Analysis Of Variability Research Articles

Arthroscopic Assessment of Temporomandibular Joint Pathologies—Is It Possible for Non-Specialists in Arthroscopy? Analysis of Variability and Reliability of Dental Students’ Ratings after a Comprehensive One-Semester Introduction

Background: Arthroscopy of the temporomandibular joint (TMJ) plays a long-established role in the diagnostics and therapy of patients suffering from arthrogenic temporomandibular disorders (TMDs), which do not respond adequately to conservative/non-invasive therapy. However, the interpretation of arthroscopic findings remains challenging. This study investigates the reliability and variability of assessing arthroscopic views of pathologies in patients with TMDs by non-specialists in arthroscopy and whether a standardized assessment tool may improve correctness. Methods: Following a comprehensive one-semester lecture, dental students in the clinical stage of education were asked to rate 25 arthroscopic views (freeze images and corresponding video clips) regarding the severity of synovitis, adhesions, and degenerative changes on a scale of 0–10 (T1). The results were compared to ratings stated by two European-board-qualified academic OMF surgeons. In a second round (T2), the students were asked to repeat the ratings using a 10-point rating scheme. Results: With regard to all three subcategories, congruency with the surgeons’ results at T1 was at a low level (p < 0.05 in 19/75 cases) and even decreased at T2 after the implementation of the TMDs-SevS (p < 0.05 in 38/75 cases). For both T1 and T2, therefore, the inter-rater agreement was at a low level, showing only a slight agreement for all three subcategories (Fleiss’ Kappa (κ) between 0.014 and 0.099). Conclusions: The judgement of the arthroscopic pathologies of the TMJ remains an area of temporomandibular surgery that requires wide experience and training in TMDs to achieve expertise in TMJ arthroscopic assessments, which cannot be transferred by theoretical instruction alone.

Long-Term Stimulation of the Left Dorsal Branch of the Thoracic Nerve Improves Ventricular Electrical Remodeling in a Canine Model of Chronic Myocardial Infarction.

To evaluate the ventricular electrophysiologic effects of long-term stimulation of the left dorsal branch of thoracic nerve (LDTN) derived from the left stellate ganglion (LSG) in a canine model of chronic myocardial infarction (MI). Seventeen adult male beagles were randomly divided into three groups: the sham group (sham operated, n = 6), the MI group (n = 6), and the MI + LDTN group (MI plus LDTN stimulation, n = 5). The canine model of chronic MI was induced by the occlusion of the left anterior descending artery (LADO). The LDTN was separated and intermittently stimulated immediately after LADO for 2months. The heart rate variability (HRV) analysis, in vivo electrophysiology, the evaluation of LSG function and neural activity, histological staining, and western blotting (WB) assay were performed to evaluate the effect of LDTN stimulation on the heart. The canine MI model was successfully established by LADO, and the LDTN was separated and stimulated immediately after LADO. The HRV analysis showed that LDTN stimulation reversed the increased LF value and LF/HF ratio of the MI group. LDTN stimulation prolonged the shortening ERP and APD90, decreased the dispersion of ERP and APD90, and increased the VFT. Additionally, LDTN stimulation inhibits the LSG function and neural activity. Furthermore, LDTN stimulation suppressed the activation of Wnt/β-catenin signaling, which contributed to the LSG neuronal apoptosis by upregulation of pro-apoptotic Bax and downregulation of anti-apoptotic Bcl-2. LDTN stimulation could attenuate cardiac sympathetic remodeling and improve ventricular electrical remodeling, which may be mediated by suppressing the activated Wnt/β-catenin signaling pathway and then promoting the LSG neuronal apoptosis.

Phenotypes of COVID-19-associated dysautonomia in patients requiring veno-venous extracorporeal membrane oxygenation

Background. Patients with novel coronavirus infection (COVID-19) receiving veno-venous extracorporeal membrane oxygenation (VV-ECMO) are typically prone to hemodynamic disorders of various severity. Tachycardia, increased cardiac output, or arterial hypotension affect the effectiveness of VV-ECMO. One of the possible causes of hemodynamic disorders leading to ineffective VV-ECMO may be dysautonomia (DA), which refers to an imbalance of sympathetic and parasympathetic divisions of the autonomic nervous system (ANS). The development of DA in various critical conditions was described previously. Dysautonomia also develops in COVID-19 (COVID-19-associated DA), but it was studied only in stable non-ICU patients. The presented study focuses on COVID-19-associated DA in critical COVID-19 patients requiring VV-ECMO support. The study was aimed at determining COVID-19-associated DA phenotypes, their impact on VV-ECMO effectiveness and disease outcomes. Materials and methods. The study included 20 patients: 12 (60%) females, 8 (40%) males. The patients had an average age of 55 years. All the patients underwent 24-hour Holter monitoring with spectral analysis of heart rate variability (HRV) assessing low-frequency component of the spectrum (LF), the high-frequency component of the spectrum (HF), the LF/HF ratio on days 1, 3, and 5 of VV-ECMO. Diagnostic criteria for COVID-19-associated DA was a decrease in LF/HF 2.28 or an increase in LF/HF 6.94. The diagnostic criteria of predominant tone of sympathetic nervous system (sympathetic tone) was an increase in LF/HF 6.94, while a decrease in LF/HF 2.28 indicated predominant parasympathetic tone. Low sympathetic tone was determined by a decrease in LF 15%, and an increase in LF 40%. Low parasympathetic tone was determined by a decrease in HF 15%, and an increase in HF 25%. The criteria used were based on the results of previous studies. The following parameters were registered in the study population: VV-ECMO weaning, duration of respiratory and VV-ECMO support, length of stay in the intensive care unit (ICU) and in hospital, and disease outcomes. Results. COVID-19-associated DA was diagnosed in all the patients. LF/HF median value was 0.1. HRV spectrum parameters changed significantly over time: on day 5 of VV-ECMO support LF and HF values significantly decreased. The patients were divided into three groups according to the DA phenotype: group 1 (n = 4 [20%]) with normal sympathetic tone and high parasympathetic tone (nShP phenotype); group 2 (n = 14 [70%]) with low sympathetic tone and high parasympathetic tone (lShP phenotype); group 3 (n = 2 [10%]) with low sympathetic tone and normal parasympathetic tone (lSnP phenotype). The latter group was excluded from further statistical analysis due to the small sample size. In group 2, the mean HR was significantly higher compared with group 1. In group 1, VV-ECMO weaning was successful in 50% of cases, whereas in group 2 it was successful in 7.2% (p = 0.04). Conclusions. To determine a dysautonomia phenotype, it is necessary to continuously monitor DA status in COVID-19 patients during VV-ECMO. Tachycardia in COVID-19 patients during VV-ECMO does not exclude the ANS imbalance with a significant predominance of parasympathetic tone over the sympathetic tone. It is this COVID-19-associated DA phenotype that is significantly associated with the unfavorable outcomes.

Study on Genetic Variability for Forage Yield and Quality Traits in Forage Sorghum [Sorghum bicolor L. Moench

The initial research related to germplasm screening was carried out in the experimental area of Instructional Dairy Farm, GBPUAT Pantnagar during kharif season 2018. The experimental material for this experiment consisted of two hundreds and eighty diverse germplasm lines of sorghum along with six checks viz., SSG 59-3, Pant Chari- 5, Pant Chari- 6, CSV-21 F, CSH-22S, and CSV-24SS. The germplasm lines were evaluated in Augmented Block Design for nineteen forage yield related traits and thirteen quality traits. The statistical analysis for genetic variability was done using analysis of variance (ANOVA), heritability (h2), genotypic coefficient of variation (GCV), phenotypic coefficient of variation (PCV), and genetic advance (GA). The analysis of variance revealed that the genotypes and checks were showing a highly significant differences for all the traits under study indicated existence of inherent genetic differences among genotypes for different characters. Mean performance of forage yield and quality related traits exhibited a wide range of variability. GCV and PCV values were observed low for most of the characters whereas high for anthracnose, zonate leaf spot and shoot fly incidence. The value of genetic advance was observed high for leaf area, green fodder yield per plant, dry fodder yield per plant, hydrocyanic acid content, plant height, anthracnose, and shoot fly incidence were relatively more than other characters. Genetic advance as per cent of mean was observed low for days to maturity, dry matter per cent, in-vitro dry matter disappearance, neutral detergent fiber, acid detergent fiber, cellulose content whereas high for leaf area, flag leaf width, panicle length, panicle width, 1000-grains weight, grain yield per plant, green fodder yield per plant, dry fodder yield per plant, total soluble solids, silica content, anthracnose, zonate leaf spot and shoot fly incidence. Heritability values were found high for all the traits under study. The genotypes bearing the desired values for different genetic variability parameters and mean performance for can be exploited in future breeding programmes for the improving forage genotypes. These genotypes can be used as donor parents in crop improvement programme for improving forage yield and quality related traits along with improved resistance against anthracnose, shooty fly and zonate leaf spot.

Differences Between Resting State fMRI BOLD Variability and Default Mode Network Connectivity in Healthy Older and Younger Adults.

Resting state fMRI analyses have been used to examine functional connectivity in the aging brain. Recently, fluctuations in the fMRI BOLD signal have been used as a potential marker of integrity in neural systems. Despite its increasing popularity, the results of BOLD variability analyses and mean based functional connectivity analyses have rarely been compared. The current study examined fMRI BOLD signal variability and default mode network seed-based analyses in healthy older and younger adults to better understand the unique contributions of these methodological approaches. 34 healthy participants were separated into a younger adult group (age 25-35, n=17) and an older adult group (age 65+, n=17). For each participant, a map of the standard deviation of the BOLD signal (SDBOLD) was derived. Group comparisons examined differences in resting-state SDBOLD in younger versus older adults. Seed-based analyses were used to examine differences between younger and older adults in the default mode network. Between-group comparisons revealed significantly greater BOLD variability in widespread brain regions in older relative to younger adults. There were no significant differences between younger and older adults in the default mode network connectivity. The current findings align with an increasing number of studies reporting greater BOLD variability in older relative to younger adults. The current results also suggest that the traditional resting state examination methods may not detect nuanced age-related differences. Further large-scale studies in an adult lifespan sample are needed to better understand the functional relevance of the BOLD variability in normative aging.

Spatiotemporal variability identification and analysis for non-stationary climatic trends for a tropical river basin of India

The non-stationary behavior of climatic variables has been increasingly recognized as a challenge that disrupts the equilibrium of human-defined climate-based stationary processes, including hydrological and agricultural practices, and irrigation systems. This study aims to investigate long-term trends and non-stationarity in climatic variables across 23 stations of the Krishna River basin, India. Prominent trends in rainfall, temperature, and their extreme indices were identified using the Modified Mann-Kendall (MMK), Bootstrapped Mann-Kendall (BMK), and Sen's Slope Estimator tests, while the Innovative Trend Analysis (ITA) test uncovered hidden trends and potential shifts in climatic patterns. This study addresses a critical research gap by exploring both significant and hidden trends in climatic variables, providing a better understanding of future dynamics. Traditional methods like MMK and Sen's Slope were insufficient to reveal these hidden trends, but ITA offered a more comprehensive analysis. The findings revealed an increase in total annual rainfall for almost 50% of the basin, which aligns with rising maximum temperatures, suggesting enhanced evaporation rates and subsequent fluctuations in rainfall patterns. Seasonal analysis indicated a shift towards decreased rainfall during winter and pre-monsoon seasons, contrasted by increased precipitation during the monsoon and post-monsoon periods, highlighting a clear alteration in rainfall distribution. The Simple Daily Intensity Index (SDII) and other indices suggest intensified rainfall events despite a decrease in the number of rainy days, indicating fewer but more intense events. Temperature analysis showed an overall increase in maximum temperatures, with the Diurnal Temperature Range (DTR) significantly increasing across all stations, implying greater daily temperature variations and potential for intensified water cycles and extreme climatic events. Furthermore, the study simplifies these trends by classifying them into two attributes: intensity and frequency, aiding policymakers in site-specific management of water resources and planning for future climatic scenarios. The presence of non-stationarity in extreme rainfall was confirmed by the Augmented Dickey-Fuller (ADF), Phillips-Perron (PP), and Kwiatkowski-Phillips-Schmidt-Shin (KPSS) tests. These findings are significant as they conclude how climate change is altering hydrological patterns at each station. The study emphasizes the necessity for adaptive management strategies to mitigate the adverse impacts on agriculture, infrastructure, and human safety.

Genetic variability, association and diversity analysis of yield and its component traits in rice (Oryza sativa) germplasm

An experiment was conducted during winter (rabi) season of 2022 at ICAR-Indian Institute of Rice Research, Hyderabad, Telangana to evaluate extent of genetic variability, heritability, diversity and the relationship between yield and its component traits in a collection of 60 rice germplasm accessions. Results showed that germplasm accessions exhibited ample genetic variability and diversity for yield traits. Based on per se performance, inter crosses between the genotypes IC458483 with high grain yield, IC210775 with more panicle length, IC75919 with high 100-grain weight, IC75980 with more productive tillers and IC75965 with high protein content could produce positive transgressive segregants for improving respective traits. Plant height, total and effective tillers, grain yield and 100-grain weight traits which exhibited the highest heritability and genetic advance could be vital for selection in hybridization programmes. Crossing among genotypes of diverse clusters specifically VI, VII and VIII is suggested as this could create a broad variation useful for selecting genotypes with both high yield and long panicles.

Derivative Method to Detect Sleep and Awake States through Heart Rate Variability Analysis Using Machine Learning Algorithms

Sleep disorders can have harmful consequences in both the short and long term. They can lead to attention deficits, as well as cardiac, neurological and behavioral repercussions. One of the most widely used methods for assessing sleep disorders is polysomnography (PSG). A major challenge associated with this method is all the cables needed to connect the recording devices, making the examination more intrusive and usually requiring a clinical environment. This can have potential consequences on the test results and their accuracy. One simple way to assess the state of the central nervous system (CNS), a well-known indicator of sleep disorder, could be the use of a portable medical device. With this in mind, we implemented a simple model using both the RR interval (RRI) and its second derivative to accurately predict the awake and napping states of a subject using a feature classification model. For training and validation, we used a database providing measurements from nine healthy young adults (six men and three women), in which heart rate variability (HRV) associated with light-on, light-off, sleep onset and sleep offset events. Results show that using a 30 min RRI time series window suffices for this lightweight model to accurately predict whether the patient was awake or napping.

Variability Analysis in Judo Para Athletes With Visual Impairments: Match-Outcome Performance in the Tokyo 2020 Paralympic Games With Evidence From the New Classification System.

Match-related performance analysis in judo Para athletes with visual impairments is important to coaches and staff to identify technical-tactical profiles of their athletes and opponents but also to identify whether there are similar characteristics in each visual class. Thus, this study explores the match-related performance in judo Para athletes and verifies the relationship between performance using the old and new classification systems. The match-derived variables were analyzed using different statistical methods considering a total of 182 matches from the Tokyo 2020 Paralympic Games. The results indicated that performance was affected by sex and degree of impairment. The new classification system seems suitable for grouping Para judo athletes, as it differentiates performance between the two proposed classes (J1 and J2), since athletes from each group compete separately. Furthermore, different variability index measures were correlated with competitive performance, demonstrating a specific performance profile for each sport class in judo.

Tamanhos de parcelas e amostras para variáveis biométricas em mudas de alface

ABSTRACT: In order to ensure reliable inferences in scientific experiments, sampling criteria should be determined and defined during the experimental design phase. Determining plot and sample sizes without scientific criteria could result in resource and labor inefficiencies with no gain in experimental precision. In this work we estimate plot and sample sizes for biometric variable analyses in lettuce seedlings. The seedlings were sown in four expanded polystyrene foam transplant trays with 128 and 200 cells. Foliar area, stem diameter, shoot height, root length, root volume, root area, fresh and dry shoot and root masses. The methods described by Paranaiba (PARANAIBA et al., 2009) and Cochran (COCHRAN, 1977) were used for plot size and sample size estimations, respectively. Sample size varied according to the variables analysed and transplant tray cell number. Root variables required the highest number of samples. For a 10% margin of error, 12 seedlings were necessary for evaluations in a 128 cell tray, while 11 seedlings were required for analysis in 200 cell trays.

More efficient adaptation of cardiovascular response to repeated restraint in spontaneously hypertensive rats: the role of autonomic nervous system.

We hypothesized that sympathetic hyperactivity and parasympathetic insuficiency in spontaneously hypertensive rats (SHR) underlie their exaggerated cardiovascular response to acute stress and impaired adaptation to repeated restraint stress exposure compared to Wistar-Kyoto rats (WKY). Cardiovascular responses to single (120 min) or repeated (daily 120 min for 1 week) restraint were measured by radiotelemetry and autonomic balance was evaluated by power spectral analysis of systolic blood pressure variability (SBPV) and heart rate variability (HRV). Baroreflex sensitivity (BRS) was measured by the pharmacological Oxford technique. Stress-induced pressor response and vascular sympathetic activity (low-frequency component of SBPV) were enhanced in SHR subjected to single restraint compared to WKY, whereas stress-induced tachycardia was similar in both strains. SHR exhibited attenuated cardiac parasympathetic activity (high-frequency component of HRV) and blunted BRS compared to WKY. Repeated restraint did not affect the stress-induced increase in blood pressure. However, cardiovascular response during the post-stress recovery period of the 7th restraint was reduced in both strains. The repeatedly restrained SHR showed lower basal heart rate during the dark (active) phase and slightly decreased basal blood pressure during the light phase compared to stress-naive SHR. SHR subjected to repeated restraint also exhibited attenuated stress-induced tachycardia, augmented cardiac parasympathetic activity, attenuated vascular sympathetic activity and improved BRS during the last seventh restraint compared to single-stressed SHR. Thus, SHR exhibited enhanced cardiovascular and sympathetic responsiveness to novel stressor exposure (single restraint) compared to WKY. Unexpectedly, the adaptation of cardiovascular and autonomic responses to repeated restraint was more effective in SHR.

Ensemble Variability Properties of Active Galactic Nuclei in the SDSS DR17

We present the results from a study of ∼9600 broadline-selected active galactic nuclei (AGNs) with host galaxies detected from the Sloan Digital Sky Survey (SDSS) Data Release 17. We compute ensemble variability statistics based on a comparison of the original SDSS photometric data with spectrophotometric measurements obtained days to decades later in the Sloan g, r, and i bands. Galaxy and AGN templates have been fitted to the SDSS spectra to isolate the AGN component from the host galaxy. The sources have absolute magnitudes in the range −24 < M i < −18 and lie at redshifts less than z ∼ 0.9. A variability analysis reveals that the anticorrelation between luminosity and variability amplitude continues down to log(Lbol [erg s−1]) = 43.5, demonstrating that the relationship extends by 4 orders of magnitude in AGN luminosity. To further explore the connection between AGN luminosity and variability, we determine the black hole mass and the accretion rate through measurement of the Hβ line width and the monochromatic luminosity at rest frame 5100 Å. Our results suggest that the accretion rate is the dominant parameter impacting the amplitude of variability and that the anticorrelation between the accretion rate and amplitude extends to rates as low as 1% Eddington. Moreover, we also identify an anticorrelation between the variability amplitude and black hole mass, with the correlation appearing strongest among the AGNs with low accretion rates.

Agreement between Ultra-Short-Term and Standard Heart Rate Variability Analysis in Resting and Post-Exercise Conditions

Background: Short-term (5 min) heart rate variability (HRV) analysis is widely used in assessing autonomic nervous system activity during exercise. While shortening the HRV measurement duration can help improve its application efficiency, its accuracy needs to be verified. This study investigated the agreement between ultra-short-term (UST) HRV (3 or 4 min) and standard 5 min HRV and explored the optimal recording duration under resting and post-exercise conditions. Methods: Fourteen participants exercised on a cycle ergometer at 60% of their maximum peak power. Data were collected during the rest condition (Pre-E) and three post-exercise conditions (Post-E1, Post-E2, and Post-E3), with indicators of the standard deviation (SDNN) of the ultra-short and short-term RR intervals and the root mean square (RMSSD) of the continuous difference between RR intervals. Repeated measures ANOVA, Cohen’s d statistic, Bland–Altman analysis, and interclass correlation coefficients (ICC) assessed the agreement between UST-HRV and ST-HRV. Results: The consistency results of SDNN and RMSSD in resting and post-exercise were different. At the Pre-E, Post-E2, and Post-E3 phases, no statistical differences for SDNN and RMSSD were observed, with ICCs surpassing 0.9, indicating a high level of agreement. However, at Post-E2, there was a significant difference between 3 min RMSSD and 5 min RMSSD (p &lt; 0.05), as well as between 3 min SDNN, 4 min SDNN, and 5 min SDNN (p &lt; 0.05). Furthermore, the limits of agreement were observed to decrease as the time duration increased in Bland–Altman plots. Conclusions: UST-HRV analysis is a reliable substitute for standard 5 min HRV assessment, particularly during resting conditions. For post-exercise measurements, assessing the appropriateness of a 3- or 4 min duration based on the exercise’s length is recommended to ensure accuracy and reliability.

Validating the Skills of Satellite Rainfall Products and Spatiotemporal Rainfall Variability Analysis over Omo River Basin in Ethiopia

Recently created long-term and regionally dispersed satellite-based rainfall estimates have emerged as crucial sources of rainfall data to assess rainfall&amp;apos;s spatial and temporal variability, particularly for data-scarce locations. &amp;lt;i&amp;gt;Objective (the general)&amp;lt;/i&amp;gt;: The purpose of this paper is to assess the skills of nine selected satellite rainfall estimates i.e., (ARC 2.0, TRMM 3B42, CHIRPS v. 2.0, TAMSAT 3.1, CMORPH v. 1.0 adj., PERSIANN CDR and DNRT, and MSWEP v. 2.2) and understand Spatio-temporal variability of rainfall over the Omo River basin using the best performing product. &amp;lt;i&amp;gt;Method&amp;lt;/i&amp;gt;: The validation analysis was done by using a point-to-grid-based comparison test at different temporal accumulations. MSWEP was selected as the best product to analyze the long-term trend and variability of rainfall over the Omo-River basin from 1990-2017. The coefficients of variation (CV) and the standardization rainfall anomalies index (SRAI) were used to examine rainfall variability, while the Mann-Kendall (MK) and Sen slope estimators were used to examine the trend and magnitude of rainfall patterns. &amp;lt;i&amp;gt;Results&amp;lt;/i&amp;gt;: The overall statistical, categorical, and volumetric validation index results show that the MSWEP is the best performing rainfall product followed by CHRIPS, 3B42, and TAMSAT according to their order of appearance than the remaining products (i.e., ARC, RFE, PER CDR, PER DNRT, and CMORPH). The CV result with the relatively highest monthly variability (CV &amp;gt; 30%) was observed in some southern, northern, southeastern, and central parts of the study area. In general, the overall annual CV shows almost no variation in the entire basin except in the lower part because of the region&amp;apos;s prevalent topographic variances, which ranged from 3455 to 352 m.a.s.l. In addition, the highest seasonal positive and negative anomalies are observed in each season in the entire basin. These abnormalities can result in significant floods and droughts that unquestionably influence the basin and its resources. &amp;lt;i&amp;gt;Conclusion&amp;lt;/i&amp;gt;: In general, the basin has an increasing trend in the southern portions and a declining trend in the central to northern tip parts of the basin, as can be observed from the annual average MK trend tests. The basin has experienced a greeter variation but is not significant except in some parts of the basin.

Variability analysis of the Phenotypic Characteristics of some Grapefruit and Pomelo under Moroccan Conditions

Variability analysis of the Phenotypic Characteristics of some Grapefruit and Pomelo under Moroccan Conditions

Impact of Sleep Apnea on Nocturnal Parasympathetic Activity in Atrial Fibrillation Patients After Catheter Ablation - Implications for Heart Rate Variability Analysis.

The impact of sleep apnea (SA) on heart rate variability (HRV) in atrial fibrillation (AF) patients has not been investigated.Methods and Results: Of 94 patients who underwent AF ablation between January 2021 and September 2022, 76 patients who had a nocturnal Holter electrocardiography and polysomnography conducted simultaneously were included in the analysis. A 15-min duration of HRV, as determined by an electrocardiogram during apnea and non-apnea time, were compared between patients with and without AF recurrence at 12 months' postoperatively. Patients had a mean age of 63.4±11.6 years, 14 were female, and 20 had AF recurrence at 12 months' follow-up. The root mean square of the difference between consecutive normal-to-normal intervals (RMSSD, ms) an indicator of a parasympathetic nervous system, was more highly increased in patients with AF recurrence than those without, during both apnea and non-apnea time (apnea time: 16.7±4.5 vs. 13.5±3.3, P=0.03; non-apnea time: 20.9±9.5 vs. 15.5±5.9, P<0.01). However, RMSSD during an apneic state was decreased more than that in a non-apneic state in both groups of patients with and without AF recurrence (AF recurrence group: 16.7±4.5 vs. 20.9±9.5, P<0.01; non-AF recurrence group; 13.5±3.3 vs. 15.5±5.9, P=0.03). Consequently, the effect of AF recurrence on parasympathetic activity was offset by SA. Similar trends were observed for other parasympathetic activity indices; high frequency (HF), logarithm of HF (lnHF) and the percentage of normal-to-normal intervals >50 ms (pNN50). Without considering the influence of SA, the results of nocturnal HRV analysis might be misinterpreted. Caution should be taken when using nocturnal HRV as a predictor of AF recurrence.

Engineering attributes of ground motions from February 2023 Türkiye earthquake sequence

The 2023 Türkiye earthquake sequence includes the 6 February M7.81 mainshock followed approximately 9 h later by an M7.74 event, and many smaller aftershocks including M6.81 and M6.37 events on 6 and 20 February, respectively. These events occurred in a region near the plate boundary of the East Anatolian Fault, in the proximity of which numerous ground motion recording stations had been installed north of the Türkiye–Syria border. As a result, the events were well recorded both near the fault and at rupture distances up to 582 km. We describe the available recordings and component-specific data processing performed with the aim of optimizing usable bandwidth. The resulting database includes 337, 365, 284, and 229 usable three-component recordings from the M7.81, M7.74, M6.81, and M6.37 events, respectively. We also present source, path, and site metadata that were compiled according to uniform protocols. Comparisons to a global ground motion model (GMM) for active tectonic regions and a local, Türkiye-specific model demonstrate the existence of complex path effects that result in relatively poor fits between the GMMs and observed data at large distances (generally R JB &gt; 200 km). Under-predictions at some stations may be influenced by directivity and/or basin effects that affect the ground motions but that are not accounted for directly in the GMMs. We present analysis of spatial variability of several intensity measures. The residual maps produced from these analyses demonstrate that the global GMM overpredicts on the Anatolian block and underpredicts on the Arabian block, which is suggestive of distinct crustal attenuation features.

Frequency Domain Parameters of Heart Rate Variability in Patients with Gastro-Oesophageal Reflux Disease

Background: Gastro-oesophageal reflux disease (GERD) has been associated with autonomicnervous dysfunction along with reduced Heart Rate Variability.Objective: To observe cardiac autonomic nerve function status by heart rate variability analysis inpatients with Gastro-oesophageal reflux disease (GERD).Methods: This cross-sectional study was carried out in the Department of Physiology, SirSalimullah Medical College (SSMC), Dhaka from 1st January, 2017 to 31st December, 2017.Forthis, total 30 male and female diagnosed GERD patients from the Out Patient Department(OPD) of Gastroenterology, BSMMU aged 20-35 years were included in the study group. LowFrequency norm (LF norm),High Frequency norm (HF norm) and LF/HF ratio of HRV parameterswere recorded. Thirty age and BMI matched healthy subject also included as control. For statisticalanalysis, unpaired t-test was done as applicable.Results: The mean LF norm was 72.10±13.97 n.u. and the mean LF/HF was 3.34±1.14. Whichwere significantly (p&lt;0.001) higher in GERD patients in comparison to that of healthy subjects.Which indicate sympathetic overactivity in GERD patients. However, the mean HF norm was24.54±10.56 n.u. Which was significantly (p&lt;0.001) lower in GERD patients as compared to that of apparently healthy subjects. Which indicate decreased parasympathetic activity in GERDpatients.Conclusion: Parasympathetic hypofunction and sympathetic over activity were found in GERDpatients.

Exploring rice genotypes for anaerobic germination: Towards sustainable direct seeding

Direct-seeded rice (DSR) production is the primary focus of this study, which explores the diversity of rice genotypes concerning their ability to withstand anaerobic germination conditions. Using advanced statistical analysis, a total of 250 rice cultivars were assessed for several anaerobic germination attributes. Significant variability was observed among genotypes for key traits including germination % (ARC14855, AG 387), shoot length and seedling dry weight, indicating potential donors for anaerobic germination tolerance. Trait association analysis, variability analysis, principal component analysis and cluster analysis were employed to uncover the genetic and phenotypic factors influencing anaerobic germination tolerance. The genotypes of cluster III could be used as donors for anaerobic germination studies, as the genotypes have revealed high average values for all the traits. The findings underscore the importance of genetic variability and heritability in breeding resilient rice varieties suited for DSR cultivation, offering valuable insights for enhancing rice cultivation practices in the face of challenges such as water scarcity and labour shortages. To improve the sustainability and productivity of paddy production systems, this research advances rice breeding procedures that aim to create varieties tolerant to anaerobic conditions.

Future of neurocritical care: Integrating neurophysics, multimodal monitoring, and machine learning

Multimodal monitoring (MMM) in the intensive care unit (ICU) has become increasingly sophisticated with the integration of neurophysical principles. However, the challenge remains to select and interpret the most appropriate combination of neuromonitoring modalities to optimize patient outcomes. This manuscript reviewed current neuromonitoring tools, focusing on intracranial pressure, cerebral electrical activity, metabolism, and invasive and noninvasive autoregulation monitoring. In addition, the integration of advanced machine learning and data science tools within the ICU were discussed. Invasive monitoring includes analysis of intracranial pressure waveforms, jugular venous oximetry, monitoring of brain tissue oxygenation, thermal diffusion flowmetry, electrocorticography, depth electroencephalography, and cerebral microdialysis. Noninvasive measures include transcranial Doppler, tympanic membrane displacement, near-infrared spectroscopy, optic nerve sheath diameter, positron emission tomography, and systemic hemodynamic monitoring including heart rate variability analysis. The neurophysical basis and clinical relevance of each method within the ICU setting were examined. Machine learning algorithms have shown promise by helping to analyze and interpret data in real time from continuous MMM tools, helping clinicians make more accurate and timely decisions. These algorithms can integrate diverse data streams to generate predictive models for patient outcomes and optimize treatment strategies. MMM, grounded in neurophysics, offers a more nuanced understanding of cerebral physiology and disease in the ICU. Although each modality has its strengths and limitations, its integrated use, especially in combination with machine learning algorithms, can offer invaluable information for individualized patient care.