Does corporate social responsibility matter to management forecast precision? Evidence from China

This article investigates whether socially responsible companies differ from other firms in the quality of earnings forecasts issued by management. Specifically, using 5192 earnings forecast observations of 669 Chinese listed companies from 2010 to 2016, we examine whether companies that perform better in corporate social responsibility (CSR) still provide higher-precision management earnings forecasts compared with companies with poor CSR performance, thereby presenting an image of transparent and accountable disclosures. Through empirical research, this paper finds that CSR is positively associated with management forecast precision. This result is robust to using alternative measures of CSR, considering mandatory disclosure sample and voluntary disclosure sample, and controlling for potential endogeneity concern by adopting the instrumental variable method. Furthermore, we find the relationship between CSR and management forecast precision is stronger in non-state-owned firms. Our findings suggest that socially responsible companies will comply with higher ethical standards and hence maintain their well-established social reputation by disclosing high-quality earnings forecasts, which lends support to the transparent forecast hypothesis. This paper enriches the existing studies regarding the economic consequences of CSR and adds empirical evidence from emerging markets

Multi-Physical Parameter Cross-Sectional Imaging of Quantitative Phase and Fluorescence by Integrated Multimodal Microscopy

Integrated multimodal cross-sectional or volumetric imaging techniques give us fruitful information to understand the behavior or status of target objects such as biological samples. Most of the reported systems for this purpose are either time consuming due to scanning or use additional reference beams such as in interferometry. Therefore, fast, simple, highly efficient, and powerful multimodal imaging systems that can perform cross-sectional imaging with simple algorithms are worth to be investigated. In this paper, a multimodal technique for cross-sectional quantitative phase and fluorescence imaging with computational microscopy is presented. We combine cross-sectional fluorescence and quantitative phase imaging by using the transport of intensity equation (TIE) and numerical wave propagation. The amplitude and phase of the fluorescence light wave with partially spatial coherence are obtained from three defocused intensity patterns. The proposed hybrid imaging system is simple, compact, and non-iterative. We present experimental results of microbeads and fluorescent proteinlabeled living cells of the moss Physcomitrella patensto demonstrate the performance of the proposed imaging system

Three-dimensional fluorescence imaging using the transport of intensity equation

We propose a nonscanning three-dimensional (3-D) fluorescence imaging technique using the transport of intensity equation (TIE) and free-space Fresnel propagation. In this imaging technique, a phase distribution corresponding to defocused fluorescence images with a point-light-source-like shape is retrieved by a TIE-based phase retrieval algorithm. From the obtained phase distribution, and its corresponding amplitude distribution, of the defocused fluorescence image, various images at different distances can be reconstructed at the desired plane after Fresnel propagation of the complex wave function. Through the proposed imaging approach, the 3-D fluorescence imaging can be performed in multiple planes. The fluorescence intensity images are captured with the help of an electrically tunable lens; hence, the imaging technique is free from motion artifacts. We present experimental results corresponding to microbeads and a biological sample to demonstrate the proposed 3-D fluorescence imaging technique

A Survey on Location-Driven Influence Maximization

Influence Maximization (IM), which aims to select a set of users from a social network to maximize the expected number of influenced users, is an evergreen hot research topic. Its research outcomes significantly impact real-world applications such as business marketing. The booming location-based network platforms of the last decade appeal to the researchers embedding the location information into traditional IM research. In this survey, we provide a comprehensive review of the existing location-driven IM studies from the perspective of the following key aspects: (1) a review of the application scenarios of these works, (2) the diffusion models to evaluate the influence propagation, and (3) a comprehensive study of the approaches to deal with the location-driven IM problems together with a particular focus on the accelerating techniques. In the end, we draw prospects into the research directions in future IM research

A series of lanthanide(iii) metal-organic frameworks derived from a pyridyl-dicarboxylate ligand: single-molecule magnet behaviour and luminescence properties

The reactions of LnIII ions with a versatile pyridyl-decorated dicarboxylic acid ligand lead to a series of novel three-dimensional (3D) Ln-MOFs, [Ln3(pta)4(Hpta)(H2O)]·xH2O (Ln = Dy (1), Eu (2), Gd (3), Tb (4), H2pta = 2-(4-pyridyl)-terephthalic acid, x = 6 for 1, 2.5 for 2, 1.5 for 3 and 2 for 4). The Ln3+ ions act as the nine-coordinated Muffin spheres, linking to each other to generate trinuclear {Ln3(OOC)6N2} SBUs, which are further extended to be interesting 3D topology architectures. To the best of our knowledge, the Dy-MOF exhibits a zero-field single-molecule magnet (SMM) behaviour with the largest effective energy barrier among the previously reported 3D MOF-based Dy-SMMs. The combined analyses of a dilution sample (1@Y) and ab initio calculation demonstrate that the thermally assisted slow relaxation is mainly attributed to the single-ion magnetism. Furthermore, fluorescence measurements reveal that H2pta can sensitize EuIII and TbIII characteristic luminescence

Expression profiles of microRNAs in skeletal muscle of sheep by deep sequencing

Objective MicroRNAs are a class of endogenous small regulatory RNAs that regulate cell proliferation, differentiation and apoptosis. Recent studies on miRNAs are mainly focused on mice, human and pig. However, the studies on miRNAs in skeletal muscle of sheep are not comprehensive. Methods RNA-seq technology was used to perform genomic analysis of miRNAs in prenatal and postnatal skeletal muscle of sheep. Targeted genes were predicted using miRanda software and miRNA-mRNA interactions were verified by quantitative real-time polymerase chain reaction. To further investigate the function of miRNAs, candidate targeted genes were enriched for analysis using gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment. Results The results showed total of 1,086 known miRNAs and 40 new candidate miRNAs were detected in prenatal and postnatal skeletal muscle of sheep. In addition, 345 miRNAs (151 up-regulated, 94 down-regulated) were differentially expressed. Moreover, miRanda software was performed to predict targeted genes of miRNAs, resulting in a total of 2,833 predicted targets, especially miR-381 which targeted multiple muscle-related mRNAs. Furthermore, GO and KEGG pathway analysis confirmed that targeted genes of miRNAs were involved in development of skeletal muscles. Conclusion This study supplements the miRNA database of sheep, which provides valuable information for further study of the biological function of miRNAs in sheep skeletal muscle

Roadmap on holography

From its inception holography has proven an extremely productive and attractive area of research. While specific technical applications give rise to 'hot topics', and three-dimensional (3D) visualisation comes in and out of fashion, the core principals involved continue to lead to exciting innovations in a wide range of areas. We humbly submit that it is impossible, in any journal document of this type, to fully reflect current and potential activity; however, our valiant contributors have produced a series of documents that go no small way to neatly capture progress across a wide range of core activities. As editors we have attempted to spread our net wide in order to illustrate the breadth of international activity. In relation to this we believe we have been at least partially successful.This work was supported by Ministerio de Economía, Industria y Competitividad (Spain) under projects FIS2017-82919-R (MINECO/AEI/FEDER, UE) and FIS2015-66570-P (MINECO/FEDER), and by Generalitat Valenciana (Spain) under project PROMETEO II/2015/015

Cell transcriptomic atlas of the non-human primate Macaca fascicularis.

Studying tissue composition and function in non-human primates (NHPs) is crucial to understand the nature of our own species. Here we present a large-scale cell transcriptomic atlas that encompasses over 1 million cells from 45 tissues of the adult NHP Macaca fascicularis. This dataset provides a vast annotated resource to study a species phylogenetically close to humans. To demonstrate the utility of the atlas, we have reconstructed the cell-cell interaction networks that drive Wnt signalling across the body, mapped the distribution of receptors and co-receptors for viruses causing human infectious diseases, and intersected our data with human genetic disease orthologues to establish potential clinical associations. Our M. fascicularis cell atlas constitutes an essential reference for future studies in humans and NHPs.We thank W. Liu and L. Xu from the Huazhen Laboratory Animal Breeding Centre for helping in the collection of monkey tissues, D. Zhu and H. Li from the Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory) for technical help, G. Guo and H. Sun from Zhejiang University for providing HCL and MCA gene expression data matrices, G. Dong and C. Liu from BGI Research, and X. Zhang, P. Li and C. Qi from the Guangzhou Institutes of Biomedicine and Health for experimental advice or providing reagents. This work was supported by the Shenzhen Basic Research Project for Excellent Young Scholars (RCYX20200714114644191), Shenzhen Key Laboratory of Single-Cell Omics (ZDSYS20190902093613831), Shenzhen Bay Laboratory (SZBL2019062801012) and Guangdong Provincial Key Laboratory of Genome Read and Write (2017B030301011). In addition, L.L. was supported by the National Natural Science Foundation of China (31900466), Y. Hou was supported by the Natural Science Foundation of Guangdong Province (2018A030313379) and M.A.E. was supported by a Changbai Mountain Scholar award (419020201252), the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA16030502), a Chinese Academy of Sciences–Japan Society for the Promotion of Science joint research project (GJHZ2093), the National Natural Science Foundation of China (92068106, U20A2015) and the Guangdong Basic and Applied Basic Research Foundation (2021B1515120075). M.L. was supported by the National Key Research and Development Program of China (2021YFC2600200).S