Results 101 to 110 of about 669,313 (269)
Abstract This paper employs the data envelope analysis (DEA) to assess technological progress and its impact on agricultural total factor productivity (TFP) across 18 the Organization for Economic Cooperation and Development (OECD) countries from 1973 to 2015.
Yu Sheng
wiley +1 more source
Abstract The Russian invasion of Ukraine in February 2022 had profound consequences for the global economy. As both countries are major commodity exporters, the food value chain was also affected. This study investigates the impact of the invasion on stock prices, profitability and sentiments of agribusinesses along the food supply chain by using an ...
Julia Höhler+2 more
wiley +1 more source
This paper describes an extended formulation for the coupled beam method (CBM). The method is originally developed for elastic bending response analysis of passenger ships with large multi-deck superstructures. The extension is mainly performed to enable
Fattaneh Morshedsolouk+1 more
doaj +1 more source
We investigate MACE‐MP‐0 and M3GNet, two general‐purpose machine learning potentials, in materials discovery and find that both generally yield reliable predictions. At the same time, both potentials show a bias towards overstabilizing high energy metastable states. We deduce a metric to quantify when these potentials are safe to use.
Konstantin S. Jakob+2 more
wiley +1 more source
On the Krein-Milman-Ky Fan theorem for convex compact metrizable sets
The Krein-Milman theorem (1940) states that every convex compact subset of a Hausdorfflocally convex topological space, is the closed convex hull of its extreme points.
Bachir, Mohammed
core +1 more source
Alpha-Concave Hull, a Generalization of Convex Hull
Bounding hull, such as convex hull, concave hull, alpha shapes etc. has vast applications in different areas especially in computational geometry. Alpha shape and concave hull are generalizations of convex hull. Unlike the convex hull, they construct non-convex enclosure on a set of points.
Asaeedi, Saeed+2 more
openaire +2 more sources
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley +1 more source