Reviewerly/exHarmony huggingface dataset:
Distillation of genuine tripartite Einstein-Podolsky-Rosen steering

We show that a perfectly genuine tripartite steerable assemblage can be distilled from partially genuine tripartite EPR steerable assemblages. In particular, we consider two types of hybrid scenarios: one-sided device-independent scenario (where one observer is untrusted, and other two observers are trusted) and two-sided device-independent scenario (where two observers are untrusted, and one observer is trusted). In both scenarios, we show distillation of perfectly genuine steerable assemblage of three-qubit Greenberger-Horne-Zeilinger states or three-qubit W states from many copies of initial partially genuine steerable assemblages of the corresponding states. In each of these cases, we demonstrate that at least one copy of a perfectly genuine steerable assemblage can be distilled with certainty from infinitely many copies of initial assemblages. In case of practical scenarios employing finite copies, we show that the efficiency of our distillation protocols reaches near perfect levels using only a few number of initial assemblages.
Blockchain Is Top Skill For 2020

This research aims to learn why Blockchain Technology can be the most demanding hard skills in companies in 2020 as quoted from LinkedIn and the positive impact that Blockchain Technology has on a company. If we see, at this time usually requires at least a third party to make a transaction, and a company usually only stores data / information on a centralized server which makes the data easy to hack. From this case, Blockchain technology can be used as a way out for a company to make data / information not easy to be hacked. Because, Blockchain uses a distributed server system that is validated, which makes Blockchain safer from evil parties who want to hack information, and Blockchain has other advantages such as more cost-effective, better transparency and traceability. Therefore Blockchain Technology is a particular attraction for a company and is the hard skill most demanded by the company in 2020.
Eigenvalues of two-phase quantum walks with one defect in one dimension

We study space-inhomogeneous quantum walks (QWs) on the integer lattice which we assign three different coin matrices to the positive part, the negative part, and the origin, respectively. We call them two-phase QWs with one defect. They cover one-defect and two-phase QWs, which have been intensively researched. Localization is one of the most characteristic properties of QWs, and various types of two-phase QWs with one defect exhibit localization. Moreover, the existence of eigenvalues is deeply related to localization. In this paper, we obtain a necessary and sufficient condition for the existence of eigenvalues. Our analytical methods are mainly based on the transfer matrix, a useful tool to generate the generalized eigenfunctions. Furthermore, we explicitly derive eigenvalues for some classes of two-phase QWs with one defect, and illustrate the range of eigenvalues on unit circles with figures. Our results include some results in previous studies, e.g., Endo et al. (Entropy 22(1):127, 2020).
Recommender Systems and Collaborative Filtering

Recommender Systems (RSs) have become an essential tool for the information society [...]
Device-independent quantification of measurement incompatibility

Incompatible measurements, i.e., measurements that cannot be simultaneously performed, are necessary to observe nonlocal correlations. It is natural to ask, e.g., how incompatible the measurements have to be to achieve a certain violation of a Bell inequality. In this paper, we provide the direct link between Bell nonlocality and the quantification of measurement incompatibility. This includes quantifiers for both incompatible and genuine-multipartite incompatible measurements. Our method straightforwardly generalizes to include constraints on the system's dimension (semi-device-independent approach) and on projective measurements, providing improved bounds on incompatibility quantifiers, and to include the prepare-and-measure scenario.Received 2 November 2020Revised 2 April 2021Accepted 30 April 2021DOI:https://doi.org/10.1103/PhysRevResearch.3.023143Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.Published by the American Physical SocietyPhysics Subject Headings (PhySH)Research AreasNonlocalityQuantum correlations in quantum informationQuantum measurementsQuantum InformationGeneral Physics
Mineralogical Setting of Precious Metals at the Assarel Porphyry Copper-Gold Deposit, Bulgaria, as Supporting Information for the Development of New Drill Core 3D XCT-XRF Scanning Technology

A petrographic investigation of ore samples from the Assarel porphyry copper deposit in the Srednogorie metallogenic zone (Bulgaria) constrains the setting and character of precious metals (Au, Ag, PGE) and related minerals within the deposit. This work supports renewed interest in understanding the deportment of precious metals and provides mineralogical knowledge during the testing and validation of novel drill core 3D X-ray computed tomography–X-ray fluorescence (XCT-XRF) scanning technology being developed as part of the X-MINE project. Scanning electron microscopy–energy dispersive spectrometry (SEM-EDS) results indicate precious metals occur in their native state (Au, Ag), as sulfides (Ag), sulfosalts (Au), tellurides (Ag, Pd), and selenides (Ag), and typically form micron-sized inclusions in pyrite and chalcopyrite or are disseminated in the groundmass of the rock. Preservation of early Fe oxide–chalcopyrite ± bornite assemblage as relics in the more dominant pyrite-chalcopyrite mineralization assemblage supports mineral disequilibrium relationships and multi-stage mineralization events. Several rare minerals (e.g., merenskyite, acanthite, sorosite, tetra-auricupride, auricupride, greenokite, bismuthinite, nagyagite, native Ni) are reported for the first time at Assarel and highlight the mineralogical diversity of the ore. The occurrence of precious metals and related minerals at Assarel attest to a complex hydrothermal system that underwent progressive physicochemical changes during the evolution of the mineralizing system (e.g., redox conditions, fluid chemistry).
An Integrated Decision Approach with Probabilistic Linguistic Information for Test Case Prioritization

This paper focuses on an exciting and essential problem in software companies. The software life cycle includes testing software, which is often time-consuming, and is a critical phase in the software development process. To reduce time spent on testing and to maintain software quality, the idea of a systematic selection of test cases is needed. Attracted by the claim, researchers presented test case prioritization (TCP) by applying the concepts of multi-criteria decision-making (MCDM). However, the literature on TCP suffers from the following issues: (i) difficulty in properly handling uncertainty; (ii) systematic evaluation of criteria by understanding the hesitation of experts; and (iii) rational prioritization of test cases by considering the nature of criteria. Motivated by these issues, an integrated approach is put forward that could circumvent the problem in this paper. The main aim of this research is to develop a decision model with integrated methods for TCP. The core importance of the proposed model is to (i) provide a systematic/methodical decision on TCP with a reduction in testing time and cost; (ii) help software personnel choose an apt test case from the suite for testing software; (iii) reduce human bias by mitigating intervention of personnel in the decision process. To this end, probabilistic linguistic information (PLI) is adopted as the preference structure that could flexibly handle uncertainty by associating occurrence probability to each linguistic term. Furthermore, an attitude-based entropy measure is presented for criteria weight calculation, and finally, the EDAS ranking method is extended to PLI for TCP. An empirical study of TCP in a software company is presented to certify the integrated approach’s effectiveness. The strengths and weaknesses of the introduced approach are conferred by comparing it with the relevant methods.
Grapevine: A <scp>profile‐based</scp> exploratory search and recommendation system for finding research advisors

Abstract Finding research advisors is an important and challenging task for college students. On one hand, a research advisor that matches student interests and past preparation could fully engage the student with an exciting and productive research experience. On the other hand, students are frequently unable to formulate their interests and experience in a way that allows them to independently find the most compatible advisors using search and browsing tools. This paper reports our experience with designing and evaluating Grapevine , an exploratory search and recommender system aimed at helping students, especially those less prepared and underrepresented in certain fields, find research advisors.
The effect of accounting information system on corporate governance

In this study, (72) financial managers and managers of the accounting department within the pharmaceutical industry in Jordan during the fiscal year 2019-2020 were exposed to a questionnaire in order to examine the influence of AIS applications on the outcomes of accounting corporate governance. Researcher adopted accounting governance variables from different studies and included Control, Commitment to Accounting Standards, Performance Evaluation and Add Confidence and Credibility to the survey. Results of study indicated an influence of all given variables of accounting governance on the outcomes of corporate governance which is attributed to the quality of accounting information and making sure that all information given are based on the standards of accounting. Some recommendations were presented with the study later on.
Prediction of English Scores of College Students Based on Multi-source Data Fusion and Social Behavior Analysis

Multi-source data fusion is the premise of applying big data technology in specific fields. Inspired by the theory on multi-source data fusion, this paper fuses various data on college students, including motion trajectories, consumptions, and social behaviors, and adopts support vector machine (SVM), a machine learning (ML) classifier to predict the English scores of college students. The behavior trajectories were taken into account, because this type of data represents the social similarity between students. Specifically, the behavioral features of college students were extracted, and subject to principal component analysis (PCA). Based on these features, the correlation between student score and social relation was analyzed, and used to predict the English scores of college students. Experimental results show that our method can accurately reflect the relationship between the social behaviors and course scores of college students.
Different valuable tools for Arabic sentiment analysis: a comparative evaluation

Arabic Natural language processing (ANLP) is a subfield of artificial intelligence (AI) that tries to build various applications in the Arabic language like Arabic sentiment analysis (ASA) that is the operation of classifying the feelings and emotions expressed for defining the attitude of the writer (neutral, negative or positive). In order to work on ASA, researchers can use various tools in their research projects without explaining the cause behind this use, or they choose a set of libraries according to their knowledge about a specific programming language. Because of their libraries' abundance in the ANLP field, especially in ASA, we are relying on JAVA and Python programming languages in our research work. This paper relies on making an in-depth comparative evaluation of different valuable Python and Java libraries to deduce the most useful ones in Arabic sentiment analysis (ASA). According to a large variety of great and influential works in the domain of ASA, we deduce that the NLTK, Gensim and TextBlob libraries are the most useful for Python ASA task. In connection with Java ASA libraries, we conclude that Weka and CoreNLP tools are the most used, and they have great results in this research domain.
Learning Management STEAM Model on Massive Open Online Courses Using Augmented Reality to Enhance Creativity and Innovation

The purposes of this study were: 1) design Learning Management STEAM Model on Massive Open Online Courses Using Augmented Reality to enhance Creativity and Innovation, 2) suitability assessment of a Learning Management STEAM Model on Massive Open Online Courses Using Augmented Reality to enhance Creativity and Innovation. The research methodology was composed of two parts: the first part involved theories and research papers relating to massive open online courses, augmented reality, elements synthesis, and the design of a Learning Management STEAM Model on Massive Open Online Courses Using Augmented Reality to enhance Creativity and Innovation; the second part involved suitability assessment of this approach. Data were analyzed by using the statistic of the mathematic mean (x̄) and standard deviation (S.D.). The overall result with regard to the suitability of a Learning Management STEAM Model on Massive Open Online Courses Using Augmented Reality to enhance Creativity and Innovation by seven experts was assessed at a very high level, which can be applied to real situations.
Self-Organisation in Lifelong Learning: Theory, Practice and Implementation Experience Involving Social Networks and a Remote Format

Currently, in the context of the global transition of the world education system to the remote format, it has become vitally important for a person to be able and ready to independently organise his/her educational and professional activities. The article considers methodological approaches to self-education in the context of its use in the process of lifelong learning/ continuous education. The authors discuss the existing concepts of self-education and ways of its organisation, taking into account age-specific features, forms and types of learning. The concepts of ‘self-organisation’ and ‘self-education’ are analysed. The essence of the scientific categories ‘self-learning’ and ‘self-organisation in education’ is revealed in relation to the system of higher education. The role of tutors as mediators in student self-organisation is shown and their main functions in this process are described. Based on a theoretical analysis of existing forms of self-organisation in education and the experience of using self-organisation, various directions and possibilities of their application in practice are delineated. Careful consideration is given to criticism of the use of self-organisation in learning and its advantages. The authors also discuss the prospects of using self-organisation in higher education, emphasising the importance and relevance of developing self-organisation as a student’s personality trait. A description is made of learning models based on self-organisation of students. Finally, the experience of implementing the self-organisation approach to the educational process is analysed. As a result of the study, the authors conclude that self-learning can be successful if it seems socially significant for students. The use of advanced digital technologies and Internet resources can also contribute to effective self-learning. The results of the study indicate that students should develop the ability to independently organise their educational activities as well as self-control/self-assessment skills, which is especially important in connection with the increase in independent work in curricula and the massive transition to the remote format in higher education during the COVID-19 pandemic.
Cartolabe: A Web-Based Scalable Visualization of Large Document Collections

We describe Cartolabe, a web-based multiscale system for visualizing and exploring large textual corpora based on topics, introducing a novel mechanism for the progressive visualization of filtering queries. Initially designed to represent and navigate through scientific publications in different disciplines, Cartolabe has evolved to become a generic framework and accommodate various corpora, ranging from Wikipedia (4.5M entries) to the French National Debate (4.3M entries). Cartolabe is made of two modules: The first relies on natural language processing methods, converting a corpus and its entities (documents, authors, and concepts) into high-dimensional vectors, computing their projection on the two-dimensional plane, and extracting meaningful labels for regions of the plane. The second module is a web-based visualization, displaying tiles computed from the multidimensional projection of the corpus using the Umap projection method. This visualization module aims at enabling users with no expertise in visualization and data analysis to get an overview of their corpus, and to interact with it: exploring, querying, filtering, panning, and zooming on regions of semantic interest. Three use cases are discussed to illustrate Cartolabe's versatility and ability to bring large-scale textual corpus visualization and exploration to a wide audience.
Transforming graph states to Bell-pairs is NP-Complete

Critical to the construction of large scale quantum networks, i.e. a quantum internet, is the development of fast algorithms for managing entanglement present in the network. One fundamental building block for a quantum internet is the distribution of Bell pairs between distant nodes in the network. Here we focus on the problem of transforming multipartite entangled states into the tensor product of bipartite Bell pairs between specific nodes using only a certain class of local operations and classical communication. In particular we study the problem of deciding whether a given graph state, and in general a stabilizer state, can be transformed into a set of Bell pairs on specific vertices using only single-qubit Clifford operations, single-qubit Pauli measurements and classical communication. We prove that this problem is <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow class="MJX-TeXAtom-ORD"><mml:mrow class="MJX-TeXAtom-ORD"><mml:mi mathvariant="double-struck">N</mml:mi><mml:mi mathvariant="double-struck">P</mml:mi></mml:mrow></mml:mrow></mml:math>-Complete.
CGTR

Contextualized neural language models have gained much attention in Information Retrieval (IR) with its ability to achieve better text understanding by capturing contextual structure. However, to achieve better document understanding, it is necessary to involve global structure of a document. In this paper, we take the advantage of Graph Convolutional Networks (GCN) to model global word-relation structure of a document to improve context-aware document ranking. We propose to build a graph for a document to model the global structure. The nodes and edges of the graph are constructed from contextual embeddings. Then we apply graph convolution on the graph to learning a new representation, and this representation covers both contextual and global structure information. The experimental results show that our method outperforms the state-of-the-art contextual language models, which demonstrate that incorporating global structure is useful for improving document ranking and GCN is an effective way to achieve it.
Simultaneous Feature Selection and Classification for Data-Adaptive Kernel-Penalized SVM

Simultaneous feature selection and classification have been explored in the literature to extend the support vector machine (SVM) techniques by adding penalty terms to the loss function directly. However, it is the kernel function that controls the performance of the SVM, and an imbalance in the data will deteriorate the performance of an SVM. In this paper, we examine a new method of simultaneous feature selection and binary classification. Instead of incorporating the standard loss function of the SVM, a penalty is added to the data-adaptive kernel function directly to control the performance of the SVM, by firstly conformally transforming the kernel functions of the SVM, and then re-conducting an SVM classifier based on the sparse features selected. Both convex and non-convex penalties, such as least absolute shrinkage and selection (LASSO), moothly clipped absolute deviation (SCAD) and minimax concave penalty (MCP) are explored, and the oracle property of the estimator is established accordingly. An iterative optimization procedure is applied as there is no analytic form of the estimated coefficients available. Numerical comparisons show that the proposed method outperforms the competitors considered when data are imbalanced, and it performs similarly to the competitors when data are balanced. The method can be easily applied in medical images from different platforms.
Exploring the Use of Olfactory Stimuli Towards Reducing Visually Induced Motion Sickness in Virtual Reality

Visually Induced Motion Sickness (VIMS) plagues a significant number of individuals who utilize Virtual Reality (VR) systems. Although several solutions have been proposed that aim to reduce the onset of VIMS, a reliable approach for moderating it within VR experiences has not yet been established. Here, we set the initial stage to explore the use of controlled olfactory stimuli towards reducing symptoms associated with VIMS. In this experimental study, participants perceived different olfactory stimuli while experiencing a first-person-view rollercoaster simulation using a VR Head-Mounted Display (HMD). The onsets of VIMS symptoms were analyzed using both the Simulator Sickness Questionnaire (SSQ) and the Fast Motion Sickness Scale (FMS). Notable reductions in overall SSQ and FMS scores suggest that providing a peppermint aroma reduces the severity of VIMS symptoms experienced in VR. Additional anecdotal feedback and potential future studies on using controlled olfactory stimuli to minimize the occurrence of VIMS symptoms are also discussed.