DeepBase: A Deep Learning-based Daily Baseflow Dataset across the United States by Parnian Ghaneei, Hamid Moradkhani

“…Recognizing the shortage in accessible high quality daily baseflow data, our objective is to generate a daily baseflow dataset across the contiguous United States (CONUS) for 1661 basins from 1981 to 2022. …”
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Battery State of Charge and State of Health Estimation Using a New Hybrid Deep Neural Network Approach by Saeid Jorkesh, Ryan Ahmed, Saeid Habibi, Reza Hosseininejad, Siyuan Xu

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The Doomsday Project, Deep Events, and the Shrinking of American Democracy by Peter Dale Scott

Subjects: “…United States…”
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Progress and insights from worldwide deep coalbed methane exploration and development by Jiaqi ZHANG, Zengqin LIU, Baojian SHEN, Shihu ZHAO, Xinjun CHEN, Jincheng YE

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Geospatial modeling of near subsurface temperatures of the contiguous United States for assessment of materials degradation by Jonathan E. Gordon, Olatunde D. Akanbi, Deepa C. Bhuvanagiri, Hope E. Omodolor, Vibha Mandayam, Roger H. French, Jeffrey M. Yarus, Erika I. Barcelos

“…Model performance generally decreased with depth, highlighting challenges in deep temperature prediction. State-level analyses emphasized the importance of considering local geological factors. …”
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A Hybrid Deep Learning Method for the Estimation of the State of Health of Lithium-Ion Batteries by Shuo Cheng

“…This paper proposes a method for estimating the state of health (SOH) of lithium-ion batteries (LIBs) using a combination of vision transformer (VIT) and gated recurrent unit (GRU) networks. …”
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Lithium-Ion Battery State of Health Degradation Prediction Using Deep Learning Approaches by Talal Alharbi, Muhammad Umair, Abdulelah Alharbi

“…The NASA battery dataset, containing charging and discharging cycles, is used for model training and evaluation. Three deep learning architectures 1D Convolutional Neural Networks (CNN), CNN plus Long Short-Term Memory (LSTM), and CNN plus Gated Recurrent Units (GRU) are used in the centralized approach. …”
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Deep learning models reveal the link between dynamic brain connectivity patterns and states of consciousness by Chloé Gomez, Lynn Uhrig, Vincent Frouin, Edouard Duchesnay, Béchir Jarraya, Antoine Grigis

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Promoting Internal Armed Conflict Resolution and Peacebuilding: The Case of the U.S.-Colombia Relations (Part II) by A. A. Manukhin

“…In the present paper the author continues the study of the challenges faced by Colombia in its struggle to overcome the internal armed conflict, as well as the role of the United States in this process. By 2010 the confrontation between the government forces and the armed rebels had reached a breaking point opening the way to a successful conclusion of the Government of Colombia–FARC peace negotiations and the beginning of the country’s post-conflict reconstruction. …”
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Effect of Dam Emplacement and Water Level Changes on Sublacustrine Geomorphology and Recent Sedimentation in Jackson Lake, Grand Teton National Park (Wyoming, United States) by Michael M. McGlue, John R. Dilworth, Hillary L. Johnson, Samuel J. Whitehead, J. Ryan Thigpen, Kevin M. Yeager, Edward W. Woolery, Summer J. Brown, Sarah E. Johnson, Cooper S. Cearley, Gillian M. Clark, T. Spencer Dixon, Ryan C. Goldsby, Autumn L. Helfrich, Bailee N. Hodelka, Edward L. Lo, Leandro Domingos-Luz, Nicholas E. Powell, Giliane G. Rasbold, William R. Swanger

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A diáspora coreana: o caso brasileiro by Bruna Mineo Antonio, José Renato de Campos Araújo

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A land-cover-assisted super-resolution model for retrospective reconstruction of MODIS-like NDVI data across the continental United States by blending Landcover300m and GIMMS NDVI3... by Zhicheng Zhang, Zhenhua Xiong, Xuewen Zhou, Kun Xiao, Wei Wu, Qinchuan Xin

“…This study introduces a novel deep learning-based model, termed the Land-Cover-assisted Super-Resolution SpatioTemporal Fusion model (LCSRSTF), designed to produce biweekly 500-meter MODIS-like data spanning from 1992 to 2010 across the Continental United States (CONUS). …”
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Feature Representations Using the Reflected Rectified Linear Unit (RReLU) Activation by Chaity Banerjee, Tathagata Mukherjee, Eduardo Pasiliao Jr.

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Pedestrian navigation: how can inertial measurment units assist smartphones? by I. A. Chistyakov, I. V. Grishov, A. A. Nikulin, M. V. Pikhletsky, I. B. Gartseev

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Validation of deep-learning accelerated quantitative susceptibility mapping for deep brain nuclei by Ying Zhou, Ying Zhou, Lingyun Liu, Shan Xu, Yongquan Ye, Ruiting Zhang, Minming Zhang, Jianzhong Sun, Peiyu Huang

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Deep Learning-Assisted Short-Term Power Load Forecasting Using Deep Convolutional LSTM and Stacked GRU by Fath U Min Ullah, Amin Ullah, Noman Khan, Mi Young Lee, Seungmin Rho, Sung Wook Baik

“…The generated feature map is forward propagated into a deep gated recurrent unit (GRU) network for learning, which provides the final PLF. …”
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Application and risk response of deep synthesis technology by Jingwen LI, Yawen LI

“…Deep synthesis technology is a widely used application in the field of artificial intelligence, particularly in intelligent services, audio and video production, media communication and information services.A basic research was conducted on the principle and implementation of deep synthesis technology.And the application of deep synthesis technology were analyzed, such as robot writing, voice synthesis, intelligent customer service, voice replication, face synthesis, posture manipulation, virtual characters and virtual scenes.Based on the analysis of the characteristics and development trend of the application of deep synthesis, the risks brought by the application of deep synthesis technology were summarized, such as the generation and dissemination of false information, infringement of the legitimate rights and interests of others, utilization by other illegal and criminal activities, and impact on national security.The measures taken by the EU, United States and China to govern the application of deep synthesis technology were studied and the countermeasures were recommended such as building a comprehensive regulatory rule system, strengthening technical supervision, and improving risk prevention awareness across society.Furthermore, the need for intelligence, authenticity, and universality in the application of deep synthesis technology was highlighted.Based on the analysis of the characteristics and development trends of deep synthesis technology, a comprehensive insight into the potential risks and countermeasures associated with its application governance were provided.…”
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Deep water vetulicolians from the lower Cambrian of China by Shuhan Ma, Julien Kimmig, James D. Schiffbauer, Ruibo Li, Shanchi Peng, Xianfeng Yang

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Energy sufficiency for deep decarbonization: A modeling framework by Jingjing Zhang, Michelle Johnson-Wang, Nina Khanna, Max Wei, Bianka Shoai-Tehrani, Nan Zhou

“…DRUMSS provides steps for implementing sufficiency measures across demand-side sectors, identifying policy actions to achieve deep decarbonization. We present three case studies, from the United States, China, and France, to illustrate implementing the DRUMSS framework in diverse contexts. …”
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