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In this paper, we study the periodic orbits of massive particles around two quantum-corrected black holes proposed in effective quantum gravity, and explore the quantum gravity effect on both the particle orbits and the associated gravitational wave signals. First, we analyze the geodesic motion of the massive particle around the black holes. We then study two important types of bound orbits of the massive particles, the marginally bound orbit and the innermost stable circular orbit. We find that, for the first black hole, increasing the quantum parameter ζ leads to larger orbital radii and reduced angular momenta for both orbits. In contrast, the second black hole shows ζ -independent orbital radii and angular momenta. By analyzing the effective potential, we determine the allowed range of the energy and the angular momentum for bound orbits, with ζ -dependence only for the first black hole. We further investigate periodic orbits with a fixed energy for both black holes, revealing that the parameter ζ similarly affects the orbits, although its effect is negligible in the second black hole. Finally, we calculate the gravitational waves emitted by the periodic orbits. The results demonstrate that increasing ζ leads to a significant phase delay for the first black hole, while only inducing a subtle phase advance for the second one. Therefore, we conclude that the first black hole can be distinguished from the Schwarzschild one through gravitational wave observations, whereas the second one cannot be effectively distinguished when the quantum correction is weak.

Recently, two new quantum-corrected black hole models satisfying covariance have been proposed within the framework of effective quantum gravity. In this paper, we study how the quantum parameter ζ affects the optical properties of two quantum-corrected black hole models. We first analyze the photon sphere, critical impact parameter, and innermost stable circular orbit as ζ varies, and constrain ζ using Event Horizon Telescope data. Additionally, by employing the ray-tracing method to study photon trajectories near the two quantum-corrected black holes, we find that ζ can reduce the range of impact parameters corresponding to the photon ring and lensed ring. We then examine the optical appearance of these black holes with thin accretion disks, showing ζ significantly brightens the first model’s image but has little effect on the second. Meanwhile, we demonstrate the contributions of the transfer functions to the observed intensity of direct and lensed ring in the observer’s field of view, which has rarely been separately illustrated in previous studies. Finally, we study the optical appearance of both quantum-corrected black holes under a static spherical accretion model, with results consistent with the above. Therefore, we conclude that the second quantum-corrected black hole is almost indistinguishable from the Schwarzschild black hole, while the first quantum-corrected black hole can be distinguished from the Schwarzschild black hole through its optical appearance.

Consistent annotation transfer from reference dataset to query dataset is fundamental to the development and reproducibility of single-cell research. Compared with traditional annotation methods, deep learning based methods are faster and more automated. A series of useful single cell analysis tools based on autoencoder architecture have been developed but these struggle to strike a balance between depth and interpretability. Here, we present TOSICA, a multi-head self-attention deep learning model based on Transformer that enables interpretable cell type annotation using biologically understandable entities, such as pathways or regulons. We show that TOSICA achieves fast and accurate one-stop annotation and batch-insensitive integration while providing biologically interpretable insights for understanding cellular behavior during development and disease progressions. We demonstrate TOSICA’s advantages by applying it to scRNA-seq data of tumor-infiltrating immune cells, and CD14+ monocytes in COVID-19 to reveal rare cell types, heterogeneity and dynamic trajectories associated with disease progression and severity. Developing computational tools for interpretable cell type annotation in scRNA-seq data remains challenging. Here the authors propose a Transformer-based model for interpretable annotation transfer using biologically understandable entities, and demonstrate its performance on large or atlas datasets.

In the early 21st century, the whole society finished the transformation from a panopticon to an electronic super panopticon. With the development of intellectual technology, the view of surveillance increases. People in a technological society are monitored in every movement they make. In Starset’s post-apocalyptic society of the future, people are controlled by technology and become docile and prolific labor machines. This essay will analyze three songs by American hard rock band Starset, Breach, Where the skies end and Icarus, using three of Foucault’s theories of discipline and punishment, hierarchical surveillance, normalizing judgment and examination. Under the disciplinary surveillance, people from Starset’s post-apocalyptic society have been tamed by the power of technology and are constantly disciplining themselves and checking themselves, becoming a single efficient producer. It also shows that society is becoming a transparent high-speed panopticon prison.

Images obtained in an unfavorable environment may be affected by haze or fog, leading to fuzzy image details, low contrast, and loss of important information. Recently, significant progress has been achieved in the realm of image dehazing, largely due to the adoption of deep learning techniques. Owing to the lack of modules specifically designed to learn the unique characteristics of haze, existing deep neural network-based methods are impractical for processing images containing haze. In addition, most networks primarily focus on learning clear image information while disregarding potential features in hazy images. To address these limitations, we propose an innovative method called contrastive multiscale transformer for image dehazing (CMT-Net). This method uses the multiscale transformer to enable the network to learn global hazy features at multiple scales. Furthermore, we introduce feature combination attention and a haze-aware module to enhance the network’s ability to handle varying concentrations of haze by assigning more weight to regions containing haze. Finally, we design a multistage contrastive learning loss incorporating different positive and negative samples at various stages to guide the network’s learning process to restore real and non-hazy images. The experimental findings demonstrate that CMT-Net provides exceptional performance on established datasets and exhibits superior visual outcomes.

At present, electric lighting accounts for ~15% of global power consumption and thus the adoption of efficient, low-cost lighting technologies is important. Halide perovskites have been shown to be good emitters of pure red, green and blue light, but an efficient source of broadband white electroluminescence suitable for lighting applications is desirable. Here, we report a white light-emitting diode (LED) strategy based on solution-processed heterophase halide perovskites that, unlike GaN white LEDs, feature only one broadband emissive layer and no phosphor. Our LEDs operate with a peak luminance of 12,200 cd m−2 at a bias of 6.6 V and a maximum external quantum efficiency of 6.5% at a current density of 8.3 mA cm−2. Systematic in situ and ex situ characterizations reveal that the mechanism of efficient electroluminescence is charge injection into the α phase of CsPbI3, α to δ charge transfer and α–δ balanced radiative recombination. Future advances in fabrication technology and mechanistic understanding should lead to further improvements in device efficiency and luminance.Heterophase CsPbI3 perovskite gives rise to bright white phosphor-free LEDs.

There is a wide variety of kinds of lipids, and complex structures which determine the diversity and complexity of their functions. With the basic characteristic of water insolubility, lipid molecules are independent of the genetic information composed by genes to proteins, which determine the particularity of lipids in the human body, with water as the basic environment and genes to proteins as the genetic system. In this review, we have summarized the current landscape on hormone regulation of lipid metabolism. After the well-studied PI3K-AKT pathway, insulin affects fat synthesis by controlling the activity and production of various transcription factors. New mechanisms of thyroid hormone regulation are discussed, receptor α and β may mediate different procedures, the effect of thyroid hormone on mitochondria provides a new insight for hormones regulating lipid metabolism. Physiological concentration of adrenaline induces the expression of extrapituitary prolactin in adipose tissue macrophages, which promotes fat weight loss. Manipulation of hormonal action has the potential to offer a new therapeutic horizon for the global burden of obesity and its associated complications such as morbidity and mortality.

Carbon neutrality, energy savings, and lighting costs and quality have always led to urgent demand for lighting technology innovation. White light-emitting diodes (WLEDs) based on a single emissive layer (SEL) fabricated by the solution method have been continuously researched in recent years; they are advantageous because they have a low cost and are ultrathin and flexible. Here, we reviewed the history and development of SEL–WLEDs over recent years to provide inspiration and promote their progress in lighting applications. We first introduced the emitters and analysed the advantages of these emitters in creating SEL–WLEDs and then reviewed some cases that involve the above emitters, which were formed via vacuum thermal evaporation or solution processes. Some notable developments that deserve attention are highlighted in this review due to their potential use in SEL–WLEDs, such as perovskite materials. Finally, we looked at future development trends of SEL–WLEDs and proposed potential research directions.

The COVID‐19 coronavirus is now spreading worldwide. Its pathogen, SARS‐CoV‐2, has been shown to use angiotensin‐converting enzyme 2 (ACE2) as its host cell receptor, same as the severe acute respiratory syndrome coronavirus (SARS‐CoV) in 2003. Epidemiology studies found males although only slightly more likely to be infected than females account for the majority of the severely ill and fatality, which also bias for people older than 60 years or with metabolic and cardiovascular diseases. Here by analyzing GTEx and other public data in 30 tissues across thousands of individuals, we found a significantly higher level in Asian females, an age‐dependent decrease in all ethnic groups, and a highly significant decrease in type II diabetic patients of ACE2 expression. Consistently, the most significant expression quantitative loci (eQTLs) contributing to high ACE2 expression are close to 100% in East Asians, >30% higher than other ethnic groups. A shockingly common enrichment of viral infection pathways was found among ACE2 anti‐expressed genes, and multiple binding sites of virus infection related transcription factors and sex hormone receptors locate at ACE2 regulatory regions. Human and mice data analysis further revealed ACE2 expression is reduced in T2D patients and with inflammatory cytokine treatment and upregulated by estrogen and androgen (both decrease with age). Our findings revealed a negative correlation between ACE2 expression and COVID‐19 fatality at both population and molecular levels. These results will be instrumental when designing potential prevention and treatment strategies for ACE2 binding coronaviruses in general. This study revealed the negative correlation of high basal ACE2 level with CoVID‐19 severity/fatality at the population level and its anticorrelation with virus infection pathway expression levels, upregulation by sex hormones and suppression by inflammatory cytokine at the molecular level.

Recently, two new spherically symmetric black hole models with covariance have been proposed in effective quantum gravity. Based on these models, we use the modified Newman–Janis algorithm to generate two rotating quantum-corrected black hole solutions, characterized by three parameters, the mass M , the spin a , and the quantum parameter ζ . To understand the effects of the quantum parameter ζ on these two rotating black holes, we investigate in detail the horizons and static limit surfaces. By constraining the possible range of the parameters, we study the shadows cast by these rotating black holes. The results indicate that for both rotating BHs, the parameter ζ mainly affects the shadow size in the non-extremal case, while it deforms the shadow shape by arising a cuspy edge in the near-extremal case. Through the presence of the cuspy edge in the shadow, we further discuss how to differentiate it from the shadows of other rotating quantum-corrected black holes. Utilizing the Event Horizon Telescope shadow observational results for M87* and Sgr A*, we set the black hole inclination angles to 17 ∘ , 50 ∘ , and 90 ∘ and subsequently calculate the angular diameter of the black hole shadows. Our analysis indicates that in the constrained parameter space for M87* and Sgr A*, the common parameter constraints obtained from the RBH-I are 0.569246 M < ζ < 0.924954 M . In contrast, the constraints from the RBH-II are 0 < ζ < 3.018 M .