THE PROGNOSTIC MODEL OF ANTITUMOR EFFECT OF TARGETED DRUGS IN IMMUNOTHERAPY by V. V. Burlyaev, А. А. Davydenko, O. M. Nikolaeva, L. I. Russu, I. A. Suetina, M. V. Mezentseva

“…The methodology takes into account the synergistic interaction of cytokines and uses sequential construction of logical formulas for selecting groups of cytokines, a statistical analysis of contingency tables and logical integration of the obtained estimates. …”
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Mechanisms and optimization of system bolts in shallow four-track HSR tunnels based on deformation pressure theory by Jianfei Ma, Shaohui He, Xiabing Liu, Jiaxin He

“…First, a theoretical framework, referred to as the deformation pressure theory arch, is introduced to elucidate the role of bolts throughout the sequential construction phases of four-track HSR tunnels. …”
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The Ordered Clustered Travelling Salesman Problem: A Hybrid Genetic Algorithm by Zakir Hussain Ahmed

“…This paper develops a hybrid genetic algorithm using sequential constructive crossover, 2-opt search, and a local search for obtaining heuristic solution to the problem. …”
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Predicting Landing Position Deviation in Low-Visibility and Windy Environment Using Pilots’ Eye Movement Features by Xiuyi Li, Yue Zhou, Weiwei Zhao, Chuanyun Fu, Zhuocheng Huang, Nianqian Li, Haibo Xu

“…Then, a random forest method is used to rank eye movement features and sequentially construct feature sets by feature importance. …”
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Micro-expression spotting based on multi-modal hierarchical semantic guided deep fusion and optical flow driven feature integration by Haolin Chang, Zhihua Xie, Fan Yang

“…Specifically, to obtain cross-modal complementary information, this scheme sequentially constructs a Multi-Scale Feature Extraction Module (MFEM) and a Multi-scale hierarchical Semantic-Guided Fusion Module (MSGFM). …”
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Using Reinforcement Learning in a Dynamic Team Orienteering Problem with Electric Batteries by Majsa Ammouriova, Antoni Guerrero, Veronika Tsertsvadze, Christin Schumacher, Angel A. Juan

“…The heuristic combines routes using calculated savings and a biased-randomized strategy, while the RL model leverages a transformer-based encoder–decoder architecture to sequentially construct solutions. We perform computational experiments on 50 problem instances, each subjected to 200 dynamic conditions, for a total of 10,000 problems solved. …”
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