Series Study of a Spin-Glass Model in Continuous Dimensionality

A high-temperature series expansion for the Edwards and Anderson spin-glass order-parameter susceptibility is computed for Ising spins on hypercubic lattices with nearest-neighbor interactions. The series is analyzed by Padé approximants with Rudnick-Nelson-type corrections to scaling. The results agree with the first-order ε expansion of Harris, Lubensky, and Chen. The critical exponent γQ increases monotonically with decreasing dimension, d, for d\u3c6, and apparently tends to infinity at d=4; however, the critical temperature does not appear to go to zero at d=4

Critical Behavior of Random Resistor Networks Near the Percolation Threshold

We use low-density series expansions to calculate critical exponents for the behavior of random resistor networks near the percolation threshold as a function of the spatial dimension d. By using scaling relations, we obtain values of the conductivity exponent μ. For d=2 we find μ=1.43±0.02, and for d=3, μ=1.95±0.03, in excellent agreement with the experimental result of Abeles et al. Our results for high dimensionality agree well with the results of ε-expansion calculations

Long Range Order in Random Anisotropy Magnets

High temperature series for the magnetic susceptibility, χ, of random anisotropy axis models in the limit of infinite anisotropy are presented, for two choices of the number of spin components, m. For m=2, we find T c =1.78 J on the simple cubic lattice, and on the face‐centered cubic lattice we find T c =4.29 J. There is no divergence of χ at finite temperature for m=3 on either lattice. For the four‐dimensional hypercubic lattice, we find finite temperature divergences of χ for both m=2 and m=3

High-Temperature Series for Random-Anisotropy Magnets

High-temperature series expansions for thermodynamic functions of random-anisotropy-axis models in the limit of infinite anisotropy are presented, for several choices of the number of spin components, m. In three spatial dimensions there is a divergence of the magnetic susceptibility χM for m=2. We find Tc/J=1.78±0.01 on the simple cubic lattice, and on the face-centered cubic lattice, we find Tc/J=4.29±0.01. There is no divergence of χM at finite temperature for m≥3 on either lattice. We also give results for simple hypercubic lattices

Critical Behavior of Random Resistor Networks

We present numerical data and scaling theories for the critical behavior of random resistor networks near the percolation threshold. We determine the critical exponents of a suitably defined resistance correlation function by a Padé analysis of low-concentration expansions as a function of dimensionality. We verify that d=6 is the critical dimensionality for the onset of mean-field behavior. We use the coherent-potential approximation to construct a mean-field scaling function for the critical region

Comparing Online with Brick and Mortar Course Learning Outcomes: An Analysis of Quantitative Methods Curriculum in Public Administration

Teaching graduate students in an intensive adult-learning format presents a special challenge for quantitative analytical competencies. Students often lack necessary background, skills and motivation to deal with quantitative-skill-based course work. This study compares learning outcomes for graduate students enrolled in three course sections (cohorts) taking a quantitative methods course in a public administration program. One cohort of students was taught online, while two student cohorts were taught face-to-face in a traditional classroom setting. Most of the online students resided in the same geographic location as the “brick-and-mortar’ students. While student backgrounds and demographics were comparable, there were notable differences in their levels of self-directed learning readiness and persistence. These differences illustrate both course design and modality features for a comparison between online and traditional brick-and-mortar learning environments. We find that predictors of student performance in an online environment are rather well described by the Self-Directed Learning Theory (SDL) and Self-Regulated Learning Theory (SRL). A statistically significant difference was found in the pretest-posttest mean scores, which indicates that students learned the course content for quantitative methods in the online section differently from those in the brick-and-mortar section. Overall, students enrolled in the online section (cohort) performed better on the posttest than did students enrolled in traditional “brick-and-mortar” classes. An age variable shows that older students performed much better than younger students on the posttest. Other differences in learning outcomes between the online and brick-and-mortar sections are analyzed in the study. Stakeholders in online education should be interested in these outcomes

Automatic Detection of Seizures with Applications

There are an estimated two million people with epilepsy in the United States. Many of these people do not respond to anti-epileptic drug therapy. Two devices can be developed to assist in the treatment of epilepsy. The first is a microcomputer-based system designed to process massive amounts of electroencephalogram (EEG) data collected during long-term monitoring of patients for the purpose of diagnosing seizures, assessing the effectiveness of medical therapy, or selecting patients for epilepsy surgery. Such a device would select and display important EEG events. Currently many such events are missed. A second device could be implanted and would detect seizures and initiate therapy. Both of these devices require a reliable seizure detection algorithm. A new algorithm is described. It is believed to represent an improvement over existing seizure detection algorithms because better signal features were selected and better standardization methods were used

Integrating Resource Defence Theory with a Neural Nonapeptide Pathway to Explain Territory-Based Mating Systems

1 Texas Research Institute for Environmental Studies, Sam Houston State University, Huntsville, TX 77341 USA; Department of Biology, Case Western Reserve University, Cleveland, OH 44106 USA. 2 Department of Integrative Biology, The University of Texas at Austin, Austin, TX 78712 USA. 3 Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, TX 78712 USA. 4 Institute for Neuroscience, The University of Texas at Austin, Austin, TX 78712 USA.The ultimate-level factors that drive the evolution of mating systems have been well studied, but an evolutionarily conserved neural mechanism involved in shaping behaviour and social organization across species has remained elusive. Here, we review studies that have investigated the role of neural arginine vasopressin (AVP), vasotocin (AVT), and their receptor V1a in mediating variation in territorial behaviour. First, we discuss how aggression and territoriality are a function of population density in an inverted-U relationship according to resource defence theory, and how territoriality influences some mating systems. Next, we find that neural AVP, AVT, and V1a expression, especially in one particular neural circuit involving the lateral septum of the forebrain, are associated with territorial behaviour in males of diverse species, most likely due to their role in enhancing social cognition. Then we review studies that examined multiple species and find that neural AVP, AVT, and V1a expression is associated with territory size in mammals and fishes. Because territoriality plays an important role in shaping mating systems in many species, we present the idea that neural AVP, AVT, and V1a expression that is selected to mediate territory size may also influence the evolution of different mating systems. Future research that interprets proximate-level neuro-molecular mechanisms in the context of ultimate-level ecological theory may provide deep insight into the brain-behaviour relationships that underlie the diversity of social organization and mating systems seen across the animal kingdom.This work was supported by an Engineering Plus NSF-ADVANCE Opportunity grant to R.G. O., and NSF Grants IOS-0843712 and IOS-1354942, an Alfred P. Sloan Foundation Fellowship, the Dwight W. and Blanche Faye Reeder Centennial Fellowship in Systematic and Evolutionary Biology, and an Institute for Cellular and Molecular Biology Fellowship to H.A.H.Integrative Biolog

Critical Dynamics of the Contact Process with Quenched Disorder

We study critical spreading dynamics in the two-dimensional contact process (CP) with quenched disorder in the form of random dilution. In the pure model, spreading from a single particle at the critical point $\lambda_c$ is characterized by the critical exponents of directed percolation: in $2+1$ dimensions, $\delta = 0.46$, $\eta = 0.214$, and $z = 1.13$. Disorder causes a dramatic change in the critical exponents, to $\delta \simeq 0.60$, $\eta \simeq -0.42$, and $z \simeq 0.24$. These exponents govern spreading following a long crossover period. The usual hyperscaling relation, $4 \delta + 2 \eta = d z$, is violated. Our results support the conjecture by Bramson, Durrett, and Schonmann [Ann. Prob. {\bf 19}, 960 (1991)], that in two or more dimensions the disordered CP has only a single phase transition.Comment: 11 pages, REVTeX, four figures available on reques

Impact of rapid urban expansion on green space structure

Rapid urban expansion has had a significant impact on green space structure. A wide variety of modelling approaches have been tested to simulate urban expansion; however, the effectiveness of simulations of the spatial structure of urban expansion remains unexplored. This study aims to model and predict urban expansion in three cities (Kuala Lumpur, Metro Manila and Jakarta), all experiencing rapid urban expansion, and to identify which are the main drivers, including spatial planning, in the resulting spatial patterns. Land Change Modeller (LCM)-Markov Chain models were used, parameterised on changes observed between 1988/1989 and 1999 and verified with the urban form observed for 2014. These models were then used to simulate urban expansion for the year 2030. The spatial structure of the simulated 2030 land use was then compared with the 2030 master plan for each city using spatial metrics. LCM-Markov Chain models proved to be a suitable method for simulating the development of future land use. There were also important differences in the projected spatial structure for 2030 when compared to the planned development in each city; substantive differences in the size, density, distance, shape and spatial pattern. Evidence suggests that these spatial patterns are influenced by the forms of rapid urban expansion experienced in these cities and respective master planning policies of the municipalities of the cities. The use of integrated simulation modelling and landscape ecology analytics supplies significant insights into the evolution of the spatial structure of urban expansion and identifies constraints and informs intervention for spatial planning and policies in cities