A host computer monitoring configuration software is designed based on C# in this paper. The hardware structure of this host computer system includes engineer station and operator station. The configuration software contains graphic interface module; trend curve module; and database module. It meets the basic needs of small and medium enterprises in the cement industry.
Wu, Xiaozhe
Li, Zhan
Li, Xiaolu
Tian, Yaomei
Fan, Yingzi
Yu, Chaoheng
Zhou, Bailing
Liu, Yi
Xiang, Rong
Yang, Li
Antibiotic-resistant bacteria present a great threat to public health. In this study, the synergistic effects of antimicrobial peptides (AMPs) and antibiotics on several multidrug-resistant bacterial strains were studied, and their synergistic effects on azithromycin (AZT)-resistance genes were analyzed to determine the relationships between antimicrobial resistance and these synergistic effects. A checkerboard method was used to evaluate the synergistic effects of AMPs (DP7 and CLS001) and several antibiotics (gentamicin, vancomycin [VAN], AZT, and amoxicillin) on clinical bacterial strains (Staphylococcus aureus, Pseudomonas aeruginosa, Acinetobacter baumannii, and Escherichia coli). The AZT-resistance genes (ermA, ermB, ermC, mefA, and msrA) were identified in the resistant strains using quantitative polymerase chain reaction. For all the clinical isolates tested that were resistant to different antibiotics, DP7 had high antimicrobial activity (<=3D 32 mg/L). When DP7 was combined with VAN or AZT, the effect was most frequently synergistic. When we studied the resistance genes of the AZT-resistant isolates, the synergistic effect of DP7-AZT occurred most frequently in highly resistant strains or strains carrying more than two AZT-resistance genes. A transmission electron microscopic analysis of the S. aureus strain synergistically affected by DP7-AZT showed no noteworthy morphological changes, suggesting that a molecular-level mechanism plays an important role in the synergistic action of DP7-AZT. AMP DP7 plus the antibiotic AZT or VAN is more effective, especially against highly antibiotic-resistant strains.
A novel model for measuring the target's slop based on the raw data of full-waveform topographic lidar is proposed. We discussed the range resolution of full-waveform topographic lidar was limited by several key parameters; including the sampling period; laser pulse width and the time period of sub-waveform. A physical model was established to calculate the target's slop and the number of the sub-waveform divided within the whole echo by algorithm. When the lidar equation and the backscatter cross-section equation were described by Gaussian functions; the receiver response function can be also described by Gaussian function. Based on geometry relationship; the expressions of the target's slop can be described by the laser's divergence angle and the marked time of the sub-waveform. This work can be used for improving accuracy and range detection and details of target's slop in future.
With the rapid economic development, the serious air pollution in Beijing attracts increasing attention in the last decade. Seen as one whole complex and grey system, the causal relationship between the social development and the air pollution in Beijing has been quantitatively analyzed in this paper. By using the grey relational model, the aim of this study is to explore how the socio-economic and human activities affect on the air pollution in the city of Beijing, China. Four air pollutants, as the particulate matter with size 2.5 micrometers or less (PM2.5), particulate matter with size 10 micrometers or less (PM10), sulfur dioxide (SO2) and nitrogen dioxide (NOx), are selected as the indicators of air pollution. Additionally, fifteen socio-economic indicators are selected to account for the regional socio-economic characteristics (economy variables, energy consumption variables, pollution emissions variables, environment and construction activity variables). The results highlight that all variables are associated with the concentrations of the four selected air pollutants, but with notable differences between the air pollutants. Most of the socio-economic indicators, such as industrial output, total energy consumption are highly correlated with PM2.5, while PM10, SO2, and NOx present in general moderate correlations with most of the socioeconomic variables. Contrary to other studies and reports this study reveals that vehicles and life energy do not have the strongest effect on air pollution in Beijing. This study provides useful information to reduce air pollution and support decision-making for sustainable development.