Search

This study examined the development of text complexity for the past 25 years of reading comprehension passages in the National Matriculation English Test (NMET) in China. Text complexity of 206 reading passages at lexical, syntactic, and discourse levels has been measured longitudinally and compared across the years. The natural language processing tools used in the study included TAALES, TAALED, TAASSC, and TAACO. To compare the differences across the years at various levels of text complexity, ANOVA and MANOVA tests were conducted. The results suggested that lexical level text complexity revealed the most evident changes throughout the years, lexical sophistication, density, and diversity levels of the most recent years of reading passages have increased remarkably compared to the early years. The syntactic level text complexity indicated a moderate elevation toward the recent years of reading passages. For the discourse level text complexity, regarding cohesion, insignificant fluctuation occurred throughout the years and the general trend was not necessarily increasing. Combined, the results indicated that text complexity of the reading comprehension passages in the NMET over the past 25 years had been steadily increasing by including more low frequency and academic vocabulary, diversifying vocabulary in the passages, and complicating sentence and grammatical structures. The results were further examined against the general curriculum standards and guidelines to analyze whether the changes were reflected in the policies. It showed that the exams required a much larger vocabulary size than the number indicated in the guidelines, suggestions for test designers and pedagogical practices were provided accordingly.

Objective To explore the effectiveness of a refined three-scene medication simulation teaching in nursing pharmacology course for nursing undergraduates. Methods Undergraduates of four-year curriculum in School of Nursing, Peking Union Medical College enrolled in 2020 and 2021 were selected as objects in control group and experimental group, respectively. Students in control group learned medication knowledge in a patient case simulation scene, while a refined three-scene medication process (before, during and after medication) simulation was applied in experimental group. The learning outcome was evaluated in forms of both test of key knowledge points and a questionnaire survey at the end of the semester. Results The scores of nursing pharmacology in experimental group were significantly higher than in control group (P＜0.001). The rates of right answer for knowledge associated with the refined class in experimental group were also significantly higher than in control group (P＜0.001). However, for knowledge that has not been adjusted for instructional design, there is no significant difference in answer accuracy between two groups. The survey by questionnaire showed that the students believed the three-scene medication simulation as good learning method and may support to strengthen professional quality of clinical performance. Conclusions Compared with the unrefined simulation class, the three-scene (before, during and after medication) class further simulated the real work flow, connected the knowledge points more reasonably, and enhanced the knowledge mastery and professional responsibility awareness.

Based on big data technology, this paper designs a digital management system for the whole process of financial reimbursement and gives the automatic transformation process of digitalization of financial reimbursement claims and accounting documents. In the K-Means algorithm, the AHC algorithm idea is introduced to construct the DH-K-Means clustering algorithm, which in turn enables the financial reimbursement behavioral portrait of enterprise employees to be constructed. To confirm the effectiveness of the system application in this paper, performance testing and portrait analysis were carried out. The results show that the maximum memory utilization of the database server is 50.42% when the number of concurrent users is 100, and the average response time of the system reaches a maximum of 825.63ms when the number of concurrent users is 200. Based on big data, the whole process of financial reporting digital management system has good stability, which can make enterprises more aware of their financial situation and then develop appropriate financial reimbursement strategies.

Cobalamin (vitamin B12; VB12) is an indispensable nutrient for all living entities in the Earth's biosphere and plays a vital role in both natural and host environments. Currently in the metagenomic era, gene families of interest are extracted and analyzed based on functional profiles by searching shotgun metagenomes against public databases. However, critical issues exist in applying public databases for specific processes such as VB12 biosynthesis pathways. We developed a curated functional gene database termed VB12Path for accurate metagenomic profiling of VB12 biosynthesis gene families of microbial communities in complex environments. VB12Path contains a total of 60 VB12 synthesis gene families, 287,731 sequences, and 21,154 homology groups, and it aims to provide accurate functional and taxonomic profiles of VB12 synthesis pathways for shotgun metagenomes and minimize false-positive assignments. VB12Path was applied to characterize cobalamin biosynthesis gene families in human intestines and marine environments. The results demonstrated that ocean and human intestine had dramatically different VB12 synthesis processes and that gene families belonging to salvage and remodeling pathway dominated human intestine but were lowest in the ocean ecosystem. VB12Path is expected to be a useful tool to study cobalamin biosynthesis processes via shotgun metagenome sequencing in both environmental and human microbiome research. IMPORTANCE Vitamin B12 (VB12) is an indispensable nutrient for all living entities in the world but can only be synthesized by a small subset of prokaryotes. Therefore, this small subset of prokaryotes controls ecosystem stability and host health to some extent. However, critical accuracy and comprehensiveness issues exist in applying public databases to profile VB12 synthetic gene families and taxonomic groups in complex metagenomes. In this study, we developed a curated functional gene database termed VB12Path for accurate metagenomic profiling of VB12 communities in complex environments. VB12Path is expected to serve as a valuable tool to uncover the hidden microbial communities producing this precious nutrient on Earth.