Bing Li^1,2,*, Liangyu Wang¹, Xia Liu^1,2, Hongbin Fan¹, Bo Wang³, Shoudi Tong¹

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1543-1561, 2024, DOI:10.32604/cmc.2024.052009

Abstract Nuclear magnetic resonance imaging of breasts often presents complex backgrounds. Breast tumors exhibit varying sizes, uneven intensity, and indistinct boundaries. These characteristics can lead to challenges such as low accuracy and incorrect segmentation during tumor segmentation. Thus, we propose a two-stage breast tumor segmentation method leveraging multi-scale features and boundary attention mechanisms. Initially, the breast region of interest is extracted to isolate the breast area from surrounding tissues and organs. Subsequently, we devise a fusion network incorporating multi-scale features and boundary attention mechanisms for breast tumor segmentation. We incorporate multi-scale parallel dilated convolution modules into… More >

Ponusa Songtipya^1,2,*, Thummanoon Prodpran^1,2, Ladawan Songtipya^1,2, Theerarat Sengsuk¹

Journal of Renewable Materials, Vol.12, No.5, pp. 951-967, 2024, DOI:10.32604/jrm.2024.049068

Abstract The synergistic effect of organoclay (OC) and zinc oxide (ZnO) nanoparticles on the crucial properties of poly(lactic acid) (PLA) nanocomposite films was systematically investigated herein. After their incorporation into PLA via the solvent casting technique, the water vapor barrier property of the PLA/OC/ZnO film improved by a maximum of 86% compared to the neat PLA film without the deterioration of Young’s modulus or the tensile strength. Moreover, the film’s self-antibacterial activity against foodborne pathogens, including gram-negative (Escherichia coli, E. coli) and gram-positive (Staphylococcus aureus, S. aureus) bacteria, was enhanced by a maximum of approximately 98–99% compared to the neat… More > Graphic Abstract

Haoping Yao¹, Xinyu Zhong², Chunxia He^1,*

Journal of Renewable Materials, Vol.12, No.5, pp. 993-1006, 2024, DOI:10.32604/jrm.2024.047758

Abstract To make full use of plant shell fibers (rice husk, walnut shell, chestnut shell), three kinds of wood-plastic composites of plant shell fibers and polyvinyl chloride (PVC) were prepared. X-ray diffraction analysis was carried out on three kinds of plant shell fibers to test their crystallinity. The aging process of the composites was conducted under 2 different conditions. One was artificial seawater immersion and xenon lamp irradiation, and the other one was deionized water spray and xenon lamp irradiation. The mechanical properties (tensile strength, flexural strength, impact strength), changes in color, water absorption, Fourier transform… More >

Mian Muhammad Danyal^1,2, Sarwar Shah Khan^3,4,*, Rahim Shah Khan⁵, Saifullah Jan², Naeem ur Rahman⁶

Journal of Intelligent Medicine and Healthcare, Vol.2, pp. 35-53, 2024, DOI:10.32604/jimh.2024.051340

Abstract Multi-modality medical images are essential in healthcare as they provide valuable insights for disease diagnosis and treatment. To harness the complementary data provided by various modalities, these images are amalgamated to create a single, more informative image. This fusion process enhances the overall quality and comprehensiveness of the medical imagery, aiding healthcare professionals in making accurate diagnoses and informed treatment decisions. In this study, we propose a new hybrid pre-processing approach, Laplacian Filter + Discrete Fourier Transform (LF+DFT), to enhance medical images before fusion. The LF+DFT approach highlights key details, captures small information, and sharpens… More >

Md. Atiqur Rahman¹, Mustavi Ibne Masum¹, Khan Md Hasib², M. F. Mridha^3,*, Sultan Alfarhood⁴, Mejdl Safran^4,*, Dunren Che⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2425-2448, 2024, DOI:10.32604/cmes.2024.050760

Abstract Brain tumors pose a significant threat to human lives and have gained increasing attention as the tenth leading cause of global mortality. This study addresses the pressing issue of brain tumor classification using Magnetic resonance imaging (MRI). It focuses on distinguishing between Low-Grade Gliomas (LGG) and High-Grade Gliomas (HGG). LGGs are benign and typically manageable with surgical resection, while HGGs are malignant and more aggressive. The research introduces an innovative custom convolutional neural network (CNN) model, Glioma-CNN. GliomaCNN stands out as a lightweight CNN model compared to its predecessors. The research utilized the BraTS 2020 More >

Madiha Hameed^1,3, Aneela Zameer^1,*, Muhammad Asif Zahoor Raja²

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2131-2164, 2024, DOI:10.32604/cmes.2024.050124

Abstract The International Skin Imaging Collaboration (ISIC) datasets are pivotal resources for researchers in machine learning for medical image analysis, especially in skin cancer detection. These datasets contain tens of thousands of dermoscopic photographs, each accompanied by gold-standard lesion diagnosis metadata. Annual challenges associated with ISIC datasets have spurred significant advancements, with research papers reporting metrics surpassing those of human experts. Skin cancers are categorized into melanoma and non-melanoma types, with melanoma posing a greater threat due to its rapid potential for metastasis if left untreated. This paper aims to address challenges in skin cancer detection… More >

Yuan Tian, Lulu Zhi, Ping Li^*, Xiangyang Hu^*

Phyton-International Journal of Experimental Botany, Vol.93, No.6, pp. 1101-1116, 2024, DOI:10.32604/phyton.2024.050220

Abstract Seed viability is an essential feature for genetic resource conservation as well as sustainable crop production. Long-term storage induces seed viability deterioration or seed aging, accompanied by the accumulation of toxic reactive oxygen species (ROS) to suppress seed germination. Controlled deterioration treatment (CDT) is a general approach for mimicking seed aging. The transcription factor ANAC089 was previously reported to modulate seed primary germination. In this study, we evaluated the ability of ANAC089 to control seed viability during aging. Compared with that in the wild-type line, the mutation of ANAC089 significantly increased HO, thereby reducing seed viability after… More >

YUANYUAN LIAO^1,2,3, XINSI LI^2,3, QIAN LI^2,3, YIZHONG WANG⁴, XIUJUN TAN^1,2,3, TING GONG^2,3,5,*

BIOCELL, Vol.48, No.6, pp. 873-887, 2024, DOI:10.32604/biocell.2024.050324

Abstract As we are facing an aging society, anti-aging strategies have been pursued to reduce the negative impacts of aging and increase the health span of human beings. Gut microbiota has become a key factor in the anti-aging process. Modulation of gut microbiota by fecal microbiota transplantation (FMT) to prevent frailty and unhealthy aging has been a hot topic of research. This narrative review summarizes the benefits of FMT for health span and lifespan, brains, eyes, productive systems, bones, and others. The mechanisms of FMT in improving healthy aging are discussed. The increased beneficial bacteria and More >

Samar M. Alqhtani¹, Toufique A. Soomro^2,*, Faisal Bin Ubaid³, Ahmed Ali⁴, Muhammad Irfan⁵, Abdullah A. Asiri⁶

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1539-1562, 2024, DOI:10.32604/cmes.2024.051475

Abstract Cancer-related to the nervous system and brain tumors is a leading cause of mortality in various countries. Magnetic resonance imaging (MRI) and computed tomography (CT) are utilized to capture brain images. MRI plays a crucial role in the diagnosis of brain tumors and the examination of other brain disorders. Typically, manual assessment of MRI images by radiologists or experts is performed to identify brain tumors and abnormalities in the early stages for timely intervention. However, early diagnosis of brain tumors is intricate, necessitating the use of computerized methods. This research introduces an innovative approach for… More > Graphic Abstract

Mozamel M. Saeed^*

Intelligent Automation & Soft Computing, Vol.39, No.2, pp. 213-231, 2024, DOI:10.32604/iasc.2024.043020

Abstract The study aims to recognize how efficiently Educational Data Mining (EDM) integrates into Artificial Intelligence (AI) to develop skills for predicting students’ performance. The study used a survey questionnaire and collected data from 300 undergraduate students of Al Neelain University. The first step’s initial population placements were created using Particle Swarm Optimization (PSO). Then, using adaptive feature space search, Educational Grey Wolf Optimization (EGWO) was employed to choose the optimal attribute combination. The second stage uses the SVM classifier to forecast classification accuracy. Different classifiers were utilized to evaluate the performance of students. According to… More >