Reviewerly/exHarmony huggingface dataset:
International Organization of Psychophysiology

Learning and memory deficits characterize the diagnosis of amnestic mild cognitive impairment (aMCI), which is widely viewed as a clinical precursor to Alzheimer's type dementia. There is a growing interest in non-pharmacologic interventions, such as mnemonic strategies, for improving learning and memory in patients with aMCI as well as for maintaining functioning in healthy older adults. Using an ecologically relevant object-location association paradigm, we conducted a randomized, controlled, single-blind study in which healthy older adults and patients with aMCI were randomized to either mnemonic strategy training or a control group that was matched for stimulus exposure. We previously reported that mnemonic strategy training resulted in significantly greater learning and memory improvements compared to the matched exposure condition, in both aMCI patients and healthy controls. The current study examined changes in neocortical activation during encoding in a subset of participants who underwent functional magnetic resonance imaging (fMRI) scanning both before and after training. To minimize potential confounds in between-group comparisons, we employed non-linear cortex based alignment and included only correctly encoded stimuli in our analyses. When re-encoding stimuli learned during training (i.e., trained stimuli), we found a general enhancement of activation in right prefrontal and parietal regions, possibly reflecting practice-related improvement in coordinate spatial processing in all but the aMCI exposure group. Left hemisphere activation was typically only evident in the mnemonic strategy trained participants, regardless of diagnostic status, with the ventrolateral prefrontal cortex appearing especially important for strategy use. While encoding relatively novel stimuli, both mnemonic strategy groups (aMCI patients and healthy controls) demonstrated increased activation in a subset of regions showing change for the trained stimuli, indicating a mnemonic strategy-induced change in the processing of new information. These findings could not be explained by repeated exposure since there was little to no activation overlap in the respective exposure control groups. The current results reinforce the potential benefits of cognitive interventions in these growing populations and indicate that neuroplastic change in key rostral and lateral prefrontal regions mediate this behavioral change.
PERANCANGAN BRAND COMMUNICATION UNTUK BISNIS ETHEREAL BESERTA MEDIA PROMOSINYA

Ethereal is a brand that sells handmade soap with an environmentally friendly concept, which puts forward natural ingredients that are safe for the skin and the environment. The design of the brand campaign and its promotional media is made as a means to communicate the value and products offered and to increase Ethereal brand awareness to potential consumers. The method used is primary data collection through interviews with three experts and three extreme users and distribution of questionnaires to 100 people who are using handmade soap. Research is also supported by literature studies, books, journals and previous research as secondary data. The results of the design are in the form of a campaign strategy and the selection of promotional media used, in accordance with the input and suggestions obtained from the results of interview trials and questionnaires.&#x0D; &#x0D; Keywords: Brand Campaign, Brand Awareness, Promotional Media, Environmentally Friendly, Handmade Soap
PROSPECTS FOR VETERINARY EDUCATION ABROAD

The experience of using an interactive whiteboard is applicable for distance learning during a pandemic. The division of students into microgroups, for the integration of knowledge in various disciplines, is applicable for the organization of self-study. On the example of the teaching experience of universities in the USA, Australia, Great Britain, Brazil.
The English - Indonesian Adaptation of Cultural Terminologies, Vocabularies and Phrases in Webster’s Reflection on Raden Ajeng Kartini

The aim of the research is to analyze the adaptation of terminologies, vocabularies and phrases from English to Indonesian. The research was descriptive qualitative research in order to answer the research problem definitely. The data of the study were taken from a biography written by Tracy Wright Webster entitled Reflection on Raden Ajeng Kartini, while the translation is done by the author itself. The total number of data found was 75 Javanese cultural concepts. Then, the data were grouped into several culture categories before presented in the analysis. The result shows that there are three basic aspects that determine the translator in carrying the adaptation strategy with the Javanese culture. Those aspects are cultural factor, linguistic factor and the translator's preference. The aspects influencing the translation strategy that the translator carries is language and Indonesian modern history. In conclusion, the translation strategy of adaptation that is carried by the translator is actually dynamic. It is because in translating the Javanese cultural concepts are alternated or even hybridized, depending upon the translator's intention whether she wants to introduce the cultural concepts to the TL reader or not. However, apart from the limitation of the biography of Reflection on Raden Ajeng Kartini translation, the English version is still important for foreigners to know more about Indonesian history, culture and society.
Meaning Extraction from Strappare Causatives in Italian

The work targets a little-known causative construction of Italian whose causative verb is strappare ‘tear/extort/snatch’ (e.g. Ada strappò la confessione a Piero ‘Ada made Piero confess against his will’). In the active voice of this clause type, the subject, licensed by strappare, is invariably associated with the semantic role ‘Causer’ (as fare does in fare causatives, see []), whilst the post-verbal NP (e.g. confessione ‘confession’) is best analyzed as the predicate licensing the remaining syntactic function/s and the related semantic role/s. The NooJ grammar which the authors propose automatically extracts the meaning of strappare causatives by means of a novel type of semantic role. The latter is labeled as Cognate Semantic Role because its wording requires a verb whose content morpheme is the same as that of the predicate licensing arguments (e.g. confessare ‘to confess’). The indirect object licensed by the predicate noun is typically associated with a semantic role expressing an Agent. However, a few predicate nouns, e.g. vittoria ‘victory’, determine an unusual pairing between syntactic functions and semantic roles. Importantly, a distinction must be made between cognate semantic roles which are guaranteed by entailments and others which hold true on pragmatic grounds.
Application of Augmented Reality Technology in the SDN 1 Sanur Building Recognition Application

This study aims to build an application to introduce the Sumerta 1 public elementary school building. This research uses AR (Augmented Reality) technology, which with this technology makes it possible to display an object in virtual form in a real world view. The method used in this application is marker-based which identifies the pattern of a marker, in the application development itself the model used is the waterfall model. In the process of building this application, using the Vuforia software development kit (SDK) and Unity as the engine.
Optimization of K Parameters on KNN in Gamelan Jegog Title Classification Using Time Domain Features

Bali is one of the provinces in Indonesia which has a lot of culture and arts, one of which is the Gamelan Jegog Bali. The technology nowadays can make it easier for humans to search for the title of a song that was previously unknown. This technology can be applied to the unknown title of Gamelan Jegog. The features used in this system are Short Time Energy and Zero Crossing Rate. The feature is extracted from Gamelan Jegog and then used to find the best k parameter from the K-Nearest Neighbor classifier. The results showed that the highest accuracy was 45% when the k parameter is 9. The amount of data used and the classification method used has an effect on the accuracy of this system when compared to similar studies.
Statistics

The cyber landscape is inherently complex. Although cyber-attacks of varying magnitude are frequently observed every day, many cyber-related crimes still go underreported. The data collected from these observations may be insufficient, incomplete, or even overwhelming. Using statistical methods, more useful information may be inferred from this type of data. This chapter introduces fundamental topics on statistical methods that relate to cyber research. Statistical methods play several essential roles in cyber research. Statistical methods ensure data are correctly collected and summarized to answer a specific question of interest. Through descriptive statistics, raw observation data can be transformed into common knowledge. Reasoning with large data sets can be overwhelming. With inferential statistics, the characteristics of more massive data sets can be gained from smaller data samples. In order to cope with cyber-related threats, which are often unknown, the concept of resilience is adapted and applied to cyber research. Through these methods, research in cyber resilience benefits from research in statistical methods. The application of statistical methods to modeling, analyzing, interpreting, and presenting information from diverse channels of cyber research hopes to aid in overcoming new cyber threats.
STEM EDUCATION IN THE CONTEXT OF FUTURE PEDAGOGICAL STAFF TRAINING

STEM education is one of the important directions of educational reform of the XXI century. The article focuses on modern initiatives that are made in the field of STEM learning and require the development of a model of education reform that responds modern needs of society. It is noted that the proposed educational scenario confirms the hypothesis underlying this study, namely, the need to reform the existing model of educational staff training in the direction from classical education to innovative STEM education. It is substantiated that the issues of STEM education are not only issues and problems in the field of natural and mathematical sciences, engineering, advanced technologies, but also, first of all, educational policy, methodology, management and organization of activities. It is confirmed that STEM education is best implemented through a combination of its different levels: formal, non-formal, informal. The article proposes mechanisms of reforming pedagogical education for the introduction of STEM education at the Pedagogical University with aim of the training of educators of the new formation and the main components of this model. The model of pedagogical staff training includes: creation of scientific and research STEM centre, educational policy (conceptual and methodological developments of education reform model in STEM direction), increase of communication intensity on STEM education topic, promotion of STEM education ideas among the general public, increase of educators’ qualifications and practitioners involved in education. A study was conducted to test this model in practice during 2016-2020. STEM-education in Ternopil Volodymyr Hnatiuk National Pedagogical University (TNPU) was implemented taking into account the updating of the content of educational and professional programs in accordance with the requirements of the labour market, personal approach, formation of competencies and skills in the field of advanced technologies. It is established that the main indicators of the results of STEM education implementation at the university are: active participation of pupils, students, teachers in various forms of STEM training in the STEM centre of the Faculty of Physics and Mathematics of TNPU, growing interest in STEM projects and STEM practices with help of excursions, competitions, festivals, science picnics.
Assessing potential hazard of technogenic formations of natural and man-made complexes of some sulphide deposits of the Eastern Zabaykalye

Abstract The analysis of chemical composition of technosol and soil samples from Akatuyevsky and Blagodatsky polymetallic deposit mines of the Eastern Zabaykalye revealed that the main pollutant in the soil samples is As. Material excess of the Maximum allowable concentrations was registered for Pb, Zn, Cd and Mn. Calculation of potential hazard coefficients showed that the most hazardous for the environment are man-made formations of Akatuyevsky and Blagodatsky mines. Of all the chemical elements which are most commonly encountered at the Akatuyevsky and Blagodatsky mines technosol the most hazardous are As, Pb, Zn and Cu. It is noted that these chemical elements are part of sulphide ore minerals.
Ab-initio Automated Optimization of Nonlocality in Photonic Quantum States

We push to the limit the device-independent paradigm by implementing an adaptive automated algorithm able to optimize the nonclassicality of unknown quantum systems, tuning parameters with unknown response functions.
IOT SUSTAINABLE INTEGRITY SYSTEM SERVICES FOR SECURITY ENVIRONMENT DATA MANAGEMENT BASED ON BLOCKCHAIN

The cutting-edge centralized Internet of Things (IoT) information flow pipeline is beginning to show its age as it struggles to keep up with the growing amount of individuals linked to IoT systems.As an outcome, the community is starting to move toward a decentralized pipeline to foster information & sharing of resources.The transition, although, isn't simple.How could they guarantee the accuracy of IoT information or processes provided by third parties when several instances allocate information/services randomly?Additionally, how might IoT
Hybrid Optimization of Multiple Intelligent Recommendation Engines for Software Development Cycles

The primary purpose is to create a hybrid recommendation system approach to improve the performance of such systems. This recommendation system would typically be used to assign or suggest a small number of developers suitable for troubleshooting a bug report. For example, managing collections inside bug repositories is software developers' task to fix any bugs that have been identified. Unfortunately, bugs are often created, so the number of developers needed is high, so it's hard to decide how many to assign to specific tasks.This better aims better to understand the outcomes of the latestscientific methods. We also addressed developer prioritization and how it can be used to determine the assignment of a problem to a developer. We have studied two aspects: first, selecting bug reports using hybrid machine learning methods, modeling prioritization in the bug repository, and supporting developer assignment tasks with our model. Second, we modeled the relevant objectives suggested by the developers' backgrounds based on proven knowledge and experience. The study focuses on two topers' experience with fixing bugs and developer rankings in the App Store. We've tried to take better assignments using developer prioritization in bug repositories, e.g., bug triage, severity identification, and re-opened bug prediction. We examine the output of the model in a representative sample of bug repositories. The results show that the prioritization of developers' prioritization triage worker and allow the program to solve the bugs more effectively in support of the software support has been clarified. The introduction article, section 2 on the literature and context, section 3 on the work contribution that will be made, section 4 on the methodology analysis and the expected outcomes will be explained, section 5 on the conclusion, and finally, on the potentialaspects of this work
Pre-training and Transfer Learning

With a machine learning approach and less focus on linguistic details, this gentle introduction to natural language processing develops fundamental mathematical and deep learning models for NLP under a unified framework. NLP problems are systematically organised by their machine learning nature, including classification, sequence labelling, and sequence-to-sequence problems. Topics covered include statistical machine learning and deep learning models, text classification and structured prediction models, generative and discriminative models, supervised and unsupervised learning with latent variables, neural networks, and transition-based methods. Rich connections are drawn between concepts throughout the book, equipping students with the tools needed to establish a deep understanding of NLP solutions, adapt existing models, and confidently develop innovative models of their own. Featuring a host of examples, intuition, and end of chapter exercises, plus sample code available as an online resource, this textbook is an invaluable tool for the upper undergraduate and graduate student.
EXPERIENCES OF PARENTS OF FIRST GRADERS IN CZECH REPUBLIC PERCEIVE EDUCATIONAL PROCESS OF READING AND WRITING DURING COVID-19 PANDEMIC

"The period of the covid pandemic changed day-to-day full-time teaching into distance learning. Teachers, but also parents without any prior training, had to react immediately. What has long been theoretically talked about professionally, namely the use of digitization of teaching in the online environment, has suddenly become a reality. Long discussions about the innovation of the curriculum for primary schools in terms of the scope and quality of educational content were suddenly solved by the teachers themselves using their professional skills and experience. Most of the surveys show [22], [15] that the teachers handled this situation very responsibly and that it can be stated that they managed it within the specific possibilities. Teachers, parents, and especially first-year primary school pupils had a very specific role during the pandemic, and thus the transition to distance learning. It is for this reason that we focused on this group, in our opinion the most affected by pandemics. The present study describes the experience of parents with distance learning reading and writing in the first grades of primary schools at the time of closing schools in the Czech Republic in the school year 2020/2021. The aim of the survey was to describe the effects of distance learning on the development of initial literacy, the differences between day-to-day and online teaching; problems, challenges, pros and cons that the distance learning period brought. The research was carried out as a multi-case study, in which interviews were conducted with six mothers of children - first-class pupils. The results showed that distance learning did not affect the quality of children's acquisition of reading and writing techniques, it only slowed it down. However, there was a decline in pupils' interest in reading and a disruption of their relationship with education in general. It was difficult for parents to motivate children to learn, to help them in case of difficulties with reading and writing techniques, and to evaluate their learning outcomes. On the other hand, distance learning has made it possible to further individualize education with regard to the needs of children and has deepened cooperation between school and family. Distance learning placed increased demands (physical and mental), especially on mothers, when it was necessary for their intensive involvement in the teaching process. Based on the evaluation of the course of distance learning, the paper brings general recommendations applicable to both distance and full-time teaching reading and writing."
COVID-19 Tweets Textual Analytics Using Machine Learning Classification for Fear Sentiment

The volume of COVID 19 microblogging messages is increasing exponentially with the popularity of COVID 19 microblogging services.With the huge number of messages seem in user interfaces, it obstruct user accessibility to useful information hide in disorganized, incomplete and unstructured text message.In order to increase user accessibility it present to aggregator related COVID-19 microblogging message into the cluster and automatically allocate them semantically meaningful labels.However, a typical features of COVID-19 microblogging messages is that they are much shorter than standard text document these messages provide insufficient terms of information for capturing semantic associations providing solution to this problem it suggest a novel framework for organizing unstructured COVID-19 microblogging messages by transforming them into semantically structured representation it express informative tree fragments by analyzing a parse tree of the messages, and then utilize external knowledge bases to increase their semantic information.Twitter dataset shows that our framework significantly outperforms existing stateof-the-art methods.This research provide insights into Corona virus fear sentiment progression, and outlines associated methods, implication, limitations and opportunities.
Tecnologías educativas móviles colaborativas para estudiantes ciegos. Una revisión sistemática

Traditional teaching methods lose prominence as new technologies emerge as aids inthe learning process. Ensuring new classroom dynamics and expanding the learning environmentbeyond the classroom is, in fact, a tempting additive for students who are developing in an era oftechnological ascension. Mobile learning or M-learning is, therefore, the most accessible andpopular way to offer educational dynamics to students, including those with some type ofdisability. Bringing together collaborative teaching, which allows students to work in groups andinteractively with each other, and the facilities provided by technology, the objective of the workis to present a systematic literature review pointing out the impact of collaborative mobiletechnologies for teaching people with Visual impairment. Following Kitchenham's systematicreview method, 592 articles in Portuguese and English were analyzed, 10 of which were selectedto answer the research questions. The results of this research reveal that the use of mobiletechnologies is efficient and more accessible, positively impacting the learning of students withvisual impairments, but still presents latent problems and challenges. This systematic reviewprovides the academic community with a current synthesis of research and development on thesubject, between 2015 and 2020, in different teaching environments regarding the educationallevel and context, characteristics, receptivity and challenges, always backed up by empirical evidence
Augmented Reality and Virtual Reality-Based Technology in Cultural Tourism

The paper intends to scrutinize the effects of augmented (AR) reality and virtual reality (VR) technology implementation in cultural tourism. Therefore, the paper explored and presented the following: (i) AR, and VR (AR/VR) based technology concept in general, (ii) AR/VR technologies application in cultural tourism with an emphasis on their potential to protect cultural heritage; (iii) the overview of AR/VR presence in cultural tourism in the 27 European Union countries (EU-27). In the discussion part, besides empirical results based on the EU-27 desk research, AR/VR technologies in cultural tourism are additionally reconsidered from the aspect of climate change. In conclusion, what is encouraged is the application of AR/VR in cultural tourism due to the benefits AR and VR bring in terms of (i) delivering quite substantial content to their visitors any time from any place, (ii) reducing the negative impact of tourism on cultural heritage and (iii) developing related strategies based on more sustainable principles and concepts.&#x0D; This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.