We perform a detailed investigation on the cosmological constraints on the holographic dark energy (HDE) model by using the Planck data. We find that HDE can provide a good fit to the Planck high-ℓ (ℓ 40) temperature power spectrum, while the discrepancy at ℓ ≃ 20 − 40 found in the ΛCDM model remains unsolved in the HDE model. The Planck data alone can lead to strong and reliable constraint on the HDE parameter c. At the 68% confidence level (CL), we obtain c = 0.508 ± 0.207 with Planck+WP+lensing, favoring the present phantom behavior of HDE at the more than 2σ CL. By combining Planck+WP with the external astrophysical data sets, i.e. the BAO measurements from 6dFGS+SDSS DR7(R)+BOSS DR9, the direct Hubble constant measurement result (H 0 = 73.8± 2.4 km s −1 Mpc −1 ) from the HST, the SNLS3 supernovae data set, and Union2.1 supernovae data set, we get the 68% CL constraint results c = 0.484 ± 0.070, 0.474 ± 0.049, 0.594 ± 0.051, and 0.642 ± 0.066, respectively. The constraints can be improved by 2%-15% if we further add the Planck lensing data into the analysis. Compared withthe WMAP-9 results, the Planck results reduce the error by 30%-60%, and prefer a phantom-like HDE at higher significant level. We also investigate the tension between different data sets. We find no evident tension when we combine Planck data with BAO and HST. Especially, we find that the strong correlation between Ω m h 3 and dark energy parameters is helpful in relieving the tension between the Planck and HST measurements. The residual value of χ 2 Planck+WP+HST − χ 2 Planck+WP is 7.8 in the ΛCDM model, and is reduced to 1.0 or 0.3 if we switch the dark energy to w model or the holographic model. When we introduce supernovae data sets into the analysis, some tension appears. We find that the SNLS3 data set is in tension with all other data sets; for example, for the Planck+WP, WMAP-9 and BAO+HST, the corresponding ∆χ 2 is equal to 6.4, 3.5 and 4.1, respectively. As a comparison, the Union2.1 data set is consistent with these three data sets, but the combination Union2.1+BAO+HST is in tension with Planck+WP+lensing, corresponding to a large ∆χ 2 that is equal to 8.6 (1.4% probability). Thus, combining internal inconsistent data sets (SNIa+BAO+HST with Planck+WP+lensing) can lead to ambiguous results, and it is necessary to perform the HDE data analysis for each independent data sets. Our tightest self-consistent constraint is c = 0.495 ± 0.039 obtained from Planck+WP+BAO+HST+lensing.

Apoptosis proteins have a central role in the development and homeostasis of an organism. These proteins are very important for understanding the mechanism of programmed cell death. Based on the idea of coarse-grained description and grouping in physics, a new feature extraction method with grouped weight for protein sequence is presented, and applied to apoptosis protein subcellular localization prediction associated with support vector machine. For the same training dataset and the same predictive algorithm, the overall prediction accuracy of our method in Jackknife test is 13.2% and 15.3% higher than the accuracy based on the amino acid composition and instability index. Especially for the else class apoptosis proteins, the increment of prediction accuracy is 41.7 and 33.3 percentile, respectively. The experiment results show that the new feature extraction method is efficient to extract the structure information implicated in protein sequence and the method has reached a satisfied performance despite its simplicity. The overall prediction accuracy of EBGW_SVM model on dataset ZD98 reach 92.9% in Jackknife test, which is 8.2-20.4 percentile higher than other existing models. For a new dataset ZW225, the overall prediction accuracy of EBGW_SVM achieves 83.1%. Those implied that EBGW_SVM model is a simple but efficient prediction model for apoptosis protein subcellular location prediction.

We monitored the change in the number density of cetyltrimethylammonium bromide (CTAB) molecules at a water/nitrobenzene (W/NB) liquid/liquid interface by a newly developed time-resolved quasi-elastic laser scattering (QELS) method. The results are used to discuss the molecular collective behavior there. From the time-courses after the injection of a CTAB solution beyond its critical micelle concentration (cmc), we found an anomalous temporary increase of the number density of CTAB molecules at the interface, which cannot be explained by a simple diffusion model. This suggests that the transfer of CTAB micelles across the interface occurs in the following process: the collapse of micelles at the interface region; the oriented adsorption of CTAB molecules onto the interface, forming a monolayer; and the desorption from the interface. Thermodynamic evaluation results also support this model; that is, the equilibrium number density of CTAB molecules at the interface follows the Langmuir adsorption isotherm obtained from our measurement, and the adsorption energy calculated from the isotherm agrees well with the theoretical value of the micelles.