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Purpose The purpose of this study is to examine the influence of firm performance on corporate social responsibility (CSR) and its possible moderating effect. Despite the significance of CSR, there remains an extensive debate about how it is affected by firm performance. Design/methodology/approach The conceptual model is mainly built on goal-setting theory. Based on archival data from multiple data sets on 1,650 companies, collected from 2010 to 2017, the hypotheses are tested using the two-stage instrumental variable regression method. Findings There is an inverted U-shaped relationship between firm performance and CSR that first increases and then decreases. In addition, considering the boundary conditions, state ownership makes the inverted U-shaped curve steeper, while high executive wage concentration makes the inverted U-shaped curve flatter. Research limitations/implications This study harmonizes the traditional contradictory findings of the influence of firm performance on CSR, that is, it supports a positive, negative or neutral relationship between the two. Originality/value This research provides a necessary structure for the CSR literature. By delving deeply into the relationship between firm performance and CSR, it enables scholars to better address the critical management question of whether earning more will lead to doing good.

In order to improve the effectiveness of signal processing, according to the actual needs of signal processing and the current problems in signal processing, this paper introduces an improved LSTM recurrent neural network algorithm to construct the signal processing algorithm. Moreover, this paper sets up the functional structure of this paper based on the neural network model structure, and builds an intelligent analysis system for signal processing tasks based on the LSTM recurrent neural network algorithm. In addition, this paper analyzes the system algorithm flow in detail, and combines experimental research to carry out the effectiveness of the system constructed in this paper, and conducts quantitative analysis from two aspects of signal threshold prediction and signal processing effect. Finally, this paper conducts experimental results research with the support of mathematical statistics methods. From the research point of view, it can be known that the system constructed in this paper has good signal processing functions.

In this study, the surfactant activated lipase from Aspergillus oryzae was used to prepare magnetic hybrid nanoflowers by embedding Fe3O4 magnetic nanoparticles (MNPs) into hybrid nanoflowers (MhNF). Meanwhile, MNPs were integrated into the activated lipase hybrid nanoflowers through covalent cross-linking (cross-linked-MhNF). Activity recovery of the MhNF and cross-linked-MhNF was 190% and 174%, respectively. However, activity recovery of lipase hybrid nanoflowers (hNF) only retained 77%. Furthermore, the MhNF displayed higher Kcat/Km value than free lipase, indicating high catalytic efficiency of MhNF. Compared with free lipase, the MhNF exhibited high tolerance against methanol and storage stability. Furthermore, the MhNF could be easily recycled by magnet without obvious activity loss. After reusing for 10 cycles, the activated hNF only retained 26% activity of its original activity, while the MhNF still maintained 84% activity of its initial activity, indicating excellent reusability. In the reaction of producing biodiesel from soybean oil, the MhNF-catalyzed biodiesel yield reached 88%, while the free enzyme was only 69%. The yield of biodiesel catalyzed by MhNF was maintained at 76% even after 6 consecutive cycles.

Enzyme catalysis has been attracting increasing interest in the past twenty years. Nevertheless, most reports concerning enzyme catalysis have been carried out using single enzymes. Recent years, multiple enzyme cascade reactions have a significant role for the production of many compounds at an industrial level because they permit to perform very complex reactions. Especially, the development of coimmobilized multienzymatic systems is increasingly driven by economic and environmental constraints that provide an impetus to develop alternatives to conventional multistep synthetic methods. Up to now, process optimization and novel strategies of coimmobilized multienzymatic systems hardly have been reviewed. In this review, we focus on some recent novel techniques in preparing co-immobilized multienzymatic systems and the up-to-date advances in the application of multienzymatic systems. Moreover, we also discuss the improvements that co-immobilization multienzymatic systems offer enzymes such as reusability, catalytic activity, and stability.

This paper proposed the role and composition of an e-business ecosystem, and analyzed some problems likely to occur among members of an e-business ecosystem such as trust, interest scrambling, information asymmetry, and coordination. Finally, it proposed four coordinating mechanisms-relation coordinating, interest coordinating, information coordinating, and operation coordinating.