Results 121 to 130 of about 8,492 (262)

A systematic review evaluating the performance of eDNA methods relative to conventional methods for biodiversity monitoring

Ecography, EarlyView.
The rapid adoption of environmental DNA (eDNA) methods has drastically changed biodiversity monitoring efforts. It is often claimed that eDNA methods are more sensitive and efficient than conventional biodiversity monitoring methods, but it is often unclear what metrics support this claim.
Nicholas J. Iacaruso, Olivia P. Reves, Sara J. Merkelz, Cassidy L. Waldrep, Mark A. Davis   +4 more
wiley   +1 more source

Shifting baselines increase the risk of misinterpreting biodiversity trends

Ecography, EarlyView.
Ecological studies quantifying the impact of land‐use change on biodiversity may be sensitive to the choice of reference points – or baselines – particularly when sampling across human land‐use gradients and other space‐for‐time comparisons. Much depends on whether the chosen baseline has already undergone shifts in species composition because of ...
Ariane Dellavalle, Adam J. M. Devenish, Crinan Jarrett, Nathaniel N. D. Annorbah, Augustus Asamoah, Kwame Boafo, Poppy E. Lane, Jake Owen, Alexandra C. Morel, Mark F. Hulme, Andreanna J. Welch, Ken Norris, Fiona J. Sanderson, Joseph A. Tobias   +13 more
wiley   +1 more source

An LMI Based Criterion for Global Asymptotic Stability of Discrete-Time State-Delayed Systems with Saturation Nonlinearities. [PDF]

Int Sch Res Notices, 2014
Kokil P.
europepmc   +1 more source

Nonlinear Response‐History Analyses of Masonry and Mixed Structures With HybriDFEM

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT The hybrid discrete‐finite element (HybriDFEM) method, previously developed to perform static and modal analysis in discrete and coupled discrete‐finite element models, is extended to nonlinear response‐history analyses. The equations of motion for the HybriDFEM model are solved through various numerical time‐integration schemes, both explicit
Igor Bouckaert, Michele Godio, João Pacheco de Almeida   +2 more
wiley   +1 more source

Generalised Kinematic Single‐Impact and Multi‐Impact Models for Rocking Structures

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT The rocking motion is fundamental in earthquake engineering, as it reflects the dynamic behaviour of many structural systems. However, simulating the impacts during rocking motion remains a challenging topic, as they occur in a very short time, generate high impulsive forces, cause sudden changes in velocities and result in rapid energy losses.
Georgios Vlachakis, Carla Colombo, Anastasios I. Giouvanidis, Paulo B. Lourenço   +3 more
wiley   +1 more source

A Multivariate Mixed‐Effects Regression Framework for Ground Motion Modeling: Integrating Parametric and Machine Learning Approaches

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT Multivariate ground motion models (GMMs) that capture the correlation between different intensity measures (IMs) are essential for seismic risk assessment. Conventional GMMs are often developed using a two‐stage approach, where separate univariate models with predefined functional forms are fitted first, and correlation is addressed in a ...
Sayed Mohammad Sajad Hussaini, Shaghayegh Karimzadeh, Paulo B. Lourenço   +2 more
wiley   +1 more source

Coherent Forecasting of Realized Volatility

Journal of Forecasting, EarlyView.
ABSTRACT The QLIKE loss function is the stylized favorite of the literature on volatility forecasting when it comes to out‐of‐sample evaluation and the state of the art model for realized volatility (RV) forecasting is the HAR model, which minimizes the squared error loss for in‐sample estimation of the parameters.
Marius Puke, Karsten Schweikert
wiley   +1 more source

Forecasting Count Data With Varying Dispersion: A Latent‐Variable Approach

Journal of Forecasting, EarlyView.
ABSTRACT Count data, such as product sales and disease case counts, are common in business forecasting and many areas of science. Although the Poisson distribution is the best known model for such data, its use is severely limited by its assumption that the dispersion is a fixed function of the mean, which rarely holds in real‐world scenarios.
Easton Huch, Candace Berrett, Mason Ferlic, Kimberly F. Sellers   +3 more
wiley   +1 more source

Intraday Functional PCA Forecasting of Cryptocurrency Returns

Journal of Forecasting, EarlyView.
ABSTRACT We study the functional PCA (FPCA) forecasting method in application to functions of intraday returns on Bitcoin. We show that improved interval forecasts of future return functions are obtained when the conditional heteroscedasticity of return functions is taken into account.
Joann Jasiak, Cheng Zhong
wiley   +1 more source

The Role of Price‐Volatility Cojumps in Volatility Forecasting

Journal of Futures Markets, EarlyView.
ABSTRACT This paper investigates whether simultaneous jumps in prices and volatility improve volatility forecasting. Using up‐to‐date high‐frequency S&P 500 and VIX data, we identify price‐volatility cojumps at the intraday granularity and construct upside, downside, and asymmetric measures.
Kefu Liao
wiley   +1 more source