Robust Logistic Principal Component Regression for classification of data in presence of outliers

The Logistic Principal Component Regression (LPCR) has found many applications in classification of high-dimensional data, such as tumor classification using microarray data. However, when the measurements are contaminated and/or the observations are mislabeled, the performance of the LPCR will be significantly degraded. In this paper, we propose a new robust LPCR based on M-estimation, which constitutes a versatile framework to reduce the sensitivity of the estimators to outliers. In particular, robust detection rules are used to first remove the contaminated measurements and then a modified Huber function is used to further remove the contributions of the mislabeled observations. Experimental results show that the proposed method generally outperforms the conventional LPCR under the presence of outliers, while maintaining a performance comparable to that obtained under normal condition. © 2012 IEEE.published_or_final_versionThe 2012 IEEE International Symposium on Circuits and Systems (ISCAS), Seoul, Korea, 20-23 May 2012. In IEEE International Symposium on Circuits and Systems Proceedings, 2012, p. 2809-281

Robust recursive eigendecomposition and subspace-based algorithms with application to fault detection in wireless sensor networks

The principal component analysis (PCA) is a valuable tool in multivariate statistics, and it is an effective method for fault detection in wireless sensor networks (WSNs) and other related applications. However, its online implementation requires the computation of eigendecomposition (ED) or singular value decomposition. To reduce the arithmetic complexity, we propose an efficient fault detection approach using the subspace tracking concept. In particular, two new robust subspace tracking algorithms are developed, namely, the robust orthonormal projection approximation subspace tracking (OPAST) with rank-1 modification and the robust OPAST with deflation. Both methods rely on robust M-estimate-based recursive covariance estimate to improve the robustness against the effect of faulty samples, and they offer different tradeoff between fault detection accuracy and arithmetic complexity. Since only the ED in the major subspace is computed, their arithmetic complexities are much lower than those of other conventional PCA-based algorithms. Furthermore, we propose new robust T 2 score and SPE detection criteria with recursive update formulas to improve the robustness over their conventional counterparts and to facilitate online implementation for the proposed robust subspace ED and tracking algorithms. Computer simulation and experimental results on WSN data show that the proposed fault detection approach, which combines the aforementioned robust subspace tracking algorithms with the robust detection criteria, is able to achieve better performance than other conventional approaches. Hence, it serves as an attractive alternative to other conventional approaches to fault detection in WSNs and other related applications because of its low complexity, efficient recursive implementation, and good performance. © 2012 IEEE.published_or_final_versio

A New Method for Preliminary Identification of Gene Regulatory Networks from Gene Microarray Cancer Data Using Ridge Partial Least Squares with Recursive Feature Elimination and Novel Brier and Occurrence Probability Measures

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A new recursive dynamic factor analysis for point and interval forecast of electricity price

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Load/Price Forecasting and Management of Demand Response for Smart Grids: Methodologies and Challenges

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Efficient Implementation and Design of A New Single-Channel Electrooculography-based Human-Machine Interface System

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Controllability and controller-observer design for a class of linear time-varying systems

“The final publication is available at Springer via http://dx.doi.org/10.1007/s10852-012-9212-6"In this paper a class of linear time-varying control systems is considered. The time variation consists of a scalar time-varying coefficient multiplying the state matrix of an otherwise time-invariant system. Under very weak assumptions of this coefficient, we show that the controllability can be assessed by an algebraic rank condition, Kalman canonical decomposition is possible, and we give a method for designing a linear state-feedback controller and Luenberger observer

Interplay between pleiotropy and secondary selection determines rise and fall of mutators in stress response

Dramatic rise of mutators has been found to accompany adaptation of bacteria in response to many kinds of stress. Two views on the evolutionary origin of this phenomenon emerged: the pleiotropic hypothesis positing that it is a byproduct of environmental stress or other specific stress response mechanisms and the second order selection which states that mutators hitchhike to fixation with unrelated beneficial alleles. Conventional population genetics models could not fully resolve this controversy because they are based on certain assumptions about fitness landscape. Here we address this problem using a microscopic multiscale model, which couples physically realistic molecular descriptions of proteins and their interactions with population genetics of carrier organisms without assuming any a priori fitness landscape. We found that both pleiotropy and second order selection play a crucial role at different stages of adaptation: the supply of mutators is provided through destabilization of error correction complexes or fluctuations of production levels of prototypic mismatch repair proteins (pleiotropic effects), while rise and fixation of mutators occur when there is a sufficient supply of beneficial mutations in replication-controlling genes. This general mechanism assures a robust and reliable adaptation of organisms to unforeseen challenges. This study highlights physical principles underlying physical biological mechanisms of stress response and adaptation

Systematic Identification of Placental Epigenetic Signatures for the Noninvasive Prenatal Detection of Edwards Syndrome

Background: Noninvasive prenatal diagnosis of fetal aneuploidy by maternal plasma analysis is challenging owing to the low fractional and absolute concentrations of fetal DNA in maternal plasma. Previously, we demonstrated for the first time that fetal DNA in maternal plasma could be specifically targeted by epigenetic (DNA methylation) signatures in the placenta. By comparing one such methylated fetal epigenetic marker located on chromosome 21 with another fetal genetic marker located on a reference chromosome in maternal plasma, we could infer the relative dosage of fetal chromosome 21 and noninvasively detect fetal trisomy 21. Here we apply this epigenetic-genetic (EGG) chromosome dosage approach to detect Edwards syndrome (trisomy 18) in the fetus noninvasively. Principal Findings: We have systematically identified methylated fetal epigenetic markers on chromosome 18 by methylated DNA immunoprecipitation (MeDIP) and tiling array analysis with confirmation using quantitative DNA methylation assays. Methylated DNA sequences from an intergenic region between the VAPA and APCDD1 genes (the VAPAAPCDD1 DNA) were detected in pre-delivery, but not post-delivery, maternal plasma samples. The concentrations correlated positively with those of an established fetal genetic marker, ZFY, in pre-delivery maternal plasma. The ratios of methylated VAPA-APCDD1(chr18) to ZFY(chrY) were higher in maternal plasma samples of 9 male trisomy 18 fetuses than those of 27 male euploid fetuses (Mann-Whitney test, P = 0.029). We defined the cutoff value for detecting trisomy 18 fetuses as mean+1.96 SD of the EGG ratios of the euploid cases. Eight of 9 trisomy 18 and 1 of 27 euploid cases showed EGG ratios higher than the cutoff value, giving a sensitivity of 88.9% and a specificity of 96.3%. Conclusions: Our data have shown that the methylated VAPA-APCDD1 DNA in maternal plasma is redominantly derived from the fetus. We have demonstrated that this novel fetal epigenetic marker in maternal plasma is useful for the noninvasive detection of fetal trisomy 18. © Tsui et al.published_or_final_versio

Fluorescent D-amino-acids reveal bi-cellular cell wall modifications important for Bdellovibrio bacteriovorous predation

Modification of essential bacterial peptidoglycan (PG) containing cell walls can lead to antibiotic resistance, for example β-lactam resistance by L,D-transpeptidase activities. Predatory Bdellovibrio bacteriovorus are naturally antibacterial and combat infections by traversing, modifying and finally destroying walls of Gram-negative prey bacteria, modifying their own PG as they grow inside prey. Historically, these multi-enzymatic processes on two similar PG walls have proved challenging to elucidate. Here, with a PG labelling approach utilizing timed pulses of multiple fluorescent D-amino acids (FDAAs), we illuminate dynamic changes that predator and prey walls go through during the different phases of bacteria:bacteria invasion. We show formation of a reinforced circular port-hole in the prey wall; L,D-transpeptidaseBd mediated D-amino acid modifications strengthening prey PG during Bdellovibrio invasion and a zonal mode of predator-elongation. This process is followed by unconventional, multi-point and synchronous septation of the intracellular Bdellovibrio, accommodating odd- and even-numbered progeny formation by non-binary division