Discussion on the Difference Between the Business Model and Profit Model

In recent years, the business model and profit model has attracted wide attentions of the domestic and foreign academic circles and enterprise circles, however, during the studies, most of them confuse the commercial mode and profit mode. It will cover the creation of enterprise value, brings the barrier to true methods of accurately reveal the enterprise profits. This paper introduced the definition of the business model and profit model, and then analyzes the relationship and differences between them. Key words: Business model; Profit model; Definition; Relationship; Difference

Preparation and enhanced properties of Fe3O4 nanoparticles reinforced polyimide nanocomposites

Polyimide (PI) nanocomposite reinforced with Fe3O4 nanoparticles (NPs) at various NPs loadings levels of 5.0, 10.0, 15.0, and 20.0 wt% were prepared. The chemical interactions of the Fe3O4 NPs/PI nanocomposites were characterized using Fourier Transform Infrared (FT-IR) spectroscopy. X-ray Diffraction (XRD) results revealed that the addition of NPs had a significant effect on the crystallization of PI. Scanning electron microscope (SEM) and the atomic force microscope (AFM) were used to characterize the dispersion and surface morphology of the Fe3O4 NPs and the PI nanocomposites. The obtained optical band gap of the nanocomposites characterized using Ultraviolet-Visible Diffuse Reflectance Spectroscopy (UV-Vis DRS) was decreased with increasing the Fe3O4 loading. Differential scanning calorimetry (DSC) results showed a continuous increase of Tg with increasing the Fe3O4 NPs loading. Some differences were observed in the onset decomposition temperature between the pure PI and nanocomposites since the NPs and the PI matrix were physically entangled together to form the nanocomposites. The contact angle of pure PI was larger than that of Fe3O4/PI nanocomposites films, and increased with increasing the loading of Fe3O4. The degree of swelling was increased with increasing the Fe3O4 loading and the swelling time. The dielectric properties of the nanocomposite were strongly related to the Fe3O4 loading levels. The Fe3O4/PI magnetic property also had been improved with increasing the loading of the magnetic nanoparticles

Species responses to changing precipitation depend on trait plasticity rather than trait means and intraspecific variation

Trait-based approaches are key to develop mechanistic understanding of differences in plant species performance under environmental change. While mean trait values have been widely used to link functional traits to species performance, the contribution of intraspecific trait variation and trait plasticity remains unclear. Moreover, environmentally induced changes in species biomass are caused by changes in the number of individuals and individual growth rate, both of which should be influenced by trait differences and plasticity. Our goal in this study is to use trait-based information to explain species performance via changes in species abundance and individual weight. We measured the mean, intraspecific variation and plasticity of nine above-ground plant traits, and a further three mean root traits from 10 common species in a precipitation manipulation experiment in semi-arid grassland. We used this trait information to explain differences in the responses of species biomass, abundance and mean individual weight to changing precipitation. Species responses were calculated as the normalised slopes of the regressions between species biomass, abundance and individual weight with the manipulated precipitation amount. We found strong differences in species responses to changing precipitation for species biomass, abundance and mean individual weight. Reduced precipitation decreased biomass, abundance and mean individual weight for some species, but increased them for others. Biomass and mean individual weight of species with resource-acquisitive traits, such as shallow rooted species, showed stronger positive responses to changing precipitation compared to resource-conservative traits, like those with deep roots. For above-ground traits, trait plasticity was the strongest predictor of species responses compared to mean traits and intraspecific trait variation. In addition, trait plasticity regulated changes in species biomass more via changes in species abundance than mean individual weight. These results indicate that trait plasticity is a key driver for determining species-specific responses to changing precipitation and needs more consideration for understanding and predicting ecosystem structure and functioning in future climate scenarios. A free Plain Language Summary can be found within the Supporting Information of this article

A New Framework of Quantitative analysis Based on WGAN

This paper follows the logic of financial investment strategies based on WGAN, one of AI algorithms. The trend prediction module and the distribution characteristics of price time series are on the basis of the WGAN. Multiple factors extraction and analysis are on the basis of natural language processing technology. Buy-sell decision module is based on DQN algorithm which is one of reinforcement learning algorithms. And a designed risk control network is used as a protector for capital of investors. A multiple feature combination is proposed to describe the stock market. In the end, four Sector ETFs were selected to make simulation experiments

A New Framework of Quantitative analysis Based on WGAN

This paper follows the logic of financial investment strategies based on WGAN, one of AI algorithms. The trend prediction module and the distribution characteristics of price time series are on the basis of the WGAN. Multiple factors extraction and analysis are on the basis of natural language processing technology. Buy-sell decision module is based on DQN algorithm which is one of reinforcement learning algorithms. And a designed risk control network is used as a protector for capital of investors. A multiple feature combination is proposed to describe the stock market. In the end, four Sector ETFs were selected to make simulation experiments

A Deep Reinforcement Learning-Based Path-Following Control Scheme for an Uncertain Under-Actuated Autonomous Marine Vehicle

In this article, a deep reinforcement learning-based path-following control scheme is established for an under-actuated autonomous marine vehicle (AMV) in the presence of model uncertainties and unknown marine environment disturbances is presented. By virtue of light-of-sight guidance, a surge-heading joint guidance method is developed within the kinematic level, thereby enabling the AMV to follow the desired path accurately. Within the dynamic level, model uncertainties and time-varying environment disturbances are taken into account, and the reinforcement learning control method using the twin-delay deep deterministic policy gradient (TD3) is developed for the under-actuated vehicle, where path-following actions are generated via the state space and hybrid rewards. Additionally, actor-critic networks are developed using the long-short time memory (LSTM) network, and the vehicle can successfully make a decision by the aid of historical states, thus enhancing the convergence rate of dynamic controllers. Simulation results and comprehensive comparisons on a prototype AMV demonstrate the remarkable effectiveness and superiority of the proposed LSTM-TD3-based path-following control scheme

Thoracic empyema due to nontuberculous mycobacteria in an immunocompetent patient without pulmonary disease: a case report

Abstract Background Pleural involvement by non-tuberculous mycobacteria (NTM), especially NTM empyema in the immunocompetent patient without pulmonary diseases is a rare disease. It is difficult to diagnose with only a few cases of immunodeficient patients in the literature. Case presentation We describe a 63-year-old male with empyema due to NTM and highlight the challenges of diagnosis. Conclusions Non-tuberculous mycobacterial infection should be considered as a cause of pleuritis or empyema without pulmonary disease, however it is a real diagnostic dilemma

Scattering of Light From Graphene-Coated Nanoparticles of Negative Refractive Index

The recent study of the Lorenz-Mie scattering from a graphene-coated sphere is extended to the case when the sphere is of negative refractive index, focusing on the two intriguing phenomena observed previously for a “bare” negative index sphere of sub-wavelength sizes, namely, the non-Rayleigh behavior and the low-frequency resonances. It is observed that while the graphene coating can regulate the non-Rayleigh scattering back towards Rayleigh, manifested with its own low frequency plasmonic resonances in the IR region; the low-frequency peak observed previously can be significantly suppressed with the result rather insensitive to the doping level of the graphene layer. These graphene-induced effects are clarified via a study of the Bohren-Hunt theory in the limit of small size parameters for the negative refracting sphere

The Immunomodulatory Effects of A2 β-Casein on Immunosuppressed Mice by Regulating Immune Responses and the Gut Microbiota

The aim of this study was to investigate the immunomodulatory effects of A2 β-casein (β-CN) in cyclophosphamide-induced immunosuppressed BALB/c mice. Experiments conducted in vitro revealed that A2 β-CN digestive products have potent immunostimulatory activities. Animal studies demonstrated that A2 β-CN improved the immunological organ index reduction trend caused by cyclophosphamide, reduced the pathological damage to the spleen tissue in immunosuppressed mice, increased the release of IL-17A, IgG, and IgA, and reduced the production of IL-4. By regulating the relative abundance of advantageous bacteria like Oscillospira, Lactobacillus, and Bifidobacteria and harmful bacteria like Coprococcus and Desulfovibrionaceae, A2 β-CN improved gut microbiota disorders in immunosuppressed mice. Moreover, A2 β-CN promoted the production of short-chain fatty acids and increased the diversity of the gut microbiota. Therefore, ingestion of A2 β-CN is beneficial to the host’s immune system and gut health. These findings provide insights for the future application of A2 β-CN-related dairy products

Model Evaluation of the Microbial Metabolic Processes in a Hydrogen-Based Membrane Biofilm Reactor for Simultaneous Bromate and Nitrate Reduction

The H2-based membrane biofilm reactor (H2-MBfR) has been acknowledged as a cost-effective microbial reduction technology for oxyanion removal from drinking water sources, but it remains unknown how the evolution of biofilm characteristics responds to the changing critical operating parameters of the H2-MBfR for simultaneous bromate (BrO3−) and nitrate (NO3−) elimination. Therefore, an expanded multispecies model, applicable to mechanistically interpret the bromate-reducing bacteria (BRB)- and denitrifying bacteria (DNB)-dominated metabolic processes in the biofilm of the H2-MBfR, was developed in this study. The model outputs indicate that (1) increased BrO3− loading facilitated the metabolism of BRB by increasing BRB fraction and BrO3− gradients in the biofilm, but had a marginal influence on NO3− reduction; (2) H2 pressure of 0.04 MPa enabled the minimal loss of H2 and the extension of the active region of BRB and DNB in the biofilm; (3) once the influent NO3− concentration was beyond 10 mg N/L, the fraction and activity of BRB significantly declined; (4) BRB was more tolerant than DNB for the acidic aquatic environment incurred by the CO2 pressure over 0.02 MPa. The results corroborate that the degree of microbial competition for substrates and space in the biofilm was dependent on system operating parameters