BIOCELL, Vol.48, Suppl.1, pp. 1-289, 2024

Abstract This article has no abstract. More >

KARAN WADHWA¹, PAYAL CHAUHAN¹, SHOBHIT KUMAR², RAKESH PAHWA^3,*, RAVINDER VERMA⁴, RAJAT GOYAL⁵, GOVIND SINGH¹, ARCHANA SHARMA⁶, NEHA RAO³, DEEPAK KAUSHIK^1,*

Oncology Research, Vol.32, No.5, pp. 877-897, 2024, DOI:10.32604/or.2024.047278

Abstract Background: Glioblastoma multiforme (GBM) is recognized as the most lethal and most highly invasive tumor. The high likelihood of treatment failure arises from the presence of the blood-brain barrier (BBB) and stem cells around GBM, which avert the entry of chemotherapeutic drugs into the tumor mass. Objective: Recently, several researchers have designed novel nanocarrier systems like liposomes, dendrimers, metallic nanoparticles, nanodiamonds, and nanorobot approaches, allowing drugs to infiltrate the BBB more efficiently, opening up innovative avenues to prevail over therapy problems and radiation therapy. Methods: Relevant literature for this manuscript has been collected from a comprehensive and systematic search of… More > Graphic Abstract

Farhad Mortezapour Shiri^1,*, Ehsan Ahmadi², Mohammadreza Rezaee¹, Thinagaran Perumal¹

Journal on Artificial Intelligence, Vol.6, pp. 85-103, 2024, DOI:10.32604/jai.2024.048911

Abstract Automatic detection of student engagement levels from videos, which is a spatio-temporal classification problem is crucial for enhancing the quality of online education. This paper addresses this challenge by proposing four novel hybrid end-to-end deep learning models designed for the automatic detection of student engagement levels in e-learning videos. The evaluation of these models utilizes the DAiSEE dataset, a public repository capturing student affective states in e-learning scenarios. The initial model integrates EfficientNetV2-L with Gated Recurrent Unit (GRU) and attains an accuracy of 61.45%. Subsequently, the second model combines EfficientNetV2-L with bidirectional GRU (Bi-GRU), yielding an accuracy of 61.56%. The… More >

Dawei Ruan¹, Mingwei Hu^1,2,3,4,5,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 821-844, 2024, DOI:10.32604/cmes.2024.048392

Abstract The specialized equipment utilized in long-line tunnel engineering is evolving towards large-scale, multifunctional, and complex orientations. The vibration caused by the high-frequency units during regular operation is supported by the foundation of the units, and the magnitude of vibration and the operating frequency fluctuate in different engineering contexts, leading to variations in the dynamic response of the foundation. The high-frequency units yield significantly diverse outcomes under different startup conditions and times, resulting in failure to meet operational requirements, influencing the normal function of the tunnel, and causing harm to the foundation structure, personnel, and property in severe cases. This article… More >

Zun-Di Huang¹, Zhen-Bin Zhou^1,2,3, Ning Chang¹, Zheng-Wei Chen^2,3,*, Su-Mei Wang^2,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 975-996, 2024, DOI:10.32604/cmes.2024.047664

Abstract The safety and stability of high-speed maglev trains traveling on viaducts in crosswinds critically depend on their aerodynamic characteristics. Therefore, this paper uses an improved delayed detached eddy simulation (IDDES) method to investigate the aerodynamic features of high-speed maglev trains with different marshaling lengths under crosswinds. The effects of marshaling lengths (varying from 3-car to 8-car groups) on the train’s aerodynamic performance, surface pressure, and the flow field surrounding the train were investigated using the three-dimensional unsteady compressible Navier-Stokes (N-S) equations. The results showed that the marshaling lengths had minimal influence on the aerodynamic performance of the head and middle… More > Graphic Abstract

Hung-Hsiang Wang¹, Chih-Ping Chen^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 685-709, 2024, DOI:10.32604/cmes.2024.047630

Abstract This paper presents a new method of using a convolutional neural network (CNN) in machine learning to identify brand consistency by product appearance variation. In Experiment 1, we collected fifty mouse devices from the past thirty-five years from a renowned company to build a dataset consisting of product pictures with pre-defined design features of their appearance and functions. Results show that it is a challenge to distinguish periods for the subtle evolution of the mouse devices with such traditional methods as time series analysis and principal component analysis (PCA). In Experiment 2, we applied deep learning to predict the extent… More >

Wenjun Zhou^1,2, Mingzhi Yang¹, Qian Peng², Yong Peng^1,*, Kui Wang¹, Qiang Xiao¹

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 735-755, 2024, DOI:10.32604/cmes.2024.047258

Abstract The widespread adoption of aluminum alloy electric buses, known for their energy efficiency and eco-friendliness, faces a challenge due to the aluminum frame’s susceptibility to deformation compared to steel. This issue is further exacerbated by the stringent requirements imposed by the flammability and explosiveness of batteries, necessitating robust frame protection. Our study aims to optimize the connectors of aluminum alloy bus frames, emphasizing durability, energy efficiency, and safety. This research delves into Multi-Objective Coordinated Optimization (MCO) techniques for lightweight design in aluminum alloy bus body connectors. Our goal is to enhance lightweighting, reinforce energy absorption, and improve deformation resistance in… More >

Xianghong Cao, Xinyu Wang, Xin Geng^*, Donghui Wu, Houru An

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 385-408, 2024, DOI:10.32604/cmes.2024.046752

Abstract This study proposes a pose estimation-convolutional neural network-bidirectional gated recurrent unit (PSE-CNN-BiGRU) fusion model for human posture recognition to address low accuracy issues in abnormal posture recognition due to the loss of some feature information and the deterioration of comprehensive performance in model detection in complex home environments. Firstly, the deep convolutional network is integrated with the Mediapipe framework to extract high-precision, multi-dimensional information from the key points of the human skeleton, thereby obtaining a human posture feature set. Thereafter, a double-layer BiGRU algorithm is utilized to extract multi-layer, bidirectional temporal features from the human posture feature set, and a… More >

FREDERICK H. SILVER^1,2,*, TANMAY DESHMUKH²

BIOCELL, Vol.48, No.4, pp. 525-540, 2024, DOI:10.32604/biocell.2024.047965

Abstract All tissues in the body are subjected externally to gravity and internally by collagen fibril and cellular retractive forces that create stress and energy equilibrium required for homeostasis. Mechanotransduction involves mechanical work (force through a distance) and energy storage as kinetic and potential energy. This leads to changes in cell mitosis or apoptosis and the synthesis or loss of tissue components. It involves the application of energy directly to cells through integrin-mediated processes, cell-cell connections, stretching of the cell cytoplasm, and activation of the cell nucleus via yes-associated protein (YAP) and transcriptional coactivator with PDZ-motif (TAZ). These processes involve numerous… More >

DANPING ZHU^1,#, GUANGMING LIU^1,#, KUAN FENG¹, SUYUN LI¹, DANDAN HU², SIDA YANG^3,*, PEIQING LI^1,*

BIOCELL, Vol.48, No.4, pp. 653-664, 2024, DOI:10.32604/biocell.2024.044856

Abstract Background: During Enterovirus type 71 (EV71) infection, the structural viral protein 1 (VP1) activates endoplasmic reticulum (ER) stress associated with peripheral myelin protein 22 (PMP22) accumulation and induces autophagy. However, the specific mechanism behind this process remains elusive. Methods: In this research, we used the VP1-overexpressing mouse Schwann cells (SCs) models co-transfected with a PMP22 silencing or Autocrine motility factor receptor (AMFR/gp78) overexpressing vector to explore the regulation of gp78 on PMP22 and its relationship with autophagy and apoptosis. Results: The activity of gp78 could be influenced by EV71-VP1, leading to a decrease in the ubiquitination and degradation of PMP22,… More >