Results 111 to 120 of about 123,872 (245)

Value-at-Risk on Central and Eastern European Stock Markets: An Empirical Investigation Using GARCH Models [PDF]

Using daily return data from the four major Central and Eastern European stock markets including fourteen highly liquid stocks and ATX (Vienna), PX (Prague), BUX (Budapest), and WIG20 (Warsaw) market indices, we model the value-at-risk using a set of ...
Vít Bubák
core   +1 more source

Mass‐Produced and High‐Performance Nanowell Biosensor Fabricated via Semiconductor Manufacturing for Rapid and Accurate COVID‐19 Diagnosis in the Clinical Field

Advanced Science, EarlyView.
A semiconductor‐fabricated nanowell biosensor enables rapid, scalable, and highly reproducible detection of SARS‐CoV‐2 antigens from nasal swabs within ∼10 minutes. Clinical validation in 249 retrospective and 243 prospective patient samples demonstrates high sensitivity and specificity, minimal cross‐reactivity, and robust batch‐to‐batch ...
Yoo Min Park, Zahra Rezaei, Nam Ho Bae, Donggee Rho, Da‐Seul Kim, EunYoung Go, YoungTae Seo, Seok Jae Lee, Won Chan Seo, Luke P. Lee, HeaYeon Lee, Su Ryon Shin   +11 more
wiley   +1 more source

Enhancing Short-Term Wind Speed Prediction Based on Deep Learning With Ensemble Learning Model for Small Wind Turbine Applications

IEEE Access
Wind is unstable and unpredictable, and power generation is not constant. Wind speed prediction reduces these disadvantages, and it is essential to measure accurate wind speed predictions to install and stabilize wind power generation systems.
J. Sathyaraj, V. Sankardoss
doaj   +1 more source

PEC‐DFM Hybrid‐Sensor Based on Nanoparticle‐Resolved Estimation for Sensitive and Reversible Glucose Monitoring

Advanced Science, EarlyView.
Abstract The accurate detection of glucose in wound exudate is critically important for monitoring chronic wound healing. While photoelectrochemical (PEC) sensors are widely used, they often suffer from material degradation caused by redox reactions during operation. Herein, we introduce a dark‐field microscopy (DFM) setup integrated with a PEC system,
Zihao Zhang, Junzheng Liu, Qinggong Wu, Yuan Zeng, Gang Xiao, Zhao Yue, Zhigang Zang, Shuang Zhao   +7 more
wiley   +1 more source

INB3P: A Multi‐Modal and Interpretable Co‐Attention Framework Integrating Property‐Aware Explanations and Memory‐Bank Contrastive Fusion for Blood–Brain Barrier Penetrating Peptide Discovery

Advanced Science, EarlyView.
INB3P is a multimodal framework for blood–brain barrier‐penetrating peptide prediction under extreme data scarcity and class imbalance. By combining physicochemical‐guided augmentation, sequence–structure co‐attention, and imbalance‐aware optimization, it improves predictive performance and interpretability.
Jingwei Lv, Qianyang Wu, Jian Liu, Binlu Yang, Yuanhao Li, Junlin Xu, Yajie Meng, Leyi Wei, Zilong Zhang, Quan Zou, Xiulai Li, Feifei Cui   +11 more
wiley   +1 more source

Learning-Driven Intelligent Passivity Control Using Nonlinear State Observers for Induction Motors

Automation
This paper proposes a learning-driven passivity-based control (PBC) strategy for sensorless induction motors, combining a nonlinear adaptive observer with recurrent neural networks (RNNs) to improve robustness and estimation accuracy under dynamic ...
Belkacem Bekhiti, Kamel Hariche, Mohamed Roudane, Aleksey Kabanov, Vadim Kramar   +4 more
doaj   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

Enhanced Deep Learning Method for Natural Gas Pipeline Flow Prediction Based on Integrated Learning

IEEE Access
Urban gas pipelines must contend with situations such as road construction and excavation for house building, where short-term emergencies leading to large-scale leaks pose significant risks to both people and the environment.
Yunhao Li, Changjing Sun, Qiang Li
doaj   +1 more source

Temporal Interference Stimulation Enhances Neural Regeneration

Advanced Science, EarlyView.
Temporal interference (TI) stimulation is proposed as a non‐invasive approach to enhance neural regeneration in the deep brain. Theta‐band TI modulation selectively promotes neural progenitor cell differentiation in vitro and augments hippocampal neurogenesis in amouse model of Alzheimer's disease‐like amyloidosis.
Sofia Peressotti, Maria Garcia Garrido, Patrycja Dzialecka, Rachel Man Hoi Law, Roberto Portillo‐Lara, Bethany Geary, Elena Faillace, Shirine Merlo‐Nikpay Aslie, Marcelina Wojewska, Maria Otero‐Jimenez, Martina Genta, Luqiao Tan, Karen Duff, Javier Alegre‐Abarrategui, Rylie Green, Nir Grossmann   +15 more
wiley   +1 more source

Distance-Based Relevance Function for Imbalanced Regression

Stats
Imbalanced regression poses a significant challenge in real-world prediction tasks, where rare target values are prone to overfitting during model training. To address this, prior research has employed relevance functions to quantify the rarity of target
Daniel Daeyoung In, Hyunjoong Kim
doaj   +1 more source