Do ESOPs enhance firm performance? Evidence from China's reform experiment

China introduced employee stock ownership plans (ESOPs) in 1992 purely as an employee incentive scheme. The government initiated the policy experiment on ESOPs as part of China's reform of its state-owned enterprises, and it was abruptly terminated 2. years after initiation. This policy experiment resulted in an exogenous sample of ESOPs that allows us to provide the first evidence from Chinese firms on the performance-ESOP relation. After examining a variety of performance measures, including ROA, ROE, Tobin's q, and productivity, we find little difference in performance between ESOP firms and non-ESOP firms. © 2010 Elsevier B.V.postprin

Interdisciplinary Fairness in Imbalanced Research Proposal Topic Inference: A Hierarchical Transformer-based Method with Selective Interpolation

The objective of topic inference in research proposals aims to obtain the most suitable disciplinary division from the discipline system defined by a funding agency. The agency will subsequently find appropriate peer review experts from their database based on this division. Automated topic inference can reduce human errors caused by manual topic filling, bridge the knowledge gap between funding agencies and project applicants, and improve system efficiency. Existing methods focus on modeling this as a hierarchical multi-label classification problem, using generative models to iteratively infer the most appropriate topic information. However, these methods overlook the gap in scale between interdisciplinary research proposals and non-interdisciplinary ones, leading to an unjust phenomenon where the automated inference system categorizes interdisciplinary proposals as non-interdisciplinary, causing unfairness during the expert assignment. How can we address this data imbalance issue under a complex discipline system and hence resolve this unfairness? In this paper, we implement a topic label inference system based on a Transformer encoder-decoder architecture. Furthermore, we utilize interpolation techniques to create a series of pseudo-interdisciplinary proposals from non-interdisciplinary ones during training based on non-parametric indicators such as cross-topic probabilities and topic occurrence probabilities. This approach aims to reduce the bias of the system during model training. Finally, we conduct extensive experiments on a real-world dataset to verify the effectiveness of the proposed method. The experimental results demonstrate that our training strategy can significantly mitigate the unfairness generated in the topic inference task.Comment: 19 pages, Under review. arXiv admin note: text overlap with arXiv:2209.1391

Treatment of Nutrient-rich Municipal Wastewater Using Mixotrophic Strain Chlorella kessleri GXLB-9

Growing algae on wastewaters offers a promising way for effective N and P recycling as well as low-cost algal biofuel feedstock accumulation. In this study, a locally isolated microalgae strain Chlorella kessleri GXLB-9 (C. kessleri GXLB-9), was evaluated for growth and nutrient removal efficiency grown in nutrient-rich wastewater centrifuged from activated sludge (NWCAS). And 3-(3, 4-dichlorophenyl)-1, 1-dimethyl urea (DCMU), one chemical that could block microalgae-based photosynthetic pathway, was used to evaluate the growth mode (autotrophy, heterotrophy or mixotrophy) of C. kessleri GXLB-9. The results showed that C. kessleri GXLB-9 was a facultative heterotrophic strain and 7-day batch cultivation idicated that the maximal removal efficiencies for total nitrogen, total phosphorus, and chemical oxygen demand (COD) were over 59%, 81%, and 88%, respectively, with high growth rate (0.490 d-1) and high biomass productivity (269 mg L-1 d-1). In addition, the impact of light-dark cycle on algae growth and nutrient removal was minimal while pH has significant impact on both algae growth and nutrient removal efficiency

Intrinsic nonlinear Hall effect and gate-switchable Berry curvature sliding in twisted bilayer graphene

Though the observation of quantum anomalous Hall effect and nonlocal transport response reveals nontrivial band topology governed by the Berry curvature in twisted bilayer graphene, some recent works reported nonlinear Hall signals in graphene superlattices which are caused by the extrinsic disorder scattering rather than the intrinsic Berry curvature dipole moment. In this work, we report a Berry curvature dipole induced intrinsic nonlinear Hall effect in high-quality twisted bilayer graphene devices. We also find that the application of the displacement field substantially changes the direction and amplitude of the nonlinear Hall voltages, as a result of a field-induced sliding of the Berry curvature hotspots. Our work not only proves that the Berry curvature dipole could play a dominant role in generating the intrinsic nonlinear Hall signal in graphene superlattices with low disorder densities, but also demonstrates twisted bilayer graphene to be a sensitive and fine-tunable platform for second harmonic generation and rectification

Systematic analysis of human microRNA divergence based on evolutionary emergence

AbstractMicroRNAs (miRNAs) play important roles in post-transcriptional gene expression control. To gain new insight into human miRNAs, we performed comprehensive sequence-based homology search for known human miRNAs to study the evolutionary distribution of human miRNAs. Furthermore, we carried out a series of studies to compare various features for different lineage-specific human miRNAs. Our results showed that major expansions of human miRNA genes coincide with the advent of vertebrates, mammals and primates. Further system-level analysis revealed significant differences in human miRNAs that arose from different evolutionary time points for a number of characteristics, implicating genetic and functional diversification for different human miRNAs during evolution. Our finds provide more useful knowledge for further exploring origins and evolution of human miRNA genes