Nonlinear Science Leaps Forward … Again.

We studied how linear and nonlinear heart rate dynamics differ between normal fetuses (n=135) and uncomplicated small-for-gestational age (SGA) fetuses (n=65), aged 32-40 weeks' gestation. We analyzed each fetal heart rate time series for 20 min. We quantified the complexity (nonlinear dynamics) of each fetal heart rate (FHR) time series by approximate entropy (ApEn) and correlation dimension (CD). The linear dynamics were analyzed by canonical correlation analysis (CCA). The ApEn and CD of the uncomplicated SGA fetuses were significantly lower than that of the normal fetuses in all three gestational periods (32-34, 35-37, 38-40 weeks). Canonical correlation ensemble in SGA fetuses is slightly higher than normal ones in all three gestational periods, especially at 35-37 weeks. Irregularity and complexity of the heart rate dynamics of SGA fetuses are lower than that of normal ones. Also, canonical ensemble in SGA fetuses is higher than in normal ones, suggesting that the FHR control system has multiple complex interactions. Along with the clear difference between the two groups' non-linear chaotic dynamics in FHR patterns, we clarified the hidden subtle differences in linearity (e.g., canonical ensemble). The decrease in non-linear dynamics may contribute to the increase in linear dynamics. The present statistical methodology can be readily and routinely utilized in obstetrics and gynecologic fields.

In this article, dynamics and stability of milling operations with cylindrical end mills are investigated. A unified–mechanics–based model, which allows for both regenerative effects and loss–of–contact effects, is presented for study of partial–immersion, high–immersion and slotting operations. Reduced–order models that can be used for certain milling operations such as full–immersion operations and finishing cuts are also presented. On the basis of these models, the loss of stability of periodic motions of the workpiece–tool system is assessed by using Poincare sections and the numerical predictions of stable and unstable motions are found to correlate well with the corresponding experimental observations. Bifurcations experienced by periodic motions of the workpiece–tool system with respect to quasi–static variation of parameters such as axial depth of cut are examined and discussed. For partial–immersion operations, consideration of both time–delay effects and loss–of–contact effects is shown to have a significant influence on the structure of the stability boundaries in the space of spindle speed and axial depth of cut. The sensitivity of system dynamics to multiple–regenerative effects, mode–coupling effects and feed rate is also discussed.

Bipolar disorder is a psychiatric disorder that is episodic and chronic and can lead to significant impairment in a person’s life. The term bipolar disorders encompasses a number of diagnoses including bipolar I disorder, bipolar II disorder, cyclothymic disorder, substance/medication-induced bipolar and related disorder, bipolar and related disorder due to another medical condition, other specified bipolar and related disorder, and unspecified bipolar and related disorder as classified by the Diagnostic and Statistical Manual of Mental Disorders—5th edition (DSM-5). Late-life bipolar disorders generally refer to the onset of disorder in patients older than 60 years, though the cutoff age can be variable. The following chapter outlines an overview of the various bipolar disorders including the diagnosis, assessment, and evidence-based treatment of the bipolar disorders. The construct of «mixed mood episode» has also garnered much attention in recent years, with research in the area affecting views on management. This chapter also contains two case studies which demonstrate the diagnostic and management challenges one may encounter in an older adult with bipolar disorder. The interplay of systemic medical complexities in this population with various mood symptoms certainly increases the challenge of treating bipolar disorder.

Heart rate complexity, derived from nonlinear heart rate variability (HRV), has been shown to help predict the outcomes of various diseases. Changes in heart rate complexity before and after paroxysmal atrial fibrillation (PAF) events are unclear. To evaluate changes in heart rate complexity through nonlinear HRV before and after PAF events. We enrolled 65 patients (72 ± 12.34 years old, 31 females) with 99 PAF events who received 24-hour Holter recording, and analyzed nonlinear HRV variables including Poincaré plot analysis, sample entropy (SampEn), and multiscale entropy (MSE). HRV analyses were applied to a 20-minute window before the onset and after the termination of PAF events. HRV parameters were evaluated and compared based on eight different 5-minute time segments, as we divided each 20-minute window into four segments of 5 minutes each. SampEn and MSE1~5 significantly decreased before the onset of PAF events, whereas SampEn, MSE1~5 and MSE6~20 significantly increased after the termination of PAF events. SD1 and SD2, which are nonlinear HRV parameters calculated via Poincaré plot analysis, did not significantly change before the PAF events, however they both decreased significantly after termination. Heart rate complexity significantly decreased before the initiation and increased after the termination of PAF events, which indicates the crucial role of nonlinear heart rate dynamics in the initiation and termination of PAF.

Early identification and treatment of young people at high risk of recurrent mood disorders: a feasibility study

Unemployment is a major problem in the world. It is very consistent problem all over the countries. The main purpose of this study is to know which factor is the main reason of unemployment. The analysis is based on the secondary data collected through authentic internet resources. The dataset is taken on annually basis from 1991 to 2020. The main demographic factors involved in this research are Gross Domestic Product (GDP), Foreign Direct Investment (FDI), Population Growth Rate (PGR) and Inflation. Multicollinearity analysis and outlier analysis is performed on all the factors included in the analysis. No multicollinearity issue is found in the analysis, while some outliers are observed in FDI. Due to outlier issue, the research is moved on to the robust regression analysis. Two strong factors are found for reduction of the unemployment rate such as PGR and FDI. The findings showed that the unemployment rate can be decreased by the increase in FDI and PGR. 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Patients with chronic heart failure (CHF) exhibit a morning surge in ventricular arrhythmias, but the underlying cause remains unknown. The aim of this study was to determine if heart rate dynamics, autonomic input (assessed by heart rate variability (HRV)) and nonlinear dynamics as well as their abnormal time-of-day-dependent oscillations in a newly developed arrhythmogenic canine heart failure model are associated with a morning surge in ventricular arrhythmias. CHF was induced in dogs by aortic insufficiency & aortic constriction, and assessed by echocardiography. Holter monitoring was performed to study time-of-day-dependent variation in ventricular arrhythmias (PVCs, VT), traditional HRV measures, and nonlinear dynamics (including detrended fluctuations analysis α1 and α2 (DFAα1 & DFAα2), correlation dimension (CD), and Shannon entropy (SE)) at baseline, as well as 240 days (240d) and 720 days (720d) following CHF induction. LV fractional shortening was decreased at both 240d and 720d. Both PVCs and VT increased with CHF duration and showed a morning rise (2.5-fold & 1.8-fold increase at 6 AM-noon vs midnight-6 AM) during CHF. The morning rise in HR at baseline was significantly attenuated by 52% with development of CHF (at both 240d & 720d). Morning rise in the ratio of low frequency to high frequency (LF/HF) HRV at baseline was markedly attenuated with CHF. DFAα1, DFAα2, CD and SE all decreased with CHF by 31, 17, 34 and 7%, respectively. Time-of-day-dependent variations in LF/HF, CD, DFA α1 and SE, observed at baseline, were lost during CHF. Thus in this new arrhythmogenic canine CHF model, attenuated morning HR rise, blunted autonomic oscillation, decreased cardiac chaos and complexity of heart rate, as well as aberrant time-of-day-dependent variations in many of these parameters were associated with a morning surge of ventricular arrhythmias.

In nonlinear error growth dynamics, the initial error cannot be accurately determined, and the forecast error, which is also uncertain, can be considered to be a random variable. Entropy in information theory is a natural measure of the uncertainty of a random variable associated with a probability distribution. This paper effectively combines statistical information theory and nonlinear error growth dynamics, and introduces some fundamental concepts of entropy in information theory for nonlinear error growth dynamics. Entropy based on nonlinear error can be divided into time entropy and space entropy, which are used to estimate the predictabilities of the whole dynamical system and each of its variables. This is not only applicable for investigating the dependence between any two variables of a multivariable system, but also for measuring the influence of each variable on the predictability of the whole system. Taking the Lorenz system as an example, the entropy of nonlinear error is applied to estimate predictability. The time and space entropies are used to investigate the spatial distribution of predictability of the whole Lorenz system. The results show that when moving around two chaotic attractors or near the edge of system space, a Lorenz system with lower sensitivity to the initial field behaves with higher predictability and a longer predictability limit. The example analysis of predictability of the Lorenz system demonstrates that the predictability estimated by the entropy of nonlinear error is feasible and effective, especially for estimation of predictability of the whole system. This provides a theoretical foundation for further work in estimating real atmospheric multivariable joint predictability.

Epidemiological research has shown those with bipolar disorders (BD) are more likely to work in creative professions. The current work is the first to examine ambition, exploration versus exploitation ratio, and insensitivity to effort/rewards among individuals with and without BD in an Asian cultural context. Writers and visual artists from Hong Kong who were diagnosed with BD completed a questionnaire to assess lifetime creative accomplishments, a self-rated measure of ambition, and two laboratory-based tasks: the observe-or-bet task to detect exploration versus exploitation tendencies, and an effort discounting task to measure sensitivity to effort required and reward level. The sample included 44 participants diagnosed with BD and 69 control participants, with 87 (77%) being female and an average age of 35.1 years (range: 18 to 65). Bayesian analyses found no group differences in creativity or related mechanisms between BD and control participants. However, decision tree algorithms revealed multivariate contributors to creative accomplishments. Replicating prior work, high ambition was key, with the most productive also willing to persevere despite high effort. Among lower-ambition individuals, control participants who engaged in balancing exploration versus exploitation had greater accomplishments. Importantly, there was no evidence that the effects of ambition or effort-based decision-making on creativity differed based on BD diagnosis. Bipolar group had lower socioeconomic status potentially impacting their self-rated creativity scores and creative potential. However, these findings remain tentative and await further investigation due to limited sample size. The findings suggest the mechanisms underlying creativity may not inherently differ for those with BD compared to controls. Ambition, especially when combined with effort and willingness, drives creative accomplishments. Strategic use of exploration versus exploitation was associated with greater creativity among less ambitious individuals without BD. A nuanced, multivariate approach is needed to understand the bipolar-creativity relationship across cultures. Study limitations included small sample size and over-representation of female participants.

Inflation has a significant impact on economic growth and monetary policy. In recent times, the US economy is facing the threat of high inflation, and the Federal Reserve has been continuously adopting interest rate hikes, which have an impact on the economy and finance. And the relationship between inflation and unemployment rate is a trade-off, so this article studies the impact of CPI and unemployment rate on the US economy. This artic le uses the US CPI and unemployment rate from 1948 to 2009 to construct a VAR model, predicts the final ten periods, and compares them with actual values. Using US CPI, unemployment rate, and GDP data from 1948 to 2009, construct a TVP-VAR model to analyze the impact of inflation and unemployment rate on economic growth.

he relationship between export and economic growth has been an important issue of discussion among scholars and economist throughout the world. The existence of nexus in between export and economic growth can be examined in several ways like growth rates relating to GDP and export, proportion of export to growth, several policies relating to accelerate economic growth and export etc. The effective way to explore nexus in export and economic growth would be the causal analysis between two variables. In the present paper, an attempt has been made to explore the relationship in between export and economic growth in Indian economy with the help of technique of causality and error correction mechanism. For this purpose, data relating to export and GDP for the period 1950-51 to 2001-02 have been taken into account. Data regarding GDP has been taken for the period 1950-51 to 2001-02 at current prices as well as at constant prices. Moreover, in order to examine causality in between export and economic growth, GDP and its components (at current and constant prices) as (1) NDP at factor cost, (2) GDP at market prices, (3) NDP at market prices, (4) GNP at factor cost, (5) NNP at factor cost, (6) GNP at market price, (7) NNP at market prices have been taken in the present study (Handbook of Statistics on Indian Economy, Economic Survey).

System dynamics perspectives and modeling opportunities for research in operations management

Many studies have been conducted to forecast and analyze the price of carbon in an emission trading scheme, also known as a cap-and-trade market. Exhaustive forecasting studies have been seldom (if ever) performed in the Western Climate Initiative (WCI) market. Because of the distinctive market dynamics in the WCI, the results of research on other markets may not be applicable to forecast the carbon price in this market. Moreover, there is a continuous debate about modelling the causality between driving forces (including energy prices, economic growth, weather, etc.) and carbon price. The objective of this paper is to forecast carbon price in the WCI market, by modelling the uncertainty of the driving forces and their causal relationship with carbon price. A probabilistic model is developed using Bayesian networks to infer the possible ranges of each driving force that could have an escalation/depreciation effect on price as well as the magnitude of this impact. The model is developed based on retrospective and prospective information on the selected driving forces in all the jurisdictions of the WCI market, providing the most probable price(s) over the period 2018–2030.

OPINION article Front. Comput. Neurosci., 09 April 2014 Volume 8 - 2014 | https://doi.org/10.3389/fncom.2014.00040

The present study aimed to compare the physiological responses of high-intensity race-pace continuous vs. interval workouts commonly used in middle-distance athletics, by means of analyzing post-exercise cardiac autonomic regulation and lactate. Nineteen highly-trained 800-m male runners were asked to run a 600-m race-pace continuous workout and a 2 × 4 × 200-m interval training, counterbalanced and randomized within one week of difference. Blood lactate jointly with linear and nonlinear heart rate dynamics were assessed during the immediate 15-min recovery. Age-category (Under23-Senior vs. Juvenile-Junior) was considered as an inter-subject factor. Peak lactate was higher following the interval training (15.51 ± 0.99 vs 13.83 ± 1.77 mmol L-1; P < 0.05) whereas lactate removal was almost nonexistent 15 min after both workouts (between 0 and 16%). Vagal modulation (ln RMSSD and lnRMSSD to RR ratio) remained significantly depressed at the end of recovery following both workouts, although the alteration was larger following the interval training. Detrended Fluctuation Analysis evidenced a more random HR behavior (DFA1 closer to 0.5) during the first 9 min of recovery after the interval training, whereas no significant change was observed in heart rate complexity (SampEn). Neither were differences found in post-exercise lactate and HR dynamics as a function of age-category. High-intensity workouts commonly used in middle-distance athletics, both race-pace continuous and intervallic approaches, induce a large depression of vagal modulation in highly trained runners, although interval trainings appear to induce even a greater alteration of both linear and nonlinear HR dynamics and a higher post-exercise peak lactate.