Effects of temperature on performances and hydration process of sulphoaluminate cement-based dual liquid grouting material and its mechanisms

Journal of Thermal Analysis and Calorimetry - In order to find out the rules of the effect of temperature on performances and hydration process of sulphoaluminate cement-based dual liquid grouting...     

The effects of learning in production and group size on the lot-sizing problem

One of the lot-sizing problem extensions that received noticeable attention in the literature is the one that investigated the effects of learning in production. The studies along this line of research assumed learning to improve with the number of repetitions following a power form. There is evidence also that the group size, i.e., the number of workers learning in a group affects performance (time per unit). This note revisits the problem and modifies it by incorporating the group size, along with cumulative production, as a proxy for measuring performance. Numerical examples are provided to illustrate the behavior of the modified model. The results of the two models are also compared to draw some meaningful insights and conclusions. Although the results favor using a simple univariate learning curve, considering group size when modeling lot-sizing problems can significantly affect the unit production cost.     

Video deraining via nonlocal low-rank regularization

Outdoor videos captured in rainy weather may be significantly corrupted by the undesired rain streaks, which severely affect the video processing tasks in outdoor computer vision systems. In this paper, we propose a tensor-based video rain streaks removal method using the nonlocal low-rank regularization. Specifically, we first divide videos into overlapped spatial–temporal patches. Then for each patch, we group its nonlocal similar spatial–temporal patches to form a third-order tensor. To model the clean videos, we characterize the wealth redundancy by adopting the tensor nuclear norm to regularize the low-rankness of the third-order tensors formed by similar spatial–temporal patches of clean videos. We also consider the piecewise smoothness and the temporal continuity of clean videos and utilize the unidirectional total variation to enhance the smoothness and continuity. Moreover, as rain streaks are sparse and smooth along the rain direction, we model the rain streaks by employing an ℓ₁ norm and the unidirectional total variation penalty to boost the sparsity and directional smoothness, respectively. We develop an efficient alternating direction method of multipliers to solve the proposed model. Experimental results on both synthetic and real rainy videos show that our method outperforms the state-of-the-art methods quantitatively and qualitatively.     

Novel biogeography-based optimization algorithm with hybrid migration and global-best Gaussian mutation

The Biogeography-Based Optimization algorithm and its variants have been used widely for optimization problems. To get better performance, a novel Biogeography-Based Optimization algorithm with Hybrid migration and global-best Gaussian mutation is proposed in this paper. Firstly, a linearly dynamic random heuristic crossover strategy and an exponentially dynamic random differential mutation one are presented to form a hybrid migration operator, and the former is used to get stronger local search ability and the latter strengthen the global search ability. Secondly, a new global-best Gaussian mutation operator is put forward to balance exploration and exploitation better. Finally, a random opposition learning strategy is merged to avoid getting stuck in local optima. The experiments on the classical benchmark functions and the complexity functions from CEC-2013 and CEC-2017 test sets, and the Wilcoxon, Bonferroni-Holm and Friedman statistical tests are used to evaluate our algorithm. The results show that our algorithm obtains better performance and faster running speed compared with quite a few state-of-the-art competitive algorithms. In addition, experimental results on Minimum Spanning Tree and K-means clustering optimization show that our algorithm can cope with these two problems better than the comparison algorithms.     

Nucleoside alkaloids with anti-platelet aggregation activity from the rhizomes of Ligusticum striatum

Two new (1–2) and six known (3–8) nucleoside alkaloids were isolated from the rhizomes of Ligusticum striatum DC. Compounds 1 and 2 (liguadenosines A and B) were unusual N-10 substituted adenosine derivatives. Their structures were elucidated by extensive spectroscopic analyses and ECD calculation. Most of them significantly inhibited the abnormal increase in platelet aggregation induced by ADP at concentrations of 50 and 100 μM. Particularly, the inhibitory effect of 3 was equivalent to aspirin.     

First principles study on the structural,electronic and phonon properties of monolayer B2Si

Using first principles density functional theory, we predict a monolayer B₂Si structure with space group Pmm2 in the present work. This structure is confirmed to be dynamically stable. Based on the plane wave pseudopotential approach, the charge density, electron localization function, density of states, energy band, phonon property and thermal conductivity of Pmm2-B₂Si are systematically studied. It is interesting that the sp² hybridization and coordination bond of Si are found in Pmm2-B₂Si, which is the most important factor for its structural stability. The density of states and energy band analysis reveals that Pmm2-B₂Si is metallic because of the partial occupied Si 3pz and B 2pz states. Moreover, the acoustic-optical coupling is important for phonon transport in Pmm2-B₂Si, and the contribution of optical modes to the lattice thermal conductivity along the [100] and [010] directions is 13% and 12%, respectively. This study gives a fundamental understanding of the structural, electronic and phonon properties in Pmm2-B₂Si.