Countries are paying increasing attention to environmental issues and are moving towards the goal of energy saving and carbon reduction. This research presents a method to analyse the effects of the ...use of non-thermal plasma (NTP) and water injection (WI) devices on the efficiency of internal combustion engines. The devices were installed on the intake manifold to investigate the effects of additional substances produced by electrolysis on the engine performance and exhaust emissions. According to the results, the addition of the NTP and WI devices affected the power efficiency and the rate of change of the brake-specific fuel consumption (BSFC) of the internal combustion engines. In addition, the change rate of hydrocarbons (HC), carbon monoxide (CO), and nitrogen oxides (NOx) in the exhaust gases was affected. In conclusion, the study found that the additional substances generated by the NTP-electrolysed water mist or air influenced the fuel combustion efficiency and exhaust emissions.
Pretesting is the most commonly used method for estimating test item difficulty because it provides highly accurate results that can be applied to assessment development activities. However, ...pretesting is inefficient, and it can lead to item exposure. Hence, an increasing number of studies have invested considerable effort in researching the automated estimation of item difficulty. Language proficiency tests constitute the majority of researched test topics, while comparatively less research has focused on content subjects. This paper introduces a novel method for the automated estimation of item difficulty for social studies tests. In this study, we explore the difficulty of multiple-choice items, which consist of the following item elements: a question and alternative options. We use learning materials to construct a semantic space using word embedding techniques and project an item's texts into the semantic space to obtain corresponding vectors. Semantic features are obtained by calculating the cosine similarity between the vectors of item elements. Subsequently, these semantic features are sent to a classifier for training and testing. Based on the output of the classifier, an estimation model is created and item difficulty is estimated. Our findings suggest that the semantic similarity between a stem and the options has the strongest impact on item difficulty. Furthermore, the results indicate that the proposed estimation method outperforms pretesting, and therefore, we expect that the proposed approach will complement and partially replace pretesting in future.
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•Additionally input the ionized gaseous water molecules into the gasoline engine by using the corona discharge.•The brake-specific fuel consumption (BSFC) was improved up to 3.0% with ...the ionized gaseous water molecules at 1000 Hz and 30 V corona discharge.•Ionized gaseous water molecules were advantageous in the reduction of CO, but increased NOx and HC.•The corona’s voltage and frequency increase in systems that increase horsepower, HC, NOx, and exhaust temperature and reduce BSFC and CO.
Among various air pollution issues, exhaust emissions from internal combustion engines have become one of society’s primary concerns. This study analyzed the water system and plasma system installed on the intake manifold to investigate the effects of additional substances produced by the electrolysis of saturated gaseous water molecules on engine performance and exhaust emissions. The results indicate that electrolyzing gaseous water molecules produce hydrogen and oxygen at different voltages and frequencies of the corona, which affects the power efficiency and the brake-specific fuel consumption (BSFC) of internal combustion engines. Moreover, it affects the concentration of hydrocarbons (HC), carbon monoxide (CO), and nitrogen oxides (NOx). The result shows that engine power increased by 2.5%, BSFC decreased by 3%, and CO decreased by 9%. However, the result indicates that HC increased by 29%, and NOx increased by 21%. In conclusion, electrolyzing saturated gaseous water molecules in a non-thermal plasma improves engine performance but increases the concentration of HC and NOx. However, the changes in performance and exhaust emissions are only noticeable at higher ignition frequencies of the non-thermal plasma, and the performance changes at lower frequencies are like only using the water system.
•The quality and readability of breast cancer websites in Chinese are not satisfactory.•Websites produced by non-profit organizations with the highest quality.•Websites produced by private ...individuals with the best readability.•Search engine ranking has no correlation with website quality or readability.
This study aimed at evaluating the quality and readability of online information about breast cancer written in Chinese.
An Internet search was conducted for “breast cancer” in Chinese using the Baidu search engine. Website quality was evaluated using the DISCERN instrument, and readability was evaluated using the Chinese Readability Index Explorer (CRIE). Higher DISCERN score indicated higher quality of websites, while higher CRIE score indicated lower readability of the content of the websites. We also investigated the effects of website producer category, and the associations of search engine ranking with DISCERN and CRIE scores.
A total of 49 websites were included. The mean overall DISCERN score was 50.27 ± 4.14, and the mean CRIE score was 6.78 ± 0.16. Websites produced by non-profit organizations had the highest overall DISCERN scores, while those produced by private individuals had the lowest CRIE scores. Search engine ranking had no significant correlation with website quality or readability.
The quality and readability of breast cancer websites in Chinese were not satisfactory, and they varied among different website producer categories.
Website producers should seek to provide more accurate, comprehensive, and easy-to-understand information to better meet the needs of breast cancer patients. In addition, search engines should revise algorithms to promote websites with higher quality and accessibility.
Textual analysis has been applied to various fields, such as discourse analysis, corpus studies, text leveling, and automated essay evaluation. Several tools have been developed for analyzing texts ...written in alphabetic languages such as English and Spanish. However, currently there is no tool available for analyzing Chinese-language texts. This article introduces a tool for the automated analysis of simplified and traditional Chinese texts, called the Chinese Readability Index Explorer (CRIE). Composed of four subsystems and incorporating 82 multilevel linguistic features, CRIE is able to conduct the major tasks of segmentation, syntactic parsing, and feature extraction. Furthermore, the integration of linguistic features with machine learning models enables CRIE to provide leveling and diagnostic information for texts in language arts, texts for learning Chinese as a foreign language, and texts with domain knowledge. The usage and validation of the functions provided by CRIE are also introduced.
The application of word associations has become increasingly widespread. However, the association norms produced by traditional free association tests tend not to exceed 10,000 stimulus words, making ...the number of associated words too small to be representative of the overall language. In this study we used text corpora totaling over 400 million Chinese words, along with a multitude of association measures, to automatically construct a Chinese Lexical Association Database (CLAD) comprising the lexical association of over 80,000 words. Comparison of the CLAD with a database of traditional Chinese word association norms shows that word associations extracted from large text corpora are similar in strength to those elicited from free association tests but contain a much greater number of associative word pairs. Additionally, the relatively small numbers of participants involved in the creation of traditional norms result in relatively coarse scales of association measurement, whereas the differentiation of association strengths is greatly enhanced in the CLAD. The CLAD provides researchers with a great supplement to traditional word association norms. A query website at
www.chinesereadability.net/LexicalAssociation/CLAD/
affords access to the database.
Text readability assessment is a challenging interdisciplinary endeavor with rich practical implications. It has long drawn the attention of researchers internationally, and the readability models ...since developed have been widely applied to various fields. Previous readability models have only made use of linguistic features employed for general text analysis and have not been sufficiently accurate when used to gauge domain-specific texts. In view of this, this study proposes a latent-semantic-analysis (LSA)-constructed hierarchical conceptual space that can be used to train a readability model to accurately assess domain-specific texts. Compared with a baseline reference using a traditional model, the new model improves by 13.88% to achieve 68.98% of accuracy when leveling social science texts, and by 24.61% to achieve 73.96% of accuracy when assessing natural science texts. We then combine the readability features developed for the current study with general linguistic features, and the accuracy of leveling social science texts improves by an even higher degree of 31.58% to achieve 86.68%, and that of natural science texts by 26.56% to achieve 75.91%. These results indicate that the readability features developed in this study can be used both to train a readability model for leveling domain-specific texts and also in combination with the more common linguistic features to enhance the efficacy of the model. Future research can expand the generalizability of the model by assessing texts from different fields and grade levels using the proposed method, thus enhancing the practical applications of this new method.
Studies on teaching of reading strategies have found that summarizing is of tremendous help to reading comprehension. However grading students’ summary writings is laborious, but given the importance ...of summarizing, an effective summarizing learning module is important. This study developed an automatic summary assessment and feedback system based on Latent Semantic Analysis (LSA) to provide score, concept and semantic feedback, and then investigated the effects of concept and semantic feedback on the writing of summaries by students in the sixth grade. The design involved two between-subject factors: semantic feedback (with, without) and concept feedback (with, without). 120 sixth-grade students from an elementary school were recruited for the study, and then were randomly assigned to each group. The overall results demonstrated the effectiveness of the proposed system in improving the summary writing skills of students. The effects of semantic feedback and concept feedback were also discussed.
•An automatic summary assessment and feedback system based on LSA is proposed.•An experiment was conducted to investigate the effects of various feedback modules.•The proposed system improved students' summary writing.•The concept feedback improved students' summarization significantly.
Radio frequency (RF) magnetron sputtering was used to sputter a thin layer of ITO:Ga with a purity of 97:3 at% on glass substrates. A layer of Zr with a purity of 99.99% was then deposited on the ...ITO:Ga layer by direct current magnetron sputtering. Finally, RF magnetron sputtering was used once again to deposit a thin ZnO layer with a purity of 99.99 at% on top of the Zr layer. The three-layered film structure was annealed in a vacuum at various temperatures in the range of 200–500 °C in order to prompt a rearrangement of the crystal structure and reduce the number of internal defects. The effects of the annealing temperature on the film thickness, electrical properties, optical properties, surface morphologies, and quality factors of the multilayered films were investigated. The trilayer film showed a minimum resistivity of 1.79 × 10−3 Ω-cm after annealing at a temperature of 500 °C and an average optical transmission of 88.14% after annealing at 300 °C. The optimal quality factor (1.44 × 10−3 Ω−1) was obtained for the film annealed at 500 °C.
In this study, double-layer transparent conductive thin films are formed by depositing silver (Ag) of 99.99% purity on a glass substrate by direct-current (DC) magnetron sputtering, then forming an ...oxide layer on the Ag layer by depositing gallium-doped indium tin oxide (ITO:Ga) with an ITO:Ga ratio of 97:3 by radio-frequency magnetron sputtering. The films are annealed in vacuum at different temperatures to rearrange the crystals in the films and thereby reduce the defect density. The thicknesses, electrical properties, optical properties, surface structures, and figures of merit (FOMs) of the ITO:Ga/Ag double-layer thin films before and after annealing are analyzed. It is found that the resistivity of the double-layer thin films decreases with increasing annealing temperature and that the lowest resistivity is 5.03×10−5 Ω-cm and the highest average transmittance is 73.33% for the specimen annealed at 450 °C, which also has the highest FOM of 5.31×103 Ω−1. The ITO:Ga/Ag double-layer thin films have excellent optical and electrical properties for photosensor applications.
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