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Immune cells have many efficient ways to participate in the host immunity, including phagocytosis, which is an important pathway to eliminate pathogens. Only β-integrin-mediated phagocytosis pathways have been confirmed in Apostichopus japonicus. The Src family kinases (SFKs), a class of non-receptor tyrosine kinases plays an important role in the regulation of phagocytic signals in invertebrates. However, the SFK-mediated phagocytic mechanism is largely unknown in A. japonicus. In this study, a novel SFK homologue (AjSrc) with a conservative SH

In this paper, the experiment of titanium powder explosion was carried out by using Hartmann and 20-L spherical explosion tank. The inhibition effect of different proportions of Ca(H2PO4)2 and CaCO3 powders on titanium powder explosion was studied, and the inhibition mechanism of inhibitor on titanium powder explosion was analyzed. The experimental results show that with the increase of the proportion of inhibitors, the flame brightness becomes darker, the propagation velocity and distance decrease gradually, and the Pex and (dp/dt)ex decrease gradually. When 80% Ca(H2PO4)2 and CaCO3 were added, the average flame propagation speed decreased to 0.59 m/s and 1.08 m/s, respectively, and decreased by 87.7% and 77.4%; the Pex decreased to 0.152 MPa and 0.206 MPa, respectively, and decreased by 80% and 72.9%. The results show that both Ca(H2PO4)2 and CaCO3 have certain inhibition effect on titanium powder explosion, and the inhibition effect of Ca(H2PO4)2 is better.

More than half of the world's food is provided by cereals, as humans obtain60% of daily calories from grains. Producing more carbohydrates is always the final target of crop cultivation. The carbohydrate partitioning pathway directly affects grain yield, but the molecular mechanisms and biological functions are poorly understood, including rice (Oryza sativa L.), one of the most important food sources. Here, we reported a prolonged grain filling duration mutant 1 (gfd1), exhibiting a long grain filling duration, less grain number per panicle, and bigger grain size without changing grain weight. Map-based cloning and molecular biological analyses revealed that GFD1 encoded a MATE transporter and expressed high in vascular tissues of the stem, spikelet hulls, and rachilla, but low in the leaf, controlling carbohydrate partitioning in the stem and grain but not in the leaf. GFD1 protein was partially localized on the plasma membrane and in the Golgi apparatus, and was finally verified to interact with two sugar transporters, OsSWEET4 and OsSUT2. Genetics analyses showed that GFD1 might control grain filling duration through OsSWEET4, adjust grain size with OsSUT2, and synergistically modulate grain number per panicle with both OsSUT2 and OsSWEET4. Together, our work proved that, the three transporters, which are all initially classified in the MFS family, could control starch storage in both the primary sink (grain) and temporary sink (stem), and affect carbohydrate partitioning in the whole plant through physical interaction, giving a new vision of sugar transporter interactome and providing a tool for rice yield improvement.

The growing number of papers on Responsible Innovation (RI) and Responsible Research and Innovation (RRI) have shaped the popularity and usefulness of RI and RRI as a technology governance concept. This study reviews and assesses the development of RRI research through a bibliometric analysis of 702 RRI-focused papers and 26,471 secondary references published in the Web of Science Core Collection database between 2006 and 2020. Firstly, the paper provides a broad outline of the field based on annual growth trends, journal distribution, and disciplinary distribution for RRI publications. Secondly, this study reveals the current state of RRI research by identifying influential literature, journals, authors, countries, and institutions. Thirdly, a phased keyword analysis is conducted to determine the stage characteristics of the RRI field. Finally, based on the bibliometric analyses, this study summarises the evolutionary trajectory of RRI and makes recommendations for future research directions. As a complement to the previous qualitative literature review, the paper provides a systematic and dynamic understanding of RRI research.

The digitalization of the automobile industry must depend on the information technology industry. The coupling development of the two creates conditions for the realization of industry 4.0 and intelligent manufacturing. The purpose of this paper is to make an empirical study on the possibility of coupling and the coupling degree, correlation degree, and innovation ability of China’s automobile industry and information technology industry. This paper takes the intelligent manufacturing of the automobile industry as the research object. According to the current situation of China’s automobile industry, this paper uses data to analyze and predict the development level of China’s automobile industry and the gap with the foreign automobile industry. Firstly, it summarizes and analyzes the development of China’s automobile industry and information technology industry. Then, the gray correlation analysis method is used to explore the factors affecting the innovation of China’s automobile industry. It is found that the relationship between capital investment and innovation is the most significant in “industrial innovation investment.” Finally, the coupling development model of the automobile industry and information technology industry is established, and the coupling degree of the two is analyzed by using the analytic hierarchy process and the Delphi method. The research of this paper mainly focuses on the automobile industry. Under the wave of internet, other industries such as the commerce and service industry also have a strong coupling relationship with the information technology industry, which will provide a new research direction for the follow-up research of experts and scholars.

Cysteine functions not only as an amino acid in proteins but also as a precursor for a large number of essential biomolecules. Cysteine is synthesized via the incorporation of sulfide to O-acetylserine under the catalysis of O-acetylserine(thiol)lyase (OASTL). In dicotyledonous Arabidopsis, nine OASTL genes have been reported. However, in their null mutants, only the mutant of CS26 encoding S-sulfocysteine synthase showed the visible phenotypic changes, displaying significantly small plants and pale-green leaves under long-day condition but not short-day condition. Up to now, no OASTL gene or mutant has been identified in monocotyledon. In this study, we isolated a green-revertible albino mutant gra78 in rice (Oryza sativa). Its albino phenotype at the early seedling stage was sensitive to temperature but independent of photoperiod. Map-based cloning revealed that candidate gene LOC_Os01g59920 of GRA78 encodes a putative S-sulfocysteine synthase showing significant similarity with Arabidopsis CS26. Complementation experiment confirmed that mutation in LOC_Os01g59920 accounted for the mutant phenotype of gra78. GRA78 is constitutively expressed in all tissues and its encoded protein is targeted to the chloroplast. In addition, qRT-PCR suggested that expression levels of four OASTL homolog genes and five photosynthetic genes were remarkably down-regulated.

An important aspect of oil spill science is understanding how the compounds within spilled oil, especially toxic components, change with weathering. In this study we follow the evolution of petroleum hydrocarbons, including n-alkanes, polycyclic aromatic hydrocarbons (PAHs) and alkylated PAHs, on a Louisiana beach and salt marsh for three years following the Deepwater Horizon spill. Relative to source oil, we report overall depletion of low molecular weight n-alkanes and PAHs in all locations with time. The magnitude of depletion, however, depends on the sampling location, whereby sites with highest wave energy have highest compound depletion. Oiled sediment from an enclosed bay shows high enrichment of high molecular weight PAHs relative to 17α(H),21β(H)-hopane, suggesting the contribution from sources other than the Deepwater Horizon spill, such as fossil fuel burning. This insight into hydrocarbon persistence as a function of hydrography and hydrocarbon source can inform policy and response for future spills.

As a ubiquitously expressed protein, cyclophilin A (CypA) is involved in a variety of pathological process, including immune suppression, inflammation, cell apoptosis, viral infection and stress response. However, the functional roles of CypA were largely unknown in economic marine animals. In this report, a novel CypA gene from sea cucumber Apostichopus japonicus (designated as AjCypA) was cloned and its function roles in immune responses were explored. The full-length cDNA of AjCypA was 1297 bp containing an open reading frame of 489 bp encoding a putative protein of 162 amino acids (aa). A conserved cyclophilin-like domain (CLD) with PPIase signature was located from 5 to 155 aa sequences in AjCypA, in which five necessary aa residues was totally conserved. In healthy sea cucumbers, AjCypA was expressed in all detected tissues, with highly expressed in muscles and weakly expressed in coelomocytes. AjCypA transcripts was significantly induced 8.08-fold and 5.65-fold in coelomocytes when sea cucumbers challenged with Vibrio splendidus in vivo and LPS in vitro, respectively. The expression pattern is similar with the expression of AjRel in the same condition. Moreover, GST pull-down and immunofluorescence analysis both revealed that AjCypA might be interacted with AjRel. Furthermore, AjCypA knockdown not only inhibited the expression of inflammation cytokines, but also suppressed the translocation of AjRel in nucleus induced by LPS. Taken together, our results suggested that AjCypA play key roles in V. splendidus mediated immune responses via suppressing the nuclear translocation of AjRel activity in sea cucumber.

This study evaluated impacts of the BP Deepwater Horizon ( DWH ) oil spill on petroleum hydrocarbons in surface waters of the Louisiana continental shelf in northern Gulf of Mexico. Surface water (~top 5 cm) without visible oil was collected from three cruises in May 2010 during the oil spill, August 2010 after the well was capped, and May 2011 one year after the spill. Concentrations of total dissolved n -alkanes (C 9 –C 35 ) in surface seawater were more than an order of magnitude higher in May 2010 than August 2010 and May 2011, indicating contamination by the DWH oil spill. This conclusion was further supported by more abundant smaller n -alkanes (C 9 –C 13 ), together with pristane and phytane, in May than August 2010 samples. In contrast, even carbon-numbered dissolved n -alkanes (C 14 –C 20 ) dominated the May 2011 samples, and this distribution pattern of dissolved n -alkanes is the first documentation for water samples in the northern Gulf of Mexico. However, this pattern was not observed in May 2011 suspended particles except for Sta. OSS. This decoupling between dissolved and particle compositions suggests that either these even carbon-numbered n -alkanes originated from bacteria rather than algae, or that the alkanes in the shelf were transported from elsewhere. Concentrations of polycyclic aromatic hydrocarbons (PAHs) in suspended particles were 5 times higher on average in May 2010 (83–252 ng L −1 ) than May 2011 (7.2–83 ng L −1 ), also indicating contamination by the DWH oil spill. Application of a biomarker ratio of 17α(H),21β(H)-30-norhopane over 17α(H),21β(H)-hopane confirmed that suspended particles from at least two stations were contaminated by the DWH oil spill in May 2010. Taken together, these results showed that surface waters of the sampling area in May 2010 were contaminated by the oil spill, but also that rapid weathering and/or physical dilution quickly reduced hydrocarbon levels by August 2010.

With the development and application of Internet technology, investors usually use Internet search engine to investigate the corporation and related information before making investment decision. As a result, Internet search engine has become an indicator of investors’ attention. This paper uses FinTech Baidu index derived from Baidu public platform to measure investors' attention, as well as FinTech index from Shenzhen stock exchange, whose index code is 399699. SZ. The index data covers a date range from June 9, 2017 to June 30, 2019. Empirically, this paper discusses the impact of online attention on the stock returns of financial science and technology sector. A vector auto-regressive (VAR) model is built to reveal the correlation between Fintech investor attention and its sector returns. Furthermore, the granger causality, impulse response and variance decomposition are analyzed. Granger causality test result indicates that FinTech investor attention is the granger cause of the stock returns of Fintech sector, and conversely the stock returns of Fintech sector are not the cause of FinTech investor attention. That is, FinTech online attention has a certain impact on the stock returns of Fintech sector. Impulse response indicates that the impact of FinTech online attention is positive, but the effect lasts in a short term. The conclusions play an important role for investors to understand the hotspot attention on FinTech which is a new emerging market investment opportunity, and provide a general knowledge about the relation between Fintech attention and market returns.

Understanding bacterial community dynamics as a result of an oil spill is important for predicting the fate of oil released to the environment and developing bioremediation strategies in the Gulf of Mexico. In this study, we aimed to elucidate the roles of temperature, water chemistry (nutrients), and initial bacterial community in selecting oil degraders through a series of incubation experiments. Surface (2 m) and bottom (1537 m) water, collected near the Deepwater Horizon site, were amended with 200 ppm light Louisiana sweet crude oil and bacterial inoculums from surface or bottom water, and incubated at 4oC or 24°C for 50 d. Bacterial community and residual oil were analyzed by pyrosequencing and gas chromatography-mass spectrometry (GC-MS), respectively. The results showed that temperature played a key role in selecting oil-degrading bacteria. Incubation at 4°C favored the development of Cycloclasticus, Pseudoalteromonas, Sulfitobacter and Reinekea, while 24°C incubations enhanced Oleibacter, Thalassobius, Phaeobacter, and Roseobacter. Water chemistry and the initial community have also potential roles in the development of hydrocarbon-degrading bacterial communities. Pseudoalteromonas, Oleibacter, and Winowgradskyella developed well in the nutrient-enriched bottom water, while Reinekea and Thalassobius were favored by low-nutrient surface water. We also revealed that the combination of 4°C, crude oil and bottom inoculum was a key factor for the growth of Cycloclasticus, while the combination of surface inoculum and bottom water chemistry was important for the growth of Pseudoalteromonas. Moreover, regardless of the source of inoculum, bottom water at 24°C was a favorable condition for Oleibacter. Redundancy analysis further revealed that temperature and initial community explained 57% and 19% of the variation observed, while oil and water chemistry contributed 14% and 10%, respectively. Overall, this study revealed the relative roles of temperature, water chemistry, and initial bacterial community in selecting oil degraders and regulating their evolution in the northern Gulf of Mexico.

Understanding the mechanisms of organic matter decomposition in hypoxic waters becomes more important globally with increasing hypoxia in coastal regions. Peptide decomposition rates were measured in low-oxygen bottom water and compared to those in oxygenated surface water of a stratified 18-m water column at a hypoxic northern Gulf of Mexico station. Water from each depth was spiked with small peptides alanine–valine–phenylalanine–alanine (AVFA) and VFA and incubated onboard for ca. 80 h to determine peptide decomposition rates, decomposition products, and bacterial community structure shifts. Decomposition rates of amended peptides were twice as high in the bottom water as in the surface water, and the pathways of peptide decomposition differed. In surface waters, the small peptides were hydrolyzed into individual amino acids extracellularly by aminopeptidase, based on the analysis of hydrolyzed fragments; hydrolysis rates remained constant throughout the incubation period. In contrast, in bottom waters the amended peptides were metabolized rapidly into ammonium by bacteria through either direct uptake or tight coupling of extracellular hydrolysis and subsequent uptake after an initial adaptation period (~ 22 h). Dissolved oxygen level did not affect peptide decomposition patterns significantly in surface or bottom water, when it was manipulated by sparging with air or nitrogen gas. The high efficiency of peptide decomposition in bottom waters corresponded to the rapid growth of several genera of Alpha- and Gammaproteobacteria. These bacterial species may have caused rapid peptide decomposition, but the exact mechanisms remain unclear. The high efficiency of peptide decomposition in hypoxic regions illustrates biogeochemical feedback to hypoxia formation in stratified coastal regions.

This paper focuses on the comparison between two fusion methods, namely early fusion and late fusion. The former fusion is carried out at kernel level, also known as multiple kernel learning, and in the latter, the modalities are fused through logistic regression at classifier score level. Two kinds of multilayer fusion structures, differing in the quantities of feature/kernel groups in a lower fusion layer, are constructed for early and late fusion systems, respectively. The goal of these fusion methods is to put each of various features into effect and mine redundant information of the combination of them, and then to develop a generic and robust semantic indexing system to bridge semantic gap between human concepts and these low-level visual features. Performance evaluated on both TRECVID2009 and TRECVID2010 datasets demonstrates that the systems with our proposed multilayer fusion methods at kernel level perform more stably to reach the goal than the classification-score-level fusion; the most effective and robust one with highest MAP score is constructed by early fusion with two-layer equally weighted composite kernel learning.

Over the past 5 years, raphidophyte blooms have been frequently observed along the South Carolina coastal zone. During the 2002, 2003, and 2004 sampling seasons, we investigated temporal fluctuations of algicidal bacteria abundance against raphidophycean flagellates (Heterosigma akashiwo, Chattonella subsalsa, and Fibrocapsa japonica) using the microplate most probable number (MPN) method in three Kiawah Island brackish stormwater detention ponds (K1, K2, and K75). Local axenic isolates of H. akashiwo, C. subsalsa, and F. japonica were obtained and their susceptibility to algicidal bacteria tested. A total of 195 algicidal bacterial strains were isolated from raphidophyte blooms in the study ponds, and 6 of them were identified at the genus level, and the taxonomic specificity of their algicidal activity was tested against local (pond) and nonlocal isolates of raphidophytes (3 species, 10 total strains). In the ponds, a consistent association was found between raphidophyte bloom development and an increase in bacteria algicidal to the bloom species. In 12 of 15 cases, bloom decline followed the increase in algicidal bacteria to maximum abundances. Although variability was found in the taxonomic specificity of the algicidal bacteria effect (i.e. the number of raphidophyte species affected by a particular bacteria strain) and raphidophyte susceptibility (i.e. the number bacteria strains affecting a particular raphidophyte species), a toxic effect was always found when strains of a raphidophyte species were exposed to algicidal bacteria isolated from a bloom caused by that same species. The results suggest that algicidal bacteria may be an important limiting factor in raphidophyte bloom sustenance and can promote bloom decline in brackish lagoonal eutrophic estuaries.

On 29 April 2003, a Heterosigma akashiwo bloom (9.5 × 10 4 cells mL −1 ) associated with a fish kill (>10 4 dead fishes estimated from aerial surveys) was observed offshore of Bulls Bay, McLellanville, South Carolina, USA. To assess a potential cause of this bloom event, we investigated the bacterial diversity and algal/bacterial interactions in the bloom microbial community. Thirty-five bacterial strains were isolated and screened for algicidal or algal growth-promoting activities. One strain (BBB25) had significant growth-promoting effects on all 7 algal species tested: three raphidophytes ( Heterosigma akashiwo , Chattonella subsalsa , Fibrocapsa japonica ), two diatoms ( Chaetoceros neogracile , Nitzschia sp.), a cryptophyte ( Cryptomonas sp.), and a chlorophyte, Ankistrodesmus sp. This strain (BBB25) is a Gram-positive, rod-shaped spore-forming bacterium. Partial 16S rDNA gene sequence and morphological characters indicated that BBB25 is related closely to the genus Bacillus . The general nature of the algal response indicates that the growth-promoting effects of BBB25 are not specific to H. akashiwo , and suggests potentially widespread effects. Since the presence or relative abundance of the other algal species was not assessed during the bloom initiation period, the selective stimulatory effect on H. akashiwo bloom formation in Bulls Bay is unknown. These results demonstrate, however, the potential for bacterial species to play a regulatory role in bloom formation.

In order to solve the problem that there is a shortage of space and computing power of the traditional spatial data mining algorithm during the processing for massive spatial data information, a combination of Rough set and distributed framework is used in the process of spatial data mining. In this paper, parallel improvement is taken into the algorithm of the traditional Rough set for spatial data mining based on the basic theory of rough set and the Map/Reduce framework, which is efficient and cheap. Then, a spatial data example is utilized to show the feasibility of the improved parallel algorithm. Empirical results show that the improved parallel algorithm of Rough set for spatial data mining can not only effectively improve the efficiency of the algorithm but also meet the need of people to deal with massive spatial data which is hardly to the algorithm of traditional Rough set. Improved Rough set parallel algorithm for spatial data mining can effectively solve the problem of shortage for massive spatial data storage and computing power mining.

In this paper, taking optimization of equipment supply for example, and on the basis of synthetically considering each factor of equipment supply, it established the mathematical model and calculation method for equipment supply optimization, with the goal of the lowest supplying total cost, proposed the solution based on genetic algorithm, discussed the design of equipment supply optimization based on genetic algorithm, and finally further analyzed and proved the model and the solution through the case.

Trajectory features have recently shown promising results to action recognition in video. Typically, they are extracted by tracking feature points with the KLT tracker or matching SIFT descriptors between frames. However, trajectory can be due to the action of interest, but also be caused by background or the camera motion. To overcome the problem, human detection is applied to roughly estimate of the location of the human in the video and segment video into Foreground/Background regions. In many cases, human actions can be identified not only by observing human body in motion, but also properties of the surrounding scene. In our work, we addresse the problem and propose an approach that integrates multiple features from scene and people. We evaluate our video description with a bag of-features model. We also present experimental results on two datasets with an increasing degree of difficulty and demonstrate significant improvements.