Measure Of Irregularity Research Articles

Abnormal brain entropy dynamics in ADHD

BackgroundBrain entropy (BEN) is a novel measure for irregularity and complexity of brain activities, which has been used to characterize abnormal brain activities in many brain disorders including attention-deficit/hyperactivity disorder (ADHD). While most research assumes BEN is stationary during scan sessions, the brain in resting state is also a highly dynamic system. The BEN dynamics in ADHD has not been explored. MethodsWe used a sliding window approach to derive the dynamical brain entropy (dBEN) from resting-state functional magnetic resonance imaging (rfMRI) dataset that includes 98 ADHD patients and 111 healthy controls (HCs). We identified 3 reoccurring BEN states. We tested whether the BEN dynamics differ between ADHD and HC, and whether they are associated with ADHD symptom severity. ResultsOne BEN states, characterized by low overall BEN and low within-state BEN located in SMN (sensorimotor network) and VN (visual network), its FW (fractional window) and MDT (mean dwell time) were increased in ADHD and positively correlated with ADHD severity; another state characterized by high overall BEN and low within-state BEN located in DMN (default mode network) and ECN (executive control network), its FW and MDT were decreased in ADHD and negatively correlated with ADHD severity. LimitationsThe window length of dBEN analysis can be further optimized to suit more datasets. The co-variation between dBEN and other dynamical brain metrics was not explored. ConclusionOur findings revealed abnormal BEN dynamics in ADHD, providing new insights into clinical diagnosis and neuropathology of ADHD.

Prediction interval soft sensor for dissolved oxygen content estimation in an electric arc furnace

In this study, a novel soft sensor modeling approach using Takagi–Sugeno (TS) fuzzy models and Prediction Intervals (PIs) is presented to quantify uncertainties in Electric Arc Furnace (EAF) steel production processes, namely to estimate the dissolved oxygen content in the steel bath. In real EAF operation, dissolved oxygen content is measured only a few times in the refining stage; therefore, the approach addresses the challenge of predicting unobserved output under conditions of irregular and scarce output measurements, using two distinct methods: Instant TS (I-TS) and Input Integration TS (II-TS). In the I-TS method, the model is computed for each individual indirect measurement, while the II-TS approach integrates these indirect measurements. The inclusion of PIs in TS models allows the derivation of the narrowest band containing a prescribed percentage of data, despite the presence of heteroscedastic noise. These PIs provide valuable insight into potential variability and allow decision-makers to evaluate worst-case scenarios. When evaluated against real EAF data, these methods were shown to effectively overcome the obstacles posed by scarce output measurements. Despite its simplicity, the I-TS model performed better in terms of interpretability and robustness to the operational reality of the EAF process. The II-TS model, on the other hand, showed excellent performance on all metrics but exhibited theoretical inconsistencies when deviating from typical operations. In addition, the proposed method successfully estimates carbon content in the steel bath using the established dissolved oxygen/carbon equilibrium, eliminating the need for direct carbon measurements. This shows the potential of the proposed methods to increase productivity and efficiency in the EAF steel industry.

Vibration separation method for permanent magnet guideway irregularity measurement

High-temperature superconducting (HTS) pinning maglev has the potential to achieve high operational speed while having a low maintenance cost, attracting a lot of attention. The HTS pinning maglev system realizes the levitation of the vehicle through the flux pinning characteristics between the high-temperature superconducting bulk and the magnetic field of the permanent magnet guideway (PMG). Thus, the profile of the magnetic field of the PMG can significantly affect the levitation status of the vehicle, which makes the PMG irregularity become one of the main excitation sources of the system. The magnetic induction intensity on the surface of the PMG can be used to characterize the PMG irregularity, but the non-contact dynamic measurement may produce large errors by the vibration of the measurement system during the process. In order to evaluate the PMG irregularity, the vibration component needs to be separated from the overall signal. In this paper, through the synchronous measurement of the Hall sensor and accelerometer, the vibration separation method of the PMG irregularity measurement is simplified to the optimal filter estimation. The particle swarm optimization (PSO) algorithm is used to calculate the parameters of the optimal filter based on the correlation coefficient criterion. The effectiveness of the proposed method is verified by the test. The separated signal is more accurate in both time domain and frequency domain for the characterization of PMG irregularity.

First climatology of F-region UHF echoes observed by the AMISR-14 system at the Jicamarca radio observatory and comparison with the climatology of VHF echoes observed by the collocated JULIA radar

Coherent backscatter radar observations made at the Jicamarca Radio Observatory (JRO) have contributed significantly to our understanding of equatorial F-region irregularities. Radar observations, however, have been made predominantly at the Very-High Frequency (VHF) band (50 MHz), which corresponds to measurements of 3-m field-aligned irregularities. The deployment of the 14-panel version of the Advanced Modular Incoherent Scatter Radar (AMISR-14) at Jicamarca provided an opportunity for observations of Ultra-High Frequency (UHF - 445 MHz) echoes which correspond to measurements of irregularities with 0.34 m scale sizes. Here, we present what we believe to be the first report describing the quiet-time climatology of sub-meter equatorial F-region irregularities derived from UHF radar measurements. The measurements were made between August 2021 and February 2023 using a 10-beam AMISR-14 mode that scanned the F-region in the magnetic equatorial plane. The results show how F-region sub-meter irregularities respond to variations in season and solar flux conditions. The results also confirm, experimentally, that the occurrence of UHF F-region echoes is controlled by the occurrence of equatorial spread F (ESF). Higher occurrence rates were observed during pre-midnight hours and during Equinox and December solstice. Reduced occurrence rates were observed during June solstice. The results show that an increase in solar flux was followed by an increase in the altitude where noticeable occurrence rates (≳ 10%) start and in the maximum altitude of these occurrence rates. The observations also show that occurrence rates lasted longer (in local time) during low solar flux conditions. Comparisons with collocated VHF radar observations showed that, despite differences in radar parameters, observation days, and the scale size (one order of magnitude) of the scattering irregularities, the two systems show similar climatological variations with only minor differences in the absolute occurrence rates. Finally, the analysis of the occurrence rates for different beams did not show substantial climatological variations over local (within a few 100s of km) zonal distances around JRO. We point out, however, that observations on a single day can show strong local variations in echo detection and intensity within the AMISR-14 field of view due to the intrinsic development and decay of ESF structures.

Quantitative Edge Analysis Can Differentiate Pancreatic Carcinoma from Normal Pancreatic Parenchyma.

This study aimed to introduce specific image feature analysis, focusing on pancreatic margins, and to provide a quantitative measure of edge irregularity, evidencing correlations with the presence/absence of pancreatic adenocarcinoma. We selected 50 patients (36 men, 14 women; mean age 63.7 years) who underwent Multi-detector computed tomography (MDCT) for the staging of pancreatic adenocarcinoma of the tail of the pancreas. Computer-assisted quantitative edge analysis was performed on the border fragments in MDCT images of neoplastic and healthy glandular parenchyma, from which we obtained the root mean square deviation SD of the actual border from the average boundary line. The SD values relative to healthy and neoplastic borders were compared using a paired t-test. A significant SD difference was observed between healthy and neoplastic borders. A threshold SD value was also found, enabling the differentiation of adenocarcinoma with 96% specificity and sensitivity. We introduced a quantitative measure of boundary irregularity, which correlates with the presence/absence of pancreatic adenocarcinoma. Quantitative edge analysis can be promptly performed on select border fragments in MDCT images, providing a useful supporting tool for diagnostics and a possible starting point for machine learning recognition based on lower-dimensional feature space.

Vibrational and Dissipative Characteristic Measurement of Solid-state Wave Gyroscope Resonators: Algorithms Based on the Identification of Free Oscillation Equations

The article describes the methodological basis for constructing computational circuits of different complexity degrees and different purposes for solving a wide range of industrial and laboratory problems to measure angular irregularity of vibrational-dissipative resonatorcharacteristics of integrating solid-state wave gyroscopes. The main method to solve such problems is the identification of the coefficients of the differential equations of quartz hemispherical resonator state in the mode of its free oscillations. The resonator oscillation equations both in the fixed measuring axes and in the moving axes of standing waves were chosen as the equations of state. After reduction to slow variables, only slowly changing amplitudeequations are left for identification problems. In all the described circuits, it is assumed that the information signals for the solved identification tasks are formed in a measuring device similar to the standard gyroscope device. These algorithms make it possible to measure the vibrational and dissipative characteristics of resonators with different degrees of completeness and directionality for different standard initial requirements to themeasurement accuracy and experimental modes, which makes it possible to reduce the measurement time and labor intensity of the established set of production control operations. Among the tasks to be solved for the free run-down mode of the resonator wave pattern are the following: angular irregularity measurement of the gyroscope resonator dissipative properties under conditions of low and significant residual frequency difference; angular non-uniformity measurement of gyroscope resonator vibrational properties (its different frequency); simultaneous measurement of resonator oscillatory and dissipative characteristics for fixed and special rotating gyroscope modes. The detailed processing of the computational schemes for the implementation of these algorithms is focused on their practical application for various tasks of production operational control. At the same time, the choice of the most suitable computational algorithm from the considered options depends on the conditions, requirements and specifics of measurements.

Optimizing time-in-target-range assessment for blood pressure: insights from a large-scale study with continual cuffless monitoring.

Blood pressure (BP) time-in-target-range (TTR) is an emerging predictor of cardiovascular risk. Conventional BP methods are fundamentally unable to provide an optimal assessment of TTR, using irregular measurements separated by lengthy intervals. We investigated the optimal duration and frequency for reliable, practical TTR assessment in clinical settings using continual monitoring. This retrospective study analyzed 2.3 million BP readings from 5,189 European home users (55 ± 11 years, 82% male, BMI 28.0 ± 5.8) using a cuffless BP monitor (Aktiia SA). Systolic BP (SBP) data over 15 consecutive days were assessed (29 ± 11 readings/subject/24-h; 434 + 132 readings/subject/15-day). Subjects were classified into risk-related TTR groups based on 15-day SBP data (24-h, target 90-125 mmHg; ≥6 daytime readings). Various measurement frequencies and durations (1-14 days; 24-h/daytime; 2, 4 or ≥ 6 readings/day) were compared to this reference. Two specific configurations paralleling ambulatory ("One-Day-24 h") and home ("One-Week-Daytime") BP monitoring were selected for detailed analysis. The reference TTR classified 63.0% of the subjects as high risk, 19.0% intermediate, and 18.0% low. "One-Day-24 h" schedule inaccurately classified 26% of subjects compared to the reference TTR, and "One-Week-Daytime" schedule inaccurately classified 45%. Classification accuracy with both schedules was high for subjects with very low or very high reference TTR, but poor otherwise. Accuracy of ≥90% in TTR classification only occurred with 7 days of continual 24-h monitoring. For the first time, with the benefit of a cuffless device that measures BP with sufficient frequency and duration, practical use of TTR is enabled as a potentially enhanced metric to manage hypertension.

Numerical investigation of nonlinear soil-structure interaction effects on response of irregular RC buildings

Kathmandu, located in a high seismic zone, predominantly features irregular structures among its building stock. These structures are particularly susceptible to severe damage during seismic events, primarily due to torsional effects. Traditional seismic designs rely particularly on fixed-base conditions that underestimate forces and displacement primarily on soft soil conditions leading to irrational design practices. This study aims to quantify the seismic performance of buildings on various base conditions through fully nonlinear Soil-structure Interaction (SSI). The soil nonlinear behaviour was modelled using the Pressure-Independ-Multi-Yield (PIMY) material with an octahedral shear stress-strain backbone curve. Three distinct soil types were considered, and structures with irregular plan configurations were modelled using finite elements in both Opensees and STKO platforms. Structural performance was analyzed through nonlinear dynamic analysis, and outputs were evaluated based on seismic parameters. Comparing nonlinear SSI with linear SSI and fixed-base conditions revealed a significant increase in structural response, expressed in terms of displacement, drift ratio, and base shear. The magnitude of diaphragm rotation was found to be influenced by a combination of building torsional irregularity and SSI effects. It is suggested that the conventional practice of using the torsional irregularity ratio as a measure of torsional irregularity be revised and enhanced to better account for these influences. It has been quantified that torsional irregularity has a relatively lesser impact on displacements, drifts, and base shear compared to SSI. In all cases, fixed-base conditions consistently exhibited the minimum response. The study explored that linear SSI and fixed-base conditions tend to underestimate structural responses, while nonlinear SSI coupled with dynamic analysis provides a more accurate representation of realistic structural behaviour for seismic design particularly in soft soil cases.

Individualized dynamic latent factor model for multi-resolutional data with application to mobile health

Summary Mobile health has emerged as a major success for tracking individual health status, due to the popularity and power of smartphones and wearable devices. This has also brought great challenges in handling heterogeneous, multi-resolution data that arise ubiquitously in mobile health due to irregular multivariate measurements collected from individuals. In this paper, we propose an individualized dynamic latent factor model for irregular multi-resolution time series data to interpolate unsampled measurements of time series with low resolution. One major advantage of the proposed method is the capability to integrate multiple irregular time series and multiple subjects by mapping the multi-resolution data to the latent space. In addition, the proposed individualized dynamic latent factor model is applicable to capturing heterogeneous longitudinal information through individualized dynamic latent factors. Our theory provides a bound on the integrated interpolation error and the convergence rate for B-spline approximation methods. Both the simulation studies and the application to smartwatch data demonstrate the superior performance of the proposed method compared to existing methods.

The brain entropy dynamics in resting state.

As a novel measure for irregularity and complexity of the spontaneous fluctuations of brain activities, brain entropy (BEN) has attracted much attention in resting-state functional magnetic resonance imaging (rs-fMRI) studies during the last decade. Previous studies have shown its associations with cognitive and mental functions. While most previous research assumes BEN is approximately stationary during scan sessions, the brain, even at its resting state, is a highly dynamic system. Such dynamics could be characterized by a series of reoccurring whole-brain patterns related to cognitive and mental processes. The present study aims to explore the time-varying feature of BEN and its potential links with general cognitive ability. We adopted a sliding window approach to derive the dynamical brain entropy (dBEN) of the whole-brain functional networks from the HCP (Human Connectome Project) rs-fMRI dataset that includes 812 young healthy adults. The dBEN was further clustered into 4 reoccurring BEN states by the k-means clustering method. The fraction window (FW) and mean dwell time (MDT) of one BEN state, characterized by the extremely low overall BEN, were found to be negatively correlated with general cognitive abilities (i.e., cognitive flexibility, inhibitory control, and processing speed). Another BEN state, characterized by intermediate overall BEN and low within-state BEN located in DMN, ECN, and part of SAN, its FW, and MDT were positively correlated with the above cognitive abilities. The results of our study advance our understanding of the underlying mechanism of BEN dynamics and provide a potential framework for future investigations in clinical populations.

Use of fractals in determining the malignancy degree of lung nodules.

A Computer-Assisted Detection (CAD) System for classification into malignant-benign classes using CT images is proposed. Two methods that use the fractal dimension (FD) as a measure of the lung nodule contour irregularities (Box counting and Power spectrum) were implemented. The LIDC-IDRI database was used for this study. Of these, 100 slices belonging to 100 patients were analyzed with both methods. The performance between both methods was similar with an accuracy higher than 90%. Little overlap was obtained between FD ranges for the different malignancy grades with both methods, being slightly better in Power spectrum. Box counting had one more false positive than Power spectrum. Both methods are able to establish a boundary between the high and low malignancy degree. To further validate these results and enhance the performance of the CAD system, additional studies will be necessary.

IGAMT: Privacy-Preserving Electronic Health Record Synthesization with Heterogeneity and Irregularity

Integrating electronic health records (EHR) into machine learning-driven clinical research and hospital applications is important, as it harnesses extensive and high-quality patient data to enhance outcome predictions and treatment personalization. Nonetheless, due to privacy and security concerns, the secondary purpose of EHR data is consistently governed and regulated, primarily for research intentions, thereby constraining researchers' access to EHR data. Generating synthetic EHR data with deep learning methods is a viable and promising approach to mitigate privacy concerns, offering not only a supplementary resource for downstream applications but also sidestepping the confidentiality risks associated with real patient data. While prior efforts have concentrated on EHR data synthesis, significant challenges persist in the domain of generating synthetic EHR data: balancing the heterogeneity of real EHR including temporal and non-temporal features, addressing the missing values and irregular measures, and ensuring the privacy of the real data used for model training. Existing works in this domain only focused on solving one or two aforementioned challenges. In this work, we propose IGAMT, an innovative framework to generate privacy-preserved synthetic EHR data that not only maintain high quality with heterogeneous features, missing values, and irregular measures but also balances the privacy-utility trade-off. Extensive experiments prove that IGAMT significantly outperforms baseline architectures in terms of visual resemblance and comparable performance in downstream applications. Ablation case studies also prove the effectiveness of the techniques applied in IGAMT.

Magnetic irregularity measurement and signal processing of permanent magnet guideway for superconducting pinning maglev train

Superconducting pinning maglev train, with the advantages of heavy self-stable levitation and super-low resistance, is expected to become a high-speed transit in the future. With the increase in speed, the more will the irregularity of the PMG (permanent magnet guideway) affects the safety and comfort of the superconducting pinning maglev train. This paper is based on the PMG of the test line for the first high-speed superconducting pinning maglev engineering prototype train in China, to measure and study the magnetic irregularity of the PMG and its characteristics. Experiments were designed to measure the irregularity with a single Dewar maglev system, which can obtain the equivalent geometric irregularity directly acting on the maglev unit of the vehicle. Firstly, the frequency response function is developed based on previous studies, which can transform the response signal of the Dewar into the irregularity signal of the PMG. Secondly, the velocity and position are measured by image recognition of ground markers. Then, the dynamic signal of the Dewar maglev system moving along the PMG is gained and conversed into equivalent geometric irregularities by the frequency response function. Finally, an equivalent geometric irregularity PSD (power spectral density) function is formed, and it can generate the geometrically random track irregularity for vehicle dynamic simulations. The dynamic simulation result suggests that the superconducting pinning maglev train has the potential for smooth operation at high-speed under the excitation of the current PMG. The studies of this paper can help to understand the irregularity of the PMG further, and the gained PSD function can provide a general reference for the dynamic study of the superconducting pinning maglev train.

Topological Properties of Polymeric Networks Modelled by Generalized Sierpiński Graphs

In this article, we compute the irregularity measures of generalized Sierpiński graphs and obtain some bounds on these irregularities. Moreover, we discuss some bounds on connectivity indices for generalized Sierpiński graphs of any arbitrary graph H along with classification of the extremal graphs used to attain them.

One-Year Results of a Phase I/II Randomized, Double-Masked, Placebo-Controlled Study of Processed Amniotic Fluid Drops After PRK.

The aim of this study was to evaluate the 1-year outcomes of using processed amniotic fluid (pAF) postoperatively after photorefractive keratectomy (PRK). Sixty-one participants were randomized to receive either placebo or pAF drops. The drops were instilled 4 times daily for 1 week after PRK along with routine postoperative medications. The primary outcome measures included uncorrected visual acuity, topographic corneal irregularity measurement, and surface staining over 1 year. A statistically significant difference in uncorrected distance visual acuity between the placebo and treatment groups was seen at 1 month post-PRK, with a visual advantage evident in the pAF group. A suggestive difference in corneal irregularity measurement was also seen between the placebo and treatment groups at 1 month postsurgery, with less irregularity noted in the pAF group. No differences in uncorrected distance visual acuity or corneal irregularity measurement were found at 3, 6, and 12 months. There was also no significant difference in corneal staining scores between the 2 groups at any of the measured time points. This 1-year study evaluating the safety and efficacy of pAF as an additional postoperative topical medication after PRK demonstrated that pAF offered a mild visual advantage at 1 month post-PRK. There were no late adverse events, and the intervention proved safe at 1 year.

International migration and illegal costs: Evidence from Africa-to-Europe smuggling routes

The 2011 Arab Spring marked the opening of the Central Mediterranean Route for irregular border crossings between Libya and Italy, which produced heterogeneous reductions of bilateral smuggling distances between country pairs in the Mediterranean region. We exploit this source of spatial and temporal variation in bilateral distance along land and sea routes to estimate the elasticity of irregular migration intentions for African and Near East countries. We estimate an elasticity of migration intentions to smuggling distances exceeding −3, mainly driven by countries with weak rule of law and high internet penetration. Our findings are consistent across irregular migration measures both at the aggregate and individual levels. We show that irregular migration elasticity is higher for youth, relatively skilled individuals and those with an informative advantage (having a social network abroad or a mobile phone).

On the stability of the principal ratio

The principal ratio of a connected graph G, γ(G), is the ratio between the largest and smallest coordinates of the principal eigenvector of the adjacency matrix of G. Over all connected graphs on n vertices, γ(G) ranges from 1 to ncn. Moreover, γ(G)=1 if and only if G is regular. This indicates that γ(G) can be viewed as an irregularity measure of G, as first suggested by Cioabă and Gregory (El. J. Lin. Alg. 2007). We are interested in how stable this measure is. In particular, we ask how γ changes when there is a small modification to a regular graph G. We show that this ratio is polynomially bounded if we remove an edge belonging to a cycle of bounded length in G, while the ratio can jump from 1 to exponential if we join a pair of vertices at distance 2. We study the connection between the spectral gap of a regular graph and the stability of its principal ratio. A naive bound shows that given a constant multiplicative spectral gap and bounded degree, the ratio remains polynomially bounded if we add or delete an edge. Using results from matrix perturbation theory, we show that given an additive spectral gap greater than (2+ϵ)n, the ratio stays bounded after adding or deleting an edge.

Atrial fibrillation organisation correlates with ventricular response regularity in patients with persistent atrial fibrillation

Abstract Background Atrial fibrillation (AF) is characterised by an irregularly irregular ventricular rhythm. However, the mechanisms by which the regularity of ventricular response is influenced by AF dynamics is yet to be understood. In AF, there is a spectrum of organisation of atrial electrical activity; from organised AF sustained by focal drivers through to disorganised AF sustained by multiple wavelet re-entry. We aimed to investigate whether the ventricular response in AF was associated with the organisation of atrial electrical activity, with the hypothesis that AF organisation correlates with ventricular response regularity. Methods We retrospectively reviewed data from 239 patients with persistent AF undergoing pulmonary vein isolation (PVI). In each patient both before and after ablation, AF organisation and measures of ventricular variability and irregularity were evaluated in 50s segments. Shannon entropy (ShEn) and Sample entropy (SampEn) derived from coronary sinus (CS) atrial electrograms were used to assess AF organisation. RR interval (RRI) metrics derived from the surface ECG were used to determine ventricular variability and irregularity. RRI variability was evaluated using the time-domain measures: normalised mean RRI difference, standard deviation of RRIs (SD RRI), normalised SD RRI, root mean square of successive RRI differences (rMSSD) and percentage of successive RR intervals that differ from each other by more than 50ms (pNN50). RRI irregularity was measured using SampEn and normalised SampEn. Results A significant decrease in atrial ShEn and SampEn was observed following PVI across all CS channels (e.g. SampEn CS 3-4: pre-ablation=0.907±0.512 vs post-ablation=0.790±0.447, p<0.0001). Both ShEn and SampEn from CS atrial electrograms were significantly correlated with the RRI variability and irregularity measures from surface ECG (pNN50, normalised mean RRI difference, normalised SD RRI and normalised SampEn) both pre- and post-ablation (pNN50: r=0.0771, p=0.00838, Figure 1; normalised mean RRI difference: r=0.144, p<0.0001; normalised SD RRI: r=0.175, p<0.0001; normalised SampEn: r=0.168, p<0.0001; correlations with SampEn CS 3-4 pre-ablation shown). Conclusion The reduction in atrial ShEn and SampEn following PVI suggests that an increase in AF organisation occurs with PVI. The significant correlations between atrial entropy and measures of RRI variability and irregularity suggest that AF organisation impacts ventricular response regularity. Therefore, interpretation of the RRI variability and irregularity from the surface ECG may give some insight, non-invasively, into the level of AF organisation.Figure 1

Irregular object measurement method based on improved adaptive slicing method

Irregular object measurement method based on improved adaptive slicing method

On the In Situ Observations of Irregularities During Rocket Flights From Thumba for Different Geophysical Conditions and the Associated Causative Mechanisms

AbstractElectron density and Neutral Wind (ENWi) probe and/or Langmuir probe were flown on three different rocket flights from equatorial station Thumba (8.5°N, 77°E), during daytime, eclipse time, and post sunset time respectively, of low solar activity period, to study ionization irregularities in the E region of the ionosphere. The spectral characteristics observed using the payloads were analyzed during the three different rocket flights. The 15 January 2010 solar eclipse event and “SOUREX 1” wind and electron density measurements confirm the validity of the wind shear theory for equatorial regions during the eclipse and post sunset periods, when electrojet is weak, using wind and electron density irregularity measurements from the same instrument (ENWi) for the first time. The spectral indices in the range of −1.2 to −1.78 and the strong wind shear due to gravity wave winds during the eclipse time as well as the post sunset time, confirm the role of neutral turbulence in the generation of irregularities in the 95–112 km altitude region. The spectral index of −2.0 to −2.7 and the presence of irregularities in the negative gradient regions establishes the role of wind‐driven gradient drift instability (GDI) in generating irregularities during the SOUREX 1 post sunset flight for altitudes below 93 km. Further, the role of gradient drift instability in triggering ionization irregularities during the daytime on 14 January 2010 is unraveled by the spectral index of −2.03 and the presence of irregularities in the positive gradient regions alone.