Sparse permutation invariant covariance estimation

The paper proposes a method for constructing a sparse estimator for the inverse covariance (concentration) matrix in high-dimensional settings. The estimator uses a penalized normal likelihood approach and forces sparsity by using a lasso-type penalty. We establish a rate of convergence in the Frobenius norm as both data dimension $p$ and sample size $n$ are allowed to grow, and show that the rate depends explicitly on how sparse the true concentration matrix is. We also show that a correlation-based version of the method exhibits better rates in the operator norm. We also derive a fast iterative algorithm for computing the estimator, which relies on the popular Cholesky decomposition of the inverse but produces a permutation-invariant estimator. The method is compared to other estimators on simulated data and on a real data example of tumor tissue classification using gene expression data.Comment: Published in at http://dx.doi.org/10.1214/08-EJS176 the Electronic Journal of Statistics (http://www.i-journals.org/ejs/) by the Institute of Mathematical Statistics (http://www.imstat.org

Interaction of a symmetrical α,α',δ,δ'-Tetramethyl-cucurbit[6]uril with Ln³⁺ : potential applications for isolation of lanthanides

The interaction of a symmetrical α,α′,δ,δ′-tetramethyl-cucurbit[6]uril (TMeQ[6]) with a series of lanthanide cations (Ln³⁺) was investigated in neutral water and in acidic solution. Analysis by single crystal X-ray diffraction revealed that different isomorphous families formed under different synthetic conditions. Such differences in the interaction between TMeQ[6] and Ln³⁺ could potentially be used for isolating heavier Ln³⁺ from their lighter counterparts in neutral solution, and lighter lanthanide cations from their heavier counterparts in acidic solution

Time-dependent quantum transport: Direct analysis in the time domain

We present a numerical approach for solving time-dependent quantum transport problems in molecular electronics. By directly solving Green's functions in the time domain, this approach does not rely on the wide-band limit approximation thereby is capable of taking into account the detailed electronic structures of the device leads which is important for molecular electronics. Using this approach we investigate two typical situations: current driven by a bias voltage pulse and by a periodic field, illustrating that the computational requirement is no more than an inversion of a relatively small triangular matrix plus several matrix multiplications. We then present numerical results of time-dependent charge current for a one-dimensional atomic chain. The numerical solution recovers known results in the wide-band limit, and reveals physical behavior for leads with finite bandwidth.published_or_final_versio

Remedial brushless AC operation of fault-tolerant doubly salient permanent-magnet motor drives

The doubly salient permanent-magnet (DSPM) machine is a new class of stator-PM brushless machines, which inherently offers the fault-tolerant feature. In this paper, a new operation strategy is proposed and implemented for fault-tolerant DSPM motor drives. The key is to operate the DSPM motor drive in a remedial brushless ac (BLAC) mode under the open-circuit fault condition, while operating in the conventional brushless dc mode under normal condition. Both cosimulation and experimental results confirm that the proposed remedial BLAC operation can maintain the average torque, reduce the torque ripple, and retain the self-starting capability under the open-circuit fault. © 2006 IEEE.published_or_final_versio

Topological Properties of Spatial Coherence Function

Topology of the spatial coherence function is considered in details. The phase singularity (coherence vortices) structures of coherence function are classified by Hopf index and Brouwer degree in topology. The coherence flux quantization and the linking of the closed coherence vortices are also studied from the topological properties of the spatial coherence function.Comment: 9 page

A new taxol-producing fungus (Pestalotiopsis malicola) and evidence for taxol as a transient product in the culture

Fungal production of the anti-tumor taxol is an effective way of making this drug in industries. We reported here a new taxol-producing fungus, NK101, from plant debris in the soil. Based on the culture characteristics, conidia structure and molecular evidence, NK101 was classified as Pestalotiopsis malicola. Taxol was verified in both the culture and the mycelium in a high level (186 μg/L). The time course of yield suggests that taxol was present as a transient product in the fungus. This work may show the diversity of using fungi to produce taxol.Key words: Taxol, saprophyte, Pestalotiopsis

Topological Aspect of Knotted Vortex Filaments in Excitable Media

Scroll waves exist ubiquitously in three-dimensional excitable media. It's rotation center can be regarded as a topological object called vortex filament. In three-dimensional space, the vortex filaments usually form closed loops, and even linked and knotted. In this letter, we give a rigorous topological description of knotted vortex filaments. By using the $\phi$-mapping topological current theory, we rewrite the topological current form of the charge density of vortex filaments and use this topological current we reveal that the Hopf invariant of vortex filaments is just the sum of the linking and self-linking numbers of the knotted vortex filaments. We think that the precise expression of the Hopf invariant may imply a new topological constraint on knotted vortex filaments.Comment: 4 pages, no figures, Accepted by Chin. Phys. Let

Determining Principal Component Cardinality through the Principle of Minimum Description Length

PCA (Principal Component Analysis) and its variants areubiquitous techniques for matrix dimension reduction and reduced-dimensionlatent-factor extraction. One significant challenge in using PCA, is thechoice of the number of principal components. The information-theoreticMDL (Minimum Description Length) principle gives objective compression-based criteria for model selection, but it is difficult to analytically applyits modern definition - NML (Normalized Maximum Likelihood) - to theproblem of PCA. This work shows a general reduction of NML prob-lems to lower-dimension problems. Applying this reduction, it boundsthe NML of PCA, by terms of the NML of linear regression, which areknown.Comment: LOD 201