Constraints on real scalar inflation from preheating of LATTICEEASY

In this paper, we undertake a detailed study of real scalar inflation by employing LATTICEEASY simulations to investigate preheating phenomena. Generally, the scalar inflation potential with non-minimal coupling can be approximated by a quartic potential. We observe that the evolutionary behavior of this potential remains unaffected by the coupling coefficient. Furthermore, the theoretical predictions for the scalar spectral index ($n_s$) and tensor-to-scalar power ratio (r) are also independent of this coefficient. Consequently, the coefficients of this model are not constrained by Planck observations. Fortunately, the properties of preheating after inflation provide a viable approach to examine these coefficients. Through LATTICEEASY simulations, we trace the evolution of particle number density, scale factor, and energy density during the preheating process. Subsequently, we derive the parameters, such as the energy ratio ($\gamma$) and the e-folding number of preheating ($N_{pre}$), which facilitate further predictions of $n_s$ and $r$. We have successfully validated real scalar inflation model using preheating of LATTICEEASY simulations based on the analytical relationship between preheating and inflation models.Comment: 13 pages, 6 figure

Photoresponsive Polymeric Reversible Nanoparticles via Self-Assembly of Reactive ABA Triblock Copolymers and Their Transformation to Permanent Nanostructures

Azobenzene-functionalized ABA triblock copolymers with controlled molecular weights are prepared first via a sequential ring-opening metathesis polymerization and acyclic diene metathesis polymerization in one-pot, which are readily converted, by a facile esterification, to the modified ABA triblock copolymers. Then, these reactive triblock copolymers can spontaneously self-assemble in a selective solvent to form reproducible and reversible polymeric core-shell nanoparticles. Finally, the stable and permanent shell-crosslinked nanoparticles are obtained by an intramolecular crosslinking reaction in dilute solution under UV light irradiation. These as-prepared polymeric nanoparticles and their precursor incorporating azobenzene chromophores exhibit distinct photoresponsive performance and morphological variation

Study on the Relation between the Mn/Al Mixed Oxides Composition and Performance of FCC Sulfur Transfer Agent

A sulfur transfer agent in catalysts can effectively reduce the emission of SO2 with minimum adverse effects on the catalytic cracking ability of the primary catalyst. In this paper, the composition and performance of sulfur transfer agents with different oxidative active components (such as Cu, Fe, Ni, Co, Ba, Zn and Cr) were prepared by acid peptization technique and characterized by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR) and N2 adsorption-desorption technique. The relationship between the composition and performance of the new sulfur transfer agents was investigated and the regeneration and recycling of the agents were performed. The results indicates that copper is a very good desulfurization active component. Moreover, the presence of CO has no significant effect on the absorption ability of SO2 by the sulfur transfer agent

A new class of metrics for learning on real-valued and structured data

We propose a new class of metrics on sets, vectors, and functions that can be used in various stages of data mining, including exploratory data analysis, learning, and result interpretation. These new distance functions unify and generalize some of the popular metrics, such as the Jaccard and bag distances on sets, Manhattan distance on vector spaces, and Marczewski-Steinhaus distance on integrable functions. We prove that the new metrics are complete and show useful relationships with f-divergences for probability distributions. To further extend our approach to structured objects such as ontologies, we introduce information-theoretic metrics on directed acyclic graphs drawn according to a fixed probability distribution. We conduct empirical investigation to demonstrate the effectiveness on real-valued, high-dimensional, and structured data. Overall, the new metrics compare favorably to multiple similarity and dissimilarity functions traditionally used in data mining, including the Minkowski () family, the fractional family, two f-divergences, cosine distance, and two correlation coefficients. We provide evidence that they are particularly appropriate for rapid processing of high-dimensional and structured data in distance-based learning

Numerical Study on Effects of Geometric Parameters on the Release Characteristics of Straight Sudden Expansion Gas Extinguishing Nozzles

In order to guide the optimization design of the nozzle of the aircraft-fixed gas fire extinguishing system, we studied the influence of nozzle geometric parameters including outlet–inlet area ratio, length–diameter aspect ratio, and wall roughness on the distribution of pressure and velocity in the nozzle on the basis of CFD simulations. Although the structure of the nozzle is axisymmetric, the spatial distribution of the pressure and velocity during the flow and release of gas extinguishing agent is not completely symmetric. It was found that both of the outlet–inlet area ratio (δ) and the length–diameter aspect ratio (ξ) had a significant impact on the distribution characteristics of the pressure and axial velocity in the nozzle. With the increase of δ, the average pressure at the outlet cross-section of the nozzle decreased monotonically, while the average axial velocity at the outlet increased approximately linearly. When ξ≥2, the uniformity of the pressure and velocity distribution at the nozzle outlet was significantly improved. Moreover, with the increase of ξ, the average pressure and the average axial velocity of the outlet both showed a non-monotonic change trend, and the optimal value of ξ should be about 3.0. Compared with δ and ξ, the influence of the nozzle wall roughness (εN) on the flow and release characteristics of the extinguishing agent was weak. With the increase of εN, the average pressure of the nozzle outlet increased slightly, while the average axial velocity at the nozzle outlet decreased slightly

Numerical Study on Effects of Geometric Parameters on the Release Characteristics of Straight Sudden Expansion Gas Extinguishing Nozzles

In order to guide the optimization design of the nozzle of the aircraft-fixed gas fire extinguishing system, we studied the influence of nozzle geometric parameters including outlet–inlet area ratio, length–diameter aspect ratio, and wall roughness on the distribution of pressure and velocity in the nozzle on the basis of CFD simulations. Although the structure of the nozzle is axisymmetric, the spatial distribution of the pressure and velocity during the flow and release of gas extinguishing agent is not completely symmetric. It was found that both of the outlet–inlet area ratio (δ) and the length–diameter aspect ratio (ξ) had a significant impact on the distribution characteristics of the pressure and axial velocity in the nozzle. With the increase of δ, the average pressure at the outlet cross-section of the nozzle decreased monotonically, while the average axial velocity at the outlet increased approximately linearly. When ξ≥2, the uniformity of the pressure and velocity distribution at the nozzle outlet was significantly improved. Moreover, with the increase of ξ, the average pressure and the average axial velocity of the outlet both showed a non-monotonic change trend, and the optimal value of ξ should be about 3.0. Compared with δ and ξ, the influence of the nozzle wall roughness (εN) on the flow and release characteristics of the extinguishing agent was weak. With the increase of εN, the average pressure of the nozzle outlet increased slightly, while the average axial velocity at the nozzle outlet decreased slightly