Multiconlitron: a general piecewise linear classifier.

Based on the "convexly separable" concept, we present a solid geometric theory and a new general framework to design piecewise linear classifiers for two arbitrarily complicated nonintersecting classes by using a "multiconlitron," which is a union of multiple conlitrons that comprise a set of hyperplanes or linear functions surrounding a convex region for separating two convexly separable datasets. We propose a new iterative algorithm called the cross distance minimization algorithm (CDMA) to compute hard margin non-kernel support vector machines (SVMs) via the nearest point pair between two convex polytopes. Using CDMA, we derive two new algorithms, i.e., the support conlitron algorithm (SCA) and the support multiconlitron algorithm (SMA) to construct support conlitrons and support multiconlitrons, respectively, which are unique and can separate two classes by a maximum margin as in an SVM. Comparative experiments show that SMA can outperform linear SVM on many of the selected databases and provide similar results to radial basis function SVM on some of them, while SCA performs better than linear SVM on three out of four applicable databases. Other experiments show that SMA and SCA may be further improved to draw more potential in the new research direction of piecewise linear learning.

Cloning, expression and characterization of HSP gene from Eimeria tenella / 生物工程学报

In order to study the functions of the HSPs (Heat shock proteins) of Eimeria tenella, we cloned a novel gene (which designated EtHSP) coding HSP of Eimeria tenella by RT-PCR and RACE (Rapid-amplification of cDNA ends). The full-length cDNA sequence of EtHSP was 1802 bp, containing a 1455 bp ORF (Open reading frame) (GenBank Accession No. FJ911605) encoding a deduced protein of 484 amino acids. Real-time PCR revealed that the mRNA level of EtHSP was much higher in sporozoites of E. tenella than other developmental stages (unsporulated oocysts, sporulated oocysts and merozoites). We constructed the recombinant plasmids pET28a(+)-EtHSP, then transformed it into E. coli BL21(DE3) for expression. SDS-PAGE indicated that the fusion protein was expressed in included bodies, with peak expression 6 h after induction by IPTG Western blotting revealed that the protein was specifically recognized by polyclonal antibodies against E. tenella, showing that the fusion protein was native antigen.

A normalized Levenshtein distance metric.

Although a number of normalized edit distances presented so far may offer good performance in some applications, none of them can be regarded as a genuine metric between strings because they do not satisfy the triangle inequality. Given two strings X and Y over a finite alphabet, this paper defines a new normalized edit distance between X and Y as a simple function of their lengths (|X| and |Y|) and the Generalized Levenshtein Distance (GLD) between them. The new distance can be easily computed through GLD with a complexity of O(|X|.|Y|) and it is a metric valued in [0, 1] under the condition that the weight function is a metric over the set of elementary edit operations with all costs of insertions/deletions having the same weight. Experiments using the AESA algorithm in handwritten digit recognition show that the new distance can generally provide similar results to some other normalized edit distances and may perform slightly better if the triangle inequality is violated in a particular data set.