Quasi-Rip: A New Type of Rip Model without Cosmic Doomsday

The fate of our universe is an unceasing topic of cosmology and the human being. The discovery of the current accelerated expansion of the universe significantly changed our view of the fate of the universe. Recently, some interesting scenarios concerning the fate of the universe attracted much attention in the community, namely the so-called "Little Rip" and "Pseudo-Rip". It is worth noting that all the Big Rip, Little Rip and Pseudo-Rip arise from the assumption that the dark energy density $\rho(a)$ is monotonically increasing. In the present work, we are interested to investigate what will happen if this assumption is broken, and then propose a so-called "Quasi-Rip" scenario, which is driven by a type of quintom dark energy. In this work, we consider an explicit model of Quasi-Rip in detail. We show that Quasi-Rip has an unique feature different from Big Rip, Little Rip and Pseudo-Rip. Our universe has a chance to be rebuilt from the ashes after the terrible rip. This might be the last hope in the "hopeless" rip.Comment: 9 pages, 2 figures, 1 table, revtex4; v2: discussions added, Phys. Rev. D in press; v3: published versio

Hybrid intelligent deep kernel incremental extreme learning machine based on differential evolution and multiple population grey wolf optimization methods

Focussing on the problem that redundant nodes in the kernel incremental extreme learning machine (KI-ELM) which leads to ineffective iteration increase and reduce the learning efficiency, a novel improved hybrid intelligent deep kernel incremental extreme learning machine (HI-DKIELM) based on a hybrid intelligent algorithms and kernel incremental extreme learning machine is proposed. At first, hybrid intelligent algorithms are proposed based on differential evolution (DE) and multiple population grey wolf optimization (MPGWO) methods which used to optimize the hidden layer neuron parameters and then to determine the effective hidden layer neurons number. The learning efficiency of the algorithm is improved by reducing the network complexity. Then, we bring in the deep network structure to the kernel incremental extreme learning machine to extract the original input data layer by layer gradually. The experiment results show that the HI-DKIELM methods proposed in this paper with more compact network structure have higher prediction accuracy and better ability of generation compared with other ELM methods

Ray tracing of multiple transmitted/reflected/converted waves in 2-D/3-D layered anisotropic TTI media and application to crosswell traveltime tomography

To overcome the deficiency of some current grid-/cell-based ray tracing algorithms, which are only able to handle first arrivals or primary reflections (or conversions) in anisotropic media, we have extended the functionality of the multistage irregular shortest-path method to 2-D/3-D tilted transversely isotropic (TTI) media. The new approach is able to track multiple transmitted/reflected/converted arrivals composed of any kind of combinations of transmissions, reflections and mode conversions. The basic principle is that the seven parameters (five elastic parameters plus two polar angles defining the tilt of the symmetry axis) of the TTI media are sampled at primary nodes, and the group velocity values at secondary nodes are obtained by tri-linear interpolation of the primary nodes across each cell, from which the group velocities of the three wave modes (qP, qSV and qSH) are calculated. Finally, we conduct grid-/cell-based wave front expansion to trace multiple transmitted/reflected/converted arrivals from one region to the next. The results of calculations in uniform anisotropic media indicate that the numerical results agree with the analytical solutions except in directions of SV-wave triplications, at which only the lowest velocity value is selected at the singularity points by the multistage irregular shortest-path anisotropic ray tracing method. This verifies the accuracy of the methodology. Several simulation results show that the new method is able to efficiently and accurately approximate situations involving continuous velocity variations and undulating discontinuities, and that it is suitable for any combination of multiple transmitted/reflected/converted arrival tracking in TTI media of arbitrary strength and tilt. Crosshole synthetic traveltime tomographic tests have been performed, which highlight the importance of using such code when the medium is distinctly anisotropi

Different nitrogen saturation thresholds for above-, below-, and total net primary productivity in a temperate steppe

Identifying the thresholds for the positive responses of total net primary productivity (NPP) to nitrogen (N) enrichment is an essential prerequisite for predicting the benefits of N deposition on ecosystem carbon sequestration. However, the responses of below-ground NPP (BNPP) to N enrichment are unknown in many ecosystems, which limits our ability to understand the carbon cycling under the scenario of increasing N availability. We examined the changes in above-ground NPP (ANPP), BNPP, and NPP of a temperate meadow steppe across a wide-ranging N addition gradient (0, 2, 5, 10, 20, and 50 g N m -2  year -1 ) during 5 years. Both ANPP and NPP increased nonlinearly with N addition rates. The N saturation threshold for ANPP (T A ) and NPP (T N ) was at the rate of 13.11 and 6.70 g N m -2  year -1 , respectively. BNPP decreased with increasing N addition when N addition rates ˃5 g N m -2  year -1 , resulting in much lower T N than T A . Soil N enrichment played a key role in driving the negative impacts of high N addition rates on BNPP, and consequently on the earlier occurrence of N saturation threshold for NPP. Our results highlight the negative effects of soil N enrichment on NPP in natural grasslands super-saturated with N. Furthermore, by considering ANPP and BNPP simultaneously, our results indicate that previous findings from above-ground might have over-estimated the positive effects of N deposition on primary productivity

Prognostic Value of Metastatic No.8p LNs in Patients with Gastric Cancer

Background. To evaluate prognostic value of metastatic No.8p LNs in patients with gastric cancer. Methods. From August 2002 to December 2011, a total of 284 gastric cancer patients who underwent gastrectomy with No.8p LNs dissection were analyzed retrospectively in this study. Patients were divided into two groups according to the status of No.8p LNs. Clinicopathological features were collected to conduct the correlation analysis. Follow-up was carried out up to December 31st, 2014. Overall survival was analyzed. Results. Out of 284 patients, metastatic No.8p LNs were found in 24 (8.5%) patients. Compared with other 260 cases, these patients suffered morphologically larger tumor (P=0.003), node stage (P=0.000), and metastatic stage (P=0.000). The 3-year overall survival rate was 26% in No.8p-positive group and 53% in No.8p-negative group. No significant difference of cumulative survival rates existed between the No.8p-positive group and No.8p-negative stage IV group (26% versus 28%, P=0.923). Patients with other distant metastasis or not in No.8p+ group had similar cumulative survival rates (24% versus 28%, P=0.914). Conclusions. Positive No.8p LNs were a poor but not an independent prognostic factor for patients with GC and should be recognized as distant metastasis