Electrolyte and metabolite composition of cystic fluid from a rat model of ARPKD by Christine A. Klemens, Mykhailo Fedoriuk, Marharyta Semenikhina, Mariia Stefanenko, Adrian Zietara, Vladislav Levchenko, Lashodya V. Dissanayake, Oleg Palygin, Alexander Staruschenko

“…Abstract Fluid-filled cysts are the key feature of polycystic kidney disease, which eventually leads to renal failure. …”
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Brain functional connectivity after Stroop task induced cognitive fatigue by Jilin Wu, Zhongtian Guan, Chunlin Li, Wei Wang, Ruifeng Sun, Ziman Zhu, Li Song, Weijun Gong

“…These findings provide a reliable theoretical basis for developing new strategies to mitigate cognitive fatigue and offer valuable insights for optimizing rehabilitation plans for patients with cognitive impairments.…”
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SinGAN-Labeler: An Enhanced SinGAN for Generating Marine Oil Spill SAR Images with Labels by Bin Wang, Lei Chen, Dongmei Song, Weimin Chen, Jintao Yu

“…These results validate SinGAN-Labeler’s capability to mitigate data scarcity and enhance oil spill detection accuracy, particularly under extreme sample limitations.…”
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Influence of Mediterranean shrublands management on soil carbon sequestration by María González-Morales, Mª Ángeles Rodríguez-González, Daniel Paredes, Luis Fernández-Pozo

“…SOC was quantified in 108 samples from wooded shrubland (WS) and shrubland without trees (S), featuring species such as Quercus rotundifolia, Phillyrea angustifolia, Retama sphaerocarpa, and Cistus ladanifer. …”
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Data augmentation based on the WGAN-GP with data block to enhance the prediction of genes associated with RNA methylation pathways by Tuo Jiang, Cong Shen, Pingjian Ding, Lingyun Luo

“…To address the challenge of data imbalance in RNA methylation-associated gene prediction tasks, this study employed a generative adversarial network to learn the feature distribution of the original dataset. The quality of synthetic samples was controlled using the Classifier Two-Sample Test (CTST). …”
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Web application using machine learning to predict cardiovascular disease and hypertension in mine workers by Sohrab Effati, Alireza Kamarzardi-Torghabe, Fatemeh Azizi-Froutaghe, Iman Atighi, Somayeh Ghiasi-Hafez

“…After preprocessing and feature engineering, the Random Forest algorithm was identified as the best-performing model, achieving 99% accuracy for HTN prediction and 97% for CVD, outperforming other algorithms such as Logistic Regression and Support Vector Machines. …”
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Modeling Investor Behavior Using Machine Learning: Mean-Reversion and Momentum Trading Strategies by Thiago Christiano Silva, Benjamin Miranda Tabak, Idamar Magalhães Ferreira

“…For that, we use feature selection techniques from machine learning to identify relevant variables in an objective and concise way.…”
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Optimizing Solar Radiation Prediction Based on The Internet of Things Platform in Photovoltaic Power Plant by Neda Ashrafi Khozani, Maryam Mahmoudi, Shabnam Nasr Esfahani

“…Meta-heuristic algorithms are utilized for optimizing tree-based methods, as well as for feature and instance selection. Employing meta-heuristic methods as the main innovation in this research not only optimizes machine learning model settings but also mitigates the impact of noise, outliers, and ineffective inputs, thereby enhancing the final output quality. …”
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Dual decoding generative adversarial networks for infrared image enhancement by Yang Yu, Lin Jiang, Qijun Hu, Qijie Cai, Qiang Zeng, Xin Sun

“…First, internal and external skip connections are designed to enhance high-frequency detail transmission and mitigate gradient vanishing in deep networks, with local details being preserved as a result. …”
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Diagnosis of Coronary Heart Disease Through Deep Learning-Based Segmentation and Localization in Computed Tomography Angiography by Bo Zhao, Jianjun Peng, Ce Chen, Yongyan Fan, Kai Zhang, Yang Zhang

“…TransCHD incorporates a Contextual Representation Learning (CRL) module and a Spatially-Aware Feature (SAF) module, enabling both local feature extraction and global contextual awareness within a unified architecture. …”
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Design and Research on a Reed Field Obstacle Detection and Safety Warning System Based on Improved YOLOv8n by Yuanyuan Zhang, Zhongqiu Mu, Kunpeng Tian, Bing Zhang, Jicheng Huang

“…Specifically, we introduce the Context-Guided Block (CG Block) in the C2f module and the Context-Guide Fusion Module (CGFM) in the Feature Pyramid Network (FPN) to enhance the model’s contextual information perception during feature extraction and fusion. …”
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Prediction and evaluation of environmental quality for nursing sow buildings via multisource sensor information fusion by Chong Chen, Xingqiao Liu, Chaoji Liu, Chengyang Yu

“…The Random Forest (RF) model was selected for the feature selection. There were six feature factors that were closely related to environmental quality, including temperature, relative humidity, concentrations of NH3, CO2,H2S and air speed. …”
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Attention-GANs: An Advanced GNSS Data Augmentation Method for Improved NLOS/LOS Classification by S. Nie, H. Yang

“…Experimental results demonstrate that our approach effectively mitigates data imbalance, improves classification accuracy, and enhances GNSS positioning robustness in complex urban environments.…”
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Deep learning-based image classification for integrating pathology and radiology in AI-assisted medical imaging by Chenming Lu, Jiayin Zhang, Ren Liu

“…DIANet leverages multi-scale feature extraction, domain-specific priors, and Bayesian uncertainty modeling to enhance interpretability and robustness. …”
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The Power of Data Journalism: The Effects of Data-Driven News Reports in Correcting Climate Change Misinformation by Mahmoud-Mohamed-Abdel Haleem, Hagar Talaat-Alnajjar

“…The study investigated how readers’ preexisting beliefs influence the mitigation of misconceptions when exposed to news content. …”
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Cross‐cutting digital technologies as a tool to counteract sanctions restrictions by S.S. Krasnykh

“…The practical application of these solutions has already demonstrated positive results in a number of industries, and their development in the Russian Federation can significantly mitigate the effects of the imposed sanctions, ensuring technological sovereignty and long‐term sustainability of the economy…”
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The low prevalence effect in fingerprint comparison amongst forensic science trainees and novices. by Bethany Growns, James D Dunn, Rebecca K Helm, Alice Towler, Jeff Kukucka

“…In this paper, we investigated whether forensic science training may mitigate the low prevalence effect in fingerprint comparison. …”
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Development of Machine Learning Models for Sandface Pressure Prediction in Oil Well by Lorraine P. Oliveira, Raul M. Foronda, Alexandre V. Grillo, Brunno F. dos Santos

“…The Oil & Gas (O&G) industry is increasingly leveraging Machine Learning (ML) techniques to predict well performance indicators, estimate missing operational metrics, and mitigate unexpected operational failures. However, the availability of extensive and high-quality datasets remains a major challenge due to the diversity of well characteristics and proprietary industry constraints. …”
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Augmented Envelope Neural Networks on RF-SoC for Digital Self-Interference Cancellation by Udara De Silva, Hiruni Silva, Arjuna Madanayake

“…Trained model parameters are subsequently applied in real-time via a neural network-based digital signal processor to mitigate self-interference. A real-time prototype operating at 2.4 GHz, featuring direct-RF sampling at 4.096 GS/s and a 20 dBm transmit power through an external PA, was implemented using an AMD-Xilinx ZCU-111 RF-SoC. …”
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Real-time ultra short-term irradiance forecasting using a novel R-GRU model for optimizing PV controller dynamics by N.B. Sushmi, D. Subbulekshmi

“…This study proposes a novel R-GRU-based ultra-short-term irradiance forecasting model that incorporates key environmental variables. To mitigate overfitting, the model utilizes dropout and L2 regularization, while feature selection and hyperparameter tuning further enhance prediction accuracy. …”
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