Subharmonics and Aperiodicity in Hysteresis Loops

We show that it is possible to have hysteretic behavior for magnets that does not form simple closed loops in steady state, but must cycle multiple times before returning to its initial state. We show this by studying the zero-temperature dynamics of the 3d Edwards Anderson spin glass. The specific multiple varies from system to system and is often quite large and increases with system size. The last result suggests that the magnetization could be aperiodic in the large system limit for some realizations of randomness. It should be possible to observe this phenomena in low-temperature experiments.Comment: 4 pages, 3 figure

Development of a Canons of Practice Policy at Washington State University

Public policy educators, researchers, and administrators at Washington State University developed the Canons of Practice to guide faculty and staff engaging in contentious public issues. The need for such a document became evident when existing university policies and procedures lacked a suitable mechanism for resolving external criticism of public policy education and research. The Canons of Practice sets parameters for involvement in public policy research and education, provides guidelines for faculty and staff conduct, defines expectations of citizens and stakeholders, and establishes due process as the core of administrative response

Beyond time-homogeneity for continuous-time multistate Markov models

Multistate Markov models are a canonical parametric approach for data modeling of observed or latent stochastic processes supported on a finite state space. Continuous-time Markov processes describe data that are observed irregularly over time, as is often the case in longitudinal medical and biological data sets, for example. Assuming that a continuous-time Markov process is time-homogeneous, a closed-form likelihood function can be derived from the Kolmogorov forward equations -- a system of differential equations with a well-known matrix-exponential solution. Unfortunately, however, the forward equations do not admit an analytical solution for continuous-time, time-inhomogeneous Markov processes, and so researchers and practitioners often make the simplifying assumption that the process is piecewise time-homogeneous. In this paper, we provide intuitions and illustrations of the potential biases for parameter estimation that may ensue in the more realistic scenario that the piecewise-homogeneous assumption is violated, and we advocate for a solution for likelihood computation in a truly time-inhomogeneous fashion. Particular focus is afforded to the context of multistate Markov models that allow for state label misclassifications, which applies more broadly to hidden Markov models (HMMs), and Bayesian computations bypass the necessity for computationally demanding numerical gradient approximations for obtaining maximum likelihood estimates (MLEs)

Gel transitions in colloidal suspensions

The idealized mode coupling theory (MCT) is applied to colloidal systems interacting via short-range attractive interactions of Yukawa form. At low temperatures MCT predicts a slowing down of the local dynamics and ergodicity breaking transitions. The nonergodicity transitions share many features with the colloidal gel transition, and are proposed to be the source of gelation in colloidal systems. Previous calculations of the phase diagram are complemented with additional data for shorter ranges of the attractive interaction, showing that the path of the nonergodicity transition line is then unimpeded by the gas-liquid critical curve at low temperatures. Particular attention is given to the critical nonergodicity parameters, motivated by recent experimental measurements. An asymptotic model is developed, valid for dilute systems of spheres interacting via strong short-range attractions, and is shown to capture all aspects of the low temperature MCT nonergodicity transitions.Comment: 12 pages, LaTeX, 5 eps figures, uses ioplppt.sty, to appear in J. Phys.: Condens. Matte

Investigation of current perspectives for NHS Wales sustainable development through procurement policies

Public sector procurement has to operate under the pressure of policies and strict budgets. This paper examines the current perspectives of NHS Wales Shared Services Partnership (NWSSP) on sustainable procurement policies through the environmental, social and economic dimensions. In particular, it investigates the adoption levels of the sustainable procurement policies of buyers (NHS Wales), examines the level of engagement of SMEs to NHS Wales, and explores the support for the existing sustainable procurement function through order-processing analysis of catalogue coverage

Hysteresis and hierarchies: dynamics of disorder-driven first-order phase transformations

We use the zero-temperature random-field Ising model to study hysteretic behavior at first-order phase transitions. Sweeping the external field through zero, the model exhibits hysteresis, the return-point memory effect, and avalanche fluctuations. There is a critical value of disorder at which a jump in the magnetization (corresponding to an infinite avalanche) first occurs. We study the universal behavior at this critical point using mean-field theory, and also present preliminary results of numerical simulations in three dimensions.Comment: 12 pages plus 2 appended figures, plain TeX, CU-MSC-747

Nonergodicity transitions in colloidal suspensions with attractive interactions

The colloidal gel and glass transitions are investigated using the idealized mode coupling theory (MCT) for model systems characterized by short-range attractive interactions. Results are presented for the adhesive hard sphere and hard core attractive Yukawa systems. According to MCT, the former system shows a critical glass transition concentration that increases significantly with introduction of a weak attraction. For the latter attractive Yukawa system, MCT predicts low temperature nonergodic states that extend to the critical and subcritical region. Several features of the MCT nonergodicity transition in this system agree qualitatively with experimental observations on the colloidal gel transition, suggesting that the gel transition is caused by a low temperature extension of the glass transition. The range of the attraction is shown to govern the way the glass transition line traverses the phase diagram relative to the critical point, analogous to findings for the fluid-solid freezing transition.Comment: 11 pages, 7 figures; to be published in Phys. Rev. E (1 May 1999

A comparison of machine learning classifiers for pediatric epilepsy using resting-state functional MRI latency data

Epilepsy affects 1 in 150 children under the age of 10 and is the most common chronic pediatric neurological condition; poor seizure control can irreversibly disrupt normal brain development. The present study compared the ability of different machine learning algorithms trained with resting-state functional MRI (rfMRI) latency data to detect epilepsy. Preoperative rfMRI and anatomical MRI scans were obtained for 63 patients with epilepsy and 259 healthy controls. The normal distribution of latency z-scores from the epilepsy and healthy control cohorts were analyzed for overlap in 36 seed regions. In these seed regions, overlap between the study cohorts ranged from 0.44-0.58. Machine learning features were extracted from latency z-score maps using principal component analysis. Extreme Gradient Boosting (XGBoost), Support Vector Machines (SVM), and Random Forest algorithms were trained with these features. Area under the receiver operating characteristics curve (AUC), accuracy, sensitivity, specificity and F1-scores were used to evaluate model performance. The XGBoost model outperformed all other models with a test AUC of 0.79, accuracy of 74%, specificity of 73%, and a sensitivity of 77%. The Random Forest model performed comparably to XGBoost across multiple metrics, but it had a test sensitivity of 31%. The SVM model did not perform \u3e70% in any of the test metrics. The XGBoost model had the highest sensitivity and accuracy for the detection of epilepsy. Development of machine learning algorithms trained with rfMRI latency data could provide an adjunctive method for the diagnosis and evaluation of epilepsy with the goal of enabling timely and appropriate care for patients