Figure of Merit and Different Combinations of Observational Data Sets

To constrain cosmological parameters, one often makes a joint analysis with different combinations of observational data sets. In this paper we take the figure of merit (FoM) for Dark Energy Task Force fiducial model (CPL model) to estimate goodness of different combinations of data sets, which include 11 widely-used observational data sets (Type Ia Supernovae, Observational Hubble Parameter, Baryon Acoustic Oscillation, Cosmic Microwave Background, X-ray Cluster Baryon Mass Fraction, and Gamma-Ray Bursts). We analyze different combinations and make a comparison for two types of combination based on two types of basic combinations, which are often adopted in the literatures. We find two sets of combinations, which have strong ability to constrain the dark energy parameters, one has the largest FoM, the other contains less observational data with a relative large FoM and a simple fitting procedure.Comment: To be published in Phys.Rev.D, 20 pages, 4 table

Notes on Ghost Dark Energy

We study a phenomenological dark energy model which is rooted in the Veneziano ghost of QCD. In this dark energy model, the energy density of dark energy is proportional to Hubble parameter and the proportional coefficient is of the order $\Lambda^3_{QCD}$, where $\Lambda_{QCD}$ is the mass scale of QCD. The universe has a de Sitter phase at late time and begins to accelerate at redshift around $z_{acc}\sim0.6$. We also fit this model and give the constraints on model parameters, with current observational data including SnIa, BAO, CMB, BBN and Hubble parameter data. We find that the squared sound speed of the dark energy is negative, which may cause an instability. We also study the cosmological evolution of the dark energy with interaction with cold dark matter.Comment: 20 pages,10 figures,Correct some typos and add new reference

More on QCD Ghost Dark Energy

The difference between vacuum energy of quantum fields in Minkowski space and in Friedmann-Robterson-Walker universe might be related to the observed dark energy. The vacuum energy of the Veneziano ghost field introduced to solve the $U(1)_A$ problem in QCD is of the form, $H+ {\cal O}(H^2)$. Based on this, we study the dynamical evolution of a phenomenological dark energy model whose energy density is of the form $\alpha H+\beta H^2$. In this model, the universe approaches to a de Sitter phase at late times. We fit the model with current observational data including SnIa, BAO, CMB, BBN, Hubble parameter and growth rate of matter perturbation. It shows that the universe begins to accelerate at redshift $z\sim 0.75$ and this model is consistent with current data. In particular, this model fits the data of growth factor well as the $\Lambda CDM$ model.Comment: 14 pages, 4 figures, 2 table

Detecting the cosmic acceleration with current data

The deceleration parameter q as the diagnostic of the cosmological accelerating expansion is investigated. By expanding the luminosity distance to the fourth order of redshift and the so-called y-redshift in two redshift bins and fitting the SNIa data (Union2), the marginalized likelihood distribution of the current deceleration parameter shows that the cosmic acceleration is still increasing, but there might be a tendency that the cosmic acceleration will slow down in the near future. We also fit the Hubble evolution data together with SNIa data by expanding the Hubble parameter to the third order, showing that the present decelerating expansion is excluded within $2\sigma$ error. Further exploration on this problem is also approached in a non-parametrization method by directly reconstructing the deceleration parameter from the distance modulus of SNIa, which depends neither on the validity of general relativity nor on the content of the universe or any assumption regarding cosmological parameters. More accurate observation datasets and more effective methods are still in need to make a clear answer on whether the cosmic acceleration will keep increasing or not.Comment: 20 pages, 5 figures, 3 table

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Seawater Intrusion Risk and Prevention Technology of Coastal and Large-Span Underground Oil Storage Cavern

The presence of a high concentration of Cl− in saltwater will erode the structure and facilities, reducing the stability and service life of the underground oil storage cavern. In order to reduce the risk of seawater intrusion, this paper studies the risk and prevention technology of seawater intrusion based on a case study of a coastal and large-span underground oil storage cavern. A refined three-dimensional hydrogeological model that comprehensively considers permeability coefficient partitions, faults, and fractured zones are constructed. The seepage fields and seawater intrusion risks of the reservoir site in its natural state, during construction, and during operation are examined, respectively. The study quantifies the water inflow and optimizes the seawater intrusion prevention technology. The results indicate that there is no risk of seawater incursion into the cavern under natural conditions. The water inflows after excavating the top, middle, and bottom sections of the main cavern are predicted to be 6797 m3/day, 6895 m3/day, and 6767 m3/day, respectively. During the excavation period, the water supply from the water curtain system is lower than the water inflow of the cavern, providing the maximum water curtain injection of 6039 m3/day. The water level in the reservoir area decreased obviously in the excavation period, but the water flow direction is from the cavern to the sea. Additionally, the concentration of Cl− in the cavern area is less than 7 mol/m3; hereby, there are no seawater intrusion risks. When only the horizontal water curtain system is deployed, seawater intrusion occurs after 18 years of cavern operation. The concentration of Cl− in the southeast of the cavern group exceeds 50 mol/m3 in 50 years, reaching moderate corrosion and serious seawater intrusion. In addition to the horizontal curtain above the cavern, a vertical water curtain system could be added on the southeast side, with a borehole spacing of 10 m and extending to 30 m below the cavern group. This scheme can effectively reduce seawater intrusion risk and extend the service life of the cavern. The findings of this research can be applied as guidelines for underground oil storage caverns in coastal areas to tackle seawater intrusion problems