Synthesis and Properties of Magnetic Carbon Nanocages Particles for Dye Removal

Magnetic carbon nanocages (MCNCs) with multiform pore structure have been synthesized by a simple low temperature carbonization process. Biorenewable lignin was used as a cheap and carbon-rich precursor for the first time. The products were characterized by X-ray diffraction (XRD), nitrogen adsorption-desorption, energy dispersive X-ray spectroscopy (EDS), vibrating sample magnetometer (VSM), transmission electron microscopy (TEM), and Raman spectrum. XRD pattern and Raman spectrum showed that the product has a high degree of graphitization crystallinity. TEM micrograph indicated that the synthesized MCNCs have the hierarchical pore and cage structure. Due to these characteristics, the obtained magnetic carbon nanocages can be used as efficient and recycled adsorbents in the removal of dye staff from textile wastewater

Research of Individual Neural Network Generation and Ensemble Algorithm Based on Quotient Space Granularity Clustering

The aim of this paper is to develop an individual neural network generation and ensemble algorithm based on quotient space granularity clustering. Firstly, we give the characteristics of the quotient space granularity and affinity propagation(AP) clustering. Secondly, we introduce the quotient space concept to the AP clustering analysis, which can find an optimal granularity from all possible granularities. Then using improved AP clustering algorithm to seek optimal results of sample clustering and using different individual neural network to learn different categories of samples so that the degree of difference between networks and the generalization ability of neural network ensemble(NNE) can be improved. Further, according to the degree of correlation between the input data and the sample category to adaptively adjust ensemble weights. The algorithm proposed here is not only a method of generating the individual neural networks, but also can adaptively adjust ensemble weights of individual neural network. Experiments show that our proposed method is validity and correctness

Research and Development of Granular Neural Networks

Granular neural networks(GNNs) as a new calculation system structure based on Granular Computing(GrC) and artificial neural network can be able to deal with all kinds of granular information of the real world. This article has made the summary on the development and the present situation of GNNs. Firstly, it introduces the basic model of GrC: word calculation model based on fuzzy sets theory, rough sets model, granular computing model based on quotient space theory and so on, summarizes the research progress of fuzzy neural networks(FNNs) and rough neural networks(RNNs), then analyses the ensemble-based methods of GNNs, researches their meeting point of three main GrC methods, and finally points out the research and development direction of GNNs

How can COVID-19 vaccines benefit people? A study based on the theory of the commons

COVID−19 vaccination is a fundamental step toward controlling the COVID−19 pandemic and defusing the public health crisis it has caused. Existing studies have demonstrated that equitable distribution of COVID−19 vaccines can only be achieved if these vaccines are treated as public goods. The question remains how to transform COVID−19 vaccines into public goods. In this paper, based on the theory of commons governance, the theoretical mechanism is analyzed to realize the adequate distribution of COVID−19 vaccines. Furthermore, feasible methods on how COVID−19 vaccines can benefit the people through the successful popularization of these vaccines in China are summarized. The results show that to ensure adequate supply of COVID−19 vaccines, government intervention is required because the government can expand the supply of the vaccine by balancing individual benefits for producing enterprises and the overall benefits for society. The government can also guarantee the right of every member in society to receive COVID−19 vaccines, thus enabling these vaccines to benefit the whole nation. By analyzing how COVID−19 vaccines benefit the people, this paper further verifies that national intervention plays an essential role in the supply and distribution of COVID−19 vaccines in both developed and developing countries. It may further mean that state intervention can play an essential role in continuing to respond to major public health events in the possible future

Discovering the Mechanisms of Oleodaphnone as a Potential HIV Latency-Reversing Agent by Transcriptome Profiling

Latent HIV is a key factor that makes AIDS difficult to cure. Highly effective and specific latent HIV activators can effectively activate latent HIV, and then combined with antiretroviral therapy to achieve a functional cure of AIDS. Here, four sesquiterpenes (1–4) including a new one (1), five flavonoids (5–9) including three biflavonoid structures, and two lignans (10 and 11) were obtained from the roots of Wikstroemia chamaedaphne. Their structures were elucidated through comprehensive spectroscopic analyses. The absolute configuration of 1 was determined by experimental electronic circular dichroism. NH2 cell model was used to test the activity of these 11 compounds in activating latent HIV. Oleodaphnone (2) showed the latent HIV activation effect as well as the positive drug prostratin, and the activation effect was time- and concentration-dependent. Based on transcriptome analysis, the underlying mechanism was that oleodaphnone regulated the TNF, C-type lectin receptor, NF-κB, IL-17, MAPK, NOD-like receptor, JAK-Stat, FoxO, and Toll-like receptor signaling pathways. This study provides the basis for the potential development of oleodaphnone as an effective HIV latency-reversing agent