Porting the Meso-NH atmospheric model on different GPU architectures for the next generation of supercomputers (version MESONH-v55-OpenACC) by J. Escobar, P. Wautelet, J. Pianezze, F. Pantillon, T. Dauhut, C. Barthe, J.-P. Chaboureau

“…This GPU porting paves the way for Meso-NH to be used on future European exascale machines.</p>…”
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Impact of climate change on river flow, using a hybrid model of LARS_WG and LSTM: A case study in the Kashkan Basin by Fatemeh Avazpour, Mohammad Reza Hadian, Ali Talebi, Ali Torabi Haghighi

“…These parameters were input into the LSTM model, and TOPSIS and WASPAS were employed to choose the optimal-performing model. …”
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Adaptive drive-based integration technique for predicting rheological and mechanical properties of fresh gangue backfill slurry by Chaowei Dong, Jianfei Xu, Nan Zhou, Jixiong Zhang, Hao Yan, Zejun Li, Yuzhe Zhang

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Offset Adjustment Mechanism and Rigid-flexible Coupling Analysis Method for Spatial Ultra-thin Paper Tape by Gan Shengyong, Hong Guanghuai, Zhou Changjiang

“…The kinematics and dynamical models of the ultra-thin paper tape are built， and the elastic modulus of the paper tape is measured. …”
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Knowledge based full aperture polishing by Schneckenburger Max, Shaikh Ayaan, Algac Ufuc, Mewis Jan

“…Understanding and controlling of the polishing process on conventional NC (Numerical Control) machines is an important step to optimize production, reduce machine time and increase production quality. …”
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Development of an XGBoost-based prediction model for wound recurrence risk in diabetic foot ulcer patients treated with antibiotic-loaded bone cement by Yi Zhang, Yi Zhang, Xingyu Sun, Cheng Cheng, Nianzong Hou, Nianzong Hou, Shiliang Han, Xin Tang

“…Artificial neural network, support vector machine, and XGBoost prediction models were built according to the selected optimal features. …”
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Equivariant diffusion for structure-based de novo ligand generation with latent-conditioning by Tuan Le, Julian Cremer, Djork-Arné Clevert, Kristof T. Schütt

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Development and Validation of Predictive Models for Differentiating Resectable Stage III Peripheral SCLC from NSCLC Using Radiomic Features and Clinical Parameters by Junjie Zhang MD, Ligang Hao MD, Qiuxu Zhang MD, Lina Zheng MD, Qian Xu PhD, Fengxiao Gao MD

“…Radiomic feature selection was performed using the LASSO algorithm, and nine machine learning models were evaluated. The optimal model was employed to compute the radiomics score (Rad-score) and construct a clinical model. …”
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Enhancing the performance of neurosurgery medical question-answering systems using a multi-task knowledge graph-augmented answer generation model by Ting Pan, Jiang Shen, Man Xu

“…Simultaneously, the model employs a multi-task learning framework, jointly optimizing answer generation, candidate answer ranking, and doctor recommendation tasks aligning machine outputs with clinician decision-making patterns while embedding safeguards against hallucination or inappropriate emotional mimicry. …”
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Development of a single-center predictive model for conventional in vitro fertilization outcomes excluding total fertilization failure: implications for protocol selection by Hai Wang, Haojie Pan, Zitong Xu, Xianjue Zheng, Shuqi Xia, Jiayong Zheng

“…Abstract Objectives To develop a multidimensional clinical indicator-based prediction model for identifying high-risk patients with fertilization failure conventional in vitro fertilization (c-IVF) cycles, thereby optimizing therapeutic decision-making. …”
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Adsorptive removal of organics and nutrients from septic tank effluent using oak wood chip biochar: Kinetic analysis and numerical modeling by Chimdi Muoghalu, Herbert Cirrus Kaboggoza, Swaib Semiyaga, Musa Manga

“…Adsorption followed a pseudo-first-order model highlighting the role of physisorption in eliminating NO3-N and COD. …”
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Adaptive crop switching for irrigated agriculture in response to climate change in the Western U.S. by Shahryar Fazli, Wenzhao Li, Surendra Maharjan, Rejoice Thomas, Aqil Tariq, Hesham El-Askary

“…Future impacts are also assessed through integrating machine learning models with climate projections from the CMIP6 framework under SSP2–4.5 and SSP5–8.5 scenarios to forecast WUEc trends from 2025 to 2099. …”
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Modeling impacts of climate-induced yield variability and adaptations on wheat and maize in a sub-tropical monsoon climate - using fuzzy logic by Md. Abdul Kaium, Md. Sharif Ahmed, Muhammad Habib-Ur-Rahman, Md. Saidul Islam, Yeasmin Akter Ratry, Md Mostofa Uddin Helal, Muhammad Ali Fardoush Siddquy, Most. Moslema Haque, Ahsan Raza, Fatma Mansour, Majed Alotaibi, Ayman El Sabagh, Reimund P. Roetter

“…Key climatic variables (temperature and rainfall) were added as model inputs, enabling the model to handle uncertainty and nonlinear interactions in the climate–yield relationship. …”
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Cell death pathway regulation by fatty acid metabolism-related genes in neuroblastoma: a multi-omics analysis identifying CHD5 as a novel biomarker by Yankun Chen, Junzhi Liu, Yubin Jia, Jiaxing Yang, Yan Jin, Yun Liu, Benfu Zhong, Qiang Zhao

“…Conclusion The developed fatty acid metabolism prognostic risk model underscores the significance of fatty acids in neuroblastoma prognosis and immune landscape, thereby facilitating the optimization of chemotherapy and immunotherapy strategies for this disease. …”
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A Novel Policy Distillation With WPA-Based Knowledge Filtering Algorithm for Efficient Industrial Robot Control by Gilljong Shin, Seongjin Yun, Won-Tae Kim

“…Deep reinforcement learning is more promising technology to support the dynamic factory situations than the legacy static robot control technologies are. The machine learning model experiences the computing resource limitation of industrial robots working the complex jobs of intelligent operations including machine vision, action planning and human collaborations. …”
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Research of Composed Profile with Wide Top High-sealing Zone of Involute Rotor by Yulong Li, Ping Liu, Yong Zang, Jun Fan, Ying Cheng

“…Then, from lightweight of rotor as design object, the optimization model is constructed. Finally, an innovative configuration of profiles is given to eliminate trapped-gas phenomenon. …”
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Colorectal cancer detection with enhanced precision using a hybrid supervised and unsupervised learning approach by Akella S. Narasimha Raju, K. Venkatesh, Ranjith Kumar Gatla, Eswara Prasad Konakalla, Marwa M. Eid, Nataliia Titova, Sherif S. M. Ghoneim, Ramy N. R. Ghaly

“…The method entails several steps with CNN models: ADa-22 and AD-22, transformer networks, and an SVM classifier, all inbuilt. …”
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SMANet: A Model Combining SincNet, Multi-Branch Spatial&#x2014;Temporal CNN, and Attention Mechanism for Motor Imagery BCI by Danjie Wang, Qingguo Wei

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AI-Driven Predictive Maintenance in Mining: A Systematic Literature Review on Fault Detection, Digital Twins, and Intelligent Asset Management by Luis Rojas, Álvaro Peña, José Garcia

“…As a response, industries are integrating predictive monitoring technologies, including machine learning, the Internet of Things, and digital twins, to enhance early fault detection and optimize maintenance strategies. …”
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An improved synergistic dual-layer feature selection algorithm with two type classifier for efficient intrusion detection in IoT environment by G Logeswari, K Thangaramya, M Selvi, J. Deepika Roselind

“…A robust feature selection subsystem, employing Synergistic Dual-Layer Feature Selection (SDFC) algorithm, combines statistical methods, such as mutual information and variance thresholding, with advanced model-based techniques, including Support Vector Machine (SVM) with Recursive Feature Elimination (RFE) and Particle Swarm Optimization (PSO) are employed to identify the most relevant features. …”
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