Surgeons are apprehensive to use DCD lungs despite similar post-transplant outcomes: A 20-year UNOS retrospective analysis by J. Sam Meyer, MSc, Oliver K. Jawitz, MD, MHS, Yury Peysakhovich, MD, Dan Aravot, MD, Matthew G. Hartwig, MD, MHS, Yaron D. Barac, MD, PhD

“…Methods: We performed a retrospective analysis of United Network for Organs Sharing (UNOS) Organ Procurement and Transplantation Network/UNOS STAR (Standard Analysis and Research) database. …”
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Global ground-based tropospheric ozone measurements: reference data and individual site trends (2000–2022) from the TOAR-II/HEGIFTOM project by R. Van Malderen, A. M. Thompson, A. M. Thompson, D. E. Kollonige, D. E. Kollonige, R. M. Stauffer, H. G. J. Smit, E. Maillard Barras, C. Vigouroux, I. Petropavlovskikh, I. Petropavlovskikh, T. Leblanc, V. Thouret, P. Wolff, P. Effertz, P. Effertz, D. W. Tarasick, D. Poyraz, G. Ancellet, M.-R. De Backer, S. Evan, V. Flood, M. M. Frey, J. W. Hannigan, J. L. Hernandez, M. Iarlori, B. J. Johnson, N. Jones, R. Kivi, E. Mahieu, G. McConville, K. Müller, T. Nagahama, J. Notholt, A. Piters, N. Prats, R. Querel, D. Smale, W. Steinbrecht, K. Strong, R. Sussmann

“…Reprocessing with uniform procedures, the TOAR-II working group Harmonization and Evaluation of Ground-based Instruments for Free-Tropospheric Ozone Measurements (HEGIFTOM) homogenized public data from five networks: ozonesondes, In-service Aircraft for a Global Observing System (IAGOS) profiles, solar absorption Fourier transform infrared (FTIR) spectrometer measurements, lidar observations, and Dobson Umkehr data. …”
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Using of Deep Learning in Beamforming Antenna Array by Ali Naji, Thamer M. Jamel M. Jamel, Hassan F. khazaal

“…To substantiate the efficacy of the technique, several illustrative examples are employed to steer the beam pattern in the desired direction. …”
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Simulating the drought response of European tree species with the dynamic vegetation model LPJ-GUESS (v4.1, 97c552c5) by B. F. Meyer, J. P. Darela-Filho, K. Gregor, A. Buras, Q.-L. Gu, A. Krause, D. Liu, P. Papastefanou, S. Asuk, T. E. E. Grams, C. S. Zang, A. Rammig

“…We quantify the uncertainty introduced by the new processes using a variance-based global sensitivity analysis. Additionally, we evaluate the model against water and carbon fluxes from a network of eddy covariance flux sites across Europe. …”
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Intelligent traffic congestion forecasting using BiLSTM and adaptive secretary bird optimizer for sustainable urban transportation by Lalitha Krishnasamy, Siva C, Rajesh Kumar Dhanaraj, Mahmoud Ahmad Al-Khasawneh, Taher Al-Shehari, Nasser A. Alsadhan, Shitharth Selvarajan

“…The better performance demonstrates that RL- BiLSTM with ASBO is well-suited to predict congestion patterns in road networks.…”
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Generative AI in construction risk management: a bibliometric analysis of the associated benefits and risks by Mohamed Abdelwahab Hassan Mohamed, M.K.S. Al-Mhdawi, Udechukwu Ojiako, Nicholas Dacre, Abroon Qazi, Farzad Rahimian

“…Using VOSViewer, visual maps illustrate research trends, collaboration networks and citation patterns. Findings – The findings reveal a notable increase in research interest in GenAI for CRM, with benefits classified into technical, operational, technological and integration categories. …”
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Identification of Isoflavonoid Biosynthesis-Related R2R3-MYB Transcription Factors in Callerya speciosa (Champ. ex Benth.) Schot Using Transcriptome-Based Gene Coexpression Analysi... by Linchan Yu, Ding Huang, Jinyuan Gu, Dongjin Pan, Yong Tan, Rongshao Huang, Shaochang Yao

“…Conserved motifs and domain distribution, expression patterns, and coexpression networks were also employed to identify the potential R2R3-MYB TFs in the regulation of isoflavonoid biosynthesis. …”
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Three Circulating miRNAs Related to Non-Small-Cell Lung Cancer Progression: An Integrative Analysis of Their Biological Roles by Yanqin Niu, Gaohui Fu, Sijian Xia, Menglong Li, Lin Qiu, Jun Wang, Kang Kang, Deming Gou

“…In this study, we observed distinct clustering patterns of LUAD or LUSC tissues compared to paired normal tissues based on miRNA expression levels, suggesting the potential involvement of circulating miRNAs in non-small-cell lung cancer (NSCLC) progression. …”
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Advanced Machine Learning Techniques for Energy Consumption Analysis and Optimization at UBC Campus: Correlations with Meteorological Variables by Amir Shahcheraghian, Adrian Ilinca

“…Among the regression models evaluated, deep neural networks are found to excel in capturing complex patterns and achieve high predictive accuracy. …”
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The arrow of time in Parkinson’s disease by Fatemeh Sadeghi, Elvira del Agua Banyeres, Alessandra Pizzuti, Abdullah Okar, Kai Grimm, Christian Gerloff, Morten L. Kringelbach, Rainer Goebel, Simone Zittel, Gustavo Deco

“…Results: We found that PD is characterized by disrupted equilibrium regimes, marked by distinct effective connectivity patterns, particularly within the motor networks. Additionally, we observed a flatter hierarchical organization in PD, with the cerebellum and thalamus exerting increased influence. …”
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Analyzing and explaining the reflective teacher approach and its role in improving curriculum knowledge: Developing an educational discourse at Farhangian University by Reza Masouminejad

“…The integrated understanding of teachers determines their reactions in creating a holistic conceptualization and creating thought patterns with specific thinking methods. Mental preparation and multi-facets mastery of intellectual elements leads to the interaction between abstract concepts and their understanding, so that none of the influential factors in the process of deep thinking of phenomena is neglected. …”
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Estimation of Ca2+ wet deposition in the Northern Hemisphere by use of CNN deep-learning model by Wanying Chen, Xingcheng Lu, Chaofan Xian, Xu Sun, Yiang Chen, Mingyun Hu, Geng Li, Jimmy C.H. Fung

“…Our findings provide insights into Ca2+ wet deposition patterns and underline ecological importance, supporting future environmental management.…”
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Exploring Generative Pre-Trained Transformer-4-Vision for Nystagmus Classification: Development and Validation of a Pupil-Tracking Process by Masao Noda, Ryota Koshu, Reiko Tsunoda, Hirofumi Ogihara, Tomohiko Kamo, Makoto Ito, Hiroaki Fushiki

“…Recently, deep learning techniques have been used to automate nystagmus classification using convolutional and recurrent neural networks. These networks can accurately classify nystagmus patterns using video data. …”
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Ranking nodes in bipartite systems with a non-linear iterative map by Andrea Mazzolini, Michele Caselle, Matteo Osella

“…Finally, we explore theoretical aspects of the map, revealing a phase transition at a critical γ dependent on the data structure that can be characterized analytically for random networks. Near the critical point, the map exhibits unique features and a distinctive “triangular” packing pattern of the incidence matrix.…”
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Spectrogram-Based Arrhythmia Classification Using Three-Channel Deep Learning Model with Feature Fusion by Alaa Eleyan, Fatih Bayram, Gülden Eleyan

“…This spectrogram is further processed to generate a histogram of oriented gradients (HOG) and local binary pattern (LBP) features. Three separate 2D convolutional neural networks (CNNs) then analyze these three image representations in parallel. …”
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Drug-induced second tumors: a disproportionality analysis of the FAERS database by Shupeng Chen, Yuzhe Zhang, Xiaojian Li, Nana Tang, Yingjian Zeng

“…Additionally, the Weibull Shape Parameter (WSP) was used to analyze the characteristic patterns of time-to-onset curves. Newly discovered signals were verified against FDA drug labels to confirm their novelty. …”
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A real-world disproportionality analysis of FDA adverse event reporting system (FAERS) events for lecanemab by Linlin Yan, Linhai Zhang, Zucai Xu, Zhong Luo

“…The median time to the occurrence of these AEs was 44 days after administration in AD patients and 30 days for Non-AD patients.ConclusionThis study utilized the FAERS database to evaluate lecanemab-associated AEs in AD and non-AD patients, along with their temporal patterns post-marketing authorization, thereby establishing a foundation for subsequent clinical pharmacovigilance. …”
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Integrative bulk and single-cell transcriptomic analysis identifies a migrasome-associated lncRNA signature predictive of prognosis and immune landscape in clear cell renal cell ca... by Junlin Shen, Chun Wang, Mingpeng Zhang, Bin Chen, Liwei Liu, Jing Tian, Zhiqun Shang

“…The associations between the model and overall survival (OS), functional enrichment, tumor mutation burden (TMB), tumor microenvironment (TME) characteristics, immune evasion, and drug sensitivity were evaluated. Single-cell transcriptomic analysis was performed to determine cell type–specific expression patterns and intercellular communication networks. …”
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Identification of a deubiquitinating gene-related signature in ovarian cancer using integrated transcriptomic analysis and machine learning framework by Suwan Hu, Mengting Wang

“…High-risk patients, as classified by the DRS, showed significantly poorer survival outcomes and distinct immune infiltration patterns compared to low-risk patients. Conclusion This study provides comprehensive insights into DUB gene expression patterns across different cell populations in ovarian carcinoma. …”
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A Deep Learning-Based Diagnostic Framework for Shaft Earthing Brush Faults in Large Turbine Generators by Katudi Oupa Mailula, Akshay Kumar Saha

“…The proposed framework combines advanced signal processing and convolutional neural networks (CNNs) to automatically recognize fault-related patterns in shaft grounding current and voltage signals. …”
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