Search

Stimulating the development of soil suppressiveness against certain pathogens represents a sustainable solution toward reducing pesticide use in agriculture. However, understanding the dynamics of suppressiveness and the mechanisms leading to pathogen control remain largely elusive. Here, we investigated the mechanisms used by the rhizosphere microbiome induces bacterial wilt disease suppression in a long-term field experiment where continuous application of bio-organic (BF) fertilizers triggered disease suppressiveness when compared to chemical fertilizer (CF) application. We further demonstrated in a greenhouse experiment that the suppressiveness of the rhizosphere bacterial communities was triggered mainly by changes in community composition rather than only by the abundance of the introduced biocontrol strain. Metagenomics approaches revealed that members of the families Sphingomonadaceae and Xanthomonadaceae with the ability to produce secondary metabolites were enriched in the BF plant rhizosphere but only upon pathogen invasion. We experimentally validated this observation by inoculating bacterial isolates belonging to the families Sphingomonadaceae and Xanthomonadaceae into conducive soil, which led to a significant reduction in pathogen abundance and increase in non-ribosomal peptide synthetase (NRPS) gene abundance. We conclude that priming of the soil microbiome with bio-organic fertilizer amendment fostered reactive bacterial communities in the rhizosphere of tomato plants in response to biotic disturbance.

Soil microbiome manipulation can potentially reduce the use of pesticides by improving the ability of soils to resist or recover from pathogen infestation, thus generating natural suppressiveness. We simulated disturbance through soil fumigation and investigated how the subsequent application of bio-organic and organic amendments reshapes the taxonomic and functional potential of the soil microbiome to suppress the pathogens Ralstonia solanacearum and Fusarium oxysporum in tomato monocultures. The use of organic amendment alone generated smaller shifts in bacterial and fungal community composition and no suppressiveness. Fumigation directly decreased F. oxysporum and induced drastic changes in the soil microbiome. This was further converted from a disease conducive to a suppressive soil microbiome due to the application of organic amendment, which affected the way the bacterial and fungal communities were reassembled. These direct and possibly indirect effects resulted in a highly efficient disease control rate, providing a promising strategy for the control of the diseases caused by multiple pathogens.

With the employment of power electronic converters, renewable energy resources introduce noticeable diversity into different generation units and dramatically change the characteristics of the supply side. Cooperation of different kinds of generation units in steady and dynamic states hence becomes important issues for grid integration. This article studies transient active power circulation caused by parameter difference among different kinds of generation units, such as synchronous generator and voltage-controlled power inverters. Parameter differences brought by power electronic inverters are analyzed, including capacity, inertia, and grid-side inductance. Moreover, a simplified transfer function model is utilized for the detailed analysis, which reveals how the transient active power circulation is influenced by the parameter difference. The theoretical analysis is verified with both simulation and experiment. Consequently, some important conjoint influences of inertia, impedance, and capacity difference are clarified, where the effectiveness and ineffectiveness of inertia and impedance imitation are concluded in transient active power allocation. Inertia and impedance design that attenuates transient active power circulation is proposed in several certain situations for inverter cooperated with other generation units.

To satisfy the robust and real-time requirements of power flow calculation for large-scale power systems, a globally convergent method is proposed with trust-region techniques, which shows satisfying robustness and convergence. Then, this method is combined with Newton's method to achieve a two-stage algorithm, benefiting from their different advantages. In the first stage, the proposed globally convergent method is used for searching power flow solution. When the values of state variables in a certain iteration are close enough to the real operational point, the algorithm enters the second stage to use Newton's method to achieve the solution. This two-stage algorithm can achieve an accurate solution for solvable cases, and can also achieve a least-square solution, which is an approximate solution for unsolvable cases. Numerical experiments show that the proposed globally convergent method and two-stage algorithm have better robustness and efficiency than the existing methods in previous research. They have universality for well- and ill-conditioned systems as well as the cases under ill-conditioned operational modes, heavy loads and inappropriate initial values. They can also handle different limit violations, such as reactive power limit in PV buses and voltage limit with tap changers action, which could significantly benefit real practice.

Acetylene (C2H2) gas concentration is a key parameter in transformer monitoring. In current work, the selective acetylene sensors which based on flower-like ZnO structures with NiO nanoparticles were successfully fabricated. The NiO–ZnO composites were synthesized by two-step hydrothermal method. And various of characterization analyses had been applied to the exploration of crystal structure and the p-n heterojunction. According to the systematic gas sensitivity tests, the response of NiO–ZnO (5%) to 50 ppm C2H2 was 15.23 at 200 °C whereas the response of pure ZnO was 4.1 in the same condition. In addition, the response value of NiO–ZnO (5%) to 50 ppm C2H2 was 3.6 times to 50 ppm H2. Such a good gas-sensing property of NiO–ZnO composites is due to p-n heterojunction and high catalytic activity of NiO.

Future power distribution networks are characterized by changes of uncertain behavior due to the integration of distributed generators (DG) and prosumers, and the design of meter deployment is more critical for the safe and effective network monitoring system. The use of any available and the newly installed metering devices such as micro phasor measurement units (μPMU) and smart meters (SM), could offer much accurate and real-time measuring data. This paper investigates a novel meter deployment method for the distribution network planning, with the objective of ensuring the quality of the state estimation (SE) under consideration of measurement uncertainty, while keeping the total amount of heterogeneous meters at a minimum. In particular, the measurement uncertainty in the SE is depicted via the interval arithmetic (IA) theory, which could offer advantageous over the existing probabilistic and fuzzy approaches. The case studies and comparison results based on an actual distribution network demonstrate the feasibility of the proposed IA-based SE algorithm and the meter deployment method.

Non-ribosomal peptides (NRPs) are one of the largest groups of natural microbial secondary metabolites, which include peptides such as the antibiotics vancomycin and gramicidin, as well as lipopeptides (surfactin, iturin A and bacillomycin). In this study, banana Fusarium wilt disease suppressive and conducive soils were chosen to investigate the role of microbes that harbor the NRPS gene in disease suppression based on the 454-pyrosequencing platform and real-time PCR technique. The results showed that higher abundances and diversity of microbes that harbor the NRPS gene were observed in the suppressive soil samples than in the conducive soil. According to the results of the DNA sequences blastx of NRPS, the main microbial taxa harboring the NRPS gene were identified, and Pseudomonas in Proteobacteria and Streptomyces in Actinobacteria might be remarkably related to Fusarium wilt disease suppression. Furthermore, the Mantel test showed that compared with bacteria community and chemical properties, the microbial community harboring the NRPS gene had a more significant impact on the disease incidences of Fusarium wilt. This study provided non-specific relationships between groups of microbes harboring NRPS genes and Fusarium wilt disease suppression suggesting potential interaction based on correlation evidence, and pointed out a potential mechanism of suppressive soil.

Spinning reserve in the electric power system is vital in dealing with the sudden drop of electricity supply caused by failure, which used to be provided by traditional power generations. With the development of information and communication technologies (ICTs), demand response (DR) is deployed gradually for providing spinning reserve by shedding flexible loads. Air conditioners (ACs) are one of the most high-quality flexible loads due to its high proportion of capacity in electricity consumption. However, power rebound spike (PRS) of AC loads tend to emerge at the end of DR. Therefore, traditional spinning reserve providers (TSRPs) have to ramp to cooperate with ACs immediately. In this paper, a DR management approach is proposed for controlling DR duration time and capacity by sequent temperature configuration. Meanwhile, the connection between PRS and DR duration time is studied. Reliability indices have also been applied to evaluate different cooperation strategies between ACs and TSRPs. Simulations based on Monte Carlo methods are performed quantitatively.

A ppb-level CO sensor based on multi-comb optical-feedback cavity enhanced absorption spectroscopy with a 2.3 μm diode laser was developed for SF6 decomposition analysis in electric power system. The effective optical path reached to 4.5 km within 35 cm length cavity. Besides, through modulating the cavity length five times automatically, the spectral resolution was improved to 0.0015 cm−1 from 0.0071 cm−1. Targeting the R(6) line of CO first overtone band at 4285.01 cm−1, which is interference free from absorption spectra of SF6 mixtures (SF6, SO2, H2S, SO2F2, HF, CF4, CO2, COS, O2 and H2O), the minimum detection limit and detection precision under different gas pressures were performed. At optimum integration time of 30 s determined by Allan deviation analysis and gas pressure of 40 torr, the minimum detection limit and detection precision of CO were better than 18 ppb and 150 ppt, respectively.

A ppb-level CO sensor based on multi-comb optical-feedback cavity enhanced absorption spectroscopy with a 2.3 μm diode laser was developed for SF6 decomposition analysis in electric power system. The effective optical path reached to 4.5 km within 35 cm length cavity. Besides, through modulating the cavity length five times automatically, the spectral resolution was improved to 0.0015 cm−1 from 0.0071 cm−1. Targeting the R(6) line of CO first overtone band at 4285.01 cm−1, which is interference free from absorption spectra of SF6 mixtures (SF6, SO2, H2S, SO2F2, HF, CF4, CO2, COS, O2 and H2O), the minimum detection limit and detection precision under different gas pressures were performed. At optimum integration time of 30 s determined by Allan deviation analysis and gas pressure of 40 torr, the minimum detection limit and detection precision of CO were better than 18 ppb and 150 ppt, respectively.

Leaf surface fertilization with liquid fertilizer produced from amino acids constitutes a potentially important source of nitrogen and is important for plant production. However, few reports have focused on the plant growth promotion by novel liquid fertilizers created by new amino acid resources, let alone the influence on leaf microbiota. In this study, the effects of liquid fertilizer, created by amino acids hydrolyzed from animal hairs with or without the PGPR strain Bacillus amyloliquefaciens SQR9, on crop yield and leaf microbiota were investigated. The results showed that leaves sprayed with amino acid liquid fertilizer (AA) and liquid biological fertilizer (AA9) persistently increased cowpea yields compared to the control amended with chemical fertilizer (CF). Fertilization with amino acid fertilizer showed no significant difference in microbial composition compared with the CF treatment; however, the introduction of functional microbes altered the microbial composition. Pearson correlation analysis, VPA analysis and SEM models all revealed that the amino acids liquid fertilizer application, but not the functional strain or the altered microbiota, performed as the direct driver attributing to yield enhancement. We conclude that leaf fertilization with a novel amino acid liquid fertilizer can greatly enhance the crop yield and that the addition of beneficial microbes may perform the role in further altering the composition of leaf microbiota.

Accurate detection of dissolved aging features in transformer oil is the key to judging the aging degree of oil-paper insulation. In this work, in order to realize in situ detection of furfural dissolved in transformer oil, silver nanoparticles were self-assembled on the surface of gold film with P-aminophenylthiophenol (PATP) as a coupling agent. Rhodamine-6G (R6G) was used as the probe molecule to test the enhancement effect. By optimizing the molecular concentration, molecular deposition time, and silver sol deposition time of PATP, the nanoparticles were made more uniform and compact, and an enhanced substrate with rich hot spots was obtained. The optimum substrate was developed, and surface-enhanced Raman spectroscopy (SERS) detection of trace furfural dissolved in transformer oil was realized. The results showed that the substrate prepared under the conditions of 0.1 mol/L PATP, 5 h deposition in PATP and 12 h immersion in silver sol, had the best reinforcement effect (that is, uniform and compact particle arrangement and no particle clusters). By use of this substrate, the minimum detectable concentration of furfural in transformer oil was about 1.06 mg/L, which provides a new method for fast and nondestructive detection of transformer aging diagnosis.

Numerical methods can provide sufficient information for thermal dynamics of district heating (DH) network. However, high computation burden restricts its application, especially for large-scale DH networks. This dilemma can be overcome by establishing fast numerical calculation procedure and properly selecting the calculation steps without reduction of numerical accuracy. The first-order implicit upwind method is an iteration-free numerical approach for fast simulation of DH pipeline thermal dynamics, while the first-order precision restricts its numerical performance. To further improve the simulation performance, two iteration-free numerical methods with high-order precision, the second-order implicit upwind method and third-order semi-implicit QUICK method are developed. Validations of the three numerical methods are conducted with the measured data of a real DH pipeline. Preferred calculation steps of the three methods are studied via comprehensive numerical experiments. Based on the preferred step size, simulation comparisons of the numerical methods are performed. Results show that the outlet temperature fluctuations of DH pipeline can be feasibly predicted by these methods with satisfying accuracy. The second-order implicit upwind method perform best considering least computation burden (0.003 s) within acceptable error. With the application of the second-order implicit upwind method, simulation analyses on DH pipeline under varying flow velocities are performed.

Efficient numerical simulation of thermo-hydraulic coupled conditions is critical for analysis and control of DH network. However, for most of meshed DH network, the flow directions of its pipelines may change, which will lead to difficulties in effective numerical calculation of the thermo-hydraulic conditions. This paper established an efficient thermo-hydraulic coupled calculation method, which utilizes the topology sorting algorithm to obtain the calculation sequence of all pipelines during numerical thermal transient calculation, according to the flow directions and flow rates of all pipelines. The flow directions and flow rates are solved by hydraulic condition calculation at each time step. The proposed method is applied to a real meshed DH network for thermal dynamic simulation. Independence analysis of hydraulic computation frequency is conducted, and convergences of the simulated temperature variations are observed when hydraulic computation frequency gets larger. Thermal dynamics of the meshed DH network are analyzed with 10-min hydraulic computation interval. Results show that the temperature decay and time delay can be up to 2.7 °C and 210 min for the simulated network. Thermal dynamic characteristics of supply temperature waves are various considering the distance from heat source, fluctuations of outdoor temperature and the variations of substation flow rate.

With no efficient method widely recognized for controlling or preventing tomato bacterial wilt, a devastating disease caused by the soil-borne bacterium Ralstonia solanacearum, tomato production is severely hindered. Therefore, the objective was thus to provide a strategy based on fumigation using ammonium bicarbonate along with organic amendment to reduce disease severity, and the impact of this treatment on the soil microbiome as well as the underlying mechanism leading to disease suppression were evaluated using high-throughput sequencing. Results showed that this combined strategy effectively controls tomato bacterial wilt disease despite the high abundance of R. solanacearum in both the bulk and rhizosphere soil in all treatments. The treatment led to significant changes in the soil bacterial and fungal communities, and at harvest time, fumigation and organic amendment equally affected the variation in the rhizosphere microbiome. Further, a shift in the rhizosphere bacterial community acted as the key factor directly and indirectly suppressing R. solanacearum and controlling bacterial wilt disease. In addition, Rhodanobacter, Terrimonas and Chitinophaga in the rhizosphere were the potential taxa involved in disease suppression. Both fumigation and organic amendment contributed to disease suppression by decreasing the abundance of R. solanacearum and altering the bacterial composition in combination with the stimulation of key bacterial taxa.

With the rapid growth of energy consumption, how to utilize energy in an efficient and cheap way becomes an intensive problem. This paper proposes an optimal operation strategy to reduce system fuel costs and increase system stability by independently considering cooling loads and adjusting CHP heat to power ratio seasonally. In this paper, a mathematical model of CHP operation is introduced to reveal the relationship between the supplementary volume of diesel oil and CHP heat to power ratio. Meanwhile, by analyzing the influence of seasonal factor on energy consumption, CHP heat to power ratio is optimized seasonally. Then, by independently considering the impacts of the cooling loads on system operation, the particle swarm optimization (PSO) algorithm is used to optimize the operation strategy of each device. Finally, this paper validates the positive effects of storage devices on improving system economy and stability under the premise of the time-of-use gas price. Results show that system fuel costs can be reduced by 5.2% if the seasonal factor is considered. Additionally, by optimizing the operation strategy, the peak valley gap of electrical loads in summer reduces by 40.7%. Moreover, the proposed strategy successfully utilizes storage capacity to shift loads and respond to gas price.

Hypothesis The microfluidic technology can drive molecules to organize into aggregates with nano-structures, and gives a possibility to control aggregate morphologies by adjusting hydrodynamic parameters of microfluidics. COMSOL Multiphysics is a useful software to simulate the mixing situation of solutions in microfluidic. Here, experiments and simulation are combined to study the self-assembly of gradient copolymers in the microfluidic device. Experiments Fluorinated gradient copolymers self-assembled in a three-dimensional co-flow focusing microfluidic device (3D CFMD). Hydrodynamic parameters of 3D CFMD were adjusted to control morphologies and the sizes of copolymer aggregates. A simulation software, COMSOL Multiphysics, was used to simulate the mixing and diffusion of outer phase stream and inner phase stream to explore the mixing kinetics of two streams in the microchannels. Findings 3D CFMD offered a novel platform for the continuous and controllable self-assembly of fluorinated gradient copolymer. Various morphologies of copolymer aggregates were obtained in 3D CFMD, but just spherical micelles were formed by a traditional solvent-inducing method. The flow velocity, initial water content of outer-phase stream, and the copolymer concentration of inner-phase stream had great effects on the morphology and size of copolymer aggregates. The simulation results made us a better understanding on the microfluidic self-assembly.

Ice flashover threatens the security and reliability of power transmission. However, the ice flashover mechanism of insulators remains poorly understood. This study analyses water droplet freezing and ion distribution in ice layer under alternating electric field. It also investigates ion migration during icing process of insulator string under alternating electric field and its effects on insulator flashover. Results showed that the average freezing time of water droplets was related to electric field strength. The extent of ion migration during freezing decreased with increasing electric field strength. The maximal melting water conductivity of the ice layer and icicle of the insulator formed under energized condition was higher than the corresponding freezing water conductivity but lower than that under non-energized condition. Furthermore, the hanging location of each insulator significantly affected the melting water conductivity of the ice layer. The surface conductivity of the ice layer increased because of the conductive ion migration in freezing water during freezing, which was an important factor that decreased the flashover voltage of the ice-covered insulator. The existence of alternating electric field would impact the extent of ion migration. This study may serve as a reference for updating prediction flashover model of ice-covered insulators during the melting period.