Results 171 to 180 of about 56,994 (264)

Rockburst prediction based on data preprocessing and hyperband‐RNN‐DNN

Deep Underground Science and Engineering, EarlyView.
A data preprocessing workflow is proposed to address challenges in rockburst data analysis. Coupled algorithms preprocess the data set, and hyperband optimization is used to enhance RNN performance. Results show that preprocessing improves accuracy, while dense layers enhance model stability and prediction performance.
Yong Fan, Chenxi Yin, Guangdong Yang, Shengyong Ding, Bin Tian   +4 more
wiley   +1 more source

Shock wave propagation characteristics of aluminum‐containing explosive in corrugated steel‐lined tunnel

Deep Underground Science and Engineering, EarlyView.
Aluminum‐enhanced afterburning renders AE explosives more hazardous than conventional ones. Corrugated steel linings reduce far‐field AE blast overpressure by ~50% through wave reflection and dissipation. The developed model accurately predicts peak pressure (<10% error) and arrival time (<3% error), supporting protective design.
Zhen Wang, Jiayu Peng, Hujun Li, Yuguo Ji, Shuobiao Li, Guokai Zhang   +5 more
wiley   +1 more source

Unveiling spatial heterogeneity in urban underground space development patterns and mechanisms for differentiated planning: A points of interest‐based study of Shanghai

Deep Underground Science and Engineering, EarlyView.
This study investigated the spatial patterns and development mechanisms of urban underground space (UUS) in Shanghai using underground points of interest data. It revealed distinct development mechanisms between the main city and suburbs, highlighting the need for differentiated UUS planning and policies to optimize underground space resources ...
Chenxiao Ma, Fangle Peng, Yongkang Qiao, Yunhao Dong   +3 more
wiley   +1 more source

Unsupervised clustering of electroclinical features in temporal lobe epilepsy: A data‐driven approach

Epileptic Disorders, EarlyView.
Abstract Objective To identify clinically meaningful patterns in ictal electroclinical features of focal epilepsy using a data‐driven, unsupervised learning approach, and to assess whether such patterns can localize and lateralize the epileptogenic zone (EZ) more accurately than conventional electroclinical interpretation.
Maria Vlachou, Bernadett Molnár, Helene Kaas, Jesper Tveit, Harald Aurlien, Martin Ejler Fabricius, Guido Rubboli, Lars Hageman Pinborg, Sándor Beniczky   +8 more
wiley   +1 more source

The small molecule simufilam dose‐dependently attenuates the worsening of seizures in a mouse model of tuberous sclerosis complex

Epilepsia, EarlyView.
Abstract Objective Novel epilepsy treatments for patients with tuberous sclerosis complex (TSC) and focal cortical dysplasia type II (FCDII) are urgently needed. In these patients, mutations in the mechanistic target of rapamycin (mTOR) pathway genes lead to mTOR hyperactivity and focal cortical malformations that frequently cause intractable epilepsy ...
Branden Stansley, Md. Monirul Islam, Dean J. Aguiar, Zoë Fuchs, Mackenzie Catron, Stephen Morairty, Ying Yuan, Radleigh Santos, Jingguo Hou, Annelies de Kater, George B. Thornton, Angelique Bordey   +11 more
wiley   +1 more source

Performance of quantile regression methods with discrete outcomes: A simulation study with applications to environmental epidemiology. [PDF]

Environ Epidemiol
Alampi JD, Lanphear BP, McCandless LC.
europepmc   +1 more source

Stereo‐EEG mapping of visual working memory with task‐related high‐gamma modulations

Epilepsia, EarlyView.
Abstract Objective We describe a safe, informative, and easy‐to‐implement approach for presurgical mapping of visual working memory (VWM) with stereo‐electroencephalography (SEEG). Methods Twenty‐four patients with drug‐resistant epilepsy, 11–23 years of age, performed a single‐probe change detection VWM task, during SEEG monitoring.
Brian Ervin, Jason Buroker, Taylor Cummins, Anna W. Byars, Craig Scholle, Leonid Rozhkov, Paul S. Horn, Jeffrey R. Tenney, Hansel M. Greiner, James L. Leach, Jesse Skoch, Francesco T. Mangano, Katherine D. Holland, Ravindra Arya   +13 more
wiley   +1 more source

Factors associated with depressive disorders in college students using quantile regression analysis. [PDF]

BMC Psychiatry
Xu H, Zhang C, Wang Z, Zhang C, Peng L, Liu X.   +5 more
europepmc   +1 more source

Daily Residential Natural Gas Demand Forecasting Using Machine Learning Regression: Comparative Evaluation With a Case Study in Qazvin Province, Iran

Energy Science &Engineering, EarlyView.
This graphical abstract summarizes the proposed framework for improving short‐term residential natural gas consumption forecasting by integrating a novel socioeconomic indicator, the subscription growth ratio (SGR), with conventional meteorological variables.
Ali Pirzad, Mostafa Khanzadi
wiley   +1 more source