PROBLEMS OF USING NEURAL NETWORKS TO PREDICT THE PRICE OF VIRTUAL ASSETS by Andrii Tsemko, Maxym Matskiv

“…The TensorFlow library, in particular the Keras API, was used for training process with customizable parameters: 150 epochs, 32 batch size, Adam optimizer, and MSE loss function. Results and Discussion. …”
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Prediction of Inflorescence Emergence in ‘Yu Her Pau’ Litchi Under Climate Change Using an Optimised Model by JenYu Chang, Lisa Tang, Chu‐Chung Chen, Yi‐Ting Zhang, Chi‐Ling Chen

“…For this predictive model, the minimum, maximum, and optimal temperatures that resulted in successful floral induction were estimated to be 0.0°C, 21.9°C, and 19.8°C, respectively; under these criteria, at least 60.37 units of cumulative cool temperatures are necessary for IE based on the historical data. …”
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Fully-Gated Denoising Auto-Encoder for Artifact Reduction in ECG Signals by Ahmed Shaheen, Liang Ye, Chrishni Karunaratne, Tapio Seppänen

“…Furthermore, a multi-component loss function is proposed to learn efficient latent representations of ECG signals and provide reliable denoising with maximal morphological preservation. …”
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Learning Distributed Parameters of Land Surface Hydrologic Models Using a Generative Adversarial Network by Ruochen Sun, Baoxiang Pan, Qingyun Duan

“…However, calibrating distributed land surface hydrologic models presents a great challenge, often resulting in uneven spatial performance due to the compression of information inherent in model outputs and observations into a single‐value objective function. To address this problem, we propose a novel Generative Adversarial Network‐based Parameter Optimization (GAN‐PO) method. …”
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Response estimation and system identification of dynamical systems via physics-informed neural networks by Marcus Haywood-Alexander, Giacomo Arcieri, Antonios Kamariotis, Eleni Chatzi

“…PINNs offer a unique advantage by embedding known physical laws directly into the neural network’s loss function, allowing for simple embedding of complex phenomena, even in the presence of uncertainties. …”
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Barriers and facilitators to the use of clinical practice guidelines in osteoarthritis care: a qualitative study among German physiotherapists by Carolin Bahns, Lisa Happe, Christian Kopkow

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Gut Hormones and Inflammatory Bowel Disease by Jonathan Weng, Chunmin C. Lo

“…GLP-1 improves glycemic control, induces weight loss, and preserves intestinal barrier function, while GLP-2 enhances epithelial repair and reduces pro-inflammatory cytokine expression in animal models of colitis. …”
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Choline metabolism underpins macrophage IL-4 polarization and RELMα up-regulation in helminth infection. by Peyman Ghorbani, Sang Yong Kim, Tyler K T Smith, Lucía Minarrieta, Victoria Robert-Gostlin, Marisa K Kilgour, Maja Ilijevska, Irina Alecu, Shayne A Snider, Kaitlyn D Margison, Julia R C Nunes, Daniel Woo, Ciara Pember, Conor O'Dwyer, Julie Ouellette, Pavel Kotchetkov, Julie St-Pierre, Steffany A L Bennett, Baptiste Lacoste, Alexandre Blais, Meera G Nair, Morgan D Fullerton

“…The impaired macrophage activation was associated with some loss in optimal immunity to H. polygyrus, with increased egg burden. …”
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Hand–Eye Separation-Based First-Frame Positioning and Follower Tracking Method for Perforating Robotic Arm by Handuo Zhang, Jun Guo, Chunyan Xu, Bin Zhang

“…Additionally, the GIoU loss function is introduced to replace the traditional IoU, further optimizing bounding box regression through the calculation of the minimum enclosing box. …”
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Additive manufacturing as smart manufacturing system for fabrication of interference screw by Lusia Permata Sari HARTANTI, Paulus Wisnu ANGGORO, Rifky ISMAIL, Jamari JAMARI, Athanasius Priharyoto BAYUSENO

“…The optimal process parameters were 50 mm/s printing speed and 0.3 mm nozzle diameter. …”
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ASAP: Automated Style-Aware Similarity Measurement for Selection of Annotated Pre-Training Datasets in 2D Biomedical Imaging by Miguel Molina-Moreno, Marcel P. Schilling, Markus Reischl, Ralf Mikut

“…Our pipeline, consisting of an autoencoder trained with self-supervised learning through a comprehensive loss function that considers the image reconstruction, style features, and dataset membership, does not need any kind of labels in training and test stages. …”
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Sonar-based object detection for autonomous underwater vehicles in marine environments by Zhen Wang, Zhen Wang, Jianxin Guo, Shanwen Zhang, Yucheng Zhang

“…Additionally, the CIoU-DFL loss optimization function was constructed to address the class imbalance in sonar data and reduce model computational complexity. …”
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Machine Learning System for Predicting Cardiovascular Disorders in Diabetic Patients by A. Mayya, H. Solieman

“…The RFC and XGBoost models achieved higher accuracy using gradient descending order to minimize the loss function. The final prediction is made using a weighted majority vote of all the decisions. …”
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Toward Efficient UAV-Based Small Object Detection: A Lightweight Network with Enhanced Feature Fusion by Xingyu Di, Kangning Cui, Rui-Feng Wang

“…Then, DyHead is used to replace the original detector head, and the discrimination ability of small targets in complex background is enhanced by adaptive weight allocation and cross-scale feature optimization fusion. Finally, the WIPIoU loss function is proposed, which integrates the advantages of Wise-IoU, MPDIoU and Inner-IoU, and incorporates the geometric center of bounding box, aspect ratio and overlap degree into a unified measure to improve the localization accuracy of small targets and accelerate the convergence. …”
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Complex Large-Deformation Multimodality Image Registration Network for Image-Guided Radiotherapy of Cervical Cancer by Ping Jiang, Sijia Wu, Wenjian Qin, Yaoqin Xie

“…On the basis of deep learning, bistructural morphology is added to the model to train the pelvic area registration evaluator, and the model can obtain parameters covering large deformation for loss function. The model was verified by the actual clinical data of cervical cancer patients. …”
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Preparation and Characterization of Protein-Based Hydrogel: Cottonseed Protein Grafted with 2-Acrylamido-2-Methylpropanesulfonic Acid (AMPS) by Dehenenet Flatie Tassw, Tamrat Tesfaye, Murugesh Babu K.

“…N,N-methylene bisacrylamide serves as the crosslinking agent, while potassium persulfate (PPS) and sodium bisulfite (SBS) function as redox initiators. The optimization of hydrogel synthesis conditions was achieved using Design Expert-11 software, adjusting the AMPS to CSP ratio. …”
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A Convolutional Neural Network for Early Supraventricular Arrhythmia Identification by Emilio J. Ochoa, Luis C. Revilla

“…A binary cross-entropy loss function, Adam optimizer, and a batch size of 128 were obtained after a hyperparameter tuning. …”
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Integrated and improved YOLOv8 and triangulated network method for extracting indicators in open-pit mine mining areas by LI Tianwen, LI Gongquan, LI Juntao

“…Based on YOLOv8, the following improvements were made to obtain Mine-YOLO: the addition of an Efficient Multi-Scale Attention (EMA) module to enhance the model's recognition and segmentation accuracy of mining field boundaries; the inclusion of a Global Attention Mechanism (GAM) module to retain open-pit mining field feature data at a global scale, improving target recognition accuracy; and the optimization of the Focaler-IoU loss function to enhance the model's ability to distinguish positive samples. …”
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The ubiquitin-conjugating enzyme UBE2D maintains a youthful proteome and ensures protein quality control during aging by sustaining proteasome activity. by Liam C Hunt, Michelle Curley, Kudzai Nyamkondiwa, Anna Stephan, Jianqin Jiao, Kanisha Kavdia, Vishwajeeth R Pagala, Junmin Peng, Fabio Demontis

“…Mechanistically, UBE2D/eff is necessary to maintain optimal proteasome function: UBE2D/eff knockdown reduces the proteolytic activity of the proteasome, and this is rescued by transgenic expression of human UBE2D2, an eff homolog. …”
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Research and Design of an Active Light Source System for UAVs Based on Light Intensity Matching Model by Rui Ming, Tao Wu, Zhiyan Zhou, Haibo Luo, Shahbaz Gul Hassan

“…Furthermore, optimization experiments are conducted on the variable active light source module. …”
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