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With the development of the urban industry in recent years, air pollution in areas such as factories and streets has become more and more serious. Air quality problems directly affect the normal lives of residents. Effectively predicting the future air condition in the area through relevant historical data has high application value for early warning of this area. Through the study of the previous monitoring data, it is found that the pollutant data of adjacent monitoring stations are correlated in more periods. Therefore, this paper proposes a hybrid model based on CNN and Bi-LSTM, using CNN to synthesize multiple adjacent stations with strong correlations to extract spatial features between data, and using Bi-LSTM to extract features in the time dimension to finally achieve pollutant concentration prediction. Using the historical data of 40 monitoring stations in different locations of Fushun city to conduct research. By comparing with the traditional prediction model, the results prove that the model proposed in this paper has higher accuracy and stronger robustness.

In order to protect and promote the effective differentiation and rational utilization of grape germplasm resources, 34 grapevine varieties were selected from the National Germplasm Resources, Taigu Grape Nursery in China: 12 wine grapes (Group I), 14 table grapes (Group II) and 12 seedless grapes (Group III), 4 of which were in Group II, too. For the purpose of genetic characterization, 15 pairs of SSR (simple sequence repeat) primers were used. Sixty-six alleles were generated among Group I, including 64 polymorphic bands, with 1–8 alleles per locus. In Group II, a total of 54 alleles, from 1 to 8 (3.6 on average) alleles per locus, were identified. In Group III, 54 alleles with an average of 3.6 alleles per locus were identified and the percentage of polymorphic alleles was 94%. The 34 varieties clustered into two major clades in the dendrogram: V. vinifera with hybrid of V. vinifera and V. labrusca or hybrid of V. amurensisi and V. vinifera were clearly differentiated. After processing and filtering the raw data, we produced the molecular fingerprint code of each variety. These results showed that the SSR markers are useful for discrimination and analysis of genetic diversity of grapevine varieties. The SSR markers could be used to examine and distinguish the genetic resources among closely related varieties. This is also an effective tool for construction of a grapevine molecular fingerprinting system. The obtained data will be useful in grape breeding in the future.

With the increase of power offtake requirements, it is proposed that the more electric engine (MEE) draws electrical power from a generator mounted directly on the gas turbine shaft-line without the use of a gearbox. It is expected that this arrangement will improve the power density and reliability of the whole system. The challenges include limited available space, high temperature, affordability, high power density and an exceedingly high reliability requirement. The segmented rotor flux switching machine is one of the promising topologies that are suitable for this application. The objective of this article is to investigate quantitatively the influence of several design parameters on the electromagnetic performance. The design parameters include, the excitation type, stator split ratio, segmented rotor length and load advance angle. Back EMF, cogging torque, average torque, torque ripple and magnetic force are considered to be the key evaluation criteria and are used to guide the search for the optimized design. The material discussed in this paper may be helpful to provide insight in the selection of key design parameters in the direct shaft-line gas turbine generators.

The Flux Switching Machine is one of the novel topologies within the hybrid machine class. It has many advantages such as flux focusing effect, compatibility with simple power converters, high fault tolerance with independent concentrated armature windings, mechanical robustness due to its simple salient pole rotor and high power density. With such attributes the machine is a promising candidate for high speed, high power density applications. It includes toothed rotor with permanent magnet excitation and segmented rotor with field coil excitation. This article reports on comparative studies into the mechanical stress, magnetic flux, back EMF, D axis, Q axis inductance and saliency ratio, loss distribution, efficiency and power density for these topologies via finite element analysis under open circuit and various load conditions. Quantitative simulation results reveal that the segmented rotor with field coil excitation topologies exhibit better electromagnetic performance, among which the 12/7 combination of stator pole and rotor segments exhibits superior EM performances than those of other combinations. Parametric analysis with respect to the aspect ratio and rotor segment arc angle are also performed on 12/7 topology to investigate their relationship with the torque, efficiency and power density.