Changes in the Near-surface Shear Layer of the Sun

We use helioseismic data obtained over two solar cycles to determine whether there are changes in the near-surface shear layer (NSSL). We examine this by determining the radial gradient of the solar rotation rate. The radial gradient itself shows a solar-cycle dependence, and the changes are more pronounced in the active latitudes than at adjoining higher latitudes; results at the highest latitudes (≳70°) are unreliable. The pattern changes with depth, even within the NSSL. We find that the near-surface shear layer is deeper at lower latitudes than at high latitudes and that the extent of the layer also shows a small solar-cycle-related change.

Influence of antiferroelectric-like behavior on tuning properties of ferroelectric HZO-based varactors

In this article, we investigate the capacitance–voltage (C–V) characteristics of $$\text {Hf}_{x}\text {Zr}_{1-x}\text {O}_{2}$$ Hf x Zr 1 - x O 2 metal-ferroelectric-metal (MFM) thin-film capacitors with various Zr doping for varactor applications. The impact of field cycling during the wake-up process on the capacitance was analyzed. In addition, the effect of antiferroelectric-like (AFE) behavior on tuning was investigated. The transition between ferroelectric (FE) and AFE regime is particularly interesting for varactor application, as a reduced bias is required for tuning. The cycle dependence of the FE and AFE properties at elevated temperatures was also investigated, where it was shown that with an increase of temperature, the tunability is reduced. Temperature measurements also comply with recent studies of ferroelastic nature of AFE behavior. Graphic abstract

Seasonal variation of inter-hemispheric field-aligned currents deduced from time-series analysis of the equatorial geomagnetic field data during solar cycle 23–24

The east–west component of magnetic field variation (∆D-component) at Davao station (Philippines, geomagnetic latitude: – 2.22˚N) are used to investigate the characteristics of the long-term Inter-Hemispheric Field-Aligned Currents (IHFACs) based on the time-series analysis from August 1998 to July 2020. Recent in situ satellite and ground-based observations have reported that dusk-side current polarity of IHFAC is often opposite to that of the noon IHFAC, being inconsistent with Fukushima's IHFACs model. We investigated the consistency of the dusk-side IHFAC polarity derived from the observations with the polarity expected from Fukushima’s IHFACs model and examined the solar cycle dependence of IHFACs. It was confirmed that the dusk-side IHFACs during June and December solstices flow in the same direction of the noontime IHFACs, which was consistent with the IHFAC polarities suggested by the Fukushima model. The dusk-side IHFACs around March and September–November months disagreed with the Fukushima model. The ∆D variations clearly showed seasonal asymmetry in the dawn and noon sectors, whereas the ∆D variations in the dusk sector demonstrated seasonal symmetry. Solar cycle dependence of IHFACs was exhibited in the dusk sector. For the dawn and noon sectors, the yearly peak-to-peak ∆D amplitude in the later solar cycle SC24 decreased by about 35% in comparison with the earlier solar cycle SC23. In contrast, the dusk-side yearly peak-to-peak ∆D amplitude increased by about 200%. The dusk-side IHFAC yearly amplitude tended to be in inverse proportion to solar activity.

Sunspot Classifications & Solar Flare Prediction: Does machine learning improve upon Poisson-based prediction models?

<p>Historically, McIntosh classifications of sunspots have been utilised for the prediction of solar flares, with modern day operational flare forecast services still reliant upon these classifications for their predictions. Here, building upon previous Poisson-based flare forecasting models that make use of Mcintosh classifications, a set of various machine learning (ML) techniques are applied to construct a set of new models to predict flares within a 24-hr period.</p><p>These ML algorithms are trained and tested using data from a range of independent solar cycle periods, cross-validation techniques are applied and the relative performance of each algorithm is compared. In order to make a direct comparison to Poisson-based forecasts, skill scores are calculated and the performance of each model is presented, results showing that the ML models perform well across multiple metrics. The implications these results have when compared with the previous Poisson-based approach are discussed as well as the problem of solar cycle dependence. Additionally, an exploration of the importance of the individual features (i.e., McIntosh components) on the performance of each prediction model and their physical implications are presented.</p>

Cell Cycle-Dependence of Autophagic Activity and Inhibition of Autophagosome Formation at M Phase in Tobacco BY-2 Cells

Autophagy is ubiquitous in eukaryotic cells and plays an essential role in stress adaptation and development by recycling nutrients and maintaining cellular homeostasis. However, the dynamics and regulatory mechanisms of autophagosome formation during the cell cycle in plant cells remain poorly elucidated. We here analyzed the number of autophagosomes during cell cycle progression in synchronized tobacco BY-2 cells expressing YFP-NtATG8a as a marker for the autophagosomes. Autophagosomes were abundant in the G2 and G1 phases of interphase, though they were much less abundant in the M and S phases. Autophagosomes drastically decreased during the G2/M transition, and the CDK inhibitor roscovitine inhibited the G2/M transition and the decrease in autophagosomes. Autophagosomes were rapidly increased by a proteasome inhibitor, MG-132. MG-132-induced autophagosome formation was also markedly lower in the M phases than during interphase. These results indicate that the activity of autophagosome formation is differently regulated at each cell cycle stage, which is strongly suppressed during mitosis.

Cell cycle dependence of apoptosis photo-triggered using peptide-photosensitizer conjugate

Investigation of the relevance between cell cycle status and the bioactivity of exogenously delivered biomacromolecules is hindered by their time-consuming cell internalization and the cytotoxicity of transfection methods. In this study, we addressed these problems by utilizing the photochemical internalization (PCI) method using a peptide/protein-photosensitizer conjugate, which enables immediate cytoplasmic internalization of the bioactive peptides/proteins in a light-dependent manner with low cytotoxicity. To identify the cell-cycle dependent apoptosis, a TatBim peptide-photosensitizer conjugate (TatBim-PS) with apoptotic activity was photo-dependently internalized into HeLa cells expressing a fluorescent ubiquitination-based cell cycle indicator (Fucci2). Upon irradiation, cytoplasmic TatBim-PS internalization exceeded 95% for all cells classified in the G1, S, and G2/M cell cycle phases with no significant differences between groups. TatBim-PS-mediated apoptosis was more efficiently triggered by photoirradiation in the G1/S transition than in the G1 and S/G2/M phases, suggesting high sensitivity of the former phase to Bim-induced apoptosis. Thus, the cell cycle dependence of Bim peptide-induced apoptosis was successfully investigated using Fucci2 indicator and the PCI method. Since PCI-mediated cytoplasmic internalization of peptides is rapid and does not span multiple cell cycle phases, the Fucci-PCI method constitutes a promising tool for analyzing the cell cycle dependence of peptides/protein functions.