Reviewerly/exHarmony huggingface dataset:
“I Keep Forgetting You’re Still Alive”: Unmasking Impoliteness in the Xsphere

Pragmatic competence entails awareness-raising of impoliteness. This paper delves into the pragmatics of impoliteness in online communication, focusing on X (Twitter) interactions, with a particular emphasis on 126 replies to Elon Musk's controversial tweet. Utilizing Culpeper's (2011) model of impoliteness formulae and implicational impoliteness, the study analyzes responses to this tweet, exploring the multifaceted dimensions of impoliteness. The research also investigates the moral order expectations expressed by the repliers, shedding light on the factors influencing their reactions and responses. By employing qualitative content analysis and thematic analysis, the study reveals the nuanced forms of impoliteness and the underlying moral order themes inherent in these online exchanges. Responsible wealth behavior, appropriate and non-offensive language, respect and decency, refraining from political narratives, engaging in social responsibility, and showingtransparency, accountability, and ethics were the identified moral order expectations. The findings underscore the relevance of examining impoliteness in the digital age, where public figures’ tweets can have far-reaching consequences and provoke diverse reactions from the online community. This research contributes to a deeper understanding of impoliteness in online discourse and its implications for social media interactions by language learners, which are currently lacking in language classrooms.
Interpretation as the Language of Modern Artistic Culture

The article explores the actual aspects of the interpretations of works of art from the point of view of using them as a source of inspiration to create a perfect new work of art or object. Based on the methods and analysis of the study, the authors attempted a systematic analysis of the phenomenon of interpretation of works of art in modern culture. The article considers such concepts as “interpretation”, “artistic image”, “interpretative activity” and identifies the features of interpretation methods. Two types of interpretation are described. The forms of interpretation of the main one are revealed, among which the authors call the interpretation of works of art by means of art of another type of art. Spiritual culture uses the language of symbols, and the language of artistic images is inherent in art. On the one hand, the interpretation of works of art depends on the symbolic language of a particular culture, on the other hand, they reflect the subjective perception of both the author of the work and the viewer. In general, the article contains a comprehensive study of the interpretation of works of art as a phenomenon of artistic culture, examines the features of the method of interpretation, its functions and the de-gree of influence on the formation of the modern language of art. The issues of the significance of the phe-nomenon of interpretation for modern culture and art are considered.
Introduction to Web APIs

Writing JavaScript in the browser means that a lot of what we can do is limited by what the browser allows us to do. While core JavaScript functionality lets us create functions, math, and variables, what if, for example, we want to use the operating system’s notification system from our code? Or store something locally on the user’s computer? For each of these, JavaScript in the browser implements various Web APIs to allow programmers to access this functionality.
Types

We’ve already talked about how JavaScript is weakly and dynamically typed – which means we do not explicitly declare the types of the data we define. That does not make types in JavaScript any more straightforward than other languages, though, and in some ways, it makes things more complicated! Types are where some of the more unusual quirks of JavaScript come to roost, so getting a good grasp on them can be tricky.
Maps and Sets

While objects and arrays are the most common way of storing data in JavaScript, they do have some limitations. For example, neither objects nor arrays have the ability to create a unique list without duplicates. Similarly, objects cannot contain keys that are not strings or symbols. To overcome these challenges and more, two additional special types of objects exist known as maps and sets. Both of these have unique functionality, which makes them well-suited to certain tasks. In this chapter, we’ll be diving into both of these objects and when to use them.
Continuous Sign Language Recognition Using Combination of Two Stream 3DCNN and SubUNet

Research on sign language recognition using deep learning has been carried out by many researchers in the field of computer science but there are still obstacles in achieving the expected level of accuracy. Not a few researchers who want to do research for Continuous Sign Language Recognition but are trapped into research for Isolated Sign Language Recognition. The purpose of this study was to find the best method for performing Continuous Sign Language Recognition using Deep Learning. The 2014 RWTH-PHOENIX-Weather dataset was used in this study. The dataset was obtained from a literature study conducted to find datasets that are commonly used in Continuous Sign Language Recognition research. The dataset is used to develop the proposed method. The combination of 3DCNN, LSTM and CTC models is used to form part of the proposed method architecture. The collected dataset is also converted into an Optical Flow frame sequence to be used as Two Stream input along with the original RGB frame sequence. Word Error Rate on the prediction results is used to review the performance of the developed method. Through this research, the best achieved Word Error Rate is 94.1% using the C3D BLSTM CTC model with spatio stream input.
Functions and Classes

Functions and classes are what we use to wrap certain pieces of functionality into reusable blocks. When JavaScript was originally released, it only had functions and used prototypes for inheritance. We covered this type of inheritance when we looked at objects.
Implementation of Design Thinking Method in UI/UX Redesign of Public Complaint Application (Case Study: Go Siaga App)

Go Siaga App is a mobile-based application by Tangerang Sub-district Police Office that provides special community services for the Tangerang sub-district community which provides features in the form of reports of disturbances in public security and reports of loss or damage. Since it is a new application released in March 2021 on Google Playstore, there are several things that need to be considered to maintain the usability of the application. This research aims to redesign the user interface and user experience (UI/UX) of the Go Siaga application using Design Thinking Method in the design process. Some of the supporting aspects for testing the user satisfaction such as effectiveness, efficiency, usefulness, satisfaction, and learnability are met in the usability testing. The results showed that the percentage of all the aspects in usability from the redesigned version were all higher than the current one with 80% of effectiveness, 80% of efficiency, 80% of usefulness, 86.67% of satisfaction, and 73.33% of learnability. Therefore, based on the research results, the redesign of Go Siaga is more effective, more efficient, more useful, more satisfying, and also easy to learn.
Енергія життя після здобуття перемоги &amp; Впровадження синергетичних підходів у процес навчання зростаючого покоління та діяльність дорослих

I In intelligence, attention is emphasized on synergistic practices, the use of which is currently expedient. After winning the Victory, they will also facilitate a practice-oriented familiarization with the educational material. At the same time, one of the prominent places is focusing attention on the emotional state of each individual. The author analyzed creative methods in the context of the representation of educational cases ("My caricature" / "Emotional caricature" / "Emoji", "Viber task" / "Viber correspondence" / "Educational correspondence"). Of great importance is the production of opinions about project-based learning technologies. The challenge and skill of time is highlighted – the ability to think critically and express one's own statements (narratives of axiological competence). The study focuses on binary/controversial issues.
Impact of Artificial Intelligence on Mammography Interpretation by Breast Radiologists, Non-Breast Radiologists, and Senior Residents

Background: Artificial intelligence (AI) is recognized to have tremendous potential to revolutionize breast cancer management through mammography. However, the extent of its impact on radiologists with different levels of experience remains largely unexplored. Therefore, this study aimed to comprehensively show how AI could assist radiologists of varying expertise including breast and non-breast radiologists, as well as senior residents, in performing mammogram interpretation.Methods: This retrospective study analyzed eligible mammograms from Cipto Mangunkusumo Hospital between January 2017 and March 2021. Mammographic readings were conducted independently by two breast radiologists, two from other subspecialties, and three senior residents, all blinded to clinical information. AI standalone performance, as well as radiologists with and without AI assistance, was measured. Results: The results showed that a total of 886 eligible mammograms were analyzed. AI standalone performance, assessed using ROC curve analysis, yielded an AUC of 0.946 (95% CI, 0.925–0.967) with sensitivity and specificity of 90.1% and 93.6%, respectively. AI assistance significantly improved the sensitivity and specificity of all radiologists, regardless of experience level, with a median increase of 19.4% (IQR, 10.4–33.5%) and 12.1% (IQR, 5.2–16.2%), respectively. Moreover, there was a trend toward a higher increase with AI assistance in dense compared to fatty breasts.Conclusions: AI proved to be a highly effective diagnostic supplement for radiologists across varying experience levels, specifically in non-breast radiologists, offering the potential to add even greater value in cases of dense breast tissue. The results were derived from a national referral tertiary hospital that generally received many breast cancer cases referred from other hospitals for further treatment. Therefore, further studies incorporating different levels of hospitals were needed.
Paradoxical inferences, biconditional interpretation, and exclusivity

Two inferences correct in classical logic are controversial in cognitive science. The reason is that people do not always deem them as valid inferences. One of them is the rule to introduce a conditional. The other one is the rule to introduce a disjunction. The theory of mental models has an account for them. Their conclusions refer to models, and, in both cases, one of those models is inconsistent with the premise. When semantics modulates and removes the incoherent model, the inferences are accepted as correct. The present paper tries to describe those phenomena within the framework of first-order predicate logic. It proposes that the rule to introduce a conditional is not admitted when the conclusion is not a conditional, but a biconditional. It also claims that the rule to introduce a disjunction is not accepted when the disjunction is exclusive.
How much Romanian does Google Translate know?

To compensate, even if on a small scale, for the scarcity of investigations of English-into-Romanian machine translations from a corpus-based genre-specific perspective, this case study concerns the quality of such translation outcomes in the particular case of two different, but closely related, text genres – everyday and newspaper/ news releases language, that have been translated with the help of Google Translate. The paper starts from Keshavarz’s (1999) very general model of error analysis to create a linguistic error profile in the two genres taken into consideration. The errors identified and discussed are illustrated with small-scale corpus examples. Since they reflect the capabilities of the Google translation platform, the findings of this paper may be relevant for its developers to get a clearer picture of its strengths and limitations and suggest ways of improving it so that it can ultimately provide higher quality translations. It may also contribute to raising translators’ attention to which areas are potentially problematic when they work, in the post-editing stage, with the English-Romanian language pair, with the particular text genres considered here.
Diagnostic Accuracy of Fine Needle Aspiration Cytology, Triple Test and Tru-cut Biopsy in the Detection of Breast Lesion

Background: The majority of breast illnesses manifest as a palpable mass. The vast majority of breast lesions are not malignant, and the vast majority of benign lesions do not progress to cancer; however, the accuracy of diagnosis can be improved by a combination of preoperative tests such as physical examination, mammography, fine-needle aspiration cytology (FNAC), and Trucut needle biopsy (TCNB) or core needle biopsy (CNB). FNAC has gained in popularity and is now the primary treatment performed after a history and clinical examination to diagnose solid and cystic breast masses. This study was designed to assess the accuracy of FNAC in comparison to Triple Test and TCNB for the diagnosis of breast masses. Methodology: From January 2023 through May 2023, this study was conducted in the Tezpur Medical College and Hospital. The research included all female patients over the age of 20 with clinically palpable lumps. Palpable breast lumps need a complete clinical breast examination, imaging, and tissue sample for a clear diagnosis to rule out cancer.The Ultrasonography/Mammography, FNAC and tru-cut biopsy procedures were performed concurrently in the same region, and the results were compared to final histopathology as the gold standard. Result: The majority of the patients in the study were in age group of &gt; 60 years. In our study Left breast was involved in 41 (58.5%) patients and right breast in 29 (41.4%) patients. The most frequent site involved was upper outer quadrant in 38 (54.2%). The overall sensitivity of FNAC in our study was 93.75%, tru-cut biopsy is 100% and that of triple test is 100% and specificity for malignancy was 91.6%, 93.6 and 95.6% for FNAC, tru-cut biopsy and triple test respectively. Conclusion: All three techniques have advantages and disadvantages. Core Needle Biopsy cannot be used in place of FNAC, and it is not required to identify all breast lesions. It can be utilised as an adjuvant in circumstances when cytology is definitive and biomarker tests are required. triple test and trucut were more accurate than FNAC in our testing.Trucut biopsy was able to provide histological diagnosis, and the findings were 100% consistent with the final histopathology report.&#x0D;
A Computational Linguistic Approach to English Lexicography

Focusing on computational linguistic approaches to English linguistics, this research explores how computational methods can be applied to dissect, understand and utilise the English language. We first looked at text analysis and processing, delving into natural language processing techniques such as text categorisation, sentiment analysis and machine translation, and their application to social media and automated text processing. In the area of lexicography and semantics, we explored how techniques such as distributed word vectors, semantic role labelling and sentiment analysis can deepen our understanding of vocabulary and semantics. We highlight the importance of these techniques in natural language processing tasks such as sentiment analysis and information retrieval. In addition, we focus on cross-language comparative and multilingual research, emphasising how big data and cross-language comparative research can reveal similarities and differences between languages and their implications for global linguistics. Finally, we explore corpus linguistics and big data analytics, highlighting the richness of linguistic data and tools they provide for linguistic research. Overall, this study highlights the importance of computational linguistic approaches to English linguistics and how they have transformed the way linguistics is studied and language technology has evolved. Future research trends will continue to drive the further development of computational linguistics methods, leading to a closer integration of linguistics with big data analytics and computational methods, creating more opportunities for the future of the field of linguistics.
A Study on Interactive Proteomic Data Clustering: A Comparison between Self-Organizing Map and Neural Gas

The neural network algorithms Self-Organizing Map (SOM) and Neural Gas (NG) use unsupervised competitive learning. These methods have the critical virtue of preserving the topological structure of the data, which means that data that are close in the input distribution are mapped to neighboring positions in the network or output. This characteristic makes them intriguing to investigate in terms of data clustering. A crucial characteristic analyzing vast amounts of data manually can be challenging and time-consuming. As a result, technologies for analyzing and visualizing massive multidimensional data sets are required. We introduce a method for comparing and visualizing the SOM and NG in this chapter. We describe these algorithms first, and then we make a pictorial comparison between them. The protein mass spectrometry data clustering is then interpreted using these visualization approaches.
Representation of Voice: A Narrative Inquiry of Indonesian EFL Learners in Poetry Writing Experience

This study was conducted to identify the students' voices and the challenges in writing the poetry from the narratives behind their poetry writing. Since the primary source of the study data was the students' narratives, this study was conducted by following the narrative inquiry method. Fifteen EFL learners who took poetry classes were taken as the study samples. The study data were collected from the students' poems, journals, and interviews. Those three different methods were applied to ensure the data validity and reliability. To identify the voices, the researchers interpreted the voices from the dictions that the students chose to write the poetry. Then, the researchers confirmed the voice's interpretation by comparing them with the students' journals and interview results. To identify the challenges, the researchers qualitatively analyzed the students' journals and the interview results using cross-case analysis. This study found that behind the narratives of learners, there are voices that have been unheard for years, the unspoken words that are kept for themselves. The voices are trauma, anxiety, and hope. The trauma includes the trauma of paranoia, bullying, and past life, and the anxiety includes anxiety of the past, present, and future. Meanwhile, the voice of hope covers optimism and enthusiasm. Besides, this study also identified that the students found some challenges in writing poetry, and they overcame those challenges by practicing more, reading more literature, finding new words, accepting more information, being more flexible, and being open to new contexts.
Could Android Learning Media Based on Visual Representation Improve Students’ Representation Abilities? : Reconsidered from a Student Teacher Perspective

This study aims to describe visual representation-based android learning media to improve students' representation abilities based on the views of teachers and students. This research involved 39 science teachers and 181 junior high school students in Lampung province. The method used in this study is a mixed method with an explanatory sequential design in order to obtain quantitative and qualitative data through questionnaires and interviews. The results of the study show that teachers and students have a positive perception of the development of visual representation-based android learning media. This study found the fact that there were several factors that caused teachers not to pay attention to students' representation abilities. The teacher believes that the use of learning media can train students' representation abilities and have an impact on increasing student representation abilities.
Cash Recycling Machine (CRM) &amp; its impact on customer satisfaction: A study on UCB PLC

Purpose: The primary purpose of this research is to explore Cash Recycling Machine (CRM) systems and determine customer satisfaction after using CRM services. Research Methodology: To collect data for this research, a questionnaire was created and a survey was conducted to assess user contentment with the Cash Recycling Machine (CRM) of the United Commercial Bank (UCB) PLC. During the investigation of the Cash Recycling Machine (CRM) system, a secondary data source was utilized. Results: An analysis indicates that Almost 97% of respondents regularly utilized CRM services while continuing to depend on conventional banking methods. Nevertheless, a significant proportion of participants (over 20%) frequently employed CRM systems. Specifically, 47% utilize these systems four to seven times each month. This study demonstrates that banks are implementing novel services to entice a larger clientele, while consumers are allowed to utilize the banks' fundamental services, such as making deposits and withdrawals. Limitations: Banks are restricted from accessing crucial information owing to data privacy concerns. Furthermore, the use of secondary data may not adequately reflect the perspective of UCB PLC, owing to scalability issues. Ultimately, the limited sample size is a result of clients' strong unwillingness to allocate time for research. Contribution: This study and its implications can be used for additional research in emerging economies to comprehensively examine the adoption of new technologies in the banking industry. Novelty: The core reaction of consumers to an emerging technology for rapid economic growth.
Investigating the effects of emotion regulation and creativity on Chinese EFL teachers’ burnout in online classes

The spread of the Coronavirus and the emergence of new technology have led to an abrupt shift in education and changed the mode of instruction. The new mode of instruction has faced teachers with new challenges, which may enhance the rate of job burnout. To avoid this phenomenon, the causes of teacher burnout in online classes should be widely identified. With this in mind, this inquiry investigated the effects of emotion regulation and creativity on EFL teachers’ burnout in online classes. We hypothesized that teachers’ creativity and ability to regulate their emotions can minimize the rate of burnout. To test this hypothesis, 329 Chinese EFL teachers were invited to respond to three validated questionnaires. The collected data were analysed through Structural Equation Modelling (SEM). The study outcomes revealed a significant correlation between Chinese EFL teachers’ creativity, emotion regulation, and burnout. The results also showed that creativity and emotion regulation can make a significant change in the rate of teacher burnout. The present results are hoped to be illuminating for all online English teachers. FUNDING INFORMATION. This work was supported by Ningbo University Teaching Research Project “Research on teaching strategy of ideological and political theory course based on acceptable psychology of college students” (JYXMXZD2023040).