This article reviews the strengths and limitations of induced pluripotent stem cell-derived cardiomyocytes (iPSC-CM) as models of cardiac arrhythmias. Specifically, the article attempts to answer the following questions: Which clinical arrhythmias can be modeled by iPSC-CM? How well can iPSC-CM model adult ventricular myocytes? What are the strengths and limitations ...

An automated algorithm to assess electrocardiogram (ECG) quality for both normal and abnormal rhythms is presented for false arrhythmia alarm suppression of intensive care unit (ICU) monitors. A particular focus is given to the quality assessment of a wide variety of arrhythmias. Data from three databases were used: the Physionet ...

Introduction: Our understanding of the complexity of arrhythmogenesis has grown progressively over the last two decades. The range of established arrhythmia mechanisms now includes numerous pathways including ion channels, membrane adaptor proteins, transcription factors and cytoplasmic signaling cascades. Areas covered: This review outlines the emerging biology underlying potentially lethal rhythm ...

In this paper, we review the information accumulated over the years regarding the phenomena of resetting and entrainment of reentrant arrhythmias. Over three decades of research and clinical applications, these phenomena have demonstrated that they stay as a main tool for an intellectual understanding of reentry and to base strategies ...

This paper presents a novel maximum margin clustering method with immune evolution (IEMMC) for automatic diagnosis of electrocardiogram (ECG) arrhythmias. This diagnostic system consists of signal processing, feature extraction, and the IEMMC algorithm for clustering of ECG arrhythmias. First, raw ECG signal is processed by an adaptive ECG filter based ...

Many are the sources of variability that can affect reproducibility of disease biomarkers from time-of-flight (TOF) Mass Spectrometry (MS) data. Here we present TOFwave, a complete software pipeline for TOF-MS biomarker identification, that limits the impact of parameter tuning along the whole chain of preprocessing and model selection modules. Peak ...

We derive a new efficient algorithm for the computation of the isotopic peak center-mass distribution of a molecule. With the use of Fourier transform techniques, the algorithm accurately computes the total abundance and average mass of all the isotopic species with the same number of nucleons. We evaluate the performance ...

Current status data arise due to only one feasible examination such that the failure time of interest occurs before or after the examination time. If the examination time is intrinsically related to the failure time of interest, the examination time is referred to as an informative censoring time. Such data ...

We present Spectral Registration with Multilayer Resampling (SRMR) as a 6 Degrees Of Freedom (DOF) registration method for noisy 3D data with partial overlap. The algorithm is based on decoupling 3D rotation from 3D translation by a corresponding resampling process of the spectral magnitude of a 3D Fast Fourier Transform ...

The Seattle Heart Failure Model (SHFM) is a multivariable model with proven prognostic value. Cardiopulmonary exercise testing (CPX) and neurohormonal markers (eg, B-type natriuretic peptide [BNP]) are also well accepted assessment techniques in the HF population and have both demonstrated robust prognostic value. The purpose of this investigation was to ...

Green [J. Acoust. Soc. Am. 87, 2662-2674 (1990)] suggested an efficient, maximum-likelihood-based approach for adaptively estimating thresholds. Such procedures determine the signal strength on each trial by first identifying the most likely psychometric functions among the pre-proposed alternatives based on responses from previous trials, and then finding the signal strength ...

We developed an application for Android™-based mobile devices that allows real-time electrocardiogram (ECG) monitoring and automated arrhythmia detection by analyzing ECG parameters. ECG data provided by pre-recorded files or acquired live by accessing a Shimmer™ sensor node via Bluetooth™ can be processed and evaluated. The application is based on the ...

In this paper, we construct an appearance model using the 3D discrete cosine transform (3D-DCT). The 3D-DCT is based on a set of cosine basis functions, which are determined by the dimensions of the 3D signal and thus independent of the input video data. In addition, the 3D-DCT can generate ...

We present a lattice-gas kinetic Monte Carlo model to investigate the formation of silicate oligomers, their aggregation and the subsequent gelation process. In the early oligomerization stage, the 3-rings are metastable, 5-rings and 6-rings are formed in very small quantities, 4-rings are abundant species, linear and branched species are transformed ...

Resting frontal encephalographic (EEG) asymmetry, often conceptualized as a trait marker for depression, is influenced by occasion-specific factors, including time of year and the time of day of the recording session as demonstrated recently (Peterson and Harmon-Jones, 2009). The current study examined the influence of seasonal and chronological variables on ...

We present an extension of the BM3D filter to volumetric data. The proposed algorithm, denominated BM4D, implements the grouping and collaborative filtering paradigm, where mutually similar d-dimensional patches are stacked together in a (d+1)-dimensional array and jointly filtered in transform domain. While in BM3D the basic data patches are blocks ...

Spatial transformation for diffusion spectrum imaging (DSI) is an important step for group analyses of DSI datasets. In this study, we developed a transformation method for DSI datasets under the framework of large deformation diffeomorphic metric mapping (LDDMM), which is termed LDDMM-DSI. The proposed method made use of the fact ...

Concentration-response studies are performed to investigate the potency of the substance under investigation. Data are typically evaluated using non-linear regression. A common model is the log-logistic model which includes parameters for lower and upper boundary of mean response, EC50 and Hill slope. Often, response and/or concentration data are transformed before ...

In dietary exposure assessment, statistical methods exist for estimating the usual intake distribution from daily intake data. These methods transform the dietary intake data to normal observations, eliminate the within-person variance, and then back-transform the data to the original scale. We propose Gaussian Quadrature (GQ), a numerical integration method, as ...

How can humans acquire relational representations that enable analogical inference and other forms of high-level reasoning? Using comparative relations as a model domain, we explore the possibility that bottom-up learning mechanisms applied to objects coded as feature vectors can yield representations of relations sufficient to solve analogy problems. We introduce ...

Knowledge and technology transfer to African laboratories and farmers is an important objective for achieving food security and sustainable crop production on the sub-Saharan African continent. Cassava (Manihot esculenta Crantz) is a vital source of calories for more than a billion people in developing countries, and its potential industrial use ...

Many digital imaging devices operate by successive photon-to-electron, electron-to-voltage, and voltage-to-digit conversion. This process is subject to various signal-dependent errors, which are typically modelled as Poisson-Gaussian noise. The removal of such noise can be approached indirectly by applying a variance-stabilizing transformation (VST) to the noisy data, denoising the stabilized data ...

Purpose: Per-beam quality-assurance (QA) methods (e.g. portal dosimetry) have been shown to be inadequate for reporting the clinical significance of delivery errors or deviations. Recently we presented a novel 'transform' method which can solve this problem utilizing 3D dosimetry techniques. Here, we evaluate the accuracy of this method under various ...

This study describes an efficient transformation system for the introduction of plasmid DNA into Bifidobacterium bifidum PRL2010 and Bifidobacterium asteroides PRL2011, for which to the best of our knowledge no transformation data have been reported previously. The method is based on electroporation of bifidobacterial cells, which were made competent by ...

Rapid discrimination of pork in Halal and non-Halal Chinese ham sausages was developed by Fourier transform infrared (FTIR) spectrometry combined with chemometrics. Transmittance spectra ranging from 400 to 4000cm(-1) of 73 Halal and 78 non-Halal Chinese ham sausages were measured. Sample preparation involved finely grinding of samples and formation of ...

Previous research suggests that the acquisition of an internal model of a complex visuo-motor transformation might proceed as a progression of approximations. Here, we test this assumption by comparing performance of three groups of participants during practice and subsequent open-loop tests with three different types of visuo-motor transformation: the kinematic ...

Integral transforms with kernels corresponding to computational units are exploited to derive estimates of network complexity. The estimates are obtained by combining tools from nonlinear approximation theory and functional analysis together with representations of functions in the form of infinite neural networks. The results are applied to perceptron networks.

We consider a hypercube view to perceive the label space of multilabel classification problems geometrically. The view allows us not only to unify many existing multilabel classification approaches but also design a novel algorithm, principal label space transformation (PLST), that captures key correlations between labels before learning. The simple and ...

We propose 2 related models for the meta-analysis of diagnostic tests. Both models are based on the bivariate normal distribution for transformed sensitivities and false-positive rates. Instead of using the logit as a transformation for these proportions, we employ the tα family of transformations that contains the log, logit, and ...

When two test forms measure the same construct but are independently modelled using item response theory, the two forms' respective metrics cannot be assumed to be equivalent. Thus, before comparing parameter estimates across forms, a linear transformation must be applied to at least one form's scale. The mean-sigma method is ...

This paper presents a new index to measure the hypnotic depth of anaesthesia (DoA) using EEG signals. This index is derived from applying combined Wavelet transform, eigenvector and normalisation techniques. The eigenvector method is first applied to build a feature function for six levels of coefficients in a discrete wavelet ...

In this paper, we propose a novel framework to estimate the parameters of a diffeomorphism that aligns a known shape and its distorted observation. Classical registration methods first establish correspondences between the shapes and then compute the transformation parameters from these landmarks. Herein, we trace back the problem to the ...

The authors developed scaling methods that monotonically transform the output of one classifier to the "scale" of another. Such transformations affect the distribution of classifier output while leaving the ROC curve unchanged. In particular, they investigated transformations between radiologists and computer classifiers, with the goal of addressing the problem of ...

ABSTRACT: BACKGROUND: To derive micronutrient recommendations in a scientifically sound way, it is important to obtain and analyse all published information on the association between micronutrient intake and biochemical proxies for micronutrient status using a systematic approach. Therefore, it is important to incorporate information from randomized controlled trials as well ...

In this work we studied the improvement in heartbeat classification achieved by including information from multilead ECG recordings in a previously developed and validated classification model. This model includes features from the RR interval series and morphology descriptors for each lead calculated from the wavelet transform. The experiments were carried ...

The trajectory tracking problem of a closed-chain five-bar robot is studied in this paper. Based on an error transformation function and the backstepping technique, an approximation-based tracking algorithm is proposed, which can guarantee the control performance of the robotic system in both the stable and transient phases. In particular, the ...

We propose a hierarchical Bayesian methodology to model spatially or spatio-temporal clustered survival data with possibility of cure. A flexible continuous transformation class of survival curves indexed by a single parameter is used. This transformation model is a larger class of models containing two special cases of the well-known existing ...

The item response times (RTs) collected from computerized testing represent an underutilized source of information about items and examinees. In addition to knowing the examinees' responses to each item, we can investigate the amount of time examinees spend on each item. In this paper, we propose a semi-parametric model for ...

In this study, an electroencephalogram (EEG) analysis system is proposed for single-trial classification of both motor imagery (MI) and finger-lifting EEG data. Applying event-related brain potential (ERP) data acquired from the sensorimotor cortices, the system mainly consists of three procedures, including enhanced active segment selection, feature extraction, and classification. First, ...

The automatic detection and classification of electroencephalogram (EEG) epileptic activity are significant in both diagnosis and relieving the heavy workload of doctors. This article presents a new EEG classification approach based on the extreme learning machine (ELM) and wavelet transform (WT). First, the WT is used to extract useful features ...

Whenever we shift our gaze, any location information encoded in the retinocentric reference frame that is predominant in the visual system is obliterated. How is spatial memory retained across gaze changes? Two different explanations have been proposed: Retinocentric information may be transformed into a gaze-invariant representation through a mechanism consistent ...

It is known that the acoustic emission (AE) signals contain potentially valuable information for grinding wheel and work conditions during automatic grinding process. However, AE signals produced in the grinding zone are usually much more complicated and it is difficult to obtain enough effective information directly from raw AE signals. ...

A computational strategy, aimed at evaluating diffraction catastrophes belonging to the X_{9} family is presented. The approach proposed is based on the use of power series expansions, suitably derived for giving meaningful representation of the whole ^{0}X_{9} subfamily, jointly with a powerful sequence transformation algorithm, the so-called Weniger transformation. The ...

ABSTRACT: BACKGROUND: Wavelets have proven to be a powerful technique for the analysis of periodic data, such as those that arise in the analysis of circadian oscillators. While many implementations of both continuous and discrete wavelet transforms are available, we are aware of no software that has been designed with ...

General Purpose Graphic Processing Units (GPGPUs) constitute an inexpensive resource for computing-intensive applications that could exploit an intrinsic fine-grain parallelism. This paper presents the design and implementation in GPGPUs of an exact alignment tool for nucleotide sequences based on the Burrows-Wheeler Transform. We compare this algorithm with state-of-the-art implementations of ...

The objective of this study was to determine whether metabolic parameters derived from ex vivo analysis of tissue samples are predictive of biologic characteristics of recurrent low grade gliomas (LGGs). This was achieved by exploring the use of multivariate pattern recognition methods to generate statistical models of the metabolic characteristics ...

Solid lipid nanoparticles (SLNs) have applications in drug delivery and the encapsulation of bioactive, lipophilic compounds. However, SLNs tend to aggregate when stored due to the lipid crystals undergoing a polymorphic transformation from the unstable α form to the stable β form. We developed a population balance equation (PBE) model ...

A new algorithm for the conversion of device dependent RGB colour data into device independent L*a*b* colour data without introducing noticeable error has been developed. By combining a linear colour space transform and advanced multiple regression methodologies it was possible to predict L*a*b* colour data with less than 2.2 colour ...

This concept of pre-conditioning data (utilizing a power transformation as an initial step) for analysis and visualization is well established within the statistical community and is employed as part of statistical modeling and analysis. Such transformations condition the data to various inherent assumptions of statistical inference procedures, as well as ...

The allometric method, which often is attributed to Julian Huxley, entails fitting a straight line to logarithmic transformations of the original bivariate data and then back-transforming the resulting equation to form a power function in the arithmetic scale. Development of the technique was strongly influenced by Huxley's own research on ...