Revolutionizing Sperm Analysis with AI: A Review of Computer-Aided Sperm Analysis Systems by Francisco J. Baldán, Diego García-Gil, Carlos Fernandez-Basso

“…Overall, this review outlines current innovations and future research directions essential for advancing personalized, efficient, and accessible fertility care.…”
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FIRM image analysis: A machine learning workflow for quantifying extracellular matrix components from electron microscopy images. by Nicholas T Gigliotti, Justin Lee, Emily H Mang, Giancarlo R Zambrano, Mitra L Taheri

“…The extracellular matrix (ECM) is a complex network of biomolecules that plays an integral role in the structure, processes, and signaling mechanisms of cells and tissues. …”
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A lightweight certificateless aggregate signature scheme without pairing for VANETs by Qiuling Yue, Weijian Jiang, Hong Lei

“…Abstract In the secure vehicular ad-hoc networks (VANETs), certificateless aggregate signature schemes(CLAS) have attracted more and more attention because they can efficiently implement message aggregation and authentication without complex certificate management. …”
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Leveraging Neural Trojan Side-Channels for Output Exfiltration by Vincent Meyers, Michael Hefenbrock, Dennis Gnad, Mehdi Tahoori

“…To achieve low latency and high efficiency, field-programmable gate arrays (FPGAs) are increasingly being employed as accelerators for neural network inference in cloud and edge devices. …”
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Fusion of non-iterative deep neural network feature extraction with kernel extreme learning machine for plant disease classification by Kirti Kirti, Navin Rajpal, Virendra P. Vishwakarma, Pramod Kumar Soni

“…Abstract Plant disease identification and detection refer to the process of recognizing and diagnosing diseases that affect plants. …”
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Investigating Single-Molecule Molecular Inversion Probes for Medium-Scale Targeted DNA Methylation Analysis by Roy B. Simons, Hieab H. H. Adams, Manfred Kayser, Athina Vidaki

“…Conclusions: The observed low specificity and uniformity indicate that smMIPs in their current form are not compatible with the lowered complexity of bisulfite-converted DNA.…”
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Study on the Leakage Diagnosis of a Chilled Water Pipeline Network System Based on Pressure Variation Rate Analysis for Climate Change Mitigation by Xuan Zhou, Fei Liu, Lisheng Luo, Shiman Peng, Junlong Xie

“…Such leakages reduce system lifespan, raise maintenance costs, and degrade operational efficiency. To overcome the limitations of current methods, such as insufficient interpretability and computational complexity in leak localization, this paper proposes a novel leakage diagnosis and localization scheme based on pressure variation rate analysis in closed chilled water pipeline networks. …”
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Orthogonal-state-based measurement device independent quantum communication: a noise-resilient approach by Chitra Shukla, Abhishek Shukla, Symeon Chatzinotas, Milos Nesladek

“…Ultimately, we discuss system and operational complexity of our proposed protocols in light of experimental elements and the processes.…”
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Enhancing chronic wound assessment through agreement analysis and tissue segmentation by Ana C. Morgado, Rafaela Carvalho, Ana Filipa Sampaio, Maria J. M. Vasconcelos

“…Moreover, the obtained inter-rater agreement scores still emphasize the inherent complexity of the task, as even experienced healthcare professionals may differ in delineating tissue boundaries. …”
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A framework for the simulation of individual glycan coordinates to analyze spatial relationships within the glycocalyx by Sarah Fritsche, Sarah Fritsche, Leonhard Möckl, Leonhard Möckl, Leonhard Möckl, Leonhard Möckl

“…Importantly, we include various experimental considerations, such as labeling and detection efficiency. This approach may contribute to establishing a new standard of connection between geometrical and molecular-resolution data in service of advancing our understanding of the functional role of the glycocalyx in biology as well as its clinical potential.…”
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Deep Learning with Dual-Channel Feature Fusion for Epileptic EEG Signal Classification by Bingbing Yu, Mingliang Zuo, Li Sui

“…While deep learning methods have shown promise, many current models suffer from limitations such as excessive complexity, high computational demands, and insufficient generalizability. …”
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Slope Stability Monitoring Methods and Technologies for Open-Pit Mining: A Systematic Review by Rohan Le Roux, Mohammadali Sepehri, Siavash Khaksar, Iain Murray

“…Slope failures in open-pit mining pose significant operational and safety issues, underscoring the importance of implementing effective stability monitoring frameworks for early hazard detection to allow for timely intervention and risk mitigation. …”
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Multijunction solar cell parameter estimation based on metaheuristic algorithms by Marwa M. Elzalabani, Doaa M. Atia, Aref Y. Eliwa, Belal A. Abou Zalam, Mahmoud S. AbouOmar

“…Several mathematical models exist for MJSC parameter estimation— Single Diode Model (SDM), Double Diode Model (DDM), and Triple Diode Model (TDM)—each offering a trade-off between complexity and accuracy, improved efficiency, and reliable operation. …”
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Enhancing bloodstream infection diagnostics: a novel filtration and targeted next-generation sequencing approach for precise pathogen identification by Ting-Syuan Lin, Ting-Syuan Lin, Ting-Syuan Lin, ZiHao Zhu, ZiHao Zhu, ZiHao Zhu, XiaoHong Lin, Hsi-Yuan Huang, Hsi-Yuan Huang, Hsi-Yuan Huang, Li-Ping Li, Li-Ping Li, Li-Ping Li, Jing Li, Jing Li, Jing Li, Jie Ni, Jie Ni, Jie Ni, PeiZhi Li, LanChun Chen, WeiXin Tang, HuiXin Liu, XiaoLong Se, MingFei Xie, Canling Long, Chih-Min Chiu, Szu-Han Fang, JiaMing Zhao, Yang-Chi-Dung Lin, Yang-Chi-Dung Lin, Yang-Chi-Dung Lin, XueTao Yu, Hsien-Da Huang, Hsien-Da Huang, Hsien-Da Huang, Hsien-Da Huang

“…The filtration membrane, designed with surface charge properties to be electrostatically attractive to leukocytes for the selective capture of specific cells, demonstrated high efficiency in removing host cells and nucleic acids, achieving over a 98% reduction in host DNA and thereby minimizing background interference in pathogen detection. …”
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CAEB7-UNet: An Attention-Based Deep Learning Framework for Automated Segmentation of C-Spine Vertebrae in CT Images by Abhishek Kumar Pandey, Kedarnath Senapati, G. P. Pateel

“…This study presents a novel channel attention-based EfficientNetB7-UNet (CAEB7-UNet) method to address this complex task effectively. …”
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Unbiased analysis of obesity related, fat depot specific changes of adipocyte volumes and numbers using light sheet fluorescence microscopy. by Natalie Theobalt, Isabel Hofmann, Sonja Fiedler, Simone Renner, Georg Dhom, Annette Feuchtinger, Axel Walch, Martin Hrabĕ de Angelis, Eckhard Wolf, Rüdiger Wanke, Andreas Blutke

“…LSFM allows for accurate and efficient determination of relevant quantitative morphological adipocyte parameters. …”
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Biologically inspired hybrid model for Alzheimer’s disease classification using structural MRI in the ADNI dataset by Houmem Slimi, Imen Cherif, Sabeur Abid, Mounir Sayadi

“…Classification metrics (precision, recall, F1-score) highlight the model’s ability to disentangle complex spatiotemporal patterns in neurodegeneration. …”
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Investigating the Capabilities of Ensemble Machine Learning Model in Identifying Near-Fault Pulse-Like Ground Motions by Jafar Al Thawabteh, Jamal Al Adwan, Yazan Alzubi, Ahmad Al-Elwan

“…In recent years, the detection and analysis of near-fault pulse-like ground motions have become increasingly crucial due to their potential to cause significant structural damage during seismic events. …”
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IoT-Enhanced Smart Parking Management With IncepDenseMobileNet for Improved Classification by Xiaoxia Zheng, Wenxi Feng, Ning Wang, Huhemandula

“…The IncepDenseMobileNet (IDMN) model integrates Inception, DenseNet, and MobileNet architectures to proficiently capture complex patterns via multi-scale feature extraction and efficient depthwise separable convolutions. …”
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Chemometric and computational modeling of polysaccharide coated drugs for colonic drug delivery by Ahmad Khaleel AlOmari, Khaled Almansour

“…Parity plots and learning curves further validate MLP’s predictive reliability, demonstrating close alignment between actual and predicted values and efficient learning with minimal overfitting. Consequently, the MLP model emerges as the most effective approach for this predictive task, offering a robust tool for accurately modeling complex spectral data. …”
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