Molecular descriptors - a mathematical approach to characterize psychedelic substances

High-Dimensional Feature Descriptors to Characterize Volumetric Data

Volumetric data offer considerably more low-level information than the density and gradient values traditionally employed in transfer function-guided volume visualization. We propose the use of a richer set of low-level feature descriptors to allow a more sensitive and refined characterization of the data. The ensemble of these feature descriptors then forms a distinct data signature that can d...

Computational Approach To Characterize

Mathematical models to characterize early epidemic growth: A review.

There is a long tradition of using mathematical models to generate insights into the transmission dynamics of infectious diseases and assess the potential impact of different intervention strategies. The increasing use of mathematical models for epidemic forecasting has highlighted the importance of designing reliable models that capture the baseline transmission characteristics of specific pat...

Structure-activity relationships of taxoids: a molecular descriptors family approach

Introduction: Taxoids, groups of diterpenoid cyclodecanes isolated from the genus Taxus, are known and used as anticancer agents. Starting from the successful results obtained by an original molecular descriptors family on structure-activity relationships (Jäntschi and Bolboacă, 2007), the aim of the research was to investigate and to assess the estimation and prediction abilities of this appro...

A New Approach to Characterize Qubit Channels

We analyze qubit channels by exploiting the possibility of representing two-level quantum systems in terms of characteristic functions. To do so, we use functions of non-commuting variables (Grassmann variables), defined in terms of generalized displacement operators, following an approach which resemble the one adopted for continuous–variable (Bosonic) systems. It allows us to introduce the no...