Reviewerly/exHarmony huggingface dataset:
Research on the Application of CBI Theme-Based Model to College English Teaching

In an age when the construction of new liberal arts is given great emphasis to, CBI teaching concept is in line with the need to cultivate internationalized talents with systematic knowledge and practical ability.It provides a new perspective in solving the problem of low level of subject consciousness, low interest in learning and weakness in practical language use in college English teaching since it enables students to acquire knowledge and skills of the language through exploring contents of of different subjects or themes.Based on the 6-T's method, this paper constructs a framework of CBI theme-based model for college English teaching, analyzes the application and effects of this model in teaching practice, and explores the direction of future research and practice.
Promoting a teaching platform for "Traditional Skills + Virtual Reality Technology”

VR (Virtual reality) technology has been applied to teaching/learning in many contexts. Our interest focuses on the application of VR in design studies, allowing students to experience craft, (technical aspects, tools and methods), providing advanced means and methods for learning, and enabling the recovery and renewal of crafting and making. VR technology is used to simulate the space environment and technological process in the production process. Students will be brought into the simulated environment through different sensing devices, so that they can operate the objects in the virtual world by themselves, so as to enhance their feelings, deepen their understanding of the traditional technology, and better learn and create. Through survey sections we can achieve an understanding of students experience of VR for craft, and the enhancement of the teaching effect in a product design course. Finally, we can increase the inheritance and development of traditional skills among young people and in the future.
Label Errors in BANKING77

We investigate potential label errors present in the popular BANKING77 dataset and the associated negative impacts on intent classification methods.Motivated by our own negative results when constructing an intent classifier, we applied two automated approaches to identify potential label errors in the dataset.We found that over 1,400 (14%) of the 10,003 training utterances may have been incorrectly labelled.In a simple experiment, we found that by removing the utterances with potential errors, our intent classifier saw an increase of 4.5% and 8% for the F1-Score and Adjusted Rand Index, respectively, in supervised and unsupervised classification.This paper serves as a warning of the potential of noisy labels in popular NLP datasets.Further study is needed to fully identify the breadth and depth of label errors in BANKING77 and other datasets.
Teaching English Through Literature In Post-Pandemic Era: A Case At An Indonesian Islamic Higher Institution

There has been little discussion about the impact of the pandemic era on the use of literature in English language teaching.This article offers an overview of the use literature to teach English in an Indonesian Islamic higher institution within the postpandemic era with the focus on the multimodality of literary texts and sorogan teaching method.This article is underpinned by and is aimed at exploring two arguments.First, the pandemic era has massively encouraged English teachers to utilize technology in their teaching in that the printed version of literary texts should become multimodal.Second, literary texts should be presented as an accessible and engaging language input.Following a qualitative analysis technique, this case study involved 37 students of State Islamic Institute of (IAIN) Metro, Indonesia.The research data were drawn from a questionnaire, the students' comments on the channels, and the students" self-generated channels.The findings of the research show that: (1) multimodality in the form of sound, videos, and music should be taken into account when utilizing literary text to teach English in the post-pandemic era, and (2) the literary texts should be appropriately adapted to reduce the language complexity either by using the students" national language or by implementing such a teaching method as sorogan which is familiar to Islamic institutional context.Multimodality, familiarity, and simplicity should become the characteristics of the literature used to teach English at Indonesian Islamic universities.
Zones in the pyrite-sphalerite association of sulfide deposits Vesennee and Tash-Yar (South Ural)

Based on the example of the Tash-Yar and Vesennee deposits, a fundamentally new approach to the problem of diffusion of elements at the boundaries of ore minerals of the pyrite-sphalerite association is considered in the article, which makes it possible to calculate the temperatures and duration of transformations of ore objects, the impact of intrusive bodies (Osennee, Avangard and many others), or experienced deep regional metamorphism (deposits of Karelia, the Baikal region, the Yenisei ridge).
On the Robustness of Offensive Language Classifiers

Social media platforms are deploying machine learning based offensive language classification systems to combat hateful, racist, and other forms of offensive speech at scale.However, despite their real-world deployment, we do not yet comprehensively understand the extent to which offensive language classifiers are robust against adversarial attacks.Prior work in this space is limited to studying robustness of offensive language classifiers against primitive attacks such as misspellings and extraneous spaces.To address this gap, we systematically analyze the robustness of state-of-theart offensive language classifiers against more crafty adversarial attacks that leverage greedyand attention-based word selection and contextaware embeddings for word replacement.Our results on multiple datasets show that these crafty adversarial attacks can degrade the accuracy of offensive language classifiers by more than 50% while also being able to preserve the readability and meaning of the modified text.
Dwell-Free Typing Using an EOG Based Virtual Keyboard

This work presents the development of an asynchronous dwell-free virtual keyboard application which can be operated using electrooculographic (EOG) data. Unlike other EOG based eye typing applications, the developed system avoids the use of dwell-times and relieves the user from the need to perform repetitive and unnatural eye movements to move a cursor towards the desired letter or the need to perform voluntary blinks to interact with the application. Instead, the proposed application requires the user to simply glance through the vicinity of the desired letters, as one would swipe through letters when typing on a touchscreen device, after which a set of word predictions are displayed for the user to select. The proposed application obtained a top five rate of 76.00 ± 12.61% using EOG data which is comparable to the top five rate of 79.00 ± 13.37% obtained when operating the application using a vision-based eye gaze tracker.
Cross-lingual Semantic Role Labelling with the ValPaL Database Knowledge

Cross-lingual Transfer Learning typically involves training a model on a high-resource source language and applying it to a lowresource target language.In this work we introduce a lexical database called Valency Patterns Leipzig (ValPal) which provides the argument pattern information about various verb-forms in multiple languages including low-resource languages.We also provide a framework to integrate the ValPal database knowledge into the state-of-the-art LSTM based model for cross-lingual semantic role labelling.Experimental results show that integrating such knowledge resulted in am improvement in performance of the model on all the target languages on which it is evaluated.
COVID-19: Challenges and Opportunities in the Online University Education

The COVID-19 pandemic had a very severe impact on the education both in schools and in universities.In the span of several weeks, educators around the world had to transform completely the teaching method and students had to adapt to the new form of learning.The following article reviews the opinions of university students based on three different studies -one before the pandemic and the distance learning, one in the middle of it and one in the end of the distance learning.The goal is to see how students' thinking and perceptions of online learning has changed over the last three years as a result of different conditions.
AN EXPERIENCE OF CREATING PREDICTIVE-METALLOGENIC MAPS BASED ON OPEN GEOLOGICAL AND GEOPHYSICAL DATA IN GIS ENVIRONMENT

The issues of using GIS tools for the preparation and design of predictive-metallogenic maps in ac-cordance with the current normative documents and the experience of domestic geological cartography are considered. Predictive and mineralogical maps of scale 1 : 1 000 000 and 1 : 200 000 for the Baikal-Amur group of metallogenic provinces were made in the ArcGIS environment. Open and stock geological and geophysical data were used as the main sources of information – unified digital models of the State Geological Maps at a scale of 1 : 1 000 000 (third generation) and 1 : 200 000 (second generation), digital maps of the anomalous magnetic field and the field of gravity in the Bouguer re-duction at a scale of 1 : 2 500 000, objects of geological and geophysical study and others. The fea-tures of these data use in the formation of mathematical, topographic and thematic basis of maps are noted. Recommendations on application of ArcGIS tools for cartographic works are given, examples of prepared predictive-metallogenic maps sheets are presented.
Measuring emotion, interaction, and cultural outcomes after a VR game: The case of São Tomé.

The development of strategies based on the preservation, innovation, and dissemination of cultural aspects of the São Tomé and Príncipe (STP), represents an essential condition for the improvement and dynamization of the culture and creativity sector. Nowadays, due to low cost and technological advances, virtual Reality (VR) devices can provide an immersive experience to share cultural aspects. The goal of this study is to analyze (1) if the memory of the cultural and natural aspects remains after the end of VR experience, (2) the emotional reaction after the experience, and (3) interaction problems reported by participants. The number of participants in this study was 10. To measure what remains related to cultural and natural aspects of STP, the Think-aloud method was used to collect information. This protocol was applied after the participant finished the VR experience (retrospective think-aloud). This allowed knowing what participants value at a specific moment. Questions related to cultural aspects were directly asked to participants through a Questionnaire with questions about paintings/artists and creole language (QPCL) After three weeks, the QPCL was applied again, to verify if the cultural/natural aspect was recalled after this period. We also apply the Self-Assessment Manikin (SAM) tool to analyze the emotional reaction. Regarding the results using think-aloud, we structure the answers into 4 categories: (1) Interaction in VR; (2) Culture; (3) Nature, and (4) The desire to be there. Concerning Interaction in VR, the majority do not report any interaction problems (7 participants). Regarding the cultural and natural aspects, the natural aspect related to the green environment was the most reported aspect (5 participants). The desire to be there, was reported by 4 participants. We did not ask if they want to visit São Tomé or any other aspect categorized (think-aloud), they just verbalized what they were thinking at the time (after finishing the VR experience). The data collected using SAM reveals that the pleasure was positive, and arousal was considerable (Pleasure Average = 7.4; Pleasure Standard Deviation = 1.3 / Arousal average = 6.8; Arousal Standard Deviation = 2.1). Three weeks later, we applied the SAM and QPCL questionnaire again, and the results were still close to the values initially reported. In conclusion, the think-aloud and QPCL methods were helpful tools to understand what participants most value during a VR game experience (related to cultural, natural, and interaction aspects), and the results related to emotional reaction (SAM questionnaire), show that the experience provided a high level of pleasure.
Design and Implementation of Job Recommendation Application ‘Jobs-3600’ for Job Seekers and Employers using Flutter

Top companies are recruiting people online and during and after covid, they work from home. Most of the recruiting companies select people by conducting online test and interviews. Likewise, job seekers also choose jobs online through online portals. Job recruitments nowadays become a very important and fundamental process for industries like Information Technology, Government, and private sectors. The web-based applications caused a substantial impact on the recruitment process. The implementation of online recruiting platforms has become a primary recruitment channel in most companies. While companies established job positions on these portals, job-seeker uses them to publish their profiles. Online recruitment platforms accomplished clear advantages for both employers and job-seekers by reducing the recruitment time and advertisement cost. There are certain recommendation systems available on the internet to support the users in searching for their requirements that match their preferences. A wide range of smart phone applications is popular to deal with all sorts of user's requirements. To improve the e-recruiting functionality, many job recommendation systems have been proposed. This paper analyzes and develop a job application process and related issues for building personalized recommendation systems for job-seekers by an application called ‘JOBS-3600.
The Best of both Worlds: Dual Channel Language modeling for Hope Speech Detection in low-resourced Kannada

In recent years, various methods have been developed to control the spread of negativity by removing profane, aggressive, and offensive comments from social media platforms.There is, however, a scarcity of research focusing on embracing positivity and reinforcing supportive and reassuring content in online forums.As a result, we concentrate our research on developing systems to detect hope speech in code-mixed Kannada.As a result, we present DC-LM, a dual-channel language model that sees hope speech by using the English translations of the code-mixed dataset for additional training.The approach is jointly modelled on both English and code-mixed Kannada to enable effective cross-lingual transfer between the languages.With a weighted F1-score of 0.756, the method outperforms other models.We aim to initiate research in Kannada while encouraging researchers to take a pragmatic approach to inspire positive and supportive online content.
Improving students’ reading comprehension in narrative text through schema activation strategy at third grade at SMPN 1 Bukit Kemuning Lampung Utara

The objectives of this research are to investigate whether there is a significant difference in the students’ reading comprehension achievement before and after the implementation of schemata activation strategy and which aspect that improves the most in reading comprehension after being taught schema activation strategy. This research was conducted at the third-grade students of SMPN 1 Bukit Kemuning in the academic year 2020/2021. The researcher took class IX. The instrument used to get the data in this research was a reading comprehension test. Reading tests in the forms of pre-test and post-test were done to collect the data. Then, the t-test was used to test the hypothesis. The result of the hypothesis test proves that schemata activation gives a positive effect on students’ reading comprehension achievement. In addition, determining reference was the aspect of reading skills which improved the most after being taught by Schema Activation Strategy. This evidence proved that teaching reading using Schema Activation Strategy facilities more in determining reference. In conclusion, this study suggests that Schema Activation Strategy can be used to improve students’ reading comprehension.
Особливості дистанційної освіти у вищій школі ХХІ століття (за матеріалами дистанційного курсу «Теорія і практика перекладу»)

Distance education technologies are positioned as a natural stage in the evolution of the traditional education system from a regular audience to a virtual one. Improving the educational process in higher education institutions is impossible without the use of complex computer software solutions, so called learning management systems.
Getting Personal with Algorithms

ANONYMOUS PERSONALIZATIONIf the web is a communication medium, today it is not a mass medium in the traditional sense.Broadcast mass media communication is standardized (providing the same content for each user) and generalized (addressing everyone).What appears on the screen of our computer or smartphone, or what our personal assistant tells us, instead, is different from what anyone else receives.We are addressed by name and informed about restaurants and happenings in our surroundings, or about sporting events that may interest us; we are notified of our appointments, of traffic conditions on the routes we take, or of birthdays of friends and relatives; we receive music playlists and movie suggestions matching our tastes.We come to know what happens in the world through the tailored format of our news feed, and when we look for information, Google presents us with results especially selected for us-as well as with a multitude of commercial ads that are supposed to specifically meet our wishes.Whereas mass media communication is anonymous, communications on the web are increasingly personalized.Being personally addressed by machines, however, is different from being personally addressed by actual persons.Algorithms do not know us nor do they understand us, yet profiling techniques make it possible to provide each
WeaNF”:" Weak Supervision with Normalizing Flows

A popular approach to decrease the need for costly manual annotation of large data sets is weak supervision, which introduces problems of noisy labels, coverage and bias.Methods for overcoming these problems have either relied on discriminative models, trained with cost functions specific to weak supervision, and more recently, generative models, trying to model the output of the automatic annotation process.In this work, we explore a novel direction of generative modeling for weak supervision: Instead of modeling the output of the annotation process (the labeling function matches), we generatively model the input-side data distributions (the feature space) covered by labeling functions.Specifically, we estimate a density for each weak labeling source, or labeling function, by using normalizing flows.An integral part of our method is the flow-based modeling of multiple simultaneously matching labeling functions, and therefore phenomena such as labeling function overlap and correlations are captured.We analyze the effectiveness and modeling capabilities on various commonly used weak supervision data sets, and show that weakly supervised normalizing flows compare favorably to standard weak supervision baselines.
Dor: Detecting Deepfake Videos Using the Dissonance between Intra- and Inter-Frame Maps

With the development of generative adversarial networks (GANs) and their variants, they have been successfully applied to the synthesis of facial images. However, the spread of fake information has posed potential security concerns for humans. In particular, the detection of deepfake videos still faces severe challenges. This study argues that if a video is represented by different modalities, manipulating a modality alone, which is a common way to deepfake videos, will lead to a certain dissonance between modalities. Consequently, a novel dual-network scheme referred to as DOR (dissonance between optical flow and RGB images) for deepfake detection is proposed. The proposed method extracts the intra- and inter-frame features from RGB image and optical flow via a dual-network architecture, and captures the dissonance between the extracted features with contrastive losses. The proposed scheme was experimentally evaluated using the latest public datasets: DeeperForensics++, UADFV, DFTIMIT, and Celeb-DF. The results demonstrated that DOR outperformed state-of-the-art methods in general. In particular, for low-resolution mixed datasets, the detection accuracy was improved by up to 6.8%. This study proves the validity of the dissonance between different modilities in deepfake detection, and explores an alternative way for deepfake detection research.
My Experience with a Virtual Event Platform at the SCLA Conference

The author's experience utilizing a virtual event platform at the SCLA 2021 Conference is highlighted.
Elucidating Empirical Research Methods in Criminology and Criminal Justice in Nigeria

The crime situation in Nigeria and indeed other parts of the world continue to be monstrous despite the efforts of the criminal justice system. The foundation of overcoming this challenge may be found in the adherence to well articulated empirical research/studies aimed at understanding and providing solutions to the ramifications of crime problems in Nigeria. Therefore, there is the urgent need to examine and highlight the methods of research in criminology and criminal justice. This is a theoretical paper which relied on secondary sources, observations and desk reviews to collect data. The data collected were analyzed using relevant thematic schemes. Relevant themes like types of research, research ethics data collection, qualitative and qualitative research and actual research process were examined. It was recommended that adherence to empirical research rather than media reports is the pathway to solving the crime problem in Nigeria.
Generation of four-mode cluster states based on cascade four-wave mixing process

As a crucial quantum resource for quantum computing and quantum information processing, cluster state has attracted extensive attention due to its unique entanglement properties and rich structures. In this work, we theoretically propose a scheme for generating four-mode entangled states based on cascaded four-wave mixing (FWM) process. The internal entanglement characteristics are studied by using the positivity under partial transposition criterion and eigenmode decomposition. In addition, the output entangled states are reconstructed and optimized by adjusting the relative phase of balanced homodyne detection and postprocessing the signal noise, and finally three four-mode cluster states with different structures are generated. Such a method can effectively reduce the excess noise induced by finite squeezing. Our theoretical results provide a reliable way of generating scalable continuous variable cluster states based on FWM process in atomic ensemble.
A visita pré-operatória de enfermagem em um hospital universitário durante a pandemia de SARS-CoV-2

The aim was to report the experience of nurses from a surgical center in carrying out the preoperative visit during the SARS-CoV-2 pandemic period. Descriptive study, experience report type, based on a preoperative visit at a university hospital in Rio de Janeiro, RJ. The preoperative patient who received a visit from the nurse is better informed about the surgical procedures and care related to the new coronavirus. The fact that most of them were not with a family member/companion, this moment brought a reassuring component to the patient, which facilitated the work of the nursing team in the trans and postoperative periods. The visits provide the operating room nurse with greater knowledge about the patient's clinical status, in addition to encouraging the multidisciplinary team to perform adequate perioperative care for safe surgery.