Narrowing the gap between machine learning scoring functions and free energy perturbation using augmented data by Ísak Valsson, Matthew T. Warren, Charlotte M. Deane, Aniket Magarkar, Garrett M. Morris, Philip C. Biggin

“…Abstract Machine learning offers great promise for fast and accurate binding affinity predictions. However, current models lack robust evaluation and fail on tasks encountered in (hit-to-) lead optimisation, such as ranking the binding affinity of a congeneric series of ligands, thereby limiting their application in drug discovery. …”
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Land drainage functioning and hydrological impacts in rural catchments: model development and field experiments by Zimmer, Daniel, Tournebize, Julien, Bouarfa, Sami, Kao, Cyril, Lesaffre, Benoît

“…The historical context, the main hypothesis derived from the Boussinesq equation and the validation of the model predictions are discussed. Theoretical developments of this equation demonstrate that a single parameter ($\sigma $)—a combination of soil and drainage system properties—is sufficient for predicting the dynamics of subsurface drain flow rates. …”
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Effect of The Duration of The Diagnosis on DNA Methylation Changes in Three Different Diabetic Genes in Type 2 Diabetes Mellitus by Harem Othman Smail

“…The study also found that the length of diagnosis may have an impact on the discriminative strength of the DNA methylation status of the ABCC8 gene, resulting in varying degrees of T2DM prediction.  …”
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Estimation of the Ultimate Bearing Capacity of the Rocks via Utilization of the AI-Based Frameworks by Bianca Damico, Matteo Conti

“…The main objective was to improve the prediction performance of Qu for rock-socketed piles. …”
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Autonomous decision-making method for ship maneuvering in complex waters of estuarine multi-class ships routeing system by HE Yixiong, ZHANG Huwei, LIU Jiaorun, ZHAO Xingya, XIANG Shouyuan, WANG Bing

“…The collision avoidance mechanism under the constraints of ship behavioural characteristics in such waters was explored by combining the control and process prediction methods with nonlinear ship manoeuvring characteristics. …”
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Ambient Atmospheric Aerosol Extinction Coefficient Reconstruction from PM2.5 Mass Concentrations and Application to Haze Identification in China by Lina Gao, Peng Yan, Jietai Mao, Xiaochun Zhang, Xiaoling Zhang, Yongxue Wu, Junshan Jing, Jianming Xu, Xuejiao Deng, Wenxue Chi

“…Finally, we assessed the bias in the predicted number of hours with haze for 61 stations in China by comparing the estimates derived from different values for the model’s parameters with those derived from the reference values and found a relative bias of less than 15% for approximately 99.8% of the stations, indicating the feasibility of our approach for detecting haze.…”
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Modeling the Distribution of Dominant Hard Ticks in Southeastern Coastal Areas of the Caspian Sea by Sedighe Nabian, Elahe Ebrahimzadeh, Abbas Farahi, Ahmad Ali Hanafi-Bojd

“…This means that tem­perature and precipitation were effective environmental variables for the prediction of appropriate regions for these tick species. …”
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Whole Exome Sequencing Reveals Rare Variants in Genes Associated with Metabolic Disorders in Women with PCOS by Priyal Sharma, Ashutosh Halder, Manish Jain, Manish Tripathi

“…Subsequently, we analysed these variants using in silico prediction software to determine their functional effects. …”
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Sequence-variable attention temporal convolutional network for volcanic lithology identification based on well logs by Hanlin Feng, Zitong Zhang, Chunlei Zhang, Chengcheng Zhong, Qiaoyu Ma

“…It provides more reliable prediction results and exhibits good stability and generalization, offering a new avenue to volcanic lithology identification.…”
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Population dynamics and yield estimation of Common Carp (Cyprinus carpio, Linnaeus, 1758) in Ayalew reservoir, Gamo Zone, Southern Ethiopia by Buchale Shishitu Shija, Atnafu W/yohans Firew

“…Jones length-based cohort analysis model and length-based Thompson and Bell yield prediction models were employed to estimate the population and production potential. …”
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LeaData a novel reference data of leather images for automatic species identification by Anjli Varghese, Malathy Jawahar, A. Amalin Prince

“…The traditional identification techniques are prone to ambiguous predictions due to insufficient reference studies. Indeed, leather image analysis with big data can pave the way for automatic and objective analysis with accurate prediction. …”
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Preference learning based deep reinforcement learning for flexible job shop scheduling problem by Xinning Liu, Li Han, Ling Kang, Jiannan Liu, Huadong Miao

“…First, a reward predictor based on preference learning is designed to model reward prediction by comparing random fragments, eliminating the need for complex reward function design. …”
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Volatility characteristics and hyperspectral-based detection models of diesel in soils by Jihye Shin, Jaehyung Yu, Jihee Seo, Lei Wang, Hyun-Cheol Kim

“…Using the hull-quotient reflectance at 2236 nm, the diesel content prediction model derived from a stepwise multiple linear regression (SMLR) achieved satisfactory accuracy with sufficient statistical significance (R2 = 0.89, RPD = 2.52). …”
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DMR: disentangled and denoised learning for multi-behavior recommendation by Yijia Zhang, Wanyu Chen, Fei Cai, Zhenkun Shi, Feng Qi

“…First, the irrelevant auxiliary behaviors that do not align with the target behavior, can negatively impact the prediction accuracy for user preference in the target behavior. …”
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Thromboelastography parameters in chronic viral liver disease and liver resection: a retrospective study by Ying Di, Jialu Li, Chunjuan Ye, Zheng Wang, Qianqian Zhu

“…TEG utility for haemostasis assessment and prediction of blood loss during liver resection should be further explored in high-quality studies.…”
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Assessment of Machine Learning Algorithms in Short-term Forecasting of PM10 and PM2.5 Concentrations in Selected Polish Agglomerations by Bartosz Czernecki, Michał Marosz, Joanna Jędruszkiewicz

“…Overall, our results confirm the high applicability of ML to short-term air quality prediction with the perfect prog approach.…”
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Effects of elastic anisotropy on the small fatigue crack deflection behavior of α-brass by Jinta Arakawa, Ryushin Kamada, Ryo Yabuki, Yuki Ogawa, Hiroyuki Akebono, Atsushi Sugeta

“…Furthermore, it was also suggested that this prediction is useful independent of grain size and the magnitude of the anisotropy of the crystal grain.…”
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MPAR-RCNN: a multi-task network for multiple person detection with attribute recognition by S. Raghavendra, S. K. Abhilash, Venu Madhav Nookala, Jayashree Shetty, Praveen Gurunath Bharathi

“…The integration of object detection and attribute recognition typically relies on approaches such as dual-stage networks, where accurate predictions depend on advanced feature extraction techniques, such as Region of Interest (RoI) pooling. …”
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Unlocking precision medicine: clinical applications of integrating health records, genetics, and immunology through artificial intelligence by Yi-Ming Chen, Tzu-Hung Hsiao, Ching-Heng Lin, Yang C. Fann

“…Deep learning techniques have significantly advanced variant calling, pathogenicity prediction, splicing analysis, and MHC-peptide binding predictions in genetics. …”
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A neural network design for black-box identification of converter impedance models in arbitrary operating conditions by CHEN Bing, ZHAO Chongbin, JIANG Qirong, WANG Xu, WANG Fangming

“…In the model verification phase, the network is fed with set operating conditions, achieving highly accurate identification of stable operating conditions and offline prediction.…”
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