Identifying cryptic species poses a substantial challenge to both biologists and naturalists due to morphological similarities. Bemisia tabaci is a cryptic species complex containing more than 44 putative species;seve...
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Identifying cryptic species poses a substantial challenge to both biologists and naturalists due to morphological similarities. Bemisia tabaci is a cryptic species complex containing more than 44 putative species;several of which are currently among the world's most destructive crop pests. Interpreting and delimiting the evolution of this species complex has proved problematic. To develop a comprehensive framework for species delimitation and identification, we evaluated the performance of distinct data sources both individually and in combination among numerous samples of the B. tabaci species complex acquired worldwide. Distinct datasets include full mitogenomes, single-copy nuclear genes, restriction site-associated DNA sequencing, geographic range, host speciation, and reproductive compatibility datasets. Phylogenetically, our well-supported topologies generated from three dense molecular markers highlighted the evolutionary divergence of species of the B. tabaci complex and suggested that the nuclear markers serve as a more accurate representation of B. tabaci species diversity. Reproductive compatibility datasets facilitated the identification of at least 17 different cryptic species within our samples. Native geographic range information provides a complementary assessment of species recognition, while the host range datasets provide low rate of delimiting resolution. We further summarized different data performances in species classification when compared with reproductive compatibility, indicating that combination of mtCOI divergence, nuclear markers, geographic range provide a complementary assessment of species recognition. Finally, we represent a model for understanding and untangling the cryptic species complexes based on the evidence from this study and previously published articles.
A voice conversion （VC） system was designed based on Gaussian mixture model （GMM） and radial basis function （RBF） neural network. As a voice conversion model, RBF network needs quantities of training data to imp...
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A voice conversion （VC） system was designed based on Gaussian mixture model （GMM） and radial basis function （RBF） neural network. As a voice conversion model, RBF network needs quantities of training data to improve its performance. For one speech, the networks trained by different segments of data have different transformation effects. Since trying segment by segment to obtain the best conversion effect is complex, a conversion method was proposed, that uses GMM for statistics before training RBF network to aim at the problem. The speech transformation and representation using adaptive interpolation of weighted spectrum （STRAIGHT） model is used for accurate extraction of vocal tract spectrum. Then GMM is used to classify the numerous spectral parameters. The obtained mean parameters were trained in RBF network. Experiment reveals that, the soft classification ability of GMM can promptly realize the reduction and classification of training data under the premise of ensuring the training effect. The selection complexity is decreased thereafter. Compared to the conventional RBF network training methods, this method can make the transformation of spectral parameters more effective and improve the quality of converted speech.
Fault diagnosis of nonlinear systems is of great importance in theory and practice, and the parameter estimation method is an effective strategy. Based on the framework of moving horizon estimation, fault parameters a...
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Fault diagnosis of nonlinear systems is of great importance in theory and practice, and the parameter estimation method is an effective strategy. Based on the framework of moving horizon estimation, fault parameters are identified by a proposed intelligent optimization algorithm called PSOSA, which could avoid premature convergence of standard particle swarm optimization （PSO） by introducing the probabilistic jumping property of simulated annealing （SA）. Simulations on a three-tank system show the effectiveness of this optimization based fault diagnosis strategy.
This article deals with downlink scheduling for multiuser multiple-input multiple-output （MIMO） systems, where the base station communicates with multiple users simultaneously through transmit beamforming. Most of t...
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This article deals with downlink scheduling for multiuser multiple-input multiple-output （MIMO） systems, where the base station communicates with multiple users simultaneously through transmit beamforming. Most of the existing transmission schemes for multiuser MIMO systems focus on optimizing sum rate performance of the system. The individual quality of service （QoS） requirements （such as packet delay and minimum transmission rate for the data traffic） are rarely considered. In this article, a novel scheduling strategy is proposed, where we try to optimize the global system performance under individual QoS constraints. By performing scheduling into two steps, namely successive user selection and power allocation, the scheduler can achieve efficient resource utilization while maintaining the QoS requirements of all users. Extensive simulations and analysis are given to show the effectiveness of the proposed scheduler.
Using the nonequilibrium Green＇s function technique, we investigate the Kondo effect in the quantum dot with perpendicular magnetic fields, in which one is the Zeeman splitting lies in the z-direction and the other i...
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Using the nonequilibrium Green＇s function technique, we investigate the Kondo effect in the quantum dot with perpendicular magnetic fields, in which one is the Zeeman splitting lies in the z-direction and the other is the spin flip points at the x-direction. It is found whatever one or two magnetic fields are applied, the local density of states （LDOS） will split into two peaks. The positions of two Kondo resonance peaks are determined by Zeeman energy △ when J = 0, and by √△^2＋J^2 when J≠0.
Some Mo-V-Te--La catalysts with varied component were prepared by hydrothermal synthesis and dried with microwave method. The component of the catalyst were greatly affected the crystal structure and Raman spectrum. T...
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Some Mo-V-Te--La catalysts with varied component were prepared by hydrothermal synthesis and dried with microwave method. The component of the catalyst were greatly affected the crystal structure and Raman spectrum. The phase in the catalysts was different when the Mo, V, and Te content varied. When the catalyst containing the same Mo, V content, due to the effect of dopant of Te element （V0.07 Mo0.93）5O14 became the main phase in the catalyst. The catalyst also showed good activity for the reaction of selective oxidation propane to acrolein and acrylic acid.
This paper focuses on the effects of five different passive turbine tip clearance flow control methods on the tip clearance flow physics, which consists of a partial suction side squealer tip, a double squealer tip, a...
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This paper focuses on the effects of five different passive turbine tip clearance flow control methods on the tip clearance flow physics, which consists of a partial suction side squealer tip, a double squealer tip, a pressure side tip shelf with inclined squealer tip on a double squealer tip, a tip platform extension edge in pressure side and in suction side respectively. A pressure-correction based, 3D Reynolds-averaged Navier-Stokes equations CFD code with Reynolds Stress Model was adopted. The variable specific heat was considered. The detailed tip clearance flow field with different squealer rims was described with the streamline and the velocity vector. Accordingly, the mechanisms of five passive controls were elucidated; the effects of the passive controls on turbine efficiency and tip clearance flow field were illuminated. The results showed that the secondary flow loss near the outer casing including the tip leakage losses and the passage vortex losses could be reduced in all the five passive control methods. The turbine efficiency could be increased via the rational passive turbine tip clearance flow control. The Improved PS Squealer had the best effect on turbine efficiency, and the efficiency increased by 0.215%.
In this paper,the effects of Lorentz force on drag reduction for a circular cylinder have been studied experimentally and *** on its effects on drag reduction,the Lorentz force is found to be classified into two parts...
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In this paper,the effects of Lorentz force on drag reduction for a circular cylinder have been studied experimentally and *** on its effects on drag reduction,the Lorentz force is found to be classified into two parts：one acts directly on the cylinder,named as the wall Lorentz force,and the other called the field Lorentz force acts on the fluid inside the boundary *** wall Lorentz force leads to the generation of a thrust,whereas the field Lorentz force results in drag *** the former dominates the drag variation,the drag would reduce accordingly and even turn into negative （thrust） with the application of Lorentz force.
The group headed by Professor Chenli Liu in the Institute of Synthetic Biology,Shenzhen Institutes of Advanced Technology(SIAT)recently developed a microfluidic synchronizer to continuously produce minimally disturbed...
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The group headed by Professor Chenli Liu in the Institute of Synthetic Biology,Shenzhen Institutes of Advanced Technology(SIAT)recently developed a microfluidic synchronizer to continuously produce minimally disturbed,normally growing synchronous bacterial cells(ACS Synth Biol.2019,8(5):962–967).This research highlight features the main advances made in this work and presents the findings of this study in the context of synthetic biology.
Hierarchical clustering algorithms, such as Pearson＇s correlation, Euclidean distance, Euclidean distance harmonic, Spearman rank correlation, Kendall＇s tau, and City-block distance, were used to find the best way t...
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Hierarchical clustering algorithms, such as Pearson＇s correlation, Euclidean distance, Euclidean distance harmonic, Spearman rank correlation, Kendall＇s tau, and City-block distance, were used to find the best way to establish theoretical MAPK/Erk signaling pathway on the basis of breast cancer line MCF-7 gene expressions. The algorithm constructs a hierarchy from top to bottom on the basis of a self-organizing tree. It dynamically finds the number of clusters at each level. It was found that only Euclidean distance harmonic is fit for the analysis of the cascade composed from a RAF1 （c-Raf）, a MKNK1, a MAPKK （MEK1/2） to MAPK （Erk） in breast cancer line MCF-7. The result is consistent with the biological experimental MAP/Erk signaling pathway, and the theoretical MAPK/Erk signaling pathway on breast cancer line MCF-7 is set up.
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