Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Structural characterization of arabinan from Pinus radiata cambium tissue : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Biochemistry at Massey University, Palmerston North, New Zealand

Cambium tissue isolated from Pinus radiata was frozen, thawed, washed with cold phosphate buffer, then extracted with phosphate buffer by passage through a French pressure cell. The washings and French press extract were dialyzed. The pectic components partially purified by chromatography on DEAE-cellulose. These polymers bound weakly to DEAE-cellulose at pH 8.0. In both extracts, an early acidic peak of high arabinose and galactose content was separated from a late acidic peak with mostly uronic acid. Within the early acidic peak, successive fractions showed an increase in uronic acid and rhamnose content. Treatment of the extracts with boiling water caused a decrease in binding of the arabinose-rich polymer to the DEAE cellulose reflected by earlier elution, and a minor decrease in average molecular size, consistent with β-elimination of the pectic backbone. The acidic fractions were then further fractionated by gel filtration on Superose and Superdex FPLC columns. The earliest of these acidic fractions had ratios of Ara:Gal:Rha = 30:16:1, this suggesting relatively long side chains of about 46 residues, and were mostly excluded by the Superdex-peptide column. The native molecular mass of the arabinose-rich polymers was determined by size exclusion chromatography and molecular masses of extract A and B were observed to be 40-100 kDa and up to >500 kDa, respectively by Superose and Superdex FPLC columns. Other characterization studies on the arabinan involved quantitative analysis of the monosaccharides derived by sulfuric acid hydrolysis and quantitation of the sugar linkages using methylation analysis. Methylation analysis suggested a highly branched arabinan structure and the presence of terminal galactosyl residues on a branched arabinan core. From the results, a tentative structure has been suggested for the arabinose rich polymers. Arabinose was mainly present as 3-, 5-, 3,5-, and terminal linked residues. Galactose was mainly present as terminal residues

SUGER: A Subgraph-based Graph Convolutional Network Method for Bundle Recommendation

Bundle recommendation is an emerging research direction in the recommender system with the focus on recommending customized bundles of items for users. Although Graph Neural Networks (GNNs) have been applied in this problem and achieve superior performance, existing methods underexplore the graph-level GNN methods, which exhibit great potential in traditional recommender system. Furthermore, they usually lack the transferability from one domain with sufficient supervision to another domain which might suffer from the label scarcity issue. In this work, we propose a subgraph-based Graph Neural Network model, SUGER, for bundle recommendation to handle these limitations. SUGER generates heterogeneous subgraphs around the user-bundle pairs, and then maps those subgraphs to the users' preference predictions via neural relational graph propagation. Experimental results show that SUGER significantly outperforms the state-of-the-art baselines in both the basic and the transfer bundle recommendation problems

Preparation and characterization of novel poly (vinyl alcohol)/collagen double-network hydrogels

Hydrogels prepared by conventional methods show poor performance in many aspects. Many double network (DN) hydrogels prepared by crosslinking agents have disadvantages such as toxicity. In this work, we prepared novel DN hydrogels with fish-originated collagen (Col) and poly (vinyl alcohol) (PVA), in which self-assembly of collagen and self-crosslinking of PVA were achieved. Infrared spectra indicated the existence of double network with chemical interactions between Col and PVA. X-ray diffraction (XRD) patterns showed that characteristic peak of freeze-thaw PVA in DN hydrogel was retained. Scanning electron microscope (SEM) images before and after degradation and swelling property tests indicated that the morphology of the hydrogel was a compact meshwork, which is consistent with the high water-retention rate. The degradation rate of the DN hydrogels was controlled by the ratio of Col and PVA. Compared with a pure collagen hydrogels, the stress of DN hydrogels was greatly enhanced from 6 to 33 kPa at a strain of 40%. This study indicates that DN hydrogels prepared by Col and PVA are an ideal biomaterial for tissue engineering. (C) 2018 Published by Elsevier B.V

Phycocyanin attenuates X-ray-induced pulmonary inflammation via the TLR2-MyD88-NF-κB signaling pathway

Phycocyanin (PC), a natural algal protein, is reported for having anti-oxidant and antiinfl ammatory properties. We investigated its ability to attenuate lung infl ammation in mice subjected to X-ray radiation. Male C57BL/6 mice were assigned to the control, total body irradiation, PC pretreatment, and PC treatment groups. Mice in the PC pretreatment group were gavaged with 200 mg/kg PC for 7 consecutive days before irradiation, and those in the PC treatment group were gavaged with 200 mg/kg PC for 7 consecutive days after irradiation. Lungs were collected on Day 7 after irradiation exposure. Hematoxylin and eosin staining of mouse lung sections showed considerable infl ammation damage 7 days after irradiation compared with the control lung but a reduction in pathological injury in the PC treatment group. Pretreatment or treatment with PC signifi cantly decreased levels of interleukin-6 and tumor necrosis factor-α in the lung, and also increased the relative mRNA expression of superoxide dismutase and glutathione. In vivo, PC signifi cantly reduced the expression of Toll-like receptor TLR2, myeloid diff erentiation primary response Myd88, and nuclear factor NF-κB, at both the transcriptional and translation level. Taken together, these data indicated that PC attenuated lung infl ammatory damage induced by radiation by blocking the TLR2- MyD88-NF-κB signaling pathway. Therefore, PC could be a protective agent against radiation-induced infl ammatory damage in normal tissues

Reconstruction Methods and Complications of Esophagogastrostomy and Jejunal Interposition in Proximal Gastrectomy for Gastric Cancer: A Meta-Analysis

Background. Proximal gastrectomy is used for the treatment of primary gastric cancer by open or laparoscopic surgery in the upper third of the stomach. Esophagogastrostomy (EG) or jejunal interposition (JI) is widely used in various reconstruction methods after proximal gastrectomy. We conducted a meta-analysis of EG and JI for treatment of gastric cancer. Materials and Methods. A search of PubMed, Embase, MEDLINE, J-STAGE, and Cochrane Library identified retrospective series on EG and JI. Weight mean differences (WMDs), odds ratios (ORs), and 95% confidence intervals (CIs) were used to analyze the operation-related data and postoperative complications. Heterogeneity was evaluated by the I2 test, and potential publication bias was assessed with Egger regression tests and sensitivity analysis. Results. Eight studies were selected, and 496 patients were included. EG group benefits were 44.81 min shorter operating time (P<0.001), 56.58 mL less blood loss (P=0.03), and 7.4 days shorter hospital stay time (P<0.001) than the JI group. Between the two groups, there was no significant difference in anastomotic leakage; otherwise, the EG group had a lower risk of anastomotic stenosis (OR=0.44, 95%CI=0.20 to 0.97, P=0.04), lower risk of intestinal obstruction (OR=0.07, 95%CI=0.01 to 0.43, P=0.004), and higher risk of reflux esophagitis (OR=2.47, 95%CI=1.07 to 5.72, P=0.03). Conclusion. The results of our study indicated that EG has significant advantages during the perioperative period and in short-term outcomes compared to JI

MAPK Gene Family in Lactuca sativa: Genome-Wide Identification, Regulatory Network, and Expression Patterns in Stem Development and Stress Responses

Mitogen-activated protein kinases (MAPKs) play essential roles in the process of stress response and plant growth and development. MAPK family genes have been identified in many plant species. In this study, 18 LsMAPK genes were identified in lettuce (Lactuca sativa). The LsMAPK members were divided into Group A, B, C, and D by phylogenetic tree analysis among Arabidopsis, rice, and lettuce. Cis-elements, which relate to abiotic stress, phytohormone response, and transcription factor binding site, were identified to exist in the promoter region of LsMAPK genes. Chromosomal location analysis showed the LsMAPK genes were distributed on eight chromosomes except chromosome 6. Interaction network analysis showed that LsMAPKs could interact with MAPK kinase (MAPKK), protein-tyrosine-phosphatase (PTP), and transcription factors (WRKY, bZIP). Quantitative reverse transcription PCR (qRT-PCR) showed that LsMAPK genes were induced by different abiotic stresses, hormone response, and stem enlargement. The comprehensive identification and characterization of LsMAPK genes in stem lettuce will lay a theoretical foundation for the functional analysis of LsMAPK genes and advance our knowledge of the regulatory mechanism of MAPK genes in plants

Development of hybrid surrogate model structures for design and optimization of CO₂capture processes: Part I. Vacuum pressure swing adsorption in a confined space

Design and optimization of CO2 capture processes have become a tremendously active area of research particularly in the past decade. In this context, development of intelligent techniques on the basis of first-principles models coupled with data-driven algorithms for such purpose looks very promising. In a series of works, we intend to present mechanism approaches in order to develop applicable structures for design and optimization of the CO2 capture processes of interest via hybrid models. A systematic method is presented for optimizing a process for capturing CO2 from a confined space through a Vacuum Pressure Swing Adsorption (VPSA) operation using a Hybrid Surrogate Model (HSM) and Non-dominated Sorting Genetic Algorithm (NSGA-III). The surrogate model is structured based on the VPSA process model offered in the Aspen Adsorption® environment and an artificial intelligence (AI) data-driven algorithm. The developed HSM is then used to predict the key process outputs including CO2 purity, air recovery ratio and energy consumption rate. Accordingly, the optimized parameters are re-substituted into the VPSA process simulator for further data processing. It is demonstrated that the proposed model architecture provides considerable computational efficiency for the process optimization with only 48 h to complete the corresponding evolutionary search, while the optimization time by the conventional NSGA-direct method is close to 1129 h. The optimization results also show that the CO2 purity changes from 1000 ppm to 399 ppm, the air recovery ratio remains at 93 %, and the energy consumption per unit product (ECP) decreases by 38.5 % to 99.7 kJ·Nm−3 air after an optimized air purification operation. The idea of chemical mechanism and industrial data twin modeling in this study holds substantial importance for the development of digital chemical twin systems and the process optimization of intelligent factor

Effect of excessive equatorial Pacific cold tongue bias on the El Nino-Northwest Pacific summer monsoon relationship in CMIP5 multi-model ensemble

El Nino induces an anomalous lower-tropospheric anticyclone over the tropical Northwest Pacific (NWP), accompanied by suppressed local convection and rainfall. The tropical NWP anomalies persist until the following summer, with major effects on the Asian summer monsoons. Based on the phase 5 of the Coupled Model Intercomparison Project (CMIP5) multi-model ensemble, this study finds that climate models commonly underestimate this El Nino-NWP teleconnection with too weak tropical NWP anticyclone and rainfall anomalies in post-El Nino summers, potentially limiting the models' skill in seasonal prediction of the Asian summer monsoons. The analyses show that such underestimated NWP anomalies in post-El Nino summers in CMIP5 models can be traced back to the well-known excessive equatorial Pacific cold tongue error in the mean. Models with an excessive westward extension of Pacific cold tongue tend to displace westward the simulated pattern of El Nino-related warm SST anomalies along the equator. The warm SST biases over the western Pacific in CMIP5 models would enhance the local atmospheric convection/rainfall and induce low-level cyclonic circulation anomalies over the tropical NWP with a Gill-type Rossby wave response, resulting in the commonly underestimated NWP anticyclone and rainfall anomalies during post-El Nino summers. The present results, along with our previous finding that the equatorial cold tongue bias would distort the projections of tropical Pacific warming pattern under increased greenhouse gas scenario, imply that reducing equatorial cold tongue bias in models can substantially improve climate simulation and prediction/projection for the tropical Pacific and Asian monsoons