Exploration and Innovation on Ideological and Political Education From the Perspective of Big Data

With the advent of Big Data age, ideological and political education, from the perspective of Big Data, gradually reveals. It combines the advantages of Big Data closely with the demands of ideological and political education, contributing to enrich the resources of ideological and political education, enhancing the effectiveness of ideological and political education and developing the discipline of ideological and political education. In the practical application, we should introduce Big Data thinking into updating the concepts of ideological and political education, apply Big Data technology into innovating the methods of ideological and political education, build the team of ideological and political education according to the requirements of Big Data age, coordinate Big Data resources to optimize the environment of ideological and political education, and continue to promote the innovation and development of ideological and political education

On Deng Xiaoping’s Youth Goal Incentive Thought and Its Enlightenment on the Realization of the Chinese Dream

Deng Xiaoping’s youth goal incentive thought derives from the Marxist world outlook and methodology and results from the historical background of reform and opening up, contains scientific connotations: an accurate understanding of the youth is the premise; scientific goal setting is the core; education and guidance to young people is the key and to inspire the incentive of young people is the essence. It has effectively promoted the development of the cause of socialism with Chinese characteristics and the growth of young talents. Deng Xiaoping’s youth goal incentive thought unifies the goal of the party and the goal of the youth and it has provided valuable insights to lead contemporary youth to actively devote into the Chinese dream of the great rejuvenation of China, that is to grasp the characteristics of contemporary youth to provide power for the Chinese dream, to scientifically develop goals to gather power for the Chinese dream, to strengthen the education and guidance of young people to devote to the Chinese dream and to stimulate the main role of the youth to force the Chinese dream

UniBrain: Universal Brain MRI Diagnosis with Hierarchical Knowledge-enhanced Pre-training

Magnetic resonance imaging~(MRI) have played a crucial role in brain disease diagnosis, with which a range of computer-aided artificial intelligence methods have been proposed. However, the early explorations usually focus on the limited types of brain diseases in one study and train the model on the data in a small scale, yielding the bottleneck of generalization. Towards a more effective and scalable paradigm, we propose a hierarchical knowledge-enhanced pre-training framework for the universal brain MRI diagnosis, termed as UniBrain. Specifically, UniBrain leverages a large-scale dataset of 24,770 imaging-report pairs from routine diagnostics. Different from previous pre-training techniques for the unitary vision or textual feature, or with the brute-force alignment between vision and language information, we leverage the unique characteristic of report information in different granularity to build a hierarchical alignment mechanism, which strengthens the efficiency in feature learning. Our UniBrain is validated on three real world datasets with severe class imbalance and the public BraTS2019 dataset. It not only consistently outperforms all state-of-the-art diagnostic methods by a large margin and provides a superior grounding performance but also shows comparable performance compared to expert radiologists on certain disease types

The development trend of influenza in China from 2010 to 2019

In this study, we quantify and evaluate the transmission capacity of different types of influenza, and evaluate the flu vaccination effect. Taking the influenza cases reported by the National Influenza Center of China from 2010 to 2019 as the research object (http://www.chinaivdc.cn/cnic), we established the SEIABR model to calculate the influenza infection rate and R0 for each year from 2010 to 2019, and calculate the influenza A and B influenza infection rates. We further added vaccination measures to the SEIABR model, and analysis the impact of different vaccination rates on the spread of influenza. We find that the range of β(infection rate) is $$6.03 \times {10^{ - 10}}$$ to $$9.66 \times {10^{ - 10}}$$, and the average is $$\left({7.95 \pm 1.27} \right) \times {10^{ - 10}}$$, the range of R0 is .98 to 1.47, and the average is 1.21. Simulation result suggest that vaccine coverage needed to reach 60%-80% to control the spread of influenza virus in China when the vaccine effectiveness was 20%-40%. When the vaccine effectiveness is 40%-60%, vaccine coverage needs to reach 40%-60% to control the spread of influenza virus in China. In China, the infection rate of influenza A is higher than influenza B, to better control the spread of the flu virus, we suggest that we also need to increase the number of people vaccinated or improve the efficiency of vaccines(the current vaccination coverage is probably less than 20%)

High-efficiency, Long-lifetime and Large-area Near-infrared QD-OLEDs

Intrinsically flexible near-infrared (NIR) light sources are experiencing rapid growth in recent years. However, NIR light sources with a combination of high-efficiency, long-lifetime, and large-area remain challenging. Here, we realize high-efficiency, long-lifetime and large-area NIR light sources based on organic light-emitting diodes (OLEDs) and NIR-emitting PbS quantum dots (QDs) as color conversion layers. To obtain highly efficient PbS QDs, a unique additive composition comprising KCl and crown ethers is employed, which can significantly passivate trap states in the air and at room temperature, thus improving the photoluminescence quantum efficiency from 24% to 35% in solution and further to 45% in blend films. The well-passivated PbS QD films are then integrated with red OLEDs and the resulting QD-OLEDs exhibit high-performance NIR emission centered at 887 nm, a high external quantum efficiency of 5.2% at a radiance of 10 W sr-1 m-2, and superior operational stability with long lifetime T90 of 188 hours at the current density of 25 mA cm-2, which presents the best result for solution-processed NIR LEDs. We also construct a large-area NIR QD-OLED (5×5 cm2) with desirable uniform emission. This work opens a new avenue to achieve robust large-area NIR light sources for broad applications

1,3-Pentadiene-Assistant Living Anionic Terpolymerization: Composition Impact on Kinetics and Microstructure Sequence Primary Analysis

The combination of a living anionic technology and a unique alternating strategy provided an exciting opportunity to prepare novel and well-defined poly(1,3-pentadiene-co-syrene-co-1,1-diphenylethylene) resins consisting of three alternating sequences of modules (A/B/C zwitterions). “A” being Styrene (St)/1,3-pentadiene (PD), “B” being diphenylethylene (DPE)/PD, “A” being DPE/St, respectively, A wide composition range of new polyolefin resins, i.e., poly (A-co-B), poly (A-co-C), and poly (B-co-C), with controlled molecular weight and very narrow molecular weight and composition distributions have been prepared by a one-pot living characteristic method. In the section of kinetic analysis, the terpolymer yields and kinetic parameters were strongly dependent on the feed/comonomer ratio as well as the content of the alternating structure. The competition copolymerization behaviors of A/B, B/C, and A/C were studied in detail in this work. By contrast, the microstructure and the thermal property of the resulting terpolymer were investigated via Nuclear magnetic resonance (NMR) and Differential scanning calorimetry (DSC) analysis. The results of 1H NMR tracking the change of [Aromatic ring]/[C=C] value indicated the distinctive copolymer-ization behavior of the selective “alternating-modules”. The glass transition temperature (Tg) was very sensitive to the terpolymer composition. By contrast to poly(A-ran-B) with only one obvious Tg, there were two Tgs in the A/C and B/C copolymerization cases. Moreover, the desirable high Tg ~ 140 °C resin was limited to the terpolymers with up to 50 mol % DPE. Finally, the “ABC-X” mechanism was proposed to interpret the unique terpolymerization behavior, which belongs to the classical “bond-forming initiation” theory

Manipulation and Optical Detection of Artificial Topological Phenomena in 2D Van der Waals Fe5GeTe2/MnPS3 Heterostructures

Abstract 2D ferromagnet is a good platform to investigate topological effects and spintronic devices owing to its rich spin structures and excellent external‐field tunability. The appearance of the topological Hall Effect (THE) is often regarded as an important sign of the generation of chiral spin textures, like magnetic vortexes or skyrmions. Here, interface engineering and an in‐plane current are used to modulate the magnetic properties of the nearly room‐temperature 2D ferromagnet Fe5GeTe2. An artificial topology phenomenon is observed in the Fe5GeTe2/MnPS3 heterostructure by using both anomalous Hall Effect and reflective magnetic circular dichroism (RMCD) measurements. Through tuning the applied current and the RMCD laser wavelength, the amplitude of the humps and dips observed in the hysteresis loops can be modulated accordingly. Magnetic field‐dependent hysteresis loops demonstrate that the observed artificial topological phenomena are induced by the generation and annihilation of the magnetic domains. This work provides an optical method for investigating the topological‐like effects in magnetic structures and proposes an effective way to modulate the magnetic properties of magnetic materials, which is important for developing magnetic and spintronic devices in van der Waals magnetic materials