Identification and verification of diagnostic biomarkers for deep infiltrating endometriosis based on machine learning algorithms by Shanping Shi, Chao Huang, Xiaojian Tang, Hua Liu, Weiwei Feng, Chen Chen

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Characterizing HIV-1 Tropism and Key Positions within the V3 Loop Using Random Forest Analysis by Karenn Evangelista Miranda, Letícia Martins Raposo

“…This study aimed to identify critical positions within the V3 loop for defining CCR5, CXCR4, and R5X4 tropisms based on HIV-1 subtype. The random forest algorithm was employed to assess variable importance. …”
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Enhancing fever of unknown origin diagnosis: machine learning approaches to predict metagenomic next-generation sequencing positivity by Zhi Gao, Zhi Gao, Zhi Gao, Yongfang Jiang, Yongfang Jiang, Yongfang Jiang, Mengxuan Chen, Mengxuan Chen, Mengxuan Chen, Weihang Wang, Weihang Wang, Weihang Wang, Qiyao Liu, Qiyao Liu, Qiyao Liu, Jing Ma, Jing Ma, Jing Ma

“…This study aimed to develop an interpretable machine learning algorithm for the effective prediction of mNGS results in patients with FUO.MethodsA clinical dataset from a large medical institution was used to develop and compare the performance of several predictive models, namely eXtreme Gradient Boosting (XGBoost), Light Gradient-Boosting Machine (LightGBM), and Random Forest, and the Shapley additive explanation (SHAP) method was employed to interpret and analyze the results.ResultsThe mNGS-positive rate among 284 patients with FUO reached 64.1%. …”
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Simple Rules of a Discrete Stochastic Process Leading to Catalan-like Recurrences by Mariusz Białecki

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Changes of gastric microflora and metabolites in patients with chronic atrophic gastritis by Yumei Ma, Jianming Jiang, Zhufeng Yang, Yongzhang Li, Haiyan Bai, Zongxiu Liu, Shuo Zhang, Zheng Zhi, Qian Yang

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A note on limits of sequences of binary trees by Rudolf Grübel

“…In analogy to recent developments in the theory of graphs, posets and permutations we investigate some general aspects of the topology, such as a characterization of the set of possible limits and its structure as a metric space. For random trees the subtree size topology arises in the context of algorithms for searching and sorting when applied to random input, resulting in a sequence of nested trees. …”
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Research on noise suppression of electronic water pumps based on HRCSVPWM by HU Xinyang, MA Xipei, LIU Jie, FAN Pingqing

“…Firstly, the Xorshift algorithm was used to design a random sequence generator to generate random numbers with good randomness to disperse a large number of harmonics concentrated in the carrier frequency and its integer multiples. …”
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Temporal causal inference with stochastic audiovisual sequences. by Shannon M Locke, Michael S Landy

“…Yet, recent research on audiovisual rate discrimination indicates that random sequences of light flashes and auditory clicks are integrated optimally regardless of temporal correlation. …”
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Integration of Bulk and Single-Cell Transcriptomics Reveals BCL2L14 as a Novel IGKC+ T Cell-Associated Therapeutic Target in Breast Cancer by He J, Akhtar A, Li J, Wei Q, Yuan Y, Ran J, Ma Y, Chen D

“…These findings provide a basis for developing advanced diagnostic tools and targeted therapies, which may ultimately enhance patient prognosis.Keywords: single cell sequencing, breast cancer, scPagwas, Mendelian randomization, bioinformatics…”
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Unraveling the role of histone acetylation in sepsis biomarker discovery by Feng Cheng, Juxin Deng, Zhaoyang Du, Lei Li, Zhaolei Qiu, Min Zhu, Hongchang Zhao, Hongchang Zhao, Zhenjie Wang, Zhenjie Wang

“…Mendelian randomization (MR), RT-qPCR, and functional assays were conducted for validation.ResultsBLOC1S1, NDUFA1, and SFT2D1 were identified as key biomarkers. …”
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Analysis of random factors of the self-education process by A. A. Solodov

“…The aim of the study is the statistical description of the random factors of the self-educationт process, namely that stage of the process of continuous education, in which there is no meaningful impact on the student’s educational organization and the development of algorithms for estimating these factors. …”
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Quasi-random numbers in some statistical systems by Vitalija Rudzkienė

“…Pseudo-random numbers come from mathematical functions and algorithms that provides such numbers called pseudo-random gene­rators. …”
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Multi-objective Path Planning for AUVs Based on Improved Whale Optimization Algorithms and Fluid Disturbance Algorithms by Yuhong MA, Wen PANG, Daqi ZHU

“…A hybrid population initialization method was developed by combining chaotic mapping to generate high-coverage initial solutions and a greedy algorithm to construct locally optimal sequences, effectively addressing the issue of poor solution quality caused by random initialization in traditional WOA. …”
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Feature Recognition of Human Motion Behavior Based on Depth Sequence Analysis by Guangyong Zhao

“…In this work, we propose a random projection-based human action recognition algorithm to address the lack of depth information in color information (RGB video frames) that is not easily affected by environmental factors such as illumination and the lack of ability to recognize actions along the direction of view. …”
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Analysis of Similarity/Dissimilarity of DNA Sequences Based on Chaos Game Representation by Wei Deng, Yihui Luan

“…Based on CGR coordinates of random sequences, we introduce some invariants for the DNA primary sequences. …”
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Machine tool FEM model correction assisted by dynamic evolution sequence by Weihao Lin, Peng Zhong, Xindi Wei, Li Zhu, Xuanlong Wu

“…Moreover, replacing the random sequence with a dynamic evolution sequence enhances the search space coverage of the heterogeneous comprehensive learning particle swarm optimization (HCLPSO) algorithm. …”
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A Random Compressive Sensing Method for Airborne Clustering WSNs by Wei Zhou, Bo Jing, Yifeng Huang

“…In this scheme, hardware resource limited cluster members sample the input signals with random sampling sequence and then transmit the sampling signals to the cluster head or Sink to reconstruct. …”
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Data Clustering Using by Chaotic SSPCO Algorithm by OICC Press Authors

“…We propose chaotic map SSPCO optimization method for clustering, which uses a chaotic map to adopt a random sequence with a random starting point as a parameter, the method relies on this parameter to update the positions and velocities of the chicks. …”
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Hybrid genetic algorithm based optimization of pilotpattern by Hanbing ZHENG, Xiang YU, Weiwei WANG

“…In OFDM system,sparse channel estimation based on compressed sensing(CS)can make full use of the inherent sparse degree of the wireless channel,which can reduce the pilot overhead and improve the spectrum efficiency.Therefore,a new method based on hybrid genetic algorithm was investigated for the pilot design of CS channel estimation,which was based on the minimization of the matrix cross correlation in the CS theory.In this method,genetic algorithm was used to obtain the initial sub-optimal pilot sequence,and then combined with the pilot position and pilot power,each entry of pilot pattern could be sequentially updated and optimized to make the minimum correlation of measurement matrix.Simulation results show that the proposed method can ensure a better mean square error and bit error rate compared to the pseudo-random pilot design and the equal distance pilot design.…”
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Multifactor Algorithm for Test Case Selection and Ordering by Atulya Gupta, Rajendra Prasad Mahapatra

“…This study contrasts randomly generated sequences with procured re-ordered test sequence for over '10' benchmark codes for the proposed prioritization scheme. …”
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