Influence of Apis mellifera in-hive conditions on germination capacity of rapeseed pollen (Brassica napus) by Luciano Alberto Marinozzi, Soledad Camila Villamil, Liliana María Gallez

“… • Fresh pollen had the thickest and most developed pollen tubes. After 24 h in the hive, pollen grains had thinner, shorter, and convoluted pollen tubes. …”
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An extended TOPSIS technique based on correlation coefficient for interval-valued q-rung orthopair fuzzy hypersoft set in multi-attribute group decision-making by Rana Muhammad Zulqarnain, Imran Siddique, Sameh Askar, Ahmad M. Alshamrani, Dragan Pamucar, Vladimir Simic

“…This study determines incineration as the most beneficial method for BMW disposal, demonstrating its more efficient use of alternative disposal techniques. …”
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Quantum Classical Algorithm for the Study of Phase Transitions in the Hubbard Model via Dynamical Mean-Field Theory by Anshumitra Baul, Herbert Fotso, Hanna Terletska, Ka-Ming Tam, Juana Moreno

“…Modeling many-body quantum systems is widely regarded as one of the most promising applications for near-term noisy quantum computers. …”
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Pano-GAN: A Deep Generative Model for Panoramic Dental Radiographs by Søren Pedersen, Sanyam Jain, Mikkel Chavez, Viktor Ladehoff, Bruna Neves de Freitas, Ruben Pauwels

“…While this is an exploratory study, the ultimate aim is to address the scarcity of data in dental research and education. A deep convolutional GAN (DCGAN) with the Wasserstein loss and a gradient penalty (WGAN-GP) was trained on a dataset of 2322 radiographs of varying quality. …”
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Deep Learning and Recurrence Information Analysis for the Automatic Detection of Obstructive Sleep Apnea by Daniele Padovano, Arturo Martinez-Rodrigo, José M. Pastor, José J. Rieta, Raul Alcaraz

“…The present paper addresses this gap by integrating convolutional neural networks (CNNs) with HRV recurrence analysis. …”
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Identify suitable artificial groundwater recharge zones using hybrid deep learning models by Navaz Khalillollahi, Mohsen Isari, Hamed Faroqi, Kaywan Othman Ahmed, Kamran Nobakht Vakili, Miklas Scholz, Saad Sh. Sammeng

“…This study evaluated four deep learning models for delineating groundwater recharge zones: Artificial Neural Network (ANN), Convolutional Neural Network (CNN), Gated Recurrent Unit (GRU), and hybrid deep learning Convolutional Neural Network-Gated Recurrent Unit (CNN-GRU). …”
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Leveraging sentiment analysis of food delivery services reviews using deep learning and word embedding by Dheya Mustafa, Safaa M. Khabour, Mousa Al-kfairy, Ahmed Shatnawi

“…Arabic is becoming one of the most extensively written languages on the World Wide Web, but because of its morphological and grammatical difficulty as well as the lack of openly accessible resources for Arabic SA, like as dictionaries and datasets, there has not been much research done on the language. …”
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Biological features and medical significance of the <i>Listeria</i> bacteria by I. A. Derevyanchenko, Lyudmila A. Kraeva

“…After thawing and subsequent cultivation of Listeria on fresh nutrient medium, a pronounced populational heteromorphism is noted: formation of protoplast-type cells, L-forms and convoluted revertant cells, which requires the use PCR and ELISA for bacteria detection. …”
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ZZ-YOLOv11: A Lightweight Vehicle Detection Model Based on Improved YOLOv11 by Zhe Zhang, Zhongyang Zhang, Gang Li, Chenxi Xia

“…After that, the most effective layer-adaptive magnitude-based pruning (LAMP) method is used to build away the redundant parameters to make the detection network more lightweight. …”
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Trajectory Tracking Control Based on Visual Localization and Adaptive Radial Basis Function Sliding Mode Control by Hung-Yih Tsai, Shih-Min Liao, Chang-Hong Liu

“…Autonomous driving is a prominent research focus in the field of intelligent vehicles, with trajectory tracking serving as a fundamental control strategy. However, most existing tracking methods rely heavily on GPS signals, making them susceptible to signal loss due to environmental obstacles such as buildings. …”
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A spatiotemporal model for urban taxi Origin–Destination prediction based on Multi-hop GCN and Hierarchical LSTM by Jiang Rong, Wangtu Xu, Yanjie Wen

“…Moreover, visualizations demonstrate that the model achieves over 85% accuracy of OD matrix, origin–destination demand prediction in most cases. Our model and dataset are open sourced at https://github.com/YanJieWen/OD-STGCN.…”
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Fish Detection Using Deep Learning by Suxia Cui, Yu Zhou, Yonghui Wang, Lujun Zhai

“…An advanced system with more computing power can facilitate deep learning feature, which exploit many neural network algorithms to simulate human brains. In this paper, a convolutional neural network (CNN) based fish detection method was proposed. …”
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Deep Learning-Based Denoising for Optical Coherence Tomography: Evaluating Self-Supervised and Generative Models Across Retinal Datasets by Diogen BABUC, Alesia LOBONŢ, Alexandru FARCAŞ, Todor IVAŞCU, Sebastian-Aurelian ŞTEFĂNIGĂ

“…Preliminary results indicated that ZS-N2N and CycleGAN consistently achieve the lowest loss and highest accuracy, making them the most effective for denoising across different pathologies. …”
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Unsupervised Domain Adaptation via Contrastive Learning and Complementary Region-Class Mixing by Xiaojing Li, Wei Zhou, Mingjian Jiang

“…In semantic segmentation, current deep convolutional neural networks rely heavily on extensive data to achieve superior segmentation results. …”
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Diagnosing Gingiva Disease Using Artificial Intelligence Techniques by Rana Khalid Sabri, Lujain Younis Abdulkadir, AbdulSattar Mohammed Khidhir, Hiba Abdulkareem Saleh

“…MobileNet emerged as the most effective model, achieving a test accuracy of 92.73%; the suggested method relies mainly on its positive result. …”
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A novel deep learning approach for predicting stone-free rates post-ESWL on uncontrasted CT by Ozgur Efiloglu, Muhammed Yildirim, Kadir Yildirim, Harun Bingol, Mustafa Kaan Akalin, Meftun Culpan, Bilal Alatas, Asif Yildirim

“…Extracorporeal shock wave lithotripsy (ESWL) is one of the most often employed therapy methods for managing kidney stones. …”
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Benchmarking Accelerometer and CNN-Based Vision Systems for Sleep Posture Classification in Healthcare Applications by Minh Long Hoang, Guido Matrella, Dalila Giannetto, Paolo Craparo, Paolo Ciampolini

“…This method yielded superior performance, reaching an accuracy exceeding 99.8% across most sleep positions. The “wake up” position was particularly easy to detect due to the absence of body movements such as heartbeat or respiration when the person is no longer in bed. …”
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Developing a Drowsiness Detection System for Safe Driving Using YOLOv9 by Fernando Candra Yulianto, Wiwit Agus Triyanto, Syafiul Muzid

“…Several drowsiness detection systems built using the eye aspect ratio (EAR), percentage of eyelid closure (PERCLOS), and convolutional neural network (CNN) methods still have limitations in terms of accuracy and response time. …”
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Spatial-Channel Multiscale Transformer Network for Hyperspectral Unmixing by Haixin Sun, Qiuguang Cao, Fanlei Meng, Jingwen Xu, Mengdi Cheng

“…In recent years, deep learning (DL) has been demonstrated remarkable capabilities in hyperspectral unmixing (HU) due to its powerful feature representation ability. Convolutional neural networks (CNNs) are effective in capturing local spatial information, but limited in modeling long-range dependencies. …”
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Application of deep learning in malware detection: a review by Yafei Song, Dandan Zhang, Jian Wang, Yanan Wang, Yang Wang, Peng Ding

“…Taken together, this will help researchers at the current stage gain insight into the unresolved challenges or barriers faced by previous researchers. Among these, the most common problem is the lack of broader and consistent datasets, followed by the need for existing models for further improvement.…”
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