Reviewerly/exHarmony huggingface dataset:
Mejora de las competencias socioemocionales en alumnos de educación infantil a través de la educación emocional

Working with pupils on appropriate social-emotional education in schools will bring numerous benefits for human beings and for the society of the future (Monjas and González, 2000). The objective of this research is to verify to what extent the students who participate in the programme significantly improve their emotional and social competence. The method used was a quasi-experimental pre-test/post- est design with a non-equivalent control group. Statistical analysis was performed using IBM SPSS software (version 25.0) and the EXCEL spreadsheet (Microsoft Office 2019) and the non-parametric Wilcoxon and Mann Whitney test was used to see if there were statistically significant differences between the different groups. A total of 173 5-year-old pupils participated in the study, of which 89 were from the experimental group and 84 from the control group, all of them from Murcia (Spain). The experimental group was enrolled in the Annual Emotional Intelligence Programme (EMOTI1) (Hurtado and Salas, 2019), and the measuring instrument used was the questionnaire for students on social competence (Caruana and Tercero, 2011). The results showed that the children who participated in the study were less aggressive and showed greater social and communicative competence. After the programme, the pupils in the experimental group interact with each other in a more sociable way and better express their emotions; they develop less violent behaviour and better know how to resolve conflict situations, which has a very positive impact on their emotional and social development.
Exact sum rules for spectral zeta functions of homogeneous 1D quantum oscillators, revisited <sup>*</sup>

Abstract We survey sum rules for spectral zeta functions of homogeneous 1D Schrödinger operators, that mainly result from the exact Wentzel–Kramers–Brillouin method.
Relationship between Social Capital and YouTube Acceptance on Social Media

Today, we live in a communication through social media as well as face-to-face. Over the Past 10 years, social media has become a major means of communication. The purpose of this study was to investigate relationship between social capital and acceptance of YouTube contents. In this study suggested effects of social capital on YouTube contents acceptance in social media. The author divided dimension of social capital as bonding social capital and bridging social capital and identify trust, reciprocity on social media. The author examined how the acceptance of YouTube contents changes according to the trust and reciprocity in social media.BR This study collected 322 questionnaires from Facebook and instagram users, in their 20s. we used to Smart PLS 3.0 to test the research model and hypotheses. Six suggested hypotheses are supported. The results were as follows. First, bonding social capital and bridging social capital have a positive effect on trust, reciprocity. Second, trust and reciprocity have a positive effect on acceptance of YouTube contents. These findings not only theoretical foundations on the research of social capital in social media, but also help company to find strategies in social media. Finally, limitations and future research are discussed.
Exploring Trends in Self-Sacrificial Leadership and Finding Ways to Improve Effectiveness: Using Atypical Big Data Analysis

Due to the global economic recession, the Korean economy is also suffering from inflation amid low growth. In this dark business environment, job performance based on the voluntary dedication and participation of organizational members is required. To create this atmosphere, the importance of the role of leaders and the use of leadership is emerging. This study explored the current status and trends in self-sacrificial leadership, focusing on atypical big data extracted from social media concerning self-sacrifice leadership that the leader
Control Freaks

Abstract This chapter explores how players communicate their intentions to a game through its input. Different means of input are explored, including direct interaction with a physical controller, or navigating a virtual interface. Design principles, such as consistency, logically mapping controls to their function, and constraining player action where necessary, are applied to define what makes a control scheme successful. The specific challenges of various control paradigms, such as the difference between first- and third-person games, are also explored. This chapter also includes some advice on designing input schemes for multiple platforms and employing creativity in control design to surprise players without violating their expectations or comfort.
Rejecting your Reality

Abstract Virtual reality (VR) offers an unprecedented level of immersion in player interaction, having established itself in the games market as a relatively niche platform, at least for the time being. Designing VR interactions is substantially different both in terms of game communication and player input, bringing a variety of challenges. Head-mounted displays offer a rich visual experience, but they can also induce motion sickness if designers aren’t careful about how they take players through a virtual world. Novel controllers present opportunities for gestural interaction, but a wide variety of hardware makes preserving consistency difficult. This chapter addresses these challenges, exploring solutions to common VR design conundrums like player locomotion and camera design. It also discusses opportunities in designing games that creatively take advantage of features specific to VR, such as room-scale physical interaction.
News Application with Voice Assistant

The world is moving at a fast pace and people do not usually find the time to read a newspaper or go through the news every day. A survey shows that a huge amount of time is spent commuting to workplaces and educational institutions. To convert that time into a productive one, we have developed an application that can work hands-free. This is a news application that works on web browsers both on mobile as well as desktop computers. The aim is to create an app that fetches news across various sources all around the world and displays it in an organized manner with a clean User Interface along with some hands free voice assistant features.
Self-supervised human semantic parsing for video-based person re-identification

Video-based person re-identification is an important research topic in computer vision that entails associating a pedestrian’s identity with non-overlapping cameras. It suffers from severe temporal appearance misalignment and visual ambiguity problems. We propose a novel self-supervised human semantic parsing approach (SS-HSP) for video-based person re-identification in this work. It employs self-supervised learning to adaptively segment the human body at pixel-level by estimating motion information of each body part between consecutive frames and explores complementary temporal relations for pursuing reinforced appearance and motion representations. Specifically, a semantic segmentation network within SS-HSP is designed, which exploits self-supervised learning by constructing a pretext task of predicting future frames. The network learns precise human semantic parsing together with the motion field of each body part between consecutive frames, which permits the reconstruction of future frames with the aid of several customized loss functions. Local aligned features of body parts are obtained according to the estimated human parsing. Moreover, an aggregation network is proposed to explore the correlation information across video frames for refining the appearance and motion representations. Extensive experiments on two video datasets have demonstrated the effectiveness of the proposed approach.
Entanglement Entropy and Non-Local Duality: Quantum Channels and Quantum Algebras

We investigate the transformation of entanglement entropy under dualities, using the Kramers-Wannier duality present in the transverse field Ising model as our example. Entanglement entropy between local spin degrees of freedom is not generically preserved by the duality; instead, entangled states may be mapped to states with no local entanglement. To understand the fate of this entanglement, we consider two quantitative descriptions of degrees of freedom and their transformation under duality. The first involves Kraus operators implementing the partial trace as a quantum channel, while the second utilizes the algebraic approach to quantum mechanics, where degrees of freedom are encoded in subalgebras. Using both approaches, we show that entanglement of local degrees of freedom is not lost; instead it is transferred to non-local degrees of freedom by the duality transformation.
<i>Traces:</i> Inkling Blockchain for Distributed Storage in Constrained IIoT Environments

Storing data from Industrial-Internet-of-Things (IIoT) sensors in blockchain (BC) for monitoring the applications leads to management issues like bloating. The crux of this work is generating traces (the part of industrial data) using an ARIMA model and storing only the metadata over the network, resulting in reduced delay and managed data. We determine the size of the traces for storing on the store and generate (S&G) blocks (blocks that store traces along with their metadata) by considering principal parameters, such as training time, block size, and error. In general, S&G consists of three phases: 1) categorizing the data into groups based on their sampling rates, 2) storing the trace of data and metadata into the blocks, and 3) retrieving the entire data. We demonstrate the feasibility of S&G with errors and regret in the range of 0.07–0.10 and 0.20–0.25, respectively, using the appropriate ARIMA model.
Development of a digital educational platform for studying radio engineering courses

The main tasks solved with the help of a digital educational platform with interactive learning opportunities are a remote process of obtaining knowledge, providing permanent access to educational materials, and monitoring the level of students’ performance. This paper considers the development of a digital educational platform for the remote study of modern Ultra high frequency (UHF) and Extremely high frequency (EHF) radio systems. The architecture of the developed platform is a client-server. The server part includes a database of collected laboratory results, and the client part is responsible for displaying and outputting the necessary information. The list of virtual labs that are part of the educational platform, as well as devices and measuring instruments used in the virtual laboratory is presented. An example of a lab with remote access implemented using the Unity 3D application development tool is given. This digital educational platform will be used by students of the «Radio Engineering, Electronics and Telecommunications» educational program to study radio engineering courses. It is shown that the use of virtual laboratory work in the educational process can replace real expensive equipment, as well as consolidate practical skills in training.
COMPARATIVE ANALYSIS OF DIFFERENT MACHINE LEARNING ALGORITHMS IN MECHANICAL DATASET.

In this paper we created a data set for tool wear of a lathe machine.In data set we have taken 29 observations that means there are 29 rows in our data set and 4 variables that means data set have 4 columns i.e.Cutting speed (rpm), Feed rate (mm/min), Radial depth of cut (mm) and Tool wear (mm).For this particular data set we are using different machine learning algorithms to train the model and find out the comparative model accuracy.decision tree, generalization of ordinary linear regression and Random forest models has been used in this paper for comparative analysis using R programming language.
The patient-centered care for patients with acute myocardial infarction: what can be improved the disease management

Introduction: Cardiovascular diseases are presented as a set of diseases that affect the cardiovascular system because of inappropriate lifestyles or unhealthy, they are consistent in risk might be modifiable through a proper disease management factor. Aim: Assess the perceptions of patients with acute myocardial infarction about this heart disease and risk factors associated. Also, identify the risk factors that can be improved to manage the disease. Design: Observational and prospective study. Methods: The survey was conducted in a Cardiac Intensive Care Unit of a Central Hospital, with inclusion of all patients admitted on a period of two months. Nineteen patients were studied with a clinical diagnosis of Acute Myocardial Infarction. Results: The analysis of the questionnaires showed that, approach the subject has a justified and reasoned relevance. The high prevalence of risk factors that can be modified highlighted the need for intervention in patients with non-modifiable risk factors. Conclusion: Patients with acute myocardial infarction do not have a correct perception of the disease and associated factors. Many of the risk factors present in patients with acute myocardial infarction are likely to be modified by an appropriate disease management, with a patient-centred care.
Drawing the Light Paths at a Lens to Find Its Effective Focal Length and Principal Planes

This paper proposes a simple method to design experiments for drawing the light paths at a lens to find its effective focal length and principal planes. In the designed experiments, long-exposure photography was used to record the light scattered using a moving sheet of paper, thus revealing the light path. According to the proposed experimental method, (1) the effective focal length of a lens and (2) the principal planes of a lens can be measured. Moreover, the system is easy to build, inexpensive, and can promote students’ understanding of geometric optics by providing an intuitive physical phenomenon. The work is also of pedagogic interest as it reveals a new simple experimental method to find the principal planes of a thick lens and its effective focal length.
EP07.03-005 MesoGraph: Graph Neural Networks for Weakly Supervised Cellular Profiling in the Subtyping of Malignant Mesothelioma Images

Malignant mesothelioma is typically subtyped into Epithelioid (E), Sarcomatoid (S), and Biphasic (B) according to the proportions of epithelioid and sarcomatoid tumor cells present. Identification of the subtype informs treatment and can improve patient outcome, however this subtyping has a high level of variability between pathologists.
Data Management Planning for an Eight-Institution, Multi-Year Research Project

While data management planning for grant applications has become commonplace alongside articles providing guidance for such plans, examples of data plans as they have been created, implemented, and used for specific projects are only beginning to appear in the scholarly record. This article describes data management planning for an eight-institution, multi-year research project. The project leveraged four data management plans (DMP) in total, one for the funding application and one for each of the three distinct project phases. By understanding researcher roles, development and content of each DMP, team internal and external challenges, and the overall benefits of creating and using the plans, these DMPs provide a demonstration of the utility of this project management tool.
Mini-Sumo Robot Design with Respect to the Control System

This paper presents problems related to the design and construction of mini-sumo robots. The authors discuss the solutions used in the presented topic using the example of a developed robot. The presented design considers tournament requirements, and demonstrates the selection of robot components. Special attention was paid to the presentation of the developed schematics and PCB fabrication.
Latina Millennial Mothers’ Experience of Reshaping Motherhood Ideals: The Role of Fashion Mommy Influencers

<p class="MsoNormal">The social media influencer phenomenon has largely explored women’s abilities and practices on digital spaces. Despite growing popularity on the subject matter, little research is available on how social media influencers help shape an individual’s identity, especially fashion mommy influencers’ (FMIs) role among Latina women in the US as they experience motherhood. To understand FMIs’ influence among Latina millennial mothers,’ data were drawn from three sources: (1) In-depth interviews, (2) digital ethnography, and (3) secondary data. Our data analysis revealed four themes that uncovered cultural and social influences on participants’ identity construction: 1) shaping of motherhood ideals (2) sense of solidarity through shared experiences with fashion mommy influencers, (3) fashion mommy influencers as a time-saving shopping reference for self, and (4) perceived distance in reality. Largely, we establish that FMIs serve as reference points on matters of fashion consumption and motherhood as Latinas construct their intersectional identities.<o:p></o:p>
Construction and Application of a Large-Scale Chinese Abstractness Lexicon Based on Word Similarity

As an important semantic feature, abstractness has been widely studied in linguistics, psychology, cognitive sciences and other fields. Many languages have constructed their abstractness lexicons, while there has never been a large-scale and high-quality abstractness lexicon in Chinese. Since manual construction is time-consuming and costly, we use the existing resources with human abstractness scores as original data, and adopt the word similarity-based approach to automatically construct a large-scale Chinese abstractness lexicon. Besides, we evaluate the quality of the constructed lexicon by comparing it with expert knowledge and previous work. It has been verified that this lexicon is roughly consistent with human cognition and can provide reliable abstractness ratings for words. Finally, the performance of this constructed lexicon on two research, cross-language comparison and Chinese text readability auto-evaluation, shows that word abstractness is an important feature in investigating cognitive differences and text complexity. The large-scale Chinese abstractness lexicon constructed in this paper has important application values.
Basic competencies of a Virtual Teacher

Virtual education offers the possibility to implement and put into practice an education process as ample and complex as it is necessary. It keeps us in touch with our students through online resources which turn it into a powerful and attractive way of communication which works based on previously set objectives. In this context the role of the teacher becomes key to achieve a meaningful, effective and quality teaching-learning process. The teacher must possess specific characteristics which will allow him to attain the desired educational objectives. The objective of this research paper is to identify and detail which are the basic competencies that a virtual teacher should cover. In order to carry out this research we made a literature review of texts focused on distance education and teaching skills necessary for it. This activity allowed us to dimension the issues that were of interest and especially to put them in context.
A Siamese Neural Network for Scalable Behavioral Biometrics Authentication

The rise in popularity of web and mobile applications brings about a need of robust authentication systems. Behavioral Biometrics Authentication has emerged as a complementary risk-based authentication approach which aims at profiling users based on their interaction with computers/smartphones. In this work we propose a novel approach based on Siamese Neural Networks to perform a few-shot verification of user’s behavior. We develop our approach to authenticate either human-computer or human-smartphone interaction. For computer interaction, our approach learns from mouse and keyboard dynamics, while for smartphone interaction it learns from holding patterns and touch patterns. The proposed approach requires only one model to authenticate all the users of a system, as opposed to the one model per user paradigm. This is a key aspect with respect to the scalability of our approach. The proposed model exhibits a few-shot classification accuracy of up to 99.8% and 90.8% for mobile and web interactions, respectively. We also test our approach on a database that contains over 100K interactions collected in the wild.
Introduction to Generative Recursion

AbstractThis chapter introduces program design and implementation using generative recursion.
The Function of Politeness of Teacher Language In Implementing Character Values To The Primary School Students

This research aims to identify the function of the language politeness of the teacher in implanting character values to students in the primary school. The research was carried out at the primary school of SD Muhammadiyah Pahandut, Kota Palangka Raya. A qualitative method was used in this research with a pragmatics research design. The pragmatics design used to analyze the data was based on the principle of politeness which included six maxims and five components of speech situation. The data were obtained from conversational discourse between teachers and students containing language politeness in teaching and learning activities at the school. Then the data were also supported by doing interviews with involved teachers and by reviewing assessment report documents of students to relate the function of the teacher's language politeness with student character values of being attained. The data obtained using the triangulation technique were analyzed and presented by the qualitative descriptive technique. The results showed that there were 150 items of teacher language politeness which provided very good functions in implanting character values to students as an effort to build character for primary school students
Zaawansowane procedury NLP jako przesłanka rekonstrukcji idei wiedzy

Advanced NLP Procedures as Premises for the Reconstruction of the Idea of Knowledge The article presents the current state of development of the Natural Language Processing (NLP) technology, in particular the GPT-3 language model, and presents its consequences for understanding the phenomenon of knowledge. The NLP technology has been experiencing remarkable development recently. The GPT-3 language model presents a level of advancement that allows it to generate texts as answers to general questions, as summaries of the presented text, etc., which reach the level surpassing the analogous level of human texts. These algorithmic operations lead to the determination of the probability distribution of its components. Texts generated by such a model should be considered as autonomous texts, using immanent, implicit knowledge embedded in language. This conclusion raises questions about the status of such knowledge. Help in the analysis is provided also by the theory of discourse, as well as the theory of discursive space based on it, that proposes the interpretation of knowledge as a trajectory of discourses in a dynamical space. Recognizing that knowledge may also be autonomous, and in particular not be at the exclusive disposal of humans, leads to the question of the status of artificial cognitive agents, such as the GPT-3 language model.