Stress and Sleep Quality: Mediating Effects of Social Support

Stress is defined as the “nonspecific response of the body to any demand made upon it” (Kohn & Frazer, 1986). Stress is among the top five threats to academic performance among college students (Pettit & DeBarr, 2011). The purpose of the study was to investigate whether stress affects perceived sleep quality, as mediated by social support, and to determine whether stress levels vary based on academic major. Using ANOVA in SPSS 24, we tested three hypotheses: stress and sleep quality are negatively correlated, social support mediates the relationship between stress and sleep quality, and stress levels will vary by academic major (specifically that science, technology, engineering, and mathematics majors will show greater perceived amounts of stress). Results of this study show that there is positive correlation between sleep and stress, a negative correlation between social support and sleep, and a negative correlation between stress and social support

Nonequilibrium phase transition in a model for social influence

We present extensive numerical simulations of the Axelrod's model for social influence, aimed at understanding the formation of cultural domains. This is a nonequilibrium model with short range interactions and a remarkably rich dynamical behavior. We study the phase diagram of the model and uncover a nonequilibrium phase transition separating an ordered (culturally polarized) phase from a disordered (culturally fragmented) one. The nature of the phase transition can be continuous or discontinuous depending on the model parameters. At the transition, the size of cultural regions is power-law distributed.Comment: 5 pages, 4 figure

Power Law of Customers' Expenditures in Convenience Stores

In a convenience store chain, a tail of the cumulative density function of the expenditure of a person during a single shopping trip follows a power law with an exponent of -2.5. The exponent is independent of the location of the store, the shopper's age, the day of week, and the time of day.Comment: 9 pages, 5 figures. Accepted for publication in Journal of the Physical Society of Japan Vol.77No.

How to Choose a Champion

League competition is investigated using random processes and scaling techniques. In our model, a weak team can upset a strong team with a fixed probability. Teams play an equal number of head-to-head matches and the team with the largest number of wins is declared to be the champion. The total number of games needed for the best team to win the championship with high certainty, T, grows as the cube of the number of teams, N, i.e., T ~ N^3. This number can be substantially reduced using preliminary rounds where teams play a small number of games and subsequently, only the top teams advance to the next round. When there are k rounds, the total number of games needed for the best team to emerge as champion, T_k, scales as follows, T_k ~N^(\gamma_k) with gamma_k=1/[1-(2/3)^(k+1)]. For example, gamma_k=9/5,27/19,81/65 for k=1,2,3. These results suggest an algorithm for how to infer the best team using a schedule that is linear in N. We conclude that league format is an ineffective method of determining the best team, and that sequential elimination from the bottom up is fair and efficient.Comment: 6 pages, 3 figure

The Strategic Exploitation of Limited Information and Opportunity in Networked Markets

This paper studies the effect of constraining interactions within a market. A model is analysed in which boundedly rational agents trade with and gather information from their neighbours within a trade network. It is demonstrated that a trader’s ability to profit and to identify the equilibrium price is positively correlated with its degree of connectivity within the market. Where traders differ in their number of potential trading partners, well-connected traders are found to benefit from aggressive trading behaviour.Where information propagation is constrained by the topology of the trade network, connectedness affects the nature of the strategies employed

Effect of Hund coupling in the one-dimensional SU(4) Hubbard model

The one-dimensional SU(4) Hubbard model perturbed by Hund coupling is studied, away from half-filling, by means of renormalization group and bosonization methods. A spectral gap is always present in the spin-orbital sector irrespective of the magnitude of the Coulomb repulsion. We further distinguish between two qualitatively different regimes. At small Hund coupling, we find that the symmetry of the system is dynamically enlarged to SU(4) at low energy with the result of {\it coherent} spin-orbital excitations. When the charge sector is not gapped, a superconducting instability is shown to exist. At large Hund coupling, the symmetry is no longer enlarged to SU(4) and the excitations in the spin sector become {\it incoherent}. Furthermore, the superconductivity can be suppressed in favor of the conventional charge density wave state.Comment: 10 pages, 1 figur

Spinons in a Crossed-Chains Model of a 2D Spin Liquid

Using Random Phase Approximation, we show that a crossed-chains model of a spin-1/2 Heisenberg spins, with frustrated interchain couplings, has a non-dimerized spin-liquid ground state in 2D, with deconfined spinons as the elementary excitations. The results are confirmed by a bosonization study, which shows that the system is an example of a `sliding Luttinger liquid'. In an external field, the system develops an incommensurate field-induced long range order with a finite transition temperature.Comment: 4 pages, 3 figures; added references; scaling analysis, preserving spin rotational invariance, is extended to finite temperatur

Fractal Profit Landscape of the Stock Market

We investigate the structure of the profit landscape obtained from the most basic, fluctuation based, trading strategy applied for the daily stock price data. The strategy is parameterized by only two variables, p and q. Stocks are sold and bought if the log return is bigger than p and less than -q, respectively. Repetition of this simple strategy for a long time gives the profit defined in the underlying two-dimensional parameter space of p and q. It is revealed that the local maxima in the profit landscape are spread in the form of a fractal structure. The fractal structure implies that successful strategies are not localized to any region of the profit landscape and are neither spaced evenly throughout the profit landscape, which makes the optimization notoriously hard and hypersensitive for partial or limited information. The concrete implication of this property is demonstrated by showing that optimization of one stock for future values or other stocks renders worse profit than a strategy that ignores fluctuations, i.e., a long-term buy-and-hold strategy.Comment: 12 pages, 4 figure