Molecular Gas and Star formation in ARP 302

We present the Submillimeter Array observation of the CO J=2-1 transition towards the northern galaxy, ARP 302N, of the early merging system, ARP 302. Our high angular resolution observation reveals the extended spatial distribution of the molecular gas in ARP 302N. We find that the molecular gas has a very asymmetric distribution with two strong concentrations on either side of the center together with a weaker one offset by about 8 kpc to the north. The molecular gas distribution is also found to be consistent with that from the hot dust as traced by the 24 micro continuum emission observed by the Spitzer. The line ratio of CO J=2-1/1-0 is found to vary strongly from about 0.7 near the galaxy center to 0.4 in the outer part of the galaxy. Excitation analysis suggests that the gas density is low, less than 10$^3$ cm$^{-3}$, over the entire galaxy. By fitting the SED of ARP 302N in the far infrared we obtain a dust temperature of $T\rm_d$=26-36 K and a dust mass of M$\rm _{dust}$=2.0--3.6$\times10^8$ M$\rm_\odot$. The spectral index of the radio continuum is around 0.9. The spatial distribution and spectral index of the radio continuum emission suggests that most of the radio continuum emission is synchrotron emission from the star forming regions at the nucleus and ARP302N-cm. The good spatial correspondance between the 3.6 cm radio continuum emission, the Spitzer 8 & 24 $\mu$m data and the high resolution CO J=2-1 observation from the SMA shows that there is the asymmetrical star forming activities in ARP 302N.Comment: 19 pages, 8 figures, accepted by A

Geometric Multi-Model Fitting by Deep Reinforcement Learning

This paper deals with the geometric multi-model fitting from noisy, unstructured point set data (e.g., laser scanned point clouds). We formulate multi-model fitting problem as a sequential decision making process. We then use a deep reinforcement learning algorithm to learn the optimal decisions towards the best fitting result. In this paper, we have compared our method against the state-of-the-art on simulated data. The results demonstrated that our approach significantly reduced the number of fitting iterations

Search for High-Mass Protostellar Objects in Cold IRAS Sources

We present the results of CS J=2-1 mapping observations towards 39 massive star-forming regions selected from the previous CO line survey of cold IRAS sources with high-velocity CO flows along the Galactic plane (Yang et al. 2002). All sources are detected in CS J=2-1 showing the existence of CS clumps around the IRAS sources. However, one-third of the sources are not deeply embedded in the dense clumps by comparison of the central powering IRAS sources and the morphologies of CS clumps. Physical parameters of the dense molecular clumps are presented. We have identified 12 high-mass protostellar object (HMPO) candidates by checking the association between the dense cores and the IRAS sources, the detection of water maser, and the radio properties towards the IRAS sources. We find that the HMPO sources are characterized by low FIR luminosity to virial mass ratios since they are in very early evolutionary stages when the massive protostars have not reached their full luminosities, which are typical for zero-age main sequence stars. Large turbulent motion in the HMPO sources may be largely due to the large kinetic energy ejected by the central protostars formed in the dense clumps. However, alternative means or undetected outflows may also be responsible for the turbulence in the clumps.Comment: 20 pages, 4 figures, accepted for publication in A

Protective effect of alcohol extract of Yulangsan leaf on chemically-induced liver injury in mice

Purpose: To investigate the protective effect of Millettia pulchra Kurz var. Laxior (Dunn) Z. Wei (Yulangsan) leaf (YLSL) on chemically-induced liver injury in mice.Methods: Models of carbon tetrachloride (CCl4) and D-galactosamine (D-GalN)-induced liver injury in Kunming mice were prepared by intraperitoneal injection. Sixty mice were randomly divided into normal saline (NS) group, liver-injury group, low-, medium- and high-dose YLSL groups (7.5, 15 and 30 g/kg dose, respectively), and biphenyldicarboxylate (BPDC) group, with 10 animals per group. Indices for liver, spleen and thymus were assessed. Serum aspartate transaminase (AST) and alanine aminotransferase (ALT) activities, levels of malondialdehyde (MDA) in liver tissues and reduced glutathione (GSH) as well as activities of superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) in liver tissue were assayed. Liver tissue damage was assessed histologically.Results: YLSL could significantly decrease the elevation of AST or ALT in liver injuries induced by CCl4 or D-GalN in mice, which showed a dose-effect relationship obviously. The high dose YLSL significantly decreased thymus weight relative to CCl4 and D-GalN (CCL4 CCL4+YLSL: 4.4213 ± 1.0544 vs 3.7120 ± 0.8534; D-GalN vs YLSL + D-GalN: 3.7272 ± 1.1655 vs 1.9548 ± 1.2996, p < 0.01). However, SOD activity was significantly increased (p < 0.01, p < 0.05). In treatment groups exposed to CCl4, GSH-Px activity was significantly increased (p < 0.01) and GSH levels decreased (middle dose group and positive control group). In treatment groups with D-GalN, GSH content was significantly increased (p < 0.01 or p < 0.05), while GSH-Px activity decreased (p <0.01).Conclusion: YLSL has protective effect against chemically-induced liver injury in mice. The mechanism may be related to attenuation of free radical-induced lipid peroxidation.Keywords: Millettia pulchra, Liver injury, Biochemical parameters, Thymus, Antioxidant, Dgalactosamine, Biphenyldicarboxylat

Resource Allocation for Capacity Optimization in Joint Source-Channel Coding Systems

Benefited from the advances of deep learning (DL) techniques, deep joint source-channel coding (JSCC) has shown its great potential to improve the performance of wireless transmission. However, most of the existing works focus on the DL-based transceiver design of the JSCC model, while ignoring the resource allocation problem in wireless systems. In this paper, we consider a downlink resource allocation problem, where a base station (BS) jointly optimizes the compression ratio (CR) and power allocation as well as resource block (RB) assignment of each user according to the latency and performance constraints to maximize the number of users that successfully receive their requested content with desired quality. To solve this problem, we first decompose it into two subproblems without loss of optimality. The first subproblem is to minimize the required transmission power for each user under given RB allocation. We derive the closed-form expression of the optimal transmit power by searching the maximum feasible compression ratio. The second one aims at maximizing the number of supported users through optimal user-RB pairing, which we solve by utilizing bisection search as well as Karmarka' s algorithm. Simulation results validate the effectiveness of the proposed resource allocation method in terms of the number of satisfied users with given resources.Comment: 6 pages, 6 figure

Preparation of magnetic chitosan corn straw biochar and its application in adsorption of amaranth dye in aqueous solution

In this study, the magnetic chitosan biochar (MCB) was magnetized by chemical coprecipitation after loading chitosan with Schiff base reaction. The prepared MCB was used to remove amaranth dye in solution. The synthesized MCB was characterized to define its surface morphology and specific elements. The amaranth dye adsorption system was optimized by varying the contact time, pH, and initial concentration. The adsorption of MCB on amaranth dye was measured in a wide pH range. According to Zeta potential, the surface of MCB was positively charged in the acidic pH region, which was more conducive to the adsorption of anionic amaranth dye. In addition, the adsorption data was fitted with the pseudo-first-order model and Langmuir adsorption model and the maximum adsorption capacity reached 404.18 mg/g. The adsorption efficiency of MCB was still above 95% after three cycles of adsorption and desorption. The removal percentage in the real sample of amaranth dye by MCB was within 94.5–98.6% and the RSD was within 0.14–1.08%. The MCB adsorbent with advantages of being easy to prepare, easy to separate from solution after adsorption, has good adsorption performance for amaranth dye and is effective potential adsorbent to remove organic anionic dye in wastewater

Higher-order Graph Attention Network for Stock Selection with Joint Analysis

Stock selection is important for investors to construct profitable portfolios. Graph neural networks (GNNs) are increasingly attracting researchers for stock prediction due to their strong ability of relation modelling and generalisation. However, the existing GNN methods only focus on simple pairwise stock relation and do not capture complex higher-order structures modelling relations more than two nodes. In addition, they only consider factors of technical analysis and overlook factors of fundamental analysis that can affect the stock trend significantly. Motivated by them, we propose higher-order graph attention network with joint analysis (H-GAT). H-GAT is able to capture higher-order structures and jointly incorporate factors of fundamental analysis with factors of technical analysis. Specifically, the sequential layer of H-GAT take both types of factors as the input of a long-short term memory model. The relation embedding layer of H-GAT constructs a higher-order graph and learn node embedding with GAT. We then predict the ranks of stock return. Extensive experiments demonstrate the superiority of our H-GAT method on the profitability test and Sharp ratio over both NSDAQ and NYSE datasetsComment: 12 pages, 6 figures