Computing the Affective-Aesthetic Potential of Literary Texts

In this paper, we compute the affective-aesthetic potential (AAP) of literary texts by using a simple sentiment analysis tool called SentiArt. In contrast to other established tools, SentiArt is based on publicly available vector space models (VSMs) and requires no emotional dictionary, thus making it applicable in any language for which VSMs have been made available (>150 so far) and avoiding issues of low coverage. In a first study, the AAP values of all words of a widely used lexical databank for German were computed and the VSM’s ability in representing concrete and more abstract semantic concepts was demonstrated. In a second study, SentiArt was used to predict ~2800 human word valence ratings and shown to have a high predictive accuracy (R2 > 0.5, p < 0.0001). A third study tested the validity of SentiArt in predicting emotional states over (narrative) time using human liking ratings from reading a story. Again, the predictive accuracy was highly significant: R2adj = 0.46, p < 0.0001, establishing the SentiArt tool as a promising candidate for lexical sentiment analyses at both the micro- and macrolevels, i.e., short and long literary materials. Possibilities and limitations of lexical VSM-based sentiment analyses of diverse complex literary texts are discussed in the light of these results

Formation of Subgap States in Carbon Nanotubes Due to a Local Transverse Electric Field

We introduce two simple models to study the effect of a spatially localized transverse electric field on the low-energy electronic structure of semiconducting carbon nanotubes. Starting from the Dirac Hamiltonian for the low energy states of a carbon nanotube, we use scattering theory to show that an arbitrarily weak field leads to the formation of localized electronic states inside the free nanotube band gap. We study the binding energy of these subgap states as a function of the range and strength of the electrostatic potential. When the range of the potential is held constant and the strength is varied, the binding energy shows crossover behavior: the states lie close to the free nanotube band edge until the potential exceeds a threshold value, after which the binding energy increases rapidly. When the potential strength is held constant and the range is varied, we find resonant behavior: the binding energy passes through a maximum as the range of the potential is increased. Large electric fields confined to a small region of the nanotube are required to create localized states far from the band edge.Comment: 15 pages + 5 figures, 1 table in RevTe

Nonradiative Recombination of Excitons in Carbon Nanotubes Mediated by Free Charge Carriers

Free electrons or holes can mediate the nonradiative recombination of excitons in carbon nanotubes. Kinematic constraints arising from the quasi one-dimensional nature of excitons and charge carriers lead to a thermal activation barrier for the process. However, a model calculation suggests that the rate for recombination mediated by a free electron is the same order of magnitude as that of two-exciton recombination. Small amounts of doping may contribute to the short exciton lifetimes and low quantum yields observed in carbon nanotubes.Comment: 18 pages, 4 figures. Submitted to Physical Review

Completion Rates in West Virginia Community and Technical Colleges

This research examined withdrawal and completion rates in courses at public community colleges in West Virginia during the Fall 2009 and Fall 2010 semesters. Online distance education has quickly gained popularity over the previous ten years, and the number of students enrolling in online education has increased at a higher rate than overall enrollment in higher education. Few studies have analyzed withdrawal and completion rates specifically in online courses. Why is student attrition so high? How does this vary from traditional face-toface courses? What can institutions do to prevent online students from withdrawing and not completing courses? This study performed a comparative analysis based on existing data for which the West Virginia Community and Technical College System (WVCTCS) institutions provide information for reporting each semester. Data that can identify the student was removed, and the remaining data compared to determine the types of courses that have the highest withdrawal and failure rates. A total of 148,939 records were analyzed from all students enrolled in community and technical college courses across the State of West Virginia during the Fall 2009 and Fall 2010 semesters. Traditional courses consisted of 86.1% of the courses, 2.0% were hybrid, and 11.9% were online. This study only looks at how many students are withdrawing and not passing online courses at West Virginia Community and Technical Colleges, it does not look into why these students withdraw at a higher rate than traditional courses. Further research is needed on the reasons why they withdraw and what can be done to prevent their departure

Further developments in correlator product states: deterministic optimization and energy evaluation

Correlator product states (CPS) are a class of tensor network wavefunctions applicable to strongly correlated problems in arbitrary dimensions. Here, we present a method for optimizing and evaluating the energy of the CPS wavefunction that is non-variational but entirely deterministic. The fundamental assumption underlying our technique is that the CPS wavefunction is an exact eigenstate of the Hamiltonian, allowing the energy to be obtained approximately through a projection of the Schr\"odinger equation. The validity of this approximation is tested on two dimensional lattices for the spin-1/2 antiferromagnetic Heisenberg model, the spinless Hubbard model, and the full Hubbard model. In each of these models, the projected method reproduces the variational CPS energy to within 1%. For fermionic systems, we also demonstrate the incorporation of a Slater determinant reference into the ansatz, which allows CPS to act as a generalization of the Jastrow-Slater wavefunction.Comment: 8 pages, 2 tables, 3 figure

Perfect Reflection of Chiral Fermions in Gated Graphene Nanoribbons

We describe the results of a theoretical study of transport through gated metallic graphene nanoribbons using a non-equilibrium Green function method. Although analogies with quantum field theory predict perfect transmission of chiral fermions through gated regions in one dimension, we find \emph{perfect reflection} of chiral fermions in armchair ribbons for specific configurations of the gate. This effect should be measurable in narrow graphene constrictions gated by a charged carbon nanotube.Comment: 9 pages, 3 figures. Submitted to Nano Letter

Approximating strongly correlated spin and fermion wavefunctions with correlator product states

We explore correlator product states for the approximation of correlated wavefunctions in arbitrary dimensions. We show that they encompass many interesting states including Laughlin's quantum Hall wavefunction, Huse and Elser's frustrated spin states, and Kitaev's toric code. We further establish their relation to common families of variational wavefunctions, such as matrix and tensor product states and resonating valence bond states. Calculations on the Heisenberg and spinless Hubbard models show that correlator product states capture both two-dimensional correlations (independent of system width) as well as non-trivial fermionic correlations (without sign problems). In one-dimensional simulations, correlator product states appear competitive with matrix product states with a comparable number of variational parameters, suggesting they may eventually provide a route to practically generalise the density matrix renormalisation group to higher dimensions.Comment: Table 1 expanded, Table 2 updated, optimization method discussed, discussions expanded in some sections, earlier work on similar wavefunctions included in text and references, see also (arXiv:0905.3898). 5 pages, 1 figure, 2 tables, submitted to Phys. Rev.

Improving primary care through information. A Wonca keynote paper.

Information from health care encounters across the entire health care spectrum, when consistently collected, analysed and applied can provide a clearer picture of patients' history as well as current and future needs through a better understanding of their morbidity burden and health care experiences. It can facilitate clinical activity to target limited resources to those patients most in need through risk adjustment mechanisms that consider the morbidity burden of populations, and it can help target quality improvement and cost saving activities in the right places. It can also open the door to a new chapter of evidence-based medicine around multi-morbidity. In summary, it can support a better integrated health system where primary care can provide continuous, coordinated, and comprehensive person-centred care to those who could benefit most. This paper explores the potential uses of information collected in electronic health records (EHRs) to inform case-mix and predictive modelling, as well as the associated challenges, with a particular focus on their application to primary care