Differentiation and histological analysis of primary human bronchial epithelial cells cultured on transwell membranes using air-liquid interface culture by Asha Ashraf, Erica D. Bruce

“…Sections are subsequently stained using hematoxylin and eosin (H&E) to assess epithelial morphology, or periodic acid–Schiff (PAS) staining to visualize polysaccharide-containing structures such as mucins. …”
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BioCurve Analyzer: a web-based shiny app for analyzing biological response curves by Zenan Xing, James Eckhardt, Aditya S. Vaidya, Sean R. Cutler

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In Vivo Imaging of Cobalt-Induced Ocular Toxicity in a Mouse Model by Basel Obied, Galit Saar, Stephen Richard, Ygal Rotenstreich, Ifat Sher, Alon Zahavi, Nitza Goldenberg-Cohen

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A two-step machine learning approach for predictive maintenance and anomaly detection in environmental sensor systems by Saiprasad Potharaju, Ravi Kumar Tirandasu, Swapnali N. Tambe, Devyani Bhamare Jadhav, Dudla Anil Kumar, Shanmuk Srinivas Amiripalli

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Bioluminescent imaging of an oomycete pathogen empowers chemical selections and rational fungicide applications by Han Chen, Jiana Mao, Yujie Fang, Waqas Raza, Zhi Li, Chongyuan Zhang, Yingguang Zhu, Yuanchao Wang, Suomeng Dong

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Development of an explainable machine learning model for Alzheimer’s disease prediction using clinical and behavioural features by Rajkumar Govindarajan, K. Thirunadanasikamani, Komal Kumar Napa, S. Sathya, J. Senthil Murugan, K. G. Chandi Priya

“…Key predictive variables such as Mini-Mental State Examination (MMSE), Activities of Daily Living (ADL), cholesterol levels, and functional assessment scores were identified and visualized using SHAP-based insights. A user-friendly, interactive web application was developed using Streamlit, allowing real-time patient data input and transparent model output visualization. …”
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An open-source workflow for identifying hydrodynamic water quality events in rivers by continuous water quality monitoring and time-series data processing using R and US EPA CANARY by L. Cronin, C.M. Taylor, C. Briciu Burghina, F.E. Lucy, F. Regan

“…Improving European surface water quality requires urgent action to address diffuse pollution sources particularly from agriculture, with increased frequency and intensity of hydroclimatic events also a key driver of pollutant export to waters and water quality decline worldwide.However, the need for comprehensive, practical protocols for sensor deployment, sensor maintenance and data management for the adoption of high frequency water quality monitoring has been highlighted, along with the challenges for citizen scientists in analyzing millions of water quality data points and sharing metadata. The practical method presented, with reproducibility built into the workflow, is designed for multiple users and a step-by-step application of the workflow is demonstrated including: • Deployment arrangement for water quality sondes in two temporary monitoring stations with different site characteristics. • Data collection and data validation methods. • Concise, reproducible, open-source workflow detailing the use of R, R markdown and US EPA CANARY software for data import, data cleaning, data visualization, data integrity, along with site-specific CANARY event system configuration for the detection of potential water quality events.Results for two monitoring stations on different rivers show CANARY successfully identified 100 % (n 47) and 97 % (n 39) of the manually identified turbidity events.…”
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GradCAM-PestDetNet: A deep learning-based hybrid model with explainable AI for pest detection and classification by Ramitha Vimala, Saharsh Mehrotra, Satish Kumar, Pooja Kamat, Arunkumar Bongale, Ketan Kotecha

“…Traditional pest detection methods are often slow, less accurate and reliant on expert knowledge. …”
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LViT-Net: a domain generalization person re-identification model combining local semantics and multi-feature cross fusion by Xintong Hu, Peishun Liu, Xuefang Wang, Peiyao Wu, Ruichun Tang

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Artificial intelligence-assisted diagnosis of early allograft dysfunction based on ultrasound image and data by Yaqing Meng, Mingyang Wang, Ningning Niu, Haoyan Zhang, Jinghan Yang, Guoying Zhang, Jing Liu, Ying Tang, Kun Wang

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Real-time volume rendering for three-dimensional fetal ultrasound using volumetric photon mapping by Jing Zou, Jing Qin

“…This study presents a novel real-time volume-rendering method equipped with a global illumination model for 3D fetal ultrasound visualization. …”
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Placenta segmentation redefined: review of deep learning integration of magnetic resonance imaging and ultrasound imaging by Asmaa Jittou, Khalid El Fazazy, Jamal Riffi

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Graph neural network-tracker: a graph neural network-based multi-sensor fusion framework for robust unmanned aerial vehicle tracking by Karim Dabbabi, Tijeni Delleji

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Principal component analysis and fine-tuned vision transformation integrating model explainability for breast cancer prediction by Huong Hoang Luong, Phuc Phan Hong, Dat Vo Minh, Thinh Nguyen Le Quang, Anh Dinh The, Nguyen Thai-Nghe, Hai Thanh Nguyen

“…Our approach exhibited a 0.98% to 17.13% improvement in accuracy compared with state-of-the-art methods, establishing a new benchmark for breast cancer histopathological image classification.…”
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Bootstrapping BI-RADS classification using large language models and transformers in breast magnetic resonance imaging reports by Yuxin Liu, Xiang Zhang, Weiwei Cao, Wenju Cui, Tao Tan, Yuqin Peng, Jiayi Huang, Zhen Lei, Jun Shen, Jian Zheng

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Advancing breast cancer diagnosis: token vision transformers for faster and accurate classification of histopathology images by Mouhamed Laid Abimouloud, Khaled Bensid, Mohamed Elleuch, Mohamed Ben Ammar, Monji Kherallah

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RStoolbox: An R package for remote sensing data analysis by Konstantin Müller, Jakob Schwalb‐Willmann, Martin Wegmann, Benjamin Leutner

“…Therefore, it is crucial to not only gather data but also to analyse, visualize and present the findings. rstoolbox R package offers a suite of functions for (a) preprocessing, (b) analysis and (c) visualization of (multi‐band) remote sensing data, implementing state‐of‐the‐art methods such as unsupervised and supervised classification, or spectral unmixing or change vector analysis. …”
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Automated pipeline for leaf spot severity scoring in peanuts using segmentation neural networks by Joshua Larsen, Jeffrey Dunne, Robert Austin, Cassondra Newman, Michael Kudenov

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Migration Mapper: Identifying movement corridors and seasonal ranges for large mammal conservation by Jerod A. Merkle, Josh Gage, Hall Sawyer, Blake Lowrey, Matthew J. Kauffman

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Temporal resolution trumps spectral resolution in UAV-based monitoring of cereal senescence dynamics by Flavian Tschurr, Lukas Roth, Nicola Storni, Olivia Zumsteg, Achim Walter, Jonas Anderegg

“…Correlation coefficients of up to 0.8 were observed between multispectral (NDVIred668-index) and visual scoring, respectively 0.9 between RGB (ExGR-index) and visual scoring. …”
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