Do foreign institutional investors drive corporate social responsibility? Evidence from listed firms in China

This paper investigates the effect of qualified foreign institutional investors (QFIIs) on corporate social responsibility (CSR) within the context of listed firms in China. We find that QFIIs offer an incisive channel for improving socially responsible practices. In addition, we find that firms with QFIIs are more likely to comply with the Global Reporting Initiative (GRI) guidelines, and that their sustainability reports tend to be longer. We also find that this positive effect is more pronounced in firms with low initial CSR scores than those with high CSR scores at the time when QFIIs enter the sample. Our empirical evidence further confirms that this positive impact is driven by QFIIs from countries with high social awareness, or QFIIs from geographically distant countries, consistent with their motives, and is linked to the ownership of QFIIs, especially when the QFII is among the top ten of the largest shareholders. Finally, our extended analysis reveals that the increase in CSR performance associated with the presence of QFIIs results in greater firm performance and easier access to finance

Terahertz scale microbunching instability driven by nonevaporable getter coating resistive-wall impedance

Non-evaporable getter (NEG) coating is widely required in the next generation of light sources and circular $e^+e^-$ colliders for small vacuum pipes to improve the vacuum level, which, however, also enhances the high-frequency resistive-wall impedance and often generates a resonator-like peak in the terahertz frequency region. In this paper, we will use the parameters of the planned Hefei Advanced Light Facility (HALF) storage ring to study the impact of NEG coating resistive-wall impedance on the longitudinal microwave instability via particle tracking simulation. Using different NEG coating parameters (resistivity and thickness) as examples, we find that the impedance with a narrow and strong peak in the high frequency region can cause micro-bunching instability, which has a low instability threshold current and contributes to a large energy spread widening above the threshold. In order to obtain a convergent simulation of the beam dynamics, one must properly resolve such a peak. The coating with a lower resistivity has a much less sharp peak in its impedance spectrum, which is helpful to suppress the micro-bunching instability and in return contributes to a weaker microwave instability

Existence and nonexistence of solutions to a critical biharmonic equation with logarithmic perturbation

In this paper, the following critical biharmonic elliptic problem \begin{eqnarray*} \begin{cases} \Delta^2u= \lambda u+\mu u\ln u^2+|u|^{2^{**}-2}u, &x\in\Omega,\\ u=\dfrac{\partial u}{\partial \nu}=0, &x\in\partial\Omega \end{cases} \end{eqnarray*} is considered, where $\Omega\subset \mathbb{R}^{N}$ is a bounded smooth domain with $N\geq5$. Some interesting phenomenon occurs due to the uncertainty of the sign of the logarithmic term. It is shown, mainly by using Mountain Pass Lemma, that the problem admits at lest one nontrivial weak solution under some appropriate assumptions of $\lambda$ and $\mu$. Moreover, a nonexistence result is also obtained. Comparing the results in this paper with the known ones, one sees that some new phenomena occur when the logarithmic perturbation is introduced

Phase Equilibria and Phase Separation of the Aqueous Solution System Containing Lithium Ions

Brines including seawater, concentrated seawater after desalinization, salt lake, oil/gas water, and well bitter are widely distributed around the world. In order to promote the comprehensive utilization and effective protection of the valuable chemical resources existing in brines such as freshwater, lithium, sodium, potassium, and magnesium salts, the systematic foundation and application foundation research including phase equilibria and thermodynamic properties for the salt‐water electrolyte solution are essential, especially for solid lithium salts and their aqueous solution systems

Adaptive multimodal continuous ant colony optimization

Seeking multiple optima simultaneously, which multimodal optimization aims at, has attracted increasing attention but remains challenging. Taking advantage of ant colony optimization algorithms in preserving high diversity, this paper intends to extend ant colony optimization algorithms to deal with multimodal optimization. First, combined with current niching methods, an adaptive multimodal continuous ant colony optimization algorithm is introduced. In this algorithm, an adaptive parameter adjustment is developed, which takes the difference among niches into consideration. Second, to accelerate convergence, a differential evolution mutation operator is alternatively utilized to build base vectors for ants to construct new solutions. Then, to enhance the exploitation, a local search scheme based on Gaussian distribution is self-adaptively performed around the seeds of niches. Together, the proposed algorithm affords a good balance between exploration and exploitation. Extensive experiments on 20 widely used benchmark multimodal functions are conducted to investigate the influence of each algorithmic component and results are compared with several state-of-the-art multimodal algorithms and winners of competitions on multimodal optimization. These comparisons demonstrate the competitive efficiency and effectiveness of the proposed algorithm, especially in dealing with complex problems with high numbers of local optima

MPR-Net:Multi-Scale Pattern Reproduction Guided Universality Time Series Interpretable Forecasting

Time series forecasting has received wide interest from existing research due to its broad applications and inherent challenging. The research challenge lies in identifying effective patterns in historical series and applying them to future forecasting. Advanced models based on point-wise connected MLP and Transformer architectures have strong fitting power, but their secondary computational complexity limits practicality. Additionally, those structures inherently disrupt the temporal order, reducing the information utilization and making the forecasting process uninterpretable. To solve these problems, this paper proposes a forecasting model, MPR-Net. It first adaptively decomposes multi-scale historical series patterns using convolution operation, then constructs a pattern extension forecasting method based on the prior knowledge of pattern reproduction, and finally reconstructs future patterns into future series using deconvolution operation. By leveraging the temporal dependencies present in the time series, MPR-Net not only achieves linear time complexity, but also makes the forecasting process interpretable. By carrying out sufficient experiments on more than ten real data sets of both short and long term forecasting tasks, MPR-Net achieves the state of the art forecasting performance, as well as good generalization and robustness performance

A maximal clique based multiobjective evolutionary algorithm for overlapping community detection

Detecting community structure has become one im-portant technique for studying complex networks. Although many community detection algorithms have been proposed, most of them focus on separated communities, where each node can be-long to only one community. However, in many real-world net-works, communities are often overlapped with each other. De-veloping overlapping community detection algorithms thus be-comes necessary. Along this avenue, this paper proposes a maxi-mal clique based multiobjective evolutionary algorithm for over-lapping community detection. In this algorithm, a new represen-tation scheme based on the introduced maximal-clique graph is presented. Since the maximal-clique graph is defined by using a set of maximal cliques of original graph as nodes and two maximal cliques are allowed to share the same nodes of the original graph, overlap is an intrinsic property of the maximal-clique graph. Attributing to this property, the new representation scheme al-lows multiobjective evolutionary algorithms to handle the over-lapping community detection problem in a way similar to that of the separated community detection, such that the optimization problems are simplified. As a result, the proposed algorithm could detect overlapping community structure with higher partition accuracy and lower computational cost when compared with the existing ones. The experiments on both synthetic and real-world networks validate the effectiveness and efficiency of the proposed algorithm

Integrating non-planar metamaterials with magnetic absorbing materials to yield ultra-broadband microwave hybrid absorbers

Broadening the bandwidth of electromagnetic wave absorbers has greatly challenged material scientists. Here, we propose a two-layer hybrid absorber consisting of a non-planar metamaterial (MM) and a magnetic microwave absorbing material (MAM). The non-planar MM using magnetic MAMs instead of dielectric substrates shows good low frequency absorption and low reflection across a broad spectrum. Benefiting from this and the high frequency strong absorption of the MAM layer, the lightweight hybrid absorber exhibits 90% absorptivity over the whole 2-18 GHz range. Our result reveals a promising and flexible method to greatly extend or control the absorption bandwidth of absorbers. (C) 2014 AIP Publishing LLC

Lithium Recovery from Brines Including Seawater, Salt Lake Brine, Underground Water and Geothermal Water

Demand to lithium rising swiftly as increasing due to its diverse applications such as rechargeable batteries, light aircraft alloys, air purification, medicine and nuclear fusion. Lithium demand is expected to triple by 2025 through the use of batteries, particularly electric vehicles. The lithium market is expected to grow from 184,000 TPA of lithium carbonate to 534,000 TPA by 2025. To ensure the growing consumption of lithium, it is necessary to increase the production of lithium from different resources. Natural lithium resources mainly associate within granite pegmatite type deposit (spodumene and petalite ores), salt lake brines, seawater and geothermal water. Among them, the reserves of lithium resource in salt lake brine, seawater and geothermal water are in 70–80% of the total, which are excellent raw materials for lithium extraction. Compared with the minerals, the extraction of lithium from water resources is promising because this aqueous lithium recovery is more abundant, more environmentally friendly and cost-effective