Results 141 to 150 of about 184 (180)
Gravitational Radiation from Post-Newtonian Sources and Inspiralling Compact Binaries. [PDF]
Living Rev Relativ, 2002 Blanchet L.
europepmc +1 more source
Orchestrating Green Transformation: How AI Adoption Enables Corporate Carbon Neutrality
Corporate Social Responsibility and Environmental Management, EarlyView.ABSTRACT As carbon neutrality has become a central goal of global climate governance, how firms achieve low‐carbon transformation has emerged as a critical research issue. However, prior studies have primarily focused on macro‐ or industry‐level analyses, offering limited and fragmented insights into how digital technologies—particularly AI—affect firm‐
Xiaonan Dong, Sungjin Son
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ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.A first‐of‐its‐kind review benchmarks three solar methane valorization pathways with unified performance metrics for clean fuel production. Meeting global climate targets and sustainable energy demands requires carbon‐neutral fuels and innovative conversion pathways.
Muhammad Abdulmoez +3 more
wiley +1 more source
One-sided difference schemes and transonic flow. [PDF]
Proc Natl Acad Sci U S A, 1980 Engquist B, Osher S.
europepmc +1 more source
FlexMat, EarlyView.Abstract Soft robots, engineered from highly compliant materials, offer superior adaptability and safety in unstructured environments compared to their rigid counterparts. Recent advancements, fueled by bio‐inspiration and material programmability, have led to the rapid co‐evolution of their core modules: actuation, sensing, protection, energy, and ...
Qiulei Liu +3 more
wiley +1 more source
Term Spread Volatility as a Leading Indicator of Economic Activity
Journal of Forecasting, EarlyView.ABSTRACT In this paper, we examine the macroeconomic predictive power of the volatility of the US Treasury yield curve slope (term spread volatility). Our forecasting exercise shows that US term spread volatility has significant predictive power for US industrial production and employment growth.
Anastasios Megaritis +3 more
wiley +1 more source
Journal of Forecasting, EarlyView.ABSTRACT Most studies on inflation forecasts have studied behavioral biases, informational frictions, or external shocks in isolation, without considering how these factors jointly drive deviations from rational expectations. We therefore adopt an integrated framework that simultaneously estimates the behavioral, informational, and external ...
Belen Chocobar, Peter Claeys
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Using DSGE and Machine Learning to Forecast Public Debt for France
Journal of Forecasting, EarlyView.ABSTRACT Forecasting public debt is essential for effective policymaking and economic stability, yet traditional approaches face challenges due to data scarcity. While machine learning (ML) has demonstrated success in financial forecasting, its application to macroeconomic forecasting remains underexplored, hindered by short historical time series and ...
Emmanouil Sofianos +4 more
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DSGE Model Forecasting: Rational Expectations Versus Adaptive Learning
Journal of Forecasting, EarlyView.ABSTRACT This paper compares within‐sample and out‐of‐sample fit of a DSGE model with rational expectations to a model with adaptive learning. The Galí, Smets, and Wouters model is the chosen laboratory using quarterly real‐time euro area data vintages, covering 2001Q1–2019Q4.
Anders Warne
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