THE RELEVANCE OF RAISING AWARENESS OF PHARMACEUTICAL WORKERS ON HIV INFECTION by Андрей Георгиевич Петров, Галина Тихоновна Глембоцкая, Ольга Владимировна Хорошилова, Сергей Николаевич Филимонов, Виктор Андреевич Семенихин

“…This fact associated with undesirable reactions should not be ignored, due to the fact that responsible participants in the retail pharmaceutical market fully perform their function in the system of specialized pharmaceutical care. …”
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Multi-Branch Network with Multi-Feature Enhancement for Improving the Generalization of Facial Forgery Detection by Siyu Meng, Quange Tan, Qianli Zhou, Rong Wang

“…Finally, independent loss functions are designed for each branch to ensure the effective learning of specific features while promoting collaborative optimization of the model through the overall loss function. …”
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Dynamical Signatures of Trumpler 19: A Statistical and Photometric Perspective by A. H. Sheikh, Biman J. Medhi, Ram Sagar

“…We identified 810 cluster members using an ensemble-based unsupervised machine learning method applied to Gaia Data Release 3 astrometric data. …”
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Machine-guided cell-fate engineering by Evan Appleton, Jenhan Tao, Songlei Liu, Christopher Glass, Gregory Fonseca, George Church

“…Summary: The creation of induced pluripotent stem cells (iPSCs) has enabled scientists to explore the function, mechanisms, and differentiation processes of many types of cells. …”
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Neutrophil extracellular trap is an important connection between hemodialysis and acute myocardial infarction by Yue Yang, Yuan-yuan Jiao, Zheng Zhang, Li Zhuo, Wen-ge Li

“…In this study, the gene expression profiles of HD (GSE15072) and AMI (GSE66360) were downloaded from the Gene Expression Omnibus database, common differentially expressed genes (DEGs) were obtained using the limma R package, the biological functions were analyzed according to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, machine learning was conducted to identify hub genes. …”
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Automated Eddy Identification and Tracking in the Northwest Pacific Based on Conventional Altimeter and SWOT Data by Lan Zhang, Cheinway Hwang, Han-Yang Liu, Emmy T. Y. Chang, Daocheng Yu

“…This study employed the elliptical Gaussian function (EGF) simulations and the py-eddy-tracker (PET) algorithm, validated by Surface Velocity Program (SVP) drifter data, to track eddies in the western North Pacific Ocean. …”
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Legendre based neural networks integrated with heuristic algorithms for the analysis of Lorenz chaotic model: an intelligent and comparative study by Khalid Masood, Muhammad Arshad, Muhammad Abubakar, Muhammad Naeem Aslam, Mohammed A. Alghamdi, Sultan H. Almotiri

“…Through this advanced LENN intelligent design framework, an objective/fitness optimization function is developed within a feedforward neural network. …”
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Canada goose fecal microbiota correlate with geography more than host‐associated factors by Joshua C. Gil, Heather R. Skeen, Celeste Cuellar, Sarah M. Hird

“…The forces shaping the composition, diversity, and function of the microbiota vary within and between species. …”
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Neuroprotective Effects of ZiBuPiYin Recipe on db/db Mice via PI3K-Akt Signaling Pathway by Activating Grb2 by Wei-ming Ren, Ze-bin Weng, Xin Li, Li-bin Zhan

“…Morris water maze (MWM) tests were used to assess memory function. The expression of Grb2, Gab2, Akt, and GSK3β in mouse hippocampus and cerebral cortex were analyzed by Western blotting. …”
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Fine-grained individual tree crown segmentation based on high-resolution images by Y. Wang, X. Dou, X. Liang

“…Its cover, distribution, structure are highly relevant to the function of water cycling, carbon storage, and climate modulating of forest. …”
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Development of an Integrated System of sEMG Signal Acquisition, Processing, and Analysis with AI Techniques by Filippo Laganà, Danilo Pratticò, Giovanni Angiulli, Giuseppe Oliva, Salvatore A. Pullano, Mario Versaci, Fabio La Foresta

“…The system analyzes sEMG signals to understand muscle function and neuromuscular control, employing convolutional neural networks (CNNs) for pattern recognition. …”
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Notice of Violation of IEEE Publication Principles: VVC/H.266 Intra Mode QTMT Based CU Partition Using CNN by Sameena Javaid, Safdar Rizvi, Muhammad Talha Ubaid, Abdullah Tariq

“…In the third phase, for the training of MLECNN model we have established the adaptive loss function and analyzing the both unknown number of partition modes and the focus on RD cost minimization. …”
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Assessment of Student IPEC Competency Using Observer-Based Evaluation in Didactic Interprofessional Education Activities by Jacqueline Zeeman, Kimberly Sanders, Tia Belvin, Philip Rodgers

“…This strategy provides an observer-based evaluation of a student’s collaborative practice readiness to function effectively on an interprofessional team. …”
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The impact of direct and indirect digital soil mapping approaches on spatial uncertainty by Gábor Szatmári, László Pásztor

“…Such questions were examined on the example of mapping soil organic carbon (SOC) in the Great Hungarian Plain, Hungary, by combining machine learning with univariate and multivariate geostatistics. …”
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Automatic Road Extraction from Historical Maps Using Transformer-Based SegFormers by Elif Sertel, Can Michael Hucko, Mustafa Erdem Kabadayı

“…We applied the variants of the transformer-based SegFormer model and evaluated the effects of different encoders, batch sizes, loss functions, optimizers, and augmentation techniques on road extraction performance. …”
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COMPARING FORECASTS OF AGRICULTURAL SECTOR EXPORT VALUES USING SARIMA AND LONG SHORT-TERM MEMORY MODELS by Aleytha Ilahnugrah Kurnadipare, Sri Amaliya, Khairil Anwar Notodiputro, Yenni Angraini, Laily Nissa Atul Mualifah

“…The best SARIMA model generated was (1,1,1)(0,1,1)12, while the optimal parameters for the LSTM model were neuron: 50, dropout rate: 0.3, number of layers: 2, activation function: relu, epochs: 500, batch size: 64, optimizer: Adam, and learning rate: 0.01. …”
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Lightweight SCD-YOLOv5s: The Detection of Small Defects on Passion Fruit with Improved YOLOv5s by Yu Zhou, Zhenye Li, Sheng Xue, Min Wu, Tingting Zhu, Chao Ni

“…Numerous small defects present significant challenges for manual inspection. Recently, deep learning (DL) has been widely applied to object detection. …”
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Spatiotemporal Data Augmentation of MODIS‐Landsat Water Bodies Using Adversarial Networks by Soukaina Filali Boubrahimi, Ashit Neema, Ayman Nassar, Pouya Hosseinzadeh, Shah Muhammad Hamdi

“…We propose a new non‐saturating loss function for the Hydro‐GAN generator, which maximizes the log of discriminator probabilities to promote stable updates and aid convergence. …”
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Building Up a Robust Risk Mathematical Platform to Predict Colorectal Cancer by Le Zhang, Chunqiu Zheng, Tian Li, Lei Xing, Han Zeng, Tingting Li, Huan Yang, Jia Cao, Badong Chen, Ziyuan Zhou

“…Our results demonstrate that (1) the explored genetic and environmental biomarkers are validated to connect to the CRC by biological function- or population-based evidences, (2) the model can efficiently predict the risk of CRC after parameter optimization by the big CRC-related data, and (3) our innovated heterogeneous ensemble learning model (HELM) and generalized kernel recursive maximum correntropy (GKRMC) algorithm have high prediction power. …”
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Multi-Stage Audio-Visual Fusion for Dysarthric Speech Recognition With Pre-Trained Models by Chongchong Yu, Xiaosu Su, Zhaopeng Qian

“…However, collecting dysarthric speech is difficult. The machine learning models cannot be trained sufficiently using dysarthric speech. …”
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