The Development of an Air Suction Precision Seed-Metering Device for Rice Plot Breeding by Wei Qin, Yuwu Li, Cheng Qian, Zhuorong Fan, Daoqing Yan, Guo Zou, Siqian Liu, Zaiman Wang, Ying Zang, Minghua Zhang

“…At a rotational speed of 20 r·min⁻¹ and negative pressure of 3200 Pa, seed-filling performance was optimal for all rice varieties. Among them, the rice variety Nayou 6388 exhibited the best seed-filling performance, with a 0.8% missing seed rate, 97.6% single and double seed rate, and 1.6% multiple seed rate. …”
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Enhanced leukemia prediction using hybrid ant colony and ant lion optimization for gene selection and classification by Santhakumar D, Gnanajeyaraman Rajaram, Elankavi R, Viswanath J, Govindharaj I, Raja J

“…The proposed hybrid approach enhances feature selection by improving accuracy, reducing computational complexity, and boosting classifier performance. …”
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Ultra‐Flexible µ‐ECoG Arrays Based on PEDOT:PSS Micropillars by Alice Lunghi, Michele Bianchi, Pierpaolo Greco, Riccardo Viaro, Michele Di Lauro, Luciano Fadiga, Fabio Biscarini

“…Here, the synergic contribution of surface micropatterning and of conductive polymers on the recording performance of a home‐built µECoG device is explored. …”
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Lightweight insulator target detection algorithm based on improved YOLOX by Bing Zeng, Wei Hua, Dezhi Li, Zhihao Zhou, Hao Wan, Yunmin Xie, Tangbing Li, Yucong Chen, Jianglei Li, Shenli Wang, Shixun Fu, Zihan Jin, Wenhua Zhang

“…Meanwhile, an Enhanced Convolutional Block Attention Module (E-CBAM) is embedded between the backbone and neck networks to significantly enhance feature extraction capabilities, overcoming the performance limitations of lightweight networks. …”
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Deep Learning Hybrid Architecture Based on Vision Transformer for Phase Analysis of Moiré Fringes by Dajie Yu, Junbo Liu, Chuan Jin, Yuyang Li, Kairui Zhang, Ji Zhou

“…Overlay accuracy is a fundamental indicator of a photolithography machine performance. Misalignment between the mask and wafer is the main factor affecting overlay accuracy. …”
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A One-Stage HMDV Algorithm Applied in Multitarget Detection in SAR Images by Lei Pang, Weihe Huang, Fengli Zhang, Yinhong Song

“…Experimental results demonstrate that the proposed model improves mean average precision accuracy by 2.4% and reduces the number of parameters to 13% of the original, confirming the model’s effectiveness and robustness.…”
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Accelerated and precise skin cancer detection through an enhanced machine learning pipeline for improved diagnostic accuracy by SM Masfequier Rahman Swapno, S.M. Nuruzzaman Nobel, P.K. Meena, V.P. Meena, Jitendra Bahadur, Abhishek Appaji

“…The ensemble model effectively classifies benign and malignant skin lesions, leveraging EfficientNetV2L's feature extraction capabilities and LGBM's computational efficiency. …”
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Neural correlates of visual object recognition in rats by Juliana Y. Rhee, César Echavarría, Edward Soucy, Joel Greenwood, Javier A. Masís, David D. Cox

“…This work reinforces the sophisticated visual abilities of rats and offers the technical foundation to use them as a powerful model for mechanistic perception.…”
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MAPM:PolSAR Image Classification with Masked Autoencoder Based on Position Prediction and Memory Tokens by Jianlong Wang, Yingying Li, Dou Quan, Beibei Hou, Zhensong Wang, Haifeng Sima, Junding Sun

“…In the fine-tuning stage, the addition of learnable memory tokens can improve classification performance. In addition, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi mathvariant="italic">L</mi><mn>1</mn></msub></semantics></math></inline-formula> loss is used for MAE optimization to enhance the robustness of the model to outliers in PolSAR data. …”
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Dynamic Real-Time Anchor Selection for Accurate UWB Indoor Positioning-Based Deep Neural Networks by Ammar Fahem Majeed, Rashidah Arsat, Muhammad Ariff Baharudin, Nurul Mu'Azzah Abdul Latiff, Abbas Albaidhani

“…In wireless localization systems, enhancing location estimation performance is critical, particularly in challenging environments, such as military urban operations and emergency response scenarios. …”
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A novel experimental device for solar radiation simulation: Design and evaluation by Rubén E. Sánchez-García, Rodrigo Salmón-Folgueras, Orlando Castilleja-Escobedo, José Luis López-Salinas

“…The temperature and irradiance ranges at 1.2 m from the luminaire are 31 to 60 °C and 50 to 1250 W/m² respectively, consistent with the global solar constant of 1361–1367 W/m². The system performance was compared against multiple benchmarks: the National Solar Radiation Database, the Photovoltaic Geographical Information System, a mathematical solar radiation model and computational fluid dynamics. …”
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Methodological Integration of Machine Learning and Geospatial Analysis for PM10 Pollution Mapping by Kalid Hassen Yasin, Muaz Ismael Yasin, Anteneh Derribew Iguala, Tadele Bedo Gelete, Erana Kebede

“…The study contributes valuable insights for implementing scalable pollution prediction systems in resource-constrained urban environments while acknowledging interpretability challenges inherent to complex ML models. • Preprocessing of spatial data from various sources, incorporating the handling of missing/abnormal data, analysis, and normalization • Implementation of the three ML algorithms with rigorous hyperparameter tuning, model validation, and performance assessment • Mapping PM10 Hotspots on the Gradient Direction and Distance from the City Center…”
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Estimation of Canopy Chlorophyll Content of Apple Trees Based on UAV Multispectral Remote Sensing Images by Juxia Wang, Yu Zhang, Fei Han, Zhenpeng Shi, Fu Zhao, Fengzi Zhang, Weizheng Pan, Zhiyong Zhang, Qingliang Cui

“…Additionally, the model performance was assessed by selecting the coefficient of determination (R²), root mean square error (RMSE) and mean absolute error (MAE). …”
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RSWD-YOLO: A Walnut Detection Method Based on UAV Remote Sensing Images by Yansong Wang, Xuanxi Yang, Haoyu Wang, Huihua Wang, Zaiqing Chen, Lijun Yun

“…Based on the YOLOv11 network, we propose several improvements to enhance the multi-scale object detection capability while achieving a more lightweight model structure. Specifically, we reconstruct the feature fusion network with a hierarchical scale-based feature pyramid structure and implement lightweight improvements to the feature extraction component. …”
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Versatility Evaluation of Landslide Risk with Window Sizes and Sampling Techniques Based on Deep Learning by Fudong Ren, Koichi Isobe

“…CNN models with 19 × 19 pixel windows typically yield the best overall performance, with CNN-19 achieving an AUC of 0.950, 0.982 and 0.969 for NIG, HKD, and IWT-MYG, respectively. …”
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Sex differences in the association of Alzheimer’s disease biomarkers and cognition in a multicenter memory clinic study by Cecilia Boccalini, Debora Elisa Peretti, Max Scheffler, Linjing Mu, Alessandra Griffa, Nathalie Testart, Gilles Allali, John O. Prior, Nicholas J. Ashton, Henrik Zetterberg, Kaj Blennow, Giovanni B. Frisoni, Valentina Garibotto

“…Mann-Whitney U tests investigated sex differences in clinical and biomarker data. Linear regression models estimated the moderating effect of sex on the relationship between biomarkers and cognitive performance and decline. …”
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Explainable vision transformer for automatic visual sleep staging on multimodal PSG signals by Hyojin Lee, You Rim Choi, Hyun Kyung Lee, Jaemin Jeong, Joopyo Hong, Hyun-Woo Shin, Hyung-Sin Kim

“…Tested on KISS–a PSG image dataset from 7745 patients across four hospitals–SleepXViT achieved a Macro F1 score of 81.94%, outperforming baseline models and showing robust performances on public datasets SHHS1 and SHHS2. …”
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Non-Destructive Monitoring of Sweet Pepper Samples After Selected Periods of Lacto-Fermentation by Ewa Ropelewska, Justyna Szwejda-Grzybowska, Anna Wrzodak, Monika Mieszczakowska-Frąc

“…The fermentation process was monitored based on image features, which were used to develop machine learning models distinguishing samples before and after various periods of lacto-fermentation (0, 3, 7, 10, 14, 21, 28, and 56 days). …”
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Detecting anomalies in graph networks on digital markets. by Agata Skorupka

“…The study proves that graph-based data is a better-performing predictor than text data. It compares different graph algorithms to extract feature sets for anomaly detection models. …”
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SB‐YOLO‐V8: A Multilayered Deep Learning Approach for Real‐Time Human Detection by Prince Alvin Kwabena Ansah, Justice Kwame Appati, Ebenezer Owusu, Edward Kwadwo Boahen, Prince Boakye‐Sekyerehene, Abdullai Dwumfour

“…ABSTRACT Over the past decade, significant advancements in computer vision have been made, primarily driven by deep learning‐based algorithms for object detection. However, these models often require large amounts of labeled data, leading to performance degradation when applied to tasks with limited data sets, particularly in scenarios involving moving objects. …”
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