DNA microarray technology is an extremely effective technique for studying gene expression patterns in cells, and the main challenge currently faced by this technology is how to analyze the large amount of gene expres...DNA microarray technology is an extremely effective technique for studying gene expression patterns in cells, and the main challenge currently faced by this technology is how to analyze the large amount of gene expression data generated. To address this, this paper employs a mixed-effects model to analyze gene expression data. In terms of data selection, 1176 genes from the white mouse gene expression dataset under two experimental conditions were chosen, setting up two conditions: pneumococcal infection and no infection, and constructing a mixed-effects model. After preprocessing the gene chip information, the data were imported into the model, preliminary results were calculated, and permutation tests were performed to biologically validate the preliminary results using GSEA. The final dataset consists of 20 groups of gene expression data from pneumococcal infection, which categorizes functionally related genes based on the similarity of their expression profiles, facilitating the study of genes with unknown functions.展开更多
In comparison with the ITRF2000 model, the ITRF2005 model represents a significant improvement in solution generation, datum definition and realization. However, these improvements cause a frame difference between the...In comparison with the ITRF2000 model, the ITRF2005 model represents a significant improvement in solution generation, datum definition and realization. However, these improvements cause a frame difference between the ITRF2000 and ITRF2005 models, which may impact GNSS data processing. To quantify this im- pact, the differences of the GNSS results obtained using the two models, including station coordinates, base- line length and horizontal velocity field, were analyzed. After transformation, the differences in position were at the millimeter level, and the differences in baseline length were less than 1 ram. The differences in the hori- zontal velocity fields decreased with as the study area was reduced. For a large region, the differences in these value were less than 1 mm/a, with a systematic difference of approximately 2 degrees in direction, while for a medium-sized region, the differences in value and direction were not significant.展开更多
We consider the problem of variable selection for the single-index random effects models with longitudinal data. An automatic variable selection procedure is developed using smooth-threshold. The proposed method share...We consider the problem of variable selection for the single-index random effects models with longitudinal data. An automatic variable selection procedure is developed using smooth-threshold. The proposed method shares some of the desired features of existing variable selection methods: the resulting estimator enjoys the oracle property;the proposed procedure avoids the convex optimization problem and is flexible and easy to implement. Moreover, we use the penalized weighted deviance criterion for a data-driven choice of the tuning parameters. Simulation studies are carried out to assess the performance of our method, and a real dataset is analyzed for further illustration.展开更多
In vehicular ad-hoc networks (VANETs), store-carry-forward approach may be used for data sharing, where moving vehicles carry and exchange data when they go by each other. In this approach, storage resource in a vehic...In vehicular ad-hoc networks (VANETs), store-carry-forward approach may be used for data sharing, where moving vehicles carry and exchange data when they go by each other. In this approach, storage resource in a vehicle is generally limited. Therefore, attributes of data that have to be stored in vehicles are an important factor in order to efficiently distribute desired data. In VANETs, there are different types of data which depend on the time and location. Such kind of data cannot be deployed adequately to the requesting vehicles only by popularity-based rule. In this paper, we propose a data distribution method that takes into account the effective life and area in addition to popularity of data. Our extensive simulation results demonstrate drastic improvements on acquisition performance of the time and area specific data.展开更多
We consider the impulsive effect on the exponential synchronization of neural networks with leakage delay under the sampled-data feedback control. We use an appropriate Lyapunov-Krasovskii functional combined with the...We consider the impulsive effect on the exponential synchronization of neural networks with leakage delay under the sampled-data feedback control. We use an appropriate Lyapunov-Krasovskii functional combined with the input delay approach and some inequality techniques to derive sufficient conditions that ensure the exponential synchronization of the delayed neural network. The conditions are formulated in terms of the leakage delay, the sampling period, and the exponential convergence rate. Numerical examples are given to demonstrate the usefulness and the effectiveness of the results.展开更多
In the paper, for the application of stochastic simulation of ground motion, we put forward a method to determine ″the combined effect of amplification and attenuation″ (combined effect for short) of soft rock site...In the paper, for the application of stochastic simulation of ground motion, we put forward a method to determine ″the combined effect of amplification and attenuation″ (combined effect for short) of soft rock site by using digital seismic data of moderate and small earthquakes. Our approach aims at solving the problem of the combined effect of soft rock site, which is difficult to determine in most regions of China because fewer measures were done for S-wave velocity structure. The combined effect of soft rock site can be determined by using the approach recom- mended by us. An example is given to discuss the practical application of the method.展开更多
We investigate cosmological dark energy models where the accelerated expansion of the universe is driven by a field with an anisotropic universe. The constraints on the parameters are obtained by maximum likelihood an...We investigate cosmological dark energy models where the accelerated expansion of the universe is driven by a field with an anisotropic universe. The constraints on the parameters are obtained by maximum likelihood analysis using observational of 194 Type Ia supernovae(SNIa) and the most recent joint light-curve analysis(JLA) sample. In particular we reconstruct the dark energy equation of state parameter w(z) and the deceleration parameter q(z). We find that the best fit dynamical w(z) obtained from the 194 SNIa dataset does not cross the phantom divide line w(z) =-1 and remains above and close to w(z)≈-0.92 line for the whole redshift range 0 ≤ z ≤ 1.75 showing no evidence for phantom behavior. By applying the anisotropy effect on the ΛCDM model, the joint analysis indicates that ?_(σ0)= 0.0163 ± 0.03,with 194 SNIa, ?_(σ0)=-0.0032 ± 0.032 with 238 the SiFTO sample of JLA and ?_(σ0)= 0.011 ± 0.0117 with 1048 the SALT2 sample of Pantheon at 1σ′confidence interval. The analysis shows that by considering the anisotropy, it leads to more best fit parameters in all models with JLA SNe datasets. Furthermore, we use two statistical tests such as the usual χ_(min)~2/dof and p-test to compare two dark energy models with ΛCDM model. Finally we show that the presence of anisotropy is confirmed in mentioned models via SNIa dataset.展开更多
In this paper, it is discussed that two tests for varying dispersion of binomial data in the framework of nonlinear logistic models with random effects, which are widely used in analyzing longitudinal binomial data. O...In this paper, it is discussed that two tests for varying dispersion of binomial data in the framework of nonlinear logistic models with random effects, which are widely used in analyzing longitudinal binomial data. One is the individual test and power calculation for varying dispersion through testing the randomness of cluster effects, which is extensions of Dean(1992) and Commenges et al (1994). The second test is the composite test for varying dispersion through simultaneously testing the randomness of cluster effects and the equality of random-effect means. The score test statistics are constructed and expressed in simple, easy to use, matrix formulas. The authors illustrate their test methods using the insecticide data (Giltinan, Capizzi & Malani (1988)).展开更多
文摘DNA microarray technology is an extremely effective technique for studying gene expression patterns in cells, and the main challenge currently faced by this technology is how to analyze the large amount of gene expression data generated. To address this, this paper employs a mixed-effects model to analyze gene expression data. In terms of data selection, 1176 genes from the white mouse gene expression dataset under two experimental conditions were chosen, setting up two conditions: pneumococcal infection and no infection, and constructing a mixed-effects model. After preprocessing the gene chip information, the data were imported into the model, preliminary results were calculated, and permutation tests were performed to biologically validate the preliminary results using GSEA. The final dataset consists of 20 groups of gene expression data from pneumococcal infection, which categorizes functionally related genes based on the similarity of their expression profiles, facilitating the study of genes with unknown functions.
基金supported by the Special Earthquake Research Project Granted by the China Earthquake Administration(201308009)
文摘In comparison with the ITRF2000 model, the ITRF2005 model represents a significant improvement in solution generation, datum definition and realization. However, these improvements cause a frame difference between the ITRF2000 and ITRF2005 models, which may impact GNSS data processing. To quantify this im- pact, the differences of the GNSS results obtained using the two models, including station coordinates, base- line length and horizontal velocity field, were analyzed. After transformation, the differences in position were at the millimeter level, and the differences in baseline length were less than 1 ram. The differences in the hori- zontal velocity fields decreased with as the study area was reduced. For a large region, the differences in these value were less than 1 mm/a, with a systematic difference of approximately 2 degrees in direction, while for a medium-sized region, the differences in value and direction were not significant.
文摘We consider the problem of variable selection for the single-index random effects models with longitudinal data. An automatic variable selection procedure is developed using smooth-threshold. The proposed method shares some of the desired features of existing variable selection methods: the resulting estimator enjoys the oracle property;the proposed procedure avoids the convex optimization problem and is flexible and easy to implement. Moreover, we use the penalized weighted deviance criterion for a data-driven choice of the tuning parameters. Simulation studies are carried out to assess the performance of our method, and a real dataset is analyzed for further illustration.
文摘In vehicular ad-hoc networks (VANETs), store-carry-forward approach may be used for data sharing, where moving vehicles carry and exchange data when they go by each other. In this approach, storage resource in a vehicle is generally limited. Therefore, attributes of data that have to be stored in vehicles are an important factor in order to efficiently distribute desired data. In VANETs, there are different types of data which depend on the time and location. Such kind of data cannot be deployed adequately to the requesting vehicles only by popularity-based rule. In this paper, we propose a data distribution method that takes into account the effective life and area in addition to popularity of data. Our extensive simulation results demonstrate drastic improvements on acquisition performance of the time and area specific data.
基金supported by the Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(Grant No.2013R1A1A2A10005201)the UAE University(Grant No.NRF Project UAEU-NRF-7-20886)
文摘We consider the impulsive effect on the exponential synchronization of neural networks with leakage delay under the sampled-data feedback control. We use an appropriate Lyapunov-Krasovskii functional combined with the input delay approach and some inequality techniques to derive sufficient conditions that ensure the exponential synchronization of the delayed neural network. The conditions are formulated in terms of the leakage delay, the sampling period, and the exponential convergence rate. Numerical examples are given to demonstrate the usefulness and the effectiveness of the results.
基金The Special Funds for Major State Basic Research Project under Grant No.2002CB412706 and National Natural Science Foundation of China (50468003).
文摘In the paper, for the application of stochastic simulation of ground motion, we put forward a method to determine ″the combined effect of amplification and attenuation″ (combined effect for short) of soft rock site by using digital seismic data of moderate and small earthquakes. Our approach aims at solving the problem of the combined effect of soft rock site, which is difficult to determine in most regions of China because fewer measures were done for S-wave velocity structure. The combined effect of soft rock site can be determined by using the approach recom- mended by us. An example is given to discuss the practical application of the method.
文摘We investigate cosmological dark energy models where the accelerated expansion of the universe is driven by a field with an anisotropic universe. The constraints on the parameters are obtained by maximum likelihood analysis using observational of 194 Type Ia supernovae(SNIa) and the most recent joint light-curve analysis(JLA) sample. In particular we reconstruct the dark energy equation of state parameter w(z) and the deceleration parameter q(z). We find that the best fit dynamical w(z) obtained from the 194 SNIa dataset does not cross the phantom divide line w(z) =-1 and remains above and close to w(z)≈-0.92 line for the whole redshift range 0 ≤ z ≤ 1.75 showing no evidence for phantom behavior. By applying the anisotropy effect on the ΛCDM model, the joint analysis indicates that ?_(σ0)= 0.0163 ± 0.03,with 194 SNIa, ?_(σ0)=-0.0032 ± 0.032 with 238 the SiFTO sample of JLA and ?_(σ0)= 0.011 ± 0.0117 with 1048 the SALT2 sample of Pantheon at 1σ′confidence interval. The analysis shows that by considering the anisotropy, it leads to more best fit parameters in all models with JLA SNe datasets. Furthermore, we use two statistical tests such as the usual χ_(min)~2/dof and p-test to compare two dark energy models with ΛCDM model. Finally we show that the presence of anisotropy is confirmed in mentioned models via SNIa dataset.
基金The project supported by NNSFC (19631040), NSSFC (04BTJ002) and the grant for post-doctor fellows in SELF.
文摘In this paper, it is discussed that two tests for varying dispersion of binomial data in the framework of nonlinear logistic models with random effects, which are widely used in analyzing longitudinal binomial data. One is the individual test and power calculation for varying dispersion through testing the randomness of cluster effects, which is extensions of Dean(1992) and Commenges et al (1994). The second test is the composite test for varying dispersion through simultaneously testing the randomness of cluster effects and the equality of random-effect means. The score test statistics are constructed and expressed in simple, easy to use, matrix formulas. The authors illustrate their test methods using the insecticide data (Giltinan, Capizzi & Malani (1988)).
