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The paper demonstrates that quasi-biennial oscillation (QBO)-like oscillations can be simulated in an ensemble of dry GCM dynamical cores that are driven by a simple Held–Suarez temperature relaxation and low-level Rayleigh friction. The tropical stratospheric circulations of four dynamical cores, which are options in NCAR’s Community Atmosphere Model, version 5 (CAM5), are intercompared. These are the semi-Lagrangian (SLD) and Eulerian (EUL) spectral transform, finite-volume (FV), and spectral element (SE) dynamical cores. The paper investigates how the model design choices impact the wave generation, propagation, and dissipation mechanisms in the equatorial region. SLD, EUL, and SE develop spontaneous QBO-like oscillations in the upper equatorial stratosphere, whereas FV does not sustain the oscillation. Transformed Eulerian-mean (TEM) analyses reveal that resolved waves are the dominant drivers of the QBOs. However, the Eliassen–Palm flux divergence is strongly counteracted by the TEM momentum budget residual, which represents the forcing by diffusion and thermal damping. Interestingly, a reversed Brewer–Dobson circulation accelerates the downward propagation of the SLD’s QBO, whereas the EUL’s and SE’s QBOs are slowed by a mean ascent. Waves are abundant in the SLD’s, EUL’s, and SE’s tropical atmosphere despite the absence of moist convection as a typical wave trigger. Dynamic instabilities are suggested as a wave-triggering mechanism in the troposphere and wave-dissipation process in the stratosphere. In particular, there are indications that the increased occurrences of strongly negative instability indicators in SLD, EUL, and SE are related to more vigorous wave activities and higher magnitudes of the resolved wave forcing in comparison to FV.

Sudden Stratospheric Warming (SSW) are extreme weather events that can significantly impact weather patterns on short to subseasonal to seasonal timescales. In this study, we present a new idealized test case of a Sudden Stratospheric Warming (SSW) event implemented in GFDL's FV3 dynamical core. The initial condition features a wintertime stratospheric circulation with a westerly jet in the Northern Hemisphere and an easterly jet in the Southern Hemisphere. In the absence of tropospheric wave forcing, the model preserves the stratospheric circulation for approximately 200 days. To induce SSW, we introduce a moving mountain to generate planetary waves. Wavenumber‐1 forcing led to a vortex displacement SSW, while wavenumber‐2 forcing produced a vortex split SSW, consistent with observational data and literature. This minimal setup offers a controlled environment for studying SSW dynamics and serves as a useful testbed for evaluating the ability of dynamical cores to capture key stratospheric processes and troposphere‐stratosphere interactions. Plain Language Summary This study focuses on simulating a Sudden Stratospheric Warming (SSW), a major atmospheric event in which the strong polar vortex in the stratosphere rapidly weakens or breaks apart, often affecting weather patterns in both the stratosphere and troposphere. Using a dynamical core FV3, we created a simple experiment to replicate this event. Starting from usual winter weather patterns, characterized by robust polar‐circulating winds, our findings indicated that, in the absence of external disruptions, the model preserved these conditions for a long period of time. To trigger an SSW, we used a moving mountain to generate atmospheric waves that propagated upward from the troposphere into the stratosphere. These waves disrupted the vortex in the stratosphere, leading to two types of SSW events: one in which the polar vortex was displaced and the other in which it split into two. Our results matched real‐world observations of the SSWs. This study offers a simple framework to study SSW dynamics and test a dynamical core's ability to simulate key stratosphere–troposphere interactions. Furthermore, as an extreme weather event, SSWs have significant implications for subseasonal to seasonal weather forecasting, potentially influencing mid‐latitude weather patterns weeks to months in advance. Key Points New idealized minimalistic configuration to simulate various types of Stratospheric Sudden Warming (SSW) is presented Wavenumber‐1 vertically propagating waves cause a vortex displacement SSW while Wavenumber‐2 waves cause a vortex split SSW FV3 robustly simulates SSW events, demonstrating its strong ability to model stratospheric dynamics and troposphere‐stratosphere interaction

The paper demonstrates that sudden stratospheric warmings (SSWs) can be simulated in an ensemble of dry dynamical cores that miss the typical SSW forcing mechanisms like moist processes, land–sea contrasts, or topography. These idealized general circulation model (GCM) simulations are driven by a simple Held–Suarez–Williamson (HSW) temperature relaxation and low-level Rayleigh friction. In particular, the four dynamical cores of NCAR’s Community Atmosphere Model, version 5 (CAM5), are used, which are the semi-Lagrangian (SLD) and Eulerian (EUL) spectral-transform models and the finite-volume (FV) and the spectral element (SE) models. Three research themes are discussed. First, it is shown that SSW events in such idealized simulations have very realistic flow characteristics that are analyzed via the SLD model. A single vortex-split event is highlighted that is driven by wavenumber-1 and -2 wave–mean flow interactions. Second, the SLD simulations are compared to the EUL, FV, and SE dynamical cores, which sheds light on the impact of the numerical schemes on the circulation. Only SLD produces major SSWs, while others only exhibit minor stratospheric warmings. These differences are caused by SLD’s more vigorous wave–mean flow interactions in addition to a warm pole bias, which leads to relatively weak polar jets in SLD. Third, it is shown that tropical quasi-biennial oscillation (QBO)–like oscillations and SSWs can coexist in such idealized HSW simulations. They are present in the SLD dynamical core that is used to analyze the QBO–SSW interactions via a transformed Eulerian-mean (TEM) analysis. The TEM results provide support for the Holton–Tan effect.

The modon, a pair of counter‐rotating vortices propelling one another along a straight line, is an idealization of some observed large‐scale and small‐scale atmospheric and oceanic processes (e.g., twin cyclones), providing a challenging nonlinear test for fluid‐dynamics solvers (known as “dynamical cores”). We present an easy‐to‐setup test of colliding modons suitable for both shallow‐water and three‐dimensional dynamical cores on the sphere. Two pairs of idealized modons are configured to collide, exchange vortices, and depart in opposite directions, repeating indefinitely in the absence of ambient rotation. This test is applicable to both hydrostatic and nonhydrostatic dynamical cores and is particularly challenging for refined grids on the sphere, regardless of solution methodology, or vertical coordinate. We applied this test to three popular dynamical cores, used by three different general circulation models: the Spectral‐Element (SE) core of the Community Atmosphere Model, the Geophysical Fluid Dynamics Laboratory (GFDL) spectral core, and the GFDL Finite‐Volume Cubed‐Sphere dynamical core (FV3). Tests with a locally refined grid and nonhydrostatic dynamics were also performed with FV3. All cores tested were able to capture the propagation, collision, and exchange of the modons, albeit the rate at which the modon was diffused varied between the three cores and showed a strong dependence on the strength of hyperdiffusion. Key Points A new test of the horizontal nonlinear vorticity dynamics in a dynamical core is presented, applicable to both shallow‐water and 3‐D cores This “modon” test is easy‐to‐setup and can create a perpetual cycle of vortex pairs colliding, exchanging, and reforming The test isolates the horizontal discretization, and the results are sensitive to the horizontal dissipation in a core

Interferon (IFN)-α is a cytokine that exhibits a wide range of biological activities and is used in various cancer treatments. It regulates numerous genes that serve roles in antiviral, antiproliferative and proapoptotic activities. For decades, one of the main aspects of clinical oncology has been the development of anticancer therapeutics that promote the effective elimination of cancer cells via apoptosis. However, the updated available information concerning IFN-α-induced cancer cell apoptosis needs to be assembled, so as to provide an improved theoretical reference for the basic scientific research and clinical treatment of malignant tumors. Therefore, the present review focuses on the potential effects of IFN-α in inducing cancer cell apoptosis. The biological characteristics of IFN-α, the apoptotic signaling pathways and molecular mechanisms of apoptosis caused by IFN-α are discussed in different types of cancer cells. The present review provided a comprehensive understanding of the effects of IFN-α on cancer cell apoptosis, which will aid in developing more efficient strategies to effectively control the progression of certain cancers.

Bi2WO6 flower-like materials (FMs) were prepared by a hydrothermal method, followed by an in-situ reduction method to prepare Au@Bi2WO6 FMs. X-ray diffraction, scanning electron microscopy, transmission electron microscopy, high-resolution transmission electron microscopy, and X-ray photoelectron spectroscopy were employed to characterize the samples. It was discovered that the calculated OV content of Au@Bi2WO6 FMs is 25.16% whereas that of Bi2WO6 FMs is 20.81%, offering appropriate active sites for the absorption of gases and thus enhancing outstanding sensing property. Moreover, the detection of volatile and hazardous substances such as formaldehyde, methanol, acetone, benzene, toluene, and xylene was carried out to assess the efficacy of the Au@Bi2WO6 FMs sensors. The optimal operating temperatures for the Bi2WO6 FMs and Au@Bi2WO6 FMs sensors were 290 and 260 °C, respectively. Compared with Au@Bi2WO6 FMs sensor and Bi2WO6 FMs one, the best response of the front was 250 (900)–100 (800) ppm formaldehyde whereas that of the latter was 90 (230). Therefore, Au@ Bi2WO6 FMs have good response and selectivity, which are promising candidates for formaldehyde detection.

Recent studies have shown that combining Transformer and conditional strategies to deal with offline reinforcement learning can bring better results. However, in a conventional reinforcement learning scenario, the agent can receive a single frame of observations one by one according to its natural chronological sequence, but in Transformer, a series of observations are received at each step. Individual features cannot be extracted efficiently to make more accurate decisions, and it is still difficult to generalize effectively for data outside the distribution. We focus on the characteristic of few-shot learning in pre-trained models, and combine prompt learning to enhance the ability of real-time policy adjustment. By sampling the specific information in the offline dataset as trajectory samples, the task information is encoded to help the pre-trained model quickly understand the task characteristics and the sequence generation paradigm to quickly adapt to the downstream tasks. In order to understand the dependencies in the sequence more accurately, we also divide the fixed-size state information blocks in the input trajectory, extract the features of the segmented sub-blocks respectively, and finally encode the whole sequence into the GPT model to generate decisions more accurately. Experiments show that the proposed method achieves better performance than the baseline method in related tasks, can be generalized to new environments and tasks better, and effectively improves the stability and accuracy of agent decision making.

Background In general, traditional antidepressants often have limited efficacy in patients with major depressive disorder (MDD). Agomelatine, as an antidepressant with a different mechanism of action, might have adjunctive effects on traditional antidepressants. This study aimed to investigate the augmentation effect of agomelatine versus placebo in treating MDD patients who failed to respond to selective serotonin reuptake inhibitors (SSRIs) and serotonin-noradrenaline reuptake inhibitors (SNRIs). Methods This is an 8-week, multi-centred, double-blinded, randomized, and placebo-controlled trial. Participants diagnosed with MDD and demonstrated inadequate response to SSRI or SNRI lasting at least 2 weeks were randomly allocated to receive either agomelatine or placebo in conjunction with SSRIs or SNRIs. The 17 items of the Hamilton Depression Scale (HAMD-17) were employed to assess depression severity. The primary outcome is the total score of HAMD-17 at week 8. Secondary outcomes included HAMD-17 scores at weeks 2 and 4 and clinical remission and response over 8 weeks. Adverse events (AEs) reported in both groups were recorded. A linear mixed model was established for both primary and secondary outcomes. Results A total of 123 eligible participants were included, among which 60 were randomized into the agomelatine group, and 63 were randomized into the placebo group. The between-group difference in HAMD-17 score reduction from baseline to week 8 was not significant (difference = − 0.12, 95% CI = − 3.94 to 3.70,  P  = 0.90; Cohen’s d  = 0.022). In addition, we did not observe significant differences between the two treatment groups for secondary outcomes, including response remission, and AEs. Conclusions This study did not obtain significant findings in favour of the augmentation effect of agomelation for MDD patients. However, agomelatine was generally well tolerated and demonstrated a favourable safety profile when used in combination with SSRIs and SNRIs. Trial registration. This trial is registered at ClinicalTrials.gov ( https://clinicaltrials.gov ), the registration number is NCT 04589143.

We have conducted a line survey toward Orion KL using the Q-band receiver of the Tianma 65 m radio telescope (TMRT), covering 34.8–50 GHz with a velocity resolution between 0.79 and 0.55 km s−1, respectively. The observations reach a sensitivity of the level of 1–8 mK, proving that the TMRT is sensitive for conducting deep-line surveys. In total, 597 Gaussian features are extracted. Among them, 177 radio recombination lines (RRLs) are identified, including 126, 40, and 11 RRLs of hydrogen, helium, and carbon, with a maximum Δn of 16, 7, and 3, respectively. The carbon RRLs are confirmed to originate from photodissociation regions with a V LSR ∼ 9 km s−1. In addition, 371 molecular transitions of 53 molecular species are identified. Twenty-one molecular species of this survey were not firmly detected in the Q band by Rizzo et al., including species such as H2CS, HCOOH, C2H5OH, H213 CO, H2CCO, CH3CHO, CH2OCH2, HCN υ 2 = 1, and CH3OCHO υ t = 1. In particular, the vibrationally excited states of ethyl cyanide (C2H5CN υ13/υ21) are for the first time firmly detected in the Q band. NH3 (15,15) and (16,16) are identified, and they are so far the highest transitions of the NH3 inversion lines detected toward Orion KL. All of the identified lines can be reproduced by a radiative transfer model.

The detection of Martian polar ice cap change patterns is important for understanding their effects on driving Mars’s global water cycle and for regulating atmospheric circulation. However, current Martian ice cap identification using optical remote sensing data mainly relies on visual interpretation, which makes it difficult to quickly extract ice caps from multiple images and analyze their fine-scale spatiotemporal variation characteristics. Therefore, this study proposes an automatic Martian polar ice cap extraction algorithm for remote sensing data and analyzes the dynamic change characteristics of the Martian North Pole ice cap using time-series data. First, the automatic Martian ice cap segmentation algorithm was developed based on the ice cap features of high reflectance in the blue band and low saturation in the RGB band. Second, the Martian North Pole ice cap was extracted for the three Martian years MY25, 26, and 28 using Mars Orbiter Camera (MOC) Mars Daily Global Maps (MDGMs) data, which had better spatiotemporal continuity to analyze its variation characteristics. Lastly, the spatiotemporal variation characteristics of the ice cap and the driving factors of ice cap ablation were explored for the three aforementioned Martian years. The results indicated that the proposed automatic ice cap extraction algorithm had good performance, and the classification accuracy exceeded 93%. The ice cap ablation boundary retreat rates and spatiotemporal distributions were similar for the three years, with approximately 105 km2 of ice cap ablation for every one degree of areocentric longitude of the Sun (Ls). The main driving factor of ice cap ablation was solar radiation, which was mainly related to Ls. In addition, elevation had a different effect on ice cap ablation at different Ls in the same latitude area near the ablation boundary of the ice cap.