Shifts in seasonal influenza patterns in Australia during and after COVID-19: A comprehensive analysis by Cynthia Lu, Ian G. Barr, Stephen Lambert, Kerrie Mengersen, Liping Wang, Weizhong Yang, Zhongjie Li, Sotiris Vardoulakis, Hilary Bambrick, Wenbiao Hu

“…Using generalised additive models, we compared predicted weekly influenza case counts during 2020–2022 with observed counts. …”
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Redefining the Diagnostic Approach to Adrenal Insufficiency: Re-Assessment of Baseline and Cortisol Increment Cut-Offs with the 1 µg Synacthen Test by Taieb Ach, Rim Dhaffar, Asma Ammar, Aycha Ghachem, Imen Halloul, Wiem Saafi, Hamza El Fekih, Ghada Saad, Yosra Hasni, Monia Zaouali

“…Diagnostic accuracy of baseline cortisol levels and cortisol increment was assessed using ROC curve analysis to determine optimal cut-offs for predicting LDST outcomes. <i>Results:</i> Among 163 patients (mean age 42.9 years, 63% female), baseline cortisol ≤ 5.35 μg/dL had 100% specificity but 41.5% sensitivity for LDST failure. …”
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Deep Learning Hybrid Architecture Based on Vision Transformer for Phase Analysis of Moir&#x00E9; Fringes by Dajie Yu, Junbo Liu, Chuan Jin, Yuyang Li, Kairui Zhang, Ji Zhou

“…By training on various types of Moir&#x00E9; fringe datasets, the model can predict the fringe wrapping phase, allowing for the analysis of elements within the wrapping phase, including displacement information. …”
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Near-Real-Time Global Thermospheric Density Variations Unveiled by Starlink Ephemeris by Zhuoliang Ou, Jiahao Zhong, Yongqiang Hao, Ruoxi Li, Xin Wan, Kang Wang, Jiawen Chen, Hao Han, Xingyan Song, Wenyu Du, Yanyan Tang

“…Due to extensive coverage and frequent maneuvers, SpaceX has publicly released predicted ephemeris data for all Starlink satellites since May 2021, with updates approximately every 8 h. …”
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Improved leaf area index reconstruction in heavily cloudy areas: A novel deep learning approach for SAR-Optical fusion integrating spatiotemporal features by Mingqi Li, Pengxin Wang, Kevin Tansey, Fengwei Guo, Ji Zhou

“…Secondly, the 2D CNN-Transformer predicted LAI and the Sentinel-2 LAI are input into the Enhanced Deep Convolutional Model for Spatiotemporal Image Fusion (EDCSTFN) model to further improve the accuracy. …”
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CC-Former: Urban Flood Mapping from InSAR Coherence with Vision Transformer: Libya and Storm Daniel as Test Case by T. Saleh, T. Saleh, T. Saleh, S. Holail, M. Al-Saad, F. Xu, M. Zahran, G.-S. Xia, G.-S. Xia

“…Specifically, CC-Former utilizes two Siamese weight-sharing encoders to extract multi-scale features from input InSAR coherence images and employs a decoder to generate final predictions. Additionally, we propose a coherence-based scaling (CoBS) module designed to focus on the acquired coherence features of urban flood classes and mitigate the imbalanced distribution of training classes. …”
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Correspondence between thalamic injury-induced changes in resting-state fMRI of monkeys and their sensorimotor behaviors and neural activities by Anirban Sengupta, Pai-Feng Yang, Jamie L. Reed, Arabinda Mishra, Feng Wang, Isaac V Manzanera Esteve, Zhangyan Yang, Li Min Chen, John C. Gore

“…Electrophysiological measurements of inter-electrode coherences and end-point histological measures also aligned well with the graded injury effects measured using rsfMRI-based FC. A simple algorithm employing FC measures from the somatosensory network could accurately predict each monkeys’ behavioral recovery timeframe after four weeks post-injury. …”
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Cardiac Magnetic Resonance Imaging with Myocardial Strain Assessment Correlates with Cardiopulmonary Exercise Testing in Patients with Pectus Excavatum by André Lollert, Tariq Abu-Tair, Tilman Emrich, Karl-Friedrich Kreitner, Alexander Sterlin, Christoph Kampmann, Gundula Staatz

“…A positive correlation between radial strain rate at the RV base and percentage of predicted maximum heart rate (rho = 0.72, <i>p</i> = 0.001) was shown, with equivalent results for circumferential strain rate (rho = −0.64, <i>p</i> = 0.005). …”
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Changes in parasite traits, rather than intensity, affect the dynamics of infection under external perturbation. by Suma Ghosh, Matthew J Ferrari, Ashutosh K Pathak, Isabella M Cattadori

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Elementary Growth Modes provide a molecular description of cellular self-fabrication. by Daan H de Groot, Josephus Hulshof, Bas Teusink, Frank J Bruggeman, Robert Planqué

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Upper thermal limits differ among and within component species in a tritrophic host-parasitoid-hyperparasitoid system. by Salvatore J Agosta, Kanchan A Joshi, Karen M Kester

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Optimizing circadian drug infusion schedules towards personalized cancer chronotherapy. by Roger J W Hill, Pasquale F Innominato, Francis Lévi, Annabelle Ballesta

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Experimental Investigation on Impact of EGR Configuration on Exhaust Emissions in Optimized PCCI-DI Diesel Engine by Getachew Alemayehu, Ramesh Babu Nallamothu, Deresse Firew, Rajendiran Gopal

“…Methanol port injection, dieseline direct injection, advanced injection timing, and different EGR rates were adapted and optimized on the baseline engine. A hybrid algorithm of grey relational analysis with the Taguchi method was implemented for optimization. …”
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Another look at the nb.t in the Moscow Mathematical Papyrus by George M. Hollenback

“…The area is found by configuring the two given dimensions as the sides of a rectangle and then reducing the long side of the rectangle by two successive reductions of    : 9 – = 8, and 8 – =7   , the product of 7   and 4½ yielding the area of the figure, 32. …”
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Modelling of Gust Factor Based Dynamic Loading of Buildings Using Python Programming by Pankaj Dumka, Rishika Chauhan, Amit Srivastava

“…Notably, it has also been observed that the wind loads decrease with the height due to reductions in the tributary area and the top mean floor height.…”
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Direct Estimation of Forest Aboveground Biomass from UAV LiDAR and RGB Observations in Forest Stands with Various Tree Densities by Kangyu So, Jenny Chau, Sean Rudd, Derek T. Robinson, Jiaxin Chen, Dominic Cyr, Alemu Gonsamo

“…Then we train a deep learning model on annotations derived from MCWS to make crown predictions on UAV red, blue, and green (RGB) tiles. …”
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Meso-scale network analysis of resting state-fMRI brain network connectivity performs poorly as a prognostic tool in critically ill traumatic brain injury patients by Jonathan Tjerkaski, William H. Thompson, Bo-Michael Bellander, Eric P. Thelin, Peter Fransson

“…Thus, although graph theoretical measures applied to brain network connectivity patterns have previously been reported to be associated with cognitive dysfunction, they appear to be unable to predict long-term functional outcomes in critically ill TBI patients. …”
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A nomogram combining clinical features, O-RADS US, and radiomics based on ultrasound imaging for diagnosing ovarian cancer by Wenting Xie, Yaoqin Wang, Zhongshi Du, Yijie Chen, Xiaohui Ke, Tingfan Wu, Zhilan Wang, Lina Tang

“…Combination nomogram model that integrates clinical features, O-RADS US, and radiomics based on ultrasound image analysis could predict ovarian malignancy with high diagnostic accuracy, indicating that this model might have a role in preoperative diagnosis for differentiating benign and malignant ovarian tumors.…”
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Sensitivity analysis of six soil organic matter models applied to the decomposition of animal manures and crop residues by Daniele Cavalli, Pietro Marino Gallina, Luca Bechini

“…Moreover, models implementing Monod kinetics predicted positive priming effects of native organic matter after soil amendment, according to co-metabolism theory. …”
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Assessing the Effect of Water on Submerged and Floating Plastic Detection Using Remote Sensing and K-Means Clustering by Lenka Fronkova, Ralph P. Brayne, Joseph W. Ribeiro, Martin Cliffen, Francesco Beccari, James H. W. Arnott

“…A K-Means unsupervised clustering algorithm was used to classify the images into two clusters: plastic and water. …”
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