This finding, coupled with our more detailed characterization of CARKL, supports a robust interdependency of metabolism and immune cell function while at the same time highlighting our overall lack of detailed knowledge on the subject.
Although Condorcet's conclusion is robust to the presence of some interdependencies between individual votes, the structure of these interdependencies matters (e.g., Boland 1989; Ladha 1992; Estlund 1994; Dietrich and List 2004; Berend and Sapir 2007; Dietrich and Spiekermann 2013).
These results are then used to show that, in environments with single-crossing preferences and well-behaved intertemporal effects, strict ex-post incentive compatibility and a condition which limits the strength of preference interdependencies are sufficient to guarantee robust full implementation.
A robust optimization model was proposed for analyzing the interdependencies between gas and electric infrastructures, which led to an uncertainty-immunized, but conservative solution [15, 16].
Robust standard errors were used to account for interdependency of outcome between twins.
For all regression analyses, robust standard errors were employed to account for interdependency between colonic segments and scan position (supine/prone) in the same patient.
If the world is more interdependent, how do we create healthy interdependencies so we rise together, rather than unhealthy interdependencies so we fall together?
Using the resistance spot welding process as an example, this paper presents a new robust design and analysis framework for products and processes with parameter interdependency.
This paper addresses the problem of determining robust signal controls in a traffic network which (a) consider the interdependency of signal controls and traffic flow patterns and (b) account for the variability or uncertainty in the origin destination demands.
"We try to provide robust answers to questions of materials and technology choice by modeling and understanding the interdependencies within a market, including resource and energy use in supply chains," says Olivetti.
This study focuses on the development of a next generation multiobjective evolutionary algorithm (MOEA) that can learn and exploit complex interdependencies and/or correlations between decision variables in monitoring design applications to provide more robust performance for large problems (defined in terms of both the number of objectives and decision variables).
