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  • Open Access

    ARTICLE

    ETHYLENE GLYCOL-BASED NANOFLUIDS – ESTIMATION OF STABILITY AND THERMOPHYSICAL PROPERTIES

    S. Ravi Tejaa , Chellapilla V. K. N. S. N. Moorthyb,*, S. Jayakumarc , Ayyagari Kiran Kumard , V. Srinivasc,*

    Frontiers in Heat and Mass Transfer, Vol.15, No.1, pp. 1-9, 2020, DOI:10.5098/hmt.15.7

    Abstract This article is a summary of research involving the evaluation of the thermo-physical properties of Mono-ethylene - glycol-based solar thermic fluids oxidized multiwalled carbon nanotubes. Nanofluids were prepared with Mono-ethylene glycol and water as base fluids in 100:0, 90:10 and 80:20 ratios. These base fluids of three categories were dispersed with purified and oxidized multiwalled carbon nanotubes (MWCNTs) in the weight fractions of 0.125, 0.25 and 0.5 percentages. The variation in zeta potential is studied to examine the dispersion stability during 2 months. Thermal conductivity and dynamic viscosity were measured by hot disk method and Anton paar viscometer respectively. Significant… More >

  • Open Access

    ARTICLE

    The correlation of miRNA expression and tumor mutational burden in uterine corpus endometrial carcinoma

    YANYA CHEN1,#, HONGYUAN WU2,#, RUISI ZHOU5,#, HELING DONG4, XUEFANG ZHANG2, XUEWEI WU1, WENSHAN CHEN1, YANTING YOU5,*, YIFEN WU3,*

    BIOCELL, Vol.47, No.6, pp. 1353-1364, 2023, DOI:10.32604/biocell.2023.027346

    Abstract Background: The relationship between microRNA (miRNA) expression patterns and tumor mutation burden (TMB) in uterine corpus endometrial carcinoma (UCEC) was investigated in this study. Methods: The UCEC dataset from The Cancer Genome Atlas (TCGA) database was used to identify the miRNAs that differ in expression between high TMB and low TMB sample sets. The total sample sets were divided into a training set and a test set. TMB levels were predicted using miRNA-based signature classifiers developed by Lasso Cox regression. Test sets were used to validate the classifier. This study investigated the relationship between a miRNA-based signature classifier and three… More >

  • Open Access

    ARTICLE

    Correlation Analysis of Wind Turbine Temperature Rise and Exergy Efficiency Based on Field-Path Coupling

    Caifeng Wen1,2, Qiang Wang1,*, Yang Cao1, Liru Zhang1,2, Wenxin Wang3, Boxin Zhang1, Qian Du1

    Energy Engineering, Vol.120, No.7, pp. 1603-1619, 2023, DOI:10.32604/ee.2023.027074

    Abstract To solve the problems of large losses and low productivity of permanent magnet synchronous generators used in wind power systems, the field-circuit coupling method is used to accurately solve the electromagnetic field and temperature field of the generator. The loss distribution of the motor is accurately obtained by considering the influence of external circuit characteristics on its internal physical field. By mapping the losses to the corresponding part of the three-dimensional finite element model of the motor, the temperature field is solved, and the global temperature distribution of the generator, considering the influence of end windings, is obtained. By changing… More >

  • Open Access

    ARTICLE

    Object Tracking Algorithm Based on Multi-Time-Space Perception and Instance-Specific Proposals

    Jinping Sun*, Dan Li, Honglin Cheng

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 655-675, 2023, DOI:10.32604/iasc.2023.038016

    Abstract Aiming at the problem that a single correlation filter model is sensitive to complex scenes such as background interference and occlusion, a tracking algorithm based on multi-time-space perception and instancespecific proposals is proposed to optimize the mathematical model of the correlation filter (CF). Firstly, according to the consistency of the changes between the object frames and the filter frames, the mask matrix is introduced into the objective function of the filter, so as to extract the spatio-temporal information of the object with background awareness. Secondly, the object function of multi-feature fusion is constructed for the object location, which is optimized… More >

  • Open Access

    ARTICLE

    CORRELATION DEVELOPMENT FOR JET IMPINGEMENT HEAT TRANSFER AND FORCE ON A MOVING CURVED SURFACE

    Ali Chitsazana, Georg Kleppa, Birgit Glasmacherb

    Frontiers in Heat and Mass Transfer, Vol.18, No.1, pp. 1-9, 2022, DOI:10.5098/hmt.18.16

    Abstract The effect of jet Reynolds number, jet exit angle, the nozzle to surface distance, jet to jet spacing on the heat transfer, and pressure force performance from multiple impinging round jets on a moving curved surface have been numerically evaluated. Two correlations are developed and validated for the average Nu number and the pressure force coefficient and the agreement between the CFD and correlations was reasonable. The surface motion effect becomes more pronounced on the Nu number distribution for low jet Re number, high jet to jet spacing, large jet to surface distance, and angled jets. The pressure force coefficient… More >

  • Open Access

    ARTICLE

    Estimation of Genetic Divergence and Character Association Studies in Local and Exotic Diversity Panels of Soybean (Glycine max L.) Genotypes

    Syed Ali Zafar1,*, Muhammad Aslam2, Haroon Zaman Khan3, Sehrish Sarwar1, Rao Saad Rehman4, Mariam Hassan1, Ramala Masood Ahmad2, Rafaqat A. Gill5, Basharat Ali6, Ibrahim Al-Ashkar7, Abdullah Ibrahim7, Md Atikur Rahman8, Ayman El Sabagh9,*

    Phyton-International Journal of Experimental Botany, Vol.92, No.6, pp. 1887-1906, 2023, DOI:10.32604/phyton.2023.027679

    Abstract The availability of favorable genetic diversity is a thriving vitality for the success of a breeding program. It provides a firm basis of selecting superior breeding lines for the development of high yielding crop genotypes. In this context, present investigation aimed to generate information on genetic divergence and character association in a diversity panel of 123 local and exotic soybean genotypes. Analysis of variance revealed significant response of the evaluated genotypes based on studied attributes. It depicted the probability of selecting desirable soybean genotypes by focusing on character association studies and genetic diversity analysis. Correlation analysis revealed that seed yield… More >

  • Open Access

    ARTICLE

    Covid-19 Detection Using Deep Correlation-Grey Wolf Optimizer

    K. S. Bhuvaneshwari1, Ahmed Najat Ahmed2, Mehedi Masud3, Samah H. Alajmani4, Mohamed Abouhawwash5,6,*

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 2933-2945, 2023, DOI:10.32604/csse.2023.034288

    Abstract The immediate and quick spread of the coronavirus has become a life-threatening disease around the globe. The widespread illness has dramatically changed almost all sectors, moving from offline to online, resulting in a new normal lifestyle for people. The impact of coronavirus is tremendous in the healthcare sector, which has experienced a decline in the first quarter of 2020. This pandemic has created an urge to use computer-aided diagnosis techniques for classifying the Covid-19 dataset to reduce the burden of clinical results. The current situation motivated me to choose correlation-based development called correlation-based grey wolf optimizer to perform accurate classification.… More >

  • Open Access

    ARTICLE

    Deep Capsule Residual Networks for Better Diagnosis Rate in Medical Noisy Images

    P. S. Arthy1,*, A. Kavitha2

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2959-2971, 2023, DOI:10.32604/iasc.2023.032511

    Abstract With the advent of Machine and Deep Learning algorithms, medical image diagnosis has a new perception of diagnosis and clinical treatment. Regrettably, medical images are more susceptible to capturing noises despite the peak in intelligent imaging techniques. However, the presence of noise images degrades both the diagnosis and clinical treatment processes. The existing intelligent methods suffer from the deficiency in handling the diverse range of noise in the versatile medical images. This paper proposes a novel deep learning network which learns from the substantial extent of noise in medical data samples to alleviate this challenge. The proposed deep learning architecture… More >

  • Open Access

    ARTICLE

    The Impact of COVID-19 on the Mental-Emotional Wellbeing of Primary Healthcare Professionals: A Descriptive Correlational Study

    Regina Lai-Tong Lee1,2,*, Anson Chiu-Yan Tang3, Ho-Yu Cheng1, Connie Yuen-Yu Chong1, Wilson Wai-San Tam4, Wai-Tong Chien1, Sally Wai-Chi Chan5

    International Journal of Mental Health Promotion, Vol.25, No.3, pp. 327-342, 2023, DOI:10.32604/ijmhp.2022.026388

    Abstract The present study aimed to examine work environment related factors and frontline primary healthcare professionals’ mental-emotional wellbeing during the COVID-19 pandemic in school communities of Hong Kong. A total of 61 (20%) school health nurses (frontline primary healthcare professionals) participated in a cross-sectional online survey from March to June 2020. Outcomes of mental-emotional health were measured using the Mental Health Continuum-Short Form (14-item scale with three subscales related to emotional, social and psychological wellbeing); the Perceived Stress Scale (10-item scale with two subscales related to perceived helplessness and lack of self-efficacy; and the Coping Orientation to Problems Experienced Inventory (Brief… More >

  • Open Access

    ARTICLE

    AlertInsight: Mining Multiple Correlation For Alert Reduction

    Mingguang Yu1,2, Xia Zhang1,2,*

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 2447-2469, 2023, DOI:10.32604/csse.2023.037506

    Abstract Modern cloud services are monitored by numerous multidomain and multivendor monitoring tools, which generate massive numbers of alerts and events that are not actionable. These alerts usually carry isolated messages that are missing service contexts. Administrators become inundated with tickets caused by such alert events when they are routed directly to incident management systems. Noisy alerts increase the risk of crucial warnings going undetected and leading to service outages. One of the feasible ways to cope with the above problems involves revealing the correlations behind a large number of alerts and then aggregating the related alerts according to their correlations.… More >

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