Reviewerly/exHarmony huggingface dataset:
A Longitudinal Study on Internet Addiction’s Effect on Health Among Adolescents

Abuse of internet networks might result in internet addiction (IA), which associates with impairment to reward processing systems and is able to harm the human body both physically and mentally.Addiction to the internet among adolescents and the effects brought by this is one of the areas where a lot of researchers put efforts in.In this paper, a designed longitudinal study exploring this topic is presented.More than 10 participants from 13 years old to 19 years with considerable internet using the time (spending more than 2 hours on the internet that were not focused on schoolwork) are selected.Questionnaires and surveys are designed or prepared to theoretically diagnose participants' mental stasis and inspect their tendencies of becoming psychologically or mentally sicked once a month.Also, a thorough physical examination will be made once a month to participants to test the internet addiction's effects on participants' physical health.Based on previous researches and investigations, researchers discovered that people with Internet addiction are highly associated with diseases like anxiety, depression, and ADHD, etc.It also increases the risk to risk factors of the cardiovascular system and, negatively affects sleeping quality, which is essential to "memory, learning, concentration and emotional balance".
Social Networking User Sites and Their Implication on Personal Security of Dagoretti North Constituency Residents in Nairobi County

This study was necessitated by the rising wave of insecurity in the posh places of Nairobi County including in the gated areas that this study presupposed was linked to information shared in social networking user sites. The study was guided by three objectives; to identify the features of online interaction in social networking user sites and their implication on personal security of Dagoretti North Constituency residents in Nairobi County, to identify personal security risks associated with interaction on social networking user sites; and to establish the risk mitigation measures that cushion social networking users in Dagoretti North Constituency in Nairobi County, Kenya. The study adopted a cross-sectional survey design. Questionnaires were used to collect data from 378 members of public while Key Informants (K.I) guide were used to collect qualitative data from 10 K.I who comprised of; police officers in crime branch sections of Kilimani and Kawangware police stations. Stratified random sampling technique was used to pick the main respondents. Data was analyzed with the aid of Statistical Package for Social Sciences (SPSS) and results presented using descriptive statistics. Qualitative responses were presented in verbatim quotes and selected comments. According to this study, Instagram (61.9%), Facebook (48.7%), Google+ (42.1%) and Twitter (31.5%) were the most frequently used sites, used every day. The study concluded that; social media sites expose user’s geographical coordinates, allow the use of pseudo names and credentials that disguise the criminals making them difficult to apprehend, made it easy to find victims with just a few keystrokes, allows replication of information and conceal originality, and hence predisposes user’s credentials to theft. The different features of social media networking sites exposed users to major personal security risks such as abductions, rape, robberies, break-ins, murders and burglaries. In order to address the personal security risks brought about by disclosure of personal identifiable information on social networking sites on the users, the study recommended policy formulation through the ICT ministry to create mechanisms for reaching out to SNS users for purposes of user education on safe usage of SNS. Further, as a matter of policy, the government should benchmark with developed countries for advanced preventive regulations measures against social networking vulnerability hence cushion and protect SNS users.
Research on Operation and Management of Intelligent Teaching System in Colleges and Universities

ABSTRCTWith the development of information technology and its in-depth application in the field of education, colleges and universities are actively building intelligent teaching system, but there are many problems in the operation and management of the system, and the advantages of the system have not been given full play.By constructing an intelligent platform for operation and management and integrating software and hardware systems, this paper realizes the goals of innovating teaching space, co-building and sharing resources, improving teaching quality and management efficiency, and meets the constantly developing teaching requirements.
ANALYSIS OF BORDER GATEWAY PROTOCOL, ITS TYPES AND MEASURES TO AVOID RISK

This is the age of digital communication. The process involves sending messages from one end of the network to other end using the internet, extranets and the Internet of Things (IOT) Technologies. Initially, the internet is a small community. But today internet becomes a global community as thousands of different administrative entities own and operate the internet. The process of transferring data across the network is known as routing. The process of routing is performed by using routers. Routers use certain protocols to achieve this task. The Broader Gateway Protocol (BGP) is an interdomain routing protocol that is used to connect two different autonomous systems. The autonomous system is collection of network that runs under a single administrative entity. This paper includes analysis and important techniques of border gateway protocol, types of BGP, its attributes, security threats and measures to avoid risks.
Research on roBERTa-based fraudulent information identification and interpretable AI

Fraudulent information identification helps people detect fraud traps in time and has certain social practical significance. At present, most of the methods with better effect on fraudulent information identification are based on deep learning, but the identification effect still needs to be improved. Secondly, the poor interpretability of the deep learning models themselves is an important obstacle to their practical implementation. To address these two issues, this paper proposes to apply the pre-trained model roBERTa to the fraudulent information identification task, and later interpret the prediction results based on LIME. The experimental results show that roBERTa achieves optimal results on the fraudulent information identification task compared to the three related benchmark models. In addition, the interpretation of the prediction results proves that roBERTa’s predictions are reliable, which lays the foundation for the practical implementation of roBERTa in fraudulent information identification scenarios.
Single image super-resolution combined with CNN and sparse representation

Usually, the high-resolution images reconstructed by the traditional single image super-resolution algorithm often have the problems of insufficient high-frequency information and blurred edges. In order to improve the quality of reconstructed images, we propose a single image super-resolution reconstruction method based on a convolutional neural network and sparse representation. First of all, the dictionary learning method of the convolutional neural network trains the input low-resolution image to obtain LR image blocks. Then, the Learned Iterative Shrinkage and Thresholding Algorithm(LISTA) network trains LR image blocks to generate the corresponding sparse coefficients. Finally, in the reconstruction step, corresponding high-resolution image patches are obtained by Multiplying low-resolution image patches with optimal sparse coefficients. Then corresponding high-resolution image patches are combined to get the final HR image. Experimental results show that the proposed method can effectively combine the two advanced image super-resolution methods to form an efficient and flexible single image super-resolution network.
Unsupervised segmentation of the Serra Dourada Granite, Goiás Tin Province, based on Airborne Geophysics

Manual interpretation of high-dimensional geoscience data can represent a significant challenge since a large volume of data is increasingly overwhelming geoscientists.Dimensional reduction techniques, such as unsupervised segmentation, can reveal high-dimensional patterns within data that can provide meaningful insights to support the geoscientific data interpretation.In this work, we use unsupervised segmentation techniques, such as Principal Component Analysis (PCA) and Model-Based Clustering on radiometric and magnetic airborne geophysical data of the Serra Dourada Granite (SDG), located at the western portion of the Goiás Tin Province, center Brazil.The SDG has an association with greisen mineralization and a late-magmatic enrichment on Rare-Earth Elements (REE), with the formation of supergene deposits of REE on its southernmost portion.Due to the high similarity of the rock's aspects on the outcrop scale, the whole batholith lacks a more accurate mapping, and the division on sub-units remains a problem.We propose here an alternative approach to assist the batholith's cartography through a quantitative analysis over the airborne geophysical data: potassium (K; %), Thorium (eTh; ppm), Uranium (eU; ppm), Total Count (CT; µR/h), and the Total Gradient Amplitude (TGA; nT/m).The features are prepared using Centered Log-Ratio, opening the compositional data, and Min-Max Feature Scaling for variance equalization.Then, we applied PCA to decrease redundancy and create the new orthogonal basis, which improves the segmentation's performance.For cluster analysis, we apply a Model-Based Clustering approach, with the Bayesian Criteria Information function, to automatically identify the most appropriate number of clusters accordingly to a probabilistic determination.Our results allow the individualization of nine significant areas with local coherence and similar multivariate relations by looping through some data segmentation rounds.Additionally, we detail the cluster with the highest values of eTh as it also has relevance for REE prospection.Finally, we evaluate the proposed segmentation by comparing its response to lithogeochemistry data and identifying the multivariate patterns found in every clusters.
CHEMICAL COMPOSITION OF DIOCTAHEDRAL TWO-LAYER CLAY MINERALS

The article shows that the variations in the chemical composition of kaolinite recorded during the analytical determination of individual oxides may be due to different reasons Among them, the following should be noted: isomorphic substitutions, crystal structure features and adsorption of amorphous oxides and hydroxides of silicon, aluminum, iron, manganese, titanium on individual clay crystallites. Additional uncertainty in the analysis results is introduced by the methods of preparation of individual samples. The characteristic of the chemical composition of individual minerals of the kaolinite group from deposits developed on the territory of Russia is given.
Online Digital Book as Learning Material in University

This development research aims to create online digital books that students can use at the university level.Development is carried out following the ADDIE development model, consisting of five stages: analysis, design, development, implementation, and evaluation.Validation is carried out with the assistance of material experts, media experts, and educational technology students.The initial data collection took place through interviews with lecturers and students at the Department of Educational Technology.During the analysis of needs, lecturers stated that they require online learning materials that students can use to understand better the materials, one of which is Digital Online Book.Media experts validated 86.0 % of the results, while material experts validated 88.6 % for an overall average of expert validation results of 87.9 per cent.Individual product trials yielded 86.0 per cent, small group trials yielded 84.0 %, and field trials yielded 88.0 %.The development and research concluded that the developed online digital book is feasible and valid for education.It demonstrates that developed online digital books are deserving of being used as instructional materials for students.
Literature Class Environments Rich in Texts Supporting the Excellent School Literature Movement

Text-rich, interesting, and accessible literacy for Special Education Needs (SEN).This study aims to describe the embodiment of the text-rich, attractive, and accessible literacy classroom environment in supporting the literacy movement in Special Education Needs Schools.A qualitative approach with a single holistic case study method review design is applied.The research procedure includes problem identification, objectives, research questions, literature review, case selection and limitation, data collection, data analysis, triangulation, and integration of findings.The results show that the school literacy environment is quite good, especially to support the school literacy movement focused on activities 15 minutes before learning; the text-rich, accessible, and engaging literacy classroom environment has not been realized and has not supported literacy learning, the role of teachers, literacy teams, school committees, and leadership is not optimal.There are complex problems in realizing a literate classroom environment in special schools, including financing, commitment, and creativity of school residents (literacy team, teachers, students, and parents/stakeholders).
Corporate Reputation of the Schools and Faculties of Social Work around Training by Competences of Intellectual Capital

Corporate governance as a knowledge management system has been approached from the organizational reputation as a result of alliances with institutions.In the health sector, the demand for quality service has led to a system of professional internships and deregulated social service in which the image of the universities and health centers involved is in question.The objective of the present work was to contrast a model for the study of the phenomenon with the intention of specifying the relationships between variables.A non-experimental, exploratory and cross-sectional study was carried out with a non-probabilistic and intentional sample of 1018 administrators, professionals and students from the health sector.It was found that the case monitoring factor reflected the image of universities as trainers of intellectual capital by competencies.In relation to the consulted literature, lines of research are proposed to specify the model.
Research on New Energy Cloud Business Model and Application Scenarios

This article systematically analyzes and sorts out the connotation, extension, and value proposition of the new energy cloud business model, and establishes an infrastructure based on the application scenarios of the new energy cloud business model to provide theoretical guidance for the evaluation and application of the new energy business model; implementation; Optimize the internal management process of the new energy business, cultivate new business forms, new models and new industries of the new energy platform; clarify the future development strategy and development direction of the new energy cloud business model, in order to seek improvement of typical business models in different application scenarios Suggested measures.
Trust, but Verify

In this chapter, we will look at ways of verifying findings from audit testing. Particularly, audit findings that involve machine learning and data science projects will be discussed in detail. The concept of “Trust, but Verify” will be introduced first. This will be followed by an explanation of why it is important to verify findings, including some of the relevant challenges of machine learning models when it comes to reperformance of testing. The chapter will end with an overview of the various sections used to report findings for data science and audit projects. The sections of the data science project will be integrated with the audit projects to ensure it supports the audit verification process.
THE GREAT WORK „DMITRY ALEKSANDROVICH PRIGOV”: ALCHEMY IN THE PROJECT OF A CONCEPTUAL POET

Problem statement. This paper traces the role of hermeticism and alchemy in the artistic production of conceptual poet Dmitry Prigov. Among the different cultural traditions that characterize his project, hermeticism plays a very important role, and especially alchemy, which provided Prigov with material at varying points throughout his artistic career. Purpose of the article. Through several examples taken both from Prigov’s verbal and visual works and from his theoretical texts, the aim of this article is to illustrate not only how the artist managed to use and modify motifs and themes relevant to the alchemical tradition, but also how he retrieved certain philosophical and aesthetic ideas of this hermetic doctrine. Conclusions. As a result, Prigov’s project should be considered a sort of alchemical “Great Work”, which responds to the need for a renewal of culture, the creation of a new concept of art and for a transformation of the role of the artist itself.
Memanfaatkan Limbah Tahu Menjadi Produk Siap Jual

Soybean (glycine max) is widely used as a food ingredient, especially foods that contain lots of high protein. Soybean seeds can also be used as a source of energy and protein. The creation of new products from processed soybean dregs (glycine max) or tofu dregs will be sold through the 4.0 marketing method, namely by using offline and online systems with the results utilizing soybean dregs (glycine max) or tofu dregs which are processed into rengginang and then using packaging design/packaging. attractive and do marketing using e-commerce.
Aiding the Digital Creation of Physical Resources: Card Sets for The Gamers4Nature Toolkit to Game Design

The Gamers4Nature (G4N) project aims to promote environmental awareness through the creation of digital games addressing that theme. The G4N Toolkit to Game design, developed within the project, is an artifact that encompasses resources to support the game creation process and sets of environmental-related thematic cards. In order to be used by other entities (e.g. Environmental Organizations), there was the need to develop a digital design tool able to be used by anyone who wishes to create thematic cards sets, while complying with the design principles and G4N brand guidelines. This paper introduces the G4N Cards Set canvas, a digital tool designed to allow users to produce their own customized thematic cards. The tool was iteratively evaluated by teachers and UX design experts (N = 13). Results emphasize the tool’s intuitiveness, its impact in reducing the user’s learning curve and cognitive load, and its usefulness and practicality in several contexts.
The Long-Term Mechanism of Extracurricular Activities in Primary and Secondary Schools: Using the Four Festivals and One Party in Huai'an No.1 Mountain Middle School as a Case Study

Extracurricular activities play a significant part in students' overall development, and the long-term mechanism is critical to extracurricular activities' educational efficiency. This paper describes Huai'an No. 1 Mountain Middle School's regular extracurricular events, which include four festivals and one party, as well as the tactics used to create a long-term mechanism for the school's extracurricular activities.
Should Critique on Governmental Policy Regarding Covid-19 Be Tolerated on Online Platforms? An Analysis of Recent Case-Law in the Netherlands

Abstract This policy and practice note describes and discusses two recent decisions by the District Court in Amsterdam regarding the applicability of YouTube’s and Facebook’s Community Guidelines on Covid-19 misinformation. The decisions (Café Weltschmerz/YouTube and Smart Exit/Facebook) illustrate the tense intersection between, on the one hand, the freedom to express criticism of the government’s policy for fighting the outbreak of Covid-19 in the Netherlands, and on the other hand, the prevention of (dis)information with the potential to harm public health. The author will point out that the two decisions, although covering the same subject matter, differ significantly in argumentation regarding the (scope of the) application of the freedom of expression. Analysing this divergence in argumentation will show that its roots can be traced back to a different valuation of the role of the online platforms regarding the dissemination of speech. A debate on this divergence is needed to prevent inconsistency in future decisions and to contribute to the broader discussion on content regulation in the European Union.
Analyzing and Applying the Technology of Online Instruction

This paper designed an introductive Nutrition and Health Class for grade 11 with the technology provided by the online instruction platform Nearpod, based on pedagogical research and theory.We further analyze the effectiveness and benefits of the technology we applied technically and pedagogically.The paper consists of four sections: In the Introduction, we introduce the background and the reasons for combining liberal education of Nutrition with online education basing on the studies of teenager dietary patterns from the USA and Hong Kong over a decade.In Analysis, we further discuss the advantage of online education and its technology compared with traditional education in four aspects: facility, discussion, group dynamic, and feedback.In Pedagogy and Technology, we discuss the strategies for improving online education based on pedagogical research and theory.In Course Content, we design an online course about liberal education of nutrition and health for Grade 11, taking advantage of the online course platform Nearpod.We introduce the basic construction and the purpose of the course.The purpose of the course is to raise students' interest in nutrients and health and apply the knowledge to improve their eating patterns by introducing them to the basic knowledge of Carbohydrates and health.In Conclusion, we summarize the previous discussion and further examine the pedagogical potency of the technology.
Medical Image Enhancement Using Recurrent Neural Networks Based Tv Homomorphic Filter

Abstract: Image Enhancement is one of the important requirements in Digital Image Processing which is important in making an image useful for various applications which can be seen in the areas of Digital photography, Medicine, Geographic Information System, Industrial Inspection, Law Enforcement and many more Digital Image Applications. Image Enhancement is used to improve the quality of poor images. X-ray image contains a large amount of information and became important basis in the process of medical diagnosis. The X-ray image has large gray dynamic range but low contrast. This work proposed a new kind of homomorphic filter with ANN which uses total variation model as the transfer function. it has a good balance in both brightness adjustment and details enhancement. And the comparison results were given, the experimental results show that the method can effectively increase the image contrast, highlight the details. Index Terms: Medical image; X-ray image; total variation (TV); image enhancement; image de-noising; ANN