Forecasting Daily and Monthly Reference Evapotranspiration in the Aidoghmoush Basin Using Multilayer Perceptron Coupled with Water Wave Optimization by Fatemeh Sayyahi, Saeed Farzin, Hojat Karami

“…The findings confirmed that the MLP-WWO could precisely predict ET.…”
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A comprehensive review of remote sensing techniques for monitoring Ulva prolifera green tides by Xiaomeng Geng, Xiaomeng Geng, Xiaomeng Geng, Huiru Li, Huiru Li, Le Wang, Weidong Sun, Yize Li

“…Additionally, it identifies the limitations and unresolved challenges in current approaches, such as constraints on data resolution, algorithmic biases, and environmental variability. The potential for integrating multi-source remote sensing data with marine environmental parameters and deep learning techniques is discussed, emphasizing their roles in improving the accuracy and reliability of monitoring and predicting Ulva prolifera green tides. …”
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Analysis of Photoelectric Detection Phase Polarity of Fiber-Optic Hydrophones Based on 3 × 3 Coupler Demodulation Technique by Yatao Li, Jianfei Wang, Mo Chen, Rui Liang, Yuren Chen, Zhou Meng, Xiaoyang Hu, Yang Lu

“…We develop a theoretical model combining the 3 × 3 coupler demodulation algorithm with coupled-mode theory to analyze acoustic signal responses. …”
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Long-Distance Measurements Using a Chromatic Confocal Sensor by Kiril Ivanov Kurtev, Juan Manuel Trujillo-Sevilla, José Manuel Rodríguez-Ramos

“…The sensor employs a robust algorithm to measure relative displacements of the sample’s motion. …”
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Research on status monitoring and positioning compensation system for digital twin of parallel robots by Yuting Zhang, Pei Gao, Zongyan Wang, Quanling He

“…Furthermore, an improved IPSO-SSA-DBP algorithm calibrates the kinematics and predicts the position error. …”
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Coffee-Leaf Diseases and Pests Detection Based on YOLO Models by Jonatan Fragoso, Clécio Silva, Thuanne Paixão, Ana Beatriz Alvarez, Olacir Castro Júnior, Ruben Florez, Facundo Palomino-Quispe, Lucas Graciolli Savian, Paulo André Trazzi

“…In the analyses, YOLOv8s stands out as the most effective, with a mAP of 54.5%, an inference time of 11.4 ms and the best qualitative predictions, making it ideal for real-time applications.…”
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MicrocrackAttentionNext: Advancing Microcrack Detection in Wave Field Analysis Using Deep Neural Networks Through Feature Visualization by Fatahlla Moreh, Yusuf Hasan, Bilal Zahid Hussain, Mohammad Ammar, Frank Wuttke, Sven Tomforde

“…This extreme class imbalance poses a challenge for deep learning models with different microscale cracks, as the network can be biased toward predicting the majority class, generally leading to poor detection accuracy for the under-represented class. …”
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Artificial Intelligence in Breast Reconstruction: A Narrative Review by Andrei Iulian Rugină, Andreea Ungureanu, Carmen Giuglea, Silviu Adrian Marinescu

“…AI shows promise in enhancing imaging for tumor detection and surgical planning, improving microsurgical precision, predicting complications such as flap failure, and optimizing postoperative monitoring. …”
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A 3D acid fracturing design calibrated to describe the productivity index in several southwestern Iranian oil fields by Mohammad Mirhashemi, Kaveh Ahangari, Ali Naghi Dehghan, Kamran Goshtasbi

“…Once these parameters are stabilized, the algorithm proceeds to calculate acid concentration at each node within the fracture area. …”
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Multi-scenario analysis of green water resource efficiency under carbon emission constraints in the Chengdu-Chongqing urban agglomeration, China: A system dynamics approach by Keyao Yu, Zhigang Li

“…These scenarios are used to simulate and predict different development paths and evaluate the impact of various key indicators on GWRE. …”
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SINS/OD integrated navigation system for shearer based on robust closed-loop path calibration by YAN Ming, FU Xiang, WANG Ranfeng, YANG Xinyu, LIU Bin

“…Then, the MCCKF was adopted to replace the traditional KF, reducing the interference caused by erroneous predicted positions in the traditional closed-loop calibration method on straightness detection. …”
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Experimental acoustic study of small horizontal axis wind turbines based on computational fluid dynamics and artificial intelligence approaches by M. Sadeghi malekabadi, A.R. Davari

“…Comparisons between CFD results and NN predictions validate the accuracy of the neural network. …”
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Exploring phonon mediated superconductivity of $$\hbox {LiB}_{{2}} \hbox {N}_{{2}}$$ and $$\hbox {LiC}_{{2}} \hbox {N}_{{2}}$$ under high pressure insight from first-principles cal... by Prutthipong Tsuppayakorn-aek, Thiti Bovornratanaraks, Komsilp Kotmool

“…In contrast, $$\hbox {LiC}_{{2}} \hbox {N}_{{2}}$$ is predicted to have a monoclinic structure (C2/m) at low pressures and a hexagonal structure ( $$P6_{3}/mmc$$ ) at higher pressures. …”
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Comparative analysis of endometrial gland imaging and pinopode detection for assessing endometrial receptivity by Min-bo Zhu, Bei-lei Chen, Meng Cen, Li-ping Chen, Zheng Shi

“…The objective was to compare the correlation between the two methods in evaluating endometrial receptivity and predicting pregnancy outcomes and to assess the consistency between the quantitative curves and pregnancy outcomes of the two methods in the cohort study. …”
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Bioinformatics analysis to explore biomarkers and mechanisms of action associated with endoplasmic reticulum stress and ferroptosis in Parkinson's disease. by Hao Wang, Lijuan Feng, Limeng He, Nan Liu, Yan Wan, Wei Zhang

“…Subsequently, biomarkers were validated using the least absolute shrinkage and selection operator regression algorithm. Additionally, correlations among biomarkers, gene set enrichment analysis, chromosomal and subcellular localization, immune cell infiltration, regulatory mechanisms, and drug predictions were conducted.…”
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Unraveling the structural and functional consequences of non-synonymous single-nucleotide polymorphisms (nsSNPs) in human SOCS2: an in silico approach by Tanvir Hossain, Md. Nur Islam, Md. Anwar Hossain, Md. Mofizur Rahman, Mohammed Mafizul Islam, Shipan Das Gupta

“…After a series of analysis, three mutants (G47R, Y49H, and I171S) were subjected to molecular dynamic simulation, principal component analysis, and free energy landscape to understand their impact during the course of mutation. The STRING algorithm was used to predict protein–protein interactions. …”
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Deep learning-based automated segmentation and quantification of the dural sac cross-sectional area in lumbar spine MRI by George Ghobrial, Christian Roth

“…The models were trained on T1-weighted axial MRI images and evaluated on metrics such as accuracy, precision, recall, F1-score, and mean absolute error (MAE).ResultsAll models exhibited a high correlation between predicted and actual DSCA values. The MultiResUNet model achieved superior results, with a Pearson correlation coefficient of 0.9917 and an MAE of 23.7032 mm2 on the primary dataset. …”
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Development of Flash Flood Forecasting System for Small and Medium‐Sized Rivers by Koji Ikeuchi, Daiki Kakinuma, Yosuke Nakamura, Shingo Numata, Takafumi Mochizuki, Keijiro Kubota, Masaki Yasukawa, Toshihiro Nemoto, Toshio Koike

“…Therefore, we developed a system that can accurately predict when river water levels will reach the Flood Risk Level (FRL). …”
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Quality of a fished resource: Assessing spatial and temporal dynamics. by Sarah J Teck, Julio Lorda, Nick T Shears, Tal Ben-Horin, Rebecca E Toseland, Sarah T Rathbone, Dave Rudie, Steven D Gaines

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Artificial intelligence-based personalised rituximab treatment protocol in membranous nephropathy (iRITUX): protocol for a multicentre randomised control trial by Céline Fernandez, Marion Cremoni, Laurent Bailly, Kevin Zorzi, Vesna Brglez, Barbara Seitz-Polski, Maxime Teisseyre, Alexandre Destere, Sylvain Benito

“…We have previously developed a machine learning algorithm to predict the risk of underdosing. We have retrospectively shown that patients with a high risk of underdosing required higher doses of rituximab to achieve remission. …”
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