Generalized synchronization and control for incommensurate fractional unified chaotic system and applications in secure communication

summary:A fractional differential controller for incommensurate fractional unified chaotic system is described and proved by using the Gershgorin circle theorem in this paper. Also, based on the idea of a nonlinear observer, a new method for generalized synchronization (GS) of this system is proposed. Furthermore, the GS technique is applied in secure communication (SC), and a chaotic masking system is designed. Finally, the proposed fractional differential controller, GS and chaotic masking scheme are showed by using numerical and experimental simulations

Parameter Optimization of SWMM Model Using Integrated Morris and GLUE Methods

The USEPA (United States Environmental Protection Agency) Storm Water Management Model (SWMM) is one of the most extensively implemented numerical models for simulating urban runoff. Parameter optimization is essential for reliable SWMM model simulation results, which are heterogeneously sensitive to a variety of parameters, especially when involving complicated simulation conditions. This study proposed a Genetic Algorithm-based parameter optimization method that combines the Morris screening method with the generalized likelihood uncertainty estimation (GLUE) method. In this integrated methodology framework, the Morris screening method is used to determine the parameters for calibration, the GLUE method is employed to narrow down the range of parameter values, and the Genetic Algorithm is applied to further optimize the model parameters by considering objective constraints. The results show that the set of calibrated parameters, obtained by the integrated Morris and GLUE methods, can reduce the peak error by 9% for a simulation, and then the multi-objective constrained Genetic Algorithm reduces the model parameters’ peak error in the optimization process by up to 6%. During the validation process, the parameter set determined from the combination of both is used to obtain the optimal values of the parameters by the Genetic Algorithm. The proposed integrated method shows superior applicability for different rainfall intensities and rain-type events. These findings imply that the automated calibration of the SWMM model utilizing a Genetic Algorithm based on the combined parameter set of both has enhanced model simulation performance

Analysis of Wind Pressure Coefficients for Single-Span Arched Plastic Greenhouses Located in a Valley Region Using CFD

The wind pressure coefficient is essential for calculating the wind loads on greenhouses. The wind pressure on single-span arched greenhouses built in valleys differs from those in plain regions. To promote our understanding of wind characteristics and ensure the structural safety of greenhouses in valley areas, an analysis of the distribution law of wind pressure on greenhouses is required. Firstly, we carried out a survey on greenhouse distribution and undulate terrain distribution near greenhouses in Tibet and measured the air density in Lhasa, Tibet. Then, employing the validated realizable k-ε turbulence model and the verification of grid independence, the wind pressure on greenhouses with different greenhouse azimuths was investigated. According to the survey results, values, such as the distance between the greenhouse and the mountain in addition to the greenhouse azimuth, were also obtained for calculating the wind pressure on greenhouses placed in valleys. A calculation model considering the relationship between the mountain distance and the wind pressure coefficient is proposed, whose results fit well with the results from computational fluid dynamics. The relative errors between the two different results are within 15%. Research shows that there is a canyon wind effect in the valley area, and its effect on wind pressure should be considered in greenhouse design. This research is valuable for the design of plastic greenhouses built in Tibet or other valley regions

CircRNA Expression Pattern and ceRNA and miRNA–mRNA Networks Involved in Anther Development in the CMS Line of Brassica campestris

Male-sterile plants provide an important breeding tool for the heterosis of hybrid crops, such as Brassicaceae. In the last decade, circular RNAs (circRNAs), as a novel class of covalently closed and single-stranded endogenous non-coding RNAs (ncRNAs), have received much attention because of their functions as “microRNA (miRNA) sponges” and “competing endogenous RNAs” (ceRNAs). However, the information about circRNAs in the regulation of male-sterility and anther development is limited. In this study, we established the Polima cytoplasm male sterility (CMS) line “Bcpol97-05A”, and the fertile line, “Bcajh97-01B”, in Brassica campestris L. ssp. chinensis Makino, syn. B. rapa ssp. chinensis, and performed RNA expression profiling comparisons between the flower buds of the sterile line and fertile line by whole-transcriptome sequencing. A total of 31 differentially expressed (DE) circRNAs, 47 DE miRNAs, and 4779 DE mRNAs were identified. By using Cytoscape, the miRNA-mediated regulatory network and ceRNA network were constructed, and the circRNA A02:23507399|23531438 was hypothesized to be an important circRNA regulating anther development at the post-transcriptional level. The gene ontology (GO) analysis demonstrated that miRNAs and circRNAs could regulate the orderly secretion and deposition of cellulose, sporopollenin, pectin, and tryphine; the timely degradation of lipids; and the programmed cell death (PCD) of tapetum cells, which play key roles in anther development. Our study revealed a new circRNA–miRNA–mRNA network, which is involved in the anther development of B. campestris, which enriched the understanding of CMS in flowering plants, and laid a foundation for further study on the functions of circRNAs and miRNAs during anther development

A new copula-based standardized precipitation evapotranspiration streamflow index for drought monitoring

Traditional univariate drought indices are likely to be insufficient for reflecting the comprehensive information of drought. Thus, it is of great significance to construct a comprehensive drought index for drought monitoring under the consideration of the complexity of meteorological and hydrological conditions in a changing environment. In this study, a new copula-based Standardized Precipitation Evapotranspiration Streamflow Index (SPESI) was proposed, which can synthetically characterize meteorological and hydrological drought. The temporal change, spatial distribution and return period of drought were comprehensively identified in the Yellow River Basin (YRB) from 1961 to 2015. Subsequently, the links between SPESI and teleconnection factors were revealed using cross wavelet transform technology. The results indicated that: (1) based on the combination of meteorological and hydrological drought information, the constructed SPESI could capture the occurrence, duration and termination of drought sensitively and effectively; (2) the seasonal and annual droughts were increasing in the YRB during 1961–2015, with different temporal change characteristics in each subzone; (3) the month and season with the most serious drought was June and summer, with an average SPESI value of −1.23 and −0.89, respectively; (4) Frank-copula was considered to be the best-fitted copula function in the YRB; and (5) the cross wavelet transform illustrated that teleconnection factors had strong influences on the evolution of drought in the YRB, and the impacts of El Niño-Southern Oscillation (ENSO), Arctic Oscillation (AO) and sunspot on the droughts were stronger than those of Pacific Decadal Oscillation (PDO). This study can provide a reliable and effective multivariate index for drought monitoring, which can also be applied in other regions

Utilizing GRACE-based groundwater drought index for drought characterization and teleconnection factors analysis in the North China Plain

Traditional drought monitoring methods rely on ground station data, which are difficult to reflect large-scale dynamic drought information. Thus, Gravity Recovery and Climate Experiment (GRACE) gravity satellite technology is applied to monitor and estimate drought, which can provide new data sources and measurement instruments for drought investigation. In this study, the GRACE groundwater drought index (GGDI) was utilized as a metric for assessing drought. The temporal evolution, spatial distribution and trend characteristics of drought were comprehensively identified in the North China Plain (NCP) from 2003 to 2015. Subsequently, the links between GGDI and teleconnection factors were clarified using cross wavelet transform technology. The results indicated that: (1) the quantitative results of GRACE were reliable and robust for drought evaluation; (2) the most serious drought event occurred from August 2013 to September 2014, with an average GGDI value of −1.36; (3) the monthly and seasonal droughts were increasing based on the modified Mann-Kendall (MMK) trend test method; and (4) the cross wavelet transform revealed that teleconnection factors had significant influences on drought evolution, and El Niño-Southern Oscillation (ENSO) had the strongest impact on drought in the NCP. This study sheds new insights into drought monitoring by using GRACE gravity satellite, which can be applied in other regions as well

Parameter optimization of SWMM model using integrated Morris and GLUE methods

The USEPA (United States Environmental Protection Agency) Storm Water Management Model (SWMM) is one of the most extensively implemented numerical models for simulating urban runoff. Parameter optimization is essential for reliable SWMM model simulation results, which are heterogeneously sensitive to a variety of parameters, especially when involving complicated simulation conditions. This study proposed a Genetic Algorithm-based parameter optimization method that combines the Morris screening method with the generalized likelihood uncertainty estimation (GLUE) method. In this integrated methodology framework, the Morris screening method is used to determine the parameters for calibration, the GLUE method is employed to narrow down the range of parameter values, and the Genetic Algorithm is applied to further optimize the model parameters by considering objective constraints. The results show that the set of calibrated parameters, obtained by the integrated Morris and GLUE methods, can reduce the peak error by 9% for a simulation, and then the multi-objective constrained Genetic Algorithm reduces the model parameters’ peak error in the optimization process by up to 6%. During the validation process, the parameter set determined from the combination of both is used to obtain the optimal values of the parameters by the Genetic Algorithm. The proposed integrated method shows superior applicability for different rainfall intensities and rain-type events. These findings imply that the automated calibration of the SWMM model utilizing a Genetic Algorithm based on the combined parameter set of both has enhanced model simulation performance

Comprehensive evaluation of hydrological drought and its relationships with meteorological drought in the Yellow River basin, China

Under the background of global warming, the acceleration of water cycle process will aggravate the risk of hydrological drought in the river basin. The Yellow River basin (YRB) is the most severely affected area by drought in China's major river basins, so it is particularly important to comprehensively evaluate the hydrological drought and explore its relationships with meteorological drought in the YRB. In this study, the Standardized Streamflow Index (SSI) was adopted as a hydrological drought index, and the evolution characteristics of hydrological drought were comprehensively evaluated in the YRB from 1961 to 2015. The duration and severity of hydrological drought events were identified based on run theory, and the copula functions with the highest goodness of fit (GOF) were used to investigate the drought return period. Finally, the Standardized Precipitation Evapotranspiration index (SPEI) was adopted as a meteorological drought index, and the relationships between hydrological and meteorological drought were revealed by cross wavelet transform method. The results indicated that: (1) drought showed an increasing trend in the YRB from 1961 to 2015, while the worst drought occurred in 1997; (2) the trend characteristic of drought was different in each subzone; (3) the most severe drought lasted for 32 months, with drought severity of 43.29, and drought return period of 23.26 years; (4) Frank-copula was considered to be the best-fitted copula function in the YRB; and (5) the cross wavelet transform illustrated that there was a positive correlation between hydrological and meteorological drought, and the phase angle relationships indicated that meteorological drought occurred earlier than hydrological drought in the YRB