Liquid metal phase change materials for thermal management of electronics by Yuchen Yao, Wei Li, Jing Liu, Zhongshan Deng

“…With the rapid development of various chips towards high performance and integration, the ‘thermal barrier’ difficulty facing electronic devices has become ever increasingly challenging, while at the same time the space size left for thermal management system already becomes much narrower. …”
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Severe COVID-19 in Third Trimester Pregnancy: Multidisciplinary Approach by Jerald Pelayo, Gabriella Pugliese, Grace Salacup, Eduardo Quintero, Adeeb Khalifeh, David Jaspan, Bhavna Sharma

“…The neonate was discharged on the 2nd day of life, while the patient was extubated on the 6th postpartum day and was discharged to acute inpatient rehabilitation facility on the 19th hospital day. …”
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Revolutionize 3D-Chip Design With Open3DFlow, an Open-Source AI-Enhanced Solution by Yifei Zhu, Zhenxuan Luan, Dawei Feng, Weiwei Chen, Lei Ren, Zhangxi Tan

“…It is a seven-step workflow that incorporates essential ASIC back-end processes while supporting multi-physics analysis, such as through silicon via (TSV) modeling, thermal analysis, and signal integrity (SI) evaluations. …”
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Mf-net: multi-feature fusion network based on two-stream extraction and multi-scale enhancement for face forgery detection by Hanxian Duan, Qian Jiang, Xin Jin, Michal Wozniak, Yi Zhao, Liwen Wu, Shaowen Yao, Wei Zhou

“…Current face forgery detection algorithms achieve high detection accuracy within-dataset. …”
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Evaluation of the performance of ERA5, ERA5-Land and MERRA-2 reanalysis to estimate snow depth over a mountainous semi-arid region in Iran by Faezehsadat Majidi, Samaneh Sabetghadam, Maryam Gharaylou, Reza Rezaian

“…Study focus: Snow is a critical component of the cryosphere, with significant seasonal and annual variability that impacts global water circulation and energy balance. While ground-based observations provide the most reliable snow depth (SND) data, their sparse distribution in remote regions necessitates the use of alternative datasets for monitoring snow depth. …”
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Advancing mmWave Altimetry for Unmanned Aerial Systems: A Signal Processing Framework for Optimized Waveform Design by Maaz Ali Awan, Yaser Dalveren, Ali Kara, Mohammad Derawi

“…This article addresses challenges arising from radial velocity due to UAS descent rates and terrain variation through theoretical and mathematical approaches for characterization and mandatory compensation. While constant false alarm rate (CFAR) algorithms have been reported for ground detection, a comparison of their variants within the scope UAS altimetry is limited. …”
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Accuracy is not enough: a heterogeneous ensemble model versus FGSM attack by Reham A. Elsheikh, M. A. Mohamed, Ahmed Mohamed Abou-Taleb, Mohamed Maher Ata

“…Abstract In this paper, based on facial landmark approaches, the possible vulnerability of ensemble algorithms to the FGSM attack has been assessed using three commonly used models: convolutional neural network-based antialiasing (A_CNN), Xc_Deep2-based DeepLab v2, and SqueezeNet (Squ_Net)-based Fire modules. …”
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Comparing the Indices predictive of the thermal injury outcome by E A. Zhirkova, T. G. Spiridonova, A. V. Sachkov, A. O. Medvedev, E. I. Eliseenkova, I. G. Borisov, M. L. Rogal, S. S. Petrikov

“…Introduction. While developing the algorithms for diagnosis and treatment of patients with thermal injury, an injury outcome prediction index with the best predictive properties should be used.Aim. …”
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Soot Mass Concentration Prediction at the GPF Inlet of GDI Engine Based on Machine Learning Methods by Zhiyuan Hu, Zeyu Liu, Jiayi Shen, Shimao Wang, Piqiang Tan

“…Integrating SVR and DNN models through stacked models extends the predictive range of a single SVR or DNN model while mitigating the overfitting of DNN models. The results of the study can serve as a reference for the development of accurate prediction algorithms to estimate soot loads in GPFs, which in turn can provide some basis for the control of the particulate mass and particle number (PN) emitted from GDI engines.…”
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Investigating ethical tradeoffs in crisis standards of care through simulation of ventilator allocation protocols. by Jonathan Herington, Jessica Shand, Jeanne Holden-Wiltse, Anthony Corbett, Richard Dees, Chin-Lin Ching, Margie Shaw, Xueya Cai, Martin Zand

“…Unlike other protocols, the New York and Maryland algorithms did not generate significant disparities in lives saved and life-years saved between White non-Hispanic, Black non-Hispanic, and Hispanic sub-populations. …”
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Synchrony of Nitrogen Wet Deposition Inputs and Watershed Nitrogen Outputs Using Information Theory by Desneiges S. Murray, Edom Moges, Laurel Larsen, Michelle D. Shattuck, William H. McDowell, Adam S. Wymore

“…Information theoretic algorithms facilitated data‐driven inferences on the hydro‐biogeochemical processes influencing the fate of N wet deposition. …”
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Machine learning analysis of cardiovascular risk factors and their associations with hearing loss by Ali Nabavi, Farimah Safari, Ali Faramarzi, Mohammad Kashkooli, Meskerem Aleka Kebede, Tesfamariam Aklilu, Leo Anthony Celi

“…The subtle changes in hearing often go unnoticed, presenting a challenge for early hearing loss detection. While machine learning shows promise, prior studies have not leveraged cardiovascular risk factors known to impact hearing. …”
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Higher-order aberrations and spherical aberration in various age groups after LASIK and cataract surgery by Robert Edward T. Ang, Patricia L. Lee, Ryan S. Torres, Michelle Marie Q. Araneta, Emerson M. Cruz, Maria Socorro M. Torno

“…In Lasik surgery, manipulating spherical aberration in the corneal periphery improves overall vision while in the central cornea provides presbyopic treatment. …”
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iMESc – an interactive machine learning app for environmental sciences by Danilo Cândido Vieira, Danilo Cândido Vieira, Fabiana S. Paula, Luciana Erika Yaginuma, Gustavo Fonseca

“…The Datalist system ensures seamless transitions between analytical workflows, while the “savepoints” feature enhances reproducibility by preserving the analysis state. …”
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Stacking ensemble learning models diagnose pulmonary infections using host transcriptome data from metatranscriptomics by Tian Zhang, Ying Deng, Wentao Wang, Zhe Zhao, Yiling Wu, Haoqian Wang, Shutao Xia, Weifang Liao, Weijie Liao

“…Abstract The prompt diagnosis of pulmonary infections with unknown etiology in patients in severe condition remains a challenge due to the lack of rapid and effective diagnostic methods. While metatranscriptomic sequencing offers a powerful approach, its clinical utility is often limited by issues of timeliness. …”
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Exploring the key ingredients and mechanisms of Banxia Xiexin decoction for the treatment of polycystic ovary syndrome based on network pharmacology and experimental validation by Bai Hai, Yingying Zhang, Jing Huang, Richard Mprah, Mingming Wang

“…KEGG analysis showed they were mainly involved in signaling pathways such as PI3K-AKT, MAPK, HIF-1 and IL17. By PPI and algorithmic analysis, we identified 8 hub genes, 5 of which (JUN, MAPK1, MAPK3, FOS, TP53) were related to oxidative stress. …”
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Programmed cell death signatures-driven microglial transformation in Alzheimer’s disease: single-cell transcriptomics and functional validation by Mi-Mi Li, Ying-Xia Yang, Ya-Li Huang, Shu-Juan Wu, Wan-Li Huang, Li-Chao Ye, Ying-Ying Xu

“…High PCDS correlated with upregulated pathways related to inflammation and immune response, while low PCDS associated with protective pathways. …”
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Ethical Aspects of the Influence of Neural Networks on the Lives of Students in the Context of a Sociological Approach (using the Example of Students of the IT Department of ETU) by A. S. Kurapova, S. V. Kurapov, A. D. Derzhavina, N. V. Shatilo

“…The results showed that the majority of students (59.2 %) positively assess the use of neural networks, while 85.1 % of respondents use them for educational purposes. …”
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Quantifying the Accuracy of UAS-Lidar Individual Tree Detection Methods Across Height and Diameter at Breast Height Sizes in Complex Temperate Forests by Benjamin T. Fraser, Russell G. Congalton, Mark J. Ducey

“…This study addresses how specific individual tree detection (ITD) methods impact the successful detection of trees of varying sizes within complex forests. First, while many studies have compared ITD methods over several sites, algorithms, or sets of parameters based on a singular validation metric, this study quantifies how 10 processing methods perform across varying tree-height size quartiles and varying tree diameter at breast height (dbh) size quartiles. …”
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Prediction of adverse drug reactions using demographic and non-clinical drug characteristics in FAERS data by Alireza Farnoush, Zahra Sedighi-Maman, Behnam Rasoolian, Jonathan J. Heath, Banafsheh Fallah

“…Abstract The presence of adverse drug reactions (ADRs) is an ongoing public health concern. While traditional methods to discover ADRs are very costly and limited, it is prudent to predict ADRs through non-invasive methods such as machine learning based on existing data. …”
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