bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tweet Topics and Sentiments Relating to COVID-19 Vaccination Among Australian Twitter Users: Machine Learning Analysis
Authors: Kwok Stephen Wai Hang , Vadde Sai Kumar , Wang Guanjin 
Published: April 2021

BackgroundCOVID-19 is one of the greatest threats to human beings in terms of health care, economy, and society in recent history. Up to this moment, there have been no signs of remission, and there is no proven effective cure. Vaccination is the primary biomedical preventive measure against the novel coronavirus. However, public bias or sentiments, as reflected on social media, may have a significant impact on the progression toward achieving herd immunity.ObjectiveThis study aimed to use machine learning methods to extract topics and sentiments relating to COVID-19 vaccination on Twitter.MethodsWe collected 31,100 English tweets containing COVID-19 vaccine–related keywords between January and October 2020 from Australian Twitter users. Specifically, we analyzed tweets by visualizing high-frequency word clouds and correlations between word tokens. We built a latent Dirichlet allocation (LDA) topic model to identify commonly discussed topics in a large sample of tweets. We also performed sentiment analysis to understand the overall sentiments and emotions related to COVID-19 vaccination in Australia.ResultsOur analysis identified 3 LDA topics: (1) attitudes toward COVID-19 and its vaccination, (2) advocating infection control measures against COVID-19, and (3) misconceptions and complaints about COVID-19 control. Nearly two-thirds of the sentiments of all tweets expressed a positive public opinion about the COVID-19 vaccine; around one-third were negative. Among the 8 basic emotions, trust and anticipation were the two prominent positive emotions observed in the tweets, while fear was the top negative emotion.ConclusionsOur findings indicate that some Twitter users in Australia supported infection control measures against COVID-19 and refuted misinformation. However, those who underestimated the risks and severity of COVID-19 may have rationalized their position on COVID-19 vaccination with conspiracy theories. We also noticed that the level of positive sentiment among the public may not be sufficient to increase vaccination coverage to a level high enough to achieve vaccination-induced herd immunity. Governments should explore public opinion and sentiments toward COVID-19 and COVID-19 vaccination, and implement an effective vaccination promotion scheme in addition to supporting the development and clinical administration of COVID-19 vaccines.
Medical Specialty Recommendations by an Artificial Intelligence Chatbot on a Smartphone: Development and Deployment
Authors: Lee Hyeonhoon , Kang Jaehyun , Yeo Jonghyeon 
Published: April 2021

Background
The COVID-19 pandemic has limited daily activities and even contact between patients and primary care providers. This makes it more difficult to provide adequate primary care services, which include connecting patients to an appropriate medical specialist. A smartphone-compatible artificial intelligence (AI) chatbot that classifies patients’ symptoms and recommends the appropriate medical specialty could provide a valuable solution.

Objective
In order to establish a contactless method of recommending the appropriate medical specialty, this study aimed to construct a deep learning–based natural language processing (NLP) pipeline and to develop an AI chatbot that can be used on a smartphone.

Methods
We collected 118,008 sentences containing information on symptoms with labels (medical specialty), conducted data cleansing, and finally constructed a pipeline of 51,134 sentences for this study. Several deep learning models, including 4 different long short-term memory (LSTM) models with or without attention and with or without a pretrained FastText embedding layer, as well as bidirectional encoder representations from transformers for NLP, were trained and validated using a randomly selected test data set. The performance of the models was evaluated on the basis of the precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC). An AI chatbot was also designed to make it easy for patients to use this specialty recommendation system. We used an open-source framework called “Alpha” to develop our AI chatbot. This takes the form of a web-based app with a frontend chat interface capable of conversing in text and a backend cloud-based server application to handle data collection, process the data with a deep learning model, and offer the medical specialty recommendation in a responsive web that is compatible with both desktops and smartphones.

Results
The bidirectional encoder representations from transformers model yielded the best performance, with an AUC of 0.964 and F1-score of 0.768, followed by LSTM model with embedding vectors, with an AUC of 0.965 and F1-score of 0.739. Considering the limitations of computing resources and the wide availability of smartphones, the LSTM model with embedding vectors trained on our data set was adopted for our AI chatbot service. We also deployed an Alpha version of the AI chatbot to be executed on both desktops and smartphones.

Conclusions
With the increasing need for telemedicine during the current COVID-19 pandemic, an AI chatbot with a deep learning–based NLP model that can recommend a medical specialty to patients through their smartphones would be exceedingly useful. This chatbot allows patients to identify the proper medical specialist in a rapid and contactless manner, based on their symptoms, thus potentially supporting both patients and primary care providers.
The development of Schoology web-based learning media with GeoGebra to improve the ICT literacy on quadratic functions
Authors: Fatahillah Arif , Puspitasari Irsalina Dwi , Hussen Saddam 
Published: April 2021

The use of technology in learning is essential for developing students' ICT literacy. However, the application of technology as a learning media remains limited. The purpose of this study is to develop a learning media to enhance students' ICT literacy. This research is conducted using a 4-D model, which consists of four stages: defining, designing, developing, and disseminating. This learning media is developed based on ICT literacy indicators. The study participants are 33 of 10th-grade students at one of the public vocational schools in Jember, East Java. Data collection methods consist of validation sheets, tests, questionnaires, interviews, and observations. The expert validation is used to validate the media, while the students' response questionnaire determines the practicality. The validity result shows that the media can be used to measure ICT literacy. Moreover, the practicality of media also shows that it can be easily applied. Furthermore, the effectiveness of learning media is obtained from the N-Gain average of test and ICT literacy questionnaire. The observation data also support the effectiveness of the media during the implementation. The result shows that the media confirmed to be effective as it can improve the students' ICT literacy. To sum up, the Schoology web-based learning media with GeoGebra is useful to improve ICT literacy on quadratic functions
Improving student’s mathematical problem solving skills through Quizizz
Authors: Setiyani Setiyani , Fitriyani Nur , Sagita Laela 
Published: April 2021

The Industrial Revolution 4.0 on Education in Indonesia affects school activities rapidly. Teachers are no longer educated in classrooms only, but they can also utilize technology to conduct distance learning. One interactive application that can be used as a form of question exercise is Quizizz. Therefore, this research aims to: first, examine the effectiveness of students' activities by using Quizizz on mathematical problem-solving skills; second, investigate the differences in the increase in students' ability to solve mathematical problems between the class with and without the Quizizz-aided learning method; third, describe the activities of students who used the Quizizz-aided drill learning method; and fourth, describe the students' responses in using Quizizz. The research was quasi-experiment with a pretest-posttest non-equivalent control group design. The participants in this study are 67 of Grade10 students divided into experimental and control classes. Data collection techniques used were tests for students' mathematical problem-solving skills and questionnaires. The instruments were validated using Pearson correlation, while the reliability was tested using Cronbach's Alpha. Then, the N-gain test was used to analyze the data. The results showed that there was an effect on students’ learning activities by using Quizizz on their problem-solving skills. Besides, there was a difference in the improvement of problem-solving skills between the class with and without Quizizz-aided. Furthermore, students’ activities in three meetings have increased. Moreover, students provided a positive response in learning using Quizizz. Thus, it can be concluded that Quizizz is effective in improving mathematical problem-solving skills.
Mathematics education undergraduates’ personal definitions of the notion of angle of contiguity in Kinematics
Authors: Ndemo Zakaria , Mtetwa David 
Published: April 2021

The concept of a mathematical definition causes severe difficulties among students during problem solving and proving activities. Students’ difficulties with the use of mathematical definitions often arise from the fact that students are often given those definitions instead of constructing them. With the aim of developing an understanding of the kinds of student teachers evoked concept images of the notion of angle of contiguity, a qualitative case study was conducted at one state university in Zimbabwe. Purposive sampling was used to select 28 mathematics undergraduate student teachers who responded to a test item. Qualitative data analysis was guided by ideas drawn from the theoretical framework of Abstraction in Context and idea of imperative features of a mathematical definition. Student teachers written responses revealed that student teachers personal concept definitions consisted of ambiguous and irrelevant formulations that did not capture the essence of the idea of the angle of contiguity. In some cases their responses were not consistent with the definition of the angle of contiguity. Although there were a few instances of adequate descriptions of the concept, (8 out of 32) these and the inadequate descriptors elicited can contribute significantly towards efforts intended to improve mathematics instruction. Improved mathematics instruction will lead to enhanced conceptualizations of mathematics concepts.
Becoming reflective practitioners: Mathematics student teachers' experiences
Authors: Ngololo Elizabeth Ndeukumwa , Kanandjebo Leena Ngonyofi 
Published: April 2021

The level of quality reflective practice remains low among student teachers majoring in Mathematics education. This paper aims to identify the levels of reflective practice possessed by Mathematics education student teachers in a teacher training program at higher learning institutions in Namibia. The professional status requires that teachers become reflective practitioners to develop their effectiveness- a skill they can acquire during their training. A reflection framework was used to identify levels of reflective practices among Mathematics student teachers. This study is qualitative and employed a narrative inquiry approach to assess the effectiveness of reflective practice as experienced by student teachers. A total of ten third-year undergraduate students majoring in Mathematics Education participated in the study by generating reflective journals. The results show that student teachers have insufficient reflective skills which are limited to the first two levels of the reflection framework: technical reflection and reflection-in-and-on-action. This could be due to little guidance offered on developing reflective skills and its use by student teachers. This study's findings will be used to improve the rationality, social and educational practices among the student teachers.
Sixth-grade students’ experiences of a digital game-based learning environment: A didactic analysis
Authors: Gök Mustafa , İnan Mevlüt 
Published: April 2021

Students' conceptual understanding and mathematical process skills can be improved through digital games in mathematics education. The starting point of this study is the idea of having students encounter this kind of environment. The study didactically describes the process of 6th-grade students’ experiences of a digital game-based learning environment. A combination of the Theory of Didactical Situations (TDS) and Digital Game-Based Learning (DGBL) was used in the design of the digital game. The research focused on knowledge-based interactions (teacher-student-game) during the implementation of the game called Race with Numbers, designed in line with this synthesis. The case study, one of the qualitative research methods, was used in the study. Research participants consist of 16 middle secondary school students studying in the 6th grade in a public school. The research data were collected with a video camera and two voice recorders. The research application lasted 75 minutes. The data analysis related to the application was carried out by describing the interaction between the students and the game at stages of TDS. The study findings indicated that TDS has significant potential in designing DGBL environments. However, strong evidence is presented that such environments enable students to realize their own learning and encourage them to use mathematical process skills (such as problem-solving, reasoning, proving, and transfer). Finally, the study highlights the importance of the digital game-based learning approach in mathematics teaching for students.
Tarinan vastaanotto ja affiliaatio autismikirjon häiriössä
Authors: Koskinen Emmi , Stevanovic Melisa 
Published: April 2021

Autismikirjon henkilöiden tarinankerrontaa on tutkittu sekä kokeellisin menetelmin että keskustelunanalyyttisesti, mutta tarinan vastaanottoon liittyvien käytänteiden erittely on jäänyt vähemmälle. Tässä tutkimuksessa paikataan tätä tutkimuksellista aukkoa keskittymällä erityisesti autismikirjon henkilöiden tarinan vastaanottoon ja affiliaatioon.
Aineistona on kymmenen videoitua keskustelua kahden mieshenkilön välillä, joista toisella on todettu Aspergerin oireyhtymä (AS) ja toinen on neurotyypillinen. Esittelemme keskustelunanalyyttisen tapaustutkimuksen avulla, miten kolme autismikirjon häiriöön ja sen vuorovaikutukseen liittyvää erityispiirrettä (sääntökeskeisyys, paikallissuuntautuneisuus ja egosentrisyys) heijastuvat AS-henkilöiden tapoihin ottaa vastaan vuorovaikutuskumppaninsa kertomia tarinoita ja millaisilta nämä tavat näyttävät affiliaation näkökulmasta. Lisääntynyt ymmärrys vuorovaikutuksen käytänteiden merkityksestä osallistujien toiminnan ja heidän välisensä suhteen rakentumiselle voi auttaa autismikirjoon liittyvien vuorovaikutuksen erityispiirteiden kuvaamisessa, sekä rakentaa ymmärrystä erilaisten ihmisten ja vuorovaikutustyylien välille.
Tunnekuvausten sukupuolierot autismikirjon ja verrokkiryhmän nuorten aikuisten kerronnassa
Authors: Dindar Katja , Loukusa Soile , Mäkinen Leena , Kotila Aija , Hurtig Tuula , Ebeling Hanna 
Published: April 2021

Aiemmissa tutkimuksissa on saatu ristiriitaisia tuloksia autismikirjon naisten ja miesten tavasta orientoitua sosiaalisiin tilanteisiin, tulkita niitä ja kertoa niistä. Tässä tutkimuksessa tarkastelimme, kuinka autismikirjon naiset (n = 7) ja miehet (n = 24) ja verrokkiryhmän naiset (n = 11) ja miehet (n = 24) kuvaavat sosiopragmaattisesti monimutkaisissa videoleikkeissä esiintyvien henkilöiden tunteita. Tarkastelimme tutkittavien vapaata kerrontaa keskittyen siihen, kuinka paljon tutkittavat tuottivat suoria ja epäsuoria tunnekuvauksia sekä missä määrin he taustoittivat tunnekuvauksiaan. Tutkimuksessa havaittiin verrokkiryhmän naisten ja autismikirjon naisten tuottavan enemmän epäsuoria tunnekuvauksia kuin autismikirjon miesten. Lisäksi autismikirjon miesten, mutta ei naisten, havaittiin taustoittavan tunnekuvauksiaan vähemmän kuin verrokkiryhmän naisten ja verrokkiryhmän miesten. Verrokkiryhmän naiset ja verrokkiryhmän miehet eivät eronneet toisistaan suorien tai epäsuorien tunnekuvausten määrässä tai tunnekuvausten taustoittamisessa. Tulokset kannustavat kiinnittämään huomiota sukupuolierojen tarkasteluun, jotta autismikirjon naisia ja autismikirjon miehiä voidaan sekä tunnistaa paremmin että tukea kohdennetummin.
Towards a Whole Body [18F] FDG Positron Emission Tomography Attenuation Correction Map Synthesizing using Deep Neural Networks
Authors: Rodríguez Colmeiro Ramiro Germán , Verrastro Claudio , Minsky Daniel , Grosges Thomas 
Published: April 2021

The correction of attenuation effects in Positron Emission Tomography (PET) imaging is fundamental to obtain a correct radiotracer distribution. However direct measurement of this attenuation map is not error-free and normally results in additional ionization radiation dose to the patient. Here, we explore the task of whole body attenuation map generation using 3D deep neural networks. We analyze the advantages thar an adversarial network training cand provide to such models. The networks are trained to learn the mapping from non attenuation corrected [18 ^F]-fluorodeoxyglucose PET images to a synthetic Computerized Tomography (sCT) and also to label the input voxel tissue. Then the sCT image is further refined using an adversarial training scheme to recover higher frequency details and lost structures using context information. This work is trained and tested on public available datasets, containing several PET images from different scanners with different radiotracer administration and reconstruction modalities. The network is trained with 108 samples and validated on 10 samples. The sCT generation was tested on 133 samples from 8 distinct datasets. The resulting mean absolute error of the networks is 90±20 and 103±18HU and a peak signal to noise ratio of 19.3±1.7 dB and 18.6±1.5, for the base model and the adversarial model respectively. The attenuation correction is tested by means of attenuation sinograms, obtaining a line of response attenuation mean error lower than 1% with a standard deviation lower than 8%. The proposeddeep learning topologies are capable of generating whole body attenuation maps from uncorrected PET image data. Moreover, the accuracy of both methods holds in the presence of data from multiple sources and modalities and are trained on publicly available datasets. Finally, while the adversarial layer enhances visual appearance of the produced samples, the 3D U-Net achieves higher metric performance
Hell Hound Rogers or The Great Town Benefactor: Who Was Henry Huttleston Rogers?
Authors: Braga David 
Published: April 2021

The Gilded Age was a period in American History from the end of the Civil War lasting until around 1900, known for big business ruling the country. Henry Huttleston Rogers was a prominent figure in the Gilded Age but has seldom been talked about because other figures of the period such as John D Rockefeller have overshadowed him. Rogers was the Vice President of Standard Oil, the most powerful trust in United States history. The lack of scholarship on Rogers and his historical significance created the need for him to be researched. Rogers’ business dealings helped lead to comprehensive legislation that regulated business, particularly President Theodore Roosevelt’s square deal. This research project sought to investigate who Henry Huttleston Rogers was and his role in the Gilded Age.
Sources on Rogers either portray him in a positive light and talk about him as The Great Town Benefactor of his native town, Fairhaven, Ma or as a robber baron who cared solely about his own wealth. Primary sources on Rogers include first hand accounts published in book form by Thomas Lawson, letters between Rogers and Mark Twain, which were published, political cartoons and archival research materials that included personal correspondence, newspapers, and building deeds. Secondary sources include a biography on Rogers and various sources published by local writers from the town of Fairhaven. With all of this taken into consideration it became evident that there was a dual personality to Rogers but that he cared about his wealth more than anything else.
Unity or Identity? European Disintegration and WWI Culture Conflict
Authors: Hannigan Conor 
Published: April 2021

A resurgence of nationalism in Europe risks undermining the European integration project. Social Psychology and International Relations (IR) literature have explored how identities are created and strengthened through a process called ‘othering’ in which groups define themselves in opposition to others. Several variables contributing to this resurgence of nationalism exist, but ‘othering’ as a means of strengthening group identity appears to be among the most salient factors. This paper draws on previous academic research and uses a historical case study to argue that ‘othering’ in times of trouble and insecurity is not a new phenomenon. My research has focused on the changing public opinion among American citizens of English, German, and Irish descent during World War I. The methodology for this research required surveying primary and secondary sources published during the period August 1914 – April 1917 in order to glean evidence of changing public opinion of specifically the English diaspora. Throughout this process, it became apparent that a resurfacing of cultural and civilizational identities among the diasporas were often the source of changing opinion. Moreover, attempts by Irish and German-Americans to discredit English civilization and the Entente cause during the war actually served to strengthen Anglo-American ties and identities. This case study illustrates how the process of ‘othering’ may be used to bolster a sense of group identity in times of insecurity. This is something that appears to be occurring in Europe and has begun a process of European disintegration.