48 research outputs found

    Combined utilization of metabolic inhibitors to prevent synergistic multi-species biofilm formation.

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    peer reviewedBiofilm is ubiquitous in industrial water systems, causing biofouling and leading to heat transfer efficiency decreases. In particular, multi-species living in biofilms could boost biomass production and enhance treatment resistance. In this study, a total of 37 bacterial strains were isolated from a cooling tower biofilm where acetic acid and propionic acid were detected as the main carbon sources. These isolates mainly belonged to Proteobacteria and Firmicutes, which occupied more than 80% of the total strains according to the 16S rRNA gene amplicon sequencing. Four species (Acinetobacter sp. CTS3, Corynebacterium sp. CTS5, Providencia sp. CTS12, and Pseudomonas sp. CTS17) were observed co-existing in the synthetic medium. Quantitative comparison of biofilm biomass from mono- and multi-species showed a synergistic effect towards biofilm formation among these four species. Three metabolic inhibitors (sulfathiazole, 3-bromopyruvic acid, and 3-nitropropionic acid) were employed to prevent biofilm formation based on their inhibitory effect on corresponding metabolic pathways. All of them displayed evident inhibition profiles to biofilm formation. Notably, combining these three inhibitors possessed a remarkable ability to block the multi-species biofilm development with lower concentrations, suggesting an enhanced effect appeared in simultaneous use. This study demonstrates that combined utilization of metabolic inhibitors is an alternative strategy to prevent multi-species biofilm formation

    Quinclorac resistance induced by the suppression of the expression of 1-aminocyclopropane-1-carboxylic acid (ACC) synthase and ACC oxidase genes in Echinochloa crus-galli var. zelayensis

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    We previously reported that the mechanism of quinclorac resistance in Echinochloa crus-galli var. zelayensis may be closely related to ethylene biosynthesis and the detoxification of cyanide. Differences in EcCAS gene sequences and expression levels may result in higher capacity to detoxify cyanide in resistant biotypes, which may avoid cyanide accumulation and avoid more ethylene and cyanide production and then avoid damage. In the present study, we focused on the mechanism of resistance related to ethylene biosynthesis in E. crus-galli var. zelayensis. The fresh weight of susceptible and moderately resistant biotypes were significantly reduced after treatment with quinclorac. However, AOA, an ethylene biosynthesis inhibitor, reduced the impact of quinclorac. On pretreatment with AOA, ethylene production was significantly reduced in the three biotypes. The highly resistant biotype produced less ethylene compared to the other two biotypes. Three ACS and seven ACO genes, which are the key genes in ethylene biosynthesis, were obtained. The expression levels of EcACS-like, EcACS7, and EcACO1 varied in the three biotypes upon treatment with quinclorac, which could be manipulated by AOA. In summary, it is inferred that the expression of EcACS-like, EcACS7, and EcACO1 can be stimulated to varying extent after quinclorac treatment in three E. crus-galli var. zelayensis biotypes, which consequently results in varying levels of ethylene production. Lower expression of these three genes results in more resistance to quinclorac, which may also be related to quinclorac resistance in E. crus-galli var. zelayensis

    Emergency Scheduling Optimization Simulation of Cloud Computing Platform Network Public Resources

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    Emergency scheduling of public resources on the cloud computing platform network can effectively improve the network emergency rescue capability of the cloud computing platform. To schedule the network common resources, it is necessary to generate the initial population through the Hamming distance constraint and improve the objective function as the fitness function to complete the emergency scheduling of the network common resources. The traditional method, from the perspective of public resource fairness and priority mapping, uses incremental optimization algorithm to realize emergency scheduling of public resources, neglecting the improvement process of the objective function, which leads to unsatisfactory scheduling effect. An emergency scheduling method of cloud computing platform network public resources based on genetic algorithm is proposed. With emergency public resource scheduling time cost and transportation cost minimizing target, initial population by Hamming distance constraints, emergency scheduling model, and the corresponding objective function improvement as the fitness function, the genetic algorithm to individual selection and crossover and mutation probability were optimized and complete the public emergency resources scheduling. Experimental results show that the proposed method can effectively improve the efficiency of emergency resource scheduling, and the reliability of emergency scheduling is better

    Emissions of non-methane hydrocarbons and typical volatile organic compounds from various grate-firing coal furnaces

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    Non-methane hydrocarbons (NMHCs) and volatile organic compounds (VOCs) emitted from grate-firing coal furnaces cause serious harmful impacts on the atmospheric environment and human health. To investigate the effects of coal type and grate-firing mode on the emissions of NMHCs and VOCs, four different coal fuels (i.e., bituminous coal (BC), bituminous briquette (BB), anthracite briquette (AB) and semi-coke (SC)) were burnt in three typical grate-firing modes (i.e., updraft mode (UDM), downdraft mode (DDM) and cross-draft mode (CDM)). Offline GC-MS (Gas Chromatography-Mass Spectrometry) analyses show that the mass of benzene and toluene accounts for more than 60% of the total amount of quantifiable benzenoid compounds under the smoldering condition, and up to almost 100% under the flaming condition. The BB burnt in the CDM produces lower NMHCs and VOCs than in the other two modes and the SC burnt in the three modes yields the lowest NMHCs and VOCs among the four coal fuels, as further clarified by online FTIR (Fourier-Transform Infrared spectroscopy) measurements. Combustion mode was found to have a prominent impact on the NMHCs and VOCs emissions in household coal stoves. The NMHCs emission factor determined by the GC-MS measurements under the flaming and smoldering stages is inversely proportional to combustion efficiency. The average VOCs emission factor calculated from the FTIR measuring data inversely varies with combustion efficiency too

    Smartphone-Based Hand-Held Optical Fiber Fluorescence Sensor for On-Site pH Detection

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    Running-Time Analysis of Brain Storm Optimization Based on Average Gain Model

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    The brain storm optimization (BSO) algorithm has received increased attention in the field of evolutionary computation. While BSO has been applied in numerous industrial scenarios due to its effectiveness and accessibility, there are few theoretical analysis results about its running time. Running-time analysis can be conducted through the estimation of the upper bounds of the expected first hitting time to evaluate the efficiency of BSO. This study estimates the upper bounds of the expected first hitting time on six single individual BSO variants (BSOs with one individual) based on the average gain model. The theoretical analysis indicates the following results. (1) The time complexity of the six BSO variants is O(n) in equal coefficient linear functions regardless of the presence or absence of the disrupting operator, where n is the number of the dimensions. Moreover, the coefficient of the upper bounds on the expected first hitting time shows that the single individual BSOs with the disrupting operator require fewer iterations to obtain the target solution than the single individual BSOs without the disrupting operator. (2) The upper bounds on the expected first hitting time of single individual BSOs with the standard normally distributed mutation operator are lower than those of BSOs with the uniformly distributed mutation operator. (3) The upper bounds on the expected first hitting time of single individual BSOs with the U−12,12 mutation operator are approximately twice those of BSOs with the U(−1,1) mutation operator. The corresponding numerical results are also consistent with the theoretical analysis results
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