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Uterine contractions monitoring is essential during pregnancy progression for due date prediction and the screening of preterm deliveries, i.e., those related to labour contractions occurring before 37 weeks of gestation. As there are different kinds of uterine contraction, distinguishing between true labour ones and normal physiological ones during pregnancy is not trivial. Thus, early identification is necessary for the effective and efficient care of pregnant women to avoid unnecessary and costly hospitalization. In this regard, while classical clinical methods proved their limitations, real-time monitoring of uterine contractions is now possible thanks to a new technique called ElectroHysteroGraphy which measures the uterine electrical activity that is a proxy for the mechanical activity of the muscles of the uterus. An exhaustive and comprehensive literature review was conducted to retrieve and report the state-of-the-art of the methods to distinguish labour contractions from pregnancy contractions. A systematic search was run on different search engines using a search string. A snowball sampling approach was applied to the references of the retrieved articles to identify further appropriate papers. According to this, the relevant references included in the bibliography of each analysed article led to other appropriate articles. Thus, papers dealing with the methods to distinguish labour from pregnancy (normal physiological) contractions and published between 2001 and 2020 were selected. Linear and nonlinear methods have been developed for uterine contractions signals (EHG/EMG) analysis to distinguish labour from pregnancy contractions. Nonlinear methods yielded better results compared to the linear methods, but not all nonlinear methods are promising in terms of clinical application.

Recently, the recognition of emotions with electroencephalographic (EEG) signals has received increasing attention. Furthermore, the nonstationarity of brain has intensified the application of nonlinear methods. Nonetheless, metrics like quadratic sample entropy (QSE), amplitude-aware permutation entropy (AAPE) and permutation min-entropy (PME) have never been applied to discern between more than two emotions. Therefore, this study computes for the first time QSE, AAPE and PME for recognition of four groups of emotions. After preprocessing the EEG recordings, the three entropy metrics were computed. Then, a tenfold classification approach based on a sequential forward selection scheme and a support vector machine classifier was implemented. This procedure was applied in a multi-class scheme including the four groups of study simultaneously, and in a binary-class approach for discerning emotions two by two, regarding their levels of arousal and valence. For both schemes, QSE+AAPE and QSE+PME were combined. In both multi-class and binary-class schemes, the best results were obtained in frontal and parietal brain areas. Furthermore, in most of the cases channels from QSE and AAPE/PME were selected in the classification models, thus highlighting the complementarity between those different types of entropy indices and achieving global accuracy results higher than 90% in multi-class and binary-class schemes. The combination of regularity- and predictability-based entropy indices denoted a high degree of complementarity between those nonlinear methods. Finally, the relevance of frontal and parietal areas for recognition of emotions has revealed the essential role of those brain regions in emotional processes., Facultad de Ingeniería, Centro de Investigaciones Ópticas

Current design codes have prepared linear analysis methods instead of nonlinear ones in order to reduce time, cost and other factors such as less need of these methods for expert knowledge. In linear analysis method, elastic strength demand of structure is decreased by applying a response modification factor called behavior factor (R) and by considering the design code regulations, structure members will be permitted to experience nonlinear response (in the time of middle-to-severe earthquakes). Because of different assumptions for linear (force-based method that has deficiencies) and nonlinear methods and whereas seismic stability or instability is not merely related to the strength of structure, rather it depends largely on the capability of structure to resist drifts, seismic performance evaluation of structures designed by linear procedure appears to be necessary using standards for evaluation. In this research, seismic performance of steel moment frames once designed based on 3rd edition of 2800-Iranian seismic code and allowable stress design (ASD) method and another time based on new ones, the 4th edition of 2800 seismic code and load and resistance factor design (LRFD) method, are compared with each other through nonlinear pushover and time-history analyses according to ASCE/SEI 41–13. Results showed positive change of design codes procedure with respect to alteration of design method in both types of ductile design, intermediate and special. Since mean of overstrength values and mean of ductility values have increased a little, mean of behavior factor values has become closer to the recommended values of the new seismic code. Also, a small number of structures met total collapse during nonlinear time-history analyses.

The ability to monitor the physiological effect of the analgesic agent is of interest in clinical practice. Nonstationary changes would appear in photoplethysmography (PPG) during the analgesics-driven transition to analgesia. The present work studied the properties of nonlinear methods including approximate entropy (ApEn) and sample entropy (SampEn) derived from PPG responding to a nociceptive stimulus under various opioid concentrations. Forty patients with ASA I or II were randomized to receive one of the four possible remifentanil effect-compartment target concentrations (Ceremi) of 0, 1, 3, and 5 ng·ml−1 and a propofol effect-compartment target-controlled infusion to maintain the state entropy (SE) at 50 ± 10. Laryngeal mask airway (LMA) insertion was applied as a standard noxious stimulation. To optimize the performance of ApEn and SampEn, different coefficients were carefully evaluated. The monotonicity of ApEn and SampEn changing from low Ceremi to high Ceremi was assessed with prediction probabilities (PK). The result showed that low Ceremi (0 and 1 ng·ml−1) could be differentiated from high Ceremi (3 and 5 ng·ml−1) by ApEn and SampEn. Depending on the coefficient employed in algorithm: ApEn with k = 0.15 yielded the largest PK value (0.875) whereas SampEn gained its largest PK of 0.867 with k = 0.2. Thus, PPG-based ApEn and SampEn with appropriate k values have the potential to offer good quantification of analgesia depth under general anesthesia.

Attention-deficit/hyperactivity disorder (ADHD) is a neuro-developmental and psychiatric disorder, which affects 11% of children around the world. Several linear and nonlinear biomarkers from electroencephalogram (EEG) signals have been proposed for diagnosis of ADHD to date. However, the determination of which type of analysis gives us the best feature and biomarker to diagnose ADHD is still controversial. In this study, we aimed to evaluate and compare several categories of features, extracted from EEG signals, for diagnosis of ADHD. Thirty 7–12-year-old children fulfilling the DSM5 criteria for ADHD and thirty healthy children underwent a noninvasive EEG evaluation at resting-state. After preprocessing, five categories of features including morphological, time, frequency, time-frequency, and nonlinear features were extracted from EEGs. The efficacy of each feature category in ADHD diagnosis was determined using statistical analysis, receiver operating characteristic (ROC) curves, and evidential K-nearest neighbor (EKNN) classifier. Statistical analyses showed that 13.15, 13.68, 14.47, 14.03, and 34.73% of extracted features were significant (p

Modern mathematical methods for analysis of heart rate variability (HRV), such as rescaled range analysis, detrended fluctuation analysis, and phase-rectified signal averaging were considered. Algorithms for calculating novel nonlinear HRV indices were described in detail. Mathematical models for simulating artificial cardiac Beat-to-beat intervals that take into account various noise processes were created. A state model of the cardiovascular system based on HRV analysis was developed. The sensitivity of HRV indices to changes in the state of the cardiovascular system was theoretically estimated using artificially simulated data.

The application of performance-based design and assessment procedures requires an accurate estimation of local component deformation demands. In the case of steel moment-resisting frames, these are usually defined in terms of plastic rotations. A rigorous estimation of this response parameter is not straightforward, requiring not only the adoption of complex nonlinear structural models, but also of time-consuming numerical integration calculations. Moreover, the majority of existing codes and guidelines do not provide any guidance in terms of how these response parameters should be estimated. Part 3 of Eurocode 8 (EC8-3) requires the quantification of plastic rotations even when linear methods of analysis are used. Therefore, the aim of the research presented in this paper is to evaluate different methods of quantifying local component demands and also to answer the question of how reliable are the estimates obtained using the EC8-3 linear analysis procedures in comparison to more accurate nonlinear methods of analysis, particularly when the linear analysis applicability criterion proposed by EC8-3 is verified. An alternative methodology to assess the applicability of linear analysis is proposed which overcomes the important limitations identified in the EC8-3 criterion.

Length–mass relationships are widely used to estimate body mass from body dimensions for freshwater macroinvertebrates. The relationships are influenced by environmental conditions and should be applied within ecosystems and geographic regions similar to those for which they were estimated. However, very few relationships exist for littoral macroinvertebrates, and thus we provide length–mass relationships for macroinvertebrates from lakes of the Central European lowlands. We compared log-linear and nonlinear methods for fitting length–mass relationships and tested the smearing factor for removing bias in mass predictions from log-linear models. We also estimated conversion factors to correct for mass changes during ethanol preservation and assessed the transferability of our results to different geographical regions. We showed that the log-linear approach gave better results in fitting length–mass relationships, while residuals showed that nonlinear models over-predict the mass of small individuals. The smearing correction factor successfully removed bias introduced by log transformation, and relationships transferred well between lakes in the same and different geographical regions. In total, 52 bias-corrected length–mass relationships are provided for littoral macroinvertebrates that are applicable also to lakes in geographic regions with similar environmental conditions, such as the Central European lowlands or the temperate lowland zone of America.

In this paper, we estimate the impact of rebate policies in various US states on the sales share of ENERGY STAR household appliances. We use annual ENERGY STAR sales data for clothes washers, dishwashers, refrigerators and air conditioners from 2001 to 2006 and the variation in the coverage of rebates across US states and over time to identify the impact of rebate policies. We use, at first, a difference-in-differences approach to estimate this impact. Then, we take into account the possibility of rebate policies being endogenous and use instrumental variables approaches in fixed effects panel data regression models. Results suggest that rebate policies increase the sales share of ENERGY STAR household appliances by 3.3 to 6.6 percentage points, and this represents an impact of 9 to 18 % on the mean level of the sales share of ENERGY STAR household appliances in the US between 2001 and 2006. We conclude that rebates on ENERGY STAR appliances increase the uptake of energy-efficient appliances.

The aim of this study was to provide a scientific basic for a unified standard of the reference value of vital capacity (VC) of healthy subjects from 6 and 84 years old in China. The normal reference value of VC was correlated to seven geographical factors, including altitude (X 1), annual duration of sunshine (X 2), annual mean air temperature (X 3), annual mean relative humidity (X 4), annual precipitation amount (X 5), annual air temperature range (X 6) and annual mean wind speed (X 7). Predictive models were established by five different linear and nonlinear methods. The best models were selected by t-test. The geographical distribution map of VC in different age groups can be interpolated by Kriging’s method using ArcGIS software. It was found that the correlation of VC and geographical factors in China was quite significant, especially for both males and females aged from 6 to 45. The best models were built for different age groups. The geographical distribution map shows the spatial variations of VC in China precisely. The VC of healthy subjects can be simulated by the best model or acquired from the geographical distribution map provided the geographical factors for that city or county of China are known.

Quantitative relationships between molecular structures and bioactivities of a set of CCR5 inhibitor derivatives were discovered. We have demonstrated the detailed application of two efficient nonlinear methods, general regression and radial basis function neural networks, for evaluation of quantitative structure–activity relationships of the studied compounds. Components produced by principal component analysis were used as input of the developed nonlinear models. Comparison between predictability of PC-GRNNs and PC-RBFNNs indicated that later method has higher ability to predict the activity of the studied molecules. In order to design novel derivatives of inhibitors with high activity and low side effects, and because experimental and calculated activities of molecules employed in the model development step, shown a good correlation, developed PC-RBFNNs QSAR model was used to calculate inhibitory activities of some suggested compounds.

A quantitative structure–property relationship (QSPR) study is performed to develop a model, relating to Na+ complex stability constant (log K) and the structure of 74 derivatives of 1,4,7,10,13-pentaoxacyclo-pentadecane ethers (15C5). Stepwise Multiple Linear Regression (SMLR) and Artificial Neural Network (ANN) methods have been exploited as linear and nonlinear methods, respectively to build the QSPR model. MOPAC software embedded in ChemOffice 2004 package was used for the minimizing energy using semi-empirical AM1 method. The optimum structures have been applied to generate more than 50 descriptors using available servers in ChemOffice 2004. The five most important constitutional, steric, electronic, thermodynamic and molecular descriptors were selected using the common preselection method combined by SMLR method. SMLR and ANN models were constructed based on the five selected descriptors. Both proposed models efficiently predict log K of 15C5 complexes. However, the results of ANN were more effective respect to SMLR model. This phenomenon reveals that log K of 15C5 complexes have a deviation from linear behavior related to the selected descriptors.

For direct sequence spread spectrum (DSSS) communication systems suffering interference, it is known that code-aided interference suppression technique outperforms all of the previous linear or nonlinear methods. In this paper, we proposed an improved code-aided technique which can improve the system performance greatly by using the eigenvector sign (EVS) spreading sequence which depends on the statistical characteristics of the interference and the thermal noise.

This study was designed to analyze the magnetoencephalogram (MEG) background activity from 20 patients with probable Alzheimer's disease (AD) and 21 control subjects by using two nonlinear methods: sample entropy (SampEn), and Lempel-Ziv complexity (LZC). The former quantifies the signal regularity, and the latter is a complexity measure. The signals were acquired with a 148-channel whole-head magnetometer placed in a magnetically shielded room. Our results show that MEG recordings are less complex and more regular in patients with AD than in control subjects. Significant differences between both groups were found in 16 MEG channels with SampEn and in 134 with LZC (p

We analysed the electroencephalogram (EEG) from Alzheimer's disease (AD) patients with two nonlinear methods: approximate entropy (ApEn) and auto mutual information (AMI). ApEn quantifies regularity in data, while AMI detects linear and nonlinear dependencies in time series. EEGs from 11 AD patients and 11 age-matched controls were analysed. ApEn was significantly lower in AD patients at electrodes O1, O2, P3 and P4 (p

The need for use of nonlinear methods for analysis of bed settlements is demonstrated, where use of linear methods of the criteria p ≤ R results in an unfounded additional increase in pu. Proceeding from the class of structures, it is recommended to determine the settlements using either special numerical solutions based on rigorous theories of plasticity, or closed time-tested engineering solutions with standard soil tests.

Two nonlinear methods are employed for the prediction of the maximum amplitude for solar cycle 23 and its declining behavior. First, a new heuristic method based on the second derivative of the (conveniently smoothed) sunspot data is proposed. The curvature of the smoothed sunspot data at cycle minimum appears to correlate (R ≃ 0.92) with the cycle's later-occurring maximum amplitude. Secondly, in order to predict the near-maximum and declining activity of solar cycle 23, a neural network analysis of the annual mean sunspot time series is also performed. The results of the present study are then compared with some other recent predictions.

Dieser Aufsatz gibt eine elementare Einfuhrung in Probleme und Methoden der nichtlinearen Signalverarbeitung und stellt neuere Entwicklungen auf diesem Gebiet im Uberblick dar. Einen wichtigen Platz nimmt dabei die Modellierung und Verarbeitung eindimensionaler Signale ein, wie sie bei einfachen Sprachkommunikations-systemen auftritt. Das Wechselspiel und die Integration deterministischer und nichtdeterministischer Ansatze wird an Hand von aktuellen Forschungsergebnissen erlautert.

One-dimensional circle maps are good models for describing the nonlinear dynamical behavior of two interacting oscillators. They have been employed to characterize the interaction between a periodic external forcing stimulus and an in vitro preparation of chick embryonic cardiac cells. They have also been used to model some human cardiac arrythmias such as modulated ventricular parasystole. In this paper, we describe several techniques involving engineering feedback control theory applied to a circle map model of human heart parasystole. Through simulations of the mathematical model, we demonstrate that a desired target phase relationship between the normal sinus rhythm and an abnormal ectopic pacemaker can be achieved rapidly with low-level external stimulation applied to the system. Specifically, we elucidate the linear, self-tuning, and nonlinear feedback approaches to control. The nonlinear methods are the fastest and most accurate, yet the most complex and computationally expensive to implement of the three types. The linear approach is the easiest to implement but may not be accurate enough in real applications, and the self-tuning methods are a compromise between the other two. The latter was successful in tracking a variety of period-1, period-2, and period-3 target phase trajectories of the heart model.

We answer several important questions concerning EEG. We also shortly discuss importance of nonlinear methods of contemporary physics in EEG analysis. Basic definitions and explanation of fundamental concepts may be found in my previous publications in NBP. It is a magnificent feeling to recognize the unity of complex phenomena which appear to be things quite apart from the direct visible truth. Albert Einstein

The two goals of Nonlinear Biomedical Physics are: firstly to show how nonlinear methods can shed new light on biological phenomena and medical applications and secondly to bridge the technical, mathematical, and cultural divides between the physical disciplines where these methods are being developed and the audience for their use in the biological and medical sciences.

Methods of contemporary physics are increasingly important for biomedical research but, for a multitude of diverse reasons, most practitioners of biomedicine lack access to a comprehensive knowledge of these modern methodologies. This paper is an attempt to describe nonlinear dynamics and its methods in a way that could be read and understood by biomedical professionals who usually are not trained in advanced mathematics. After an overview of basic concepts and vocabulary of nonlinear dynamics, deterministic chaos, and fractals, application of nonlinear methods of biosignal analysis is discussed. In particular, five case studies are presented: 1. Monitoring the depth of anaesthesia and of sedation; 2. Bright Light Therapy and Seasonal Affective Disorder; 3. Analysis of posturographic signals; 4. Evoked EEG and photo-stimulation; 5. Influence of electromagnetic fields generated by cellular phones.

A method is considered for increasing the immunity from interference of broadband systems for measuring and transmitting information. It is based on utilizing nonlinear methods to process spread-spectrum signals. The possibility is investigated of using a quasioptimal receiving device which can be implemented in practice. It is shown that the proposed method makes it possible to solve the rejection problem at the physical level.

A review of the various linear and nonlinear methods used to obtain resolution beyond natural linewidth is given.

This issue ofAlgorithmica present papers on various aspects of nonlinear methods for solving linear programming problems, inspired by the work of Karmarkar. This introduction describes some of these aspects and briefly mentions other recent developments in the field. A bibliography of recent articles is included.

The stability and accuracy of some explicit nonlinear methods for the numerical integration of stiff systems of ordinary differential equations are investigated. It is shown, that in the general case they can produce the essential error. The special class of stiff systems is singled out, for which these methods are highly efficient. Some numerical results are also presented.