Increase In Kurtosis Research Articles

Assessment of arousal recovery after cardiac arrest using diffusion kurtosis MRI with higher b-values: a pilot study

ABSTRACT Objective Comatose survivors of cardiac arrest (CA) pose a complex challenge for physicians reliant on imperfect studies to determine the extent of neurologic injury. Clinically available imaging is frequently relied upon despite limited sensitivity. We conducted a prospective pilot study comparing diffusion kurtosis imaging (DKI)-MRI and somatosensory evoked potentials (SSEPs) in comatose survivors of CA to investigate the benefit of utilizing higher diffusion b-values to enhance prediction of arousal recovery. Methods Survivors of CA admitted from June 2015 through November 2019 with DKI-MRI and SSEPs were evaluated. Advanced diffusion metrics differentiating present or absent SSEPs were analyzed using whole-brain voxelwise nonparametric permutation inference with threshold-free cluster enhancement. Results Twenty survivors of CA were included, mean age 52, 45% female and out-of-hospital arrests accounting for 75% of cases. Baseline characteristics and examination findings were not statistically different between groups at admission or 48 h after achieving normothermia. A decrease in mean diffusivity (MD) and increase in mean kurtosis (MK) was demonstrated in subjects without arousal recovery potential, most prominently in the posterior mesial temporal, parietal and occipital lobes. Conclusion DKI-MRI may improve early arousal recovery prediction during the immediate phase of post-CA care, especially where SSEPs are unavailable or unreliable.

Simultaneous Increase of Mean Susceptibility and Mean Kurtosis in the Substantia Nigra as an MRI Neuroimaging Biomarker for Early-Stage Parkinson's Disease: A Systematic Review and Meta-Analysis.

Parkinson's disease (PD) is the second most common neurodegenerative disorder. Early detection is crucial for treatment and slowing disease progression. Simultaneous alterations in mean susceptibility (MS) from quantitative susceptibility mapping (QSM) and mean kurtosis (MK) from diffusion kurtosis imaging (DKI) can serve as reliable neuroimaging biomarkers for early-stage PD (ESPD) in the basal ganglia nuclei, including the substantia nigra (SN), putamen (PUT), globus pallidus (GP), and caudate nucleus (CN). Systematic review and meta-analysis. One hundred eleven patients diagnosed with ESPD and 81 healthy controls (HCs) were included from four studies that utilized both QSM and DKI in both subject groups. Three-dimensional multi-echo gradient echo sequence for QSM and spin echo planar imaging sequence for DKI at 3 Tesla. A systematic review and meta-analysis using PRISMA guidelines searched PubMed, Web of Science, and Scopus. Random-effects model, standardized mean difference (SMD) to compare MS and MK between ESPD patients and HCs, I2 statistic for heterogeneity, Newcastle-Ottawa Scale (NOS) for risk of bias, and Egger's test for publication bias. A P-value <0.05 was considered significant. MS values were significantly higher in SN (SMD 0.72, 95% CI 0.31 to 1.12), PUT (SMD 0.68, 95% CI 0.29 to 1.07), and GP (SMD 0.53, 95% CI 0.19 to 0.87) in ESPD patients compared to HCs. CN did not show a significant difference in MS values (P = 0.15). MK values were significantly higher only in SN (SMD = 0.72, 95% CI 0.16 to 1.27). MK values were not significantly different in PUT (P = 1.00), GP (P = 0.97), and CN (P = 0.59). Studies had high quality (NOS 7-8) and no publication bias (P = 0.967). Simultaneous use of MS and MK may be useful as an early neuroimaging biomarker for ESPD detection and its differentiation from HCs, with significant differences observed in the SN. 2 TECHNICAL EFFICACY: Stage 2.

Effect of turbulent integral scale on non-Gaussian characteristics of surface wind pressure on square cylinder

This study investigated the statistical properties of the pressure fluctuations on a square cylinder across three distinct turbulence fields characterized by varying turbulent integral scales. The effect of turbulent integral scale on the non-Gaussian characteristics and extreme surface wind pressure acting on square cylinders beneath the separating flow were studied in detail. The findings indicated that the pressure distribution on the windward surface generally conformed to a Gaussian distribution, whereas notable non-Gaussian characteristics were observed in the pressure distribution on the side and leeward surfaces. The fluctuating pressure, skewness, kurtosis, peak factor, and extreme pressure increase with an increasing ratio of turbulent integral scale to structural depth (Lux/D), whereas the mean pressure remains unaffected by variations in Lux/D. As Lux increased, the energy of the internal vortices in the shear layer also increased. As a result, the non-Gaussian features of the pressure caused by vortex breakdown become more pronounced. Compared with Lux/D = 1.96, the underestimated value of the extreme pressure on the square cylinder had a maximum difference of up to 15.4% at Lux/D = 0.53. Therefore, the corresponding turbulent integral scale should be accurately simulated when measuring wind loading on a structure through wind tunnel tests.

Non-integrable soliton gas: The Schamel equation framework

Soliton gas or soliton turbulence is a subject of intense studies due to its great importance to optics, hydrodynamics, electricity, chemistry, biology and plasma physics. Usually, this term is used for integrable models where solitons interact elastically. However, soliton turbulence can also be a part of non-integrable dynamics, where long-lasting solutions in the form of almost solitons may exist. In the present paper, the complex dynamics of ensembles of solitary waves is studied within the Schamel equation using direct numerical simulations. Some important statistical characteristics (distribution functions, moments, etc.) are calculated numerically for unipolar and bipolar soliton gases. Comparison of results with integrable Korteweg–de Vries (KdV) and modified KdV (mKdV) models are given qualitatively. Our results agree well with the predictions of the KdV equation in the case of unipolar solitons. However, in the bipolar case, we observed a notable departure from the mKdV model, particularly in the behavior of kurtosis. The observed increase in kurtosis signifies the amplification of distribution function tails, which, in turn, corresponds to the presence of high-amplitude waves.

Investigation of critical factors influencing the underestimation of hearing loss predicted by the ISO 1999 predicting model.

To analyze factors influencing the underestimation of noise-induced permanent threshold shift (NIPTS) among manufacturing workers, providing baseline data for revising noise exposure standard. A cross-sectional study was designed with 2702 noise-exposed workers from 35 enterprises from 10 industries. Personal noise exposure level(LAeq,8h) and noise kurtosis level were determined by a noise dosimeter. Questionnaires and hearing loss tests were performed for each subject. The predicted NIPTS was calculated using the ISO 1999:2013 model for each participant, and the actual measured NIPTS was corrected for age and sex. The factors influencing the underestimation of NIPTS were investigated. The predicted NIPTS at each test frequency (0.5, 1, 2, 3, 4, or 6kHz) and mean NIPTS at 2, 3, 4, and 6kHz (NIPTS2346) using the ISO 1999:2013 model were significantly lower than their corresponding measured NIPTS, respectively (P < 0.001). The ISO model significantly underestimated the NIPTS2346 by 12.36 dB HL. The multiple linear regression analysis showed that noise exposure level, exposure duration, age, and kurtosis could affect the degree of underestimation of NIPTS2346. The generalized additive model (GAM) with (penalized) spline components showed nonlinear relationships between critical factors (age, exposure duration, noise level, and kurtosis) and the underestimated NIPTS2346.The underestimated NIPTS2346 decreased with an increase in exposure duration (especially over ten years). There was no apparent trend in the underestimated NIPTS2346 with age. The underestimated NIPTS2346 decreased with the increased noise level [especially > 90 dB(A)]. The underestimated NIPTS2346 increased with an increase in noise kurtosis after adjusting for the noise exposure level and exposure duration and ultimately exhibiting a linear regression relationship. The ISO 1999 predicting model significantly underestimated the noise-induced hearing loss among manufacturing workers. The degree of underestimation became more significant at the noise exposure condition of fewer than ten years, less than 90 dB(A), and higher kurtosis levels. It is necessary to apply kurtosis to adjust the underestimation of hearing loss and consider the applying condition of noise energy metrics when using the ISO predicting model.

Can minimum toe clearance predict community-based trips by older adults?

BackgroundTripping is the leading cause of falls by older adults. While tripping theoretically occurs when minimum toe clearance (MTC) is insufficient to avoid an unseen obstacle, the relationship between MTC and community-based trips is unknown. Research questionTo what extent do MTC and its variability predict the number of community-based trips during gait by older adults? Method51 older adults with normal or obese body mass index walked across an 8 m walkway. For each step, we identified MTC as the local minimum of the vertical trajectory of a toe marker during the swing phase. We calculated the across-steps mean, median, interquartile range, and standard deviation for MTC, and skewness and kurtosis of the distribution of all MTC values for an individual. Every two weeks for one year, participants reported on community-based trips. A series of negative binomial regressions were used to predict the number of trips over obstacles (with or without a fall) based on MTC measures. Results28 participants experienced at least one trip, with 14 experiencing two or more. In the absence of any covariates, only kurtosis and skewness significantly predicted the incidence rate of trips. However, neither remained significant after accounting for fall history. The model that included kurtosis and fall history predicted trips better than one with fall history alone, with the incidence rate of trips decreasing by 35% for every unit increase in kurtosis (incidence rate ratio of 0.64 with 95% confidence interval: 0.38 – 1.08; p = 0.09) SignificanceWhile MTC has the potential to provide insight into older adults more likely to trip over obstacles in the community, assessing MTC during level-ground walking within a lab environment may lack ecological validity to strongly describe the risk of community-based trips above and beyond fall history.

Intravoxel Incoherent Motion (IVIM) Magnetic Resonance Imaging (MRI) for Assessment of Treatment Response in Pancreatic Cancer

Intravoxel Incoherent Motion (IVIM) Magnetic Resonance Imaging (MRI) is an emergent technique used to quantify diffusion and perfusion without the use of contrast agent. Our objective was to evaluate changes in IVIM parameters pre- and post-Radiation Therapy (RT) / chemotherapy in Pancreatic Ductal Adenocarcinoma (PDAC) patients to correlate these parameters and their changes with tumor radiation response. Pre- and post-treatment IVIM scans were acquired from 12 patients (median age: 70 [41-83]) with PDAC treated with RT (median: 98 [39-116] Gy BED) and chemotherapy. CA19-9 was used as a surrogate of radiation response and its validity was confirmed using the Kaplan-Meier method and the log-rank test. The Diffusion Weighted Images (DWI) were acquired on a 3T MRI scanner using a free-breathing, spin echo-based echo-planar imaging (SE-EPI) sequence with six b-values (0, 30, 60, 100, 600, 1000 s/mm2). Tumors were segmented using Dynamic Contrast Enhanced (DCE) MRI and registered to the DWI images. A voxel-wise, bi-exponential, IVIM model was fitted to the DWI images to derive the perfusion fraction (f), diffusion coefficient (D), and pseudo-diffusion coefficient (D*) distributions inside the tumor. IVIM parameter distributions were described using histogram analysis by extracting the median, standard deviation, skew, kurtosis, and percentiles (5, 10, 25, 75, 90, 95). Statistical comparisons between pre- and post-RT images were performed using the nonparametric permutation test for small sample sizes. Kaplan-Meier analysis of pre- and post-RT showed significantly reduced survival (p = 0.04) in patients who had a CA19-9 increase (n = 6) compared to those who decreased or stayed the same (n = 6). The median f showed a significant increase (p = 0.03) in patients who experienced a decrease in CA19-9 while D showed a significant decrease (p = 0.03). Among the calculated histogram percentiles, both the 5th and 10th percentile in the f distribution showed a near-significant increase (p = 0.06) when CA19-9 decreased while the 95th of the D distribution showed a near-significant decrease (p = 0.06). In patients who experienced an increase in CA19-9, a near-significant change (p = 0.06) in the skew (decrease) and kurtosis (increase) of the f distribution was observed. D* showed no significant correlations across all testing. Both f and D exhibited significant changes in PDAC patients undergoing RT and chemotherapy, reflecting changes in tumor response to treatment. The findings warrant further investigation to utilize IVIM in characterizing treatment response in PDAC patients.

Evolution and Statistical Analysis of Internal Random Wave Fields within the Benjamin–Ono Equation

This study investigates the numerical evolution of an initially internal random wave field characterized by a Gaussian spectrum shape using the Benjamin–Ono (BO) equation. The research focuses on analyzing various properties associated with the random wave field, including the transition to a steady state of the spectra, statistical moments, and the distribution functions of wave amplitudes. Numerical simulations are conducted across different Ursell parameters, revealing intriguing findings. Notably, it is observed that the spectra of the wave field converge to a stationary state in a statistical sense, while exhibiting statistical characteristics that deviate from a Gaussian distribution. Moreover, as the Ursell parameter increases, the positive skewness of the wave field intensifies, and the kurtosis increases. The investigation also involves the computation of the probability of rogue wave formation, revealing deviations from the Rayleigh distribution. Notably, the study uncovers distinct types of internal rogue waves, specifically referred to as the “two sisters” and “three sisters” phenomena.

Risk perception or hazard perception? Examining misperceptions of miners' personal exposures to noise.

While perceptions of risk have been examined in the workplace to understand safety behavior, hazard perception has been overlooked, particularly for chemical, physical, and biological agents. This study sought to establish the prevalence of one type of mismatch in hazard perception, - noise misperception - among miners, to examine whether different types of noisy environments (e.g., continuous, highly variable, etc.) alter workers' misperception of their noise exposures, and to evaluate whether noise misperception is associated with hearing protection device (HPD) use behavior. In this cross-sectional study across 10 surface mines in the USA, 135 normal-hearing participants were surveyed on their perceptions of exposure to noise at work and were monitored for three shifts, each with personal noise dosimetry, to examine which workers had a mismatch in perceived versus true noise exposure by 8-hr, time-weighted average, NIOSH exposure limits (TWANIOSH). Mixed effects logistic regression and probit Bayesian Kernel Machine Regression (BKMR) models examining on the odds of noise misperception associated with four different noise metrics (kurtosis, crest factor, variability, and number of peaks >135dB) were used to determine which types of noisy environments may influence noise misperception. The relationship between noise misperception and odds of not wearing HPDs during a work shift was further examined. Our findings showed that nearly 1 in 3 workers underestimated their exposure to noise when their true exposure was in fact hazardous (TWANIOSH≥85 dBA) for at least one shift, and 6% misperceived hazardous exposures for all shifts. Work shifts with highly kurtotic noise distributions (>3) had 3.1 (95% CI: 1.1 to 8.4) times significantly higher odds of resulting in misperceived noise; no other noise metric was significantly associated with noise misperception. BKMR modeling provided further evidence that kurtosis dominates this relationship, with an IQR increase in kurtosis significantly associated with 1.68 (95% CI: 1.13 to 2.50) higher odds of noise misperception. Although not statistically significant, misperception of hazardous noise exposure was associated with 3.2 (95% CI: 0.8 to 12.5) times higher odds of not using earplugs during a work shift. Misperception of noise occurs in the workplace, and likely occurs for other physical, chemical, and biological exposures. This hazard misperception may influence risk perceptions and worker behavior and reduce the effectiveness of behavior-related training. Elimination, substitution, or engineering controls of exposures is the best way to prevent hazard misperceptions and exposure-related diseases.

Influence of gadolinium, field-strength and sequence type on quantified perfusion values in phase-resolved functional lung MRI.

The purpose of this study is to evaluate the influences of gadolinium-based contrast agents, field-strength and different sequences on perfusion quantification in Phase-Resolved Functional Lung (PREFUL) MRI. Four cohorts of different subjects were imaged to analyze influences on the quantified perfusion maps: 1) at baseline and after 2 weeks to obtain the reproducibility (26 COPD patients), 2) before and after the administration of gadobutrol (11 COPD, 2 PAH and 1 asthma), 3) at 1.5T and 3T (12 healthy, 4 CF), and 4) with different acquisition sequences spoiled gradient echo (SPGR) and balanced steady-state free precession (bSSFP) (11 COPD, 7 healthy). Wilcoxon-signed rank test, Bland-Altman plots, voxelwise Pearson correlations, normalized histogram analyses with skewness and kurtosis and two-sample Kolmogorov-Smirnov tests were performed. P value ≤ 0.05 was considered statistically significant. In all cohorts, linear correlations of the perfusion values were significant with correlation coefficients of at least 0.7 considering the entire lung (P<0.01). The reproducibility cohort revealed stable results with a similar distribution. In the gadolinium cohort, the quantified perfusion increased significantly (P<0.01), and no significant change was detected in the histogram analysis. In the field-strength cohort, no significant change of the quantified perfusion was shown, but a significant increase of skewness and kurtosis at 3T (P = 0.01). In the sequence cohort, the quantified perfusion decreased significantly in the bSSFP sequence (P<0.01) together with a significant decrease of skewness and kurtosis (P = 0.02). The field-strength and sequence cohorts had differing probability distribution in the two-sample Kolmogorov-Smirnov tests. We observed a high susceptibility of perfusion quantification to gadolinium, field-strength or MRI sequence leading to distortion and deviation of the perfusion values. Future multicenter studies should strictly adhere to the identical study protocols to generate comparable results.

Large-field-of-view scanning electron microscopy of the paraventricular nucleus of the hypothalamus during diet-induced obesity.

Dysregulation in the paraventricular nucleus of the hypothalamus (PVN) is associated with a variety of diseases including those related to obesity. Although most investigations have focused on molecular changes, structural alterations in PVN neurons can reveal underlying functional disruptions. Although electron microscopy (EM) can provide nanometer resolution of brain structures, an inherent limitation of traditional transmission EM is the single field of view nature of data collection. To overcome this, we used large-field-of-view high-resolution backscatter scanning electron microscopy (bSEM) of the PVN. By stitching high-resolution bSEM images, taken from normal chow and high-fat diet mice, we achieved interactive, zoomable maps that allow for low-magnification screening of the entire PVN and high-resolution analyses of ultrastructure at the level of the smallest cellular organelle. Using this approach, quantitative analysis across the PVN revealed marked electron-dense regions within neuronal nucleoplasm following high-fat diet feeding, with an increase in kurtosis, indicative of a shift away from a normal distribution. Furthermore, measures of skewness indicated a shift toward darker clustered electron-dense regions, potentially indicative of heterochromatin clusters. We further demonstrate the utility to map out healthy and altered neurons throughout the PVN and the ability to remotely perform bSEM imaging in situations that require social distancing, such as the COVID-19 pandemic. Collectively, these findings present an approach that allows for the precise placement of PVN cells within an overall structural and functional map of the PVN. Moreover, they suggest that obesity may disrupt PVN neuronal chromatin structure.NEW & NOTEWORTHY Paraventricular nucleus of the hypothalamus (PVN) alterations are linked to obesity-related conditions, but limited knowledge exists about neuroanatomical changes in this region. A large-field-of-view backscatter scanning electron microscopy (bSEM) method was used, which allowed the identification of up to 40 PVN neurons in individual samples. During obesity in mice, bSEM revealed changes in PVN neuronal nucleoplasm, possibly indicating chromatin clustering. This microscopy advancement offers valuable insights into neuroanatomy in both healthy and disease conditions.

Higher Dose Noninvasive Transcutaneous Auricular Vagus Nerve Stimulation Increases Feeding Volumes and White Matter Microstructural Complexity in Open-Label Study of Infants Slated for Gastrostomy Tube

To determine whether transcutaneous auricular vagus nerve stimulation (taVNS) paired with twice daily bottle feeding increases the volume of oral feeds and white matter neuroplasticity in term-age-equivalent infants failing oral feeds and determined to need a gastrostomy tube. In this prospective, open-label study, 21 infants received taVNS paired with 2 bottle feeds for 2 - 3weeks (2x). We compared 1) increase oral feeding volumes with 2x taVNS and previously reported once daily taVNS (1x) to determine a dose response, 2) number of infants who attained full oral feeding volumes, and 3) diffusional kurtosis imaging and magnetic resonance spectroscopy before and after treatment by paired t tests. All 2x taVNS treated infants significantly increased their feeding volumes compared with 10days before treatment. Over 50% of 2x taVNS infants achieved full oral feeds but in a shorter time than 1x cohort (median 7 days [2x], 12.5days [1x], P<.05). Infants attaining full oral feeds showed greater increase in radial kurtosis in the right corticospinal tract at the cerebellar peduncle and external capsule. Notably, 75% of infants of diabetic mothers failed full oral feeds, and their glutathione concentrations in the basal ganglia, a measure of central nervous system oxidative stress, were significantly associated with feeding outcome. In infants with feeding difficulty, increasing the number of daily taVNS-paired feeding sessions to twice-daily significantly accelerates response time but not the overall response rate of treatment. taVNS was associated with white matter motor tract plasticity in infants able to attain full oral feeds. Clinicaltrials.gov (NCT04643808).

Spatial Wave Measurement Based on U-net Convolutional Neural Network in Large Wave Flume

This study proposed a spatial wave measurement method based on a U-net convolutional neural network. First, frame images are extracted from a video collected by a physical model experiment, and a dataset of spatial wave measurements is created and extended using a data enhancement method. A U-net convolutional neural network is built to extract the spatial wave information of the images; evidently, the segmented water level is close to that of the original image. Next, the U-net convolutional neural network is compared with the sensor, pixel recognition, and Canny edge detection methods. Pixel recognition results reveal that the maximum and minimum errors of the U-net convolutional neural network are 3.92% and 1.05%, those of the Canny edge detection are 5.97% and 1.33%, and those of the sensor are 11.8% and 1.6%, respectively. Finally, the nonlinear characteristic quantities of waves are measured using the proposed U-net convolutional neural network. The kurtosis and asymmetry calculated in the spatial domain are slightly larger than those calculated in the time domain, whereas the skewness calculated in the spatial domain is smaller than that calculated in the time domain. The asymmetry and kurtosis increase with an increase in wave height and period, whereas the skewness increases with an increase in wave height but decreases with an increase in period.

Experimental Analysis of Frictional Performance of EN AW-2024-T3 Alclad Aluminium Alloy Sheet Metals in Sheet Metal Forming

Friction occurring in the area of contact between the sheet metal and the tool in sheet metal forming is one of the factors determining the quality of the surface of the drawpiece and the formability of the workpiece. Knowledge of the friction conditions allows the optimal forming conditions to be determined in terms of lubrication and applied pressures. The article presents the results of experimental studies of friction in EN AW-2024-T3 Alclad sheets using a special device simulating the sheet–tool contact in the blank-holder area during SMF. The friction tests were carried out at various pressures, under dry friction, and with the use of typical oils with a wide range of viscosity. The effect of the friction process parameters on the COF and surface roughness parameters Rsk and Rku was analysed using analysis of variance. The model F-values imply that the regression models for all the output parameters were significant. A monotonic decrease in the COF with an increase in the mean contact pressure and lubricant viscosity was observed for both dry and lubricated conditions. DELVAC 1340 engine oil with the highest viscosity significantly lowered the COF. The lubrication efficiency with LAN46 machine oil and LVH22 hydraulic oil showed an upward trend with an increasing mean contact pressure. In general, friction reduces the value of average roughness, Ra, and skewness, Rsk. Meanwhile, friction under contact pressures in the analysed range (4.4–11.7 MPa) causes an increase in kurtosis, Rku.

Dynamic response of monopile-supported wind turbines considering non-Gaussian characteristics of wind inflow

Available wind turbine design standards usually assume that the inflow wind field is a smooth Gaussian process, but the in-situ measured data show that the inflow wind presents a certain degree of non-Gaussian characteristics. This study investigates the dynamic response of the supporting structure of the wind turbine under both Gaussian and non-Gaussian wind fields. The Mises stress at the tower base and the mudline of the monopile are considered. Through the global maxima method and the average conditional exceedance rate method, the extreme value response of the turbine under a given mean recurrence interval is obtained. The results indicate that by taking the non-Gaussian characteristics of wind fields into account, the short-term extreme values are generally larger than those under Gaussian wind fields. For the long-term extreme values of the stress at the two critical points, the influence of kurtosis is significantly greater than the skewness. Meanwhile, the long-term stress extreme value also increases with the increase of kurtosis. The non-Gaussian characteristic of the wind field has a particular influence on the safe operation of the wind turbine and should be considered when designing wind turbines.

Brain microstructure abnormalities in the 3xTg-AD mouse – A diffusion MRI and morphology correlation study

The widely studied triple transgenic (3xTg-AD) mouse provides a robust model of Alzheimer's disease (AD) with region dependent patterns of progressive amyloid-β (Aß) and tau pathology. Using diffusion MRI (dMRI), we investigated the sensitivity of dMRI measures in capturing AD pathology associated microstructure alterations in older 3xTg-AD mice, and the degree to which dMRI changes correlate with measurements of Aβ and tau pathology. 3xTg-AD and normal control (NC) mice, 15 to 21 months of age, were used in this study. In vivo dMRI data were acquired for the generation of diffusion tensor (DT) and diffusional kurtosis (DK) measures within the hippocampus and fimbria (Fi). For these same brain regions, Aβ and tau pathology were quantified by morphological analysis of Aß1–42 and AT8 immunoreactivity. Two-tailed, two-sample t-tests were performed to assess group differences in each brain region of interest (ROI), with the Benjamini-Hochberg false discovery rate (FDR) method being applied to adjust for multiple comparisons. Spearman correlation coefficients were calculated to investigate associations between diffusion and morphological measures. Our results revealed, depending on the brain region, DT and DK measures were able to detect group differences. In the dorsal hippocampus (HD), fractional anisotropy (FA) was significantly higher in the 3xTg-AD mice compared with NC mice. In the subiculum (SUB), FA, axial diffusivity (D||) and radial kurtosis (K┴) were significantly higher in 3xTg-AD mice compared with NC mice. Morphological quantification of Aß1–42 and AT8 immunoreactivity showed elevated Aß and tau in the Fi, ventral hippocampus (HV) and SUB of 3xTg-AD mice. The presence of Aβ and tau was significantly correlated with several DT and DK measures, particularly in the SUB, where an increase in tau correlated with an increase in mean kurtosis (MK) and K┴. This work demonstrates significant dMRI differences between older 3xTg-AD and NC mice in the hippocampus and Fi. Significant correlations were found between dMRI and morphological measures of Aβ and tau pathology. These results support the potential of dMRI-derived parameters as biomarkers of AD pathology. Since the imaging methods employed here are easily translatable to clinical MRI, our results are also relevant for human AD patients.

Dynamics diagnosis of the COVID-19 deaths using the Pearson diagram

The pandemic COVID-19 brings with it the need for studies and tools to help those in charge make decisions. Working with classical time series methods such as ARIMA and SARIMA has shown promising results in the first studies of COVID-19. We advance in this branch by proposing a risk factor map induced by the well-known Pearson diagram based on multivariate kurtosis and skewness measures to analyze the dynamics of deaths from COVID-19. In particular, we combine bootstrap for time series with SARIMA modeling in a new paradigm to construct a map on which one can analyze the dynamics of a set of time series. The proposed map allows a risk analysis of multiple countries in the four different periods of the pandemic COVID-19 in 55 countries. Our empirical evidence suggests a direct relationship between the multivariate skewness and kurtosis. We observe that the multivariate kurtosis increase leads to the rise of the multivariate skewness. Our findings reveal that the countries with high risk from the behavior of the number of deaths tend to have pronounced skewness and kurtosis values.

Machine learning based method of correcting nonlinear local Lyapunov vectors ensemble forecasting

In this study, the feasibility and effectiveness of machine learning algorithm to improve ensemble forecasts using nonlinear local Lyapunov vectors (NLLVs) are explored preliminarily based on the Lorenz96 model. The results show that the machine learning model (Ens-ML) based on the ridge regression algorithm and the results of NLLV ensemble forecasting can effectively improve the overall forecasting skill. The Ens-ML outperforms the ensemble-averaged forecasting (EnsAve) and control forecasts (Ctrl) as well as the machine learning model based on Ctrl results (Ctrl-ML). It is also found that the improvement of forecasting skill depends on the total number of ensemble members used in the Ens-ML model, i.e. the increase of the number of ensemble members is conducive to the improvement of forecasting skill and to the decrease of overfitting in the early stage. By comparing the performances among different experimental cases, we find that the experimental forecasting errors of Ens-ML, Ctrl-ML and EnsAve are gradually smaller than that of Ctrl as the forecasting time increases. The attractors forecasted by Ens-ML, Ctrl-ML and EnsAve are also analyzed. Their attractor probability distributions show a contraction of the value domain, an increase in kurtosis and a convergence to the mean, especially for Ens-ML.

Research on the statistical characteristic of freak waves based on observed wave data

Freak waves are characterized by high wave, great destructive power, abrupt behavior, and a significant threat to offshore structures. In this study, the observed wave data of multiple sea areas are utilized, the relation between the occurrence of freak waves at real sea states and the statistical characteristics of wave trains are investigated, and the probable reasons for freak wave generation at real sea conditions is explored. It can be found that for the wave trains with higher kurtosis, the occurrence probability of huge wave height is underestimated by the Rayleigh distribution. It can be accurately predicted by the MER distribution and GC distribution. Generally, the occurrence probability of freak wave increases linearly with the increase of kurtosis from the statistical results, and the MER model is capable of describing the relation between occurrence probability of freak wave and kurtosis. Moreover, the generation types of freak waves are analyzed based on the wavelet energy spectrum and time process of wave surface for typical freak waves in the observation data. Freak waves at real sea states are attributed to the modulation instability and wave energy superposition.

Differential diagnostics of the presence of damage by the method of digital polarization mapping of microsocopy images of hystological sections of human organs

The article presents the results of experimental testing of methods of azimuthal-invariant polarization mapping of microscopic images of samples of histological sections of the myocardium and lung tissue; time monitoring of changes in the magnitude of statistical moments of the 1-4th orders, characterizing the distributions of the azimuth and ellipticity of polarization of microscopic images of myocardial and lung tissue samples with different age of damage; determination of the diagnostic efficiency (time interval and accuracy) of establishing the age of damage to human internal organs by digital histological methods of mapping azimuth maps and polarization ellipticity of microscopic images.&#x0D; Aim of the work. Development of a digital histology technique for samples of human internal organs.&#x0D; Materials and methods. The object of the study was the histology of samples of human internal organs (myocardium, lung tissue) with different duration of damage from 1 hour to 120 hours. For control, we used BT samples from those who died from coronary artery disease with different duration of damage from 1 hour to 120 hours. The studies were carried out using the method of digital polarization mapping of microscopic images of histological sections of biological tissues of human internal organs.&#x0D; Results. Revealed the following ranges ramp variation quantity statistics polarizing digital histology and accuracy of the limitation of damage: a. Arts azimuth polarization microscopic image of a magnification ×40 (asymmetry – 12 hours, kurtosis – 12 hours, accuracy – 55-60 min), maps of ellipticity of polarization of microscopic images with a magnification of ×40 (asymmetry – 12 hours, kurtosis – 12 hours, accuracy – 65-75 min).&#x0D; Conclusions. Scenarios of changes in the statistical structure of maps of azimuth and ellipticity of polarization of microscopic images of histological sections of human internal organs have been determined - with an increase in the duration of damage, the value of the mean and variance decreases, the asymmetry and kurtosis increase.