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It is crucial to advance network education exam informatization and mobile learning. One of them is the creation of a database system for exams, which contains crucial information. This study aims to analyze and solves key technologies including constraint check paper forming algorithms. This study using fuzzy query methods and spatial queries design a single exam table structure and exam papers for the exam database. The process of this study including collect and sort the complete set of GIS exams at major universities across the country, design a variety of GIS single questions, and build an exam database system. The result of this research is a personalized random paper formation system and query and spatial analysis by college and area for exam papers for the first time. It describes rich functions and stable performance by testing. The built system becomes an indispensable technical support instead of paper-based exams for information exams and scientific exams of many colleges and universities.

The intracellular pathogen Salmonella enterica serovar Typhimurium (S. Typhimurium) exploits host macrophage as a crucial survival and replicative niche. To minimize host immune response stimulated by flagellin, the expression of flagellar genes is downregulated during S. Typhimurium growth within host macrophages. However, the underlying mechanisms are largely unknown. In this study, we show that STM14_1285 (named AsiR), a putative RpiR-family transcriptional regulator, which is downregulated within macrophages as previously reported and also confirmed here, positively regulates the expression of flagellar genes by directly binding to the promoter of flhDC. By generating an asiR mutant strain and a strain that persistently expresses asiR gene within macrophages, we confirmed that the downregulation of asiR contributes positively to S. Typhimurium replication in macrophages and systemic infection in mice, which could be attributed to decreased flagellar gene expression and therefore reduced flagellin-stimulated secretion of pro-inflammatory cytokines IL-1β and TNF-α. Furthermore, the acidic pH in macrophages is identified as a signal for the downregulation of asiR and therefore flagellar genes. Collectively, our results reveal a novel acidic pH signal-mediated regulatory pathway that is utilized by S. Typhimurium to promote intracellular replication and systemic pathogenesis by repressing flagellar gene expression.

Nitric oxide (NO) is produced as an innate immune response against microbial infections. Salmonella Typhimurium (S. Typhimurium), the major causative pathogen of human gastroenteritis, induces more severe systemic disease in mice. However, host factors contributing to the difference in species-related virulence are unknown. Here, we report that host NO production promotes S. Typhimurium replication in mouse macrophages at the early infection stage by activating Salmonella pathogenicity island-2 (SPI-2). The NO signaling-induced SPI-2 activation is mediated by Fnr and PhoP/Q two-component regulatory system. NO (5–20 μM) significantly induced fnr transcription, while Fnr directly activated phoP/Q transcription. Mouse infection assays revealed a NO-dependent increase in bacterial burden in systemic organs during the initial days of infection, indicating an early contribution of host NO to virulence. It is likely that this pathway is not activated in human macrophages, owing to the lack of NO production. This study reveals a novel host signaling-mediated virulence activation pathway in S. Typhimurium that contributes significantly to its systemic infection in mice, providing important insights into Salmonella pathogenesis and host–pathogen interaction.

It is difficult to balance local details and global distribution using a single source image in marine target detection of a large scene. To solve this problem, a technique based on the fusion of optical image and synthetic aperture radar (SAR) image for the extraction of sea ice is proposed in this paper. The Band 2 (B2) image of Sentinel-2 (S2) in the research area is selected as optical image data. Preprocessing on the optical image, such as resampling, projection transformation and format conversion, are conducted to the S2 dataset before fusion. Imaging characteristics of the sea ice have been analyzed, and a new deep learning (DL) model, OceanTDL5, is built to detect sea ices. The fusion of the Sentinel-1 (S1) and S2 images is realized by solving the optimal pixel values based on deriving Poisson Equation. The experimental results indicate that the use of a fused image improves the accuracy of sea ice detection compared with the use of a single data source. The fused image has richer spatial details and a clearer texture compared with the original optical image, and its material sense and color are more abundant.

Salmonella Typhimurium establishes systemic infection by replicating in host macrophages. Here we show that macrophages infected with S. Typhimurium exhibit upregulated glycolysis and decreased serine synthesis, leading to accumulation of glycolytic intermediates. The effects on serine synthesis are mediated by bacterial protein SopE2, a type III secretion system (T3SS) effector encoded in pathogenicity island SPI-1. The changes in host metabolism promote intracellular replication of S. Typhimurium via two mechanisms: decreased glucose levels lead to upregulated bacterial uptake of 2- and 3-phosphoglycerate and phosphoenolpyruvate (carbon sources), while increased pyruvate and lactate levels induce upregulation of another pathogenicity island, SPI-2, known to encode virulence factors. Pharmacological or genetic inhibition of host glycolysis, activation of host serine synthesis, or deletion of either the bacterial transport or signal sensor systems for those host glycolytic intermediates impairs S. Typhimurium replication or virulence. Salmonella Typhimurium establishes systemic infection by replicating in host macrophages. Here, Jiang et al. show that infected macrophages exhibit upregulated glycolysis and decreased serine synthesis, leading to accumulation of glycolytic intermediates that promote intracellular replication and virulence of S. Typhimurium.

Salmonella Typhimurium is an invasive enteric pathogen that causes gastroenteritis in humans and life-threatening systemic infections in mice. During infection of the intestine, S. Typhimurium can exploit nitrate as an electron acceptor to enhance its growth. However, the roles of nitrate on S. Typhimurium systemic infection are unknown. In this study, nitrate levels were found to be significantly increased in the liver and spleen of mice systemically infected by S. Typhimurium. Mutations in genes encoding nitrate transmembrane transporter (narK) or nitrate-producing flavohemoprotein (hmpA) decreased the replication of S. Typhimurium in macrophages and reduced systemic infection in vivo, suggesting that nitrate utilization promotes S. Typhimurium systemic virulence. Moreover, nitrate utilization contributes to the acidification of the S. Typhimurium cytoplasm, which can sustain the virulence of S. Typhimurium by increasing the transcription of virulence genes encoding on Salmonella pathogenicity island 2 (SPI-2). Furthermore, the growth advantage of S. Typhimurium conferred by nitrate utilization occurred only under low-oxygen conditions, and the nitrate utilization was activated by both the global regulator Fnr and the nitrate-sensing two-component system NarX-NarL. Collectively, this study revealed a novel mechanism adopted by Salmonella to interact with its host and increase its virulence.

The two-parameter constant false alarm rate (CFAR) detection algorithm uses the background average $u_{b}$ and the standard deviation $\sigma _{b}$ to determine the target detection threshold, which is simple and easy to implement. However, it is limited by the assumption of Gaussian distribution. Based on different probability distributions, the research improves the two-parameter CFAR algorithm, and proposes the two-parameter CFAR method based on initial detection, and the detection methods based on Loglogistic Distribution model and Adjoint Covariance Correction Model (ACCM). Three methods are used to detect and extract ocean targets in the same research area, and the results are compared and analyzed. The experimental results show that ACCM proposed in the research fits the long tail characteristic of the ocean background under complex ocean conditions well. Its goodness of fit is improved by nearly 50% compared with Loglogistic Distribution model, and its amount of false alarm of ocean target detection is 77.78% of Loglogistic model. In addition, in view of a large amount of calculation caused by the sliding window of the traditional two-parameter CFAR, OceanTDA9 deep learning model is designed for initial detection in research, which improves the detection speed of ocean targets.

Paper wastes form the major biodegradable fraction of the municipal solid waste. One of the best ways to treat paper wastes is using them as a feedstock for biomethane production through anaerobic digestion (AD). However, the AD characteristics, kinetics, and energy potential of different types of paper wastes are not clear. In this study, four kinds of typical paper wastes including corrugated board (CB), office paper (OP), tissue paper (TP), and magazine paper (MP) were used as feedstocks to produce biomethane at different volatile solids (VS) organic loading (OL). TP had a high cellulose content and showed high biomethane potential, while the lowest was obtained by CB, possibly due to its high lignin content. Kinetic analysis showed that Cone and modified Gompertz model could fit the biomethane production process well. Energy potential analysis revealed that biomethane yield, electric generating efficiency, and electricity price were the principal factors accounting for the profitability of biomethane production project treating paper wastes. Overall, paper wastes could be a promising feedstock for biomethane production, because paper wastes not only had high biomethane yield and biodegradability that exceeded many kinds of organic wastes but also could be continuously supplied for AD plants without the influence of seasonal changes.

Salmonella Typhimurium is a Gram-negative intestinal pathogen that can infect humans and a variety of animals, causing gastroenteritis or serious systemic infection. Replication within host macrophages is essential for S. Typhimurium to cause systemic infection. By analyzing transcriptome data, the expression of yhjC gene, which encodes a putative regulator in S. Typhimurium, was found to be significantly up-regulated after the internalization of Salmonella by macrophages. Whether yhjC gene is involved in S. Typhimurium systemic infection and the related mechanisms were investigated in this study. The deletion of yhjC reduced the replication ability of S. Typhimurium in macrophages and decreased the colonization of S. Typhimurium in mouse systemic organs (liver and spleen), while increasing the survival rate of the infected mice, suggesting that YhjC protein promotes systemic infection by S. Typhimurium. Furthermore, by using transcriptome sequencing and RT-qPCR assay, the transcription of several virulence genes, including spvD, iroCDE and zraP, was found to be down-regulated after the deletion of yhjC. Electrophoretic mobility shift assay showed that YhjC protein can directly bind to the promoter region of spvD and zraP to promote their transcription. These findings suggest that YhjC contributes to the systemic virulence of S. Typhimurium via the regulation of multiple virulence genes and YhjC could represent a promising target to control S. Typhimurium infection.

Salmonella enterica serovar Typhi (S. Typhi) is a human-limited intracellular pathogen and the cause of typhoid fever, a severe systemic disease. Pathogen–host interaction at the metabolic level affects the pathogenicity of intracellular pathogens, but it remains unclear how S. Typhi infection influences host metabolism for its own benefit. Herein, using metabolomics and transcriptomics analyses, combined with in vitro and in vivo infection assays, we investigated metabolic responses in human macrophages during S. Typhi infection, and the impact of these responses on S. Typhi intracellular replication and systemic pathogenicity. We observed increased glucose content, higher rates of glucose uptake and glycolysis, and decreased oxidative phosphorylation in S. Typhi-infected human primary macrophages. Replication in human macrophages and the bacterial burden in systemic organs of humanized mice were reduced by either the inhibition of host glucose uptake or a mutation of the bacterial glucose uptake system, indicating that S. Typhi utilizes host-derived glucose to enhance intracellular replication and virulence. Thus, S. Typhi promotes its pathogenicity by inducing metabolic changes in host macrophages and utilizing the glucose that subsequently accumulates as a nutrient for intracellular replication. Our findings provide the first metabolic signature of S. Typhi-infected host cells and identifies a new strategy utilized by S. Typhi for intracellular replication.

Having been generated with a tremendous amount annually, paper waste (PW) represents a large proportion in municipal solid waste (MSW) and also a potential source of renewable energy production through the application of anaerobic digestion (AD). However, the recalcitrant lignocellulosic structure poses obstacles to efficient utilization in this way. Recently, anaerobic and microaerobic pretreatment have attracted attention as approaches to overcome the obstacles of biogas production. This study was set out to present a systematic comparison and assessment of anaerobic and microaerobic pretreatment of PW with different oxygen loadings by five microbial agents: composting inoculum (CI), straw-decomposing inoculum (SI), cow manure (CM), sheep manure (SM), and digestate effluent (DE). The hints of microbial community evolution during the pretreatment and AD were tracked by 16S rRNA high-throughput sequencing. The results demonstrated that PW pretreated by DE with an oxygen loading of 15 ml/gVS showed the highest cumulative methane yield (CMY) of 343.2 ml/gVS, with a BD of 79.3%. In addition to DE, SI and SM were also regarded as outstanding microbial agents for pretreatment because of the acceleration of methane production at the early stage of AD. The microbial community analysis showed that Clostridium sensu stricto 1 and Clostridium sensu stricto 10 possessed high relative abundance after anaerobic pretreatment by SI, while Bacteroides and Macellibacteroides were enriched after microaerobic pretreatment by SM, which were all contributable to the cellulose degradation. Besides, aerobic Bacillus in SI and Acinetobacter in SM and DE probably promoted lignin degradation only under microaerobic conditions. During AD, VadinBC27, Ruminococcaceae Incertae Sedis, Clostridium sensu stricto 1, Fastidiosipila, and Caldicoprobacter were the crucial bacteria that facilitated the biodegradation of PW. By comparing the groups with same microbial agent, it could be found that changing the oxygen loading might result in the alternation between hydrogenotrophic and acetoclastic methanogens, which possibly affected the methanogenesis stage. This study not only devised a promising tactic for making full use of PW but also provided a greater understanding of the evolution of microbial community in the pretreatment and AD processes, targeting the efficient utilization of lignocellulosic biomass in full-scale applications.

This study investigated methane production, long-chain fatty acids (LCFAs) profile, and predominant microorganisms in anaerobic digestion (AD) of lipid-rich swine slaughterhouse waste (SSW). The maximum methane yield was 999.2 mL/g VS. LCFAs, as inhibitory hydrolysis products, accumulated first to 1165 mg/L on day 3, and then decreased sharply to 125.7 mg/L on day 9, and finally were degraded to 20 mg/L on day 27. Linoleic acid (C18:2), oleic acid (C18:1) and palmitic acid (C16:0) were the dominant LCFAs. The easy conversion of C18:1 to C16:0 compared with difficult degradation of C16:0 resulted in an increase of C16:0 on day 4–6. Predominant microorganisms were Clostridium, Syntrophomonas and Methanospirillum. This study proved the high methane potential of lipid-rich SSW and gained insights into the degradation process by analysis of intermediates of LCFAs and predominant microorganisms. The results can provide valuable guidance for efficient utilization of this waste to produce methane in future.

Lignocellulosic biomass is the most abundant natural resource with high biomethane potential. However, complex structure of lignocellulosic biomass has hampered the efficient utilization of this bioresource. Previous studies have investigated the overall anaerobic digestion performance of lignocellulosic biomass, but the individual participation of each lignocellulosic component during anaerobic digestion remained unclear. Thus, this study investigated the methane production characteristics of cellulose, hemicellulose, lignin and their mixtures along with the microbial communities involved in anaerobic digestion. The results showed that the biomethane potential of cellulose was higher than that of hemicellulose; however, hemicellulose was hydrolysed more quickly than cellulose, while lignin was very difficult to be digested. The higher concentrations of acetic, n-butyric and n-valeric acids hydrolysed from the hemicellulose resulted in a lower pH and more severe inhibition on methane production than that of cellulose, and the methanogenesis gradually recovered after pH adjustment. The co-digestion of cellulose and hemicellulose increased the methane yield and biodegradability compared to mono-digestions. The addition of lignin to cellulose brought more significant decrease in the methane yield of cellulose than that of hemicellulose. Substrate-related bacteria such as Clostridium sensu stricto, Lutaonella, Cloacibacillus and Christensenella showed higher relative abundance in cellulose digestate, and sugar-fermenting bacteria such as Saccharofermentans, Petrimonas and Levilinea were more rich in the digestate of hemicellulose. Moreover, methanogenic Methanospirillum and Methanothrix likely contributed to the methane production of cellulose, while aciduric methanogens from Methanobrevibacter, Methanomassiliicoccus, Methanobacterium and Methanoculleus contributed to that of hemicellulose. This study provides a deeper understanding of the mechanism in the bioconversion of lignocellulosic biomass during anaerobic digestion.

A large amount of sheep dung (SD) produced on farms in China is a potential feedstock for production of clean energy in the form of biogas. Similarly, waste paper can be a notable energy source that is worth exploiting. In this study, we assessed the feasibility of co-digesting nitrogen-rich SD with the carbon-rich corrugated board (CB) or waste office paper (OP) in varying volatile solids (VS) ratios, to produce methane. Synergistic effect of co-digesting SD with CB and SD with OP on methane production was found in this study. The highest methane yields of 151.62 and 198.85 mL/g-VS were obtained during the co-digestions of SD with CB at 4:1 ratio (SDCB) and SD with OP at 2:3 ratio (SDOP), respectively. High-throughput 16 S rRNA gene sequencing demonstrated that the microbial diversity and richness in SDCB and SDOP co-digests were higher than in SD and OP mono-digests, respectively. Characteristic bacteria and archaea in the digests were strongly substrate-related and might contribute to methane production. The validated results indicated that methane production through anaerobic co-digestion of SD and waste paper can be an efficient way that could not only reduce environmental pollution but also contribute to methane production.

Alkaline pretreatment of lignocellulosic biomass has been intensively investigated but heavy water usage and environmental pollution from wastewater limits its industrial application. This study presents a pretreatment technique by in-situ injection of potassium hydroxide concentrations ranging from 0.8% to 10% (w/w) into the briquetting process of wheat straw and meadow grass. Results show that the biomethane yield and hydrolysis rate was improved significantly with a higher impact on wheat straw compared to meadow grass. The highest biomethane yield from wheat straw briquettes of 353mL.g-1 VS was obtained with 6.27% (w/w) potassium hydroxide injection, which was 14% higher than from untreated wheat straw. The hydrolysis rates of wheat straw and meadow grass increased from 4.27×10-2 to 5.32×10-2d-1 and 4.19×10-2 to 6.00×10-2d-1, respectively. The low water usage and no wastewater production make this a promising technology.

This study employs a microaerobic pretreatment that includes different microbial reagents combined with oxygen to enhance the energy conversion potential of rice straw (RS) via anaerobic digestion (AD) in a more cost-effective and time-efficient manner. Five broad varieties of microbial reagents including liquid consortium (LC), cow manure (CM), sheep dung (SD), biogas slurry (BS), and straw-decomposing consortia (SC), have been used as sources of useful microbes at varying oxygen concentrations of 0, 6, 12 and 24 mLO2/gVS to explore the effect of microaerobic pretreatment on RS degradation. The results showed that RS pretreated with SC had the highest cumulative methane yield (CMY) of 311.7 mL/gVS at 12 mLO2/gVS, followed by BS, CM, LC, and SD, with the CMYs of 270.5, 263.2, 257.1, and 256.7 mL/gVS at 6 mLO2/gVS, respectively. The RS pretreated with SC, BS, CM, LC, and SD led to improvements in the methane yield by 88.7%, 63.7%, 59.3%, 55.6%, and 55.4%, respectively, compared to the untreated RS. The microbial community analysis revealed that the relative abundance (RA) of Firmicutes, which are known to play a key role in accelerating the rate of hydrolysis, increased after microbial pretreatment combined with oxygen supply. The RA of Clostridium III, which facilitates cell wall degradation via hydrolytic pathways along with other sugar-fermenting bacteria, such as Saccharofermentans, Lutaonella, and Sedimentibacter, increased after AD in the digestate of pretreated RS compared to that in untreated RS. Moreover, a shift in acetoclastic and hydrogenotrophic archaea, including Methanothrix and Methanospirillum, was also observed, indicating precursor changes resulted by pretreatments and varied microbial metabolism, which might have enhanced the methane production process of RS. The energy potential analysis revealed that microbial pretreatment was a suitable technique for stimulating the energy conversion efficiency of RS. This study can be used as a reference for future utilization of a diverse range of lignocellulosic materials for clean energy production.

Effectiveness of steam explosion (SE) pretreatment for deconstructing the complex structural carbohydrates (SC) and lignin recalcitrance properties of rice straw (RS) for conjunctive improvement of biofuel yield and waste valorization was evaluated. This work exhibited successful pretreatment of RS at a different pressure (1.2, 1.5, and 1.8 MPa) and retention (3, 6, 9, and 12 min) for enhancement of SC contribution to biomethane production. Regression analysis demonstrated that SE pretreatment efficiency improved at high-temperature and short-retention time for biodegradation of RS. Maximum cumulative methane yield (EMY) achieved 254.8 mL/gvs at 1.2 MPa (3 min) of SE-treated RS with 62.7% of very significant improvement compared with untreated RS (156.6 mL/gvs). Furthermore, solid fraction of xylose, arabinose, cellobiose, glucose, and acid-soluble lignin in SE-treated RS of 1.2 MPa (3 min) were biodegraded by 27.4%, 46.4%, 100%, 48.8%, and 14.1%, respectively, after anaerobic digestion. Therefore, SE pretreatment was an encouraging approach for enhancing SC conversion to biomethane and waste resource to circular economy.

Tobacco stalk, a common agricultural waste derived from the harvest of tobacco, caused serious environmental pollution in China. In this study, the performance of biomethane production and characteristics of four varieties of tobacco stalk were investigated for the first time. The results showed that the highest cumulative methane yield of 130.2 mL/g-VS was obtained from Nicotiana tabacum L., Yunyan114, which had lower lignin content than other varieties of tobacco stalk. Moreover, different kinetic models were used to describe the biomethane production process, and it was found that the modified Gompertz model was more suitable to simulate the anaerobic digestion (AD) of tobacco stalk. The findings of this study not only showed a feasible method for minimizing the pollution issues of tobacco stalk waste but also gave fundamental information for future AD application.

On the basis of summarizing the research results of visual variables, we define six dynamic visual variables of the map symbol in this paper. We analyze the related attributes of dynamic symbols, and then construct a dynamic map expression model based on symbols. A key technology to realize dynamic expression——the key frame transform algorithm is present in the paper. The cartography process of the urban population proportion dynamic change map of the cities in Shandong province are taken as an example to demonstrate the methods and process of dynamic mapping based on the above map dynamic expression theories and models, which includes base map digitization, sorting and processing of attribute data, adding the map elements, the creation of special dynamic effect such as color transform, continuous flashing and object moving, and realization of interactive function. Finally, the paper shows the dynamic map of sea level rising influence on Qingdao, the Typhoon Soulik traveling map, the Western European natural gas trade flow variation map, the Bangkok flood risk level dynamic map, and other dynamic map effect at the end of the article.

Combining the SQL Server database and Visual C# language, the paper takes the ASP.NET technology as the core, develops and constructs the Geographic Information System (GIS) network education based on the Web platform, realizes the fusion between GIS professional knowledge and website. Rich resources, Friendly interface, fluent Video, fast Navigation and good interaction make it possible to achieve the network education system of GIS supported by the computer.