Evolution of Complex Features in Digital Organisms

This thesis examines how complex features evolve in digital organisms, and how capabilities that evolved earlier provide a scaffold for evolving new features. I wanted to see how the organisms used previous adaptations to succeed in new environments, and how significant are these previous adaptations. The system used is the Avida platform, which is software that implements Darwinian evolution on self-replicating digital organisms. First, the system is seeded with ancestors that can only replicate, which gave a baseline for the quality of the task at the end of evolution. Second, the system used ancestors from a simpler environment as seeds. I observed that the quality of the task improved, but not drastically except for one of the environments. Lastly, the organism gets transferred form the simplest environment to the most complex one. I observed that only when the transplant included a similar complex adaptation the improvement was remarkable

Virial Expansion of the Nuclear Equation of State

We study the equation of state (EOS) of nuclear matter as function of density. We expand the energy per particle (E/A) of symmetric infinite nuclear matter in powers of the density to take into account 2,3,. . .,N-body forces. New EOS are proposed by fitting ground state properties of nuclear matter (binding energy, compressibility and pressure) and assuming that at high densities a second order phase transition to the Quark Gluon Plasma (QGP) occurs. The latter phase transition is due to symmetry breaking at high density from nuclear matter (locally color white) to the QGP (globally color white). In the simplest implementation of a second order phase transition we calculate the critical exponent ? by using Landau's theory of phase transition. We find ? = 3. Refining the properties of the EOS near the critical point gives ? = 5 in agreement with experimental results. We also discuss some scenarios for the EOS at finite temperatures

MarineTools.temporal: A Python package to simulate Earth and environmental time series

The assessment of the uncertainty about the evolution of complex processes usually requires different realizations consisting of multivariate temporal signals of environmental data. However, it is common to have only one observational set. MarineTools.temporal is an open-source Python package for the non-stationary parametric statistical analysis of vector random processes suitable for environmental and Earth modelling. It takes a single timeseries of observations and allows the simulation of many time series with the same probabilistic behavior. The software generalizes the use of piecewise and compound distributions with any number of arbitrary continuous distributions. The code contains, among others, multi-model negative log-likely functions, wrappednormal distributions, and generalized Fourier timeseries expansion. Its programming philosophy significantly improves the computing time and makes it compatible with future extensions of scipy.stats. We apply it to the analysis of freshwater river discharge, water currents, and the simulation of ensemble projections of sea waves, to show its capabilities

Structure of 10N in 9C+p resonance scattering

The structure of exotic nucleus 10N was studied using 9C+p resonance scattering. Two L=0 resonances were found to be the lowest states in 10N. The ground state of 10N is unbound with respect to proton decay by 2.2(2) or 1.9(2) MeV depending on the 2- or 1- spin-parity assignment, and the first excited state is unbound by 2.8(2) MeV.Comment: 6 pages, 4 figures, 1 table, submitted to Phys. Lett.

STUDY OF THE O-18+Ni-64 TWO-NEUTRON TRANSFER REACTION AT 84 MeV BY MAGNEX

A study of the two-neutron transfer reaction of the O-18 + Ni-64 system at 84 MeV incident energy to the ground and first 2(+) excited state of the residual Ni-66 nucleus is presented. The experiment was performed at the INFN-LNS (Italy) by using the large acceptance MAGNEX spectrometer. Theoretical models are used in order to disentangle the competition between long-range and short-range correlations

Long-range versus short-range correlations in the two-neutron transfer reaction Ni 64 (O 18, O 16) Ni 66

Recently, various two-neutron transfer studies using the (18O,16O) reaction were performed with a large success. This was achieved because of a combined use of the microscopic quantum description of the reaction mechanism and of the nuclear structure. In the present work we use this methodology to study the two-neutron transfer reaction of the 18O+64Ni system at 84 MeV incident energy, to the ground and first 2+ excited state of the residual 66Ni nucleus. All the experimental data were measured by the large acceptance MAGNEX spectrometer at the Instituto Nazionale di Fisica Nucleare \u2013Laboratori Nazionali del Sud (Italy). We have performed exact finite range cross section calculations using the coupled channel Born approximation (CCBA) and coupled reaction channel (CRC) method for the sequential and direct two-neutron transfers, respectively. Moreover, this is the first time that the formalism of the microscopic interaction boson model (IBM-2) was applied to a two-neutron transfer reaction. From our results we conclude that for two-neutron transfer to the ground state of 66Ni, the direct transfer is the dominant reaction mechanism, whereas for the transfer to the first excited state of 66Ni, the sequential process dominates. A competition between long-range and short-range correlations is discussed, in particular, how the use of two different models (Shell model and IBM's) help to disentangle long- and short-range correlations

A Cross-Cultural Comparison Study: The Effectiveness of Schema Training Modules Among Hispanic Students

Previous studies indicated that misconceptions related to heat transfer, fluid mechanics, and thermodynamics, persist among engineering juniors and seniors even after they completed college-level courses in these subjects. Researchers have proposed an innovative instructional approach, the ontological schema training method, which helps students develop appropriate schemas or conceptual frameworks for learning difficult science concepts. Three online training modules were designed to help engineering students develop appropriate schemas in heat transfer, diffusion and microfluidics. The effectiveness of these modules was examined with two different student populations from two different universities (US and Hispanic). At each institution, participants were assigned randomly to a control or experimental group. The treatment for each group at both institutions was exactly the same. Preliminary results indicated a mixed effectiveness of the training modules among these populations