OBJECTIVE: Airway glottic insufficiency, or glottal gap, may lead to a breathy voice quality. It is hypothesized that a glottal gap may be a source of nonlinearity in speech production. This study aims to gain a chaotic and acoustic profile of glottal gap voice provided by phonation of excised larynges subjected to the insertion of a metal shim in the posterior glottis.
METHODS: Nonrandomized quasi-experimental study.
METHODS: Posterior glottal gap varied from 0 to 3.5 mm in 0.5 mm intervals. Each treatment was investigated independently in a sample population of eight excised canine larynges. Phonation of the larynges for each treatment was recorded and analyzed for the cepstral peak prominence (CPP), harmonics-to-noise ratio (HNR), and correlation dimension.
RESULTS: Kruskal-Wallis rank-sum tests yielded significant differences across shim groups for all parameters. Dunn-Bonferroni post-hoc tests revealed that the control group differed significantly from the 1.5, 2, 2.5, 3, and 3.5 mm groups for all metrics. Moreover, Kendall correlation tests indicated a moderately positive correlation between glottal gap size and correlation dimension, a moderately negative correlation between glottal gap size and CPP and between glottal gap size and the HNR.
CONCLUSIONS: Glottic insufficiency provides a source of nonlinearity in phonation. Nonlinear dynamic analysis provides quantitative insight into glottal gap voice. This study encourages future studies to further evaluate the relationship between glottal gap and correlation dimension.

Sea surface temperature (SST), with its complex and dynamic behavior, is a major driver of ocean-atmosphere interactions. The purpose of this study is to investigate the behavior of SST and its prediction using a chaotic approach. Average mutual information (AMI) and Cao methods were used to reconstruct the phase space. The Lyapunov exponent and correlation dimension were used to investigate chaos. The Lyapunov exponent index was used to predict SST with a 5-year average prediction horizon using the local prediction method between 2023 and 2027. The results showed a 3-month delay time for the Pacific and Antarctic Oceans, and a 2-month delay time for the Atlantic, Indian, and Arctic Oceans. The optimal embedding dimension for all oceans is between 6 and 7. Our analysis reveals that the dynamics of SST in all oceans exhibit varying degrees of chaos, as indicated by the correlation dimension. The local prediction method achieves relatively accurate short-term SST predictions due to the clustering of SST points around specific attractors in the phase space. However, in the long term, the accuracy of this method decreases as the points in the phase space of SST can spread randomly. The model performance ranking with a Percent Mean Relative Absolute Error shows that the Indian Ocean has the best performance compared to other oceans, while the Atlantic, Pacific, and Antarctic and Arctic Oceans are in the next ranks. This study contributes to understanding the dynamics of SST and has practical value for use in the development of climate models.

There are numerous types of cognitive tasks classified as mental tracking (MT), working memory (WM), reaction time (RT), discrimination and decision-making and verbal fluency (VF). However, limited studies have investigated the effects of cognitive task type on postural control in older adults.
s: The aim of this study was to investigate the effect of aging and several types of cognitive tasks on postural control in terms of nonlinear analysis.
Postural control was investigated under 6 conditions (single task and dual-task with RT; easy and difficult VF; easy and difficult WM; easy and difficult MT. Outcome measurements were the max Lyapunov, entropy, and correlation dimension at anteroposterior (AP) and mediolateral (ML) directions.
The results revealed that within the older group, the AP & ML max Lyapunov at dual-task with difficult WM and MT was significantly higher than all other conditions. In addition, the older group had lower AP entropy at dual-task with easy VF, difficult WM, and easy as well as difficult MT.
The results can be useful to understand the postural control mechanisms and to detect the alterations following aging and applying different types of cognitive tasks. In addition, the investigated parameters can be a basis for identifying postural control deficiencies.

UNASSIGNED: It is proved that there are differences between gait performed by females and males, which appear in movements of selected body parts. Despite numerous state-of-the-art studies related to the discriminative analysis of motion capture data, the question of whether measures of signal complexity and uncertainty can extract valuable features for the problem of sex distinction still remains open. It is the subject of the paper.
UNASSIGNED: Correlation dimension, as well as approximate and sample entropies, are selected to describe motion data. In the numerical experiments, the collected dataset with 884 samples of 25 females and 30 males was used. The measurements took place in the Human Motion Laboratory (HML), equipped with a highly precise motion capture system. Two variants of data representation were investigated-time series that contain joint rotations of taken skeleton model as well as positions of the markers attached to the human body. Finally, a comparative analysis between the populations of females and males using descriptive statistics, non-parametric estimation, and statistical hypotheses verification was carried out.
UNASSIGNED: There are statistically significant sex differences extracted by the taken measures. In general, the movements of lower limbs result in greater values of correlation dimension and entropies for females, while selected upper body parts play a similar role for males. The dissimilarities are mainly observed in hip, ankle, shoulder, and head movements.
UNASSIGNED: Correlation dimension and entropy measures provide robust and explainable features of motion capture data with a valuable description of the human locomotion system. Thus, beyond the importance of discovered differences between females and males, their interpretation and understanding are also known.

The paper presents a method for analysing the pressure signal at the compressor outlet, which allows to detect when the machine operating point approaches the area where a stall is about to occur. The signal analysis method is based on nonlinear feature extraction from the dynamic signal. The correlation dimension (dcorr) is used to quantify the complexity of the measured signal, its value decreasing if the analysed signal originates from deterministic processes. The results presented indicate that the correlation dimension of the signal decreases at flow rates approximately 10% above the flow rate at which negative effects on machine performance occur. This trend has been observed across multiple rotor speeds. These findings suggest that the perturbations associated with the onset of the stall can propagate to the compressor outlet, leading to less chaotic pressure behaviour that reflects the dynamics of these perturbations. The fact that stall can be identified from the pressure signal in the space between the rotor and the diffuser in its early stages is well known, but the possibility of identifying stall at the compressor outlet, where the perturbations are significantly attenuated, has not been documented in the literature.

Few studies have evaluated the effect of a secondary motor task on the standing posture based on nonlinear analysis. However, it is helpful to extract information related to the complexity, stability, and adaptability to the environment of the human postural system. This study aimed to analyze the effect of two motor tasks with different difficulty levels in motor performance complexity on the static standing posture in healthy young adults. Thirty-five healthy participants (23.08 ± 3.92 years) performed a postural single task (ST: keep a quiet standing posture) and two motor dual tasks (DT). i.e., mot-DT(A)—perform the ST while performing simultaneously an easy motor task (taking a smartphone out of a bag, bringing it to the ear, and putting it back in the bag)—and mot-DT(T)—perform the ST while performing a concurrent difficult motor task (typing on the smartphone keyboard). The approximate entropy (ApEn), Lyapunov exponent (LyE), correlation dimension (CoDim), and fractal dimension (detrending fluctuation analysis, DFA) for the mediolateral (ML) and anterior-posterior (AP) center-of-pressure (CoP) displacement were measured with a force plate while performing the tasks. A significant difference was found between the two motor dual tasks in ApEn, DFA, and CoDim-AP (p < 0.05). For the ML CoP direction, all nonlinear variables in the study were significantly different (p < 0.05) between ST and mot-DT(T), showing impairment in postural control during mot-DT(T) compared to ST. Differences were found across ST and mot-DT(A) in ApEn-AP and DFA (p < 0.05). The mot-DT(T) was associated with less effectiveness in postural control, a lower number of degrees of freedom, less complexity and adaptability of the dynamic system than the postural single task and the mot-DT(A).

Neurodegenerative diseases are caused by progressive degeneration of the central nervous system (CNS)\'s neuronal structure. Well-known diseases in this category include Alzheimer\'s disease (AD), Parkinson\'s disease (PD), and multiple sclerosis (MS), which are also addressed in this study. The CNS appears to be a complex dynamic system, whose parameters change during the disease due to neuronal damage, resulting in various symptoms. Since the change in dynamic behavior is due to the neurons\' death and change in neurons\' connectivity, brain images of the affected areas appear to provide a good understanding of this change. This work attempts to focus on brain magnetic resonance images (MRI) and examine the effect of neuronal loss on the images. To this end, the complex features of these images, including 2D and Higuchi\'s fractal dimensions (HFD), correlation dimension (CD), largest Lyapunov exponent (LLE), and approximate entropy (ApEn) were calculated. Despite small differences in numerical values (0.01-0.35), these values differ significantly. This shows that the brain dynamic system behaves and functions differently in the disease state, which is clear in the behavior of global features. These three diseases have the same functional pattern, and this study seems to have captured the roots of these seemingly variant diseases.

We investigated the relationship between the mechanical degrees of freedom (DoF) and its postural dynamics. The joint DoF was fixed to constrain the mechanical DoF. Nine participants were required to perform a single-leg stance task. The center of pressure trajectory data was analyzed. Ankle fixation induced a larger amount of variability in the anteroposterior direction, and less dimensionality and complexity in the mediolateral direction. These results suggest that the ankle joint fixation caused limited postural sway in the mediolateral direction; therefore, functional DoF and complexity decreased. In contrast, it increased the amount of postural sway variability in the anteroposterior direction. Our findings imply a direct relationship between the mechanical DoF of the human movement system and its postural dynamics.

Here we discuss the current perspectives of comprehensive heart rate variability (HRV) analysis in electrocardiogram (ECG) signals as a non-invasive and reliable measure to assess autonomic function in sleep-related breathing disorders (SDB). It is a tool of increasing interest as different facets of HRV can be implemented to screen and diagnose SDB, monitor treatment efficacy, and prognose adverse cardiovascular outcomes in patients with sleep apnea. In this context, the technical aspects, pathophysiological features, and clinical applications of HRV are discussed to explore its usefulness in better understanding SDB.

The issue of monitoring and early warning of rock instability has received increasing critical attention in the study of rock engineering. To investigate the damage evolution process of granite under triaxial compression tests, acoustic emission (AE) tests were performed simultaneously. This study firstly introduced two novel parameters, i.e., the coefficient of variation (CoV) of the information entropy and correlation dimension of the amplitude data from the AE tests, to identify the precursor of the failure of granite. Then the relationship between the changes in these parameters and the stress-time curve was compared and analyzed. The results of this study show that: (1) There is a strong correlation between the CoV of the information entropy and the failure process of granite. The granite failed when the CoV curve raised to a plateau, which could be used as an indicator of rock instability. (2) The fluctuation of the correlation dimension indicates the different stages during the loading process, i.e., the initial compaction stage, the linear elastic stage, the yield stage, and the failure stage. Each stage contains a descending and a rising process in the correlation dimension curve, and the exhibited starting point or the bottom point at the correlation dimension curve could be selected as the indicator point for the rock instability. (3) The combined analysis of the Information entropy and Correlation dimension can improve the accuracy of rock instability prediction. This study provides new insights into the prediction of rock instability, which has theoretical implications for the stability of subsurface engineering rock masses.