Using Baidu Index to Understand the Public Concern of Children's Mental Health in Mainland China in the Context of COVID-19 Epidemic

This study aims to understand the temporal and spatial characteristics of public concern for "children's mental health" in China in the context of the COVID-19 epidemic. Baidu Index is a research tool to collect and analyze massive data on Chinese netizens' behaviors. Using Baidu Index as the research tool, this paper analyzes the trend and distribution of Chinese netizens' attention to "children's mental health" from December 1st, 2019 to March 20th, 2022 from three aspects of trend research, demand map, and crowd portrait. The study found that since the outbreak of COVID- 19, the search trend of "children's mental health" has shown a cyclical change, peaking in May and valley around the Spring Festival and National Day, and stable in other periods. "Mental health", "handwritten newspaper on mental health" and "youth mental health" are the most popular buzzwords among the public. The groups concerned with "children's mental health" is mainly distributed in Guangdong, Jiangsu, Beijing, and the majority are women between 30 and 39 years old. Meanwhile, search trends for "mental health" are like that for "children's mental health." The factors influencing the search volume change of "children's mental health" include Chinese traditional holidays, Spring Festival, National Day, Chinese Mental Health Day, and policies and instructions on children's mental health issued by the PRC Ministry of Education. The public would like to know about "mental health", "handwritten newspaper on mental health" and "adolescent mental health"

Raising interest in master of physical education during the COVID-19 pandemic: An analysis of Baidu Index data

Objective: Current evidence shows the master of physical education has attracted attention since its opening. The study aims to quantify recent trends in the public interest and related online search behavior for master of physical education, and “nowcast” future scenarios with respect to the master of physical education. Methods: Baidu Index, a database of search engines with massive information, was employed. By searching for the keyword master of physical education, and using content analysis to understand the data information related to master of physical education. It extracted the search trend data regarding Chinese interest in the master of physical education from November 21, 2016, to November 21, 2022. Finally, it compares the search trend of search interests in the master of physical education with related terms. Results: It found that the search trend of master of physical education was on the rise overall. Specifically, the peak value appeared in September 2019, the valley value appeared around the Spring Festival each year, and the search trend in other periods was stable. Conclusion: The raise in public interest in a master of physical education will likely result in an increase in the number of candidates who are going to attend the National Graduate Entrance Exam to pursue a master of physical education. In the coming months or more, the competition for the employment of sports professionals in China will become more intense. Affected by the COVID-19, more people are interested in health and physical exercise, and then pay attention to the Master of Physical Education. The Sports Law of the People's Republic of China has been revised recently, which has led to more people interested in the master of physical education

Data Cubes in Hand: A Design Space of Tangible Cubes for Visualizing 3D Spatio-Temporal Data in Mixed Reality

Tangible interfaces in mixed reality (MR) environments allow for intuitive data interactions. Tangible cubes, with their rich interaction affordances, high maneuverability, and stable structure, are particularly well-suited for exploring multi-dimensional data types. However, the design potential of these cubes is underexplored. This study introduces a design space for tangible cubes in MR, focusing on interaction space, visualization space, sizes, and multiplicity. Using spatio-temporal data, we explored the interaction affordances of these cubes in a workshop (N=24). We identified unique interactions like rotating, tapping, and stacking, which are linked to augmented reality (AR) visualization commands. Integrating user-identified interactions, we created a design space for tangible-cube interactions and visualization. A prototype visualizing global health spending with small cubes was developed and evaluated, supporting both individual and combined cube manipulation. This research enhances our grasp of tangible interaction in MR, offering insights for future design and application in diverse data contexts

High-Throughput RNA Sequencing of Pseudomonas-Infected Arabidopsis Reveals Hidden Transcriptome Complexity and Novel Splice Variants

We report the results of a genome-wide analysis of transcription in Arabidopsis thaliana after treatment with Pseudomonas syringae pathovar tomato. Our time course RNA-Seq experiment uses over 500 million read pairs to provide a detailed characterization of the response to infection in both susceptible and resistant hosts. The set of observed differentially expressed genes is consistent with previous studies, confirming and extending existing findings about genes likely to play an important role in the defense response to Pseudomonas syringae. The high coverage of the Arabidopsis transcriptome resulted in the discovery of a surprisingly large number of alternative splicing (AS) events – more than 44% of multi-exon genes showed evidence for novel AS in at least one of the probed conditions. This demonstrates that the Arabidopsis transcriptome annotation is still highly incomplete, and that AS events are more abundant than expected. To further refine our predictions, we identified genes with statistically significant changes in the ratios of alternative isoforms between treatments. This set includes several genes previously known to be alternatively spliced or expressed during the defense response, and it may serve as a pool of candidate genes for regulated alternative splicing with possible biological relevance for the defense response against invasive pathogens

The biological function of the type II toxin-antitoxin system ccdAB in recurrent urinary tract infections

Urinary tract infections (UTIs) represent a significant challenge in clinical practice, with recurrent forms (rUTIs) posing a continual threat to patient health. Escherichia coli (E. coli) is the primary culprit in a vast majority of UTIs, both community-acquired and hospital-acquired, underscoring its clinical importance. Among different mediators of pathogenesis, toxin-antitoxin (TA) systems are emerging as the most prominent. The type II TA system, prevalent in prokaryotes, emerges as a critical player in stress response, biofilm formation, and cell dormancy. ccdAB, the first identified type II TA module, is renowned for maintaining plasmid stability. This paper aims to unravel the physiological role of the ccdAB in rUTIs caused by E. coli, delving into bacterial characteristics crucial for understanding and managing this disease. We investigated UPEC-induced rUTIs, examining changes in type II TA distribution and number, phylogenetic distribution, and Multi-Locus Sequence Typing (MLST) using polymerase chain reaction (PCR). Furthermore, our findings revealed that the induction of ccdB expression in E. coli BL21 (DE3) inhibited bacterial growth, observed that the expression of both ccdAB and ccdB in E. coli BL21 (DE3) led to an increase in biofilm formation, and confirmed that ccdAB plays a role in the development of persistent bacteria in urinary tract infections. Our findings could pave the way for novel therapeutic approaches targeting these systems, potentially reducing the prevalence of rUTIs. Through this investigation, we hope to contribute significantly to the global effort to combat the persistent challenge of rUTIs

Using Baidu index to investigate the spatiotemporal characteristics of knowledge management in China

In the era of knowledge economy, knowledge has become the guide to creating economic and social value. Knowledge economy calls for knowledge management, and modern knowledge management is a new management theory and management method emerging in the time of knowledge economy, which explains the relevance of this research. Baidu is the largest Chinese search engine in the world, and the Baidu Index developed by Baidu is one of the most important statistical analysis platforms of the Internet and even the whole data age. The purpose of this paper is to investigate spatiotemporal characteristics of Chinese public attention to knowledge management through the Baidu index. Text analysis and process tracing are used to explain the reasons for the spatial and temporal characteristics of the Chinese public's attention to knowledge management. Through Baidu index network search engine, this paper analyses search trend, demand graph, and demographic and geographic distribution. This paper selects the time period from January 1, 2011 to January 1, 2022. The results of the study show that the search trend of "knowledge management" in the past 11 years peaked at the end of 2016, and the decrease appeared around the Spring Festival and National Day each year. "Learning organization", "knowledge base" and "information management" are the words most concerned by the public. It was stated that the groups concerned about “knowledge management” were mainly distributed in Guangdong, Beijing, and Shanghai. Among them, the predominant group was male aged 20-29. The factors that affect the changes in the search volume of “knowledge management” mainly include the traditional Chinese holidays, the Spring Festival, the National Day, and the release of knowledge management-related norms. In addition, the study found similar search trends for “knowledge management” and “knowledge management system”. This paper only takes "knowledge management" in Baidu Index as the research object. Whether it is suitable for all network engines, needs to be tested furtherl

Raising interest in master of physical education during the COVID-19 pandemic: An analysis of Baidu Index data

Objective: Current evidence shows the master of physical education has attracted attention since its opening. The study aims to quantify recent trends in the public interest and related online search behavior for master of physical education, and “nowcast” future scenarios with respect to the master of physical education. Methods: Baidu Index, a database of search engines with massive information, was employed. By searching for the keyword master of physical education, and using content analysis to understand the data information related to master of physical education. It extracted the search trend data regarding Chinese interest in the master of physical education from November 21, 2016, to November 21, 2022. Finally, it compares the search trend of search interests in the master of physical education with related terms. Results: It found that the search trend of master of physical education was on the rise overall. Specifically, the peak value appeared in September 2019, the valley value appeared around the Spring Festival each year, and the search trend in other periods was stable. Conclusion: The raise in public interest in a master of physical education will likely result in an increase in the number of candidates who are going to attend the National Graduate Entrance Exam to pursue a master of physical education. In the coming months or more, the competition for the employment of sports professionals in China will become more intense. Affected by the COVID-19, more people are interested in health and physical exercise, and then pay attention to the Master of Physical Education. The Sports Law of the People's Republic of China has been revised recently, which has led to more people interested in the master of physical education

Preparation, characterization and application of magnetic Fe3O4-CS for the adsorption of orange I from aqueous solutions.

Fe3O4 (Fe3O4-CS) coated with magnetic chitosan was prepared as an adsorbent for the removal of Orange I from aqueous solutions and characterized by FTIR, XRD, SEM, TEM and TGA measurements. The effects of pH, initial concentration and contact time on the adsorption of Orange I from aqueous solutions were investigated. The decoloration rate was higher than 94% in the initial concentration range of 50-150 mg L(-1) at pH 2.0. The maximum adsorption amount was 183.2 mg g-1 and was obtained at an initial concentration of 400 mg L(-1) at pH 2.0. The adsorption equilibrium was reached in 30 minutes, demonstrating that the obtained adsorbent has the potential for practical application. The equilibrium adsorption isotherm was analyzed by the Freundlich and Langmuir models, and the adsorption kinetics were analyzed by the pseudo-first-order and pseudo-second-order kinetic models. The higher linear correlation coefficients showed that the Langmuir model (R(2) = 0.9995) and pseudo-second-order model (R(2) = 0.9561) offered the better fits

Real-Time Water Level Prediction in Open Channel Water Transfer Projects Based on Time Series Similarity

Changes in the opening of gates in open channel water transfer projects will cause fluctuations in the water level and flow of adjacent open channels and thus bring great challenges for real-time water level prediction. In this paper, a novel slope-similar shape method is proposed for real-time water level prediction when the change of gate opening at the next moment is known. The water level data points of three consecutive moments constitute the query. The slope similarity is used to find the historical water level datasets with similar change trend to the query, and then the best slope similarity dataset is determined according to the similarity index and the gate opening change. The water level difference of the next moment of the best similar data point is the water level difference of the predicted moment, and thus the water level at the next moment can be obtained. A case study is performed with the Middle Route of the South-to-North Water Diversion Project of China. The results show that 87.5% of datasets with a water level variation of less than 0.06 m have an error less than 0.03 m, 71.4% of which have an error less than 0.02 m. In conclusion, the proposed method is feasible, effective, and interpretable, and the study provides valuable insights into the development of scheduling schemes