We study the nature of the phase transition in the fully frustrated simple cubic lattice with the $XY$ spin model. This system is the Villain’s model generalized in three dimensions. The ground state is very particular with a 12-fold degeneracy. Previous studies have shown unusual critical properties. With the powerful Wang-Landau flat-histogram Monte Carlo method, we carry out in this work intensive simulations with very large lattice sizes. We show that the phase transition is clearly of first order, putting an end to the uncertainty which has lasted for more than 20 years.

Most subterranean termites forage for food by creating tunnel galleries underground. These tunnel networks reflect a compromise between foraging efficiency and other environmental constraints, such as soil hardness and moisture content. Thus, understanding tunnel networks is important for understanding foraging behavior. Due to the difficulties in direct observation of tunneling patterns in the field, we used a theoretical approach for this analysis. We first constructed a lattice model to simulate the tunnel networks of Coptotermes formosanus Shiraki and Reticulitermes flavipes (Kollar) on the basis of the experimental data provided by Su et al. (Su, N.-Y., Stith, B.M., Puche, H., Bardunias, P., 2004. Characterization of tunneling geometry of subterranean termites (Isoptera: Rhinotermitidae) by computer simulation. Sociobiology 44 (3), 471–483.). Using this model and two of its modified versions, we explored the relationship between the food encounter rate and food distributions and analyzed how this relationship is influenced by changes in the tunnel characteristic constituents, such as the branching tunnel length and frequency. Additionally, we investigated the effects of landscape heterogeneity on the foraging efficiency. In the discussion, we briefly introduced our novel individual-based model comprising individual termites and their surroundings, and we addressed the necessity of this model in the functioning of the network and the formation of the network in relation to foraging behavior.

We developed a new approach to shape recognition that uses the outline of an object and is based on a novel ???ranch length similarity??(BLS) entropy. ?BLS entropy was defined on a simple branching network consisting of a single node and branches.? The simple pattern was referred to as a ??븂it branching network??(UBN).? The approach involves obtaining BLS entropy profiles from UBNs that are created by joining each pixel in the outline of a shape with every other pixel in the shape???border.? To test whether they can be used effectively to recognize an object???shape, we obtained BLS entropy profiles from the shapes of twenty battle tanks depicted with 460??50 pixel resolution, and identical shapes depicted at lower resolution.? The d-shapes were generated by decreasing the resolution of the original shapes to 60% in 10% increments.? Each BLS entropy profile calculated from the original shape set was compared with all BLS entropy profiles obtained from the d-shapes using correlation coefficients.? The BLS entropy profile for a given shape was more similar to identical shapes depicted at different resolutions than to different shapes.? Therefore, this process was able to successfully discriminate between the shapes tested regardless of resolution, and the proposed approach can be a useful tool for recognizing an object???shape.

Response behaviors of indicator species have been used for monitoring environmental disturbances. Markov processes were applied to elucidation of behavioral changes of animals. Movement of Daphnia magna in two dimensions was continuously observed before and after the treatments of an insecticide, diazinon, at low concentration. The Self-Organizing Map (SOM) was initially used to train complex ment data to classify different ment states. Subsequently, a hidden Markov model (HMM) was applied to sequencing the ment states identified by the SOM. Transition probability matrix (TPM) and emission probability matrix (EPM) were efficiently estimated by HMM. Markov processes were separately observed before and after the treatments, and the changes in the response behaviors of indicator organisms were demonstrated in stressful conditions

Subterranean termites construct complicated tunnel networks for foraging below ground. Thus, they often encounter tunnel intersections during foraging activity. Directional selection by termites at intersections is likely to affect foraging efficiency because depending on their selection, the path length from food resources to the nest can vary significantly. In order to understand how termites are guided to choose the most economical path without the use of pheromones, we artificially excavated two tunnels of varying widths (W₁ and W₂; 2, 3, or 4 mm) that intersected at a 90° angle in each of nine soil­filled arenas. We observed the directional selection of termites at intersections in arenas with combinations of W₁ (mm) and W₂ (mm) (W₁, W₂). For (W₁, W₂) = (2, 2) and (4, 4), termites statistically equally chose the three directions left, right, and straight, while for the (3, 3) arena combination, termites preferentially decided to go straight. On the other hand, for (W₁, W₂) = (2, 3) (2, 4), and (3, 4), termites advancing from narrower tunnels into intersections tended to turn right or left, while termites coming from the wider tunnel were more inclined to go straight. On the assumption that a wider tunnel is more frequently used by termites in the field, we can deduce that the wider tunnel may represent the most efficient/shortest path. Thus, this simple selection mechanism can prevent termites from deviating from the most economical path.

Previous studies have explored the relationship between termite branch tunnel geometry and foraging efficiency in a model simulation in which foraging efficiency, γ, for two termite species, Coptotermes formosanus Shiraki and Reticulitermes flavipes (Kollar) (Isoptera: Rhinotermitidae), was investigated in response to two variables, the probability of tunnel branching (P_branch) and the probability of tunnel branch termination (P_term). It was found that simulated tunnel patterns based on empirical data did not have maximum foraging efficiency. We hypothesized that termites could increase their foraging efficiency in response to landscape heterogeneity. The present study investigated how termites could control the two variables, P_branch and P_term, in response to the external environment in terms of tunnel network connectivity. It was found that the best simulated strategy for C. formosanus and R. flavipes termites would occur if both P_branch and P_term were increased together. This study provides possible mechanisms for foraging strategies in subterranean termites and a baseline for future empirical work.

Zero plane displacement (d) is the elevated height of the apparent momentum sink exerted by the vegetation on the air. For a vegetative canopy, d depends on the roughness structure of a plant canopy such as leaf area index, canopy height and canopy density, and thus is critical for the analysis of canopy turbulence and the calculation of surface scalar fluxes. In this research note, we estimated d at the Gwangneung coniferous forest by employing two independent methods of Rotach (1994) and Martano (2000), which require only a single-level eddy-covariance measurement. In general, these two methods provided comparable estimates of $d/h_c$ (where $h_c$ is the canopy height, i.e., ~23m), which ranged from 0.51 to 0.97 depending on wind directions. These estimates of $d/h_c$ were within the ranges (i.e., 0.64~0.94) reported from other forests in the literature but were sensitive to the forms of the nondimensional functions for atmospheric stability. Our finding indicates that one should be careful in interepreation of zero plane displacement estimated from a single-level eddy covariance measurement that is conductaed within the roughness sublayer.

We conducted a sensitivity test of Joint UK Land Environment Simulator (JULES), in which the influence of biophysical parameters on the simulation of gross primary productivity (GPP) and ecosystem respiration (RE) was investigated for two typical ecosystems in Korea. For this test, we employed the whole-year observation of eddy-covariance fluxes measured in 2006 at two KoFlux sites: (1) a deciduous forest in complex terrain in Gwangneung and (2) a farmland with heterogeneous mosaic patches in Haenam. Our analysis showed that the simulated GPP was most sensitive to the maximum rate of RuBP carboxylation and leaf nitrogen concentration for both ecosystems. RE was sensitive to wood biomass parameter for the deciduous forest in Gwangneung. For the mixed farmland in Haenam, however, RE was most sensitive to the maximum rate of RuBP carboxylation and leaf nitrogen concentration like the simulated GPP. For both sites, the JULES model overestimated both GPP and RE when the default values of input parameters were adopted. Considering the fact that the leaf nitrogen concentration observed at the deciduous forest site was only about 60% of its default value, the significant portion of the model's overestimation can be attributed to such a discrepancy in the input parameters. Our finding demonstrates that the abovementioned key biophysical parameters of the two ecosystems should be evaluated carefully prior to any simulation and interpretation of ecosystem carbon exchange in Korea.