Mining sequences with exceptional transition behaviour of varying order using quality measures based on information-theoretic scoring functions

Discrete Markov chains are frequently used to analyse transition behaviour in sequential data. Here, the transition probabilities can be estimated using varying order Markov chains, where order k specifies the length of the sequence history that is used to model these probabilities. Generally, such a model is fitted to the entire dataset, but in practice it is likely that some heterogeneity in the data exists and that some sequences would be better modelled with alternative parameter values, or with a Markov chain of a different order. We use the framework of Exceptional Model Mining (EMM) to discover these exceptionally behaving sequences. In particular, we propose an EMM model class that allows for discovering subgroups with transition behaviour of varying order. To that end, we propose three new quality measures based on information-theoretic scoring functions. Our findings from controlled experiments show that all three quality measures find exceptional transition behaviour of varying order and are reasonably sensitive. The quality measure based on Akaike’s Information Criterion is most robust for the number of observations. We furthermore add to existing work by seeking for subgroups of sequences, as opposite to subgroups of transitions. Since we use sequence-level descriptive attributes, we form subgroups of entire sequences, which is practically relevant in situations where you want to identify the originators of exceptional sequences, such as patients. We show this relevance by analysing sequences of blood glucose values of adult persons with diabetes type 2. In the experiments, we find subgroups of patients based on age and glycated haemoglobin (HbA1c), a measure known to correlate with average blood glucose values. Clinicians and domain experts confirmed the transition behaviour as estimated by the fitted Markov chain models.

Electronic and Transport Properties of Sr-site Substituted: CaxSr(1-x)VO3

The Mott-insulator phase transition behaviour of the superstructure of strongly correlated system, CaxSr(1-x)VO3 (x =0, 0.33, 0.67, 1) have studied using the conventional density functional theory and the dynamical mean field theory. The Mott-Hubbard metal-insulator phase transition of superstructures, Ca0.33Sr0.67VO3 and Ca0.67Sr0.33VO3 formed by the CaVO3 and SrVO3 correlated metals, are obtained at U=4.5eV with β= 6(eV)-1 and U =4.5eV with β= 7(eV)-1 respectively. The values of U and β calculated through the Maximum Entropy model using the Green’s function data, are consistent with the experimental results. The value of Seebeck coefficient (S) of superstructure Ca0.33Sr0.67VO3 and Ca0.67Sr0.33VO3 are found to be +0.0011[V/K] and -0.0011[V/K] within the chemical potential μ = -1.266 eV to μ = -0.938 eV. The figures of merit (ZT) are found to be 0.97 at room temperature for these systems. The variation of electrical and thermal conductivities has also been discussed.

A unified quark-nuclear matter equation of state from the cluster virial expansion within the generalized Beth–Uhlenbeck approach

We consider a cluster expansion for strongly correlated quark matter where the clusters are baryons with spectral properties that are described within the generalized Beth–Uhlenbeck approach by a medium dependent phase shift. We employ a simple ansatz for the phase shift which describes an on-shell bound state with an effective mass and models the continuum by an anti-bound state located at the mass of the three-quark continuum threshold, so that the Levinson theorem is fulfilled by construction. The quark and baryon interactions are accounted for by the coupling to scalar and vector meson mean fields modelled by density functionals. At increasing density and temperature, due to the different medium-dependence of quark and baryon masses, the Mott dissociation of baryons occurs and its contributions to the thermodynamics vanish. It is demonstrated on this simple example that this unified approach to quark-hadron matter is capable of describing crossover as well as first order phase transition behaviour in the phase diagram with a critical endpoint. Changing the meson mean field, the case of a “crossover all over” in the phase diagram is also obtained.

Dual-supramolecular contacts induce extreme Hofmann framework distortion and multi-stepped spin-crossover

A ligand with dual-supramolecular contact character has been exploited to induce extreme Hofmann framework distortion and a resultant multi-stepped spin-crossover transition behaviour with a mismatch between structural and spin-state periodicity.

Evolutionary Image Transition and Painting Using Random Walks

We present a study demonstrating how random walk algorithms can be used for evolutionary image transition. We design different mutation operators based on uniform and biased random walks and study how their combination with a baseline mutation operator can lead to interesting image transition processes in terms of visual effects and artistic features. Using feature-based analysis we investigate the evolutionary image transition behaviour with respect to different features and evaluate the images constructed during the image transition process. Afterwards, we investigate how modifications of our biased random walk approaches can be used for evolutionary image painting. We introduce an evolutionary image painting approach whose underlying biased random walk can be controlled by a parameter influencing the bias of the random walk and thereby creating different artistic painting effects.