Diagnosis of Alzheimer’s disease using brain $$^{18}\textrm{F}$$ -FDG PET imaging based on a state space model by Yufang Dong, Yonglin Chen, Zhe Jin, Xingbo Dong

“…This not only reduces the computational burden and enhances operational efficiency but also improves the model’s ability to capture global features. …”
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Enhancing transferability of machine learning-based polarizability models in condensed-phase systems via atomic polarizability constraint by Mandi Fang, Yinqiao Zhang, Zheyong Fan, Daquan Tan, Xiaoyong Cao, Chunlei Wei, Nan Xu, Yi He

“…Atomic polarizabilities derived from semi-empirical QM calculations were integrated as training constraints for its balance of computational efficiency and physical interpretability. The constrained TNEP model demonstrated improved accuracy in predicting molecular polarizabilities for larger clusters and condensed-phase systems, attributed to the model’s refined ability to properly partition molecular polarizabilities into atomic contributions across systems with diverse configurational features. …”
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Adaptive Path Planning for Multi-Drone Systems Based on SFS, DPF, and Learning Based Refinement by Srwa Ahmed Mustafa, Amin Salih Kakshar

“…The drone industry needs path-planning algorithms to develop efficient solutions, including monitoring functions, military, and surveillance. …”
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Transforming oil market analysis: A novel GAN + LSTM predictive framework by Prity Kumari, G.Y. Chandan, Satish Kumar M

“…This model has been viewed as dominant due to its ability to integrate and gain information from complex data patterns. …”
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DualCascadeTSF-MobileNetV2: A Lightweight Violence Behavior Recognition Model by Yuang Chen, Yong Li, Shaohua Li, Shuhan Lv, Fang Lin

“…Meanwhile, the model incorporates the efficient lightweight structure of MobileNetV2, significantly reducing the number of parameters and computational complexity. …”
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A Combined Windowing and Deep Learning Model for the Classification of Brain Disorders Based on Electroencephalogram Signals by Dina Abooelzahab, Nawal Zaher, Abdel Hamid Soliman, Claude Chibelushi

“…Background: The electroencephalogram (EEG) is essential for diagnosing and classifying brain disorders, enabling early medical intervention. Its ability to identify brain abnormalities has increased its clinical use in assessing changes in brain activity. …”
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Maximizing solar distillation performance for conical solar still through varied energy storage materials by Abdelkader Bellila, Abd Elnaby Kabeel, Mohammed El Hadi Attia, H. A. Dahab, M. A. Elazab

“…These materials were analyzed based on their ability to improve energy and exergy efficiencies. …”
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Novel Hybrid Deep Learning Model for Forecasting FOWT Power Output by Mohammad Barooni, Deniz Velioglu Sogut, Parviz Sedigh, Masoumeh Bahrami

“…A hybrid deep learning model combining Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks is proposed to predict the performance of FOWTs accurately and more efficiently than traditional numerical models. This model addresses computational complexity and lengthy processing times of conventional models, offering adaptability, scalability, and efficient handling of nonlinear dynamics. …”
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High-Resolution Direction of Arrival Estimation of Underwater Multitargets Using Swarming Intelligence of Flower Pollination Heuristics by Nauman Ahmed, Huigang Wang, Shanshan Tu, Norah A.M. Alsaif, Muhammad Asif Zahoor Raja, Muhammad Kashif, Ammar Armghan, Yasser S. Abdalla, Wasiq Ali, Farman Ali

“…The proposed scheme for estimating the DOA generates efficient outcomes compared to the state-of-the-art algorithms over the Monte Carlo simulations.…”
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Dual-branch attention network-based stereoscopicvideo compression by TANG Shu, ZHAO Yu, YANG Shuli, XIE Xian-Zhong

“…However, most existing deep learning-based stereoscopic video compression networks only use convolutional operations to extract and fuse features, which limits their ability to effectively capture non-repetitive texture details within local areas and cannot capture global features, thus affects the quality of image reconstruction during decoding seriously. …”
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Platonic dynamical decoupling sequences for interacting spin systems by Colin Read, Eduardo Serrano-Ensástiga, John Martin

“…In this work, we design efficient decoupling sequences composed solely of global $\mathrm{SU}(2)$ rotations and based on tetrahedral, octahedral, and icosahedral point groups, which we call Platonic sequences. …”
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A Multiscale CNN-Based Intrinsic Permeability Prediction in Deformable Porous Media by Yousef Heider, Fadi Aldakheel, Wolfgang Ehlers

“…Examples demonstrate the CNN’s ability to accurately predict the permeability tensor in connection with the deformation state through the porosity parameter. …”
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Advanced microfluidic strategies for core-shell nanoparticles: the next-generation of polymeric and lipid-based drug nanocarriers by Giuseppe Nunziata, Alessandro Borroni, Filippo Rossi

“…This level of precision is particularly relevant in drug delivery, where the ability to fine-tune nanoparticle size, composition, and surface properties directly influences therapeutic efficacy. …”
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Formation dynamics of biomass of lentil crops depending on the plant density in the steppe zone of Kazakhstan by Nurlan Serekpayev, Nurbolat Mukhanov, Almas Kurbanbayev, Balzhan Akhylbekova

“…The right planting density and the optimal number of seeds introduced during sowing play a crucial role in ensuring the efficient production of lentils. This factor significantly affects the process of culture rooting, the ability of plants to absorb solar radiation, the development of vegetation cover, as well as the level of infection with harmful insects, pests, and diseases. …”
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Fungal Biomass Fermentation: Valorizing the Food Industry’s Waste by Simas Borkertas, Jonas Viskelis, Pranas Viskelis, Paulina Streimikyte, Ugne Gasiunaite, Dalia Urbonaviciene

“…This fermentation method offers advantages like lower production costs, reduced waste disposal issues, and the efficient utilization of agricultural residues and fruit and vegetable by-products. …”
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Enhancing diabetes risk prediction through focal active learning and machine learning models. by Wangyouchen Zhang, Zhenhua Xia, Guoqing Cai, Junhao Wang, Xutao Dong

“…Additionally, the model's generalization ability was further validated on the public PIMA Indians Diabetes DataBase, outperforming traditional models in both accuracy and recall. …”
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Hybrid Deep Neural Network with Domain Knowledge for Text Sentiment Analysis by Jawad Khan, Niaz Ahmad, Youngmoon Lee, Shah Khalid, Dildar Hussain

“…These findings highlight the effectiveness of this approach for text sentiment analysis tasks, demonstrating its ability to improve sentiment analysis performance compared to previously proposed methods.…”
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Unravelling the potential of prussian blue analogues in oxygen electrocatalysis: A perspective on surface reconstruction by Priya Jain, Pravin Popinand Ingole

“…This perspective will guide the new entrants in the field to understand the process of surface transformation for establishing structure-property-activity relationships and thus to develop highly efficient PBA-based electrocatalysts.…”
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Tips and Pitfalls in Using Social Media Platforms for Survey Dissemination by William Lay Keat Ong, Vineet Gauhar, Daniele Castellani, Jeremy Y.C. Teoh

“…MethodsWe performed a scoping review of this topic and explored different strategies commonly employed for conducting efficient health care surveys via social media platforms. …”
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Synthesis and antimicrobial evaluation of fluoro chalcone-based 1,5-benzodiazepines: a green chemistry approach using microwave technique by Gajanan Kottapalle, Rajashree Markandewar, Nagesh Deshmukh, Avinash Shinde

“…A simple and efficient method has been developed for the synthesis of fluorine-containing 1,5-benzodiazepine compounds, starting from fluorine-substituted chalcones and ortho-phenylenediamine. …”
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