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  • Open Access

    ARTICLE

    Examining the In Vitro Efficacy of the IAP Antagonist Birinapant as a Single Agent or in Combination With Dacarbazine to Induce Melanoma Cell Death

    Vesna Vetma*†‡, Jan Rožanc§, Emilie M. Charles*†, Christian T. Hellwig*†‡¶, Leonidas G. Alexopoulos§#, Markus Rehm*†‡#

    Oncology Research, Vol.25, No.9, pp. 1489-1494, 2017, DOI:10.3727/096504017X14897145996933

    Abstract Antagonists of inhibitors of apoptosis proteins (IAPs), alone or in combination with genotoxic therapeutics, have been shown to efficiently induce cell death in various solid tumors. The IAP antagonist birinapant is currently being tested in phase II clinical trials. We herein aimed to investigate the antitumor efficacy of dacarbazine in vitro, both as a single agent and in combination with birinapant, in melanoma cell lines. Covering clinically relevant drug concentration ranges, we conducted a total of 5,400 measurements in a panel of 12 human melanoma cell lines representing different stages of disease progression. Surprisingly, functionally More >

  • Open Access

    ARTICLE

    MicroRNA-138 Inhibits Cell Growth, Invasion, and EMT of Non-Small Cell Lung Cancer via SOX4/p53 Feedback Loop

    Dandan Li*, Changjun He, Junfeng Wang, Yanbo Wang, Jianlong Bu, Xianglong Kong, Dawei Sun

    Oncology Research, Vol.26, No.3, pp. 385-400, 2018, DOI:10.3727/096504017X14973124850905

    Abstract Many studies have shown that downregulation of miR-138 occurs in a variety of cancers including non-small cell lung cancer (NSCLC). However, the precise mechanisms of miR-138 in NSCLC have not been well clarified. In this study, we investigated the biological functions and molecular mechanisms of miR-138 in NSCLC cell lines, discussing whether it could turn out to be a therapeutic biomarker of NSCLC in the future. In our study, we found that miR-138 is downregulated in NSCLC tissues and cell lines. Moreover, the low level of miR-138 was associated with increased expression of SOX4 in… More >

  • Open Access

    ARTICLE

    Research on Demand Response Potential of Adjustable Loads in Demand Response Scenarios

    Zhishuo Zhang, Xinhui Du*, Yaoke Shang, Jingshu Zhang, Wei Zhao, Jia Su

    Energy Engineering, Vol.121, No.6, pp. 1577-1605, 2024, DOI:10.32604/ee.2024.047706

    Abstract To address the issues of limited demand response data, low generalization of demand response potential evaluation, and poor demand response effect, the article proposes a demand response potential feature extraction and prediction model based on data mining and a demand response potential assessment model for adjustable loads in demand response scenarios based on subjective and objective weight analysis. Firstly, based on the demand response process and demand response behavior, obtain demand response characteristics that characterize the process and behavior. Secondly, establish a feature extraction and prediction model based on data mining, including similar day clustering,… More >

  • Open Access

    ARTICLE

    Forecasting the Academic Performance by Leveraging Educational Data Mining

    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 >

  • Open Access

    ARTICLE

    Extraction et mise en contexte spatial des propositions relatives au transport dans le Grand Débat National

    Jacques Fize1, Lucile Sautot2, Martin Lentschat3, Laurence Dujourdy4, Ludovic Journaux5, Mohamed Hilal6

    Revue Internationale de Géomatique, Vol.31, No.2, pp. 329-354, 2022, DOI:10.3166/RIG.31.329-354© 2022

    Abstract Le Grand Débat National, lancé début 2019 par Emmanuel Macron, président de la République, pour répondre au mouvement social des « Gilets jaunes », a permis de collecter les contributions de citoyens sur la transition écologique via une plateforme en ligne. Dans cet article, nous exploitons le corpus constitué par ces contributions pour identifier des zones où les participants demandent le développement de pistes cyclables et d’équipements ferroviaires. Pour cela, nous avons créé un modèle de classification permettant d’identifier les contributions traitant de la thématique du transport et proposé une méthode d’extraction de contributions traduisant More >

  • Open Access

    ARTICLE

    Binary Program Vulnerability Mining Based on Neural Network

    Zhenhui Li1, Shuangping Xing1, Lin Yu1, Huiping Li1, Fan Zhou1, Guangqiang Yin1, Xikai Tang2, Zhiguo Wang1,*

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1861-1879, 2024, DOI:10.32604/cmc.2023.046595

    Abstract Software security analysts typically only have access to the executable program and cannot directly access the source code of the program. This poses significant challenges to security analysis. While it is crucial to identify vulnerabilities in such non-source code programs, there exists a limited set of generalized tools due to the low versatility of current vulnerability mining methods. However, these tools suffer from some shortcomings. In terms of targeted fuzzing, the path searching for target points is not streamlined enough, and the completely random testing leads to an excessively large search space. Additionally, when it… More >

  • Open Access

    ARTICLE

    A Predictive Energy Management Strategies for Mining Dump Trucks

    Yixuan Yu, Yulin Wang*, Qingcheng Li, Bowen Jiao

    Energy Engineering, Vol.121, No.3, pp. 769-788, 2024, DOI:10.32604/ee.2023.044042

    Abstract The plug-in hybrid vehicles (PHEV) technology can effectively address the issues of poor dynamics and higher energy consumption commonly found in traditional mining dump trucks. Meanwhile, plug-in hybrid electric trucks can achieve excellent fuel economy through efficient energy management strategies (EMS). Therefore, a series hybrid system is constructed based on a 100-ton mining dump truck in this paper. And inspired by the dynamic programming (DP) algorithm, a predictive equivalent consumption minimization strategy (P-ECMS) based on the DP optimization result is proposed. Based on the optimal control manifold and the SOC reference trajectory obtained by the More >

  • Open Access

    ARTICLE

    Opinion Mining on Movie Reviews Based on Deep Learning Models

    Mian Muhammad Danyal1, Muhammad Haseeb1, Sarwar Shah Khan2,*, Bilal Khan1, Subhan Ullah1

    Journal on Artificial Intelligence, Vol.6, pp. 23-42, 2024, DOI:10.32604/jai.2023.045617

    Abstract Movies reviews provide valuable insights that can help people decide which movies are worth watching and avoid wasting their time on movies they will not enjoy. Movie reviews may contain spoilers or reveal significant plot details, which can reduce the enjoyment of the movie for those who have not watched it yet. Additionally, the abundance of reviews may make it difficult for people to read them all at once, classifying all of the movie reviews will help in making this decision without wasting time reading them all. Opinion mining, also called sentiment analysis, is the… More >

  • Open Access

    ARTICLE

    Multiple-Object Tracking Using Histogram Stamp Extraction in CCTV Environments

    Ye-Yeon Kang1, Geon Park1, Hyun Yoo2, Kyungyong Chung1,*

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3619-3635, 2023, DOI:10.32604/cmc.2023.043566

    Abstract Object tracking, an important technology in the field of image processing and computer vision, is used to continuously track a specific object or person in an image. This technology may be effective in identifying the same person within one image, but it has limitations in handling multiple images owing to the difficulty in identifying whether the object appearing in other images is the same. When tracking the same object using two or more images, there must be a way to determine that objects existing in different images are the same object. Therefore, this paper attempts… More >

  • Open Access

    ARTICLE

    Examining the Use of Scott’s Formula and Link Expiration Time Metric for Vehicular Clustering

    Fady Samann1,2,*, Shavan Askar3

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2421-2444, 2024, DOI:10.32604/cmes.2023.031265

    Abstract Implementing machine learning algorithms in the non-conducive environment of the vehicular network requires some adaptations due to the high computational complexity of these algorithms. K-clustering algorithms are simplistic, with fast performance and relative accuracy. However, their implementation depends on the initial selection of clusters number (K), the initial clusters’ centers, and the clustering metric. This paper investigated using Scott’s histogram formula to estimate the K number and the Link Expiration Time (LET) as a clustering metric. Realistic traffic flows were considered for three maps, namely Highway, Traffic Light junction, and Roundabout junction, to study the… More >

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