Sequential Star Formation in the filamentary structures of Planck Galactic cold clump G181.84+0.31

We present a multi-wavelength study of the Planck cold clump G181.84+0.31, which is located at the northern end of the extended filamentary structure S242. We have extracted 9 compact dense cores from the SCUBA-2 850 um map, and we have identified 18 young stellar objects (YSOs, 4 Class I and 14 Class II) based on their Spitzer, Wide-field Infrared Survey Explorer (WISE) and Two-Micron All-Sky Survey (2MASS) near- and mid-infrared colours. The dense cores and YSOs are mainly distributed along the filamentary structures of G181.84 and are well traced by HCO$^{+}$(1-0) and N$_{2}$H$^{+}$(1-0) spectral-line emission. We find signatures of sequential star formation activities in G181.84: dense cores and YSOs located in the northern and southern sub-structures are younger than those in the central region. We also detect global velocity gradients of about 0.8$\pm$0.05 km s$^{-1}$pc$^{-1}$ and 1.0$\pm$0.05 km s$^{-1}$pc$^{-1}$ along the northern and southern sub-structures, respectively, and local velocity gradients of 1.2$\pm$0.1 km s$^{-1}$pc$^{-1}$ in the central substructure. These results may be due to the fact that the global collapse of the extended filamentary structure S242 is driven by an edge effect, for which the filament edges collapse first and then further trigger star formation activities inward. We identify three substructures in G181.84 and estimate their critical masses per unit length, which are $\sim$ 101$\pm$15 M$_{\odot}$ pc$^{-1}$, 56$\pm$8 M$_{\odot}$ pc$^{-1}$ and 28$\pm$4 M$_{\odot}$ pc$^{-1}$, respectively. These values are all lower than the observed values ($\sim$ 200 M$_{\odot}$ pc$^{-1}$), suggesting that these sub-structures are gravitationally unstable.Comment: 20 pages, 17 figures, article, accepte

Chemical exploration of Galactic cold cores

Context. A solar-type system starts from an initial molecular core that acquires organic complexity as it evolves. The so-called prestellar cores that can be studied are rare, which has hampered our understanding of how organic chemistry sets in and grows. Aims. We selected the best prestellar core targets from the cold core catalogue (based on Planck and Herschel observations) that represent a diversity in terms of their environment to explore their chemical complexity: 1390 (in the compressed shell of Lambda Ori), 869 (in the MBM12 cloud), and 4149 (in the California nebula). Methods. We obtained a spectral survey with the IRAM 30 m telescope in order to explore the molecular complexity of the cores. We carried out a radiative transfer analysis of the detected transitions in order to place some constraints on the physical conditions of the cores and on the molecular column densities. We also used the molecular ions in the survey to estimate the cosmic-ray ionisation rate and the S/H initial elemental abundance using a gas-phase chemical model to reproduce their abundances. Results. We found large differences in the molecular complexity (deuteration, complex organic molecules, sulphur, carbon chains, and ions) and compared their chemical properties with a cold core and two prestellar cores. The chemical diversity we found in the three cores seems to be correlated with their chemical evolution: two of them are prestellar (1390 and 4149), and one is in an earlier stage (869). Conclusions. The influence of the environment is likely limited because cold cores are strongly shielded from their surroundings. The high extinction prevents interstellar UV radiation from penetrating deeply into the cores. Higher spatial resolution observations of the cores are therefore needed to constrain the physical structure of the cores, as well as a larger-scale distribution of molecular ions to understand the influence of the environment on their molecular complexity.Peer reviewe

Evaluation and Analysis of Hallucination in Large Vision-Language Models

Large Vision-Language Models (LVLMs) have recently achieved remarkable success. However, LVLMs are still plagued by the hallucination problem, which limits the practicality in many scenarios. Hallucination refers to the information of LVLMs' responses that does not exist in the visual input, which poses potential risks of substantial consequences. There has been limited work studying hallucination evaluation in LVLMs. In this paper, we propose Hallucination Evaluation based on Large Language Models (HaELM), an LLM-based hallucination evaluation framework. HaELM achieves an approximate 95% performance comparable to ChatGPT and has additional advantages including low cost, reproducibility, privacy preservation and local deployment. Leveraging the HaELM, we evaluate the hallucination in current LVLMs. Furthermore, we analyze the factors contributing to hallucination in LVLMs and offer helpful suggestions to mitigate the hallucination problem. Our training data and human annotation hallucination data will be made public soon.Comment: 11 pages, 5 figure

Direct training high-performance deep spiking neural networks: a review of theories and methods

Spiking neural networks (SNNs) offer a promising energy-efficient alternative to artificial neural networks (ANNs), in virtue of their high biological plausibility, rich spatial-temporal dynamics, and event-driven computation. The direct training algorithms based on the surrogate gradient method provide sufficient flexibility to design novel SNN architectures and explore the spatial-temporal dynamics of SNNs. According to previous studies, the performance of models is highly dependent on their sizes. Recently, direct training deep SNNs have achieved great progress on both neuromorphic datasets and large-scale static datasets. Notably, transformer-based SNNs show comparable performance with their ANN counterparts. In this paper, we provide a new perspective to summarize the theories and methods for training deep SNNs with high performance in a systematic and comprehensive way, including theory fundamentals, spiking neuron models, advanced SNN models and residual architectures, software frameworks and neuromorphic hardware, applications, and future trends

High Glucose and Lipopolysaccharide Prime NLRP3 Inflammasome via ROS/TXNIP Pathway in Mesangial Cells

While inflammation is considered a central component in the development in diabetic nephropathy, the mechanism remains unclear. The NLRP3 inflammasome acts as both a sensor and a regulator of the inflammatory response. The NLRP3 inflammasome responds to exogenous and endogenous danger signals, resulting in cleavage of procaspase-1 and activation of cytokines IL-1β, IL-18, and IL-33, ultimately triggering an inflammatory cascade reaction. This study observed the expression of NLRP3 inflammasome signaling stimulated by high glucose, lipopolysaccharide, and reactive oxygen species (ROS) inhibitor N-acetyl-L-cysteine in glomerular mesangial cells, aiming to elucidate the mechanism by which the NLRP3 inflammasome signaling pathway may contribute to diabetic nephropathy. We found that the expression of thioredoxin-interacting protein (TXNIP), NLRP3, and IL-1β was observed by immunohistochemistry in vivo. Simultaneously, the mRNA and protein levels of TXNIP, NLRP3, procaspase-1, and IL-1β were significantly induced by high glucose concentration and lipopolysaccharide in a dose-dependent and time-dependent manner in vitro. This induction by both high glucose and lipopolysaccharide was significantly inhibited by N-acetyl-L-cysteine. Our results firstly reveal that high glucose and lipopolysaccharide activate ROS/TXNIP/ NLRP3/IL-1β inflammasome signaling in glomerular mesangial cells, suggesting a mechanism by which inflammation may contribute to the development of diabetic nephropathy

The TOP-SCOPE Survey of Planck Galactic Cold Clumps : Survey Overview and Results of an Exemplar Source, PGCC G26.53+0.17

The low dust temperatures (<14 K) of Planck Galactic cold clumps (PGCCs) make them ideal targets to probe the initial conditions and very early phase of star formation. "TOP-SCOPE" is a joint survey program targeting similar to 2000 PGCCs in J = 1-0 transitions of CO isotopologues and similar to 1000 PGCCs in 850 mu m continuum emission. The objective of the "TOP-SCOPE" survey and the joint surveys (SMT 10 m, KVN 21 m, and NRO 45 m) is to statistically study the initial conditions occurring during star formation and the evolution of molecular clouds, across a wide range of environments. The observations, data analysis, and example science cases for these surveys are introduced with an exemplar source, PGCC G26.53+0.17 (G26), which is a filamentary infrared dark cloud (IRDC). The total mass, length, and mean line mass (M/L) of the G26 filament are similar to 6200 M-circle dot, similar to 12 pc, and similar to 500 M-circle dot pc(-1), respectively. Ten massive clumps, including eight starless ones, are found along the filament. The most massive clump as a whole may still be in global collapse, while its denser part seems to be undergoing expansion owing to outflow feedback. The fragmentation in the G26 filament from cloud scale to clump scale is in agreement with gravitational fragmentation of an isothermal, nonmagnetized, and turbulent supported cylinder. A bimodal behavior in dust emissivity spectral index (beta) distribution is found in G26, suggesting grain growth along the filament. The G26 filament may be formed owing to large-scale compression flows evidenced by the temperature and velocity gradients across its natal cloud.Peer reviewe

Using CO line ratios to trace compressed areas in bubble N131

Aims. N131 is a typical infrared dust bubble showing an expanding ring-like shell. We study the CO line ratios that can be used to trace the interaction in the expanding bubble. Methods. We carried out new CO (3–2) observations toward bubble N131 using the 15 m JCMT, and derived line ratios by combining these observations with our previous CO (2–1) and CO (1–0) data from IRAM 30 m observations. To trace the interaction between the molecular gas and the ionized gas in the HII region, we used RADE

miR-455-3p ameliorates pancreatic acinar cell injury by targeting Slc2a1

Objective With the number of patients with acute pancreatitis (AP) increasing year by year, it is pressing to explore new key genes and markers for the treatment of AP. miR-455-3p/solute carrier family 2 member 1 (Slc2a1) obtained through bioinformatics analysis may participate in the progression of AP. Materials and Methods The C57BL/6 mouse model of AP was constructed for subsequent studies. Through bioinformatics analysis, the differentially expressed genes related to AP were screened and hub genes were identified. A caerulein-induced AP animal model was constructed to detect the pathological changes of mouse pancreas by HE staining. The concentrations of amylase and lipase were measured. Primary mouse pancreatic acinar cells were isolated and subjected to microscopy to observe their morphology. The enzymatic activities of trypsin and amylase were detected. The secretion of inflammatory cytokines in mouse were measured with the ELISA kits of TNF-α, IL-6 and IL-1β to determine pancreatic acinar cell damage. A binding site between the Slc2a1 3′ UTR region and the miR-455-3p sequence was verified by dual-luciferase reporter assay. The expression of miR-455-3p was quantified by qRT-PCR, and Slc2a1 were detected by western blot. Results A total of five (Fyn, Gadd45a, Sdc1, Slc2a1, and Src) were identified by bioinformatics analysis, and miR-455-3p/Slc2a1 were further studied. HE staining results showed that the AP models were successfully established by caerulein induction. In mice with AP, the expression of miR-455-3p was reduced, while that of Slc2a1 was increased. In the caerulein-induced cell model, the expression of Slc2a1 was significantly reduced after intervention of miR-455-3p mimics, whereas increased after miR-455-3p inhibitor treatment. miR-455-3p decreased the secretion of inflammatory cytokines in the cell supernatant, reduced the activity of trypsin and amylase, and alleviated the cell damage induced by caerulein. In addition, Slc2a1 3’UTR region was bound by miR-455-3p, and its protein expression was also regulated. Conclusion miR-455-3p alleviated caerulein-induced mouse pancreatic acinar cell damage by regulating the expression of Slc2a1

Enhancing the Performance of Transformer-based Spiking Neural Networks by Improved Downsampling with Precise Gradient Backpropagation

Deep spiking neural networks (SNNs) have drawn much attention in recent years because of their low power consumption, biological rationality and event-driven property. However, state-of-the-art deep SNNs (including Spikformer and Spikingformer) suffer from a critical challenge related to the imprecise gradient backpropagation. This problem arises from the improper design of downsampling modules in these networks, and greatly hampering the overall model performance. In this paper, we propose ConvBN-MaxPooling-LIF (CML), an improved downsampling with precise gradient backpropagation. We prove that CML can effectively overcome the imprecision of gradient backpropagation from a theoretical perspective. In addition, we evaluate CML on ImageNet, CIFAR10, CIFAR100, CIFAR10-DVS, DVS128-Gesture datasets, and show state-of-the-art performance on all these datasets with significantly enhanced performances compared with Spikingformer. For instance, our model achieves 77.64 $\%$ on ImageNet, 96.04 $\%$ on CIFAR10, 81.4$\%$ on CIFAR10-DVS, with + 1.79$\%$ on ImageNet, +1.54$\%$ on CIFAR100 compared with Spikingformer.Comment: 12 page