Oncology Research Editorial Office

Oncology Research, Vol.32, No.8, pp. 1387-1387, 2024, DOI:10.32604/or.2024.055039

Abstract This article has no abstract. More >

Oncology Research Editorial Office

Oncology Research, Vol.32, No.8, pp. 1383-1383, 2024, DOI:10.32604/or.2024.055036

Abstract This article has no abstract. More >

Oncology Research Editorial Office

Oncology Research, Vol.32, No.8, pp. 1381-1381, 2024, DOI:10.32604/or.2024.055035

Abstract This article has no abstract. More >

Tengda Li, Gang Wang, Qiang Fu^*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2559-2586, 2024, DOI:10.32604/cmes.2024.052039

Abstract Aiming at the problems of low solution accuracy and high decision pressure when facing large-scale dynamic task allocation (DTA) and high-dimensional decision space with single agent, this paper combines the deep reinforcement learning (DRL) theory and an improved Multi-Agent Deep Deterministic Policy Gradient (MADDPG-D2) algorithm with a dual experience replay pool and a dual noise based on multi-agent architecture is proposed to improve the efficiency of DTA. The algorithm is based on the traditional Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm, and considers the introduction of a double noise mechanism to increase the action exploration… More >

Hao Chen^#, Runfeng Xie^#, Xiangyang Cui, Zhou Yan, Xin Wang, Zhanwei Xuan^*, Kai Zhang^*

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4283-4296, 2024, DOI:10.32604/cmc.2024.049129

Abstract Accurately recommending candidate news to users is a basic challenge of personalized news recommendation systems. Traditional methods are usually difficult to learn and acquire complex semantic information in news texts, resulting in unsatisfactory recommendation results. Besides, these traditional methods are more friendly to active users with rich historical behaviors. However, they can not effectively solve the long tail problem of inactive users. To address these issues, this research presents a novel general framework that combines Large Language Models (LLM) and Knowledge Graphs (KG) into traditional methods. To learn the contextual information of news text, we… More >

Nidhika Chauhan¹, Navneet Kaur², Kamaljit Singh Saini³, Sahil Verma³, Kavita³, Ruba Abu Khurma^4,5, Pedro A. Castillo^6,*

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3757-3782, 2024, DOI:10.32604/cmc.2024.046516

Abstract Cloud computing is a dynamic and rapidly evolving field, where the demand for resources fluctuates continuously. This paper delves into the imperative need for adaptability in the allocation of resources to applications and services within cloud computing environments. The motivation stems from the pressing issue of accommodating fluctuating levels of user demand efficiently. By adhering to the proposed resource allocation method, we aim to achieve a substantial reduction in energy consumption. This reduction hinges on the precise and efficient allocation of resources to the tasks that require those most, aligning with the broader goal of… More >

Maie Aboghazalah^1,*, Passent El-kafrawy², Abdelmoty M. Ahmed³, Rasha Elnemr⁵, Belgacem Bouallegue³, Ayman El-sayed⁴

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3855-3875, 2024, DOI:10.32604/cmc.2023.039936

Abstract Heart monitoring improves life quality. Electrocardiograms (ECGs or EKGs) detect heart irregularities. Machine learning algorithms can create a few ECG diagnosis processing methods. The first method uses raw ECG and time-series data. The second method classifies the ECG by patient experience. The third technique translates ECG impulses into Q waves, R waves and S waves (QRS) features using richer information. Because ECG signals vary naturally between humans and activities, we will combine the three feature selection methods to improve classification accuracy and diagnosis. Classifications using all three approaches have not been examined till now. Several More >

Quan Zhou^*, Haiyang Li

Energy Engineering, Vol.121, No.7, pp. 1781-1803, 2024, DOI:10.32604/ee.2024.049387

Abstract Renewable energy is becoming more attractive as traditional fossil fuels are rapidly depleted and expensive, and their use would release pollutants. Power systems that use both wind and solar energy are more reliable and efficient than those that utilize only one energy. Hybrid renewable energy systems (HRES) are viable for remote areas operating in standalone mode. This paper aims to present the state-of-the-art research on off-grid solar-wind hybrid energy systems over the last two decades. More than 1500 published articles extracted from the Web of Science are analyzed by bibliometric methods and processed by CiteSpace… More >

Yanhua Li^*1, Xia Chen^†1, Hong Lu^*

Oncology Research, Vol.24, No.6, pp. 511-519, 2016, DOI:10.3727/096504016X14719078133483

Abstract The gene solute carrier family 34 (sodium phosphate), member 2 (SLC34A2), is a member of the SLC34 family. Increasing evidence suggests that SLC34A2 is involved in the development of many human carcinomas. However, its role in hepatocellular carcinoma (HCC) is still unclear. Therefore, in this study we investigated the role of SLC34A2 in HCC and explored the underlying mechanism. We found that the expression of SLC34A2 is upregulated in HCC cell lines. Knockdown of SLC34A2 obviously inhibited HCC cell proliferation, migration/invasion, and the epithelial–mesenchymal transition (EMT) phenotype. Furthermore, knockdown of SLC34A2 significantly inhibited the expression More >

Xue-fei Jin, Hai Li, Shi Zong, Hong-yan Li

Oncology Research, Vol.24, No.6, pp. 477-485, 2016, DOI:10.3727/096504016X14685034103716

Abstract Collagen triple helix repeat containing-1 (CTHRC1), a secreted glycoprotein, is frequently upregulated in human cancers. However, the functional role of CTHRC1 in renal cell carcinoma (RCC) remains unclear. Thus, the aim of this study was to explore the role of CTHRC1 in RCC. Our results demonstrated that CTHRC1 was upregulated in RCC tissues and cell lines. Knockdown of CTHRC1 significantly inhibits the proliferation in RCCs. Furthermore, knockdown of CTHRC1 significantly inhibited the epithelial-to-mesenchymal transition (EMT) process in RCCs, as well as suppressed RCC cell migration and invasion. Mechanistically, knockdown of CTHRC1 inhibited the expression of More >