The Research on the Paths of Popular Science Education about Myopia Prevention and Control among College Students in the Context of Shifting the Focus Forward

Currently, the number of myopic people in China has reached as high as 600 million, and it shows a trend of “early onset, high incidence, and a high degree of severity”. The issue of myopia among children and adolescents has attracted widespread attention from all sectors of society. Comprehensive myopia prevention and control efforts have been launched nationwide. Popular science education, vision screening, and improving visual environments are effective measures for preventing myopia. However, among the target audience for comprehensive myopia prevention and control, the preschool children group has been neglected, and the work of myopia prevention and control for this group has been significantly weakened and marginalized. Due to insufficient awareness of prevention and control, the hyperopia reserve in the preschool children group is being continuously depleted, leading to the early onset of myopia. In light of this situation, the focus of myopia prevention and control needs to shift forward, and it is worth exploring and pondering how college students with a background in optometry can develop entertaining and engaging popular science education materials and methods.

基于预训练模型和Transformer架构的大数据与计算机类科普书籍难度分类研究

针对当前研究在书籍级长文本可读性评估方面的不足,本文提出了一种新颖的PTDE-CAC模型。该模型将书籍分割为固定片段,利用无监督聚类获取难度感知片段,对预训练模型进行再训练,使其学习难度知识,将长文本表示为多个不同难度级别的向量。本文构建了大数据、计算机科普教材分级数据集,实验证明PTDE-CAC模型在可读性评估中表现优异,优于传统方法和现有预训练模型。本工作为书籍级可读性评估提供了新思路,也为相关教材编写选择提供了参考。

Analysis and Prediction of Content Popularity for Online Video Service:A Youku Case Study

Understanding the characteristics and predicting the popularity of the newly published online videos can provide direct implications in various contexts such as service design, advertisement planning, network management and etc. In this paper, we collect a real-world large-scale dataset from a leading online video service provider in China, namely Youku. We first analyze the dynamics of content publication and content popularity for the online video service. Then, we propose a rich set of features and exploit various effective classification methods to estimate the future popularity level of an individual video in various scenarios. We show that the future popularity level of a video can be predicted even before the video's release, and by introducing the historical popularity information the prediction performance can be improved dramatically. In addition, we investigate the importance of each feature group and each feature in the popularity prediction, and further reveal the factors that may impact the video popularity. We also discuss how the early monitoring period influences the popularity level prediction. Our work provides an insight into the popularity of the newly published online videos, and demonstrates promising practical applications for content publishers,service providers, online advisers and network operators.

On-line Popularity Monitoring Method Based on Bloom Filters and Hash tables for Differentiated Traffic

Towards line speed and accurateness on-line content popularity monitoring on Content Centric Networking(CCN) routers, we propose a three-stage scheme based on Bloom filters and hash tables for differentiated traffic. At the first stage, we decide whether to deliver the content to the next stage depending on traffic types. The second stage consisting of Standard Bloom filters(SBF) and Counting Bloom filters(CBF) identifies the popular content. Meanwhile, a scalable sliding time window based monitoring scheme for different traffic types is proposed to implement frequent and real-time updates by the change of popularities. Hash tables according with sliding window are used to record the popularity at the third stage. Simulation results reveal that this method reaches a 40 Gbps processing speed at lower error probability with less memory, and it is more sensitive to the change of popularity. Additionally, the architecture which can be implemented in CCN router is flexible and scalable.

Exploring Content Popularity in Information-Centric Networks

Information-Centric Networking(ICN), an alternative architecture to the current Internet infrastructure, focuses on the distribution and retrieval of content by employing caches in a network to reduce network traffic. The employment of caches may be accomplished using graph-based and content-based criteria such as the position of a node in a network and content popularity. The contribution of this paper lies on the characterization of content popularity for on-path in-network caching. To this end, four dynamic approaches for identifying content popularity are evaluated via simulations. Content popularity may be determined per chunk or per object, calculated by the number of requests for a content against the sum of requests or the maximum number of requests. Based on the results, chunk-based approaches provide 23% more accurate content popularity calculations than object-based approaches. In addition, approaches that are based on the comparison of a content against the maximum number of requests have been shown to be more accurate than the alternatives.

Popularity Prediction of Social Media Post Using Tensor Factorization

The traditional method of doing business has been disrupted by socialmedia. In order to develop the enterprise, it is essential to forecast the level ofinteraction that a new post would receive from social media users. It is possiblefor the user’s interest in any one social media post to be impacted by external factors or to dwindle as a result of changes in his behaviour. The popularity detectionstrategies that are user-based or population-based are unable to keep up with theseshifts, which leads to inaccurate forecasts. This work makes a prediction abouthow popular the post will be and addresses any anomalies caused by factors outside of the study. A novel improved PARAFAC (A-PARAFAC) method that istensor factorization-based has been presented in order to cope with the user criteria that will be used in the future to rate any project. We consolidated the information on the historically popular content, and we accelerated the computation bychoosing the top contents that were most like each other. The tensor is factorisedwith the application of the Adam optimization. It has been modified such that thebias is now included in the gradient function of A-PARAFAC, and the value ofthe bias is updated after each iteration. The prediction accuracy is improved by32.25% with this strategy compared to other state of the art methods.

Striving For A New Growth Model

China will face some structural challenges in the next five years. Global interest rates will likely rise. The labor force in China is shrinldng. Property and infrastructure investments face constraints as growth is driven. Financial risks have reached alarming levels.

Striving for Coordinated Development of SCO and BRI

The Shanghai Cooperation Organization and the Belt and Road Initiative are both at a new historic juncture. With shared conditions for coordinated development, they are in a position to give full play to their advantages, further optimize their functions and goals, and pursue mutual improvement and joint development in the new period.

Striving for“Standard Economy”

Promotion of the "standard economy" itself is an integral part of upgrading the quality of China’s economic development, transforming economic growth mode and responding to foreign trade barriers as well as a key strategy for improving foreign trade level.

What Accounts for the Popularity of Twilight Saga——From the Perspective of Culture Studies

The huge success of Twilight series and its adapted films is a blockbuster in the field of literature and film industry,attracting a great amount of audience and creating a box-office marvel.The book series also receives a wide attention from literary critics with analysis of different perspectives.This study aims to explore what accounts for Twilight's popularity with cultural studies,including aspects of teenage culture,masculinity,psychoanalysis,gender and sexuality.A comprehensive angel is provided to look at Twilight and its transformation to a classic.

Striving for Ecological Advancement

IR, soil, and water - the basic elements of the ecological system - are not simply substances for human beings to survive on,

Optimizing Surgical Conditions with the Use of a Modified Spontaneous Respiration, Intravenous Anesthesia and High-Flow Nasal Oxygen for Pediatric Laser Laryngeal Surgery

The use of SponTaneous Respiration using IntraVEnous anesthesia and High-flow nasal oxygen (STRIVE-Hi) in laryngeal surgery has become more widely reported. This method eliminates the endotracheal tube as a fuel for a potential fire. However, little has been published on its use in the pediatric population. Our case report describes its use in a 2-year-old undergoing micro-direct laryngoscopy with CO2 assisted supraglottoplasty and rigid bronchoscopy for airway obstruction from congenital laryngomalacia. The STRIVE-Hi technique was modified for the pediatric patient by using a lower flow through the nasal cannula (4 L). No major changes in SpO2 were detected during the 30-minute procedure. With back up airway safety equipment in place, STRIVE is proving to be a safe technique with major advantages when used in this unique scenario.

Perseveringly Striving for Artistic Perfection Rooting in Belief

Established in 1957, Shaanxi Acrobatic Troupe has developed so rapidly with the effort of several generations that she has formed her unique artistic style and performing characteristics. Her performance is exquisite and fabulous and shows great skills. There are more than 130 performers in the troupe at present and the troupe mainly gives acrobatic and magic performances. As one of the most well-known acrobatic troupes in China. Shaanxi Acrobatic Troupe has overcome trials and hardships in the last 49 y...

STRIVING FOR EXCELLENCE:SHANXI SHOWCASES CPC'S EFFORTS TO BUILD A DISCIPLINED PARTY

The third thematic seminar of the Stories of the Communist Party of China(CPC)series focusing on party-building,with'Building a Well-disciplined Party in All Aspects:The Practice of Shanxi'as its theme,was held in Beijing on June 30.Song Tao,Minister of the International Department of the CPC Central Committee(IDCPC),Luo Huining,Secretary of the CPC Shanxi

Predicting the Popularity of Online News Based on the Dynamic Fusion of Multiple Features

Predicting the popularity of online news is essential for news providers and recommendation systems.Time series,content and meta-feature are important features in news popularity prediction.However,there is a lack of exploration of how to integrate them effectively into a deep learning model and how effective and valuable they are to the model’s performance.This work proposes a novel deep learning model named Multiple Features Dynamic Fusion(MFDF)for news popularity prediction.For modeling time series,long short-term memory networks and attention-based convolution neural networks are used to capture long-term trends and short-term fluctuations of online news popularity.The typical convolution neural network gets headline semantic representation for modeling news headlines.In addition,a hierarchical attention network is exploited to extract news content semantic representation while using the latent Dirichlet allocation model to get the subject distribution of news as a semantic supplement.A factorization machine is employed to model the interaction relationship between metafeatures.Considering the role of these features at different stages,the proposed model exploits a time-based attention fusion layer to fuse multiple features dynamically.During the training phase,thiswork designs a loss function based on Newton’s cooling law to train the model better.Extensive experiments on the real-world dataset from Toutiao confirm the effectiveness of the dynamic fusion of multiple features and demonstrate significant performance improvements over state-of-the-art news prediction techniques.