Cluster synchronization in networks of distinct groups of maps

In this paper, we study cluster synchronization in general bi-directed networks of nonidentical clusters, where all nodes in the same cluster share an identical map. Based on the transverse stability analysis, we present sufficient conditions for local cluster synchronization of networks. The conditions are composed of two factors: the common inter-cluster coupling, which ensures the existence of an invariant cluster synchronization manifold, and communication between each pair of nodes in the same cluster, which is necessary for chaos synchronization. Consequently, we propose a quantity to measure the cluster synchronizability for a network with respect to the given clusters via a function of the eigenvalues of the Laplacian corresponding to the generalized eigenspace transverse to the cluster synchronization manifold. Then, we discuss the clustering synchronous dynamics and cluster synchronizability for four artificial network models: (i) p-nearest-neighborhood graph; (ii) random clustering graph; (iii) bipartite random graph; (iv) degree-preferred growing clustering network. From these network models, we are to reveal how the intra-cluster and inter-cluster links affect the cluster synchronizability. By numerical examples, we find that for the first model, the cluster synchronizability regularly enhances with the increase of p, yet for the other three models, when the ratio of intra-cluster links and the inter-cluster links reaches certain quantity, the clustering synchronizability reaches maximal.     

Numerical and experimental study of excited light and auto-fluorescence diffusion in teeth

Excited light and corresponding intrinsic fluorescence diffusion inside teeth tissue are an essential problem for light-based carious lesion detection. Based on finite element numerical analysis of diffusion equation, the photon density distribution of both excited light and autofluorescence of 2D premolar teeth model is obtained. The dependence of excited light and autofluorescence density distribution inside the teeth model on the scattering coefficient of enamel (5–25 mm⁻¹) and dentine (100–140 mm⁻¹) is numerically simulated and analyzed. The fitted results reveal that fluorescence intensity decreases exponentially. Optical penetration depth and fluorescence relative depth declined with the increment of scattering coefficient of enamel. And the dentine had the opposite effect. Finally, the experiment of measurement of fluorescence intensity on the teeth surface is conducted and the result is compared with the numerical computation.     

Evaluation of natural recharge of Chingshui geothermal reservoir using tritium as a tracer

Naturally existing tritium in groundwater was applied as a tracer to evaluate the natural recharge of the Chingshui geothermal reservoir. The residence time (or, age) of Chingshui geothermal water was first determined with tritium data at 15.2 and 11.3 year using the plug flow and dispersive model, respectively. The annual natural recharge was then estimated by combining the use of the residence time and the fluid-in-place of the Chingshui geothermal reservoir. The natural recharge for Chingshui geothermal reservoir was estimated at 5.0 × 10⁵ and 6.7 × 10⁵ m³ year^?1 using the plug flow and dispersive model, respectively. Chingshui geothermal water is largely from a fractured zone in the Jentse Member of the Miocene Lushan Formation. The dispersive model more adequately represents the fracture flow system than the simple plug flow model.     

Formation of seasonal groups and application of seasonal indices

Estimating seasonal variations in demand is a challenging task faced by many organisations. There may be many stock-keeping units (SKUs) to forecast, but often data histories are short, with very few complete seasonal cycles. It has been suggested in the literature that group seasonal indices (GSI) methods should be used to take advantage of information on similar SKUs. This paper addresses two research questions: (1) how should groups be formed in order to use the GSI methods? and (2) when should the GSI methods and the individual seasonal indices (ISI) method be used? Theoretical results are presented, showing that seasonal grouping and forecasting may be unified, based on a Mean Square Error criterion, and K-means clustering. A heuristic K-means method is presented, which is competitive with the Average Linkage method. It offers a viable alternative to a company's own grouping method or may be used with confidence if a company lacks a grouping method. The paper gives empirical findings that confirm earlier theoretical results that greater accuracy may be obtained by employing a rule that assigns the GSI method to some SKUs and the ISI method to the remainder.     

Theoretical study on the phase stability,elasticity, hardness and electronic structures of Ni–P compounds

A systematic investigation concerned with phase stability, elastic properties, hardness and relevant electronic structure of Ni–P compounds (Ni₃P, Ni₁₂P₅, Ni₂P, Ni₅P₄, NiP, NiP₂ and NiP₃) was carried out using first principles calculations. The calculated results show that the Ni–P compounds have strong hardness, ranging from 7.80–14.54 GPa. Also, the hardness values gradually increase with the P content. Electronic structure analysis shows that the strong Ni–P and part of P–P hybrid orbitals play important roles in the hardness of these compounds. The calculated elastic constants indicated that the Ni₃P, Ni₁₂P₅ and NiP₂ phases are significantly anisotropic, the NiP and Ni₂P exhibit some anisotropy, while the Ni₅P₄ and NiP₃ show a relatively isotropic character. At last, the properties of these Ni–P compounds including lattice constants, thermodynamic stability, elastic constants C_ij, bulk modulus B, shear modulus G, Young's modulus E and Poisson's ratio ν have been calculated.     

Congruences of multipartition functions modulo powers of primes

Let p _r (n) denote the number of r-component multipartitions of n, and let S _γ,λ be the space spanned by η(24z) ^γ ?(24z), where η(z) is the Dedekind’s eta function and ?(z) is a holomorphic modular form in \(M_{\lambda}(\mathrm{SL}_{2}(\mathbb{Z}))\) . In this paper, we show that the generating function of \(p_{r}(\frac{m^{k} n +r}{24})\) with respect to n is congruent to a function in the space S _γ,λ modulo m ^k . As special cases, this relation leads to many well known congruences including the Ramanujan congruences of p(n) modulo 5,7,11 and Gandhi’s congruences of p ₂(n) modulo 5 and p ₈(n) modulo 11. Furthermore, using the invariance property of S _γ,λ under the Hecke operator \(T_{\ell^{2}}\) , we obtain two classes of congruences pertaining to the m ^k -adic property of p _r (n).     

Subgrid-scale dynamics and model test in a turbulent stratified jet with coexistence of stable and unstable stratification

The subgrid-scale dynamics of stratified flows is studied in a horizontally introduced turbulent jet with coexistence of stable and unstable stratification of a low Richardson number case and a high Richardson number case. The positive production of subgrid-scale kinetic energy and the production of scalar variance suggest the forward energy cascade. The subgrid-scale buoyant destruction plays a role as a sink of subgrid-scale kinetic energy in the stable stratification while holds a role of turbulent generation in the unstable stratification. The role-switch of buoyant destruction in the stable stratification of high-Ri case implies the occurrence of a destabilising process triggered by the coupled instability mechanisms. The energy balance assumption related to the production of and the dissipation of subgrid-scale kinetic energy as well as the subgrid-scale buoyant destruction may fail. The a-priori test suggests the scale-invariant dynamic and standard Smagorinsky models not to work properly here, while the scale-dependent dynamic model gives a decent performance but with restrictions of the ratio between two testing filter scales.     

Canonical Forest

We propose a new classification ensemble method named Canonical Forest. The new method uses canonical linear discriminant analysis (CLDA) and bootstrapping to obtain accurate and diverse classifiers that constitute an ensemble. We note CLDA serves as a linear transformation tool rather than a dimension reduction tool. Since CLDA will find the transformed space that separates the classes farther in distribution, classifiers built on this space will be more accurate than those on the original space. To further facilitate the diversity of the classifiers in an ensemble, CLDA is applied only on a partial feature space for each bootstrapped data. To compare the performance of Canonical Forest and other widely used ensemble methods, we tested them on 29 real or artificial data sets. Canonical Forest performed significantly better in accuracy than other ensemble methods in most data sets. According to the investigation on the bias and variance decomposition, the success of Canonical Forest can be attributed to the variance reduction.