Deep Learning Strategies for Intraday Optimal Carbon Options Trading with Price Impact Considerations by Qianhui Lai, Qiang Yang

“…Using the data from the European carbon market, we apply our deep learning strategy to four types of price impact functions: linear, logarithmic, power law, and time-varying. …”
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Autonomous deployment and energy efficiency optimization strategy of UAV based on deep reinforcement learning by Yi ZHOU, Xiaoyong MA, Fuxiao GAO, Wei LI, Nan CHENG, Ning LU

“…Utilizing a UAV to build aerial mobile small cell can provide more flexible and efficient access services for ground terminal users.Constrained by the coverage and limited energy of the UAV,it is necessary to study how to build a fast,efficient and energy-saving air-ground collaborative network.To deal with complex dynamic scenarios,the UAV needs to deploy an optimal coverage position,and meanwhile reduce both path loss and energy consumption in the deployment process.Based on the deep reinforcement learning,a strategy of autonomous UAV deployment and efficiency optimization was proposed.The coverage state set of UAV was established,and the energy efficiency was used as a reward function.Depth neural network and Q-learning were used to guide UAV to make autonomous decision and deploy the optimal position.The simulation results show that the deployment time of the proposed method can be effectively reduced by 60%,while the energy consumption can be reduced by 10%~20%.…”
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Learning the diffusion of nanoparticles in liquid phase TEM via physics-informed generative AI by Zain Shabeeb, Naisargi Goyal, Pagnaa Attah Nantogmah, Vida Jamali

“…Herein, we present LEONARDO, a deep generative model that leverages a physics-informed loss function and an attention-based transformer architecture to learn the stochastic motion of nanoparticles in LPTEM. …”
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Lessons learned from 5 years of pegvaliase in US clinics: A case series by Erin Cooney, Zineb Ammous, Tricia Bender, Gillian E. Clague, Marilyn Clifford, Angela Crutcher, Laura Davis-Keppen, Kirsten Havens, Melissa Lah, Stephanie Sacharow, Amarilis Sanchez-Valle, Erika Vucko, Bridget Wardley, Leah Wessenberg, Hans C. Andersson

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PCOS and Inositols – Advances and Lessons We are Learning. A Narrative Review by Lentini G, Querqui A, Monti N, Bizzarri M

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Using multiple machine learning algorithms to optimize the water quality index model and their applicability by Fei Ding, Shilong Hao, Wenjie Zhang, Mingcen Jiang, Liangyao Chen, Haobin Yuan, Nan Wang, Wenpan Li, Xin Xie

“…Six combined weights were determined by game theory combining objective and subjective weights (AHP). Three aggregation functions were established, including a new function proposed based on the sigmoid function and two existing functions. …”
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Network security traffic detection and legal supervision based on adaptive metric learning algorithm by Liu Zhen

“…This paper proposes an adaptive algorithm of metric learning based on deep learning, which classifies and learns the source domain images, and adds and modifies the classification margin to enrich the aligned classification boundary images. …”
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Intelligent Rail Flaw Detection System Based on Deep Learning and Support Vector Machine by Jiangping LUO, Xizhuo YU, Jingwei CAO, Weihong DU

“…Currently, detection systems of rail flaw detection vehicles in China have automatic flaw recognition function, which has problems with low accuracy, high false alarm rate and occurrence of underreport because of the adoption of simple logic judgment method based on the existing rules. …”
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Lived Experiences of Technology and Livelihood Education Teachers on the Challenges and Benefits of Facilitating Online Learning by Evelyn Jaurigue-Sublay

“…This is encouraged for the academic program to function.…”
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Machine Learning Algorithms in EEG Analysis of Kleefstra Syndrome: Current Evidence and Future Directions by Katerina D. Tzimourta

“…The electroencephalogram (EEG) serves as a non-invasive tool to explore brain function in KS; yet, systematic characterizations of EEG features remain extremely limited. …”
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Reinforcement Learning Control Design for Perching Maneuver of Unmanned Aerial Vehicles with Wind Disturbances by ZHANG Weizhen, HE Zhen, TANG Zhangfan

“…Then, the SINDYc method is employed to learn sparse models of the perching system offline under different wind conditions, using historical data and a candidate function library, to effectively identify the wind information. …”
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An Efficient Aircraft Conflict Detection and Resolution Method Based on an Improved Reinforcement Learning Framework by Qiucheng Xu, Zhangqi Chen, Fangfang Li, Zhiyuan Shen, Wenbin Wei

“…This paper proposes an improved reinforcement learning framework to achieve conflict detection and resolution. …”
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Research on the correlation between gut microbiota and brain cognitive function under chronic hypoxia at high altitude by Feng Zeng, Hanxue Li, Yan Ma, Yan Ma, Shuang Ma, Shuang Ma

“…All groups had free access to water; CA and HA groups received oral administration of a four-antibiotic cocktail in drinking water to deplete gut microbiota and establish pseudo-germ-free mouse models. Cognitive function was assessed by the Morris water maze, Expression levels of hippocampal BDNF, SYP, and PSD-95 were determined using Western blotting. …”
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Abnormal Resting-State Functional Connectivity Strength in Mild Cognitive Impairment and Its Conversion to Alzheimer’s Disease by Yuxia Li, Xiaoni Wang, Yongqiu Li, Yu Sun, Can Sheng, Hongyan Li, Xuanyu Li, Yang Yu, Guanqun Chen, Xiaochen Hu, Bin Jing, Defeng Wang, Kuncheng Li, Frank Jessen, Mingrui Xia, Ying Han

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Evaluation of the efficacy of Tai Chi on the cognitive function of patients with mild cognitive dysfunction and research on its mechanism by Lin Lin, Lin Lin, Yao-Xi He, Quan Wen, Jia-Yang Liu, Yu Dai, Yu-Zhe Fei, Hang Li, Chang-Qing Li, Huan Zhou, Huan Zhou

“…The Montreal Cognitive Assessment (MoCA), Trail Making Test-A (TMT-A), Auditory Verbal Learning Test (AVLT), and biochemical assessments (measuring brain-derived neurotrophic factor, BDNF, and platelet factor 4, PF4) were administered to investigate overall cognitive function, executive function, memory capacity, and changes in serum concentrations of BDNF and PF4 before, after, and during the follow-up period. …”
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Prediction of the Control Effect of Fractured Leakage in Unconventional Reservoirs Using Machine Learning Method by Lei Pu, Jianjian Song, Mingbiao Xu, Jun Zhou, Peng Xu, Shanshan Zhou

“…The training was carried out based on the collected field data, the appropriate activation function was set, and the deep well network structure was optimized. …”
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Deep Learning-Based Multitarget Motion Shadow Rejection and Accurate Tracking for Sports Video by Chunxia Duan

“…The detector first scans each sports video image frame one by one, observing the previously discovered and learned image frame subregions one by one until the current moment that is highly like the target to be tracked. …”
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End-to-end handwritten Ge’ez multiple numerals recognition using deep learning by Ruchika Malhotra, Maru Tesfaye Addis

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Computer-Assisted Autonomous Linguistic Learning: A Novel Approach to Second Language Expertise by Eda Başak Hancı-Azizoglu, Ersen Vural

“…Within the context of this research study, an accomplished learner’s think-aloud process and autoethnography function as data to internalize how a learner can transform from a language learner to a language expert through autonomous computer-assisted language learning strategies. …”
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Cross-View Correspondence Modeling for Joint Representation Learning Between Egocentric and Exocentric Videos by Zhehao Zhu, Yoichi Sato

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