Silvia C. Ramírez-Rodríguez¹, Pablo Preciado-Rangel¹, Marcelino Cabrera-De La Fuente², Susana González-Morales², Hortensia Ortega-Ortiz^3,*

Phyton-International Journal of Experimental Botany, Vol., , DOI:10.32604/phyton.2024.048096

Abstract

Biodegradable nanoparticles such as chitosan nanoparticles (CSNPs) are used in sustainable agriculture since they avoid damage to the environment; CSNPs have positive effects such as the accumulation of bioactive compounds and increased productivity in plants. This study aimed to investigate the impact of applying CSNPs on lettuce, specifically focusing on enzymatic activity, bioactive compounds, and yield. The trial was conducted using a completely randomized design, incorporating CSNPs: 0, 0.05, 0.1, 0.2, 0.4, and 0.8 mg mL⁻¹. The doses of 0.4 mg mL⁻¹ improve yields up to 24.6% increases and 0.1 mg mL⁻¹ of CSNPs increases total phenols by 31.2% and… More >

Chuandong Qin^1,2, Yu Cao^1,*, Liqun Meng¹

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.049228

Abstract Brain tumors come in various types, each with distinct characteristics and treatment approaches, making manual detection a time-consuming and potentially ambiguous process. Brain tumor detection is a valuable tool for gaining a deeper understanding of tumors and improving treatment outcomes. Machine learning models have become key players in automating brain tumor detection. Gradient descent methods are the mainstream algorithms for solving machine learning models. In this paper, we propose a novel distributed proximal stochastic gradient descent approach to solve the L₁-Smooth Support Vector Machine (SVM) classifier for brain tumor detection. Firstly, the smooth hinge loss is introduced to be used… More >

Amal Hkiri^1,*, Hamzah Faraj², Omar Ben Bahri², Mouna Karmani¹, Sami Alqurashi², Mohsen Machhout¹

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.049207

Abstract The Internet of Things (IoT) has witnessed a significant surge in adoption, particularly through the utilization of Wireless Sensor Networks (WSNs), which comprise small internet-connected devices. These deployments span various environments and offer a multitude of benefits. However, the widespread use of battery-powered devices introduces challenges due to their limited hardware resources and communication capabilities. In response to this, the Internet Engineering Task Force (IETF) has developed the IPv6 Routing Protocol for Low-power and Lossy Networks (RPL) to address the unique requirements of such networks. Recognizing the critical role of RPL in maintaining high performance, this paper proposes a novel… More >

Zhijun Guo¹, Yun Sun^2,*, Ying Wang¹, Chaoqi Fu³, Jilong Zhong^4,*

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.048112

Abstract Due to the time-varying topology and possible disturbances in a conflict environment, it is still challenging to maintain the mission performance of flying Ad hoc networks (FANET), which limits the application of Unmanned Aerial Vehicle (UAV) swarms in harsh environments. This paper proposes an intelligent framework to quickly recover the cooperative coverage mission by aggregating the historical spatio-temporal network with the attention mechanism. The mission resilience metric is introduced in conjunction with connectivity and coverage status information to simplify the optimization model. A spatio-temporal node pooling method is proposed to ensure all node location features can be updated after destruction… More >

Zhigao Zeng^1,2, Aoting Tang^1,2, Shengqiu Yi^1,2, Xinpan Yuan^1,2, Yanhui Zhu^1,2,*

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.047989

Abstract Radiomics is a non-invasive method for extracting quantitative and higher-dimensional features from medical images for diagnosis. It has received great attention due to its huge application prospects in recent years. We can know that the number of features selected by the existing radiomics feature selection methods is basically about ten. In this paper, a heuristic feature selection method based on frequency iteration and multiple supervised training mode is proposed. Based on the combination between features, it decomposes all features layer by layer to select the optimal features for each layer, then fuses the optimal features to form a local optimal… More >

K. Umapathi^1,*, S. Shobana¹, Anand Nayyar², Judith Justin³, R. Vanithamani³, Miguel Villagómez Galindo⁴, Mushtaq Ahmad Ansari⁵, Hitesh Panchal^6,*

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.047961

Abstract Breast cancer detection heavily relies on medical imaging, particularly ultrasound, for early diagnosis and effective treatment. This research addresses the challenges associated with computer-aided diagnosis (CAD) of breast cancer from ultrasound images. The primary challenge is accurately distinguishing between malignant and benign tumors, complicated by factors such as speckle noise, variable image quality, and the need for precise segmentation and classification. The main objective of the research paper is to develop an advanced methodology for breast ultrasound image classification, focusing on speckle noise reduction, precise segmentation, feature extraction, and machine learning-based classification. A unique approach is introduced that combines Enhanced… More >

Han Zhou^1,2, Hongtao Xu^1,2, Xinyue Chang^1,2, Wei Zhang^1,2, Heng Dong^1,2,*

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.047754

Abstract Many deep learning-based registration methods rely on a single-stream encoder-decoder network for computing deformation fields between 3D volumes. However, these methods often lack constraint information and overlook semantic consistency, limiting their performance. To address these issues, we present a novel approach for medical image registration called the Dual-VoxelMorph, featuring a dual-channel cross-constraint network. This innovative network utilizes both intensity and segmentation images, which share identical semantic information and feature representations. Two encoder-decoder structures calculate deformation fields for intensity and segmentation images, as generated by the dual-channel cross-constraint network. This design facilitates bidirectional communication between grayscale and segmentation information, enabling the… More >

YU-YAN LAN^1,#, TSUN-CHIH CHENG^2,#, YI-PING LEE³, CHIA-YIH WANG^3,*, BU-MIIN HUANG^3,4,*

BIOCELL, Vol., , DOI:10.32604/biocell.2024.050701

Abstract Background: Paclitaxel is a compound derived from Pacific yew bark that induces various cancer cell apoptosis. However, whether it also has anticancer activities in KOSC3 cells, an oral cancer cell line, is unclear. Methods: 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide, flow cytometry, and western blotting assays were carried out to assess cell viability, subG1 phase of the cell cycle, and apoptosis-related protein expression, respectively. Results: Our findings indicate that paclitaxel could inhibit cell viability and increase the expression of apoptotic markers, including plasma membrane blebbing and the cleavage of poly ADP-ribose polymerase in KOSC3 cells. Also, the treatment with paclitaxel remarkably elevated the percentage… More > Graphic Abstract

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., , 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 decreased pathological bacteria decreased gut… More >

YI HU^1,#, ZHONGYANG REN^2,#, ZHENGZHONG ZHAO¹, YONGJIA HUANG³, WANTING HUANG³, JIE LIU^3,*, LING DING^3,*

BIOCELL, Vol., , DOI:10.32604/biocell.2024.049140

Abstract Background: Acute pancreatitis (AP), known for its rapid onset and significant incidence and mortality rates, presents a clinical challenge due to the limited availability of effective treatments and preventive measures. Anemarsaponin B (ASB) has emerged as a potential therapeutic agent, demonstrating capabilities in reducing immune inflammation, positioning it as a promising candidate for AP treatment. Methods: We investigated the effects of ASB on AP in mice, induced by caerulein and lipopolysaccharide (LPS). Peripheral blood samples were collected 24 h post-induction with caerulein to assess of key biomarkers including lipase, amylase, TNF-α, IL-1β, IL-6, SOD, and GSH-Px. A range of techniques… More >