Comparison of methods for resolving the contributions of local emissions to measured concentrations by T. D. Edwards, Y. K. Wong, C.-H. Jeong, J. M. Wang, Y. Su, G. J. Evans

“…When testing algorithmic predictions of upwind-of-highway backgrounds, we found that regression models surpassed the performance of time-series methods, with best predictions having <span class="inline-formula"><i>R</i>²</span> exceeding 0.8 for all four pollutants. …”
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Harnessing gene expression to identify the genetic basis of drug resistance by Bo‐Juen Chen, Helen C Causton, Denesy Mancenido, Noel L Goddard, Ethan O Perlstein, Dana Pe'er

“…We systematically applied our algorithm to data generated from a collection of yeast segregants, using genotype and gene expression data generated under drug‐free conditions to predict the response to 94 drugs and experimentally confirmed 14 novel gene–drug interactions. …”
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Seismic Vibration Control and Multi-Objective Optimization of Transmission Tower with Tuned Mass Damper Under Near-Fault Pulse-like Ground Motions by Ying Lin, Tao Liu

“…Finally, the NSGA-III algorithm is adopted to perform the multi-objective optimization of a transmission tower equipped with TMD. …”
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Digital-twin driven alignment control method for marine shafting with air spring vibration isolation system by Song Liu, Liang Shi, Wei Xu, ZeChao Hu

“…To obtain the optimal air spring pressures, the genetic algorithm is introduced to solve the optimization problem, fully exploiting its global search capacity. …”
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The Role of Performance Metrics in Estimating Market Values of Footballers in Europe's Top Five Leagues by Murat Işık, Mehmet Ali Yalçınkaya

“…In the classification analysis, players' market values were categorized into four classes (low, lower-mid, upper-mid, and high), and their class memberships were predicted based on performance metrics. The CNN algorithm achieved the highest accuracy, with a success rate of 97%. …”
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Generative AI for drug discovery and protein design: the next frontier in AI-driven molecular science by Uddalak Das

“…Generative artificial intelligence (AI) has emerged as a disruptive paradigm in molecular science, enabling algorithmic navigation and construction of chemical and proteomic spaces through data-driven modeling. …”
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Counterfactual choice and learning in a neural network centered on human lateral frontopolar cortex. by Erie D Boorman, Timothy E Behrens, Matthew F Rushworth

“…Using a three-alternative decision-making task, a Bayesian reinforcement-learning algorithm, and fMRI, we investigated the coding of counterfactual choices and prediction errors in the human brain. …”
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A Dynamic Branch-Switching Method for Parametrically Excited Systems by A.Y.T. Leung, T. Ge

“…The branch-switching algorithm in static is applied to steady state dynamic problems. …”
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An estimation method of lightning-voltage sag severity based on adaptive association rule mining by WANG Ying, LEI Lei, HU Wenxi, XIAO Xianyong

“…The key condition attributes that affect voltage sag severity are screened by attribute reduction algorithm. An association rule mining algorithm based on parameter adaption is proposed, which overcomes the problem that the results of traditional association rules mining methods are affected by non-uniform data. …”
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Transfer Learning‐Assisted Porous Polymer Humidity Sensor for Powered Air‐Purifying Mask by Yue Wang, Xinkai Qi, Lu Chen, Yongchao Cheng, Zhefu Mu, Xiuquan Gu, Shiyin Li, Yunfeng Song, Xinjian He, Sheng Huang

“…By integrating this sensor with a powered air‐purifying system and employing a transfer learning algorithm, the system predicts respiratory signals and adjusts the air supply in real‐time. …”
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Towards a shape-performance integrated digital twin for lumbar spine analysis [version 2; peer review: 2 approved, 1 not approved] by Wei Sun, Xueguan Song, Xiwang He, Xiaonan Lai, Yiming Qiu, Liming Shu, Zhonghai Li

“…Methods A finite element model (FEM) of the lumbar spine was firstly developed using computed tomography (CT) and constrained by the body movement which calculated by the inverse kinematics algorithm. The Gaussian process regression was utilized to train the predicted results and create the digital twin of the lumbar spine in real-time. …”
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Identifying the Dimensions of Degraded Impact Structures Using Digital Elevation Models: A Proof of Concept for Silicate Planets by Connor J. Anderson, James B. Garvin, Devin R. McClain, Scott S. Sinno, Katherine A. Melocik, Compton J. Tucker

“…Application of these methods to additional impact structures is required to quantify prediction uncertainty before applying this methodology to more recent impact structures with questionable diameters.…”
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A Model for Fat Content Detection in Walnuts Based on Near-Infrared Spectroscopy by Langqin Luo, Honghua Zhang, Yu Wang, Jianliang Zhang, Rui Zhang, Shan Gao, Yuanyong Dian, Zijin Bai, Chunhui Feng, Ze Zhang

“…After first optimizing the initial spectrum data using five preprocessing methods, we established separate prediction models for walnut kernel fat content based on either a back propagation neural network or a support vector regression (SVR) algorithm. …”
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PRE-PROCESSING DATA ON MULTICLASS CLASSIFICATION OF ANEMIA AND IRON DEFICIENCY WITH THE XGBOOST METHOD by Fathu Nurrahman, Hari Wijayanto, Aji Hamim Wigena, Nunung Nurjanah

“…Then pre-processing data will be carried out using MissForest imputation, Boruta featuring selection, and SMOTE to help improve the performance of the classification model in predicting a particular class. After the data pre-processing process is carried out, classification modeling will be carried out using the XGBoost algorithm. …”
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Maturity Classification and Quality Determination of Cherry Using VNIR Hyperspectral Images and Comprehensive Chemometrics by Yuzhen Wei, Siyi Yao, Feiyue Wu, Qiangguo Yu

“…After the chemometrics related to hyperspectral imaging had been examined, the least square-support vector regression models based on the feature bands, which were selected by the shuffled frog leaping algorithm, showed the best performance, and the determination coefficients of prediction (R2P) for cherry sugar content and acidity reached 0.976 and 0.906, respectively. …”
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Data processing of non-stationary capillary viscometer for blood by V. G. Leshchenko, M. V. Goltsev, D. V. Mansurov, V. A. Mansurov

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Clinical Utility of HeartLogic, a Multiparametric Telemonitoring System, in Heart Failure by Juan Carlos López-Azor, Noelia de la Torre, María Dolores García-Cosío Carmena, Pedro Caravaca Pérez, Catalina Munera, Irene Marco Clement, Rocío Cózar León, Jesús Álvarez-García, Marta Pachón, Fernando Arribas Ynsaurriaga, Rafael Salguero Bodes, Juan Francisco Delgado Jiménez, Javier de Juan Bagudá

“…Telemonitoring through multiple variables measured on cardiac devices has the potential to improve the follow-up of patients with heart failure. The HeartLogic algorithm (Boston Scientific), implemented in some implantable cardiac defibrillators and cardiac resynchronisation therapy, allows monitoring of the nocturnal heart rate, respiratory movements, thoracic impedance, physical activity and the intensity of heart tones, with the aim of predicting major clinical events. …”
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Research on Fusion of Locomotive Safety Monitoring and Detection Data and Its Application by GONG Li, QIAO Bin, ZHAO Chao, YAO Kai

“…To solve the problems of long cycle, high cost and low efficiency of traditional maintenance methods, a method of equipment quality diagnosis, evaluation and prediction based on decision tree algorithm is put forward to build an intelligent maintenance system. …”
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Nanosatellite Autonomous Navigation via Extreme Learning Machine Using Magnetometer Measurements by Gilberto Goracci, Fabio Curti, Mark Anthony de Guzman

“…This work presents an algorithm to perform autonomous navigation in spacecraft using onboard magnetometer data during GPS outages. …”
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An Analytical Solution for the Hydraulics of Looped Pipe Networks by Mohammad Mehdi Riyahi, Amin E. Bakhshipour, Carlo Giudicianni, Ulrich Dittmer, Ali Haghighi, Enrico Creaco

“…Finally, a Z-test hypothesis test is applied to assess the efficacy of the modified shortest-path algorithm. The results show that this algorithm attains an average accuracy of 90% in predicting exact flow directions, with a confidence level of 99%.…”
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