bluuebunny/crossref_metadata_2025_split huggingface dataset:
In vivo antimalarial activity of Cyperus rotundus and its combination with dihydroartemisinin against Plasmodium berghei
Authors: Ounjaijean Sakaewan , Lektip Charupa , Somsak Voravuth 
Published: September 2023

Abstract
Background
The increase in the number of drug-resistant Plasmodium species continues to be a serious public health concern. Therefore, identification of potential novel antimalarial drugs derived from therapeutic plants could help solve this issue. This study investigated whether Cyperus rotundus aqueous crude extract (CRE) and its combination with dihydroartemisinin (DHA) were effective against Plasmodium berghei ANKA-infected mice.
Methods
CRE was prepared from C. rotundus rhizomes and evaluated in acute and subacute toxicity tests on BALB/c mice. The antimalarial effectiveness of CRE was assessed at 100, 200, and 400 mg/kg in a 4-day suppressive test with curative and prophylactic testing and measurement of packed cell volume (PCV), body weight (BW), rectal temperature, and mean survival time (MST).
Results
Following acute and subacute treatment, CRE caused no harmful effects or mortality in mice. When compared with that in the untreated control, infected mice administered with 400 mg/kg of CRE in a 4-day suppressive test exhibited the strongest antimalarial activity (55.30% inhibition) with prolonged MST. However, curative and prophylactic assays did not reveal CRE to have antimalarial activity. In comparison with that achieved with the single therapy, the combination of DHA and CRE at ED50/2 (1 and 200 mg/kg, respectively) produced considerable antimalarial activity at 90.08% inhibition with synergism (combination index = 0.21701). For the other parameters, CRE administration prevented malarial-induced changes in PCV, BW, and rectal temperature.
Conclusions
CRE treatment significantly inhibited malaria in the 4-day suppressive test, and CRE combined with DHA had a synergistic antimalarial effect.
A WaveNet-based convolutional neural network for river water level prediction
Authors: Chen Jun , Huang Yanhua , Wu Teng , Yan Jing 
Published: September 2023

Abstract

River water level prediction (WLP) plays an important role in flood control, navigation, and water supply. In this study, a WaveNet-based convolutional neural network (WCNN) with a lightweight structure and good parallelism was developed to improve the prediction accuracy and time effectiveness of WLP. It was applied to predict 1/2/3 days ahead the water levels at the Waizhou gauging station of the Ganjiang River (GR) in China, and it was compared with two recurrent neural networks (long short-term memory (LSTM) and gated recurrent unit (GRU)). The results showed that the WCNN model achieved the best prediction performance with the fewest training parameters and time. Compared with the LSTM and GRU models in the 1-day ahead prediction, the training parameters were reduced from 73,851 and 55,851 to 32,937, respectively. The root mean square error (RMSE) was reduced from 0.071 and 0.076 to 0.057, respectively. The mean absolute error (MAE) was reduced from 0.052 and 0.059 to 0.038, respectively. The Nash–Sutcliffe efficiency (NSE) and coefficient of determination (R2) both increased to 0.998. This result indicated that the improved model was more efficient for WLP.
Emergency intervention modes for ice jam events in large-scale water diversion projects
Authors: Xu Zepeng , Liu Mengkai , Guan Guanghua , Guo Xinlei 
Published: September 2023

Abstract
The formation of ice jams is sudden, and they will cause abnormal water level fluctuations in water diversion projects, affecting the water supply and even causing severe flood disasters. Based on the characteristics of the Middle Route of the South-to-North Water Diversion Project, this paper uses the numerical simulation method to establish an emergency intervention effect simulation model for ice jam events. The hydraulic response characteristics of the project under gate group scheduling and taking different emergency measures are analyzed with the water level deviation and stabilization time consumption of the pool as indicators. Moreover, this paper proposes an emergency intervention mode for ice jam events. The results show that using the gate group scheduling after ice jam events will cause a sharp rise in the upstream water level of the pool where the ice jams are located. Also, compared with other emergency measures, the electric heating ice melting measure has less influence on water level, and the de-icing effect is better. Finally, the emergency intervention mode can significantly reduce the maximum water level deviation and shorten the time required to stabilize the water level.
Uptake, accumulation, and degradation of dibutyl phthalate by three wetland plants
Authors: Fan Yaocheng , Li Tiancui , Zhang Zihan , Song Xiaoyong , Cun Deshou , Cui Baihui , Wang Yuewei 
Published: September 2023

Abstract

The uptake and degradation mechanisms of dibutyl phthalate (DBP) by three wetland plants, namely Lythrum salicaria, Thalia dealbata, and Canna indica, were studied using hydroponics. The results revealed that exposure to DBP at 0.5 mg/L had no significant effect on the growth of L. salicaria and C. indica but inhibited the growth of T. dealbata. After 28 days, DBP concentrations in the roots of L. salicaria, T. dealbata, and C. indica were 8.74, 5.67, and 5.46 mg/kg, respectively, compared to 2.03–3.95 mg/kg in stems and leaves. Mono-n-butyl phthalate concentrations in L. salicaria tissues were significantly higher than those in the other two plants at 23.1, 15.0, and 13.6 mg/kg in roots, stems, and leaves, respectively. The roots of L. salicaria also had the highest concentration of phthalic acid, reaching 2.45 mg/kg. Carboxylesterase, polyphenol oxidase, and superoxide dismutase may be the primary enzymes involved in DBP degradation in wetland plants. The activities of these three enzymes exhibited significant changes in plant tissues. The findings suggest L. salicaria as a potent plant for phytoremediation and use in constructed wetlands for the treatment of DBP-contaminated wastewater.
Мотивация студентов-психологов: роль контента масс медиа-психологов в ее формировании
Authors: Смирнова Нина В. 
Published: September 2023

Введение. Данная статья посвящена исследованию влияния контента медиа-психологов на академическую мотивацию студентов-психологов. Исследование заполнит пробел в существующих научных знаниях, поскольку в данный момент мало известно об отношении студентов-психологов к просмотру психологического контента и о связи этого отношения с мотивацией. Методы. Выборка исследования составила 67 человек, из которых: 92,5% составили девушки, а 7,5% – мужчины. Применялись такие методики, как ШАМ (Шкала академической мотивации), САМОАЛ и авторская анкета-опросник. Результаты. Исследование показало высокую вовлеченность студентов-психологов в деятельность масс медиа-психологов. Большая часть из учащихся обозначает важность такого контента для развития критического мышления и профессиональных навыков в целом. Так же, было выявлено, что студенты часто обращающиеся к контенту масс медиа-психологов имеют более высокий уровень познавательной мотивации и креативности, по сравнению с теми, кто не интересуется таким контентом. Обсуждение результатов. Полученные согласуются с исследованиями авторов, которые изучали особенности мотивации студентов-психологов и влияние медиа-контента на ее развитие. Исследование показало, что положительное влияние масс медиа-психологов на мотивацию студентов психологов действительно присутствует.
Desapariciones forzadas – Desapariciones. La experiencia argentina - Implicancias subjetivas
Authors: Freier María 
Published: September 2023

Este artículo expone la relevancia de la desaparición de personas en el contexto de la dictadura cívico militar en Argentina (1976-1983); describe el clima represivo, el plan sistemático de persecución, secuestros y desapariciones sufridos por la sociedad argentina, la cual emprendió una resistencia y lucha, con el miedo y el dolor a cuestas; así como la importancia del activismo nacional e internacional para la judicialización de delitos de lesa humanidad. La autora escribe desde un pensamiento situado, como hermana de una persona secuestrada-desaparecida en la dictadura de 1978; refiere la creación y consolidación de instituciones para el reconocimiento y búsqueda de desaparecidos y asistencia a las víctimas, así como la aplicación y desarrollo de la antropología forense en la investigación de violaciones a los derechos humanos como dos factores que han contribuido a la construcción de la memoria histórica social y subjetiva de este flagelo en Argentina.
Karnauph Classifier: A Hybrid Mathematical Model for Data Classification
Authors: Zabian Arwa 
Published: September 2023

Abstract
The speed at which the data is generated, processed and stored to meet the demands of our lives today requires new technologies for handling and using this amount of data. Research on the effective usage of this data suggests that data analysis can contribute to international development, by improving decision-making, in health care, economic, and human resource development. Using artificial intelligence helps in discovering the important features of the data and to use it in classifying known data or in predicting the state of unseen data. In this paper, we propose a hybrid model that combines between Decision Tree algorithm and the Naïve Bayes algorithm in linear functions to improve the performance of a single classifier. Our algorithm is tested for three features and four features on binary data only. The simulation results indicate that our proposed algorithm outperforms the two algorithms tested separately on the same data in terms of accuracy which refers to the number of cases predicted correctly.
The promotion path of high-quality development of rural tourism based on intelligent cloud platform system
Authors: Zhu Weiqi 
Published: September 2023

Abstract
With the continuous development of the economy and the level of science and technology, people are no longer satisfied with the old rural tourism model, and information technology is developing rapidly, which brings an opportunity for developing rural tourism innovation. As a product of the comprehensive development of the information age in recent years, “Internet+Rural Tourism” builds an intelligent cloud platform for rural information services relying on big data and other advantages and establishes a rural intelligent tourism service system to provide convenient, intelligent, and diversified services for tourists. This paper elaborates on the practical significance of “Internet + rural tourism” development opportunities”. It proposes to scientifically calculate the environmental capacity of rural eco-tourism areas, control the scale of visitors and reasonably invest in costs because of the problems of lagging infrastructure facilities and limited distribution of inputs and outputs in the process of its development. The results of this paper show that the satisfaction level of rural tourism tourists is the lowest, with the degree of “dissatisfaction” as high as 38.40%; in the rating of rural tourism indicators, the rating of rural ecological environment is only 52.41, the average rating of rural economic indicators is 60.12, and the average rating of comprehensive management indicators is 58.2. The results of this paper also illustrate that the current rural tourism development has three major problems: environment, economy, and management and that rural tourism should not blindly invest high costs if it wants to seek high-quality development but should seek long-term development of rural tourism based on its characteristics and rural ecological environment indicators.
A mining method of integrating Civic Science elements into English teaching in higher vocational courses based on information fusion technology
Authors: Zheng Suying , Cui Tonglu 
Published: September 2023

Abstract
To implement the fundamental task of establishing moral education and practicing the concept of curriculum thinking and politics education, we promote the construction of English curriculum thinking and politics in higher education institutions from the necessity and feasibility of English curriculum thinking and politics and put forward the implementation strategy of English curriculum thinking and politics in higher education. In this paper, we use information fusion technology to fully explore the feasibility of integrating the thinking politics elements of higher vocational courses into English teaching and achieve the purpose of the study by exploring the ability to improve teachers’ thinking politics education, exploring the thinking politics education elements of teaching materials, and enriching the thinking politics education resources of courses. The basic algorithm of information fusion technology and the computational model of information fusion based on the RBF neural network are used to construct the mechanism of English Civic Education. According to the research, 90.71% of the teachers in the higher vocational English course education are in favor of stopping the courses such as “Bible reading,” which are not conducive to transmitting the truth of Marxism and promoting the core socialist values among college students; 80.5% of the teachers think that they should actively respond to the call of the Party and promptly 80.5% of the teachers think that they should actively respond to the Party’s call, set up teaching and research teams, study the teaching materials, explore and carry out the “Civic Politics in College English Course”, and the students generally think that the “Civic Politics in College English Course” exposes them to a large number of topics that are “closely related to the national political policies and other courses”. The students generally think that the English language courses have exposed them to much English knowledge that is “closely related to the national political policies and other courses, especially the Civic and Political Science courses”, and the English classes have become “interesting and useful”. The appropriate amount of “political thinking in the curriculum” obviously affects teaching English at university. It helps to carry out the whole process of education and teaching effectively, transform the whole staff from a dedicated person to a creative person, and effectively realize the whole staff, the whole process, and the comprehensive education of people.
Visualization communication mode and path optimization of data news in the context of big data
Authors: Zhang Hezhen 
Published: September 2023

Abstract
With the development of big data technology, not only driving the development of the social economy but also the news media industry is developing in the direction of integration and innovation, and promoting the dissemination of news through data value factors is the focus of current research. This paper takes data news as the research object, takes the framework theory as the entry point, and mainly studies the data news production dilemma and its optimization path. Firstly, the data news information is classified by entity extraction, and the weights between the entity information are calculated to establish the association. Secondly, the IE-Page Rank algorithm is proposed to get the IER value of each information entity by iterative calculation, which is used to identify its importance and quantitatively get the importance ranking of all information entities. Finally, the basic framework of data news visualization is constructed, and the applicable visualization optimization dissemination path is given in the case. The research results show that compared with the traditional media news dissemination model, the improved data visualization dissemination model increases efficiency by 32.3%, timeliness by 18.9%, user satisfaction by 21.1%, and effectively increases the reading volume and dissemination paths by 17.2% of users. The improved data news visualization dissemination model proposed in this paper improves the professionalization of data analysis, enhances the interactivity and visualization of data news works, and provides guidance for disseminating data news.
Media-based information display in university libraries based on a generalized differential equation numerical method
Authors: Li Shulong , Li Lina , Zhang Feng 
Published: September 2023

Abstract
To solve the problems of time lag and high repetition rate of information released in the media-oriented information display of college libraries, this paper improves the media-oriented information display platform based on the numerical method of generalized differential equations. The intervals of the generalized differential equations solutions for the media-oriented information display of college libraries are discretized using a grid to obtain sub-intervals. The points on the grid for each subinterval are approximated continuously using the K-step edge-value method to obtain the information dissemination cycle solution. The bifurcated periodic solution is used to check the obtained information release period solution, and the final information update period is 7 days. The results of improving the media-based information display platform of university libraries and putting it into operation of university libraries show that: Using the information update cycle determined by the generalized differential function to improve the media-based information display platform of university libraries, the repetition rate of language information release decreases from 30% to 10%. The working hours of librarians were reduced from 5 hours per week to 3.5 hours per week. It can be seen that after improving the media-based information display platform of university libraries based on the numerical method of a generalized differential equation, the repetition rate of information release and the work efficiency of librarians of the platform is improved.
Research on the current situation and countermeasures of cultivating talents in recreational sports under the perspective of artificial intelligence
Authors: Dong Zhonglei , Sha Nu 
Published: September 2023

Abstract
With the change of the fourth generation of information technology represented by artificial intelligence, higher education is gradually stepping into the stage of intelligent development, and leisure sports majors as one of the majors that are booming, which puts forward higher requirements on the teaching power of teachers of leisure sports majors. Therefore, studying the current situation of talent cultivation of leisure sports majors under artificial intelligence plays a good role in promoting the overall improvement of the teaching quality of leisure sports majors. In this paper, the current situation of talent training and classroom teaching of leisure sports majors is studied based on a convolutional neural network in the artificial intelligence perspective, and the framework of artificial intelligence technology for leisure sports education is constructed. It can be seen that the attitude of leisure sports students towards theory class is better; 40.93% think theory class is very important, 38.13% think theory class is more important, and 19.27% think the importance of theory class is average. Students’ attitudes toward practical classes were better than those toward theoretical classes, with 63.71% considering practical classes very important and 26.85% considering them more important. From the analysis results, we can see that there are still problems of weak basic theory research, confusion of cultivation goals, lack of science in curriculum setting, and lack of teachers in cultivating talents in leisure sports majors. In summary, this paper argues that colleges and universities and college teachers should take the initiative to apply the technical framework of artificial intelligence in leisure sports education, strengthen theoretical research, make up for the shortcomings of teaching materials, as well as integrate training objectives, improve curriculum settings, enhance faculty strength, investigate the talent specification needs of the market in-depth, proactively meet the arrival of the era of artificial intelligence, and contribute to the cultivation of talents in leisure sports majors.
The digital economy is an important path to boosting common prosperity
Authors: Li Nan , Ma Zheng 
Published: September 2023

Abstract
Promoting progress in the digital development of social wealth is the key strategy to promote wealth transformation. The increase has been increasing at present. Increase GDP of national wealth strategy to our country to promote wealth transformation The increase of wealth is increasing at present. This paper proposes recommendations for other regional differences to promote continuous updating of development concepts, innovation-driven development, and optimization of industrial structure to provide a good environment for the digital economy to promote the increase of wealth in increasing construction. With this as the key theory from 2012 to 2019, here we designed an economic measurement model that uses simple linear regression, benchmark test, correlation test, and intermediary effect test to conduct empirical research, measure the current situation, and develop existing grade classification and economic development level, and empirically analyzes the impact of development grade phenomenon on the commonwealth. The results show that different regions have different conditions. At the same time, grade performance contributes to the development of good results economy, with the greatest impact on the West and the least impact on the Center. In general, a subdivision of social hierarchy, the level of the high-quality economy has been improving, parameter problems in different regions roughly describe a stable, rising direction, average values of the national, eastern and central, and western regions in 2007 are 31.11, 37.53 and 27.40, rising to 42.65, 50.11 and 38.34 in 2019, respectively. Thus, the digital economy provides effective and feasible new development ideas and changes in key economic issues and is a key force driving China’s economic growth and an important path to boost common prosperity.
Optimization of cross-border e-commerce marketing strategy based on deep learning model
Authors: Cui Rui 
Published: September 2023

Abstract
The advent of the era of artificial intelligence provides technical support for cross-border e-commerce marketing to break the traditional competitive model and make efforts to build an online shopping platform that can meet international sellers’ and consumers’ transactions at any time around the world. This paper constructs a cross-border e-commerce marketing strategy optimization model based on deep reinforcement learning and convolutional neural network under artificial intelligence technology and explores the optimization method of the cross-border e-commerce marketing strategy by verifying the accuracy of the model and mining and analyzing the example data of Company A’s cross-border e-commerce platform. From the data, the accuracy of the deep convolutional neural network model is 99.47%, the proportion of beauty and beauty, mother and child care, and medical and health products in the product marketing strategy is 79.92%, 71.48%, and 59.93%, respectively, and the proportion of search traffic of the top three keywords in the search channel marketing is 42.69%, 31.23%, and 22.65%, respectively, and the ranking of the bottom The average traffic search of the seven types of keywords is less than 10%. This also shows that the optimization of a cross-border e-commerce marketing strategy based on the deep convolutional neural network can clearly analyze the data in the current marketing strategy, guide how to optimize the marketing strategy based on the data, and then improve the economic benefits of cross-border e-commerce enterprises. Applying a deep convolutional neural network model in a cross-border e-commerce marketing strategy also provides a direction for the new development field of artificial intelligence technology, which is beneficial to the further development of artificial intelligence technology.