Quantitative image analysis of the extracellular matrix of esophageal squamous cell carcinoma and high grade dysplasia via two-photon microscopy by Kausalya Neelavara Makkithaya, Wei-Chung Chen, Chun-Chieh Wu, Ming-Chi Chen, Wei-Hsun Wang, Jackson Rodrigues, Ming-Tsang Wu, Nirmal Mazumder, I-Chen Wu, Guan-Yu Zhuo

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Developments in solar-driven desalination: Technologies, photovoltaic integration, and processes by Mohamed El-Sayed M. Essa, Hemdan S. El-sayed, Elwy E. El-kholy, Mohammed Amer, Mahmoud Elsisi, Uzair Sajjad, Khalid Hamid, Hilmy El-sayed Awad

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Research trends and prospects in global riverine carbon fluxes: A bibliometric analysis by Wei Fang, Mohd Remy Rozainy Mohd Arif Zainol, Xianbao Zha, Pingping Luo

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From Simulation to Field Validation: A Digital Twin-Driven Sim2real Transfer Approach for Strawberry Fruit Detection and Sizing by Omeed Mirbod, Daeun Choi, John K. Schueller

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Design and Characterization of the Modified Purdue Subcritical Pile for Nuclear Research Applications by Matthew Niichel, Vasileios Theos, Riley Madden, Hannah Pike, True Miller, Brian Jowers, Stylianos Chatzidakis

“…First demonstrated in 1942, subcritical and zero-power critical assemblies, also known as piles, are a fundamental tool for research and education at universities. Traditionally, their role has been primarily instructional and for measuring the fundamental properties of neutron diffusion and transport. …”
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What are new opportunities for clinical practice the VERIFY study opens and which values for native diabetes patients? Joint conclusion on the advisory board results. November 6, 2... by Marina V. Shestakova, Mikhail B. Antsiferov, Alexander S. Ametov, Gagik R. Galstyan, Tatiana Y. Demidova, Alexey V. Zilov, Tatiana N. Markova, Nina A. Petunina, Natalya A. Chernikova, Minara S. Shamkhalova

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Capsule neural network and its applications in drug discovery by Yiwei Wang, Binyou Wang, Jun Zou, Anguo Wu, Yuan Liu, Ying Wan, Jiesi Luo, Jianming Wu

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Hierarchical Classification of Variable Stars Using Deep Convolutional Neural Networks by Mahdi Abdollahi, Nooshin Torabi, Sadegh Raeisi, Sohrab Rahvar

“…There have been many attempts to classify variable stars by traditional algorithms like Random Forest. In recent years, neural networks as classifiers have come to notice because of their lower computational cost compared to traditional algorithms. …”
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Development of clinical decision support for patients older than 65 years with fall-related TBI using artificial intelligence modeling. by Biche Osong, Eric Sribnick, Jonathan Groner, Rachel Stanley, Lauren Schulz, Bo Lu, Lawrence Cook, Henry Xiang

“…Data were split into two sets, where 80% developed a decision tree, and 20% tested predictive performance. We employed a conditional inference tree algorithm with bootstrap (B = 100) and grid search options to grow the decision tree and measure discrimination ability using the area under the curve (AUC) and calibration plots.…”
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Digital mapping of peat thickness and extent in Finland using remote sensing and machine learning by Jonne Pohjankukka, Timo A. Räsänen, Timo P. Pitkänen, Arttu Kivimäki, Ville Mäkinen, Tapio Väänänen, Jouni Lerssi, Aura Salmivaara, Maarit Middleton

“…Additionally, we provided an approach for evaluating spatial prediction uncertainty based on the models’ internal prediction agreement. …”
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FLAML version 2.3.3 model-based assessment of gross primary productivity at forest, grassland, and cropland ecosystem sites by J. Lai, J. Lai, Y. Zhang, A. Wang, W. Fei, Y. Diao, R. Li, J. Wu

“…It has the potential to be applied in predicting GPP for different vegetation types at a regional scale.…”
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A Synergy Between Machine Learning and Formal Concept Analysis for Crowd Detection by Anas M. Al-Oraiqat, Oleksandr Drieiev, Sattam Almatarneh, Mohammadnoor Injadat, Karim A. Al-Oraiqat, Hanna Drieieva, Yassin M. Y. Hasan

“…We also define bottom-up parsing algorithms to recommend the suitable crowd prevention plan w.r.t. the crowd level. …”
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Monitoring soil salinization in Arid cotton fields using Unmanned Aerial Vehicle hyperspectral imagery by Jinming Zhang, Jianli Ding, Jiao Tan, Jinjie Wang, Zihan Zhang, Zeyuan Wang, Xiangyu Ge

“…The results indicate: (1) SG smoothing and FOD technology effectively enhanced the spectral characteristics of cotton field soils and crop canopies. (2) The soil salinity prediction model constructed using 0.7-order FOD combined with the BOSS algorithm yields the best performance, with an R2 of 0.92, RMSE of 0.15 dS m−1, and RPD of 3.54 on the test set. (3) The soil salinity distribution map generated from the optimal model clearly revealed the spatial distribution characteristics of salinity in the 0–10 cm topsoil layer, with significant differences observed under different cover conditions. …”
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Leveraging computer-aided drug design for the discovery of phytohormone analogs: A review by Yuling Guo, Ghulam Qanmber, Zhao Liu, Han Yang, Jun Li, Zhikun Yang, Zhongxian Li, Linlin Yang, Zuoren Yang

“…These include the need for more accurate models and advanced algorithms to predict hormone-receptor interactions and metabolic pathways. …”
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Two-step consensus clustering approach to immune cell infiltration: An integrated exploration and validation of prognostic and immune implications in sarcomas by Ao-Yu Li, Jie Bu, Hui-Ni Xiao, Zi-Yue Zhao, Jia-Lin Zhang, Bin Yu, Hui Li, Jin-Ping Li, Tao Xiao

“…We further validated the biomarkers for ImmCI and gene-driven clusters via experimental verification and the accuracy of the ImmCI score in predicting survival outcomes and immunotherapy efficacy by external validation cohorts (testing cohort). …”
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A mineral-strength conversion model based on LIBS technology and rapid batch testing and application of uniaxial compressive strength by Qinghe ZHANG, Xiaorui WANG, Chuanbing WANG, Weiguo LI, Fengqiang GONG, Xinsheng ZHANG, Jingguo LI

“…The mass fraction of mineral components is analyzed via the support vector regression (SVR) algorithm. In the end, a mineral-strength conversion model is established to calculate the UCS from the predicted values of mineral component concentrations, and its rationality and scientific validity are validated by the standard mechanical tests. …”
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Performance of Noise Map Service Working in Cloud Computing Environment by Karolina MARCINIUK, Maciej SZCZODRAK, Bożena KOSTEK

“…In the paper, a noise map service designated for the user interested in environmental noise is presented. Noise prediction algorithm and source model, developed for creating acoustic maps, are working in the cloud computing environment. …”
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Transient Attracting Profiles in the Great Pacific Garbage Patch by L. Kunz, A. Griesel, C. Eden, R. Duran, R. Duran, B. Sainte-Rose

“…<p>A major challenge for cleanup operations in the Great Pacific Garbage Patch is the daily prediction of plastic concentrations that allows identifying hotspots of marine debris. …”
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Recent developments of artificial intelligence methods for sea ice concentration monitoring using high-resolution imaging datasets by Marzuraikah Mohd Stofa, Siti Raihanah Abdani, Asraf Mohamed Moubark, Muhammad Ammirrul Atiqi Mohd Zainuri, Ahmad Asrul Ibrahim, Nor Azwan Mohamed Kamari, Mohd Asyraf Zulkifley

“…Monitoring of sea ice concentration through remote sensing technology is critical in predicting sea ice-related hazards, facilitating safe ship navigation and enabling polar environmental research. …”
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Acoustic Features for Identifying Suicide Risk in Crisis Hotline Callers: Machine Learning Approach by Zhengyuan Su, Huadong Jiang, Ying Yang, Xiangqing Hou, Yanli Su, Li Yang

“…ObjectiveIn this study, we investigated the feasibility of using acoustic features to predict suicide risk in crisis hotline callers. We also adopted a machine learning approach to analyze the complex acoustic features of hotline callers, with the aim of developing suicide risk prediction models. …”
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