Application of artificial intelligence in computer network technology

With the continuous development of science and technology in China, a rtifi cial intelligence has played an important role in many industries. By applying artifi cial intelligence to computer network technology, computer network technology can provide greater help for people’s life and work, enrich the content of computer network technology, and improve the effi ciency of people’s life and work. In the era of big data, the computer system gradually has some defects. The introduction of artifi cial intelligence technology can greatly improve the effi ciency and quality of computer data processing. In view of this, this paper will analyze the application of artifi cial intelligence in computer network technology, and put forward some strategies for your reference

Recent progress in the shape deformation of polymeric hydrogels from memory to actuation

Shape deformation hydrogels, which are one of the most promising and essential classes of stimuli-responsive polymers, could provide large-scale and reversible deformation under external stimuli. Due to their wet and soft properties, shape deformation hydrogels are anticipated to be a candidate for the exploration of biomimetic materials, and have shown various potential applications in many fields. Here, an overview of the mechanisms of shape deformation hydrogels and methods for their preparation is presented. Some innovative and efficient strategies to fabricate programmable deformation hydrogels are then introduced. Moreover, successful explorations of their potential applications, including information encryption, soft robots and bionomic systems, are discussed. Finally, remaining great challenges including the achievement of multiple stable deformation states and the combination of shape deformation and sensing are highlighted

A panther chameleon skin-inspired core@shell supramolecular hydrogel with spatially organized multi-luminogens enables programmable color change

Organization of different iridophores into a core@shell structure constitutes an evolutionary novelty for panther chameleons that allows their skins to display diverse color change. Inspired by this natural color-changing design, we present a responsive core@shell-structured multi-luminogen supramolecular hydrogel system that generates a programmable multi-color fluorescent change. Specifically, red Eu$^{3+}$-amidopicolinate (R) luminogen is incorporated into the core hydrogel, while blue naphthalimide (B) and green perylene-tetracarboxylic acid (G) luminogens are grown into two supramolecular shell hydrogels. The intensities of G/B luminogens could then be controlled independently, which enables its emission color to be programmed easily from red to blue or green, nearly covering the full visible spectrum. Because of the differential excitation energies between these luminogens, a desirable excitation wavelength-dependent fluorescence is also achieved. Colorful materials with a patterned core@shell structure are also demonstrated for anti-counterfeiting, opening up the possibility of utilizing a bioinspired core@shell structure to develop an efficient multi-color fluorescent system with versatile uses

The Change of the US Tariff Policy: Engels's Perspective and Enlightenment

Engels discussed tariff and the related issues on many occasions in his writings. Using “tariff” as the keyword, we search all the 50 volumes of Marx and Engels Collected Works and find out two important stages in which Engels formulated intensively tariff and related issues. The first one is 1845–1853, when Engels mainly elaborated from the perspective of the impact of tariffs on the interests of various classes in the European nations, and the second one is 1879–1893, when he mainly elaborated from the perspective of the relation between tariff policies and the stage of economic development in the United States and the roles played by the tariff policies in the national competition. At the second stage, standing at the height of world history and starting from competition and evolution, Engels made a comprehensive and in-depth illustration of the changes in the US tariff policies and their roles; at this stage, he recognized to a certain extent some of List's thoughts on tariff, which is not in conflict with his criticism of List at the first stage. The essence of Engels's thoughts on tariffs is the multi-level investigation based on his profound historical insight and grand global vision. Engels's thoughts of the political economy formulated on the development and evolution of the tariff policies and their roles and mechanisms after the US Civil War are still of great practical significance even for nowadays. </p

Astragaloside IV Enhances Melanogenesis via the AhR-Dependent AKT/GSK-3β/β-Catenin Pathway in Normal Human Epidermal Melanocytes

Astragalus membranaceus root has been widely used for repigmentation treatment in vitiligo, but its mechanism is poorly understood. We sought to investigate the effect of astragaloside IV (AS-IV), a main active extract of the Astragalus membranaceus root, on melanin synthesis in normal human epidermal melanocytes (NHEMs) and to elucidate its underlying mechanisms. Melanin content, tyrosinase activity, qPCR, western blot, and immunofluorescence were employed. Specific inhibitors and small interfering RNA were used to investigate the possible pathway. AS-IV stimulated melanin synthesis and upregulated the expression of melanogenesis-related genes in a concentration-dependent manner in NHEMs. AS-IV could activate the aryl hydrocarbon receptor (AhR), and AS-IV-induced melanogenesis was inhibited in si-AhR-transfected NHEMs. In addition, we showed that AS-IV enhanced the phosphorylation of AKT and GSK-3β and nuclear translocation of β-catenin. AS-IV-induced MITF expression upregulation and melanin synthesis were decreased in the presence of β-catenin inhibitor FH353. Furthermore, AhR antagonist CH223191 inhibited the activation of AKT/GSK-3β/β-catenin signaling, whereas the expression of CYP1A1 (marker of AhR activation) was not affected by the AKT inhibitor in AS-IV-exposed NHEMs. Our findings show that AS-IV induces melanogenesis through AhR-dependent AKT/GSK-3β/β-catenin pathway activation and could be beneficial in the therapy for depigmented skin disorders

Deep Learning Predicts EBV Status in Gastric Cancer Based on Spatial Patterns of Lymphocyte Infiltration

EBV infection occurs in around 10% of gastric cancer cases and represents a distinct subtype, characterized by a unique mutation profile, hypermethylation, and overexpression of PD-L1. Moreover, EBV positive gastric cancer tends to have higher immune infiltration and a better prognosis. EBV infection status in gastric cancer is most commonly determined using PCR and in situ hybridization, but such a method requires good nucleic acid preservation. Detection of EBV status with histopathology images may complement PCR and in situ hybridization as a first step of EBV infection assessment. Here, we developed a deep learning-based algorithm to directly predict EBV infection in gastric cancer from H&amp;E stained histopathology slides. Our model can not only predict EBV infection in gastric cancers from tumor regions but also from normal regions with potential changes induced by adjacent EBV+ regions within each H&amp;E slide. Furthermore, in cohorts with zero EBV abundances, a significant difference of immune infiltration between high and low EBV score samples was observed, consistent with the immune infiltration difference observed between EBV positive and negative samples. Therefore, we hypothesized that our model&rsquo;s prediction of EBV infection is partially driven by the spatial information of immune cell composition, which was supported by mostly positive local correlations between the EBV score and immune infiltration in both tumor and normal regions across all H&amp;E slides. Finally, EBV scores calculated from our model were found to be significantly associated with prognosis. This framework can be readily applied to develop interpretable models for prediction of virus infection across cancers

Restricted mean survival time regression model with time-dependent covariates

In clinical or epidemiological follow-up studies, methods based on time scale indicators such as the restricted mean survival time (RMST) have been developed to some extent. Compared with traditional hazard rate indicator system methods, the RMST is easier to interpret and does not require the proportional hazard assumption. To date, regression models based on the RMST are indirect or direct models of the RMST and baseline covariates. However, time-dependent covariates are becoming increasingly common in follow-up studies. Based on the inverse probability of censoring weighting (IPCW) method, we developed a regression model of the RMST and time-dependent covariates. Through Monte Carlo simulation, we verified the estimation performance of the regression parameters of the proposed model. Compared with the time-dependent Cox model and the fixed (baseline) covariate RMST model, the time-dependent RMST model has a better prediction ability. Finally, an example of heart transplantation was used to verify the above conclusions.Comment: 24 pages, 4 table

Multiple-Responsive and Amphibious Hydrogel Actuator Based on Asymmetric UCST-Type Volume Phase Transition

Multiple-Responsive and Amphibious Hydrogel Actuator Based on Asymmetric UCST-Type Volume Phase Transitio

Effects of He-D Interaction on Irradiation-Induced Swelling in Fe9Cr Alloys

The atomic-scale defects such as (deuterium, helium)-vacancy clusters in nuclear energy materials are one of the causes for the deterioration of the macroscopic properties of materials. Unfortunately, they cannot be observed by transmission electron microscopy (TEM) before they grow to the nanometer scale. Positron annihilation spectroscopy (PAS) has been proven to be sensitive to open-volume defects, and could characterize the evolution of the size and concentration of the vacancy-like nanoclusters. We have investigated the effects of He-D interaction on the formation of nanoscale cavities in Fe9Cr alloys by PAS and TEM. The results show that small-sized bubbles are formed in the specimen irradiated with 5 × 1016 He+/cm2, and the subsequent implanted D-ions contribute to the growth of these helium bubbles. The most likely reason is that helium bubbles previously formed in the sample captured deuterium injected later, causing bubbles to grow. In the lower dose He-irradiated samples, a large number of small dislocations and vacancies are generated and form helium-vacancy clusters with the helium atoms