Features and stability analysis of non-Schwarzschild black hole in quadratic gravity

Black holes are found to exist in gravitational theories with the presence of quadratic curvature terms and behave differently from the Schwarzschild solution. We present an exhaustive analysis for determining the quasinormal modes of a test scalar field propagating in a new class of black hole backgrounds in the case of pure Einstein-Weyl gravity. Our result shows that the field decay of quasinormal modes in such a non-Schwarzschild black hole behaves similarly to the Schwarzschild one, but the decay slope becomes much smoother due to the appearance of the Weyl tensor square in the background theory. We also analyze the frequencies of the quasinormal modes in order to characterize the properties of new back holes, and thus, if these modes can be the source of gravitational waves, the underlying theories may be testable in future gravitational wave experiments. We briefly comment on the issue of quantum (in)stability in this theory at linear order.Comment: 18 pages, 4 figures, 1 table, several references added, version published on JHE

CLIP-Hand3D: Exploiting 3D Hand Pose Estimation via Context-Aware Prompting

Contrastive Language-Image Pre-training (CLIP) starts to emerge in many computer vision tasks and has achieved promising performance. However, it remains underexplored whether CLIP can be generalized to 3D hand pose estimation, as bridging text prompts with pose-aware features presents significant challenges due to the discrete nature of joint positions in 3D space. In this paper, we make one of the first attempts to propose a novel 3D hand pose estimator from monocular images, dubbed as CLIP-Hand3D, which successfully bridges the gap between text prompts and irregular detailed pose distribution. In particular, the distribution order of hand joints in various 3D space directions is derived from pose labels, forming corresponding text prompts that are subsequently encoded into text representations. Simultaneously, 21 hand joints in the 3D space are retrieved, and their spatial distribution (in x, y, and z axes) is encoded to form pose-aware features. Subsequently, we maximize semantic consistency for a pair of pose-text features following a CLIP-based contrastive learning paradigm. Furthermore, a coarse-to-fine mesh regressor is designed, which is capable of effectively querying joint-aware cues from the feature pyramid. Extensive experiments on several public hand benchmarks show that the proposed model attains a significantly faster inference speed while achieving state-of-the-art performance compared to methods utilizing the similar scale backbone.Comment: Accepted In Proceedings of the 31st ACM International Conference on Multimedia (MM' 23

Deep Refinement-Based Joint Source Channel Coding over Time-Varying Channels

In recent developments, deep learning (DL)-based joint source-channel coding (JSCC) for wireless image transmission has made significant strides in performance enhancement. Nonetheless, the majority of existing DL-based JSCC methods are tailored for scenarios featuring stable channel conditions, notably a fixed signal-to-noise ratio (SNR). This specialization poses a limitation, as their performance tends to wane in practical scenarios marked by highly dynamic channels, given that a fixed SNR inadequately represents the dynamic nature of such channels. In response to this challenge, we introduce a novel solution, namely deep refinement-based JSCC (DRJSCC). This innovative method is designed to seamlessly adapt to channels exhibiting temporal variations. By leveraging instantaneous channel state information (CSI), we dynamically optimize the encoding strategy through re-encoding the channel symbols. This dynamic adjustment ensures that the encoding strategy consistently aligns with the varying channel conditions during the transmission process. Specifically, our approach begins with the division of encoded symbols into multiple blocks, which are transmitted progressively to the receiver. In the event of changing channel conditions, we propose a mechanism to re-encode the remaining blocks, allowing them to adapt to the current channel conditions. Experimental results show that the DRJSCC scheme achieves comparable performance to the other mainstream DL-based JSCC models in stable channel conditions, and also exhibits great robustness against time-varying channels

Tracing primordial black holes in nonsingular bouncing cosmology

We in this paper investigate the formation and evolution of primordial black holes (PBHs) in nonsingular bouncing cosmologies. We discuss the formation of PBH in the contracting phase and calculate the PBH abundance as a function of the sound speed and Hubble parameter. Afterwards, by taking into account the subsequent PBH evolution during the bouncing phase, we derive the density of PBHs and their Hawking radiation. Our analysis shows that nonsingular bounce models can be constrained from the backreaction of PBHs

A mass-balance-based emission inventory of non-methane volatile organic compounds (NMVOCs) for solvent use in China

Non-methane volatile organic compounds (NMVOCs) are important precursors of ozone (O3) and secondary organic aerosol (SOA), which play key roles in tropospheric chemistry. A huge amount of NMVOC emissions from solvent use are complicated by a wide spectrum of sources and species. This work presents a long-term NMVOC emission inventory of solvent use during 2000&ndash;2017 in China. Based on a mass (material) balance method, NMVOC emissions were estimated for six categories, including coatings, adhesives, inks, pesticides, cleaners, and personal care products. The results show that NMVOC emissions from solvent use in China increased rapidly from 2000 to 2014 then kept stable after 2014. The total emission increased from 1.6&thinsp;Tg (1.2&ndash;2.2&thinsp;Tg at 95&thinsp;% confidence interval) in 2000 to 10.6&thinsp;Tg (7.7&ndash;14.9&thinsp;Tg) in 2017. The substantial growth is driven by the large demand for solvent products in both industrial and residential activities. However, increasing treatment facilities in the solvent-related factories in China restrained the continued growth of solvent NMVOC emissions in recent years. Rapidly developing and heavily industrialized provinces such as Jiangsu, Shandong, and Guangdong contributed significantly to the solvent use emissions. Oxygenated VOCs, alkanes, and aromatics were the main components, accounting for 42&thinsp;%, 28&thinsp;%, and 21&thinsp;% of total NMVOC emissions in 2017, respectively. Our results and previous inventories are generally comparable within the estimation uncertainties (&minus;27&thinsp;%&ndash;52&thinsp;%). However, there exist significant differences in the estimates of sub-categories. Personal care products were a significant and quickly rising source of NMVOCs, which were probably underestimated in previous inventories. Emissions from solvent use were growing faster compared with transportation and combustion emissions, which were relatively better controlled in China. Environmentally friendly products can reduce the NMVOC emissions from solvent use. Supposing all solvent-based products were substituted with water-based products, it would result in 37&thinsp;%, 41&thinsp;%, and 38&thinsp;% reduction of emissions, ozone formation potential (OFP), and secondary organic aerosol formation potential (SOAP), respectively. These results indicate there is still large potential for NMVOC reduction by reducing the utilization of solvent-based products and implementation of end-of-pipe controls across industrial sectors. </div

Development of novel monoclonal antibodies for blocking NF-κB activation induced by CD2v protein in African swine fever virus

BackgroundCD2v, a critical outer envelope glycoprotein of the African swine fever virus (ASFV), plays a central role in the hemadsorption phenomenon during ASFV infection and is recognized as an essential immunoprotective protein. Monoclonal antibodies (mAbs) targeting CD2v have demonstrated promise in both diagnosing and combating African swine fever (ASF). The objective of this study was to develop specific monoclonal antibodies against CD2v.MethodsIn this investigation, Recombinant CD2v was expressed in eukaryotic cells, and murine mAbs were generated through meticulous screening and hybridoma cloning. Various techniques, including indirect enzyme-linked immunosorbent assay (ELISA), western blotting, immunofluorescence assay (IFA), and bio-layer interferometry (BLI), were employed to characterize the mAbs. Epitope mapping was conducted using truncation mutants and epitope peptide mapping.ResultsAn optimal antibody pair for a highly sensitive sandwich ELISA was identified, and the antigenic structures recognized by the mAbs were elucidated. Two linear epitopes highly conserved in ASFV genotype II strains, particularly in Chinese endemic strains, were identified, along with a unique glycosylated epitope. Three mAbs, 2B25, 3G25, and 8G1, effectively blocked CD2v-induced NF-κB activation.ConclusionsThis study provides valuable insights into the antigenic structure of ASFV CD2v. The mAbs obtained in this study hold great potential for use in the development of ASF diagnostic strategies, and the identified epitopes may contribute to vaccine development against ASFV