Xiang Kan¹, Yan Li², Tian Li^1,*, Jiye Zhang¹

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.5, pp. 1075-1091, 2024, DOI:10.32604/fdmp.2023.044050

Abstract A pantograph serves as a vital device for the collection of electricity in trains. However, its aerodynamic resistance can limit the train’s running speed. As installing fairings around the pantograph is known to effectively reduce the resistance, in this study, different fairing lengths are considered and the related aerodynamic performances of pantograph are assessed. In particular, this is accomplished through numerical simulations based on the k-ω Shear Stress Transport (SST) two-equation turbulence model. The results indicate that the fairing diminishes the direct impact of high-speed airflow on the pantograph, thereby reducing its aerodynamic resistance. However, it More >

Ping Chen^*, Qing Jin^*, Qiang Fu^*, Peidong You^*, Xi Jiang^*, Qin Yuan^*, Huifang Huang^†

Oncology Research, Vol.24, No.4, pp. 215-223, 2016, DOI:10.3727/096504016X14634208143021

Abstract This study aimed to investigate the role of the PI3K/Akt signaling pathway in multidrug resistance of acute myeloid leukemia (AML) cells induced by cocultured stromal cells. Human AML cell lines HL-60 and U937 were adhesion cocultured with human bone marrow stromal cell line HS-5 cells. Such coculturing induced HL-60 and U937 cells resistant to chemotherapeutic drugs including daunorubicin (DNR), homoharringtonine (HHT), and cytosine arabinoside (Ara-C). The coculturing-induced resistance of AML cells to DNR, HHT, and Ara-C can be partially reversed by inhibition of the PI3K/Akt signaling pathway. Clinically, AML patients with a low level of More >

Gangcan Li, Yanping Song, Yunjie Zhang, Hao Wang, Jia Xie

Oncology Research, Vol.24, No.2, pp. 109-116, 2016, DOI:10.3727/096504016X14611963142254

Abstract Acute myeloid leukemia (AML) is the most lethal hematological malignancy, and the occurrence of chemoresistance prevents the achievement of complete remission following the standard therapy. MicroRNAs have been extensively investigated as critical regulators of hematopoiesis and leukemogenesis, and they represent a promising strategy for AML therapy. In this study, we identified miR-34b as a novel regulator in myeloid proliferation and apoptosis of leukemic cells. We found that miR-34b was developmentally upregulated in plasma and myeloid cells of healthy subjects, while it was significantly reduced in blood samples of patients with AML and AML cell lines.… More >

Annie Im, Ali Amjad, Mounzer Agha, Anastasios Raptis, Jing-Zhou Hou, Rafic Farah, Seah Lim, Alison Sehgal, Kathleen A. Dorritie, Robert L. Redner, Brian McLaughlin, Yongli Shuai, Shrina Duggal, Michael Boyiadzis

Oncology Research, Vol.24, No.2, pp. 73-80, 2016, DOI:10.3727/096504016X14586627440156

Abstract Relapsed acute myeloid leukemia (AML) represents a major therapeutic challenge. Achieving complete remission (CR) with salvage chemotherapy is the first goal of therapy for relapsed AML. However, there is no standard salvage chemotherapy. The current study evaluated outcomes and prognostic factors for achievement of CR in 91 AML patients in first relapse who were treated with the mitoxantrone–etoposide combination regimen. The overall response rate (CR and CRi) was 25%. Factors that were associated with a lower rate of CR included older age, shorter duration of first CR, low hemoglobin, and low platelet count. The median… More >

Yueli Gu^*, Jinchun Si^†, Xichun Xiao^*, Ying Tian^*, Shuo Yang^*

Oncology Research, Vol.25, No.7, pp. 1069-1079, 2017, DOI:10.3727/096504016X14829256525028

Abstract Aberrant expression of microRNA-92a (miR-92a) has been investigated in various cancers. However, the function and mechanism of miR-92a in acute myeloid leukemia (AML) remain to be elucidated. Our data showed that miR-92a was evidently downregulated and methylenetetrahydrofolate dehydrogenase 2 (MTHFD2) was remarkably upregulated in AML cell lines HL-60 and THP-1. Dual luciferase reporter assay revealed that MTHFD2 was a direct target of miR-92a. Gain- and loss-of-function analysis demonstrated that MTHFD2 knockdown or miR-92a overexpression notably inhibited proliferation and promoted apoptosis of AML cell lines. Restoration of MTHFD2 expression reversed proliferation inhibition and apoptosis induction of More >

Yasir Maqsood¹, Syed Muhammad Usman^1,*, Musaed Alhussein², Khursheed Aurangzeb^2,*, Shehzad Khalid³, Muhammad Zubair⁴

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2795-2811, 2024, DOI:10.32604/cmc.2024.049410

Abstract Wheat is a critical crop, extensively consumed worldwide, and its production enhancement is essential to meet escalating demand. The presence of diseases like stem rust, leaf rust, yellow rust, and tan spot significantly diminishes wheat yield, making the early and precise identification of these diseases vital for effective disease management. With advancements in deep learning algorithms, researchers have proposed many methods for the automated detection of disease pathogens; however, accurately detecting multiple disease pathogens simultaneously remains a challenge. This challenge arises due to the scarcity of RGB images for multiple diseases, class imbalance in existing… More >

Saeed Seraj¹, Ali Safaa Sadiq^1,*, Omprakash Kaiwartya¹, Mohammad Aljaidi², Alexandros Konios¹, Mohammed Ali³, Mohammed Abazeed³

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2123-2149, 2024, DOI:10.32604/cmc.2024.048914

Abstract Mobile banking security has witnessed significant R&D attention from both financial institutions and academia. This is due to the growing number of mobile baking applications and their reachability and usefulness to society. However, these applications are also attractive prey for cybercriminals, who use a variety of malware to steal personal banking information. Related literature in mobile banking security requires many permissions that are not necessary for the application’s intended security functionality. In this context, this paper presents a novel efficient permission identification approach for securing mobile banking (MoBShield) to detect and prevent malware. A permission-based… More >

Shalu¹, Twinkle Acharya¹, Dhwanilnath Gharekhan^1,*, Dipak Samal²

Revue Internationale de Géomatique, Vol.33, pp. 111-134, 2024, DOI:10.32604/rig.2024.051788

Abstract Seismic vulnerability modeling plays a crucial role in seismic risk assessment, aiding decision-makers in pinpointing areas and structures most prone to earthquake damage. While machine learning (ML) algorithms and Geographic Information Systems (GIS) have emerged as promising tools for seismic vulnerability modeling, there remains a notable gap in comprehensive geospatial studies focused on India. Previous studies in seismic vulnerability modeling have primarily focused on specific regions or countries, often overlooking the unique challenges and characteristics of India. In this study, we introduce a novel approach to seismic vulnerability modeling, leveraging ML and GIS to address… More >

Sapiah Sakri¹, Shakila Basheer¹, Zuhaira Muhammad Zain¹, Nurul Halimatul Asmak Ismail^2,*, Dua’ Abdellatef Nassar¹, Manal Abdullah Alohali¹, Mais Ayman Alharaki¹

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1157-1185, 2024, DOI:10.32604/cmc.2024.048051

Abstract Background: Sepsis, a potentially fatal inflammatory disease triggered by infection, carries significant health implications worldwide. Timely detection is crucial as sepsis can rapidly escalate if left undetected. Recent advancements in deep learning (DL) offer powerful tools to address this challenge. Aim: Thus, this study proposed a hybrid CNNBDLSTM, a combination of a convolutional neural network (CNN) with a bi-directional long short-term memory (BDLSTM) model to predict sepsis onset. Implementing the proposed model provides a robust framework that capitalizes on the complementary strengths of both architectures, resulting in more accurate and timelier predictions. Method: The sepsis prediction… More >

Shabana Ramzan¹, Yazeed Yasin Ghadi², Hanan Aljuaid³, Aqsa Mahmood^1,*, Basharat Ali⁴

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 183-199, 2024, DOI:10.32604/cmc.2024.047603

Abstract Traditional farming procedures are time-consuming and expensive as based on manual labor. Farmers have no proper knowledge to select which crop is suitable to grow according to the environmental factors and soil characteristics. This is the main reason for the low yield of crops and the economic crisis in the agricultural sector of the different countries. The use of modern technologies such as the Internet of Things (IoT), machine learning, and ensemble learning can facilitate farmers to observe different factors such as soil electrical conductivity (EC), and environmental factors like temperature to improve crop yield.… More >