Identifying human activities causing water pollution based on microbial community sequencing and source classifier machine learning by Zhangmu Jing, Yi Zhang, Xiaoling Liu, Qingqian Li, Yanji Hao, Yeqing Li, Hongjie Gao

“…Combined of microbiological indices (MBIs), microbial relative abundance (MRA), and environmental and geographical indices (EGIs), the source classifier machine learning (SCML) algorithm was used to categorize five human activities (i.e., low human-impact, agricultural inputs, domestic inputs, industrial inputs, and dam construction). …”
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Multi-objective Optimization Model of Track Utilization for Depot-returning Urban Rail Transit Trains with Shunting Operation Constraints by ZHANG Zengchao, XU Peng, XIN Liping, FAN Rui, LI Chen, WU Zelin

“…With the minimum number of shunting operations and the shortest running distance for maintenance as the objective function, and taking the constraints of shunting operations into account, a multi-objective optimization model for train track utilization is developed based on an improved grey wolf algorithm, featuring first for individual independent depot-returning plan (early and late depot-returning) and then for all depot-returning plans as a whole. …”
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Automated Quantification of Neuropad Improves Its Diagnostic Ability in Patients with Diabetic Neuropathy by Georgios Ponirakis, Hassan Fadavi, Ioannis N. Petropoulos, Shazli Azmi, Maryam Ferdousi, Mohammad A. Dabbah, Ahmad Kheyami, Uazman Alam, Omar Asghar, Andrew Marshall, Mitra Tavakoli, Ahmed Al-Ahmar, Saad Javed, Maria Jeziorska, Rayaz A. Malik

“…The categorical output showed no significant difference in diagnostic efficacy for these same measures. An image analysis algorithm generating a continuous output (Sudometrics) improved the diagnostic ability of Neuropad, particularly in detecting autonomic and small fibre neuropathy.…”
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Bayesian calibration and uncertainty quantification for a large nutrient load impact modelZenodoZenodoZenodo by Karel Kaurila, Risto Lignell, Frede Thingstad, Harri Kuosa, Jarno Vanhatalo

“…We then integrated over this (approximate) parameter posterior to produce probabilistic predictions for algal biomass and chlorophyll a concentration under alternative nutrient load reduction scenarios. Our computational algorithm allowed for fast posterior inference and the Gaussian process emulator had good predictive accuracy within the highest posterior probability mass region. …”
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Clinical relevance and druggability of sole reciprocal kinase fusions: A large‐scale study by Jiao Feng, Tonghui Ma, Chunyang Wang, Baoming Wang, Qian Liu, Zhengchuang Liu, Houquan Tao, Zaiyuan Ye

“…Conclusion This inaugural multicenter study introduces a novel algorithm for detecting and treating sole reciprocal fusions in advanced cancers, expanding the patient population potentially amenable to KIs.…”
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POMA-C: A Framework for Solving the Problem of Precise Anesthesia Control Under Incomplete Observation Environment in Low-Income Areas by Yide Yu, Huijie Li, Dennis Wong, Anmin Hu, Jian Huo, Yan Ma, Yue Liu

“…The framework employs the POMCPOW (Partially Observable Monte Carlo Planning with Observation Weighting) algorithm, which integrates Monte Carlo Tree Search (MCTS) and particle filtering to estimate the patient’s true physiological state and guide optimal anesthetic decisions. …”
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Fractal cycles of sleep, a new aperiodic activity-based definition of sleep cycles by Yevgenia Rosenblum, Mahdad Jafarzadeh Esfahani, Nico Adelhöfer, Paul Zerr, Melanie Furrer, Reto Huber, Famke F Roest, Axel Steiger, Marcel Zeising, Csenge G Horváth, Bence Schneider, Róbert Bódizs, Martin Dresler

“…Children and adolescents had shorter fractal cycles than young adults (76±34 vs 94±32 min). The fractal cycle algorithm detected cycles with skipped REM sleep in 91–98% of cases. …”
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Experimental research on remote non-contact laser vibration measurement for tunnel lining cavities by Hongyun Yang, Yu Xie, Zhi Lin, Lin Li, Xiang Chen, Wanlin Feng, Honglin Ran, Li He

“…The vibration differences between the defective and healthy parts were analyzed using the spatial spectral entropy algorithm. The results showed that for cavities with side lengths of 200mm, depths of 50mm, and filled with hollow wooden boxes, the maximum velocity amplitudes of the surface concrete were 10.68, 3.55, and 4.01 times higher than those of the healthy parts, respectively. …”
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A Novel Two-Stage Deep Learning Model for Network Intrusion Detection: LSTM-AE by Vanlalruata Hnamte, Hong Nhung-Nguyen, Jamal Hussain, Yong Hwa-Kim

“…This kind of research enables the identification of the most efficient algorithm for identifying future cyber-attacks. We proposed a novel two-stage deep learning technique hybridizing Long-Short Term Memory (LSTM) and Auto-Encoders (AE) for detecting attacks. …”
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Developing a Robust Model Based on the Gaussian Process Regression Approach to Predict Biodiesel Properties by Inna Pustokhina, Amir Seraj, Hafsan Hafsan, Seyed Mojtaba Mostafavi, S. M. Alizadeh

“…The basic purpose of the present study is to design a precise algorithm based on Gaussian Process Regression (GPR) model with several kernel functions, i.e., Rational Quadratic, Squared Exponential, Matern, and Exponential, to estimate biodiesel properties. …”
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Medium Energy Electron Flux in Earth's Outer Radiation Belt (MERLIN): A Machine Learning Model by A. G. Smirnov, M. Berrendorf, Y. Y. Shprits, E. A. Kronberg, H. J. Allison, N. A. Aseev, I. S. Zhelavskaya, S. K. Morley, G. D. Reeves, M. R. Carver, F. Effenberger

“…In this paper, we present an alternative approach using the Light Gradient Boosting (LightGBM) machine learning algorithm. The Medium Energy electRon fLux In Earth's outer radiatioN belt (MERLIN) model takes as input the satellite position, a combination of geomagnetic indices and solar wind parameters including the time history of velocity, and does not use persistence. …”
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Modeling saturation exponent of underground hydrocarbon reservoirs using robust machine learning methods by Abhinav Kumar, Paul Rodrigues, A. K. Kareem, Tingneyuc Sekac, Sherzod Abdullaev, Jasgurpreet Singh Chohan, R. Manjunatha, Kumar Rethik, Shivakrishna Dasi, Mahmood Kiani

“…A well-known outlier detection algorithm is applied on the gathered data to assess the data reliability before model development. …”
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Treatment of patients with tumor/treatment-related hypothalamic obesity in the first two years following surgical treatment or radiotherapy by Hermann L. Müller, Julian Witte, Bastian Surmann, Manuel Batram, Kylie Braegelmann, Mathias Flume, Julia Beckhaus, Nicolas Touchot, Carsten Friedrich

“…We analyze German claims data to better understand treatment pathways for patients living TTR-HO during the two years following the index surgical treatment. A database algorithm identified patients with TTR-HO in a representative German payer claims database between 2010 and 2021 (n = 5.42 million patients). …”
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Predicting the Number of COVID-19 Sufferers in Malang City Using the Backpropagation Neural Network with the Fletcher–Reeves Method by Syaiful Anam, Mochamad Hakim Akbar Assidiq Maulana, Noor Hidayat, Indah Yanti, Zuraidah Fitriah, Dwi Mifta Mahanani

“…Backpropagation, a type of ANN algorithm, offers predictive problem solving with good performance. …”
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A Novel Hierarchical/Decentralized AGC Scheme for Power Systems Integrated With Large-Scale Solar Power Plants by Siavash Yari, Masood Mottaghizadeh, Innocent Kamwa, Dmitry Rimorov

“…Following this, the decentralized AGC system works hierarchically and in parallel with the centralized algorithm to regulate the frequency and tie lines exchange power. …”
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Statewide Forest Canopy Cover Mapping of Florida Using Synergistic Integration of Spaceborne LiDAR, SAR, and Optical Imagery by Monique Bohora Schlickmann, Inacio Thomaz Bueno, Denis Valle, William M. Hammond, Susan J. Prichard, Andrew T. Hudak, Carine Klauberg, Mauro Alessandro Karasinski, Kody Melissa Brock, Kleydson Diego Rocha, Jinyi Xia, Rodrigo Vieira Leite, Pedro Higuchi, Ana Carolina da Silva, Gabriel Maximo da Silva, Gina R. Cova, Carlos Alberto Silva

“…Using a random forest algorithm, our model achieved an R² of 0.69, RMSD of 0.17, and MD of 0.001, based on out-of-bag samples for internal validation. …”
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A comparative approach of analyzing data uncertainty in parameter estimation for a Lumpy Skin Disease model by Edwiga Renald, Miracle Amadi, Heikki Haario, Joram Buza, Jean M. Tchuenche, Verdiana G. Masanja

“…The assessment of the uncertainties is determined with the help of Adaptive Metropolis Hastings algorithm, a Markov Chain Monte Carlo (MCMC) standard statistical method. …”
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RETRACTED: An Infrared Small Target Detection Method Based on a Weighted Human Visual Comparison Mechanism for Safety Monitoring by Yuanyuan Chen, Huiqian Wang, Yu Pang, Jinhui Han, En Mou, Enling Cao

“…In the experimental section, our algorithm was compared with some popular methods, and the experimental findings indicated that our method showed strong detection capability based on the commonly used performance indicators of the ROC curve, SCRG, and BSF, especially in low signal-to-noise ratio situations. …”
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Use of stepwise m5 model tree to forecast the P24max based on teleconnection indices by Golnar Ghanbarzadeh, Khalil Ghorbani, Meysam Salarijazi, Chooghi Bairam Komaki, Laleh Rezaei Ghaleh

“…The stepwise execution of the M5 model tree showed that the algorithm follows a greedy approach, and it is not necessary to use all variables to predict P24max. …”
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MARVEL Analysis of the Measured High-resolution Spectra of 12C16O by Salman Mahmoud, Nayla El-Kork, Nariman Abu Elkher, Mubarak Almehairbi, Malathe Samir Khalil, Tibor Furtenbacher, Attila G. Császár, Olga P. Yurchenko, Sergey N. Yurchenko, Jonathan Tennyson

“…The Measured Active Rotational–Vibrational Energy Levels (MARVEL) algorithm is used to determine accurate empirical rotational–vibrational energy levels for the ground electronic state of the diatomic ^12 C ^16 O molecule. 2293 energy levels have been obtained through a careful analysis of lines measured and assigned in high-resolution experimental spectra reported previously in 68 publications. …”
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