The mechanical properties of interfacial transition zones (ITZs) have traditionally been simplified by reducing the stiffness of cement in previous simulation methods. A novel approach based on the discrete element method (DEM) has been developed for modeling concrete. This new approach efficiently simulates the meso-structure of ITZs, accurately capturing their heterogeneous properties. Validation against established uniaxial compression experiments confirms the precision of this model. The proposed model can model the process of damage evolution containing cracks initiation, propagation and penetration. Under increasing loads, cracks within ITZs progressively accumulate, culminating in macroscopic fractures that traverse the mortar matrix, forming the complex,… More >