Lassaad K. Smirani¹, Leila Jamel^2,*, Latifah Almuqren²

CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2024.047551

Abstract This study presents a layered generalization ensemble model for next generation radio mobiles, focusing on supervised channel estimation approaches. Channel estimation typically involves the insertion of pilot symbols with a well-balanced rhythm and suitable layout. The model, called Stacked Generalization for Channel Estimation (SGCE), aims to enhance channel estimation performance by eliminating pilot insertion and improving throughput. The SGCE model incorporates six machine learning methods: random forest (RF), gradient boosting machine (GB), light gradient boosting machine (LGBM), support vector regression (SVR), extremely randomized tree (ERT), and extreme gradient boosting (XGB). By generating meta-data from five models (RF, GB, LGBM, SVR,… More >

Chanho Park¹, Takefumi Ogawa^2,*

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.048901

Abstract Six degrees of freedom (6DoF) input interfaces are essential for manipulating virtual objects through translation or rotation in three-dimensional (3D) space. A traditional outside-in tracking controller requires the installation of expensive hardware in advance. While inside-out tracking controllers have been proposed, they often suffer from limitations such as interaction limited to the tracking range of the sensor (e.g., a sensor on the head-mounted display (HMD)) or the need for pose value modification to function as an input interface (e.g., a sensor on the controller). This study investigates 6DoF pose estimation methods without restricting the tracking range, using a smartphone as… More >

Jun Wang, Changfu Si, Zhen Wang, Qiang Fu^*

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.050223

Abstract Nowadays, with the rapid development of industrial Internet technology, on the one hand, advanced industrial control systems (ICS) have improved industrial production efficiency. However, there are more and more cyberattacks targeting industrial control systems. To ensure the security of industrial networks, intrusion detection systems have been widely used in industrial control systems, and deep neural networks have always been an effective method for identifying cyber attacks. Current intrusion detection methods still suffer from low accuracy and a high false alarm rate. Therefore, it is important to build a more efficient intrusion detection model. This paper proposes a hybrid deep learning… More >

HYUNHO KIM¹, UIJU CHO², SOOK HEE HONG³, HYUNG SOON PARK¹, IN-HO KIM³, HO JUNG AN¹, BYOUNG YONG SHIM¹, JIN HYOUNG KANG^3,*

Oncology Research, Vol., , DOI:10.32604/or.2024.048919

Abstract Background: Apolipoprotein B mRNA editing catalytic polypeptide (APOBEC), an endogenous mutator, induces DNA damage and activates the ataxia telangiectasia and Rad3-related (ATR)-checkpoint kinase 1 (Chk1) pathway. Although cisplatin-based therapy is the mainstay for muscle-invasive bladder cancer (MIBC), it has a poor survival rate. Therefore, this study aimed to evaluate the efficacy of an ATR inhibitor combined with cisplatin in the treatment of APOBEC catalytic subunit 3B (APOBEC3B) expressing MIBC. Methods: Immunohistochemical staining was performed to analyze an association between APOBEC3B and ATR in patients with MIBC. The APOBEC3B expression in MIBC cell lines was assessed using real-time polymerase chain reaction… More >

LICHEN XU^1,2, PAN ZHANG^3,*, GUIQI ZHANG², ZHAOLIANG SHEN⁴, XIZHUANG BAI^1,3,*

Oncology Research, Vol., , DOI:10.32604/or.2024.047704

Abstract Background: Osteosarcoma (OS), recognized as the predominant malignant tumor originating from bones, necessitates an in-depth comprehension of its intrinsic mechanisms to pinpoint novel therapeutic targets and enhance treatment methodologies. The role of fat mass and obesity-associated (FTO) in OS, particularly its correlation with malignant traits, and the fundamental mechanism, remains to be elucidated. Materials and Methods: 1. The FTO expression and survival rate in tumors were analyzed. 2. FTO in OS cell lines was quantified utilizing western blot and PCR. 3. FTO was upregulated and downregulated separately in MG63. 4. The impact of FTO on the proliferation and migration of… More >

Bairu Li¹, Jingyu Jia¹, Hemin Wang¹, Jiaju Sun¹, Enyan Chen¹, Xin Li^1,2,3,*

Phyton-International Journal of Experimental Botany, Vol., , DOI:10.32604/phyton.2024.050450

Abstract Trypsin, a novel superoxide scavenger, significantly enhances the storage quality of Hylocereus undatus (H. undatus). To elucidate the preservation mechanism of trypsin on H. undatus, a widely targeted metabolomic analysis, and transcriptomics analysis were conducted. Firstly, a total of 453 metabolites were identified, with organic acids and their derivatives constituting the largest proportion (25%). Amino acids and their metabolites, prominent among organic acids, were further analyzed. Among them, 73 metabolites were associated with amino acids, and 37 exhibited significant differences. The most enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway was arginine biosynthesis (map00220), with polyamine metabolites showing the… More >

Alexis Salazar-Navarro¹, Victor Ruiz-Valdiviezo², Jose Joya-Dávila³, Daniel Gonzalez-Mendoza^1,*

Phyton-International Journal of Experimental Botany, Vol., , DOI:10.32604/phyton.2024.049612

Abstract Coffee Leaf Rust (CLR) is caused by Hemileia vastatrix in Coffea spp. It is one of the most dangerous phytopathogens for coffee plantations in terms of coffee productivity and coffee cup quality. In this review, we resume the problem of CLR in Mexico and the pathogenesis of H. vastatrix. The review abord plant-pathogen interactions which lead a compatible or incompatible interactions and result in CLR disease or resistance, respectively. The review abord Coffea spp. defense response pathways involved in H. vastatrix pathogenicity. Additionally, current measures to control H. vastatrix proliferation and germination were aborded focused on phytosanitary actions, and biological… More >

Xin Yin^1,#, Shuai Wang^1,#, Chunguang Wang¹, Haichao Wang², Zheying Zong^1,3,*, Zeyu Ban¹

Phyton-International Journal of Experimental Botany, Vol., , DOI:10.32604/phyton.2024.049114

Abstract This study employed the bibliometric software CiteSpace 6.1.R6 to analyze the correlation between thermal infrared, spectral remote sensing technology, and the estimation of economic forest water stress. It aimed to review the development and current status of this field, as well as to identify future research trends. A search was conducted on the China National Knowledge Infrastructure (CNKI) database using the keyword “water stress” for relevant studies from 2003 to 2023. The visual analysis function of CNKI was used to generate the distribution of annual publication volume, and CiteSpace 6.1.R6 was utilized to create network maps illustrating collaboration among authors… More >

Xiaolu Qin^1,3, Xinyu Li^1,3, Yi Yang², Mei Huang², Shengli Wu¹, Pianchou Gongpan¹, Lianzhang Wu², Juncai He², Changan Geng^1,3,*

Phyton-International Journal of Experimental Botany, Vol., , DOI:10.32604/phyton.2024.048192

Abstract The fruits of Amomum tsao-ko (Cao-Guo) were documented in Chinese Pharmacopoeia for the treatment of abdominal pain, vomiting, and plague. In our previous study, a series of diarylheptanes and flavonoids with α-glucosidase and protein tyrosine phosphatase 1B (PTP1B) inhibitory activity have been reported from the middle-polarity part of A. tsao-ko, whereas the antidiabetic potency of the low-polarity constituents is still unclear. In this study, three new hydroxytetradecenals, (2E, 4E, 8Z, 11Z)-6R-hydroxytetradeca-2,4,8,11-tetraenal (1), (2E, 4E, 8Z)-6R-hydroxytetradeca-2,4,8-trienal (2) and (2E, 4E)-6R-hydroxytetradeca-2,4-dienal (3) were obtained from the volatile oils of A. tsao-ko. The structures of compounds 1–3 were determined using spectroscopic data involving… 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., , 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 the automated segmentation of brain… More > Graphic Abstract