Results 181 to 190 of about 15,607 (298)

Understanding Engagement in Collaborative Governance Networks Through Motivation, Learning, and Values

open access: yesEnvironmental Policy and Governance, EarlyView.
ABSTRACT Collaborative governance networks are increasingly central to local climate action, yet research offers limited understanding of the personal, psychological, and informal factors that sustain engagement within them. This paper examines how such networks facilitate meaningful and lasting participation through an in‐depth study of Malmö Works, a
Gustav Osberg
wiley   +1 more source

Psychopharmacology of Catatonia: A Tour D'horizon. [PDF]

open access: yesPsychopharmacol Bull
Naguy A, Pridmore S, Ozidu V, Alamiri B.
europepmc   +1 more source

Governing Positive Energy Districts: The Role of Legitimation and Identity Across Residential and Industrial Contexts

open access: yesEnvironmental Policy and Governance, EarlyView.
ABSTRACT Increasing electricity demand from data centres, industrial applications, electric vehicles and domestic heating is creating pressure to develop electricity systems in many parts of the world, but especially in Western countries. In response to challenges such as grid congestion, interconnection queues and climate‐related hazards, network ...
Jussi Valta   +3 more
wiley   +1 more source

A Deep Learning Framework for Forecasting Medium‐Term Covariance in Multiasset Portfolios

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT Forecasting the covariance matrix of asset returns is central to portfolio construction, risk management, and asset pricing. However, most existing models struggle at medium‐term horizons, several weeks to months, where shifting market regimes and slower dynamics prevail.
Pedro Reis, Ana Paula Serra, João Gama
wiley   +1 more source

Forecasting With Dynamic Factor Models Estimated by Partial Least Squares

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT Dynamic factor models (DFMs) have found great success in nowcasting and short‐term macroeconomic forecasting when incorporating large sets of predictive information. The factor loadings are typically estimated cross‐sectionally with principal component analysis (PCA) or maximum likelihood (ML), which ignore whether the factors have predictive ...
Samuel Rauhala
wiley   +1 more source

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