The present paper investigates the intricacies of the Chinese English slang world with a focus on the use of the term "vibe." The goal here is to provide a look at how terms change and what their metonymic uses are in the approaches of translanguaging. Through the use of a corpus approach to this issue, the goal is to bring out the meanings and their cultural dimensions expressed in this slang word. Against this backdrop, this paper uses the rich linguistic resource from a translanguaging perspective to explore how users navigate the complexities implicated in online self-presentation with the use of such slang. Therefore, the paper scrutinizes the concept of metonymy in Chinese English slang in an attempt to unearth the symbolic meanings or connotations that have been buried in the meaning of the term "vibe." The result of this analysis is a contribution toward understanding the changing landscape of language and communication in this digital era using linguistic data from the Chinese English slang ecosystem.

The paper discusses the change of meaning and metonymium of Emo in Chinese cyber language here. Drawing on corpus-based analysis of emo posts published in the social media network Sina micro blog, we investigate how such aesthetics and sociocultural meanings attached to being “Emo”serves as a metonymy that enables diverse representations of affective states as well as situated emotion enactments. The findings suggest that the term “Emo”has been stretched as it is no longer confined to emotional events within or possibly just beyond emo, with a broader range of listings reflecting different emotions in various contexts. The metonymical nature of the use of “Emo”in Chinese reflects a broader cultural and social phenomenon occurring today in China -- particularly among some young net users. The research underscores the emotional expression pattern of Chinese netizens, which renders a good reference to comprehensively understand the evolution of language type in digital context.

The study looks at how joining live video chats with native English speakers on TikTok helps people who are learning English feel more ready to talk in English and less nervous about it. This study looks at EFL students who join TikTok live sessions. The researcher wants to understand how confident and nervous the students feel when they communicate. He uses qualitative research methods to do this. The study shows that using TikTok in a fun and calming way could help people learn a new language and reduce feelings of worry. This is helpful for teachers and language experts who want to use social media to help people learn languages.

The escalation of climate change and the increasing frequency of extreme weather events have amplified the importance of precise and timely lightning prediction. This predictive capability is pivotal for the preservation of life, protection of property, and maintenance of crucial infrastructure safety. Recently, the rapid advancement and successful application of data-driven deep learning across diverse sectors, particularly in computer vision and spatio-temporal data analysis, have opened up innovative avenues for enhancing both the accuracy and efficiency of lightning prediction. This article presents a comprehensive review of the broad spectrum of existing lightning prediction methodologies. Starting from traditional numerical forecasting techniques, we traverse the path to the most recent breakthroughs in deep learning research. We encapsulate these diverse methods, shedding light on their progression and summarizing their capabilities, while also predicting their future development trajectories. This exploration is designed to enhance our understanding of these methodologies, allowing us to better utilize their strengths, navigate their limitations, and potentially integrate these techniques to create novel and powerful lightning prediction tools. Through such endeavors, our aim is to bolster our preparedness against the growing unpredictability of our climate and ensure a proactive stance towards lightning prediction.

In order to explore the grassland ecosystem productivity and landscape ecological patterns of main pastoral grasslands in China, it provides a theoretical basis for the efficient implementation of ecological engineering and rational management of grassland resources in the region. This study analyzed the changes in grassland area, landscape index (LSI), and net primary productivity (NPP) in seven major pastoral areas in China in 1985, 1995, 2005, and 2015. Results showed that (1) the sizes of the grassland study area in 1985, 1995, 2005, and 2015 were 248.34, 243.93, 245.80, and 244.660 km2 respectively. (2) The dominance of grassland in the landscape pattern increased from 2005 to 2015 as compared with that in 1985–1995 and 1995–2005. The degrees of spatial heterogeneity were reduced. (3) The grassland NPP showed spatial and temporal differences. The average NPP of grassland increased by 21.30%, 16.47%, and 36.17% during 1985–1995, 2005–2015, and 1985–2015, respectively. From 1995 to 2005, the average NPP decreased by 5.05 gC/m2, which is equivalent to -3.61% of the average NPP in 1995. The total amount of grassland NPP in the study area was the greatest in 2015, showing increments of 36.37% and 16.61% compared with those in 1985 and 2005, respectively.

A Gem-quality rubies and sapphires are often commercially heat treated at about 800°C or higher temperatures to enhance their colour and clarity, and hence quality. For this study, selected corundum samples containing diaspore- and goethite inclusions were heated step-by-step to a maximum of 1000 °C with the aim to monitor the dehydration and phase transformation of these oxyhydroxides to corundum and hematite during heating. Based on our experiments and in agreement with literature, the dehydration of diaspore in corundum occurs between 525 to 550 °C, whereas goethite transforms to hematite already between 300 and 325 °C. As both, diaspore and goethite are common inclusions in rubies, sapphires, and other corundum varieties, these dehydration reactions and phase transformations can be considered important criteria to separate unheated stones from heated ones, specifically in cases in which other methods (e.g. microscopy, FTIR) are unsuccessful.

Objective: To investigate the protein expression levels of cyclin‑dependent kinase subunit 2 (CKS2) and cluster of differentiation (CD) 47 in gastric cancer (GC) and their clinical significances. Methods: A total of 126 GC patients who underwent radical resection were selected as study subjects. Additionally, 32 patients with benign gastric tumor, 42 patients with low-grade intraepithelial neoplasia (LGIEN), and 49 patients with high-grade intraepithelial neoplasia (HGIEN) who underwent surgery were selected as the control groups. Immunohistochemistry was used to detect the expression of CKS2 and CD47 in surgical specimens. We statistically analyzed the clinical significance of the expression of the two factors. Results: (1) The positivity rates for CKS2 in benign gastric tumor tissue, LGIEN tissue, HGIEN tissue, and GC tissue gradually increased, i.e., 6.3% (2/32), 30.9% (13/42), 38.8% (19/49), and 60.3% (76/126), respectively, and the positivity rates for CD47 were 18.8% (6/32), 38.1% (16/42), 46.9% (23/49), and 65.9% (83/126), respectively. (2) High expression of CKS2 and CD47 were associated with tumor diameter, Lauren classification, number of lymph node metastases, and TNM stage. In addition, the immunohistochemical scores for CKS2 and CD47 were positively correlated (r=0.625, P=0.000). (3) The median follow-up time of 126 patients was 46.5 months, and the overall survival rate was 40.5% (51/126). Survival analysis showed that compared with that in the CKS2 (-) group, the overall survival rate for patients in the CKS2 (+) group was significantly worse (25.0% vs 64.0%, 2=15.67, P=0.000) and that compared with the CD47 (-) group, the CD47 (+) group had significantly worse overall survival (30.1% vs 60.5%, 2=15.67, P=0.000). (4) The overall survival rates of CKS2(+)CD47(+) group, CKS2(+)CD47(-) group, CKS2(-)CD47(+) group, and CKS2 (-)CD47 (-) group were 20.0%(13/65), 58.3%(7/12), 57.1%(8/14), 65.7% (23/35), respectively, the prognosis of patients in CKS2(+)CD47(+) group was significantly poor. Conclusion: High expression levels of CKS2 and CD47 were closely related to the occurrence of GC and can be used as independent risk factors to assess the prognosis of patients.

Cytosine (C) to uracil (U) RNA editing is one of the most important post-transcriptional processes, however exploring C-to-U editing events efficiently within the crop mitochondrial genome remains a challenge. An improving predictive RNA editor for crop mitochondrial genomes, iPReditor-CMG, was proposed, which was based on SVM, three common crop mitochondrial genomes and self-sequenced tobacco mitochondrial ATPase. After multi-combination feature extracting, high-dimension feature screening and multi-test independent predicting, the results showed that the average accuracy of intraspecific prediction was 0.85, and the highest value even up to 0.91, which outperformed the previous reference models. While the prediction accuracies were 0.78 between dicotyledons and no more than 0.56 between dicotyledons and monocotyledons, implying a possible similarity in C-to-U editing mechanisms among close relatives. The best model was finally identified with an independent test accuracy of 0.91 and an area under the curve of 0.88, and further suggested that five unreported feature sequences TGACA, ACAAC, GTAGA, CCGTT and TAACA were closely associated with the editing phenomenon. Multiple evaluation findings supported that the iPReditor-CMG could be effectively applied to predict crop mitochondrial editing sites, which may contribute to insight into their recognition mechanisms and even other post-transcriptional events in crop mitochondria.

After prolonged development, most domestic and international oilfields have entered a late stage of high water cut and high recovery, with a comprehensive water cut reaching up to 90%. Carbon-oxygen ratio logging can directly distinguish oil layers from water layers with low salinity, unknown salinity, or significantly varying salinity in cased wells. This makes it highly valuable for detecting oil and gas layers and locating and monitoring oil-water interfaces. It is currently one of the most effective methods for determining residual oil saturation in cased wells. This paper is based on two carbon-oxygen ratio spectrum interpretation models (the fan and ratio chart methods). It compares and analyzes these two methods and optimizes the interpretation parameters in the ratio chart model using an improved genetic algorithm. The results are effectively integrated with reservoir and conventional logging interpretation results, reducing the impact of lithology and physical properties on measurement values. This provides a theoretical foundation for improving the interpretation capability and accuracy of carbon-oxygen ratio logging, allowing for quicker and more accurate identification of water-flooded layers. This technical support aids in monitoring oil-water dynamics, determining water-flooded layers, and enhancing production potential during oilfield development.