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  • Open Access

    ARTICLE

    ESTIMATION AND VALIDATION OF INTERFACIAL HEAT TRANSFER COEFFICIENT DURING SOLIDIFICATION OF SPHERICAL SHAPED ALUMINUM ALLOY (AL 6061) CASTING USING INVERSE CONTROL VOLUME TECHNIQUE

    L. Anna Gowsalyaa , P.D. Jeyakumarb,*, R. Rajaramanc,†, R. Velrajd

    Frontiers in Heat and Mass Transfer, Vol.12, pp. 1-7, 2019, DOI:10.5098/hmt.12.21

    Abstract Solidification of casting is a complex phenomenon which requires accurate input to simulate for real time applications. Interfacial heat transfer coefficient (IHTC) is an important input parameter for the simulation process. The IHTC is varying with respect to time during solidification and the exact value is to be given as input for the accurate simulation of the casting process. In this work an attempt is made to estimate the IHTC during solidification of spherical shaped aluminum alloy component with sand mould. The mould surface heat flux and mould surface temperatures are estimated by inverse control volume technique using the temperature… More >

  • Open Access

    ARTICLE

    Performance Evaluation of Deep Dense Layer Neural Network for Diabetes Prediction

    Niharika Gupta1, Baijnath Kaushik1, Mohammad Khalid Imam Rahmani2,*, Saima Anwar Lashari2,*

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 347-366, 2023, DOI:10.32604/cmc.2023.038864

    Abstract Diabetes is one of the fastest-growing human diseases worldwide and poses a significant threat to the population’s longer lives. Early prediction of diabetes is crucial to taking precautionary steps to avoid or delay its onset. In this study, we proposed a Deep Dense Layer Neural Network (DDLNN) for diabetes prediction using a dataset with 768 instances and nine variables. We also applied a combination of classical machine learning (ML) algorithms and ensemble learning algorithms for the effective prediction of the disease. The classical ML algorithms used were Support Vector Machine (SVM), Logistic Regression (LR), Decision Tree (DT), K-Nearest Neighbor (KNN),… More >

  • Open Access

    ARTICLE

    Validation of the Chinese Version of the Affective Exercise Experiences Questionnaire (AFFEXX-C)

    Ting Wang1, Boris Cheval2,3, Silvio Maltagliati4, Zachary Zenko5, Fabian Herold6, Sebastian Ludyga7, Markus Gerber7, Yan Luo8, Layan Fessler4, Notger G. Müller6, Liye Zou1,*

    International Journal of Mental Health Promotion, Vol.25, No.7, pp. 799-812, 2023, DOI:10.32604/ijmhp.2023.028324

    Abstract Despite the well-established benefits of regular physical activity (PA) on health, a large proportion of the world population does not achieve the recommended level of regular PA. Although affective experiences toward PA may play a key role to foster a sustained engagement in PA, they have been largely overlooked and crudely measured in the existing studies. To address this shortcoming, the Affective Exercise Experiences (AFFEXX) questionnaire has been developed to measure such experiences. Specifically, this questionnaire was developped to assess the following three domains: antecedent appraisals (e.g., liking vs. disliking exercise in groups), core affective exercise experiences (i.e., pleasure vs.… More >

  • Open Access

    ARTICLE

    Genetic algorithm-optimized backpropagation neural network establishes a diagnostic prediction model for diabetic nephropathy: Combined machine learning and experimental validation in mice

    WEI LIANG1,2,*, ZONGWEI ZHANG1,2, KEJU YANG1,2,3, HONGTU HU1,2, QIANG LUO1,2, ANKANG YANG1,2, LI CHANG4, YUANYUAN ZENG4

    BIOCELL, Vol.47, No.6, pp. 1253-1263, 2023, DOI:10.32604/biocell.2023.027373

    Abstract Background: Diabetic nephropathy (DN) is the most common complication of type 2 diabetes mellitus and the main cause of end-stage renal disease worldwide. Diagnostic biomarkers may allow early diagnosis and treatment of DN to reduce the prevalence and delay the development of DN. Kidney biopsy is the gold standard for diagnosing DN; however, its invasive character is its primary limitation. The machine learning approach provides a non-invasive and specific criterion for diagnosing DN, although traditional machine learning algorithms need to be improved to enhance diagnostic performance. Methods: We applied high-throughput RNA sequencing to obtain the genes related to DN tubular… More >

  • Open Access

    ARTICLE

    Prognostic prediction and expression validation of NSD3 in pan-cancer analyses

    SHA LI1,2,#, YAQIONG LIU3,#, CHAOLING YAO1, ANJI XU1, XIAOLING ZENG4, YUXIN GE4, XIAOWU SHENG4, HAILIN ZHANG1,2, XIAO ZHOU1,2,*, YING LONG1,2,*

    BIOCELL, Vol.47, No.5, pp. 1003-1019, 2023, DOI:10.32604/biocell.2023.027209

    Abstract Background: Nuclear receptor binding SET domain protein-3 (NSD3) is a histone lysine methyltransferase and a crucial regulator of carcinogenesis in several cancers. We aimed to investigate the prognostic value and potential function of NSD3 in 33 types of human cancer. Methods: The data were obtained from The Cancer Genome Atlas. Kaplan-Meier analysis, CIBERSORT, gene set enrichment analysis, and gene set variation analysis were performed. The expression of NSD3 was measured using quantitative real-time polymerase chain reaction and western blot. Results: The expression of NSD3 was altered in pan-cancer samples. Patients with higher levels of NDS3 generally had shorter overall survival… More >

  • Open Access

    ARTICLE

    Dynamic Modeling and Sensitivity Analysis for an MEA-Based CO2 Capture Absorber

    Hongwei Guan1, Lingjian Ye2,3,*, Yurun Wang2, Feifan Shen4, Yuchen He3

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3535-3550, 2023, DOI:10.32604/iasc.2023.036399

    Abstract The absorber is the key unit in the post-combustion monoethanolamine (MEA)-based carbon dioxide (CO2) capture process. A rate-based dynamic model for the absorber is developed and validated using steady-state experimental data reported in open literature. Sensitivity analysis is performed with respect to important model parameters associated with the reaction, mass transport and physical property relationships. Then, a singular value decomposition (SVD)-based subspace parameter estimation method is proposed to improve the model accuracy. Finally, dynamic simulations are carried out to investigate the effects of the feed rate of lean MEA solution and the flue inlet conditions. Simulation results indicate that the… More >

  • Open Access

    ARTICLE

    Spectral Analysis and Validation of Parietal Signals for Different Arm Movements

    Umashankar Ganesan1,*, A. Vimala Juliet2, R. Amala Jenith Joshi3

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2849-2863, 2023, DOI:10.32604/iasc.2023.033759

    Abstract Brain signal analysis plays a significant role in attaining data related to motor activities. The parietal region of the brain plays a vital role in muscular movements. This approach aims to demonstrate a unique technique to identify an ideal region of the human brain that generates signals responsible for muscular movements; perform statistical analysis to provide an absolute characterization of the signal and validate the obtained results using a prototype arm. This can enhance the practical implementation of these frequency extractions for future neuro-prosthetic applications and the characterization of neurological diseases like Parkinson’s disease (PD). To play out this handling… More >

  • Open Access

    ARTICLE

    Selection and Validation of Reference Genes for Normalization of RT-qPCR Analysis in Developing or Abiotic-Stressed Tissues of Loquat (Eriobotrya japonica)

    Shoukai Lin1,2,#, Shichang Xu1,#, Liyan Huang1, Fuxiang Qiu1, Yihong Zheng1, Qionghao Liu1, Shiwei Ma1,2, Bisha Wu1,2, Jincheng Wu1,2,*

    Phyton-International Journal of Experimental Botany, Vol.92, No.4, pp. 1185-1201, 2023, DOI:10.32604/phyton.2023.026752

    Abstract Loquat (Eriobotrya japonica Lindl.) is a subtropical evergreen fruit tree that produces fruits with abundant nutrients and medicinal components. Confirming suitable reference genes for a set of loquat samples before qRT-PCR experiments is essential for the accurate quantification of gene expression. In this study, eight candidate reference genes were selected from our previously published RNA-seq data, and primers for each candidate reference gene were designed and evaluated. The Cq values of the candidate reference genes were calculated by RT-qPCR in 31 different loquat samples, including 12 subgroups of developing or abiotic-stressed tissues. Different combinations of stable reference genes were screened… More >

  • Open Access

    ARTICLE

    Selection and validation of reference genes for quantitative real-time polymerase chain reaction analyses of Serratia ureilytica DW2

    FENGLIN BAI1,2,#, BIANXIA BAI1,2,#, TINGTING JIN1,2, GUIPING ZHANG1,2, JIAHONG REN1,2,*

    BIOCELL, Vol.47, No.3, pp. 647-656, 2023, DOI:10.32604/biocell.2023.024758

    Abstract Background: Serratia ureilytica DW2 is a highly efficient phosphate-solubilizing bacteria isolated from Codonopsis pilosula rhizosphere soil that can promote the growth of C. pilosula; nonetheless, until now, no validated reference genes from the genus Serratia have been reported that can be used for the normalization of quantitative real-time polymerase chain reaction (RT–qPCR) data. Methods: To screen stable reference genes of S. ureilytica DW2, the expression of its eight candidate reference genes (16S rRNA, ftsZ, ftsA, mreB, recA, slyD, thiC, and zipA) under different treatment conditions (pH, temperature, culture time, and salt content) was assayed by RT–qPCR. The expression stability of… More >

  • Open Access

    ARTICLE

    Offshore Software Maintenance Outsourcing Process Model Validation: A Case Study Approach

    Atif Ikram1,2,*, Masita Abdul Jalil1, Amir Bin Ngah1, Adel Sulaiman3, Muhammad Akram3, Ahmad Salman Khan4

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5035-5048, 2023, DOI:10.32604/cmc.2023.034692

    Abstract The successful execution and management of Offshore Software Maintenance Outsourcing (OSMO) can be very beneficial for OSMO vendors and the OSMO client. Although a lot of research on software outsourcing is going on, most of the existing literature on offshore outsourcing deals with the outsourcing of software development only. Several frameworks have been developed focusing on guiding software system managers concerning offshore software outsourcing. However, none of these studies delivered comprehensive guidelines for managing the whole process of OSMO. There is a considerable lack of research working on managing OSMO from a vendor’s perspective. Therefore, to find the best practices… More >

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