Spectra and eigenspaces of arbitrary lifts of graphs

We describe, in a very explicit way, a method for determining the spectra and bases of all the corresponding eigenspaces of arbitrary lifts of graphs (regular or not)

Corrigendum: Quality of life and quality of education among physiotherapy students in Europe (Frontiers in Medicine, (2024), 11, (1344028), 10.3389/fmed.2024.1344028)

In the published article, an author name was incorrectly written as [Sara Laura Cortés-Amaro]. The correct spelling is [Sara Cortés-Amaro]. The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated

On the spectra and eigenspaces of the universal adjacency matrices of arbitrary lifts of graphs

The universal adjacency matrix U of a graph Γ, with adjacency matrix A, is a linear combination of A, the diagonal matrix D of vertex degrees, the identity matrix I, and the all-1 matrix J with real coefficients, that is, U=c1A+c2D+c3I+c4J, with ci∈ R and c1≠0. Thus, in particular cases, U may be the adjacency matrix, the Laplacian, the signless Laplacian, and the Seidel matrix. In this paper, we develop a method for determining the universal spectra and bases of all the corresponding eigenspaces of arbitrary lifts of graphs (regular or not). As an example, the method is applied to give an efficient algorithm to determine the characteristic polynomial of the Laplacian matrix of the symmetric squares of odd cycles, together with closed formulas for some of their eigenvalues

Characterization of PM10 sampled on the top of a former mining tower by the high-volume wind direction-dependent sampler using INNA

The PM10 concentrations in the studied region (Ostravsko-karvinska agglomeration, Czech Republic) exceed air pollution limit values in the long-term and pose a significant problem for human health, quality of life and the environment. In order to characterize the pollution in the region and identify the pollution origin, Instrumental Neutron Activation Analysis (INAA) was employed for determination of 34 elements in PM10 samples collected at a height of 90 m above ground level. From April 2018 to March 2019, 111 PM10 samples from eight basic wind directions and calm and two smog situations were sampled. The elemental composition significantly varied depending on season and sampling conditions. The contribution of three important industrial sources (iron and steelworks, cement works) was identified, and the long-range cross-border transport representing the pollution from the Polish domestic boilers confirmed the most important pollution inflow during the winter season.Web of Science121art. no. 2