MIN SHEN^1,2, XIAOMAN XU^1,2, GUANGLING SUN¹, LIANGZHU WANG¹, TAO YING¹, HANG SU¹, WEI WANG¹, QINGHUA CAO^1,*, ZHEZHE SUN^1,*

BIOCELL, Vol.48, No.3, pp. 491-499, 2024, DOI:10.32604/biocell.2023.047640

Abstract Objective: Circular RNAs (circRNAs) have been shown to involve in pathological processes of ischemic stroke (IS), including autophagy. This study was designed to explore the effect of circR-ZC3HC1 on neuronal autophagy in IS and the related mechanisms. Methods: Expression of circR-ZC3HC1 in blood samples of IS patients and healthy controls was detected. Hippocampal neurons were treated with oxygen and glucose deprivation (OGD) to establish IS in vitro model. The expression of LC3 and p62 and the number of autophagosomes were examined to evaluate the autophagy level of OGD induced neurons using western blotting and transmission electron microscope. Cell apoptosis rate… More >

Congjun Rao¹, Mengxi Li¹, Tingting Huang^2,*, Feiyu Li¹

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 699-724, 2024, DOI:10.32604/cmes.2023.044898

Abstract Stroke is a chronic cerebrovascular disease that carries a high risk. Stroke risk assessment is of great significance in preventing, reversing and reducing the spread and the health hazards caused by stroke. Aiming to objectively predict and identify strokes, this paper proposes a new stroke risk assessment decision-making model named Logistic-AdaBoost (Logistic-AB) based on machine learning. First, the categorical boosting (CatBoost) method is used to perform feature selection for all features of stroke, and 8 main features are selected to form a new index evaluation system to predict the risk of stroke. Second, the borderline synthetic minority oversampling technique (SMOTE)… More >

Zuo-Hua Li¹, Qing-Gui Wu^1,*, Jun Teng^1,*, Chao-Jun Chen^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 865-884, 2024, DOI:10.32604/cmes.2023.029927

Abstract Collisions between a moving mass and an anti-collision device increase structural responses and threaten structural safety. An active mass damper (AMD) with stroke limitations is often used to avoid collisions. However, a stroke-limited AMD control system with a fixed limited area shortens the available AMD stroke and leads to significant control power. To solve this problem, the design approach with variable gain and limited area (VGLA) is proposed in this study. First, the boundary of variable-limited areas is calculated based on the real-time status of the moving mass. The variable gain (VG) expression at the variable limited area is deduced… More >

Qi Liu¹, Zihao Wu^1,*, Xiaodong Liu²

Journal on Internet of Things, Vol.4, No.3, pp. 169-181, 2022, DOI:10.32604/jiot.2022.040368

Abstract This study proposed a lightweight but high-performance convolution network for accurately classifying five upper limb movements of arm, involving forearm flexion and rotation, arm extension, lumbar touch and no reaction state, aiming to monitoring patient’s rehabilitation process and assist the therapist in elevating patient compliance with treatment. To achieve this goal, a lightweight convolution neural network TMCA-Net (Time Multiscale Channel Attention Convolutional Neural Network) is designed, which combines attention mechanism, uses multi-branched convolution structure to automatically extract feature information at different scales from sensor data, and filters feature information based on attention mechanism. In particular, channel separation convolution is used… More >

Mesfer Al Duhayyim^1,*, Sidra Abbas^2,*, Abdullah Al Hejaili³, Natalia Kryvinska⁴, Ahmad Almadhor⁵, Uzma Ghulam Mohammad⁶

Computer Systems Science and Engineering, Vol.47, No.1, pp. 413-429, 2023, DOI:10.32604/csse.2023.037127

Abstract Stroke is a life-threatening disease usually due to blockage of blood or insufficient blood flow to the brain. It has a tremendous impact on every aspect of life since it is the leading global factor of disability and morbidity. Strokes can range from minor to severe (extensive). Thus, early stroke assessment and treatment can enhance survival rates. Manual prediction is extremely time and resource intensive. Automated prediction methods such as Modern Information and Communication Technologies (ICTs), particularly those in Machine Learning (ML) area, are crucial for the early diagnosis and prognosis of stroke. Therefore, this research proposed an ensemble voting… More >

LUOJUN ZHENG, LUAN WENG, DIWEN SHOU^*

BIOCELL, Vol.47, No.6, pp. 1345-1352, 2023, DOI:10.32604/biocell.2023.028866

Abstract Background: Ischemic stroke is characterized by permanent or transient obstruction of blood flow, leading to a growing risk factor and health burden. Tianmagouteng yin (TMG) is commonly used in Chinese medicine to treat cerebral ischemia. The aim of this study was to investigate the neuroprotective effects of TMG against ischemic stroke. Methods: Either permanent middle cerebral artery occlusion (pMCAO) or sham operation was performed on anesthetized Wistar male rats (n = 36). Results: Results demonstrated that TMG administration reduced the infarction volume and mitigated the neurobehavioral deficits. Hematoxylin and eosin (HE) staining and Prussian blue staining revealed that TMG attenuated… More >

Hussein Al-Gburi^*, Doaa Fadhil Kareem, Malik N. Hawas

Frontiers in Heat and Mass Transfer, Vol.18, pp. 1-6, 2022, DOI:10.5098/hmt.18.28

Abstract In this article, an investigational analysis has been conducted to explore the effect of biodiesel fuel blends on characteristics of engine and releases (CO2, CO, HCl, and NOx) of single-cylinder, four strokes at the variable biodiesel concentration. The releases of gases and the engine's characteristics were measured at six blending biofuels and six-speed conditions and constant load. The blending proportions of biodiesel with diesel fuel-based by volume were at 0% pure diesel, 5%, 10%, 15%, 20%, and 25%. This investigation aims to assess the biodiesel fuel mixture's impact on the CI engine performance in terms of its Bsfc, Ƞbth, and… More >

Azhar Tursynova¹, Batyrkhan Omarov^1,2, Natalya Tukenova^3,*, Indira Salgozha⁴, Onergul Khaaval³, Rinat Ramazanov⁵, Bagdat Ospanov⁵

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1431-1446, 2023, DOI:10.32604/cmc.2023.034400

Abstract In the field of stroke imaging, deep learning (DL) has enormous untapped potential. When clinically significant symptoms of a cerebral stroke are detected, it is crucial to make an urgent diagnosis using available imaging techniques such as computed tomography (CT) scans. The purpose of this work is to classify brain CT images as normal, surviving ischemia or cerebral hemorrhage based on the convolutional neural network (CNN) model. In this study, we propose a computer-aided diagnostic system (CAD) for categorizing cerebral strokes using computed tomography images. Horizontal flip data magnification techniques were used to obtain more accurate categorization. Image Data Generator… More >

Yuqi He^1,2,3, Shirui Shao¹, Gusztáv Fekete³, Xiaoyi Yang¹, Xuanzhen Cen^1,4, Yang Song^1,4, Dong Sun^1,*, Yaodong Gu^1,*

Molecular & Cellular Biomechanics, Vol.19, No.4, pp. 221-235, 2022, DOI:10.32604/mcb.2022.027285

Abstract Introduction: Footwork is one of the training contents that table tennis players and coaches focus on. This study aimed to gain a thorough understanding of the muscle activity of the table tennis footwork and creating a musculoskeletal model to investigate the muscle forces, joint kinematic, and joint kinetic characteristics of the footwork during topspin forehand stroke. Methods: Six male table tennis athletes (height: 171.98 ± 4.97 cm; weight: 68.77 ± 7.86 kg; experience: 10.67 ± 1.86 years; age: 22.50 ± 1.64 years) performed chasse step and one-step footwork to return the ball from the coach by topspin forehand stroke. The… More >

Shakunthala Masi^*, Helenprabha Kuttiappan

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 733-744, 2023, DOI:10.32604/iasc.2023.025919

Abstract In medical science for envisaging human body’s phenomenal structure a major part has been driven by image processing techniques. Major objective of this work is to detect of cerebral atherosclerosis for image segmentation application. Detection of some abnormal structures in human body has become a difficult task to complete with some simple images. For expounding and distinguishing neural architecture of human brain in an effective manner, MRI (Magnetic Resonance Imaging) is one of the most suitable and significant technique. Here we work on detection of Cerebral Atherosclerosis from MRI images of patients. Cerebral Atherosclerosis is a cerebral vascular disease causes… More >