Design Variables for Self-Directed Learning in MOOC Environment

Massive Open Online Courses (MOOCs) can meet education needs from diverse social, cultural, and access backgrounds and require a minimal cost of resources from learners. To successfully scaffold large and distributed populations to learn effectively in these MOOCs, the design needs to optimize self-directed learning. In this paper, the researchers investigated the design variables for MOOCs\u27 learning environment that allowed learning choices made by learners. With this study, the researchers developed a 21-item questionnaire based on a review of the literature and their MOOC design and implementation practices, Massive Online Open Course Learning Environment Design Questionnaire (MOOC-LED). The researchers used the quantitative survey study and developed an initial examination of the MOOC-LED factor structure, validity, and internal reliability. The analyses were based on the anonymous data of 162 participants’ perception of learning in MOOCs. The scholarly significance of the 21-item MOOC-LED questionnaire is discussed with its limitations, implications, and future directions

Assessment-Orientated Instructional Design Using DREAM Approach

This presentation proposes an assessment-oriented instructional design approach to enhancing student learning with blended learning environments and report its pilot implementation. Students gain significant learning experience through understanding the relationship between learning outcomes and learning process, connecting acquired knowledge, being able to tackle problems individually or on teams, and learning how to learn (Entwistle, Tait, & McCune, 2000; Fink, 2013; Suskie, 2010; Wiggins, 1998). These components ought to be designed in learning activities to educate learners through formative assessment such as self-reflection, peer evaluation, and constructive feedback from instructor (Angelo & Cross,1993; Wiggins, 1998). In blended learning with online environments, all learning activities are referred to as assessment measures, because all activities formatively assess student progress (Baily, Hendricks, & Applewhite, 2015). With the planful blending of asynchronous and synchronous technologies, assessment can be designed to facilitate learning, with the following key components: • Design learner-centered assessment that includes self-reflection, synthesis, and integration • Revitalize collaborative learning with online discussion and rubrics • Enable good feedback by the instructor and students • Align grading rubrics with assessment activities and learning outcomes • Mediate with technologies to ensure academic integrit

RefBERT: A Two-Stage Pre-trained Framework for Automatic Rename Refactoring

Refactoring is an indispensable practice of improving the quality and maintainability of source code in software evolution. Rename refactoring is the most frequently performed refactoring that suggests a new name for an identifier to enhance readability when the identifier is poorly named. However, most existing works only identify renaming activities between two versions of source code, while few works express concern about how to suggest a new name. In this paper, we study automatic rename refactoring on variable names, which is considered more challenging than other rename refactoring activities. We first point out the connections between rename refactoring and various prevalent learning paradigms and the difference between rename refactoring and general text generation in natural language processing. Based on our observations, we propose RefBERT, a two-stage pre-trained framework for rename refactoring on variable names. RefBERT first predicts the number of sub-tokens in the new name and then generates sub-tokens accordingly. Several techniques, including constrained masked language modeling, contrastive learning, and the bag-of-tokens loss, are incorporated into RefBERT to tailor it for automatic rename refactoring on variable names. Through extensive experiments on our constructed refactoring datasets, we show that the generated variable names of RefBERT are more accurate and meaningful than those produced by the existing method

EALink: An Efficient and Accurate Pre-trained Framework for Issue-Commit Link Recovery

Issue-commit links, as a type of software traceability links, play a vital role in various software development and maintenance tasks. However, they are typically deficient, as developers often forget or fail to create tags when making commits. Existing studies have deployed deep learning techniques, including pretrained models, to improve automatic issue-commit link recovery.Despite their promising performance, we argue that previous approaches have four main problems, hindering them from recovering links in large software projects. To overcome these problems, we propose an efficient and accurate pre-trained framework called EALink for issue-commit link recovery. EALink requires much fewer model parameters than existing pre-trained methods, bringing efficient training and recovery. Moreover, we design various techniques to improve the recovery accuracy of EALink. We construct a large-scale dataset and conduct extensive experiments to demonstrate the power of EALink. Results show that EALink outperforms the state-of-the-art methods by a large margin (15.23%-408.65%) on various evaluation metrics. Meanwhile, its training and inference overhead is orders of magnitude lower than existing methods.Comment: 13 pages, 6 figures, published to AS

Cmah deficiency may lead to age-related hearing loss by influencing miRNA-PPAR mediated signaling pathway

Background Previous evidence has indicated CMP-Neu5Ac hydroxylase (Cmah) disruption inducesaging-related hearing loss (AHL). However, its function mechanisms remain unclear. This study was to explore the mechanisms of AHL by using microarray analysis in the Cmah deficiency animal model. Methods Microarray dataset GSE70659 was available from the Gene Expression Omnibus database, including cochlear tissues from wild-type and Cmah-null C57BL/6J mice with old age (12 months, n = 3). Differentially expressed genes (DEGs) were identified using the Linear Models for Microarray data method and a protein–protein interaction (PPI) network was constructed using data from the Search Tool for the Retrieval of Interacting Genes database followed by module analysis. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis was performed using the Database for Annotation, Visualization and Integrated Discovery. The upstream miRNAs and potential small-molecule drugs were predicted by miRwalk2.0 and Connectivity Map, respectively. Results A total of 799 DEGs (449 upregulated and 350 downregulated) were identified. Upregulated DEGs were involved in Cell adhesion molecules (ICAM1, intercellular adhesion molecule 1) and tumor necrosis factor (TNF) signaling pathway (FOS, FBJ osteosarcoma oncogene; ICAM1), while downregulated DEGs participated in PPAR signaling pathway (PPARG, peroxisome proliferator-activated receptor gamma). A PPI network was constructed, in which FOS, ICAM1 and PPARG were ranked as hub genes and PPARG was a transcription factor to regulate other target genes (ICAM1, FOS). Function analysis of two significant modules further demonstrated PPAR signaling pathway was especially important. Furthermore, mmu-miR-130b-3p, mmu-miR-27a-3p, mmu-miR-27b-3p and mmu-miR-721 were predicted to regulate PPARG. Topiramate were speculated to be a potential small-molecule drug to reverse DEGs in AHL. Conclusions PPAR mediated signaling pathway may be an important mechanism for AHL. Downregulation of the above miRNAs and use of topiramate may be potential treatment strategies for ALH by upregulating PPARG

Study of Salicylic Acid Influence on Seedling Growth and Nitrogen Metabolism in Watermelon (Citrullus lanatus L.)

Salicylic acid is involved in the regulation of metabolic activity and defense mechanism in plants under various stress conditions. Present study was conducted to determine the effects of salicylic acid (10 to 500 μM) on seedling growth, development and nitrogen use efficiency in watermelon (Citrullus lanatus L.) plants with or without nitrogen nutrient. Salicylic acid increased contents of chlorophyll, total non-structural carbohydrate and total nitrogen, as well as nitrate assimilation through the induction of nitrate reductase (EC 1.6.6.1) activity in isolated watermelon cotyledons. Accumulation of salicylic acid was two-fold higher in cotyledons without nitrate supply in comparison to that with nitrate supply. Further 50 μM of SA induced enhancement in seed germination and growth characteristics. However higher salicylic acid concentrations inhibited above physiological characteristics. Results show that, field application of salicylic acid need optimum physiological concentration (e.g., 50 μM) to increase nitrogen use efficiency particularly during germination and seedling growth

The lncRNA-mediated ceRNA network of Altica viridicyanea is involved in the regulation of the Toll/Imd signaling pathway under antibiotic treatment

Long noncoding RNAs (lncRNAs) play significant roles in the regulation of mRNA expression or in shaping the competing endogenous RNA (ceRNA) network by targeting miRNA. The insect gut is one of the most important tissues due to direct contact with external pathogens and functions in the immune defense against pathogen infection through the innate immune system and symbionts, but there are limited observations on the role of the lncRNA-involved ceRNA network of the Toll/Imd pathway and correlation analysis between this network and bacterial microbiota in the Altica viridicyanea gut. In this research, we constructed and sequenced six RNA sequencing libraries using normal and antibiotic-reared samples, generating a total of 17,193 lncRNAs and 26,361 mRNAs from massive clean data by quality control and bioinformatic analysis. Furthermore, a set of 8,539 differentially expressed lncRNAs (DELs) and 13,263 differentially expressed mRNAs (DEMs), of which related to various immune signaling pathways, such as the Toll/Imd, JAK/STAT, NF-κB, and PI3K-Akt signaling pathways, were obtained between the two experimental groups in A. viridicyanea. In addition, numerous GO and KEGG enrichment analyses were used to annotate the DELs and their target genes. Moreover, six Toll family members and nineteen signal genes from the Toll/Imd signaling pathway were identified and characterized using online tools, and phylogenetic analyses of the above genes proved their classification. Next, a lncRNA-miRNA-mRNA network of the Toll/Imd pathway was built, and it contained different numbers of DEMs in this pathway and related DELs based on prediction and annotation. In addition, qRT-PCR validation and sequencing data were conducted to show the expression patterns of the above DELs and DEMs related to the Toll/Imd signaling pathway. Finally, the correlated investigations between DELs or DEMs of the Toll/Imd signaling pathway and most changes in the gut bacterial microbiota revealed significantly positive or negative relationships between them. The present findings provide essential evidence for innate immune ceRNAs in the beetle gut and uncover new potential relationships between innate immune pathways and the gut bacterial microbiota in insects

Distributional effects of vehicle tax in the framework of transportation externalities

Figure S2.The relationship between perivascular CD4 infiltration and 12 months follow-up DLCO (p = 0.134, r = −0.205). (PPT 43 kb

Molecular imaging research in atherosclerosis: A 23-year scientometric and visual analysis

Background: Cardiovascular and cerebrovascular diseases are major global health problems, and the main cause is atherosclerosis. Recently, molecular imaging has been widely employed in the diagnosis and therapeutic applications of a variety of diseases, including atherosclerosis. Substantive facts have announced that molecular imaging has broad prospects in the early diagnosis and targeted treatment of atherosclerosis.Objective: We conducted a scientometric analysis of the scientific publications over the past 23 years on molecular imaging research in atherosclerosis, so as to identify the key progress, hotspots, and emerging trends.Methods: Original research and reviews regarding molecular imaging in atherosclerosis were retrieved from the Web of Science Core Collection database. Microsoft Excel 2021 was used to analyze the main findings. CiteSpace, VOSviewer, and a scientometric online platform were used to perform visualization analysis of the co-citation of journals and references, co-occurrence of keywords, and collaboration between countries/regions, institutions, and authors.Results: A total of 1755 publications were finally included, which were published by 795 authors in 443 institutions from 59 countries/regions. The United States was the top country in terms of the number and centrality of publications in this domain, with 810 papers and a centrality of 0.38, and Harvard University published the largest number of articles (182). Fayad, ZA was the most productive author, with 73 papers, while LIBBY P had the most co-citations (493). CIRCULATION was the top co-cited journal with a frequency of 1,411, followed by ARTERIOSCL THROM VAS (1,128). The co-citation references analysis identified eight clusters with a well-structured network (Q = 0.6439) and highly convincing clustering (S = 0.8865). All the studies calculated by keyword co-occurrence were divided into five clusters: “nanoparticle,” “magnetic resonance imaging,” “inflammation,” “positron emission tomography,” and “ultrasonography”. Hot topics mainly focused on cardiovascular disease, contrast media, macrophage, vulnerable plaque, and microbubbles. Sodium fluoride ⁃PET, targeted drug delivery, OCT, photoacoustic imaging, ROS, and oxidative stress were identified as the potential trends.Conclusion: Molecular imaging research in atherosclerosis has attracted extensive attention in academia, while the challenges of clinical transformation faced in this field have been described in this review. The findings of the present research can inform funding agencies and researchers toward future directions