Non parametric estimation of the diffusion coefficients of a diffusion with jumps

In this article, we consider a jump diffusion process ${\left(X_t\right)}_{t\ge 0}$, with drift function $b$, diffusion coefficient $\sigma$ and jump coefficient ${\xi }^2$. This process is observed at discrete times $t=0,\Delta ,\dots ,n\Delta$. The sampling interval $\Delta$ tends to 0 and the time interval $n\Delta$ tends to infinity. We assume that ${\left(X_t\right)}_{t\ge 0}$ is ergodic, strictly stationary and exponentially $\beta$-mixing. We use a penalized least-square approach to compute adaptive estimators of the functions ${\sigma }^2+{\xi }^2$ and ${\sigma }^2$. We provide bounds for the risks of the two estimators.     

Anisotropy Effects and Observational Data on the Constraints of Evolution Dark Energy Models

We investigate cosmological dark energy models where the accelerated expansion of the universe is driven by a field with an anisotropic universe. The constraints on the parameters are obtained by maximum likelihood analysis using observational of 194 Type Ia supernovae(SNIa) and the most recent joint light-curve analysis(JLA) sample. In particular we reconstruct the dark energy equation of state parameter w(z) and the deceleration parameter q(z). We find that the best fit dynamical w(z) obtained from the 194 SNIa dataset does not cross the phantom divide line w(z) =-1 and remains above and close to w(z)≈-0.92 line for the whole redshift range 0 ≤ z ≤ 1.75 showing no evidence for phantom behavior. By applying the anisotropy effect on the ΛCDM model, the joint analysis indicates that ?_(σ0)= 0.0163 ± 0.03,with 194 SNIa, ?_(σ0)=-0.0032 ± 0.032 with 238 the SiFTO sample of JLA and ?_(σ0)= 0.011 ± 0.0117 with 1048 the SALT2 sample of Pantheon at 1σ′confidence interval. The analysis shows that by considering the anisotropy, it leads to more best fit parameters in all models with JLA SNe datasets. Furthermore, we use two statistical tests such as the usual χ_(min)~2/dof and p-test to compare two dark energy models with ΛCDM model. Finally we show that the presence of anisotropy is confirmed in mentioned models via SNIa dataset.     

Residual stress in polyethylene pipes

This paper deals with residual stress in polyethylene (PE) pipes as an important factor that influences their lifetime. Residual hoop stress distribution in a PE pipe was determined using a methodology previously carried out by the authors on polypropylene pipes. Axial residual stress magnitude was determined by comparison of experimental data and finite element modelling. Based on the obtained results, a new simplified methodology for determining the residual hoop stress is proposed. The method needs only one circular specimen made of pipe, but, unlike older methods, provides a more precise estimation of residual hoop stress distribution taking into account its exponential shape. Some older results from literature are recalculated using this method and residual hoop stress of various PE pipe grades and dimensions are then compared. To provide an idea of residual hoop stress influence on lifetime of a pipe, a lifetime estimation is carried out for the examined pipe.     

Strong cliques in vertex-transitive graphs

A clique (resp, independent set) in a graph is strong if it intersects every maximal independent set (resp, every maximal clique). A graph is clique intersect stable set (CIS) if all of its maximal cliques are strong and localizable if it admits a partition of its vertex set into strong cliques. In this paper we prove that a clique $C$ in a vertex-transitive graph $\mathrm{\Gamma }$ is strong if and only if $\text{◂=▸}\text{◂⋅▸}\mid C\mid \mid I\mid =\mid V\left(\mathrm{\Gamma }\right)\mid$ for every maximal independent set $I$ of $\mathrm{\Gamma }$. On the basis of this result we prove that a vertex-transitive graph is CIS if and only if it admits a strong clique and a strong independent set. We classify all vertex-transitive graphs of valency at most 4 admitting a strong clique, and give a partial characterization of 5-valent vertex-transitive graphs admitting a strong clique. Our results imply that every vertex-transitive graph of valency at most 5 that admits a strong clique is localizable. We answer an open question by providing an example of a vertex-transitive CIS graph which is not localizable.     

Wettability and surface energy of parylene F deposited on PDMS

For the first time, the wettability and surface energy of parylene F were investigated. The results showed that parylene F had a hydrophobic surface with an eigen water contact angle of 104.7 ± 0.6°. We found that 3.5 μl probe liquid was an optimal value for the contact angle measurement of parylene F. Moreover, we found that the Lifshitz–van der Waals/acid–base approach was unsuitable for determining the surface energy of parylene F, whereas the Owens–Wendt–Kaelble approach and the limitless liquid–solid interface wetting system were compatible. The surface energy of parylene F was estimated to be 27.06 mJ/m² (Owens–Wendt–Kaelble) and 40.41 mJ/m² (Limitless liquid-solid interface wetting system). Furthermore, this investigation also provided a reference for the applications of empirical and physics-based semi-empirical approaches for the estimation of surface energy.     

一种基于序贯估计的直达声区水面舰船 被动测距方法 *

该文利用基于射线的盲解卷积方法，从直达声区的水面舰船噪声中提取出船和锚系于海底的垂直接收阵之间的时域信道响应，并利用直达波在不同阵元相对于参考阵元的到达时间差，通过序贯方法，利用射线模型和声速剖面信息，对水面舰船距接收阵的距离进行了估计。通过处理海深约为580 m的2016年美国圣巴巴拉海峡的实验数据，对1.6~3.5 km直达声区范围内Anna Maersk商船与垂直阵之间的距离进行了估计，验证了测距方法的有效性，并将结果与系统测量值和几何方法的估计值进行了比较。由于该方法不需要对海底参数进行估计，所以在海底参数未知时要优于传统匹配场方法；在声速剖面存在跃层且海底为多层分布的复杂信道条件下，该方法仍能对距离进行有效估计，且与测量值的相对误差在6%以内，小于几何方法的估计误差，测距结果精度较高。