Metabolic pathway activation and immune microenvironment features in non-small cell lung cancer: insights from single-cell transcriptomics by Yanru Liu, Yanru Liu, Yanru Liu, Hanmin Liu, Hanmin Liu, Ying Xiong, Ying Xiong

“…Wet lab experiments validated the role of KRT6B in NSCLC, demonstrating that KRT6B expression is elevated and it stimulates the proliferation of cancer cells.DiscussionThese observations not only enhance our understanding of metabolic reprogramming and its biological functions in NSCLC but also provide new perspectives for early detection, prognostic evaluation, and targeted therapy. However, future research should further explore the specific mechanisms of these metabolic pathways and their application potentials in clinical practice.…”
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Permission clustering-based attribute value optimization by Wenchao WU, Zhiyu REN, Xuehui DU

“…In new large-scale computing environment, the attributes of entities were massive and they had complex sources and uneven quality, which were great obstacles to the application of ABAC (attribute-based access control).The attributes were also hard to be corrected manually, making it difficult to be applied in access control system straightly.To solve the optimization problem of nominal attributes, a novel algorithm of attribute value optimization based on permission clustering was designed, in which entities were presented by the privilege set related to them.So that the entities were tagged by density-based clustering method with distances of their privilege set presentations.Then the attribute values were reduced and corrected based on rough set theory.Finally, the algorithm was verified on UCI data sets, which proved that after applying it, ABAC policy mining was improved in the evaluation criteria, such as the true positive rate and F1-score.…”
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Active Inference-Driven Multi-Armed Bandits: Superior Performance through Dynamic Correlation Adjustments by Lin Xiaoqi

“…In recent years, Multi-Armed Bandit (MAB) algorithms have gained substantial attention due to their effectiveness in real-world applications, such as recommendation systems, autonomous systems, and dynamic resource allocation. …”
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Short-term Wind Power Forecasting Based on BWO‒VMD and TCN‒BiGRU by LU Jing, ZHANG Yanru, WANG Rui

“…Its capacity to manage complex time series data is demonstrated, and the advancement and innovation of algorithms and models are supported. New directions for technological progress and practical application in the field of wind power prediction are established.…”
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Ultrasound-based machine learning model to predict the risk of endometrial cancer among postmenopausal women by Yi-Xin Li, Yu Lu, Zhe-Ming Song, Yu-Ting Shen, Wen Lu, Min Ren

“…Three models were developed: (1) R model: radiomics-based machine learning (ML) algorithms; (2) CNN model: image-based CNN algorithms; (3) DLR model: a hybrid model combining radiomics and deep learning features with ML algorithms. …”
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A New Gradient Based Surface Defect Detection Method for the Ceramic Tile by Murat Alparslan Güngör

“…Performance of the proposed method was evaluated with quality metric and subjective evaluation. …”
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Principal component analysis of time delay in large IP network by Xuan WEI, Xiaoying HUANG

“…Network time delay is one of the key indexes to evaluate network performance.Principal component analysis (PCA) is a kind of multivariable analysis and declination algorithm commonly used in the field of data mining.Based on PCA analysis of time delay in large IP networks, aiming to find out the deep reason of time delay and the interdependencies among nodes of the network, a scientific and reasonable network time delay evaluation system was built, and effective suggestions for IP network construction and optimization were finally got.The off-line analysis of the historical network delay is only a preliminary application of the PCA.In the future, PCA can be applied to the real-time on-line monitoring and analysis of the network performance, such as network traffic, network delay, network packet loss, etc., in combination with the network topology, current network traffic direction, routing, distance and other related factors, thus the efficiency and quality of network operations can be further improved.…”
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Machine learning approaches in the therapeutic outcome prediction in major depressive disorder: a systematic review by Veronica Atemnkeng Ntam, Tatjana Huebner, Michael Steffens, Catharina Scholl

“…The objective of the evaluation was to assess applicability of currently published ML-approaches for clinical settings in the EU on the basis of quality, ethical, social, and legal criteria.MethodsWe performed a bibliographic search on PubMed and Google Scholar for studies from January 2016 to December 2024 on ML-applications predicting treatment outcomes in MDD. …”
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Synthetic Financial Data: A Case Study Regarding Polish Limited Liability Companies Data by Aleksandra Szymura

“…This action enables the resulting dataset to be of the highest quality. In further research, it is proposed that other algorithms are tested (e.g. …”
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Quantum computing challenges and solutions in software industry—A multivocal literature review by Masaud Salam, Muhammad Ilyas

“…Subsequently, these challenges were examined deeply and determined that five of them are the most critical, these are ‘Lack of quantum specific algorithms, dev and testing methodologies’, ‘Difficult compilation and debugging’, ‘Lack of development tools and technology’, ‘Lack of development guidelines & Quality Assurance Standards’ and ‘Lack of professional expert’, together founding over 30% of occurrences. …”
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Automatic text generation system for endangered languages based on conditional generative adversarial networks by Zhong Luo

“…Future research directions include optimizing CGAN parameters using algorithms like particle swarm optimization, refining discriminator outputs in loss calculations, and incorporating cultural and linguistic features specific to endangered languages to improve the quality of the generated texts.…”
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Airport-FOD3S: A Three-Stage Detection-Driven Framework for Realistic Foreign Object Debris Synthesis by Hanglin Cheng, Yihao Li, Ruiheng Zhang, Weiguang Zhang

“…Traditional Foreign Object Debris (FOD) detection methods face challenges such as difficulties in large-size data acquisition and the ineffective application of detection algorithms with high accuracy. …”
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Development and validation of a machine learning model for online predicting the risk of in heart failure: based on the routine blood test and their derived parameters by Jianchen Pu, Yimin Yao, Xiaochun Wang

“…In addition, eight different machine learning algorithms were applied for prediction, and the prediction performances of these algorithms were comprehensively evaluated using the receiver operating characteristic curve, area under the curve (AUC), calibration curve analysis, and decision curve analysis and confusion matrix.ConclusionsUsing LASSO regression analysis, leukocyte, neutrophil, red blood cell, hemoglobin, platelet, and monocyte-to-lymphocyte ratios were identified as risk factors for HF. …”
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Opposition-based chaotic evolution for optimization by Tianshui Li, Yan Pei

“…The findings support the broader applicability of OBCE in real-world engineering design problems where solution quality and efficiency are critical.…”
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MMAgentRec, a personalized multi-modal recommendation agent with large language model by Xiaochen Xiao

“…Secondly, the scarcity of high quality datasets and the unnaturalness of recommendation systems pose pressing issues. …”
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A Review on Trending Machine Learning Techniques for Type 2 Diabetes Mellitus Management by Panagiotis D. Petridis, Aleksandra S. Kristo, Angelos K. Sikalidis, Ilias K. Kitsas

“…Our work indicates that Gradient Boosting and tree-based models are the most successful ones, the SHAPley and Wrapper algorithms being quite popular feature interpretation and evaluation methods, highlighting urinary markers and dietary intake as emerging diabetes predictors besides the typical invasive ones. …”
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Chaotic Hénon–Logistic Map Integration: A Powerful Approach for Safeguarding Digital Images by Abeer Al-Hyari, Mua’ad Abu-Faraj, Charlie Obimbo, Moutaz Alazab

“…Performance evaluation in terms of encryption time, throughput, and image quality metrics validates the effectiveness of the proposed integrated approach. …”
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Capability-driven framework to automate discovery of bounded contexts in large-scale requirements engineering by Shohreh Ajoudanian, Maryam Nooraei Abadeh

“…We also provide the applicability of the approach from various points of view including quality and stability of bounded contexts, average precision, and query assessment. …”
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Research on Discrete Dynamic System Modeling of Vocal Performance Teaching Platform Based on Big Data Environment by Xiaohui Gong

“…Based on this, this study studies the innovation of the teaching model of national vocal music in colleges and universities based on the deep recurrent neural network algorithm and designs the teaching quality evaluation model based on the deep recurrent neural network algorithm. …”
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A Low-Cost Antipodal Vivaldi Antenna-Based Peanut Defect Rate Detection System by Yuanyuan Yin, Fangyan Ma, Xiaohong Liu, Shuhao Wang, Junjie Xia, Liqing Zhao

“…As a result, it offers an affordable and practical solution for quality control in peanut production, showing great potential for wide application in the peanut industry.…”
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