Problems in Setting Teaching Objectives and Countermeasures to Work out Teaching Objectives in College English Class

The professional competence of college English teachers in setting teaching goal has a direct impact on their teaching design level. Enhancing college teachers’ ability in setting classroom teaching goal facilitates the improvement of their design level. By combining with the teaching design scheme of normal class, this paper defines the meaning of College English classroom teaching objectives, analyzes the problems that the college English teachers have in setting teaching objectives, and puts forward corresponding countermeasures to develop the college English teachers’ capability of setting teaching objectives, which are expected to promote college English teachers’ ability to design the activities for their class

Controlling Lethal Browning of \u3cem\u3eHemarthria compressa\u3c/em\u3e Tissue Cultures

Hemarthria compressa is an important warm-season forage grass for use in Southwest China. However, due to poor seed set, it is propagated by vegetative cuttings of stolons, rhizomes, and nodal sections. The in vitro propagation of H. compressa is still faced with difficulties including blackening or browning of tissues prior to culturing due to the oxidation of phenolic compounds by polyphenolic oxidase enzyme present in excised tissue (Yang et al. 2008). The objectives of the study were to investigate possible means of successful initiation of cultures through elimination of phenolic browning

MiR-148a inhibits angiogenesis by targeting ERBB3.

MicroRNAs (miRNAs) play an important role in carcinogenesis in various solid cancers including breast cancer. Down-regulation of microRNA-148a (miR-148a) has been reported in certain cancer types. However, the biological role of miR-148a and its related targets in breast cancer are unknown yet. In this study, we showed that the level of miR-148a was lower in MCF7 cells than that in MCF10A cells. V-erb-b2 erythroblastic leukemia viral oncogene homolog 3 (ERBB3) is a direct target of miR-148a in human breast cancer cells through direct binding of miR-148a to ERBB3 3\u27-UTR region. Overexpression of miR-148a in MCF7 cells inhibited ERBB3 expression, blocked the downstream pathway activation including activation of AKT, ERK1/2, and p70S6K1, and decreased HIF-1α expression. Furthermore, forced expression of miR-148a attenuated tumor angiogenesis in vivo. Our results identify ERBB3 as a direct target of miR-148a, and provide direct evidence that miR-148a inhibits tumor angiogenesis through ERBB3 and its downstream signaling molecules. This information would be helpful for targeting the miR-148a/ERBB3 pathway for breast cancer prevention and treatment in the future

KERMIT: Knowledge Graph Completion of Enhanced Relation Modeling with Inverse Transformation

Knowledge graph completion is a task that revolves around filling in missing triples based on the information available in a knowledge graph. Among the current studies, text-based methods complete the task by utilizing textual descriptions of triples. However, this modeling approach may encounter limitations, particularly when the description fails to accurately and adequately express the intended meaning. To overcome these challenges, we propose the augmentation of data through two additional mechanisms. Firstly, we employ ChatGPT as an external knowledge base to generate coherent descriptions to bridge the semantic gap between the queries and answers. Secondly, we leverage inverse relations to create a symmetric graph, thereby creating extra labeling and providing supplementary information for link prediction. This approach offers additional insights into the relationships between entities. Through these efforts, we have observed significant improvements in knowledge graph completion, as these mechanisms enhance the richness and diversity of the available data, leading to more accurate results

Finetuning Large-Scale Pre-trained Language Models for Conversational Recommendation with Knowledge Graph

In this paper, we present a pre-trained language model (PLM) based framework called RID for conversational recommender system (CRS). RID finetunes the large-scale PLMs such as DialoGPT, together with a pre-trained Relational Graph Convolutional Network (RGCN) to encode the node representations of an item-oriented knowledge graph. The former aims to generate fluent and diverse dialogue responses based on the strong language generation ability of PLMs, while the latter is to facilitate the item recommendation by learning better node embeddings on the structural knowledge base. To unify two modules of dialogue generation and item recommendation into a PLMs-based framework, we expand the generation vocabulary of PLMs to include an extra item vocabulary, and introduces a vocabulary pointer to control when to recommend target items in the generation process. Extensive experiments on the benchmark dataset ReDial show RID significantly outperforms the state-of-the-art methods on both evaluations of dialogue and recommendation

Photometry of Variable Stars from THU-NAOC Transient Survey I: The First 2 Years

In this paper, we report the detections of stellar variabilities from the first 2-year observations of sky area of about 1300 square degrees from the Tsinghua University-NAOC Transient Survey (TNTS). A total of 1237 variable stars (including 299 new ones) were detected with brightness < 18.0 mag and magnitude variation >= 0.1 mag on a timescale from a few hours to few hundred days. Among such detections, we tentatively identified 661 RR Lyrae stars, 431 binaries, 72 Semiregular pulsators, 29 Mira stars, 11 slow irregular variables, 11 RS Canum Venaticorum stars, 7 Gamma Doradus stars, 5 long period variables, 3 W Virginis stars, 3 Delta Scuti stars, 2 Anomalous Cepheids, 1 Cepheid, and 1 nove-like star based on their time-series variability index Js and their phased diagrams. Moreover, we found that 14 RR Lyrae stars show the Blazhko effect and 67 contact eclipsing binaries exhibit the O'Connell effect. Since the period and amplitude of light variations of RR Lyrae variables depend on their chemical compositions, their photometric observations can be used to investigate distribution of metallicity along the direction perpendicular to the Galactic disk. We find that the metallicity of RR Lyrae stars shows large scatter at regions closer to the Galactic plane (e.g., -3.0 < [Fe/H] < 0) but tends to converge at [Fe/H]~ -1.7 at larger Galactic latitudes. This variation may be related to that the RRAB Lyrae stars in the Galactic halo come from globular clusters with different metallicity and vertical distances, i.e. OoI and OoII populations, favoring for the dual-halo model.Comment: 18 pages, 19 figures, published in AJ, 150, 10