Progesterone Administration Modulates Cortical TLR4/NF-κB Signaling Pathway after Subarachnoid Hemorrhage in Male Rats

Our previous study concerning brain trauma has shown that progesterone could regulate toll-like receptor 4 (TLR4) and nuclear factor-kappa B (NF-κB) signaling pathway in the brain, which also has been proved to play important roles in early brain injury (EBI) after subarachnoid hemorrhage (SAH). The aim of the current study was to investigate whether progesterone administration modulated TLR4/NF-κB pathway signaling pathway in the brain at the early stage of SAH. All SAH animals were subjected to injection of 0.3 ml fresh arterial, non-heparinized blood into prechiasmatic cistern in 20 seconds. Male rats were given 0 or 16 mg/kg injections of progesterone at post-SAH hours 1, 6, and 24. Brain samples were extracted at 48 h after SAH. As a result, SAH could induce a strong up-regulation of TLR4, NF-κB, pro-inflammatory cytokines, MCP-1, and ICAM-1 in the cortex. Administration of progesterone following SAH could down-regulate the cortical levels of these agents related to TLR4/NF-κB signaling pathway. Post-SAH progesterone treatment significantly ameliorated the EBI, such as the clinical behavior scale, brain edema, and blood-brain barrier (BBB) impairment. It was concluded that post-SAH progesterone administration may attenuate TLR4/NF-κB signaling pathway in the rat brain following SAH

5-(Pyridin-4-yl)isophthalic acid

In the title compound, C13H9NO4, the two carb­oxy­lic groups and the benzene ring are approximately co-planar with a maximum atomic deviation 0.175 (4) Å, while the pyridine ring is oriented at a dihedral angle of 31.07 (18)° with respect to the benzene ring. In the crystal, mol­ecules are linked by O—H⋯O, O—H⋯N and weak C—H⋯O hydrogen bonds, forming a three-dimensional supra­molecular framework

Production of dibaryon dNΩd_{N\Omega} in kaon induced reactions

In this work, we propose to investigate the $d_{N\Omega}$ dibaryon production in the process $K^- p \rightarrow d_{N\Omega} \bar{\Xi}^0$ by utilizing the kaon beam with the typical momentum to be around 10 GeV, which may be available at COMPASS, OKA@U-70 and SPS@CERN. The cross sections for $K^- p \rightarrow d_{N\Omega} \bar{\Xi}^0$ are estimated and in particular, the cross sections can reach up to $577.20\ \mathrm{\mu b}$ at $P_{K}=20$ GeV. Considering that $d_{N\Omega}$ dominantly decay into $\Xi \Lambda$ and $\Xi \Sigma$, we also estimate the cross sections for $K^- p \to \Xi^0 \Lambda \bar{\Xi}^0$ and $K^- p \to \Xi^+ \Sigma^- \bar{\Xi}^0$, which can reach up to $134.89$ and $5.93 \ \mathrm{\mu b}$, respectively, at$P_K=20$ GeV.Comment: 7 pages, 4 figure

Graph Mining for Cybersecurity: A Survey

The explosive growth of cyber attacks nowadays, such as malware, spam, and intrusions, caused severe consequences on society. Securing cyberspace has become an utmost concern for organizations and governments. Traditional Machine Learning (ML) based methods are extensively used in detecting cyber threats, but they hardly model the correlations between real-world cyber entities. In recent years, with the proliferation of graph mining techniques, many researchers investigated these techniques for capturing correlations between cyber entities and achieving high performance. It is imperative to summarize existing graph-based cybersecurity solutions to provide a guide for future studies. Therefore, as a key contribution of this paper, we provide a comprehensive review of graph mining for cybersecurity, including an overview of cybersecurity tasks, the typical graph mining techniques, and the general process of applying them to cybersecurity, as well as various solutions for different cybersecurity tasks. For each task, we probe into relevant methods and highlight the graph types, graph approaches, and task levels in their modeling. Furthermore, we collect open datasets and toolkits for graph-based cybersecurity. Finally, we outlook the potential directions of this field for future research

Ethyl (E)-3-anilino-2-cyano-3-mercaptoacrylate

In the title compound, C12H12N2O2S, there are S—H⋯N and N—H⋯O hydrogen-bond inter­actions. The N—H⋯O hydrogen bond is bifurcated, with the hydrogen being simultaneously donated to two equivalent O atoms, forming one intra- and one inter­molecular N—H⋯O bond with an R 1 2(4) motif. The motif of the S—H⋯N hydrogen bond is R 2 2(12)

MetaPortrait: Identity-Preserving Talking Head Generation with Fast Personalized Adaptation

In this work, we propose an ID-preserving talking head generation framework, which advances previous methods in two aspects. First, as opposed to interpolating from sparse flow, we claim that dense landmarks are crucial to achieving accurate geometry-aware flow fields. Second, inspired by face-swapping methods, we adaptively fuse the source identity during synthesis, so that the network better preserves the key characteristics of the image portrait. Although the proposed model surpasses prior generation fidelity on established benchmarks, to further make the talking head generation qualified for real usage, personalized fine-tuning is usually needed. However, this process is rather computationally demanding that is unaffordable to standard users. To solve this, we propose a fast adaptation model using a meta-learning approach. The learned model can be adapted to a high-quality personalized model as fast as 30 seconds. Last but not the least, a spatial-temporal enhancement module is proposed to improve the fine details while ensuring temporal coherency. Extensive experiments prove the significant superiority of our approach over the state of the arts in both one-shot and personalized settings.Comment: CVPR 2023, project page: https://meta-portrait.github.i

Electrostatic theory for designing lossless negative permittivity metamaterials

In this Letter, we develop an electrostatic theory for designing bulk composites with effective lossless negative permittivities. The theory and associated design procedure are validated by comparing their predictions with those of rigorous full-wave simulations. It is demonstrated that the excitation of the Frohlich mode (the first-order surface mode) of the constitutive nanoparticles plays a key role in achieving negative permittivities with compensated losses.Comment: 9 pages, 2 figure