IGWO-MALSTM: An Improved Grey Wolf-Optimized Hybrid LSTM with Multi-Head Attention for Financial Time Series Forecasting by Mingfu Zhu, Haoran Qi, Panke Qin

“…The present study investigates the potential of time series forecasting (TSF) in financial application scenarios, aiming to predict future spreads and inform investment decisions more effectively. …”
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Spectroscopic Quantification of Metallic Element Concentrations in Liquid-Propellant Rocket Exhaust Plumes by Siyang Tan, Song Yan, Xiang Li, Tong Su, Qingchun Lei, Wei Fan

“…Finally, the trained network is employed to predict the concentration of metallic elements from the measured atomic emission spectra. …”
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Computational selection of transcriptomics experiments improves Guilt-by-Association analyses. by Prajwal Bhat, Haixuan Yang, László Bögre, Alessandra Devoto, Alberto Paccanaro

“…We demonstrate that: using the selected experiments there is a statistically significant improvement in correlation between genes in the functional category of interest; the selected experiments improve GBA-based gene function prediction; the effectiveness of the selected experiments increases with annotation specificity; our algorithm can be successfully applied to GBA-based pathway reconstruction. …”
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Ultra-Short-Term Forecasting-Based Optimization for Proactive Home Energy Management by Siqi Liu, Zhiyuan Xie, Zhengwei Hu, Kaisa Zhang, Weidong Gao, Xuewen Liu

“…This study proposes a ultra-short-term forecasting-driven proactive energy consumption optimization strategy that integrates advanced forecasting models with multi-objective scheduling algorithms. By leveraging deep learning techniques like Graph Attention Network (GAT) architectures, the system predicts ultra-short-term household load profiles with high accuracy, addressing the volatility of residential energy use. …”
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Surrogate model for calculating spatial magnetic track forces in permanent magnet levitation transportation by LIU Haodong, FENG Yang, ZHAO Chunfa, LUO Shihui, SONG Xiaolin

“…Furthermore, the predicted overall resultant and corresponding torque for the 600 mm long vehicle-mounted PML module also demonstrate high accuracy. …”
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Designing diverse and high-performance proteins with a large language model in the loop. by Carlos A Gomez-Uribe, Japheth Gado, Meiirbek Islamov

“…We present a protein engineering approach to directed evolution with machine learning that integrates a new semi-supervised neural network fitness prediction model, Seq2Fitness, and an innovative optimization algorithm, biphasic annealing for diverse and adaptive sequence sampling (BADASS) to design sequences. …”
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Microgrid Resilience Enhancement with Sensor Network-Based Monitoring and Risk Assessment Involving Uncertain Data by Tangxiao Yuan, Kossigan Roland Assilevi, Kondo Hloindo Adjallah, Ayité Sénah A. Ajavon, Huifen Wang

“…At the application level, this framework is successfully applied to two critical decision-making scenarios: the first is to optimize the power allocation strategy between solar energy and the auxiliary grid, aiming to maximize cost efficiency and minimize power outage losses; the second is to develop low-risk maintenance plans based on the predicted failure probabilities of microgrid components with uncertain information. …”
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The Gut Microbiota and Colorectal Cancer: Understanding the Link and Exploring Therapeutic Interventions by Imen Zalila-Kolsi, Dhoha Dhieb, Hussam A. Osman, Hadjer Mekideche

“…The study of intratumoral microbiota offers new diagnostic and prognostic tools that, combined with artificial intelligence algorithms, could predict treatment responses and assess the risk of adverse effects. …”
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A Novel Mutation of the CYP11B2 in a Saudi Infant with Primary Hypoaldosteronism by Lama Alfaraidi, Abrar Alfaifi, Rawan Alquaiz, Faten Almijmaj, Horia Mawlawi

“…Given the position of the transition at a highly conserved nucleotide and the predictions of different bioinformatic algorithms, it is likely that the mutation is the pathogenic cause of this condition. …”
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Potential natural vegetation pattern based on major tree distribution modeling in the western Rif of Morocco by Ghallab A, Boubekraoui H, Laaribya S, Ben-Said M

“…In a fragile ecological environment, understanding the potential spatial distribution of species and the underlying environmental conditions is crucial for resolving ecosystem management issues and predicting impacts of global change. This study aimed to determine the potential distribution of fourteen major Mediterranean taxa (seven conifers and seven broadleaves) native to northwestern Morocco using the Maximum Entropy Algorithm (MaxEnt). …”
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Mechanisms and optimization for simultaneous removal of Cd(II) and Sb(V) from aqueous solutions using birnessite and fulvic acid composite by Changsheng Jin, Jingjing Lu, Yin Gao, Baowei Hu, Yuxi Liu

“…The RF model demonstrated superior predictive accuracy (R² = 0.8037, RMSE = 0.0625) compared to the RSM and GABP models. …”
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Comprehensive analysis of cuproptosis-related genes in immune infiltration and development of a novel diagnostic model for acute kidney injury by Yajing Li, Yingxue Ding

“…The six-gene cuproptosis-related signature exhibited remarkable predictive efficiency for AKI.…”
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Edge computing-based ensemble learning model for health care decision systems by Asir Chandra Shinoo Robert Vincent, Sudhakar Sengan

“…The main drawback of traditional Machine Learning (ML) techniques is their failure to predict reliably. To solve this problem, the proposed model creates an Ensemble Extreme Learning Machine (EN-ELM) algorithm that combines predictors trained on several different data sets. …”
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Non-Destructive Detection of Soybean Storage Quality Using Hyperspectral Imaging Technology by Yurong Zhang, Wenliang Wu, Xianqing Zhou, Jun-Hu Cheng

“…The feature variables were extracted by a variable iterative space shrinkage approach (VISSA), competitive adaptive reweighted sampling (CARS), and a successive projections algorithm (SPA). Partial least squares regression (PLSR), support vector machine (SVM), and extreme learning machine (ELM) models were developed to predict crude fatty acid values of soybeans. …”
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Computational design exploration of rocket nozzle using deep reinforcement learning by Aagashram Neelakandan, Arockia Selvakumar Arockia Doss, Natrayan Lakshmaiya

“…A key novelty of this work is the integration of a CNN-LSTM-based surrogate model to accelerate the design process by predicting Mach numbers from nozzle images, significantly reducing reliance on computationally expensive CFD simulations. …”
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Studi Komparasi Naive Bayes, K-Nearest Neighbor, dan Random Forest untuk Prediksi Calon Mahasiswa yang Diterima atau Mundur by Puteri Sejati, Munawar Munawar, Marzuki Pilliang, Habibullah Akbar

“…This study used the classification method to predict prospective students. They are accepted or withdrawn. …”
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Multi-objective RGB-D fusion network for non-destructive strawberry trait assessment by Zhenzhen Cheng, Yifan Cheng, Bailing Miao, Tingting Fang, Shoufu Gong

“…This study proposes a multi-objective learning algorithm that leverages RGB-D multimodal information to estimate these quality metrics. …”
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Operation optimisation of direct current microgrids toward stability and economy: a model-data co-driven framework by Yuxin Zhu, Fei Wang, Zhengyu Lin, James Fleming

“…Case study illustrates that the proposed method is not affected by prediction errors and avoids the violation of stability constraints. …”
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Emerging opportunities and challenges for the future of reservoir computing by Min Yan, Can Huang, Peter Bienstman, Peter Tino, Wei Lin, Jie Sun

“…Shown to have the potential of achieving higher-precision prediction in chaotic systems, those pioneering works led to a great amount of interest and follow-ups in the community of nonlinear dynamics and complex systems. …”
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NEW APPROACHES IN TREATMENT OF PATIENTS WITH PERFORATED DUODENAL ULCER by P. N. Romashchenko, N. A. Maistrenko, A. E. Korovin, S. A. Sibirev, P. A. Sidorchuk

“…The results of conducted clinical study showed that in order to establish the correct preoperative diagnosis and the choice of rational treatment of patients with perforated duodenal ulcer it is necessary to conduct a purposeful complex investigation, including an assessment of general somatic state and the operative-anaesthetic risk of patients and changes of pyloroduodenal zone and the severity of peritonitis and prediction of lethality. The diagnostic algorithm let the authors make a diagnosis of perforated duodenal ulcer before the operation and decide on an adequate volume of surgical intervention. …”
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