Jae Hong Lee¹, Sungkyu Cho^2,*, Jae Gun Kwak², Hye Won Kwon², Woong-Han Kim², Mi Kyoung Song³, Sang-Yun Lee³, Gi Beom Kim³, Eun Jung Bae³

Congenital Heart Disease, Vol.19, No.1, pp. 69-83, 2024, DOI:10.32604/chd.2024.045137

Abstract Background: The optimal surgical timing and clinical outcomes of ventricular septal defect (VSD) closure in neonates remain unclear. We aimed to evaluate the clinical outcomes of VSD closure in neonates (age ≤ 30 days). Methods: We retrospectively reviewed 50 consecutive neonates who underwent VSD closure for isolated VSDs between August 2003 and June 2021. Indications for the procedure included congestive heart failure/failure to thrive and pulmonary hypertension. Major adverse events (MAEs) were defined as the composite of all-cause mortality, reoperation, persistent atrioventricular block, and significant (≥grade 2) valvular dysfunction. Results: The median age and body weight at operation were 26.0… More >

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 >

Pankaj Saha^a, Gautam Biswas^a,b,*

Frontiers in Heat and Mass Transfer, Vol.2, No.3, pp. 1-5, 2011, DOI:10.5098/hmt.v2.3.3008

Abstract Detailed flow structure in turbulent flows through a rectangular channel containing built-in winglet type vortex generators have been analyzed by means of solutions of the full Navier-Stokes equations using a Large-Eddy Simulation (LES) technique. The Reynolds number of investigation is 6000. The geometry of interest consists of a rectangular channel with a built-in winglet pair on the bottom wall with common-flow-down arrangement. The winglet pair induces streamwise longitudinal vortices behind it. The vortices swirl the flow around the axis parallel to the mainstream direction and disrupt the growth of thermal boundary layer entailing enhancement of heat transfer. The influence of… More >

Seoyun Kim^1,#, Hyerim Yu^2,#, Jeewoo Yoon^1,3, Eunil Park^1,2,*

Computer Systems Science and Engineering, Vol.48, No.2, pp. 413-429, 2024, DOI:10.32604/csse.2023.041575

Abstract Given the increasing number of countries reporting degraded air quality, effective air quality monitoring has become a critical issue in today’s world. However, the current air quality observatory systems are often prohibitively expensive, resulting in a lack of observatories in many regions within a country. Consequently, a significant problem arises where not every region receives the same level of air quality information. This disparity occurs because some locations have to rely on information from observatories located far away from their regions, even if they may be the closest available options. To address this challenge, a novel approach that leverages machine… More >

Anas Bilal¹, Azhar Imran², Talha Imtiaz Baig^3,4, Xiaowen Liu^1,*, Haixia Long¹, Abdulkareem Alzahrani⁵, Muhammad Shafiq⁶

Computer Systems Science and Engineering, Vol.48, No.2, pp. 511-528, 2024, DOI:10.32604/csse.2023.039672

Abstract Artificial Intelligence (AI) is being increasingly used for diagnosing Vision-Threatening Diabetic Retinopathy (VTDR), which is a leading cause of visual impairment and blindness worldwide. However, previous automated VTDR detection methods have mainly relied on manual feature extraction and classification, leading to errors. This paper proposes a novel VTDR detection and classification model that combines different models through majority voting. Our proposed methodology involves preprocessing, data augmentation, feature extraction, and classification stages. We use a hybrid convolutional neural network-singular value decomposition (CNN-SVD) model for feature extraction and selection and an improved SVM-RBF with a Decision Tree (DT) and K-Nearest Neighbor (KNN)… More >

Amr Ismail¹, Walid Hamdy^1,2, Aya M. Al-Zoghby³, Wael A. Awad³, Ahmed Ismail Ebada³, Yunyoung Nam⁴, Byeong-Gwon Kang^4,*, Mohamed Abouhawwash^5,6

Computer Systems Science and Engineering, Vol.48, No.2, pp. 273-285, 2024, DOI:10.32604/csse.2023.038192

Abstract Deep learning (DL) plays a critical role in processing and converting data into knowledge and decisions. DL technologies have been applied in a variety of applications, including image, video, and genome sequence analysis. In deep learning the most widely utilized architecture is Convolutional Neural Networks (CNN) are taught discriminatory traits in a supervised environment. In comparison to other classic neural networks, CNN makes use of a limited number of artificial neurons, therefore it is ideal for the recognition and processing of wheat gene sequences. Wheat is an essential crop of cereals for people around the world. Wheat Genotypes identification has… More >

Etienne Costa-Patry^a, Jonathan Olivier^b, John R. Thome^a,∗

Frontiers in Heat and Mass Transfer, Vol.3, No.1, pp. 1-14, 2012, DOI:10.5098/hmt.v3.1.3002

Abstract This article presents new experimental results for two-phase flow boiling of R-134a, R-1234ze(E) and R-245fa in a micro-evaporator. The test section was made of copper and composed of 52 microchannels 163μm wide and 1560μm high with the channels separated by 178μm wide fins. The channels were 13.2mm long. There were 35 local heaters and temperature measurements arranged in a 5×7 array as a pseudo-CPU. The total pressure drops of the test section were below 20kPa in all cases. The wall heat transfer coefficients were generally above 10’000W/m²K and a function of the heat flux, vapor quality and mass flux. A… More >

Arvind Pattamatta^a,*, Ghanshyam Singh^b

Frontiers in Heat and Mass Transfer, Vol.3, No.2, pp. 1-11, 2012, DOI:10.5098/hmt.v3.2.3005

Abstract The present study deals with the assessment of different turbulence models for heated wall jet flow. The velocity field and thermal characteristics for isothermal and uniform heat flux surfaces in the presence of wall jet flow have been predicted using different turbulence models and the results are compared against the experimental data of Wygnanski et al. (1992), Schneider and Goldstein (1994), and AbdulNour et al. (2000). Thirteen different turbulence models are considered for validation, which include the Standard k-ε (SKE), Realizable k-ε (RKE), shear stress transport (SST), Sarkar & So (SSA), v ² -f, Reynolds stress Model (RSM), and Spalart… More >

Wuyang Fan, Shisheng Zhong^*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2525-2555, 2024, DOI:10.32604/cmes.2023.046951

Abstract The dynamic balance assessment during the assembly of the coordinator gyroscope significantly impacts the guidance accuracy of precision-guided equipment. In dynamic balance debugging, reliance on rudimentary counterweight empirical formulas persists, resulting in suboptimal debugging accuracy and an increased repetition rate. To mitigate this challenge, we present a multi-head residual graph attention network (ResGAT) model, designed to predict dynamic balance counterweights with high precision. In this research, we employ graph neural networks for interaction feature extraction from assembly graph data. An SDAE-GPC model is designed for the assembly condition classification to derive graph data inputs for the ResGAT regression model, which… More >