Dissecting the γ\gamma-ray emissions of the nearby galaxies NGC 1068 and NGC 253

Intrigued by recent high-energy study results for nearby galaxies with gamma-ray emission and in particular NGC~1068 that has been detected as a neutrino-emitting source by the IceCube Neutrino Observatory, we conduct detailed analysis of the $\gamma$-ray data for the galaxies NGC~1068 and NGC~253, obtained with the Large Area Telescope onboard {\it the Fermi Gamma-ray Space Telescope}. By checking for their possible spectral features and then constructing light curves in corresponding energy ranges, we identify flare-like activity from NGC ~1068 in $\geq$2\,GeV energy range and significant long-term variations of NGC~253 in $\geq$5\,GeV energy range. In the former, the emission appears harder in the two half-year flare-like events than that in the otherwise `quiescent' state. In the latter, there is a 2-times decrease in the flux before and after MJD~57023, which is clearly revealed by the test-statistic maps we obtain. Considering studies carried out and models proposed for the $\gamma$-ray emissions of the two sources, we discuss the implications of our findings. The jet in NGC~1068 may contribute to the \gr\ emission. The nature of the long-term variations in NGC~253 is not clear, but the variation part of the emission may be connected to the very-high-energy (VHE) emission of the galaxy and could be verified by VHE observations.Comment: 9 pages, 6 figures, 2 tables, submitted to Ap

Mobility Accelerates Learning: Convergence Analysis on Hierarchical Federated Learning in Vehicular Networks

Hierarchical federated learning (HFL) enables distributed training of models across multiple devices with the help of several edge servers and a cloud edge server in a privacy-preserving manner. In this paper, we consider HFL with highly mobile devices, mainly targeting at vehicular networks. Through convergence analysis, we show that mobility influences the convergence speed by both fusing the edge data and shuffling the edge models. While mobility is usually considered as a challenge from the perspective of communication, we prove that it increases the convergence speed of HFL with edge-level heterogeneous data, since more diverse data can be incorporated. Furthermore, we demonstrate that a higher speed leads to faster convergence, since it accelerates the fusion of data. Simulation results show that mobility increases the model accuracy of HFL by up to 15.1% when training a convolutional neural network on the CIFAR-10 dataset.Comment: Submitted to IEEE for possible publicatio

Graph based Label Enhancement for Multi-instance Multi-label learning

Multi-instance multi-label (MIML) learning is widely applicated in numerous domains, such as the image classification where one image contains multiple instances correlated with multiple logic labels simultaneously. The related labels in existing MIML are all assumed as logical labels with equal significance. However, in practical applications in MIML, significance of each label for multiple instances per bag (such as an image) is significant different. Ignoring labeling significance will greatly lose the semantic information of the object, so that MIML is not applicable in complex scenes with a poor learning performance. To this end, this paper proposed a novel MIML framework based on graph label enhancement, namely GLEMIML, to improve the classification performance of MIML by leveraging label significance. GLEMIML first recognizes the correlations among instances by establishing the graph and then migrates the implicit information mined from the feature space to the label space via nonlinear mapping, thus recovering the label significance. Finally, GLEMIML is trained on the enhanced data through matching and interaction mechanisms. GLEMIML (AvgRank: 1.44) can effectively improve the performance of MIML by mining the label distribution mechanism and show better results than the SOTA method (AvgRank: 2.92) on multiple benchmark datasets.Comment: 7 pages,2 figure

A study of 10 Rotating Radio Transients using Parkes radio telescope

Rotating Radio Transients (RRATs) are a relatively new subclass of pulsars that emit detectable radio bursts sporadically. We conducted an analysis of 10 RRATs observed using the Parkes telescope, with 8 of these observed via the Ultra-Wideband Receiver. We measured the burst rate and produced integrated profiles spanning multiple frequency bands for 3 RRATs. We also conducted a spectral analysis on both integrated pulses and individual pulses of 3 RRATs. All of their integrated pulses follow a simple power law, consistent with the known range of pulsar spectral indices. Their average spectral indices of single pulses are -0.9, -1.2, and -1.0 respectively, which are within the known range of pulsar spectral indices. Additionally, we find that the spreads of single-pulse spectral indices for these RRATs (ranging from -3.5 to +0.5) are narrower compared to what has been observed in other RRATs (Shapiro-Albert et al. 2018; Xie et al. 2022). It is notable that the average spectral index and scatter of single pulses are both relatively small. For the remaining 5 RRATs observed at the UWL receiver, we also provided the upper limits on fluence and flux density. In addition, we obtained the timing solution of PSR J1709-43. Our analysis shows that PSRs J1919+1745, J1709-43 and J1649-4653 are potentially nulling pulsars or weak pulsars with sparse strong pulses.Comment: 16 pages, 8 figures, RAA accepte

Comparison of 68Ga-FAP-2286 and 18F-FDG PET/CT in the diagnosis of advanced lung cancer

PurposeThe 68Ga/177Lu-FAP-2286 is a newly developed tumor imaging agent that shows potential for visualizing and treating tumor stroma. The objective of this research was to evaluate the effectiveness of 68Ga-FAP-2286 PET/CT and 18F-FDG PET/CT in diagnosing advanced lung cancer.MethodsIn this prospective study, patients with lung cancer who underwent 68Ga-FAP-2286 and 18F-FDG PET/CT examinations between September 2022 and June 2023 were analyzed. Lesion uptake was converted to SUVmax. A paired T-test was used to compare the SUVmax, and the number of positive lesions detected by the two methods was recorded.ResultsIn total, 31 participants (median age: 56 years) were assessed. The uptake of 68Ga-FAP-2286 was significantly higher than that of 18F-FDG in primary lesions (9.90 ± 5.61 vs. 6.09 ± 2.84, respectively, P < 0.001), lymph nodes (7.95 ± 2.75 vs. 5.55 ± 1.59, respectively, P=0.01), and bone metastases (7.74 ± 3.72 vs. 5.66 ± 3.55, respectively, P=0.04). Furthermore, the detection sensitivity of lymph nodes using 68Ga-FAP-2286 PET/CT was superior to that with 18F-FDG PET/CT [100% (137/137) vs. 78.8% (108/137), respectively], as well as for bone metastases [100% (384/384) vs. 68.5% (263/384), respectively]. However, the detection sensitivity for primary tumors using both modalities was comparable [100% (13/13) for both].ConclusionCompared to 18F-FDG PET/CT, 68Ga-FAP-2286 PET/CT demonstrated better lesion detection capabilities for lung cancer, particularly in lymph nodes and bone metastases, providing compelling imaging evidence for the efficacy of 177Lu-FAP-2286 treatment

A bibliometric analysis based on hotspots and frontier trends of positron emission tomography/computed tomography utility in bone and soft tissue sarcoma

PurposeThis study aimed to analyze articles on the diagnosis and treatment of bone and soft tissue sarcoma using positron emission tomography (PET)/computed tomography (CT) published in the last 13 years. The objective was to conduct a bibliometric analysis and identify the research hotspots and emerging trends.MethodsWeb of Science was used to search for articles on PET/CT diagnosis and treatment of bone and soft tissue sarcoma published from January 2010 to June 2023. CiteSpace was utilized to import data for bibliometric analysis.ResultsIn total, 425 relevant publications were identified. Publications have maintained a relatively stable growth rate for the past 13 years. The USA has the highest number of published articles (139) and the highest centrality (0.35). The UDICE-French Research Universities group is the most influential institution. BYUN BH is a prominent contributor to this field. The Journal of Clinical Oncology has the highest impact factor in the field.ConclusionThe clinical application of PET/CT is currently a research hotspot. Upcoming areas of study concentrate on the merging of PET/CT with advanced machine learning and/or alternative imaging methods, novel imaging substances, and the fusion of diagnosis and therapy. The use of PET/CT has progressively become a crucial element in the identification and management of sarcomas. To confirm its efficacy, there is a need for extensive, multicenter, prospective studies

Multi-dark-state resonances in cold multi-Zeeman-sublevel atoms

We present our experimental and theoretical studies of multi-dark-state resonances (MDSRs) generated in a unique cold rubidium atomic system with only one coupling laser beam. Such MDSRs are caused by different transition strengths of the strong coupling beam connecting different Zeeman sublevels. Controlling the transparency windows in such electromagnetically induced transparency system can have potential applications in multi-wavelength optical communication and quantum information processing.Comment: 11pages, 4figure

X-ray radiation and runaway electron beams generated during discharges in atmospheric-pressure air at rise times of voltage pulse of 500 and 50 ns

The parameters of X-ray radiation and runaway electron beams (RAEBs) generated at long-pulse discharges in atmospheric-pressure air were investigated. In the experiments, high-voltage pulses with the rise times of 500 and 50 ns were applied to an interelectrode gap. The gap geometry provided non-uniform distribution of the electric field strength. It was founded that at the voltage pulse rise time of 500 ns and the maximum breakdown voltage Um for 1 cm-length gap, a duration [full width at half maximum (FWHM)] of a RAEB current pulse shrinks to 0.1 ns. A decrease in the breakdown voltage under conditions of a diffuse dischargeleads to an increase in the FWHM duration of the electron beam current pulse up to several nanoseconds. It was shown that when the rise time of the voltage pulse is of 500 ns and thediffuse discharge occurs in the gap, the FWHM duration of the X-ray radiation pulse canreach≈100 ns. It was established that at a pulse-periodic diffuse discharge fed by high-voltage pulses with the rise time of 50 ns, an energy of X-ray quanta and their number increase with increasing breakdown voltage. Wherein the parameter Um/pd is saved

Dmbg-Net: Dilated multiresidual boundary guidance network for COVID-19 infection segmentation

Accurate segmentation of infected regions in lung computed tomography (CT) images is essential for the detection and diagnosis of coronavirus disease 2019 (COVID-19). However, lung lesion segmentation has some challenges, such as obscure boundaries, low contrast and scattered infection areas. In this paper, the dilated multiresidual boundary guidance network (Dmbg-Net) is proposed for COVID-19 infection segmentation in CT images of the lungs. This method focuses on semantic relationship modelling and boundary detail guidance. First, to effectively minimize the loss of significant features, a dilated residual block is substituted for a convolutional operation, and dilated convolutions are employed to expand the receptive field of the convolution kernel. Second, an edge-attention guidance preservation block is designed to incorporate boundary guidance of low-level features into feature integration, which is conducive to extracting the boundaries of the region of interest. Third, the various depths of features are used to generate the final prediction, and the utilization of a progressive multi-scale supervision strategy facilitates enhanced representations and highly accurate saliency maps. The proposed method is used to analyze COVID-19 datasets, and the experimental results reveal that the proposed method has a Dice similarity coefficient of 85.6% and a sensitivity of 84.2%. Extensive experimental results and ablation studies have shown the effectiveness of Dmbg-Net. Therefore, the proposed method has a potential application in the detection, labeling and segmentation of other lesion areas