To assess the potential environmental impact of human/industrial systems, life cycle assessment (LCA) is a very common method. There are two prominent types LCA, namely attributional (ALCA) and consequential (CLCA). A lot literature covers these approaches, but general consensus on what they represent an overview all their differences seems lacking, nor has every feature been fully explored. Th...

 In this paper, a new homological dimension of modules, copresented dimension, is defined. We study some basic properties of this homological dimension. Some ring extensions are considered, too. For instance, we prove that if $Sgeq R$ is a finite normalizing extension and $S_R$ is a projective module, then for each right $S$-module $M_S$, the copresented dimension of $M_S$ does not exceed the c...

Faces play a central role in person perception. People spontaneously judge others' personality based on their facial appearance and these impressions guide many consequential decisions. When do people rely appearance? In five studies (N = 1936, four preregistered), we test whether reliance depends the goal of impression formation (i.e., which trait dimension targets are evaluated). Trait are, t...

Accurately evaluating the size of a neurovascular lesion is essential for properly devising treatment strategies. The magnification factor must be considered in order to measure the dimension of a lesion from an angiogram. Although a method to calculate the magnification of the lesion by linear interpolation of the measurable magnification factors of two markers has been in use, this paper show...

We consider completely invariant subsets A of weakly expanding piecewise monotonic transformations T on [0, 1]. It is shown that the upper box dimension of A is bounded by the minimum tA of all parameters t for which a t-conformal measure with support A exists. In particular, this implies equality of box dimension and Hausdorff dimension of A.

MOTIVATION The classification of high-dimensional data is always a challenge to statistical machine learning. We propose a novel method named shallow feature selection that assigns each feature a probability of being selected based on the structure of training data itself. Independent of particular classifiers, the high dimension of biodata can be fleetly reduced to an applicable case for conse...