Redshift drift exploration for interacting dark energy

By detecting redshift drift in the spectra of Lyman-$\alpha$ forest of distant quasars, Sandage-Loeb (SL) test directly measures the expansion of the universe, covering the "redshift desert" of $2 \lesssim z \lesssim5$. Thus this method is definitely an important supplement to the other geometric measurements and will play a crucial role in cosmological constraints. In this paper, we quantify the ability of SL test signal by a CODEX-like spectrograph for constraining interacting dark energy. Four typical interacting dark energy models are considered: (i) $Q=\gamma H\rho_c$, (ii) $Q=\gamma H\rho_{de}$, (iii) $Q=\gamma H_0\rho_c$, and (iv) $Q=\gamma H_0\rho_{de}$. The results show that for all the considered interacting dark energy models, relative to the current joint SN+BAO+CMB+$H_0$ observations, the constraints on $\Omega_m$ and $H_0$ would be improved by about 60\% and 30--40\%, while the constraints on $w$ and $\gamma$ would be slightly improved, with a 30-yr observation of SL test. We also explore the impact of SL test on future joint geometric observations. In this analysis, we take the model with $Q=\gamma H\rho_c$ as an example, and simulate future SN and BAO data based on the space-based project WFIRST. We find that in the future geometric constraints, the redshift drift observations would help break the geometric degeneracies in a meaningful way, thus the measurement precisions of $\Omega_m$, $H_0$, $w$, and $\gamma$ could be substantially improved using future probes.Comment: 6 pages, 5 figures; accepted for publication in EPJC. arXiv admin note: text overlap with arXiv:1407.712

Stakeholders’ perception towards sustainable business locations of purpose-built office in Kuala Lumpur, Malaysia

Purpose-built office (PBO) market in Malaysia has become more challenging in coming years since the sustainability has added new dimensions to the complexity in the location evaluation of PBO. Nevertheless, there is a lack of research in this country that studied the sustainable business locations of PBO based on the stakeholders’ perceptions. Therefore, this thesis aimed to develop a sustainable business location model to match the stakeholders’ perceptions on location of PBO in Golden Triangle Kuala Lumpur, Malaysia. For this purpose, ten main sustainable business location characteristics of PBO were identified. In developing the sustainable business location model of PBO, 8 out of 10 selected local expert panels who are property clients, valuers, property managers, estate agents and property consultants were involved in the content validation. For investigating the stakeholders’ perceptions towards sustainable business location characteristics of PBO, 190 pairwise comparison questionnaire sets were distributed and 157 questionnaires (82.63% response rate) were responded by the occupants of 19 selected PBOs. Analytic Network Process (ANP) technique was used to analyse the weight of dependence for sustainable business location characteristics of PBO based on the perceptions of PBO’s occupants. Hence, supermatrix approach was used to develop the location factor matrix for sustainable business locations of PBO. The research was successful in developing an ANP model and location factor matrix for sustainable business locations of PBO. The results has showed that the availability of transport options (C2), efficiency of property market (C5), access to public transportation and terminal (C8), and access to market (C9) characteristics have high limiting values for all the selected streets. Therefore, the results obtained in this research can provide new academic attainment for Malaysia in improving the development of purpose-built office market in Malaysia

Sliding Window Technique For Forest Fire Prediction

Every year, forest fire in Portugal causes large areas of land being destroyed and there are cases of death. In this research pattern discovery is being used to generate patterns of meteorological conditions in relation to area burnt of forest fire. The meteorological conditions that are being investigated are temperature, relative humidity, wind speed and rainfall. The combination of these four conditions forms the patterns that are of interest in this research. The sliding window technique is being used to generate patterns for meteorological conditions that are significant to forest fire. The initial dataset is being transformed by changing the continuous values of the attributes into categorical values of the attributes. The patterns are then being generated through the sliding window methodology. Patterns that could not be validated are being regarded as invalid and thus are discarded while the patterns that could be validated are taken for further analysis. Patterns that are valid are then being grouped based on the burnt area associated with a pattern. The rules are then generated by transforming the categorical values into intervals and the merging of different records into the same rules. The rule generation stage produces eight distinct patterns of meteorological conditions that could predict the size of forest fire. In addition, this study showed that the sliding window technique could be used in non-temporal data

Spatiotemporal dynamics of a diffusive predator–prey model with fear effect

This paper concerned with a diffusive predator–prey model with fear effect. First, some basic dynamics of system is analyzed. Then based on stability analysis, we derive some conditions for stability and bifurcation of constant steady state. Furthermore, we derive some results on the existence and nonexistence of nonconstant steady states of this model by considering the effect of diffusion. Finally, we present some numerical simulations to verify our theoretical results. By mathematical and numerical analyses, we find that the fear can prevent the occurrence of limit cycle oscillation and increase the stability of the system, and the diffusion can also induce the chaos in the system