Gaussian Process Prior Models for Electrical Load Forecasting

This paper examines models based on Gaussian Process (GP) priors for electrical load forecasting. This methodology is seen to encompass a number of popular forecasting methods, such as Basic Structural Models (BSMs) and Seasonal Auto-Regressive Intergrated (SARI) as special cases. The GP forecasting models are shown to have some desirable properties and their performance is examined on weekly and yearly Irish load data

Factors Affecting the FcRn-Mediated Transplacental Transfer of Antibodies and Implications for Vaccination in Pregnancy.

At birth, neonates are particularly vulnerable to infection and transplacental transfer of immunoglobulin G (IgG) from mother to fetus provides crucial protection in the first weeks of life. Transcytosis of IgG occurs via binding with the neonatal Fc receptor (FcRn) in the placental synctiotrophoblast. As maternal vaccination becomes an increasingly important strategy for the protection of young infants, improving our understanding of transplacental transfer and the factors that may affect this will become increasingly important, especially in low-income countries where the burden of morbidity and mortality is highest. This review highlights factors of relevance to maternal vaccination that may modulate placental transfer-IgG subclass, glycosylation of antibody, total maternal IgG concentration, maternal disease, infant gestational age, and birthweight-and outlines the conflicting evidence and questions that remain regarding the complexities of these relationships. Furthermore, the intricacies of the Ab-FcRn interaction remain poorly understood and models that may help address future research questions are described

Gaussian Process Prior Models for Electrical Load Forecasting

This paper examines models based on Gaussian Process (GP) priors for electrical load forecasting. This methodology is seen to encompass a number of popular forecasting methods, such as Basic Structural Models (BSMs) and Seasonal Auto-Regressive Intergrated (SARI) as special cases. The GP forecasting models are shown to have some desirable properties and their performance is examined on weekly and yearly Irish load data

Gaussian Process Prior Models for Electrical Load Forecasting

This paper examines models based on Gaussian Process (GP) priors for electrical load forecasting. This methodology is seen to encompass a number of popular forecasting methods, such as Basic Structural Models (BSMs) and Seasonal Auto-Regressive Intergrated (SARI) as special cases. The GP forecasting models are shown to have some desirable properties and their performance is examined on weekly and yearly Irish load data

Gaussian Process Prior Models for Electrical Load Forecasting

This paper examines models based on Gaussian Process (GP) priors for electrical load forecasting. This methodology is seen to encompass a number of popular forecasting methods, such as Basic Structural Models (BSMs) and Seasonal Auto-Regressive Intergrated (SARI) as special cases. The GP forecasting models are shown to have some desirable properties and their performance is examined on weekly and yearly Irish load data