Automated recognition of deep-sea benthic megafauna in polymetallic nodule mining areas based on deep learning by Guofan Long, Wei Song, Xiangchun Liu, Ziyao Fang, Jinqi An, Kun Liu, Yaqin Huang, Xuebao He

“…Its backbone integrates deformable convolutions, attention mechanisms, and ResNet structures to improve feature extraction and reduce background interference. …”
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First M87 Event Horizon Telescope Results. VI. The Shadow and Mass of the Central Black Hole by The Event Horizon Telescope Collaboration, Kazunori Akiyama, Antxon Alberdi, Walter Alef, Keiichi Asada, Rebecca Azulay, Anne-Kathrin Baczko, David Ball, Mislav Baloković, John Barrett, Dan Bintley, Lindy Blackburn, Wilfred Boland, Katherine L. Bouman, Geoffrey C. Bower, Michael Bremer, Christiaan D. Brinkerink, Roger Brissenden, Silke Britzen, Avery E. Broderick, Dominique Broguiere, Thomas Bronzwaer, Do-Young Byun, John E. Carlstrom, Andrew Chael, Chi-kwan Chan, Shami Chatterjee, Koushik Chatterjee, Ming-Tang Chen, Yongjun Chen, Ilje Cho, Pierre Christian, John E. Conway, James M. Cordes, Geoffrey B. Crew, Yuzhu Cui, Jordy Davelaar, Mariafelicia De Laurentis, Roger Deane, Jessica Dempsey, Gregory Desvignes, Jason Dexter, Sheperd S. Doeleman, Ralph P. Eatough, Heino Falcke, Vincent L. Fish, Ed Fomalont, Raquel Fraga-Encinas, Per Friberg, Christian M. Fromm, José L. Gómez, Peter Galison, Charles F. Gammie, Roberto García, Olivier Gentaz, Boris Georgiev, Ciriaco Goddi, Roman Gold, Minfeng Gu, Mark Gurwell, Kazuhiro Hada, Michael H. Hecht, Ronald Hesper, Luis C. Ho, Paul Ho, Mareki Honma, Chih-Wei L. Huang, Lei Huang, David H. Hughes, Shiro Ikeda, Makoto Inoue, Sara Issaoun, David J. James, Buell T. Jannuzi, Michael Janssen, Britton Jeter, Wu Jiang, Michael D. Johnson, Svetlana Jorstad, Taehyun Jung, Mansour Karami, Ramesh Karuppusamy, Tomohisa Kawashima, Garrett K. Keating, Mark Kettenis, Jae-Young Kim, Junhan Kim, Jongsoo Kim, Motoki Kino, Jun Yi Koay, Patrick M. Koch, Shoko Koyama, Michael Kramer, Carsten Kramer, Thomas P. Krichbaum, Cheng-Yu Kuo, Tod R. Lauer, Sang-Sung Lee, Yan-Rong Li, Zhiyuan Li, Michael Lindqvist, Kuo Liu, Elisabetta Liuzzo, Wen-Ping Lo, Andrei P. Lobanov, Laurent Loinard, Colin Lonsdale, Ru-Sen Lu, Nicholas R. MacDonald, Jirong Mao, Sera Markoff, Daniel P. Marrone, Alan P. Marscher, Iván Martí-Vidal, Satoki Matsushita, Lynn D. Matthews, Lia Medeiros, Karl M. Menten, Yosuke Mizuno, Izumi Mizuno, James M. Moran, Kotaro Moriyama, Monika Moscibrodzka, Cornelia Müller, Hiroshi Nagai, Neil M. Nagar, Masanori Nakamura, Ramesh Narayan, Gopal Narayanan, Iniyan Natarajan, Roberto Neri, Chunchong Ni, Aristeidis Noutsos, Hiroki Okino, Héctor Olivares, Tomoaki Oyama, Feryal Özel, Daniel C. M. Palumbo, Nimesh Patel, Ue-Li Pen, Dominic W. Pesce, Vincent Piétu, Richard Plambeck, Aleksandar PopStefanija, Oliver Porth, Ben Prather, Jorge A. Preciado-López, Dimitrios Psaltis, Hung-Yi Pu, Venkatessh Ramakrishnan, Ramprasad Rao, Mark G. Rawlings, Alexander W. Raymond, Luciano Rezzolla, Bart Ripperda, Freek Roelofs, Alan Rogers, Eduardo Ros, Mel Rose, Arash Roshanineshat, Helge Rottmann, Alan L. Roy, Chet Ruszczyk, Benjamin R. Ryan, Kazi L. J. Rygl, Salvador Sánchez, David Sánchez-Arguelles, Mahito Sasada, Tuomas Savolainen, F. Peter Schloerb, Karl-Friedrich Schuster, Lijing Shao, Zhiqiang Shen, Des Small, Bong Won Sohn, Jason SooHoo, Fumie Tazaki, Paul Tiede, Remo P. J. Tilanus, Michael Titus, Kenji Toma, Pablo Torne, Tyler Trent, Sascha Trippe, Shuichiro Tsuda, Ilse van Bemmel, Huib Jan van Langevelde, Daniel R. van Rossum, Jan Wagner, John Wardle, Jonathan Weintroub, Norbert Wex, Robert Wharton, Maciek Wielgus, George N. Wong, Qingwen Wu, André Young, Ken Young, Ziri Younsi, Feng Yuan, Ye-Fei Yuan, J. Anton Zensus, Guangyao Zhao, Shan-Shan Zhao, Ziyan Zhu, Joseph R. Farah, Zheng Meyer-Zhao, Daniel Michalik, Andrew Nadolski, Hiroaki Nishioka, Nicolas Pradel, Rurik A. Primiani, Kamal Souccar, Laura Vertatschitsch, Paul Yamaguchi

“…Associating the crescent feature with the emission surrounding the black hole shadow, we infer an angular gravitational radius of GM / Dc ^2  = 3.8 ± 0.4 μ as. …”
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Automated Fixed-Point Precision Optimization for FPGA Synthesis by Ines Winandy, Arnaud Dion, Florent Manni, Pierre-Loic Garoche, Dorra Ben Khalifa, Matthieu Martel

“…While fixed-point arithmetic offers significant performance and area advantages over floating-point implementations, deriving an appropriate fixed-point representation remains a challenging task. In particular, developers must carefully select the number of bits assigned to the integer and fractional parts of each variable to balance accuracy and resource consumption. …”
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Simultaneous profiling of classic and 11-oxygenated androgens via a novel derivatization method coupled with HPLC-MS/MS: A game-changer for endocrine disorders by Xianhua Zhang, Huiyu Xu, Yue Sun, Xin Xiong, Lingling Liu, Li Yang, Libo Zhao, Xiaona Li, Rong Li, Rongsheng Zhao

“…A novel quaternary ammonium aminooxy (QAO) reagent was employed as the derivatization agent, featuring a permanently charged MS-tag and an aminooxy group that reacts with steroid ketone groups. …”
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Deep learning-driven modality imputation and subregion segmentation to enhance high-grade glioma grading by Jiabin Yu, Qi Liu, Chenjie Xu, Qinli Zhou, Jiajun Xu, Lingying Zhu, Chen Chen, Yahan Zhou, Binggang Xiao, Lin Zheng, Xiaofeng Zhou, Fengming Zhang, Yuhang Ye, Hongmei Mi, Dongping Zhang, Li Yang, Zhiwei Wu, Jiayi Wang, Ming Chen, Zhirui Zhou, Haoyang Wang, Vicky Y. Wang, Enyu Wang, Dong Xu

“…Abstract Purpose This study aims to develop a deep learning framework that leverages modality imputation and subregion segmentation to improve grading accuracy in high-grade gliomas. …”
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External Validation of a Risk Prediction Model for Atherosclerotic Cardiovascular Diseases in a Large National Health‐Checkup and Claim Database by Takanori Honda, Yoshihiko Furuta, Akihiro Maezono, Sanmei Chen, Yuki Ishida, Hiroko Furuhashi, Masaya Kumamoto, Emi Oishi, Yasumi Kimura, Daigo Yoshida, Toshiharu Ninomiya

“…Background The Hisayama risk prediction model for atherosclerotic cardiovascular diseases (ASCVDs) has been featured in the latest Japanese preventive guidelines, yet it lacks external validation. …”
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Machine learning-guided field site selection for river classification by Zhihao Wang, Gregory Brian Pasternack, Yufang Jin, Costanza Rampini, Serena Alexander, Nikhil Kumar, Rune Storesund, K. Martin Perales, Christopher Lim, Stephanie Moreno, Igor Lacan

“…Machine learning has been recognized for discovering and extracting streams’ geomorphic patterns efficiently and accurately from data, but its application in field site sampling design is still in its infancy. This study developed a general and practical field site selection framework by incorporating machine learning in a human-in-the-loop manner. …”
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Assessing the influence of lived-experience experts on healthcare providers in a virtual community of practice: a qualitative study by Stephanie Sargent Weaver, Monique Carry, Jeanne Bertolli, Job Godino, Job Godino, Bruce Struminger, Douglas Taren, John D. Scott, Sydney P. Sharp, Jane Samaniego, Donna R. Bean, Anindita Issa, Jin-Mann S. Lin, Elizabeth R. Unger, Christian B. Ramers

“…A distinctive feature of LC&FIRP was the inclusion of lived-experience experts. …”
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Lightweight grading segmentation network for powdery mildew based on model pruning and knowledge distillation by Yuheng Li, Lisha Ye, Yu Zhang, Lijuan Zhou, Qian Chen

“…To bridge this gap, this study develops and validates light-PMSeg, a lightweight instance segmentation framework designed for accurate, real-time disease grading. …”
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Polygenic prediction of human longevity on the supposition of pervasive pleiotropy by M. Reza Jabalameli, Jhih-Rong Lin, Quanwei Zhang, Zhen Wang, Joydeep Mitra, Nha Nguyen, Tina Gao, Mark Khusidman, Sanish Sathyan, Gil Atzmon, Sofiya Milman, Jan Vijg, Nir Barzilai, Zhengdong D. Zhang

“…Abstract The highly polygenic nature of human longevity renders pleiotropy an indispensable feature of its genetic architecture. Leveraging the genetic correlation between aging-related traits (ARTs), we aimed to model the additive variance in lifespan as a function of the cumulative liability from pleiotropic segregating variants. …”
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Chemoreactomic analysis of the drug prototype рilim-1 in comparison with zinc derivatives of nonsteroidal anti-inflammatory drugs by P. A. Galenko-Yaroshevsky, I. Y. Torshin, A. N. Gromov, I. A. Reyer, O. A. Gromova, B. A. Trofimov, L. N. Parshina, R. A. Murashko, O. V. Shelemekh, A. V. Zadorozhniy, V. L. Popkov, A. V. Zelenskaya, I. B. Nektarevskaya, A. V. Sergeeva, A. V. Uvarov, Yu. V. Tovkach, I. V. Sholl

“…The chemoreactome assessment of the pharmacological properties of рilim-1 and zinc derivatives of known NSAIDs (ketorolac, diclofenac and nimesulide) was carried out using the methods of chemoinformation analysis of molecules developed at the scientific school of Academician Yu.I. …”
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Mapping Antarctic Blue Ice Areas With Sentinel-2A/B Images and LightGBM Model by Xiaolong Teng, Jiahui Xu, Xiangbin Cui, Guitao Shi, Zhengyi Hu, Qingyu Gu, Bailang Yu, Jianping Wu, Yan Huang

“…This study integrated remote sensing techniques with ensemble learning algorithms to develop a high-resolution (10 m) Antarctic-wide BIA dataset using Sentinel-2 imagery based on the years 2017–2022. …”
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The Application of Imperialist Competitive Algorithm in Determining the Optimal Parameters of Empirical Area Reduction Method to Predict the Sedimentation Process in Dez Dam by Arash Azari, Sadegh Soori Hossein Bonakdari, Hossein Bonakdari

“…Common methods for correcting these curves after reservoir sedimentation have been developed based on the conditions and statistics and information recorded in reservoirs abroad. …”
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The Persistent Threat of Chronic Inflammation on the Mortality Among Cervical Cancer Survivors: A Mendelian Randomization and Machine Learning Analysis Using UK Biobank and Chinese... by Wang J, Chen Z, Guan M, Ma Z, Peng L, Chen J, Fiori PL, Carru C, Capobianco G, Coradduzza D, Zhou L

“…Nine ML and logistic regression (LR) integrated prognosis models were developed for 1042 subjects with cervical cancer (random allocation into training and validation cohorts at 6:4 ratio).Results: Three potential causative CIMs for cervical cancer were identified via a two-sample MR. …”
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Investigating Protective and Risk Factors and Predictive Insights for Aboriginal Perinatal Mental Health: Explainable Artificial Intelligence Approach by Guanjin Wang, Hachem Bennamoun, Wai Hang Kwok, Jenny Paola Ortega Quimbayo, Bridgette Kelly, Trish Ratajczak, Rhonda Marriott, Roz Walker, Jayne Kotz

“…ObjectiveWe explored different explainable artificial intelligence (XAI)–powered machine learning techniques for developing culturally informed, strengths-based predictive modeling of perinatal psychological distress among Aboriginal mothers. …”
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Design of Block-Scrambling-Based privacy protection mechanism in healthcare using fusion of transfer learning models with Hippopotamus optimization algorithm by Ghada Moh. Samir Elhessewi, Mohammed Yahya Alzahrani, Mohammad Alamgeer, Abdulbasit A. Darem, Da’ad Albalawneh, Mohammed Alqahtani, Mutasim Al Sadig, Sultan Alanazi

“…At first, the block-scrambling-based encryption (BSBE) technique is utilized in the image encryption pre-processing stage, and then the decryption process is performed. The feature extraction process employs the fusion of MobileNetV2, GoogLeNet, and AlexNet techniques. …”
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Diagnostic and prognostic role of 18F-FDG PET/CT for sarcomatoid differentiation in renal cell carcinoma by Ritai Na, Zhao Chen, Yongshun Liu, Qianrui Chen, Qi Yang, Yongkang Qiu, Tianyao Wang, Lele Song, Sitong Wu, Wenpeng Huang, Xinyao Sun, Shaozhong Xian, Lei Kang

“…Abstract Background Sarcomatoid differentiation is an invasive dedifferentiated feature of tumor and associated with poor prognosis in renal cell carcinoma (RCC) patients. …”
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Bi‐Regional Machine Learning Radiomics Based on CT Noninvasively Predicts LOX Expression Level and Overall Survival in Hepatocellular Carcinoma by Kexin Gao, Musa Yaermaimaiti, Yiwei Wang, Guanggai Xia, Ting Xu, Hongcheng Wang

“…Two radiomic models were developed using the least absolute shrinkage and selection operator (LASSO) regression analysis. …”
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OSBPL3 modulates the immunosuppressive microenvironment and predicts therapeutic outcomes in pancreatic cancer by Qihui Sun, Xiaoqi Zhu, Qi Zou, Yang Chen, Tingting Wen, Tingting Jiang, Xiaojia Li, Fang Wei, Keping Xie, Jia Liu

“…Results Our risk prediction model, developed using machine learning algorithms, demonstrated high predictive accuracy across multiple datasets. …”
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A Detailed Investigation of HD 209458 b HST and JWST Transmission Spectra with SANSAR by Avinash Verma, Jayesh Goyal, Swaroop Avarsekar, Gaurav Shukla

“…In particular, even though we can detect the CO _2 feature with just NIRCam, we cannot constrain its abundances robustly without the optical baseline.…”
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