Game Analysis of Regulation for Online Prescription Drugs under Customer Feedback Mechanism

Objective To study the way to better regulate the online sales of prescription drugs,and to provide reference for the adjustment of relevant policies since the online sales of prescription drugs has become an inevitable trend.Methods A game model was constructed for the strategy choice of pharmaceutical e-commerce platform,customers and government departments based on differential game theory and Nash equilibrium game model to analyze the pure strategy Nash equilibrium,Nash equilibrium dominant strategy of each subject and the mixed strategy Nash equilibrium under different conditions.Besides,Matlab was used to carry out simulation analysis.Results and Conclusion The study shows that:(1)Improving the credibility of the government and reducing the cost of government regulation can not only make the pharmaceutical e-commerce platform operate with high quality,but also give greater play to government functions;(2)The greater the influence of social evaluation on pharmaceutical e-commerce platforms,the lower the cost of high-quality operation of pharmaceutical e-commerce platform,and the greater the probability of customer choosing real evaluation strategy;(3)The greater the customers’perception of potential risk,the greater the compensation,and the lower the cost of reporting.Then,the greater the probability that government departments will choose strict regulation.Finally,the model solution and simulation analysis are combined to provide countermeasures and suggestions for the safety regulation of online sales of prescription drugs.

Strategies for Fostering Interaction in Online Classrooms:A Conversation Analysis of Teacher-Student Verbal Interaction in Random Questioning in Pandemic-Initiated Online Teaching

This paper aims to explore how a veteran teacher organizes online teaching initiated by the pandemic and how she deals with the problems in online teacher-student verbal interaction.By analyzing a corpus of 20 audio-recorded online lessons between a math teacher and her students during the COVID-19 pandemic from April 11 to May 10,2022,four interactional segments are selected as the focus of the study.The results of the conversation analysis of the segments showed that students’modesty,lack of confidence,lack of ability,and network delay are the main factors affecting online teacher-student interaction.By encouraging students to answer questions,enlightening students to give answers,enriching students’answers,and entertaining the teaching atmosphere(“4Es”strategies),the teacher solved the problems successfully.The findings from this study can provide pedagogical experience and implications for practical teaching.

Online pharmaceutical process analysis of Chinese medicine using a miniature mass spectrometer: Extraction of active ingredients as an example

The automation of traditional Chinese medicine(TCM)pharmaceuticals has driven the development of process analysis from offline to online.Most of common online process analytical technologies are based on spectroscopy,making the identification and quantification of specific ingredients still a challenge.Herein,we developed a quality control(QC)system for monitoring TCM pharmaceuticals based on paper spray ionization miniature mass spectrometry(mini-MS).It enabled real-time online qualitative and quantitative detection of target ingredients in herbal extracts using mini-MS without chromatographic separation for the first time.Dynamic changes of alkaloids in Aconiti Lateralis Radix Praeparata(Fuzi)during decoction were used as examples,and the scientific principle of Fuzi compatibility was also investigated.Finally,the system was verified to work stably at the hourly level for pilot-scale extraction.This mini-MS based online analytical system is expected to be further developed for QC applications in a wider range of pharmaceutical processes.

Behavior analysis and formative assessments in online oral medicine education during the COVID-19 pandemic

BACKGROUND During the coronavirus disease 2019(COVID-19)pandemic,traditional teaching methods were disrupted and online teaching became a new topic in education reform and informatization.In this context,it is important to investigate the necessity and effectiveness of online teaching methods for medical students.This study explored stomatology education in China to evaluate the development and challenges facing the field using massive open online courses(MOOCs)for oral medicine education during the pandemic.AIM To investigate the current situation and challenges facing stomatology education in China,and to assess the necessity and effectiveness of online teaching methods among medical students.METHODS Online courses were developed and offered on personal computers and mobile terminals.Behavioral analysis and formative assessments were conducted to evaluate the learning status of students.RESULTS The results showed that most learners had already completed MOOCs and achieved better results.Course behavior analysis and student surveys indicated that students enjoyed the learning experience.However,the development of oral MOOCs during the COVID-19 pandemic faced significant challenges.CONCLUSION This study provides insights into the potential of using MOOCs to support online professional learning and future teaching innovation,but emphasizes the need for careful design and positive feedback to ensure their success.

The Driving Strategy of Online Ideological and Political Class in Universities Based on SWOT Analysis

The epidemic provided practical opportunities for online classes and also tested its drawbacks. To analyze the internal strengths (S) and weaknesses (W) as well as the external opportunities (O) and threats (T) of the online ideological and political class with SWOT theory, based on which to explore targeted solutions, is a “symptomatic” approach to improving the quality of the online ideological and political class. The analysis results are as follows: S includes “not limited by time and space”, “comprehensive teaching monitoring data”, “diverse and innovative interactive forms”, and “abundant high-quality teaching resources”. W refers to “increased difficulty in classroom control”, “teachers’ psychological pressure caused by online teaching”, and “limited by hardware conditions”. O means the opportunity provided by the modernization of ideological and political education and epidemics. T indicates external threats, such as limitations from the network and the severe impact of wrong values on the internet. The driving strategy for above case could be “upgrading of online teaching platforms”, “building a teaching team skilled in information technology teaching”, “improving hardware facilities” and “joining forces to confront value crisis”.

Online Capacitor Voltage Transformer Measurement Error State Evaluation Method Based on In-Phase Relationship and Abnormal Point Detection

The assessment of the measurement error status of online Capacitor Voltage Transformers (CVT) within the power grid is of profound significance to the equitable trade of electric energy and the secure operation of the power grid. This paper advances an online CVT error state evaluation method, anchored in the in-phase relationship and outlier detection. Initially, this method leverages the in-phase relationship to obviate the influence of primary side fluctuations in the grid on assessment accuracy. Subsequently, Principal Component Analysis (PCA) is employed to meticulously disentangle the error change information inherent in the CVT from the measured values and to compute statistics that delineate the error state. Finally, the Local Outlier Factor (LOF) is deployed to discern outliers in the statistics, with thresholds serving to appraise the CVT error state. Experimental results incontrovertibly demonstrate the efficacy of this method, showcasing its prowess in effecting online tracking of CVT error changes and conducting error state assessments. The discernible enhancements in reliability, accuracy, and sensitivity are manifest, with the assessment accuracy reaching an exemplary 0.01%.

Rapid online analysis of trace elements in steel using a mobile fiber-optic laser-induced breakdown spectroscopy system

A mobile fiber-optic laser-induced breakdown spectrometer(FO-LIBS) prototype was developed to rapidly detect a large quantity of steel material online and quantitatively analyze the trace elements in a large-diameter steel tube.Twenty-four standard samples and a polynomial fitting method were used to establish calibration curve models.The R^2 factors of the calibration curves were all above 0.99,except for Cu,indicating the elements’ strong self-absorption effect.Five special steel materials were rapidly detected in the steel mill.The average absolute errors of Mn,Cr,Ni,V,Cu,and Mo in the special steel materials were 0.039,0.440,0.033,0.057,0.003,and0.07 wt%,respectively,and their average relative errors fluctuated from 2.9% to 15.7%.The results demonstrated that the performance of this mobile FO-LIBS prototype can be compared with that of most conventional LIBS systems,but the more robust and flexible characteristics of the FO-LIBS prototype provide a feasible approach for promoting LIBS from the laboratory to the industry.

Topic Sentiment Analysis in Online Learning Community from College Students

Purpose:Opinion mining and sentiment analysis in Online Learning Community can truly reflect the students’learning situation,which provides the necessary theoretical basis for following revision of teaching plans.To improve the accuracy of topic-sentiment analysis,a novel model for topic sentiment analysis is proposed that outperforms other state-of-art models.Methodology/approach:We aim at highlighting the identification and visualization of topic sentiment based on learning topic mining and sentiment clustering at various granularitylevels.The proposed method comprised data preprocessing,topic detection,sentiment analysis,and visualization.Findings:The proposed model can effectively perceive students’sentiment tendencies on different topics,which provides powerful practical reference for improving the quality of information services in teaching practice.Research limitations:The model obtains the topic-terminology hybrid matrix and the document-topic hybrid matrix by selecting the real user’s comment information on the basis of LDA topic detection approach,without considering the intensity of students’sentiments and their evolutionary trends.Practical implications:The implication and association rules to visualize the negative sentiment in comments or reviews enable teachers and administrators to access a certain plaint,which can be utilized as a reference for enhancing the accuracy of learning content recommendation,and evaluating the quality of their services.Originality/value:The topic-sentiment analysis model can clarify the hierarchical dependencies between different topics,which lay the foundation for improving the accuracy of teaching content recommendation and optimizing the knowledge coherence of related courses.

Development and Analysis of a Machine Learning Based Software for Assisting Online Classes during COVID-19

Amid the Covid-19 widespread, it has been challenging for educational institutions to conduct online classes, facing multiples challenges. This paper provides an insight into different approaches in facing those challenges which includes conducting a fair online class for students. It is tough for an instructor to keep track of their students at the same time because it is difficult to screen if any of the understudies within the class are not present, mindful, or drowsing. This paper discusses a possible solution, something new that can offer support to instructors seeing things from a more significant point of view. The solution is a facial analysis computer program that can let instructors know which students are attentive and who is not. There’s a green and red square box for face detection, for which Instructors can watch by seeing a green box on those mindful students conjointly, a red box on those who are not mindful at all. This paper finds that the program can automatically give attendance by analyzing data from face detection. It has other features for which the teacher can also know if any student leaves the class early. In this paper, model design, performance analysis, and online class assistant aspects of the program have been discussed.

Competitive analysis of online inventory problem with interrelated prices

This paper investigates the online inventory problem with interrelated prices in which a decision of when and how much to replenish must be made in an online fashion even without concrete knowledge of future prices. Four new online models with different price corre- lations are proposed in this paper, which are the linear-decrease model, the log-decrease model, the logarithmic model and the exponential model. For the first two models, the online algo- rithms are developed, and as the performance measure of online algorithm, the upper and lower bounds of competitive ratios of the algorithms are derived respectively. For the exponential and logarithmic models, the online algorithms are proposed by the solution of linear programming and the corresponding competitive ratios are analyzed, respectively. Additionally, the algorithm designed for the exponential model is optimal, and the algorithm for the logarithmic model is optimal only under some certain conditions. Moreover, some numerical examples illustrate that the algorithms based on the dprice-conservative strategy are more suitable when the purchase price fluctuates relatively flat.

Competitive analysis of price online inventory problem with cost function

In this paper,a new price is given to the online decision maker at the beginning of each day.The trader must decide how many items to purchase according to the current price.We present three variants and an online algorithm based on cost function.The competitive ratio of the online algorithm is given for each variant,which is a performance measure of an online algorithm.More importantly,we show that the online algorithm is optimal.

Online Test and Fault Diagnosis of Yarn Quality Using Wavelet Analysis and FFT

A new online system of monitoring yarn quality and fault diagnosis is presented. This system integrates the technologies of sensor, signal process, communication, network, computer, control, instrument structure and mass knowledge of experts. Comparing with conventional off-line yarn test, the new system can find the quality defects of yarn online in time and compensate for the lack of expert knowledge in manual analysis. It can save a lot of yarn wasted in off-line test and improve product quality. By using laser sensor to sample the diameter signal of yarn and doing wavelet analysis and FFT to extract fault characteristics, a set of reasoning mechanism is established to analyze yarn quality and locate the fault origination. The experimental results show that new system can do well in monitoring yarn quality online comparing with conventional off-line yarn test. It can test the quality of yarn in real-time with high efficiency and analyze the fault reason accurately. It is very useful to apply this new system to upgrade yarn quality in cotton textile industry at present.

Application of Online Solid-phase Extraction Technology in the Field of Environmental Analysis

For purpose of purification and enrichment, environmental samples usually need to be pretreated before analysis because of low concentration of residual organic matters. Solid-phase extraction （SPE） is one of the frequently used methods of pretreatment. This article introduces the methodological principle and flow channel of SPE as well as the categories of frequently used small extraction column, analyzes the application of online SPE technology in environmental analysis, generalizes the advantages of online SPE and sets forth its developmental trend.

Flow Injection Analysis of Hydrazine in the Aqueous Streams of Purex Process by Liquid Chromatography System Coupled with UV-Visible Detector

Present study describes the development of a rapid, sensitive and selective flow injection analysis of hydrazine in the aqueous streams of purex process by liquid chromatography system coupled with UV-Visible detector. The method is based on the formation of yellow coloured azine complex by reaction of hydrazine with para-dimethy laminobenzaldehyde (pDMAB). The formed yellow coloured complex is stable in acidic medium and has a maximum absorption at 460 nm. The presence of uranium in hydrazine solution is not interfering in the analysis. Under optimum condition, the absorption intensity linearly increased with the concentration of hydrazine in the range from 0.05-10 mg?L–1 with a correlation coefficient of R2=0.9999 (n=7). The experimental detection limit is 0.05mgL–1. The sampling frequency is 15 samples h–1 and the relative standard deviation was 2.1% for 0.05 mg?L–1. This method is suitable for automatic and continuous analysis and successfully applied to determine the concentration of hydrazine in the aqueous stream of nuclear fuel reprocessing.

Service Quality Measurement and Competition Strategy Analysis of Online Shopping

E-Commerce refers to such business behavior as conducting trades on a virtual network through the Internet.The core elements contributing to the success of online stores include not only the web-based presentation and the low-price strategy but the quality of online service as well.Importance-Performance Analysis is a method frequently used to evaluate performance and analyze competition strategies.Using IPA,this study analyzed and investigated the service quality of the online shopping of a case company and proposed 10 indexes to measure the service quality of online shopping.a number of suggestions on competition strategies were provided for the case company to improve its competition strategies.

A Genre Analysis of Online English Job Advertisement

In the recent years, posting online job advertisements has become a major way for a growing number of multinational cor-porations to publicize their employment information and to recruit job seekers. Nevertheless, the language and space of online jobadvertisement are uneven, which may affect the companies to attract and communicate with the potential candidates. Based on thetheoretical framework of moves and steps analysis suggested by Swales(1990) and Bhatia(2004), the study aims to explore thestructural pattern of this genre and to examine the lexico-grammatical features of each move and step. After analyzing four piecesof job advertisements retrieved from different recruiting websites, the study reveals that there are six moves in the whole structureof online job advertisement, among these, three moves are obligatory, named: establishing credential, introducing the position, to-gether with specifying required qualifications, skills, and experiences. Meanwhile, in each move, the positive adjectives, verbs, andfirst person are frequently used to serve the promotional function, and therefore to intensify the communicative purpose. The studymay contribute to the application of genre analysis in business English teaching, and also be instructive to the reading and writingof online job advertisement.

Genre Analysis of Online Company Profiles from Sporting Goods Brands

With the development of globalization and information technology,online company profile has been an effective commu-nication channel between companies and their target customers or clients.Online company profile,as a specific genre,has the dis-tinct features and functions in commercial activities.This study aims to do linguistic study of the constitution and the role of thesecompany profiles about sporting goods for communication on the Internet.To realize it,six company profiles have been selectedfrom the official websites of each sports company.The genre analysis of these samples is conducted from the perspective ofHasan’s Contextual Configuration(CC)and Generic Structure Potential(GSP).This thesis attempts to give the suggestions on howto compose a company profile for readers and sporting companies and the reference for the related researches in the future.

Analysis on the status and influencing factors of undergraduate nursing students’ online learning engagement in the context of the pandemic

Objective:This project has mainly studied the online learning engagement of undergraduate nursing students and analyzes influencing factors of online learning and teaching mode during the Novel Coronavirus(COVID-19).This research has significant references for improving the efficiency and quality of the online learning mode of students.Methods:In this study,212 undergraduate nursing students were selected from a comprehensive university in Jilin Province by combining convenience sampling and cluster sampling methods.And these students were conducted with a general information questionnaire,Online Academic Emotion Scale,and Online Learning Engagement Scale.The influencing factors of this teaching mode were analyzed by multiple linear stepwise regression.Results:The total score of online learning engagement of undergraduate students was 53.85±7.38,which positively correlated with positive high arousal emotion and negative high arousal emotion,but weakly negatively correlated with negative low arousal emotion(r=0.661,0.246,-0.187,P<0.001).Grade,type of online class,online learning time,and positively high arousal emotion were mainly affected the online learning engagement of undergraduate nursing students,which explained 78.5%of the total variation(P<0.001).Conclusion:The online learning engagement of undergraduate nursing students was above the middle level under the background of the COVID-19 pandemic.Lectures and professors who teach undergraduate nursing students,should integrate the individuation characters of nursing students,and motivate their positively high arousal emotion to improve online learning engagement of students to ensure the quality of online teaching mode.

Analysis of Factors Affecting Online Drug Purchase–Based on Factor Analysis

Objective To explore the factors affecting consumers’online drug purchases,and construct models of these factors to provide references for the development and popularization of online pharmacies.Methods Through searching,classifying,integrating,and extracting evaluation indexes of online pharmacies in literature,the indexes of factors affecting online drug purchases were initially established.Then SPSS24.0 was used for data analysis,and finally factor analysis was applied for screening and combining the indexes.Results and Conclusion A model of influencing factors for online drug purchases is set up with 4 factors and 14 indexes.Convenient service is the most important factor affecting online drug purchases.Highly educated young people prefer to buy drugs online.At present,online drug purchase is only a supplement to the purchase of drugs in offline pharmacies,and the penetration rate is not high.Online pharmacies should give full play to their advantages in terms of drug types,prices,logistics and after-sales services to make online drug purchases more mainstream.

Influence of Online Learning Attitude in the Blended Teaching Model on the Final Grades

The combination of online teaching and traditional offline teaching can maximize the advantages of both.Based on the blended teaching of English Reading course,39 students were selected as the research subjects to study the relationship between their online learning attitudes and their grades in the final examination.Judged from the number of times for each student to download teaching resources,the number of assignments submitted online,and the quality of the submitted assignments,each student’s attitude toward online learning was examined comprehensively,and a correlation analysis was conducted through SPSS Statistics 21.0 to explore the influence of online learning attitude on English reading performance.Through data collection and analysis of the online learning attitudes over a 16-week period,a significant positive correlation was found between the online learning attitudes and the English reading grades,indicating that the online learning attitude in the blended learning model plays a crucial role in improving the English reading skill,and students should maintain a positive attitude toward online teaching in blended learning.