Metabolic dysfunction-associated steatotic liver disease and risk of cardiovascular disease.

OBJECTIVE: We explored clinical implications of the new definition of metabolic dysfunction-associated steatotic liver disease (MASLD) by assessing its prevalence and associated cardiovascular disease (CVD) risk. DESIGN: From nationwide health screening data, we identified 9 775 066 adults aged 20-79 who underwent health examination in 2009. Participants were categorised into four mutually exclusive groups: (1) MASLD; (2) MASLD with increased alcohol intake (MetALD); (3) MASLD with other combined aetiology (the three collectively referred to as MASLD/related steatotic liver disease (SLD)); and (4) no MASLD/related SLD. SLD was determined by fatty liver index ≥30. The primary outcome was CVD event, defined as a composite of myocardial infarction, ischaemic stroke, heart failure or cardiovascular death. RESULTS: The prevalence of MASLD, MetALD and MASLD with other combined aetiology was 27.5%, 4.4% and 1.5%, respectively. A total of 8 808 494 participants without prior CVD were followed up for a median of 12.3 years, during which 272 863 CVD events occurred. The cumulative incidence and multivariable-adjusted risk of CVD were higher in participants with MASLD/related SLD than in those without (HR 1.38 (95% CI 1.37 to 1.39)). Multivariable-adjusted HR (95% CI) of CVD events was 1.39 (1.38 to 1.40) for MASLD, 1.28 (1.26 to 1.30) for MetALD and 1.30 (1.26 to 1.34) for MASLD with other combined aetiology compared to the absence of any of these conditions. CVD risk was also higher in participants with metabolic dysfunction-associated fatty liver disease or non-alcoholic fatty liver disease than in those without the respective condition. CONCLUSION: Over one-third of Korean adults have MASLD/related SLD and bear a high CVD risk.

Changes in the intrinsic severity of severe acute respiratory syndrome coronavirus 2 according to the emerging variant: a nationwide study from February 2020 to June 2022, including comparison with vaccinated populations.

BACKGROUND: As the population acquires immunity through vaccination and natural infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), understanding the intrinsic severity of coronavirus disease (COVID-19) is becoming challenging. We aimed to evaluate the intrinsic severity regarding circulating variants of SARS-CoV-2 and to compare this between vaccinated and unvaccinated individuals. METHODS: With unvaccinated and initially infected confirmed cases of COVID-19, we estimated the case severity rate (CSR); case fatality rate (CFR); and mortality rate (MR), including severe/critical cases and deaths, stratified by age and compared by vaccination status according to the period regarding the variants of COVID-19 and vaccination. The overall rate was directly standardized with age. RESULTS: The age-standardized CSRs (aCSRs) of the unvaccinated group were 2.12%, 5.51%, and 0.94% in the pre-delta, delta, and omicron period, respectively, and the age-standardized CFRs (aCFRs) were 0.60%, 2.49%, and 0.63% in each period, respectively. The complete vaccination group had lower severity than the unvaccinated group over the entire period showing under 1% for the aCSR and 0.5% for the aCFR. The age-standardized MR of the unvaccinated group was 448 per million people per month people in the omicron period, which was 11 times higher than that of the vaccinated group. In terms of age groups, the CSR and CFR sharply increased with age from the 60 s and showed lower risk reduction in the 80 s when the period changed to the omicron period. CONCLUSIONS: The intrinsic severity of COVID-19 was the highest in the delta period, with over 5% for the aCSR, whereas the completely vaccinated group maintained below 1%. This implies that when the population is vaccinated, the impact of COVID-19 will be limited, even if a new mutation appears. Moreover, considering the decreasing intrinsic severity, the response to COVID-19 should prioritize older individuals at a higher risk of severe disease.

Epidemiology of Respiratory Viruses in Korean Children Before and After the COVID-19 Pandemic: A Prospective Study From National Surveillance System.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic led to a decrease in the seasonal incidence of many respiratory viruses worldwide due to the impact of nonpharmaceutical interventions (NPIs). However, as NPI measures were relaxed, respiratory viral infections re-emerged. We aimed to characterize the epidemiology of respiratory viruses in Korean children during post-COVID-19 pandemic years compared to that before the pandemic. METHODS: A nationwide prospective ongoing surveillance study has been conducted for detection of respiratory viruses between January 2017 and June 2023. We included data on adenovirus (AdV), human bocavirus (HBoV), human coronavirus (HCoV), human metapneumovirus (HMPV), human rhinovirus (HRV), influenza virus (IFV), parainfluenza virus (PIV), and respiratory syncytial virus (RSV), which were detected in children and adolescents younger than 20 years. We analyzed the weekly detection frequency of individual viruses and the age distribution of the affected children. The study period was divided into prepandemic (2017-2019) and postpandemic (2021-2023) periods. RESULTS: A total of 19,589 and 14,068 samples were collected in the pre- and postpandemic periods, respectively. The overall detection rate of any virus throughout the study period was 63.1%, with the lowest occurring in the 2nd half of 2020 (50.6%) and the highest occurring in the 2nd half of 2021 (72.3%). Enveloped viruses (HCoV, HMPV, IFV, PIV, and RSV) almost disappeared, but nonenveloped viruses (AdV, HBoV, and HRV) were detected even during the peak of the COVID-19 pandemic. The codetection rate increased from 15.0% prepandemic to 19.1% postpandemic (P < 0.001). During the postpandemic period, a large out-of-season PIV and HMPV epidemic occurred, but the usual seasonality began to be restored in 2023. The mean age of children with each virus detected in 2023 was significantly greater than that in prepandemic years (P = 0.003 and 0.007 for AdV and HCoV, respectively; P < 0.001 for others). The mean age of children with IFV increased in 2022 (11.1 ± 5.2 years) from prepandemic years (7.9 ± 4.6 years) but decreased to 8.7 ± 4.1 years in 2023. CONCLUSION: With the relaxation of NPI measures, several seasonal respiratory viruses cocirculated with unusual seasonal epidemic patterns and were associated with increasing age of infected children.

Enhancing Human Cutaneous Wound Healing through Targeted Suppression of Large Conductance Ca2+-Activated K+ Channels.

The modulation of K+ channels plays a crucial role in cell migration and proliferation, but the effect of K+ channels on human cutaneous wound healing (CWH) remains underexplored. This study aimed to determine the necessity of modulating K+ channel activity and expression for human CWH. The use of 25 mM KCl as a K+ channel blocker markedly improved wound healing in vitro (in keratinocytes and fibroblasts) and in vivo (in rat and porcine models). K+ channel blockers, such as quinine and tetraethylammonium, aided in vitro wound healing, while Ba2+ was the exception and did not show similar effects. Single-channel recordings revealed that the Ba2+-insensitive large conductance Ca2+-activated K+ (BKCa) channel was predominantly present in human keratinocytes. NS1619, an opener of the BKCa channel, hindered wound healing processes like proliferation, migration, and filopodia formation. Conversely, charybdotoxin and iberiotoxin, which are BKCa channel blockers, dramatically enhanced these processes. The downregulation of BKCa also improved CWH, whereas its overexpression impeded these healing processes. These findings underscore the facilitative effect of BKCa channel suppression on CWH, proposing BKCa channels as potential molecular targets for enhancing human cutaneous wound healing.

Information Geometry Theoretic Measures for Characterizing Neural Information Processing from Simulated EEG Signals.

In this work, we explore information geometry theoretic measures for characterizing neural information processing from EEG signals simulated by stochastic nonlinear coupled oscillator models for both healthy subjects and Alzheimer's disease (AD) patients with both eyes-closed and eyes-open conditions. In particular, we employ information rates to quantify the time evolution of probability density functions of simulated EEG signals, and employ causal information rates to quantify one signal's instantaneous influence on another signal's information rate. These two measures help us find significant and interesting distinctions between healthy subjects and AD patients when they open or close their eyes. These distinctions may be further related to differences in neural information processing activities of the corresponding brain regions, and to differences in connectivities among these brain regions. Our results show that information rate and causal information rate are superior to their more traditional or established information-theoretic counterparts, i.e., differential entropy and transfer entropy, respectively. Since these novel, information geometry theoretic measures can be applied to experimental EEG signals in a model-free manner, and they are capable of quantifying non-stationary time-varying effects, nonlinearity, and non-Gaussian stochasticity presented in real-world EEG signals, we believe that they can form an important and powerful tool-set for both understanding neural information processing in the brain and the diagnosis of neurological disorders, such as Alzheimer's disease as presented in this work.

Minimum Information Variability in Linear Langevin Systems via Model Predictive Control.

Controlling the time evolution of a probability distribution that describes the dynamics of a given complex system is a challenging problem. Achieving success in this endeavour will benefit multiple practical scenarios, e.g., controlling mesoscopic systems. Here, we propose a control approach blending the model predictive control technique with insights from information geometry theory. Focusing on linear Langevin systems, we use model predictive control online optimisation capabilities to determine the system inputs that minimise deviations from the geodesic of the information length over time, ensuring dynamics with minimum "geometric information variability". We validate our methodology through numerical experimentation on the Ornstein-Uhlenbeck process and Kramers equation, demonstrating its feasibility. Furthermore, in the context of the Ornstein-Uhlenbeck process, we analyse the impact on the entropy production and entropy rate, providing a physical understanding of the effects of minimum information variability control.

Alkaline-sensitive two-pore domain potassium channels form functional heteromers in pancreatic ß-cells.

Two-pore domain K+ channels (K2P channels), active as dimers, produce inhibitory currents regulated by a variety of stimuli. Among them, TWIK1-related alkalinization-activated K+ channel 1 (TALK1), TWIK1-related alkalinization-activated K+ channel 2 (TALK2), and TWIK1-related acid-sensitive K+ channel 2 (TASK2) form a subfamily of structurally related K2P channels stimulated by extracellular alkalosis. The human genes encoding these proteins are clustered at chromosomal region 6p21 and coexpressed in multiple tissues, including the pancreas. The question whether these channels form functional heteromers remained open. By analyzing single-cell transcriptomic data, we show that these channels are coexpressed in insulin-secreting pancreatic ß-cells. Using in situ proximity ligation assay and electrophysiology, we show that they form functional heterodimers both upon heterologous expression and under native conditions in human pancreatic ß-cells. We demonstrate that heteromerization of TALK2 with TALK1 or with TASK2 endows TALK2 with sensitivity to extracellular alkalosis in the physiological range. We further show that the association of TASK2 with TALK1 and TALK2 increases their unitary conductance. These results provide a new example of heteromerization in the K2P channel family expanding the range of the potential physiological and pathophysiological roles of TALK1/TALK2/TASK2 channels, not only in insulin-secreting cells but also in the many other tissues in which they are coexpressed.

Trends, clinical characteristics, antimicrobial susceptibility patterns, and outcomes of Campylobacter bacteraemia: a multicentre retrospective study.

PURPOSE: We aimed to explore the clinical characteristics of Campylobacter bacteraemia and identify the trends, risk factors for mortality, and antimicrobial susceptibility patterns from clinical samples. METHODS: This retrospective cohort study included patients confirmed to have Campylobacter bacteraemia from seven hospitals between January 2010 and June 2021. Data on demographics and underlying history, clinical manifestation, and antimicrobial susceptibility patterns were collected and analyzed. Annual cases of Campylobacter enteritis were extracted from a public database. RESULTS: A total of 108 patients were included, and five species were isolated. Campylobacter jejuni accounted for 54 (50.0%) cases and 17 (16%) patients had no symptoms other than fever. In-hospital mortality occurred in 14 (13.0%) patients. C. jejuni bacteraemia was associated with lower mortality compared to non-C. jejuni bacteraemia. Underlying cancer and septic shock were the significant factors associated with in-hospital mortality. Quinolone resistance was high (59%), whereas only 4% of isolates exhibited macrolide resistance. There has been a significant increase in the number of Campylobacter enteritis cases, which was strongly correlated with the number of Campylobacter bacteraemia cases (Pearson's coefficient: 0.953; p < 0.0001). CONCLUSION: The notably increasing incidence of Campylobacter bacteraemia and antibiotic resistance patterns can challenge the treatment, necessitating collective efforts of national surveillance and networks by many departments.

A stochastic model of edge-localized modes in magnetically confined plasmas.

Magnetically confined plasmas are far from equilibrium and pose considerable challenges in statistical analysis. We discuss a non-perturbative statistical method, namely a time-dependent probability density function (PDF) approach that is potentially useful for analysing time-varying, large, or non-Gaussian fluctuations and bursty events associated with instabilities in the low-to-high confinement transition and the H-mode. Specifically, we present a stochastic Langevin model of edge-localized modes (ELMs) by including stochastic noise terms in a previous ODE ELM model. We calculate exact time-dependent PDFs by numerically solving the Fokker-Planck equation and characterize time-varying statistical properties of ELMs for different energy fluxes and noise amplitudes. The stochastic noise is shown to introduce phase-mixing and plays a significant role in mitigating extreme bursts of large ELMs. Furthermore, based on time-dependent PDFs, we provide a path-dependent information geometric theory of the ELM dynamics and demonstrate its utility in capturing self-regulatory relaxation oscillations, bursts and a sudden change in the system. This article is part of a discussion meeting issue 'H-mode transition and pedestal studies in fusion plasmas'.

H-mode transition and pedestal studies.

The high confinement mode (H-mode) is the widely adopted standard operation scenario for the path to fusion in toroidal confinement devices. Since its discovery in 1982, the H-mode and access to the H-mode (the low to high and high to low transitions) remain two of the most actively researched areas in magnetically confined fusion programmes across the world. Significant progress has been made in the understanding of the intricate H-mode phase dynamics in recent years, from improvement in experimental diagnostic capability, theoretical development and modelling. The 'H-mode transition and pedestal studies' Special Issue provides a timely overview of recent progress in the study of H-modes covering experimental studies, further theoretical inquiry and computational modelling. This article is part of a discussion meeting issue 'H-mode transition and pedestal studies in fusion plasmas'.

H-mode dithering phase studies on ST40.

The dithering H-mode phase, characterized by oscillations, is generally observed at input power values close to the L-H transition power threshold and low plasma collisionalities (low electron density and/or high plasma temperature). Measurements to characterize the dithering phase are presented for the low aspect ratio, high magnetic field tokamak, ST40. The dithering phase oscillation frequency is observed between 400 and 800 Hz and demonstrates an inverse relationship with core plasma density. Dithering phase H-modes are documented across a nonlinear, low-density power threshold operational space, with signature low- and high-density branches. The minimum power threshold for dithering H-mode access is measured at a core, line average electron density of 4.7(±0.5) × 1019 m-3, close to a predicted value of 4.1(±0.4) × 1019 m-3 from multi-machine studies. ASTRA calculated values of power coupled to the ion species, at the dithering H-mode transition, exhibit a similar nonlinear dependence on density. This analysis points to the important contribution of the ion thermal channel to the L-H phase transition. The low-frequency plasma density and D-alpha dithers appear to be accompanied by sudden bursts of magnetohydrodynamic (MHD) activity. A simple model is tested to demonstrate a possible scenario of self-regulation among turbulence, zonal flows, pressure (density) gradient and MHD activities. This article is part of a discussion meeting issue 'H-mode transition and pedestal studies in fusion plasmas'.

The Impact of Entry Restrictions on the Spread of Severe Acute Respiratory Syndrome Coronavirus Variants Between 2021 and 2022.

To contain the surge of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the South Korean government has implemented non-pharmacological interventions as well as border restrictions. The efficacy of entry restrictions should be evaluated to facilitate their preparation for new variants of SARS-CoV-2. This study explored the impact of border policy changes on overseas entrants and local cases of SARS-CoV-2 variants. Data from the Korea Disease Control and Prevention Agency randomly collected between April 11, 2021 and August 20, 2022 were evaluated using the Granger causality model. The results showed that the outbreak gap of delta variants between international and domestic cases was 10 weeks, while that of omicron variants was approximately 2 weeks, meaning that the quarantine policy helped contain delta variants rather than more transmissible variants. It is recommended that countries implement quarantine policies based on particular purposes accounting for the specific features of different variants to avoid potential negative impacts on the economy.

Within-Host Evolution of SARS-CoV-2 in a B-Cell Depleted Patient With Successful Treatment.

Prolonged viral shedding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in an immunocompromised host is a challenge as the treatment and infection control for chronic coronavirus disease 2019 infection is not well established and there is a potential risk of new variants emerging. A 48-year-old woman who underwent chemotherapy, including rituximab and steroid, had reactivation of SARS-CoV-2 68 days after the virus was first detected. She successfully recovered after receiving convalescent plasma and intravenous immunoglobulin. Genomic analysis demonstrated that viruses collected from the nasopharyngeal specimens at day 0 and day 68 had 18 different nucleotide mutations, implying within-host evolution after in-depth epidemiologic investigation.

Significant Reduction in External Ventricular Drain-Related Infections After Introducing a Novel Bundle Protocol: A Before and After Trial.

BACKGROUND: External ventricular drain (EVD)-related infection (ERI) is a serious complication in neurosurgical patients. The estimated ERI rates range from 5 to 20 cases per 1,000 EVD catheter days. The pathophysiology of ERI is similar to central line-associated bloodstream infections (CLABSIs) stemming from skin-derived bacterial colonization. The use of bundle management can reduce CLABSI rates. Due to the pathogenic similarities between infections related to the two devices, we developed and evaluated the effectiveness of an ERI-bundle protocol based on CLABSI bundles. METHODS: From November 2016 to November 2021, we conducted a study to evaluate the effectiveness of an ERI-bundle protocol. This study adopted a before-and-after trial, comparing the ERI rates for the 2 years before and 3 years after the introduction of the newly developed ERI-bundle protocol. We also analyzed the contributing factors to ERI using logistic regression analysis. RESULTS: A total of 183 patients with 2,381 days of catheter use were analyzed. The ERI rate decreased significantly after the ERI-bundle protocol from 16.7% (14 of 84; 14.35 per 1,000 catheter days) to 4.0% (4 of 99; 3.21 per 1,000 catheter days) (P = 0.004). CONCLUSION: Introduction of the ERI-bundle protocol was very effective in reducing ERI.

The Profile of Early Sedation Depth and Clinical Outcomes of Mechanically Ventilated Patients in Korea.

BACKGROUND: Current international guidelines recommend against deep sedation as it is associated with worse outcomes in the intensive care unit (ICU). However, in Korea the prevalence of deep sedation and its impact on patients in the ICU are not well known. METHODS: From April 2020 to July 2021, a multicenter, prospective, longitudinal, noninterventional cohort study was performed in 20 Korean ICUs. Sedation depth extent was divided into light and deep using a mean Richmond Agitation-Sedation Scale value within the first 48 hours. Propensity score matching was used to balance covariables; the outcomes were compared between the two groups. RESULTS: Overall, 631 patients (418 [66.2%] and 213 [33.8%] in the deep and light sedation groups, respectively) were included. Mortality rates were 14.1% and 8.4% in the deep and light sedation groups (P = 0.039), respectively. Kaplan-Meier estimates showed that time to extubation (P < 0.001), ICU length of stay (P = 0.005), and death (P = 0.041) differed between the groups. After adjusting for confounders, early deep sedation was only associated with delayed time to extubation (hazard ratio [HR], 0.66; 95% confidence interval [CI], 0.55-0.80; P < 0.001). In the matched cohort, deep sedation remained significantly associated with delayed time to extubation (HR, 0.68; 95% CI, 0.56-0.83; P < 0.001) but was not associated with ICU length of stay (HR, 0.94; 95% CI, 0.79-1.13; P = 0.500) and in-hospital mortality (HR, 1.19; 95% CI, 0.65-2.17; P = 0.582). CONCLUSION: In many Korean ICUs, early deep sedation was highly prevalent in mechanically ventilated patients and was associated with delayed extubation, but not prolonged ICU stay or in-hospital death.

Comparative Computational Analysis of Spike Protein Structural Stability in SARS-CoV-2 Omicron Subvariants.

The continuous emergence of new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants with multiple spike (S) protein mutations pose serious threats to current coronavirus disease 2019 (COVID-19) therapies. A comprehensive understanding of the structural stability of SARS-CoV-2 variants is vital for the development of effective therapeutic strategies as it can offer valuable insights into their potential impact on viral infectivity. S protein mediates a virus' attachment to host cells by binding to angiotensin-converting enzyme 2 (ACE2) through its receptor-binding domain (RBD), and mutations in this protein can affect its stability and binding affinity. We analyzed S protein structural stability in various Omicron subvariants computationally. Notably, the S protein sequences analyzed in this work were obtained directly from our own sample collection. We evaluated the binding free energy between S protein and ACE2 in several complex forms. Additionally, we measured distances between the RBD of each chain in S protein to analyze conformational changes. Unlike most of the prior studies, we analyzed full-length S protein-ACE2 complexes instead of only RBD-ACE2 complexes. Omicron subvariants including BA.1, BA.2, BA.2.12.1, BA.4/BA.5, BA.2.75, BA.2.75_K147E, BA.4.6 and BA.4.6_N658S showed enhanced stability compared to wild type, potentially due to distinct S protein mutations. Among them, BA.2.75 and BA.4.6_N658S exhibited the highest and lowest level of stability, respectively.

Effects of Stochastic Noises on Limit-Cycle Oscillations and Power Losses in Fusion Plasmas and Information Geometry.

We investigate the effects of different stochastic noises on the dynamics of the edge-localised modes (ELMs) in magnetically confined fusion plasmas by using a time-dependent PDF method, path-dependent information geometry (information rate, information length), and entropy-related measures (entropy production, mutual information). The oscillation quenching occurs due to either stochastic particle or magnetic perturbations, although particle perturbation is more effective in this amplitude diminishment compared with magnetic perturbations. On the other hand, magnetic perturbations are more effective at altering the oscillation period; the stochastic noise acts to increase the frequency of explosive oscillations (large ELMs) while decreasing the frequency of more regular oscillations (small ELMs). These stochastic noises significantly reduce power and energy losses caused by ELMs and play a key role in reproducing the observed experimental scaling relation of the ELM power loss with the input power. Furthermore, the maximum power loss is closely linked to the maximum entropy production rate, involving irreversible energy dissipation in non-equilibrium. Notably, over one ELM cycle, the information rate appears to keep almost a constant value, indicative of a geodesic. The information rate is also shown to be useful for characterising the statistical properties of ELMs, such as distinguishing between explosive and regular oscillations and the regulation between the pressure gradient and magnetic fluctuations.

Stochastic Dynamics of Fusion Low-to-High Confinement Mode (L-H) Transition: Correlation and Causal Analyses Using Information Geometry.

We investigate the stochastic dynamics of the prey-predator model of the Low-to-High confinement mode (L-H) transition in magnetically confined fusion plasmas. By considering stochastic noise in the turbulence and zonal flows as well as constant and time-varying input power Q, we perform multiple stochastic simulations of over a million trajectories using GPU computing. Due to stochastic noise, some trajectories undergo the L-H transition while others do not, leading to a mixture of H-mode and dithering at a given time and/or input power. One of the consequences of this is that H-mode characteristics appear at a smaller input power QQc as a second peak. The coexisting H-mode and dithering near Q=Qc leads to a prominent bimodal PDF with a gradual L-H transition rather than a sudden transition at Q=Qc and uncertainty in the input power. Also, a time-dependent input power leads to increased variability (dispersion) in stochastic trajectories and a more prominent bimodal PDF. We provide an interpretation of the results using information geometry to elucidate self-regulation between zonal flows, turbulence, and information causality rate to unravel causal relations involved in the L-H transition.

Causality Analysis with Information Geometry: A Comparison.

The quantification of causality is vital for understanding various important phenomena in nature and laboratories, such as brain networks, environmental dynamics, and pathologies. The two most widely used methods for measuring causality are Granger Causality (GC) and Transfer Entropy (TE), which rely on measuring the improvement in the prediction of one process based on the knowledge of another process at an earlier time. However, they have their own limitations, e.g., in applications to nonlinear, non-stationary data, or non-parametric models. In this study, we propose an alternative approach to quantify causality through information geometry that overcomes such limitations. Specifically, based on the information rate that measures the rate of change of the time-dependent distribution, we develop a model-free approach called information rate causality that captures the occurrence of the causality based on the change in the distribution of one process caused by another. This measurement is suitable for analyzing numerically generated non-stationary, nonlinear data. The latter are generated by simulating different types of discrete autoregressive models which contain linear and nonlinear interactions in unidirectional and bidirectional time-series signals. Our results show that information rate causalitycan capture the coupling of both linear and nonlinear data better than GC and TE in the several examples explored in the paper.

Statistical Analysis of Plasma Dynamics in Gyrokinetic Simulations of Stellarator Turbulence.

A geometrical method for assessing stochastic processes in plasma turbulence is investigated in this study. The thermodynamic length methodology allows using a Riemannian metric on the phase space; thus, distances between thermodynamic states can be computed. It constitutes a geometric methodology to understand stochastic processes involved in, e.g., order-disorder transitions, where a sudden increase in distance is expected. We consider gyrokinetic simulations of ion-temperature-gradient (ITG)-mode-driven turbulence in the core region of the stellarator W7-X with realistic quasi-isodynamic topologies. In gyrokinetic plasma turbulence simulations, avalanches, e.g., of heat and particles, are often found, and in this work, a novel method for detection is investigated. This new method combines the singular spectrum analysis algorithm with a hierarchical clustering method such that the time series is decomposed into two parts: useful physical information and noise. The informative component of the time series is used for the calculation of the Hurst exponent, the information length, and the dynamic time. Based on these measures, the physical properties of the time series are revealed.