Results 91 to 100 of about 27,723 (301)
Advanced Materials, EarlyView.This work reports a direct, biocompatible method to synthesize UiO‐66, enabling one‐step encapsulation of proteins without compromising crystallinity or activity. Using advanced in situ and ex situ techniques, the study reveals that proteins integrate concurrently with MOF growth, forming crystalline protein@UiO‐66 nanoparticles, and provide insight ...
Jesús Cases Díaz +5 more
wiley +1 more source
Multivariate exponential smoothing for forecasting tourist arrivals to Australia and New Zealand [PDF]
In this paper we propose a new set of multivariate stochastic models that capture time varying seasonality within the vector innovations structural time series (VISTS) framework.
Ashton de Silva, George Athanasopoulos
core
Advanced Materials, EarlyView.A new benign solvent (1,3‐diphenylacetone) enables a simple, safe, and sustainable dissolution and gelation method to convert waste PET into low density, monolithic aerogels with high mechanical strength (E = 20 MPa) and remarkably low thermal conductivity (k = 21.9 to 28.9 mW/m·K).
Kira R. Baugh +9 more
wiley +1 more source
A State Space Framework for Automatic Forecasting Using Exponential Smoothing Methods. [PDF]
We provide a new approach to automatic business forecasting based on an extended range of exponential smoothing methods. Each method in our taxonomy of exponential smoothing methods can be shown to be equivalent to the forecasts obtained from a state ...
Grose, S. +3 more
core
Smoothing Hazard Functions and Time-Varying Effects in Discrete Duration and Competing Risks Models [PDF]
, 1995 State space or dynamic approaches to discrete or grouped duration data with competing risks or multiple terminating events allow simultaneous modelling and smooth estimation of hazard functions and time-varying effects in a flexible way. Full Bayesian or
Stefan Wagenpfeil +3 more
core +1 more source
Automatic time series forecasting: the forecast package for R. [PDF]
Automatic forecasts of large numbers of univariate time series are often needed in business and other contexts. We describe two automatic forecasting algorithms that have been implemented in the forecast package for R.
Rob J. Hyndman, Yeasmin Khandakar
core +2 more sources
Advanced Materials, EarlyView.We introduce a computational workflow that combines quantum chemical calculations and machine learning techniques to predict the catalytic performance of a wide range of catalysts in the nitrogen reduction reaction (NRR). The analysis of the trained models provides insights into the complex structure–activity relationship in experimental catalytic ...
Leonardo Di Ciano +5 more
wiley +1 more source
Local Linear Forecasts Using Cubic Smoothing Splines [PDF]
We show how cubic smoothing splines fitted to univariate time series data can be used to obtain local linear forecasts. Our approach is based on a stochastic state space model which allows the use of a likelihood approach for estimating the smoothing ...
Baki Billah +3 more
core
FORECASTING AIR TRAFFIC VOLUMES USING SMOOTHING TECHNIQUES
Havacılık ve Uzay Teknolojileri Dergisi, 2014 For many years, researchers have been using statistical tools to estimate parameters of macroeconomic models. Forecasting plays a major role in logistic planning and it is an essential analytical tool in countries’ air traffic strategies. In recent years,
Emrah Önder, Sultan Kuzu
doaj
Advanced Materials, EarlyView.Oppositely charged single enzyme nanogels (SENs) phase‐separate into bi‐enzymatic coacervate microdroplets, acting as both scaffold and functional units. By tuning SEN ratios, these coacervates create specific microenvironments that enable selective small‐molecule enrichment and efficient intermediate diffusion.
Andoni Rodriguez‐Abetxuko +11 more
wiley +1 more source