Reviewerly/exHarmony huggingface dataset:
Digital Contact Tracing Applications against COVID-19: A Systematic Review

&lt;b&gt;&lt;i&gt;Objective:&lt;/i&gt;&lt;/b&gt; The novel coronavirus 2019 (COVID-19) pandemic has triggered public anxiety around the world. So far, the evidence suggests that prevention on a public scale is the most effective health measure for thwarting the progress of COVID-19. Another critical aspect of preventing COVID-19 is contact tracing. We aimed to investigate the effectiveness of digital contact tracing applications currently available in the context of the COVID-19 pandemic. &lt;b&gt;&lt;i&gt;Methods:&lt;/i&gt;&lt;/b&gt; We undertook a systematic review and narrative synthesis of all literature relating to digital contact tracing applications in the context of COVID-19. We searched 3 major scientific databases. Only articles that were published in English and were available as full-text articles were selected for review. Data were extracted and narrative syntheses conducted. &lt;b&gt;&lt;i&gt;Results:&lt;/i&gt;&lt;/b&gt; Five studies relating to COVID-19 were included in the review. Our results suggest that digitalized contact tracing methods can be beneficial for impeding the progress of COVID-19. Three key themes were generated from this systematic review. First, the critical mass of adoption of applications must be attained at the population level before the sensitivity and positive predictive value of the solution can be increased. Second, usability factors such as access, ease of use, and the elimination of barriers are essential in driving this uptake. Third, privacy must be ensured where possible as it is the single most significant barrier against achieving critical mass. &lt;b&gt;&lt;i&gt;Conclusion:&lt;/i&gt;&lt;/b&gt; Contact tracing methods have proved to be beneficial for impeding the progress of COVID-19 as compared to older, more labour-intensive manual methods.
AML by design: Designing a central bank digital currency to stifle money laundering

This article explores how technical central bank digital currency (CBDC) design choices can be used to make a CBDC inherently resistant to money laundering. These design choices not only further anti-money laundering (AML), but they can also help to better balance AML priorities with other goals including financial inclusion, privacy and compliance costs. Moreover, CBDCs provide an opportunity to measure the effectiveness of different design choices in real time. These measurements can facilitate the iterative redesign of CBDCs to identify optimal approaches to meeting regulatory objectives
Digital Marketing's Influence on Consumer Purchasing Decision: A Case Study in Iraq

Examining the effects of digital marketing on customer purchase decisions was the main goal of this study.Specific objectives guided the study, including the evaluation of digital marketing platforms in Iraq with the ability to impact purchasing decisions and the identification of product categories that customers purchased on digital media platforms. Although the corporation is not completely responsible for the purchase choice process of consumers, It is a comprehensive procedure that takes into account psychological aspects, social influence, word-of-mouth, cultural values, and financial level. A total of 250 questionnaires were delivered, with the exclusion of the unfinished surveys, and 220 usable samples were obtained, yielding an overall response rate of 88%. Multiple regressions, reliability tests, correlation tests, and descriptive analysis were all employed in this study. The findings of this study also demonstrated the major effect of digital marketing on customer purchase decisions, including social media marketing and mobile marketing. Hypothesis testing, however, showed that various well-known digital marketing platforms in Iraq had an impact on students' behavior. Through digital media platforms, students in Iraq make purchases across a wide range of product categories, and digital marketing has an impact. In the end, firms need to implement plans to harness the digital world and technology as well as raise brand recognition through online media in order to compete in today's business climate.
A scheme to create and verify scalable entanglement in optical lattice

Abstract To achieve scalable quantum information processing, great efforts have been devoted to the creation of large-scale entangled states in various physical systems. Ultracold atom in optical lattice is considered as one of the promising platforms due to its feasible initialization and parallel manipulation. In this work, we propose an efficient scheme to generate and characterize global entanglement in the optical lattice. With only two-layer quantum circuits, the generation utilizes two-qubit entangling gates based on the superexchange interaction in double wells. The parallelism of these operations enables the generation to be fast and scalable. To verify the entanglement of this non-stabilizer state, we mainly design three complementary detection protocols which are less resource-consuming compared to the full tomography. In particular, one just needs two homogenous local measurement settings to identify the entanglement property. Our entanglement generation and verification protocols provide the foundation for the further quantum information processing in optical lattice.
Maximum F1-Score Training for End-to-End Mispronunciation Detection and Diagnosis of L2 English Speech

End-to-end (E2E) neural models are increasingly attracting attention as a promising modeling approach for mispronunciation detection and diagnosis (MDD). Typically, these models are trained by optimizing a cross-entropy criterion, which corresponds to improving the log-likelihood of the training data. However, there is a discrepancy between the objectives of model training and the MDD evaluation, since the performance of an MDD model is commonly evaluated in terms of F1-score instead of phone or word error rate (PER/WER). In view of this, we in this paper explore the use of a discriminative objective function for training E2E MDD models, which aims to maximize the expected F1-score directly. A series of experiments conducted on the L2-ARCTIC dataset show that our proposed method can yield considerable performance improvements in relation to some state-of-the-art E2E MDD approaches and the celebrated GOP method.
Evaluation of Women’s Entrepreneurship Education Based on BP Neural Network

Entrepreneurship education is the key to cultivating the entrepreneurial spirit of national talents. The goal of entrepreneurship education is to cultivate a large number of pioneering talents, and women’s entrepreneurship education is particularly important. The government, enterprises, schools, and all sectors of society start from multiple channels to let students strengthen their entrepreneurial awareness and improve their entrepreneurial ability. This paper uses the most advanced BP neural network algorithm to study and evaluate women’s entrepreneurship education. This paper briefly introduces the concept and model of the artificial neural network and establishes a BP neural network model while improving the classical BP neural network. Then, we list the application process of the BP neural network model in evaluating women’s entrepreneurship education. We select college students for empirical analysis, determine the number of neurons, and select 9 items as the evaluation index of women’s entrepreneurship education. Using valid assumptions, we further determine the model learning rate and momentum factor. Finally, the results show that the actual evaluation results based on the BP neural network are basically the same as the expected results, and the maximum relative error between the actual value and the expected value is approximately 1.64 %, and the comprehensive evaluation value is 92 points. The proposed algorithm can effectively avoid the problems of instability and slow convergence of the traditional model and can comprehensively improve the accuracy of the evaluation results of women’s entrepreneurship education.
Technology-Based Pedagogy for Mathematics Education in South Africa: Sustainable Development of Mathematics Education Post COVID-19

The COVID-19 pandemic has transformed life globally. So too, teaching and learning in higher education have transformed to include technology-based pedagogy and online learning to curb the spread of the contagious Coronavirus. In the era of the 21st century, technology-based pedagogy is important for supporting teaching and learning. In mathematics higher education contexts, coupled with embracing abstract concepts in mathematics, there are different notions of what it means to include technology-based pedagogy during the COVID-19 pandemic. This qualitative study explored 38 postgraduate students’ experiences and perceptions of using technology-based pedagogy during the COVID-19 pandemic. These participants were mathematics education students and practicing mathematics teachers at schools in South Africa. The theory of virtual communities of practice framed this study. Participants were invited to two interactive virtual workshops using various technology-based pedagogy during the COVID-19 pandemic. Subsequently, these participants were invited to participate in online interviews focusing on their experiences and perceptions of technology-based pedagogy for learning mathematics education. This study reveals the challenges and strengths of using technology-based pedagogy for learning mathematics education during COVID-19. These results are relevant when considering perceptions, experiences, and implications of technology-based pedagogy for sustainable mathematics education during and post-COVID-19.
A CNN based model for Identification of the Level of Participation in Virtual Classrooms using Eye Movement Features

As the widespread Internet connection is expanding, the transition from traditional classroom learning to virtual learning is now easier than ever. Online education has developed all over and replacing traditional learning. The ability to precisely monitor user behavior and understand where the pain spots are in the learning process is one of the benefits of the change to online learning. Therefore, this research will provide a benefit to Online learning education. Here, Fixation recognizable proof, which involves confining and identifying Fixation and saccades in eye-tracking conventions, is a vital piece of eye movement information handling that can altogether affect more elevated level examinations. Fixation distinguishing proof techniques, then again, are normally talked about casually and seldom analyzed. The work specified gives a scientific classification of fixation distinguishing proof calculations that groups calculations as per how they utilize spatial and fleeting data in eye-following conventions. Utilizing this scientific categorization, the Adaptive algorithm that is suggestive of one-of-a-kind classes in the scientific classification and is based on regularly utilized strategies. Then, at that point, utilizing a bunch of subjective rules, we investigate and look at this algorithm. Here, CNN has been utilized for face information registering and Adaptive calculation for eye fixation. The after effects of these correlations have interesting ramifications for how algorithms will be utilized later on. Providing an expected results on adapting for eye contact lenses and kajal strengthens the research work. An alert and email system that notifies the participant if there is a lack in focus during the online class is proposed.
Uncertainty Propagation Based MINLP Approach for Artificial Neural Network Structure Reduction

The performance of artificial neural networks (ANNs) is highly influenced by the selection of input variables and the architecture defined by hyper parameters such as the number of neurons in the hidden layer and connections between network variables. Although there are some black-box and trial and error based studies in the literature to deal with these issues, it is fair to state that a rigorous and systematic method providing global and unique solution is still missing. Accordingly, in this study, a mixed integer nonlinear programming (MINLP) formulation is proposed to detect the best features and connections among the neural network elements while propagating parameter and output uncertainties for regression problems. The objective of the formulation is to minimize the covariance of the estimated parameters while by (i) detecting the ideal number of neurons, (ii) synthesizing the connection configuration between those neurons, inputs and outputs, and (iii) selecting optimum input variables in a multi variable data set to design and ensure identifiable ANN architectures. As a result, suggested approach provides a robust and optimal ANN architecture with tighter prediction bounds obtained from propagation of parameter uncertainty, and higher prediction accuracy compared to the traditional fully connected approach and other benchmarks. Furthermore, such a performance is obtained after elimination of approximately 85% and 90% of the connections, for two case studies respectively, compared to traditional ANN in addition to significant reduction in the input subset.
VARIANT OF OTP CIPHER WITH SYMMETRIC KEY SOLUTION

The paper proposes a solution to construct symmetric–key cryptographic algorithms based on OTP cipher developed based on the cipher One – Time Pad (OTP). Advantages of the algorithms built according to the proposed new solution is to have secure and efficient implementation as OTP cipher, but the establishment, management - distribution and usage of keys are exactly the same as the Symmetric key cryptosystems in practice (DES, AES,. . . ).
Fast Image Restoration Method Based on the L0, L1, and L2 Gradient Minimization

In this paper, we propose a novel image denoising method by coupling with L0, L1 and L2 gradient minimization. Our proposed method smoothes the gradient difference between image pixels and noise pixels and sharpens the edges by increasing the steepness of transition. We focus on global noise processing rather than local features and adaptively process noise signals with different characteristics. Based on the half-quadratic splitting method, we perform a smoothing step realized by a Poisson approach and two edge-preserving steps through an optimization formulation. This iterative method is fast, simple, and easy to implement. The proposed numerical scheme can be performed to a discrete cosine transform implementation, which can be applied with parallel GPUs computing in a straightforward manner. Various tests are presented, including both qualitative and quantitative tests, to demonstrate that the proposed method is efficient and robust for producing image processing results with good quality.
The Role of Mother’s Education and Early Skills in Language and Literacy Learning Opportunities

The purpose of this study was to examine the relationship between language and literacy learning opportunities, early skills, socioeconomic status, and mother’s education in children’s early education. In addition, we attempted to determine the language domains needed for training as well as the ideal duration for language and literacy learning for children. We used a mixed methods design to assess early childhood language and literacy skills. The study involved 2550 early childhood learners, 235 teachers, and parents of learner participants from 112 kindergartens. The standard measure of language proficiency was used to measure the learners’ early language and literacy skills. Mother’s education and learners’ early abilities were positively correlated with learners’ language and literacy learning opportunities. Learners who have mothers with a high level of education receive significant opportunities to learn language and literacy compared to those with mothers with a low level of education. Therefore, their language skills are superior. There are 12 language domains needed for training in early childhood and the ideal duration of language learning for children is 26 minutes per day or 182 minutes a week. The language domains are determining factors for obtaining reading skills in the future. Mother’s education and child’s early skills really help children in language and literacy learning. The implication of this research is that literacy programs are needed for early childhood learners who have low initial abilities and children with mothers with a low level of education.
Opportunities for the implementation of career lift technology in higher educational institutions

Introduction. The article is devoted to the involvement of higher education stakeholders in the process of building students and graduates’ careers. The purpose of the article is to summarize modern ideas about the phenomenon of ‘a career lift’ and present author's views on the possibilities of implementing a career lift technology in higher educational institutions. Materials and Methods. The paper presents a subject-centered conceptual model of implementing the career lift technology, based on the methodology of systemic, subject-activity and environmental approaches to scientific cognition. The research methods included etymological and bibliographic analysis used to summarize and clarify the concepts of ‘career’ and ‘career lift’. The modeling method was employed for the complex study and reproduction of the structure and the properties of the career lift technology in universities. Results. The author presented an analysis of existing world approaches to the interpretation of the concept of ‘career’, summarized their main features and presented a clarified definition of this phenomenon. Based on the etymological and bibliographic analysis of the concepts ‘career’, ‘lift’ and ‘career lift’, reflected in dictionaries and scholarly literature (both Russian and international), the author proposed and justified her approach interpreting the career lift phenomenon. As a result, the author proposed two ways of interpreting the concept of the career lift. According to the first one, a career lift is a type of career building chosen by a person. The second one considers career lift as a technology of career support for students, graduates, and professionals. Based on the analysis and personal experience, the author developed and justified a subject-centered model of the career lift technology, implemented in several stages related to individual goals of a person as a subject of education. It is important to note that the model contains links between student's goals and goals and activities of higher education institutions and other stakeholders. The author argues that all the components of each level relatively exist as independent, since they always act interconnected with each other. Conclusions. The author concludes that the subject-centered implementation of the career lift technology, based on the principles of consistency, flexibility, individual and environmental determination, and multidimensionality, is designed to ensure the effectiveness of actions and interactions within its structure.
Procedural Justice and Self Governance on Twitter

Online platforms are increasingly being held to account for the content that their users post. Regulation of content has long been a secondary concern of platforms, but more recently as platforms focus on their content governance, they have typically drawn their regulatory model from offline legal frameworks built around sanctioning and punishment of rule violators. This study approaches these problems using an alternative approach, also drawn from legal scholarship, that is based upon motivating voluntary rule following by emphasizing the fairness of platform rules and the justice of the processes used to communicate content moderation decisions. Using a survey (n=10,487) sent to rule violators on Twitter paired with an analysis of participants’ platform behaviors, this study looks at the relationship between people’s judgments of the procedural justice of an enforcement action and the participants’ likelihood of reoffending in the future. We find that those who felt more fairly treated during their enforcement were less likely to recidivate (beta = -.05, p &lt; .001). This, along with the study’s other findings, indicates an opportunity for platforms to put a stronger focus on people’s experience with enforcement systems as a potential pathway for reducing recidivism.
Quantum Computing in Supply Chain Management State of the Art and Research Directions

Quantum computing is the most promising computational advance of the coming decade for solving the most challenging problems in supply chain management and logistics. This paper reviews the state-of-the-art of quantum computing and provides directions for future research. First, general concepts relevant to quantum computers and quantum computing are introduced. Second, the dominating quantum technologies are presented. Third, the quantum industry is analyzed, and recent applications in different fields of supply chain management and logistics are illustrated. Fourth, directions for future research are given. We hope this review to educate and inspire the use of quantum computing in the fields of optimization, artificial intelligence, and machine learning for supply chain and logistics.
Impact of Innovation Types on Enterprises Sales Growth: Evidence from Kosovo

This paper aims to analyze the impact of the types of innovations in increasing the sales of Kosovo's enterprises. The findings of this paper confirm the hypotheses that organizational innovations, product/process innovations and marketing innovations have a positive impact on increasing the level of sales. This empirical research was conducted with enterprises in Kosovo, so the main limitation of this research is the non-inclusion of enterprises of Albania, Montenegro, North Macedonia, Bosnia and Herzegovina, etc. The involvement of enterprises from these countries would provide a broader picture of the research issues for transition countries. This empirical research is of particular importance because it studies the impact of types of innovation on increasing the sales level of enterprises in transition countries. Kosovo suffer from weak enterprises sector and underdeveloped entrepreneurship sector. Without the development of an innovative system of the private sector and the entrepreneurial sector, Kosovo cannot overcome the transition process. Therefore, this paper could be a reference point for the government policies of Kosovo, which should support all enterprises in the development of all types of innovations.