Introduction to Coding Theory for Flow Equations of Complex Systems Models

The modeling of complex dynamic systems depends on the solution of a differential equations system. Some problems appear because we do not know the mathematical expressions of the said equations. Enough numerical data of the system variables are known. The authors, think that it is very important to establish a code between the different languages to let them codify and decodify information. Coding permits us to reduce the study of some objects to others. Mathematical expressions are used to model certain variables of the system are complex, so it is convenient to define an alphabet code determining the correspondence between these equations and words in the alphabet. In this paper the authors begin with the introduction to the coding and decoding of complex structural systems modeling.

Local probe of fractional edge states of S=1 Heisenberg spin chains

Spin chains are among the simplest physical systems in which electron-electron interactions induce novel states of matter. Here we propose to combine atomic scale engineering and spectroscopic capabilities of state of the art scanning tunnel microscopy to probe the fractionalized edge states of individual atomic scale S=1 spin chains. These edge states arise from the topological order of the ground state in the Haldane phase. We also show that the Haldane gap and the spin-spin correlation length can be measured with the same technique.

Motivational profiles Spanish students of Compulsory Secondary Education: Differential analysis of academic self-attributions

Academic goals and academic self-attributions are relevant variables in school settings. The objective of this study is to identify whether there are combinations of multiple goals that lead to different motivational profiles and to determine whether there are significant differences between the groups obtained regarding causal attributions of success and failure (ability, effort, or external causes) in Mathematics and Language and Literature, and in overall academic performance. The Goal Achievement Tendencies Questionnaire (AGTQ) and the Sydney Attribution Scale (SAS) were administered to a sample of 2022 students of compulsory secondary education, ranging in age from 12 to 16 years (M = 13.81, SD = 1.35). Cluster analysis identified four motivational profiles: a group of students with a high generalized motivation profile, a group of students with low generalized motivation profile, a group of students with predominance of learning goals and achievement goals, and a final group of students with predominance of social reinforcement goals. Results revealed statistically significant differences between the profiles obtained in academic self-attributions.