Complex-valued Adaptive System Identification via Low-Rank Tensor Decomposition

Machine learning (ML) and tensor-based methods have been of significant interest for the scientific community for the last few decades. In a previous work we presented a novel tensor-based system identification framework to ease the computational burden of tensor-only architectures while still being able to achieve exceptionally good performance. However, the derived approach only allows to process real-valued problems and is therefore not directly applicable on a wide range of signal processing and communications problems, which often deal with complex-valued systems. In this work we therefore derive two new architectures to allow the processing of complex-valued signals, and show that these extensions are able to surpass the trivial, complex-valued extension of the original architecture in terms of performance, while only requiring a slight overhead in computational resources to allow for complex-valued operations

Enhanced Nonlinear System Identification by Interpolating Low-Rank Tensors

Function approximation from input and output data is one of the most investigated problems in signal processing. This problem has been tackled with various signal processing and machine learning methods. Although tensors have a rich history upon numerous disciplines, tensor-based estimation has recently become of particular interest in system identification. In this paper we focus on the problem of adaptive nonlinear system identification solved with interpolated tensor methods. We introduce three novel approaches where we combine the existing tensor-based estimation techniques with multidimensional linear interpolation. To keep the reduced complexity, we stick to the concept where the algorithms employ a Wiener or Hammerstein structure and the tensors are combined with the well-known LMS algorithm. The update of the tensor is based on a stochastic gradient decent concept. Moreover, an appropriate step size normalization for the update of the tensors and the LMS supports the convergence. Finally, in several experiments we show that the proposed algorithms almost always clearly outperform the state-of-the-art methods with lower or comparable complexity.Comment: 12 pages, 4 figures, 3 table

MK2 and ETV1 Are Prognostic Factors in Esophageal Adenocarcinomas

Background. Esophageal cancer is ranked in the top ten of diagnosed tumors worldwide. Even though improvements in survival could be noticed over the last years, prognosis remains poor. ETS translocation variant 1 (ETV1) is a member of a family of transcription factors and is phosphorylated by mitogen-activated protein kinase (MAPK)-activated protein kinase 2 (MK2). Aim of this study was to evaluate the prognostic role of MK2 and ETV1 in esophageal cancer. Methods. Consecutive patients that underwent surgical resection at the department of surgery at the Medical University of Vienna between 1991 and 2012 were included into this study. After microscopic analysis, tissue micro arrays (TMAs) were created and immunohistochemistry was performed with antibodies against MK2 and ETV1. Results. 323 patients were included in this study. Clinical data was achieved from a prospective patient data base. Nuclear overexpression of MK2 was observed in 143 (44.3%) cases for nuclear staining and in 142 (44.0%) cases a cytoplasmic overexpression of MK2 was observed. Nuclear and cytoplasmic ETV1 overexpression was detected in 20 cases (6.2%) and 30 cases (9.3%), respectively. In univariate survival analysis, cMK2 and nETV1 were found to be significantly associated with patients' overall survival. Whereas overexpression of cMK2 was associated with shorter, nETV1 was associated with longer overall survival. In multivariate survival analysis, both cMK2 and nETV1 were found to be independent prognostic factors for the subgroup of EAC as well. Discussion. Expression of MK2 and ETV1 are prognostic factors in patients, with esophageal adenocarcinoma

Modern Esophageal Function Testing and Gastroesophageal Reflux Disease in Morbidly Obese Patients

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Alternative therapies for GERD : a way to personalized antireflux surgery

Gastroesophageal reflux disease (GERD) is a commondisorder, known to affect about20%of theWestern population. Although conventional medical or surgical treatment has proven effective, there is certainly room for improvements. As only 10% of GERD patients are finally treated by antireflux surgery, a large therapeutic window exists. This treatment gap consists of patients who are not effectively treated with proton pump inhibitor but do not want to run the potential risks of conventional surgery. During the last two decades, several novel and intriguing options for the surgical treatment of GERD have been introduced and found their way into clinical use. The following summary will give an update of certain alternative therapeutic options to treat GERD or its pathological consequences

Adaptive System Identification via Low-Rank Tensor Decompositi

Tensor-based estimation has been of particular interest of the scientific community for several years now. While showing promising results on system estimation and other tasks, one big downside is the tremendous amount of computational power and memory required – especially during training – to achieve satisfactory performance. We present a novel framework for different classes of nonlinear systems, that allows to significantly reduce the complexity by introducing a least-mean-squares block before, after, or between tensors to reduce the necessary dimensions and rank required to model a given system. Our simulations show promising results that outperform traditional tensor models, and achieve equal performance to comparable algorithms for all problems considered while requiring significantly less operations per time step than either of the state-of-the-art architectures

An apoplastic peptide signal activates salicylic acid signalling in maize

Control of plant pathogen resistance or susceptibility largely depends on the promotion of either cell survival or cell death. In this context, papain-like cysteine proteases (PLCPs) regulate plant defence to drive cell death and protection against biotrophic pathogens. In maize (Zea mays), PLCPs are crucial in the orchestration of salicylic acid (SA)-dependent defence signalling. Despite this central role in immunity, it remains unknown how PLCPs are activated, and which downstream signals they induce to trigger plant immunity. Here, we present the discovery of an immune signalling peptide, Zea mays immune signalling peptide 1 (Zip1). A mass spectrometry approach identified the Zip1 peptide being produced after salicylic acid (SA) treatment. In vitro studies using recombinant proteins demonstrate that PLCPs are required to release bioactive Zip1 from its propeptide precursor (PROZIP1). Strikingly, Zip1 treatment strongly elicits SA accumulation in maize leaves. Moreover, RNAseq based transcriptome analyses revealed that Zip1 and SA treatments induce highly overlapping transcriptional changes. Consequently, Zip1 promotes the infection of the necrotrophic pathogen Botrytis cinerea in maize, while it reduces virulence of the biotrophic fungus Ustilago maydis. Together, Zip1 represents the previously missing signal that is released by PLCPs to activate SA defence signalling

A fungal substrate mimicking molecule suppresses plant immunity via an inter-kingdom conserved motif

Ustilago maydis is a biotrophic fungus causing corn smut disease in maize. The secreted effector protein Pit2 is an inhibitor of papain-like cysteine proteases (PLCPs) essential for virulence. Pit2 inhibitory function relies on a conserved 14 amino acids motif (PID14). Here we show that synthetic PID14 peptides act more efficiently as PLCP inhibitors than the full-length Pit2 effector. Mass spectrometry shows processing of Pit2 by maize PLCPs, which releases an inhibitory core motif from the PID14 sequence. Mutational analysis demonstrates that two conserved residues are essential for Pit2 function. We propose that the Pit2 effector functions as a substrate mimicking molecule: Pit2 is a suitable substrate for apoplastic PLCPs and its processing releases the embedded inhibitor peptide, which in turn blocks PLCPs to modulate host immunity. Remarkably, the PID14 core motif is present in several plant associated fungi and bacteria, indicating the existence of a conserved microbial inhibitor of proteases (cMIP)

Successful application of ancient DNA extraction and library construction protocols to museum wet collection specimens

Millions of scientific specimens are housed in museum collections, a large part of which are fluid preserved. The use of formaldehyde as fixative and subsequent storage in ethanol is especially common in ichthyology and herpetology. This type of preservation damages DNA and reduces the chance of successful retrieval of genetic data. We applied ancient DNA extraction and single stranded library construction protocols to a variety of vertebrate samples obtained from wet collections and of different ages. Our results show that almost all samples tested yielded endogenous DNA. Archival DNA extraction was successful across different tissue types as well as using small amounts of tissue. Conversion of archival DNA fragments into single-stranded libraries resulted in usable data even for samples with initially undetectable DNA amounts. Subsequent target capture approaches for mitochondrial DNA using homemade baits on a subset of 30 samples resulted in almost complete mitochondrial genome sequences in several instances. Thus, application of ancient DNA methodology makes wet collection specimens, including type material as well as rare, old or extinct species, accessible for genetic and genomic analyses. Our results, accompanied by detailed step-by-step protocols, are a large step forward to open the DNA archive of museum wet collections for scientific studies