Results 71 to 80 of about 87,160 (322)

Oil shocks and stock market volatility of the BRICS: A GARCH-MIDAS approach

, 2020
In this study, we employ the GARCH–MIDAS (Generalised Autoregressive Conditional Heteroskedasticity variant of Mixed Data Sampling) model to investigate the response of stock market volatility of the BRICS group of countries (Brazil, Russia, India, China,
Afees A. Salisu, Rangan Gupta
semanticscholar   +1 more source

From Reactive to Proactive Volatility Modeling With Hemisphere Neural Networks

Journal of Applied Econometrics, EarlyView.
ABSTRACT We revisit maximum likelihood estimation (MLE) for macroeconomic density forecasting through a novel neural network architecture with dedicated mean and variance hemispheres. Our architecture features several key ingredients making MLE work in this context.
Philippe Goulet Coulombe, Mikael Frenette, Karin Klieber   +2 more
wiley   +1 more source

Estimating the Impact of Fundamental Macroeconomic Factors on the Capital Market: A MIDAS Approach [PDF]

تحقیقات مالی
ObjectiveAs one of the pillars of financing countries, the stock market plays a key role in the prosperity of economic activities. The key position of the stock market has caused much research to be conducted to identify the factors affecting it.
Reza Tehrani, Mahmoud Moktarband, Menal Aboodeh   +2 more
doaj   +1 more source

MIDAS: Microcluster-Based Detector of Anomalies in Edge Streams [PDF]

AAAI Conference on Artificial Intelligence, 2019
Given a stream of graph edges from a dynamic graph, how can we assign anomaly scores to edges in an online manner, for the purpose of detecting unusual behavior, using constant time and memory?
Siddharth Bhatia, Bryan Hooi, Minji Yoon, Kijung Shin, C. Faloutsos   +4 more
semanticscholar   +1 more source

Cardiac MR Fingerprinting at 0.55T Using a Deep Image Prior for Joint T1, T2, and M0 Mapping

Journal of Magnetic Resonance Imaging, EarlyView.
ABSTRACT Background 0.55T systems offer unique advantages and may support expanded access to cardiac MRI. Purpose To assess the feasibility of 0.55T cardiac MR Fingerprinting (MRF), leveraging a deep image prior reconstruction to mitigate noise. Study Type Phantom and prospective in vivo assessment.
Zhongnan Liu, Zexuan Liu, Imran Rashid, Mauricio Stanzione Galizia, Christopher Scoma, William Truesdell, Prachi Agarwal, Nicole Seiberlich, Liyue Shen, Jesse Hamilton   +9 more
wiley   +1 more source

Automated Coregistered Segmentation for Volumetric Analysis of Multiparametric Renal MRI

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose This study aims to develop and evaluate a fully automated deep learning‐driven postprocessing pipeline for multiparametric renal MRI, enabling accurate kidney alignment, segmentation, and quantitative feature extraction within a single efficient workflow. Methods Our method has three main stages.
Aya Ghoul, Cecilia Liang, Isabelle Loster, Lavanya Umapathy, Bernd Kühn, Petros Martirosian, Ferdinand Seith, Sergios Gatidis, Thomas Küstner   +8 more
wiley   +1 more source

New Advances of Degradable Magnesium‐Based Metal Biomaterials in the Field of Orthopedics

Rare Metals, EarlyView.
ABSTRACT Based on their outstanding biomechanical properties and superior osteogenic activity, magnesium (Mg) and its alloys have been extensively investigated for their biocompatibility and therapeutic efficacy in treating fractures and bone defects.
Jia‐Nan Yu, Shao‐Sheng Jia, Rong‐Bang Sun, Tong Zhang, Ling‐Chuang Bai, Di Mei, Shi‐Jie Zhu, Lan Chen, Shao‐Kang Guan   +8 more
wiley   +1 more source

Versatile High‐Sensitivity EPR Using Superconducting Spiral Microresonators

Small Methods, EarlyView.
A significant sensitivity enhancement in conventional X‐band pulsed EPR is achieved using planar spiral microresonators fabricated from high‐temperature superconducting YBCO. Fully compatible with standard instrumentation, the approach enables high‐fidelity spin control under typical sample conditions.
Gediminas Usevičius, Mantas Šimėnas, Blaise L. Geoghegan, Oscar W. Kennedy, Ignas Pocius, Patrick Hogan, Ana Villanueva Ruiz de Temino, Jean‐Baptiste Verstraete, Paulina Verbaitytė, Angeliki Chatziathanasiou, G. Antilen Jacob, Mindaugas Kamarauskas, Marius Treideris, Paulius Gečys, Joseph Alexander, Vidmantas Kalendra, Jūras Banys, Maxie M. Roessler, John J.L. Morton   +18 more
wiley   +1 more source

UNO: Unified Self‐Supervised Monocular Odometry for Platform‐Agnostic Deployment

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT This work presents UNO, a unified monocular visual odometry framework that enables robust and adaptable pose estimation across diverse environments, platforms and motion patterns. Unlike traditional methods that rely on deployment‐specific tuning or predefined motion priors, our approach generalises effectively across a wide range of real ...
Wentao Zhao, Yihe Niu, Yanbo Wang, Tianchen Deng, Shenghai Yuan, Zhenli Wang, Rui Guo, Jingchuan Wang   +7 more
wiley   +1 more source

Decarbonising Respiratory Care: The Impact of a Low‐Carbon Salbutamol Pressurised Metered‐Dose Inhalers

Allergy, EarlyView.
Healthcare systems contribute up to 5% of global GHG emissions, with inhalers contributing a proportion of these. The carbon footprint of current salbutamol inhalers (pMDI with HFA‐134a propellant and DPI) and a planned salbutamol pMDI with low‐GWP propellant HFA‐152a was quantified across seven countries.
James King, Ashley Woodcock, Antonio Anzueto, Alexander J. K. Wilkinson, Christer Janson, Richard Henderson, Sourabh Fulmali, Maximilian Plank   +7 more
wiley   +1 more source