Reviewerly/exHarmony huggingface dataset:
Legal Basis of Civil Liability for Applications of Artificial Intelligence (Particularly Robotics) According to the UAE Civil Transactions Law

This research is a modest legal contribution, the aim of which is to shed light on the texts of the Civil Transactions Law related to civil liability and to identify the extent to which they can be applied to artificial intelligence applications (particularly robotics). Despite the many massive benefits of these applications, they are not without risks, like most modern innovations. Its use may result in significant damage. These damages are often not precisely known who is responsible for them, are the manufacturers of them? Or the engineers who programmed it? Or the people who supervised its operation? Or deny responsibility for the existence of the foreign cause? And to discuss the previous questions in the UAE law, we will first explain the identity of artificial intelligence and its privacy. Secondly, we will briefly present the forms of civil liability in the UAE Civil Transactions Law. Finally, we will show the extent to which artificial intelligence applications can be subject to the legal rules related to these forms.
Data Health Functionality using Hyperledger Fabric Technology

A permissioned blockchain infrastructure called Hyperledger Fabric offers a modular architecture, smart contract execution, configurable consensus, membership services, and a representation of roles between the nodes present in the infrastructure. It also provides high rated integrity sharing. Since patient health records are highly confidential, in order to maintain security, this study examines how to communicate medical data with better privacy protection in healthcare. The transfer of health-related data functions using Hyperledger framework improves the storage reliability and security. Furthermore, the healthcare supply chain process can be improved by hyperledger fabric networks by enhancing the visibility and traceability of network interactions. Companies that have accessibility to the ledger on a fabric network can see the same unchangeable data, enforcing responsibility and lowering the possibility of counterfeiting. This study's findings showcase the utilization of blockchain technology to improve the privacy of data sharing and storage in the healthcare sectors.
Solving Adaptive Distributed Routing Algorithm Using Crow Search Algorithm

Crow Search Algorithm (CSA) can be defined as one of the new swarm intelligence algorithms that has been developed lately, simulating the behavior of a crow in a storage place and the retrieval of the additional food when required. In the theory of the optimization, a crow represents a searcher, the surrounding environment represents the search space, and the random storage of food location represents a feasible solution. Amongst all the food locations, the one where the maximum amount of the food is stored is considered as the global optimum solution, and objective function represents the food amount. Through the simulation of crows’ intelligent behavior, the CSA attempts to find the optimum solutions to a variety of the problems that are related to the optimization. This study presents a new adaptive distributed algorithm of routing on CSA. Because the search space may be modified according to the size and kind of the network, the algorithm can be easily customized to the issue space. In contrast to population-based algorithms that have a broad and time-consuming search space. For ten networks of various sizes, the technique was used to solve the shortest path issue. And its capability for solving the problem of the routing in the switched networks is examined: detecting the shortest path in the process of a data packet transfer amongst the networks. The suggested method was compared with four common metaheuristic algorithms (which are: ACO, AHA, PSO and GA) on 10 datasets (integer, weighted, and not negative graphs) with a variety of the node sizes (10 - 297 nodes). The results have proven that the efficiency of the suggested methods is promising as well as competing with other approaches.
Face Generation Using General Adversial Networks

Face generation is a difficult task with numerous uses in security (for example, creating portraits from descriptions), styling, and entertainment. In this study, we investigate generating faces conditioned on identification using modifications to generative adversarial networks (GANs). In the realm of artificial intelligence, deep learning has had significant success, and several deep learning models have been created. One of the deep learning models, Generative Adversarial Networks (GAN), which was proposed based on zero-sum game theory and has become a new research hotspot. The importance of the GAN model variation is to provide more accurate and realistic data by using unsupervised learning to obtain the data distribution. Due to their vast potential for use in areas including language processing, video processing, and image and vision computing, GANs are currently the subject of extensive research. This project introduces the history of the GAN, theoretical models, and extensional variants of GANs, where the variants can either modify the fundamental structures of the original GAN or further optimise it. The typical uses of GANs are then described. Finally, a summary of the current GAN issues and a description of the models' upcoming work are provided.
Mass Spectrometry-Detected Monoclonal Gammopathy of Undetermined Significance is Associated with Obesity and Other Novel Modifiable Risk Factors: Results of the Promise Study

Background: Monoclonal gammopathy of undetermined significance (MGUS) is a premalignant condition of multiple myeloma with few known risk factors. The emergence of mass spectrometry (MS) for the detection of MGUS has provided new opportunities to evaluate its risk factors.Methods: 2628 individuals at elevated risk for multiple myeloma were enrolled in a prospective screening study and completed an exposure survey. Participants were screened concurrently by MS and serum protein electrophoresis/immunofixation (SPEP/IFX). Monoclonal proteins (M-proteins) detected by MS with concentrations >0·2 g/L were categorized as MS-MGUS. Multivariable logistic regression models evaluated associations between exposures and MS and SPEP/IFX outcomes.Findings: Prevalence of MS-MGUS and SPEP/IFX-detected MGUS were 9% and 4%. Compared to having a normal weight (BMI: 18·5 to <25 kg/m2), obesity (BMI: >30 kg/m2) was associated with MS-MGUS, adjusting for age, sex, Black race, education, and income (odds ratio [OR] 1·73, 95% CI 1·21—2·47; p=0·0025). High physical activity (>73·5 MET-hours/week vs. <10·5 MET-hours/week) had a decreased likelihood of MS-MGUS (OR 0·45, 95% CI 0·24—0·80; p=0·0091), whereas heavy smoking and short sleep had an increased likelihood of MS-MGUS (>20 pack-years vs. never smoker: OR 2·26, 95% CI 1·13—4·31; p=0·017 and sleep <6 vs. >6 hours/day: OR 2·11, 95% CI 1·26—3·42; p=0·0031). Associations between exposures and SPEP/IFX-detected MGUS did not reach statistical significance.Interpretation: MS-MGUS is associated with a broader range of modifiable risk factors than previously identified. Findings may inform targeted screening and prevention strategies.Funding Information: This study was funded in part by the National Institutes of Health (F32 CA220859, K22 CA251648, R25 AI147393, R38 HL150212). This research was also supported by a Stand Up To Cancer Dream Team Research Grant (Grant Number: SU2C-AACR-DT-28-18).Declaration of Interests: DS, DB, MCP are current employees of The Binding Site. SH is a current employee, member of the Board of Directors, and holds patents related to The Binding Site. IMG has served as a consultant for AbbVie, Adaptive, Aptitude Health, BMS, Cellectar, CurioScience, Genetch, Janssen, Janssen Central American and Caribbean, Karyopharm, Medscape, Oncopeptides, Sanofi, Takeda, The Binding Site, Gene Network Sciences Healthcare, and GSK. IMG’s spouse, William Savage, is CMO and equity holder at Disc Medicine. All other authors declare no competing interest.Ethics Approval Statement: This study was conducted upon approval of protocol 18-370 by the institutional review board of the Dana-Farber Cancer Institute.
Digital Content Creation: An Analysis of the Impact of Recommendation Systems

The success of digital content platforms such as YouTube depends on the creativity of independent content creators and the efficiency of content distribution. These platforms share advertising revenue with content creators to induce creative effort. Most platforms also use recommendation systems to provide personalized content recommendations for each consumer. Since the creators' revenues depend on their demand, the criteria of demand allocation embedded in the recommendation system may influence creators' content creation behavior. In this paper, we study how a platform's recommendation system can affect content creation, profits, and welfare. Our results show that a platform may benefit by deliberately biasing its recommendations to intensify competition among creators. Interestingly, we find that biased recommendations can lead to a win-win in which the platform, consumers, and content creators can benefit. We also show that consumers may be worse off when they are more knowledgeable and less dependent on the recommendation system. In addition, we find that the platform, consumers, and creators can benefit when the platform has better information on consumer preferences.
Practice Path, Effectiveness and Experience of ALS in the Philippines

ALS in the Philippines is an informal education method with national characteristics.ALS in the Philippines is not only the crystallization of the Philippine people's exploration of education for all, but also the law of education for all.In order to ensure that individuals who cannot accept or cannot complete the formal school education of schools receive the same education opportunities, the Philippines has gradually formed an ALS with national characteristics to meet the personalized needs of learning objects, focus on meeting the needs of social development, complement the formal school education of schools, and be oriented by qualifications and ability.The Philippine ALS has achieved remarkable results in meeting educational needs and adapting to social development.Adhering to the service-learning-oriented, demand-oriented curriculum, flexible and diverse learning methods, scientific and complete system, and differentiated development
Covid and our civil liberties

The Political QuarterlyVolume 94, Issue 1 p. 154-156 Book Review Covid and our civil liberties Morgan Jones, Corresponding Author Morgan Jones [email protected] Search for more papers by this author Morgan Jones, Corresponding Author Morgan Jones [email protected] Search for more papers by this author First published: 05 January 2023 https://doi.org/10.1111/1467-923X.13225Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL No abstract is available for this article. Volume94, Issue1January/March 2023Pages 154-156 RelatedInformation
Project-Based Learning Role Analysis to Improve Student's Writing Skills in Elementary School

The purpose of this research activity is to describe the role of the Project Based Learning model in writing skills in fourth-grade elementary school students. The method used in this research is a research method. descriptive qualitative. The place for this research is SDN 2 Girimoyo Karangploso, Malang. Class IV students totaling 25 people and class IV teachers at SDN 2 Girimoyo Karangploso are the subjects in this study. Documentation, observation, and interviews are techniques that will be used as data collection techniques. Data analysis techniques in this study are the stages of data reduction, data presentation, and data verification. The results of this study indicate that the learning process using Project Based Learning is more efficient in students' writing skills than learning using the lecture method and the use of teaching materials in the form of learning books. Where learning activities using the Project model. Based Learning is able to make students play an active role in learning activities, students are better able to express ideas about what they want to write on the given sheet, namely the vegetable planting documentation sheet.
Literature review on technologies and games that motivated people to practice physical activity during the pandemic

With the pandemic arrival, changes in people’s lives have become increasingly frequent, also affecting the education and physical health sector. As a consequence, many schools, gyms and clubs ended up closing. However, so that the activities did not stop, there was a need to adapt to technology, involving digital classes, physical activities with the use of applications and data analysis using data science. For this article, a systematic review was carried out, with the objective of evaluating the motivation to practice physical activities during the pandemic (2020 - 2021). We found (226) articles, selected (49) articles and extracted (16). The results, for the most part, were positive for the use of technologies in the practice of physical activities. Thus, the research carried out here reinforces the importance for more research in the area of physical education, health and well-being of people, mainly due to the decrease in this practice due to Covid-19.
iGO2 Portable Oxygen Concentrator

Biomedical Safety & Standards 53(2):p 15, February 01, 2023. | DOI: 10.1097/01.BMSAS.0000912544.23889.92
Implementasi Chatbot Untuk Rekomendasi Tema Tugas Akhir Program Studi Informatika Menggunakan Metode Simple Additive Weight

Many of courses that have been taken makes it difficult for students to determine one area to focus on in determining the theme of the final project. The case study of this research is the Informatics Study Program at the Adisutjipto Aerospace Technology Institute, Yogyakarta. For this reason, a chatbot with a decision support system was made using the simple additive weighting (SAW) method which adds up the weights of the performance of each object that is different and has the same opportunity on all the criteria it has. This method requires the process of normalizing the decision matrix (X) to a scale that can be compared with all existing alternative ratings. The number of observation scores is the sum of the scores of each observation statement multiplied by the weight of the score according to the Likert scale. The maximum score is the maximum score on the Likert scale multiplied by the number of questions, so 5 x 9 = 45. The expected score is the maximum score multiplied by the number of respondents, so 45 x 30 = 1,200. Based on the feasibility test of the chatbot system for the final project recommendation using this method, it succeeded in calculating the feasibility of an application of 1074 (89.5%) with the formula for calculating the percentage of eligibility which was tested by 30 students of the 2017 class of Informatic Study Program, Adisutjipto Aerospace Technology Institute.
Alzheimer’s Disease: The Intellectual Structure of Brazilian Research before and after the Implementation of the National Agenda for Health Research Priorities

Introduction: Alzheimer’s Disease, the most common type of dementia, affects mainly the elderly population and will grow significantly in the coming decades. Objectives: To investigate Brazilian scientific research on Alzheimer’s Disease before and after the implementation of the National Agenda for Health Research Priorities. Methodology: A quantitative research study based on data from Brazilian scientific output on Alzheimer’s Disease collected from the Scopus database in 1974-2005 and 2006-2019. Scientometric methods were used, especially journal and author cocitation analysis. Results: The findings show a growth of original and review articles on Alzheimer’s Disease, published mainly in journals focused on health sciences and authored by researchers from institutions in the Southeast region. The analysis of co-citation journals revealed that Brazilian research on Alzheimer’s Disease, in the first period, was distributed on 72 titles focused on health sciences and, in the second period, 679 titles with broader field coverage. The co-citation authors initially revealed 93 authors co-cited in distant clusters and, in the second period, 1,000 authors co-cited in more connected clusters. Conclusion: Attention is drawn to the strong growth in the Brazilian production of Alzheimer’s Disease after the implementation of the Agenda, as well as to a change in the intellectual structure of research on Alzheimer’s Disease. It is supposed that the Agenda may have acted as a vital element not only for scientific production but also for the release of resources and the participation of researchers, both fundamental actors that would also explain the observed changes.
IMPLEMENTATION OF ASI (AUDITORY VISUAL SELF IMPROVEMENT) MODEL THROUGH DIGITAL VISUALIZATION MEDIA FOR LEARNING TO READ POETRY IN ELEMENTARY SCHOOLS

This article describes the effect of the ASI (Auditory Visual Self Improvement) model through YouTube digital visualization media to improve students’ poetry reading skills in elementary schools. This research is a classroom action research method, which consisted of two cycles. Each cycle consists of planning, action, observation, and reflection. The results of research in each cycle indicate an improvement. Classically, students were declared to have completed 100% of learning in cycle II, because all students in reading poetry achieved 80 or above. This learning completeness is above the KKM target of 80%. Based on these proportions, the criteria for qualitative data assessment are classified as "very good". It shows that ASI (Auditory Visual Self Improvement) learning model assisted by digital visualization media in general can be used as alternative learning to improve students’ poetry reading skills in elementary schools.
IMPLEMENTATION OF MIND MAPPING IN IMPROVING SIXTH-GRADE STUDENTS’ DESCRIPTIVE WRITING ABILITY AT SDN BLIMBING 2 MALANG

This article analyzes the influence of mind mapping in improving sixth-grade elementary school students’ descriptive writing ability. The type of research is qualitative research with a problem-solving research design. Problem-solving is an approach that indicates the data in the form of words or statements obtained through interviews, documentation, observations, and so on. Classroom action research is conducted to solve problems in learning in the classroom or to improve learning quality. The research subjects involved 24 students of class VI at SDN Blimbing 2. The test results before implementing the class research action indicate that the average value is 54. In cycle I, the average value is 68.7 with a completeness percentage of 42%. It shows that between the pretest and cycle 1 there is an increasing value of 14.7. In cycle 2, the average value increases to 75.2 with a completeness percentage of 100%. The observation results of students’ activity in cycle 1 achieve 71% while in cycle 2 it achieves 81%, which means that there is an increasing percentage of 10%. The observation results teacher’s teaching management in cycle 1 achieves a percentage of 73% and in cycle 2 it achieves a percentage of 87%, which means that there is an increasing percentage of 15%. Thus, the data analysis of students’ writing descriptive essays through mind mapping from the pretest, cycle 1 to cycle 2 has achieved an average score target.
Sentiment Analysis on COVID-19 Twitter Data

Corona virus first appeared in December 2019 in Wuhan, China which eventuaUy lead to a catastrophic impact allover the world. The entire world had been fighting this pandemic and expressing their feelings, sharing their opinions on various social media platforms. Substantially Twitter had been the better medium to express their opinion and share updates about the situation. This paper analyzes the sentiments of the public based on positive, negative, and neutral tweets. This analysis eventually helps in the prediction of the covid-19 situation in the world. The dataset was collected from Kaggle which was uploaded by Gabriel Prada containing more than 1,70,000 tweets. Based on tbese tweets posted on Twitter a sentiment analysis was performed. Data Collecting, Data cleaning (Removing RL, #, @ and various types of punctuation), Tokenization, Stemming, removing stop- words were performed, and to fmd the polarity, two types of analyzers were used that is TextBlob and Mmn. 1,79,108 tweets were manually analyzed and comparing it with both the analyzers shows Afmn is more accurate. To evaluate the accuracy a few Machine learning Algorithms had been applied (Logistic Regression, aive Bayes, Decision Tree, and Linear Regression) for predicting the sentiment of the tweet.
Manuscript Analysis of Children's Language Skills and Number Concepts through Technology in the Digital Era

Language is one of the elements behind the development of aspects of development that occur in early childhood, as well as a tool or means to communicate with other people and the environment. To develop and stimulate children’s language development, they can carry out activities such as listening, speaking, reading, and writing, as well as saying and counting number symbols with digital-era devices. This study aims to describe language skills and recognize the concept of numbers in early childhood through technology. This research method is a literature study or review with a qualitative approach that collects data or is based on scientific writing, combining research with existing literature to solve problems. Collecting library data includes reading, storing, and managing research and concluding research materials. The research results show that developing language skills and recognizing numbers in early childhood requires activities such as listening, speaking, reading and writing, calling and counting number symbols through technology.
PELATIHAN MENGANALISIS BUTIR SOAL DENGAN MENGGUNAKAN APLIKASI ITEMAN PADA MAHASISWA PGSD SMESTER VI INSTITUT PENDIDIKAN NUSANTARA GLOBAL

The assessment process does not end with just asking questions. They will come to an analysis of the quality of the questions. Item analysis was carried out to determine the quality of the items prepared. Questions that are of good quality will greatly affect the results of the assessment and capture the learning outcomes well. The purpose of this training is to introduce how to analyze items using ITEMAN by paying attention to the characteristics of the level of difficulty, discriminating power, and the function of the item distractor. This research is descriptive research using observation, interview, and evaluation methods. Participants in this training consisted of 25 students and female students who were students from IPNG. The results of this study were that all participants felt helped in making questions that would soon set their feet in the world of education and some of them even became teachers or instructors. This means that the ITEMAN application really helps our teachers to compose questions.