SVR model and OLCI images reveal a declining trend in phycocyanin levels in typical lakes across Northeast China by Changchun Song, Yipei Xu, Chong Fang, Chi Zhang, Zhuohang Xin, Zhihong Liu

“…A novel segmented PC concentration remote sensing inversion model was developed using the support vector regression (SVR) algorithm and Sentinel-3 OLCI data to examine the spatiotemporal variations in PC concentrations across 11 representative lakes in Northeast China. …”
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Predicting local control of brain metastases after stereotactic radiotherapy with clinical, radiomics and deep learning features by Hemalatha Kanakarajan, Wouter De Baene, Patrick Hanssens, Margriet Sitskoorn

“…A Random Forest machine learning algorithm was employed to train four models using: (1) clinical features only; (2) clinical and radiomics features; (3) clinical and DL features; and (4) clinical, radiomics, and DL features. …”
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Beyond 0-1: The 1-N Principle and Fast Validation of N-Sorter Sorting Networks by Robert B. Kent, Marios S. Pattichis

“…In order to verify these N-sorters, the authors propose the 1-N principle, which states that testing an N-sorter with all distinct orderings of N input values is necessary and sufficient to prove the N-sorter’s correctness. An algorithm is defined which generates a vector set consisting of all distinct orderings of N inputs, which is then used to fully verify the associated single-stage N-sorter. …”
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Enhanced dry SO₂ capture estimation using Python-driven computational frameworks with hyperparameter tuning and data augmentation by Robert Makomere, Hilary Rutto, Alfayo Alugongo, Lawrence Koech, Evans Suter, Itumeleng Kohitlhetse

“…In addition, it was the least convoluted algorithm according to Akaike information criterion and Bayesian information criterion assessments. …”
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Characteristics, Incidence, and Management of Immune Checkpoint Inhibitors Related Cardiovascular Adverse Events in Real-World Practice-A Retrospective Study in Chinese Han Populat... by Wang RH, Chen Y, Lou YL, Lu YL, Xu HM

“…CVAEs were identified through clinical assessment and the Naranjo algorithm. The management and outcomes of CVAEs were monitored over a median follow-up duration of 8 months.Results: Among the included 203 patients, 4.4% (9/203) developed CVAEs, including heart failure (n = 3), arrhythmia (n = 2), myocarditis (n = 2), and pericardial disease (n = 2), with a proportion (6/9) tending to be severe (grade 3 or grade 4). …”
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Sign Language Recognition Based on CNN-BiLSTM Using RF Signals by Yajun Zhang, Yuankang Wang, Feng Li, Weiqian Yu, Congcong Wang, Ying Jiang

“…Secondly, to accurately delineate the start and end points of sign language action signals, we propose an improved version of the Varri signal segmentation algorithm called Varri+ to effectively optimize the segmentation of sign language actions. …”
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Random forest model that incorporates solar-induced chlorophyll fluorescence data can accurately track crop yield variations under drought conditions by Guangpo Geng, Qian Gu, Hongkui Zhou, Bao Zhang, Zuxin He, Ruolin Zheng

“…In this study, remote sensing data, climate data, and soil moisture data from the winter wheat growth period in northern China from 2003 to 2017 were used to construct a crop yield simulation model based on the Random Forest (RF) algorithm. The effect of drought on winter wheat yield was quantitatively evaluated by calculating the fitting accuracy of the RF model, analyzing the importance of the factors influencing yield simulations, identifying a typical drought event, and determining the yield estimation accuracy as well as the percent yield loss (PYL) under drought conditions. …”
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Unveiling the Effect of Age and IgE Level on Alopecia Areata: Insights from Comparative RNAseq Analysis by Liu H, Yang S, Xian H, Liu Y, Zhang Y, Chen Y, Xu Y, Liu J, Yang B, Luo Y

“…Moreover, pediatric AA patients with atopic predisposition often exhibit elevated IgE levels, early onset, and a poor prognosis.Purpose: This study aimed to investigate the impact of age and IgE levels on AA by conducting RNA sequencing on scalp samples from AA patients with atopic predisposition, age-matched healthy controls, and AA samples with varying IgE levels.Patients and Methods: We employed the single-sample Gene Set Enrichment Analysis (ssGSEA) algorithm in conjunction with gene expression analysis to assess immune infiltration. …”
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Data-driven multi-fault detection in pipelines utilizing frequency response function and artificial neural networks by Hussein A. M. Hussein, Sharafiz B. Abdul Rahim, Faizal B. Mustapha, Prajindra S. Krishnan, Nawal Aswan B. Abdul Jalil

“…This research presents a data-driven structural health monitoring (SHM) approach for pipeline systems that leverages frequency response function (FRF) signals and artificial neural network (ANN) algorithms to accurately identify and classify diverse pipeline fault conditions. …”
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Morphological Neuroimaging Biomarkers for Tinnitus: Evidence Obtained by Applying Machine Learning by Yawen Liu, Haijun Niu, Jianming Zhu, Pengfei Zhao, Hongxia Yin, Heyu Ding, Shusheng Gong, Zhenghan Yang, Han Lv, Zhenchang Wang

“…From this feature pool, a hybrid feature selection algorithm combining the F-score and sequential forward floating selection (SFFS) methods was performed to select features. …”
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The Ionospheric Effects of the 2022 Hunga Tonga Volcano Eruption and the Associated Impacts on GPS Precise Point Positioning Across the Australian Region by B. A. Carter, R. Pradipta, T. Dao, J. L. Currie, S. Choy, P. Wilkinson, P. Maher, R. Marshall, K. Harima, M. Le Huy, T. Nguyen Chien, T. Nguyen Ha, T. J. Harris

“…However, when the PPP algorithm was initiated from a cold start either shortly before or after the TID arrivals, the convergence times were significantly longer. …”
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Investigating the effects of previous injury on subsequent training loads, physical fitness, and injuries in youth female basketball players by Yuanqi Huang, Shaonan Wang, Changfei Li, Yukun Wang, Zhanshuang Bai, Zhanshuang Bai, Binghao Lv, Yuheng Gui, Zhongjian Wei

“…Previous injury status was clustered using the K-means clustering algorithm to separate players into high-risk and low-risk groups. …”
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Assessing Nonlinear Dynamics and Trends in Precipitation by Ensemble Empirical Mode Decomposition (EEMD) and Fractal Approach in Benin Republic (West Africa) by Médard Noukpo Agbazo, Gabin Koto N’Gobi, Eric Alamou, Basile Kounouhewa, Abel Afouda

“…To overcome the detrending issue in the standard MFDFA method, the EEMD algorithm is embedded into the MFDFA. The study period is subdivided into three subperiods: 1951–1970, 1971–1990, and 1991–2010. …”
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Aircraft hybrid-electric environment for analysis and design (AHEAD) applied on a fixed-wing drone by Manuel A. Rendón, Patrícia H. Hallak, Yipsy Roque Benito, Marcelo Assato, Camila de Oliveira Cunha, Daniel Miranda Esther, Rafael Grande Pancini Delmonte, Denys Pinto Gonçalves

“…The aircraft is modeled in SUAVE and OpenVSP [1], propeller in QBlade [2], ICE in Diesel-RK [3], electrical components in MATLAB®/SIMULINK®, and the method algorithm is programmed in Python. By employing this method, it is possible to analyze the viability of substituting actual propulsion by hybrid.…”
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Detection of Dengue Virus-Specific IgM and IgG Antibodies through Peptide Sequences of Envelope and NS1 Proteins for Serological Identification by Pradeep Kumar Nagar, Deepali Savargaonkar, Anupkumar R. Anvikar

“…Whole protein sequences of E and NS1 of DENV were obtained from UniProtKB database. On the basis of algorithm prediction from DNASTAR, BCEPRED, and IEDB data resources, twelve peptides of E (EP1 to EP12) and eight peptides of NS1 (NS1-1 to NS1-8) were selected, which were common in all serotypes. …”
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Composition optimization design and high temperature mechanical properties of cast heat-resistant aluminum alloy via machine learning by Changmei Hao, Yudong Sui, Yanru Yuan, Pengfei Li, Haini Jin, Aoyang Jiang

“…This study combines experimental and machine learning methods to predict the optimal alloy composition for maximum ultimate tensile strength(UTS) at 300 °C and 350 °C. The AdaBoost algorithm was chosen as the final model. Experimental results show that predictions of the machine learning model deviate by only 7.75 % from the actual results, with an R2 of 0.94. …”
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Utilizing bioinformatics and machine learning to identify CXCR4 gene-related therapeutic targets in diabetic foot ulcers by Hengyan Zhang, Ye Zhou, Heguo Yan, Changxing Huang, Licong Yang, Yangwen Liu

“…Feature selection methods such as LASSO, SVM-RFE and random forest algorithm were applied to localize possible therapeutic target genes. …”
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Diabetes and Cataracts Development—Characteristics, Subtypes and Predictive Modeling Using Machine Learning in Romanian Patients: A Cross-Sectional Study by Adriana Ivanescu, Simona Popescu, Adina Braha, Bogdan Timar, Teodora Sorescu, Sandra Lazar, Romulus Timar, Laura Gaita

“…A Random Forest Classification algorithm was employed to predict the incidence of different associations of cataracts (1, 2, or 3 types). …”
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Analysis and validation of serum biomarkers in brucellosis patients through proteomics and bioinformatics by Xiao Li, Bo Wang, Xiaocong Li, Juan He, Yue Shi, Rui Wang, Dongwei Li, Ding Haitao, Ding Haitao

“…IntroductionThis study aims to utilize proteomics, bioinformatics, and machine learning algorithms to identify diagnostic biomarkers in the serum of patients with acute and chronic brucellosisMethodsProteomic analysis was conducted on serum samples from patients with acute and chronic brucellosis, as well as from healthy controls. …”
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Validity of Wearable Inertial Sensors for Gait Analysis: A Systematic Review by Giuseppe Prisco, Maria Agnese Pirozzi, Antonella Santone, Fabrizio Esposito, Mario Cesarelli, Francesco Amato, Leandro Donisi

“…Wearable technologies, especially inertial measurement units (IMUs), enable portable and accessible assessments outside the lab, though challenges with sensor placement, signal selection, and algorithm design can affect accuracy. This systematic review aims to bridge the benchmarking gap between IMU-based and traditional systems, validating the use of wearable inertial systems for gait analysis. …”
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