YUN ZHANG^1,2,#, SHALING TANG^1,2,#, YUBO GAO^1,2, ZHONGTING LU^1,2, YUAN YANG^1,2, JING CHEN³, TAO LI^4,*

Oncology Research, Vol.32, No.1, pp. 61-71, 2024, DOI:10.32604/or.2023.043481

Abstract Colorectal cancer (CRC) is a major global health problem with high morbidity and mortality rates. Surgical resection is the main treatment for early-stage CRC, but detecting it early is challenging. Therefore, effective therapeutic targets for advanced patients are still lacking. Exosomes, tiny vesicles in body fluids, play a crucial role in tumor metastasis, immune regulation, and drug resistance. Interestingly, they can even serve as a biomarker for cancer diagnosis and prognosis. Studies have shown that exosomes can carry miRNA, mediate the polarization of M1/M2 macrophages, promote the proliferation and metastasis of cancer cells, and affect the prognosis of CRC. Since… More > Graphic Abstract

AMGAD M. RABIE^*

BIOCELL, Vol.47, No.10, pp. 2133-2139, 2023, DOI:10.32604/biocell.2023.030057

Abstract Despite the global decline in the severity of the coronavirus disease 2019 (COVID-19) cases, the disease still represents a major concern to the relevant scientific and medical communities. The primary concern of drug scientists, virologists, and other concerned specialists in this respect is to find ready-to-use suitable and potent anticoronaviral therapies that are broadly effective against the different species/strains of the coronaviruses in general, not only against the current and previous coronaviruses (e.g., the recently-appeared severe acute respiratory syndrome coronavirus 2 “SARS-CoV-2”), i.e., effective antiviral agents for treatment and/or prophylaxis of any coronaviral infections, including those of the coming ones… More > Graphic Abstract

Zhaoan Wang¹, Shaoping Xiao^1,*, Cheryl Reuben², Qiyu Wang², Jun Wang²

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 285-297, 2023, DOI:10.32604/cmc.2023.044366

Abstract This paper presents designing sequence-to-sequence recurrent neural network (RNN) architectures for a novel study to predict soil NOx emissions, driven by the imperative of understanding and mitigating environmental impact. The study utilizes data collected by the Environmental Protection Agency (EPA) to develop two distinct RNN predictive models: one built upon the long-short term memory (LSTM) and the other utilizing the gated recurrent unit (GRU). These models are fed with a combination of historical and anticipated air temperature, air moisture, and NOx emissions as inputs to forecast future NOx emissions. Both LSTM and GRU models can capture the intricate pulse patterns… More >

Maryam Bukhari¹, Sadaf Yasmin¹, Sheneela Naz², Mehr Yahya Durrani¹, Mubashir Javaid³, Jihoon Moon⁴, Seungmin Rho^5,*

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 1251-1279, 2023, DOI:10.32604/cmc.2023.040329

Abstract Effective smart healthcare frameworks contain novel and emerging solutions for remote disease diagnostics, which aid in the prevention of several diseases including heart-related abnormalities. In this context, regular monitoring of cardiac patients through smart healthcare systems based on Electrocardiogram (ECG) signals has the potential to save many lives. In existing studies, several heart disease diagnostic systems are proposed by employing different state-of-the-art methods, however, improving such methods is always an intriguing area of research. Hence, in this research, a smart healthcare system is proposed for the diagnosis of heart disease using ECG signals. The proposed framework extracts both linear and… More >

T. M. Nithya^1,*, R. Umanesan², T. Kalavathidevi³, C. Selvarathi⁴, A. Kavitha⁵

Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2537-2547, 2023, DOI:10.32604/iasc.2022.028804

Abstract Big data analytics is a popular research topic due to its applicability in various real time applications. The recent advent of machine learning and deep learning models can be applied to analyze big data with better performance. Since big data involves numerous features and necessitates high computational time, feature selection methodologies using metaheuristic optimization algorithms can be adopted to choose optimum set of features and thereby improves the overall classification performance. This study proposes a new sigmoid butterfly optimization method with an optimum gated recurrent unit (SBOA-OGRU) model for big data classification in Apache Spark. The SBOA-OGRU technique involves the… More >

Leilei Chen^2,3, Haozhi Li^3,4, Lu Meng⁵, Pan Chen³, Pei Li^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.4, pp. 1-2, 2023, DOI:10.32604/icces.2023.010584

Abstract In this paper, a Direct FE² method is proposed to simulate the electromechanical coupling problem of inhomogeneous materials. The theoretical foundation for the proposed method, downscaling and upscaling principles, is the same as that of the FE² method. The two-level simulation in the Direct FE² method may be addressed in an integrative framework where macroscopic and microscopic degrees of freedom (DOFs) are related by multipoint constraints (MPCs) [1]. This critical characteristic permits simple implementation in commercial FE software, eliminating the necessity for recurrent data transfer between two scales [2-4]. The capabilities of Direct FE² are validated using four numerical examples,… More >

Shuo Yang¹, Yongxing Shen^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.4, pp. 1-1, 2023, DOI:10.32604/icces.2023.09207

Abstract Fatigue refers to repeated cyclic loading well below the ultimate failure stress of the structure. It accounts for most mechanical failures, and thus deserves serious consideration in engineering practice. Phase field approach is a powerful tool for fracture simulation, which tracks arbitrary and complicated crack paths without extra criterion. This approach has been widely applied to various cracking problems, such as shell fracture, beam fracture , etc. The phase field approach for fracture has been adapted for fatigue fracture in recent years. Due to the mesh requirement of the phase field approach and the large amount of load steps of… More >

Zhelong He^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.1, pp. 1-1, 2023, DOI:10.32604/icces.2023.010452

Abstract This presentation introduces a concurrent topology and fiber-path optimization for continuous fiber composite under thermos-mechanical loadings. The optimization goal is to minimize the structural compliance of composite with thermos-mechanical coupling while satisfying volume fraction constraint, and ensuring the manufacturability by using continuous fibers and avoiding the appearance of over thin members. Level-set function is utilized to represent both shape boundary and fiber path. The zero isocontour of level-set function is updated using a shape sensitivity analysis for anisotropic composite, and fiber paths in shape are given by level-set functions determined from shape boundary. A level-set-based mesh evolution method is introduced… More >

Zhixian Qi^1,2,*, Shuohe Wang^1,2, Qiang Xue^1,2, Haiting Mi³, Jian Wang^1,2

Energy Engineering, Vol.120, No.9, pp. 2059-2077, 2023, DOI:10.32604/ee.2023.028595

Abstract A current identification method based on optimized variational mode decomposition (VMD) and sample entropy (SampEn) is proposed in order to solve the problem that the main protection of the urban rail transit DC feeder cannot distinguish between train charging current and remote short circuit current. This method uses the principle of energy difference to optimize the optimal mode decomposition number k of VMD; the optimal VMD for DC feeder current is decomposed into the intrinsic modal function (IMF) of different frequency bands. The sample entropy algorithm is used to perform feature extraction of each IMF, and then the eigenvalues of… More >

Zhaoting Liu¹, Jianbo Wu^1,*, Sha He², Xin Rao³, Shiqiang Wang², Shen Wang¹, Wei Wei⁴

Structural Durability & Health Monitoring, Vol.17, No.4, pp. 299-314, 2023, DOI:10.32604/sdhm.2023.022554

Abstract It is known that eddy current effect has a great influence on magnetic flux leakage testing (MFL). Usually, contact-type encoder wheels are used to measure MFL testing speed to evaluate the effect and further compensate testing signals. This speed measurement method is complicated, and inevitable abrasion and occasional slippage will reduce the measurement accuracy. In order to solve this problem, based on eddy current effect due to the relative movement, a speed measurement method is proposed, which is contactless and simple. In the high-speed MFL testing, eddy current induced in the specimen will cause an obvious modification to the applied… More > Graphic Abstract