Reviewerly/exHarmony huggingface dataset:
Erato: Cooperative Data Story Editing via Fact Interpolation

As an effective form of narrative visualization, visual data stories are widely used in data-driven storytelling to communicate complex insights and support data understanding. Although important, they are difficult to create, as a variety of interdisciplinary skills, such as data analysis and design, are required. In this work, we introduce Erato, a human-machine cooperative data story editing system, which allows users to generate insightful and fluent data stories together with the computer. Specifically, Erato only requires a number of keyframes provided by the user to briefly describe the topic and structure of a data story. Meanwhile, our system leverages a novel interpolation algorithm to help users insert intermediate frames between the keyframes to smooth the transition. We evaluated the effectiveness and usefulness of the Erato system via a series of evaluations including a Turing test, a controlled user study, a performance validation, and interviews with three expert users. The evaluation results showed that the proposed interpolation technique was able to generate coherent story content and help users create data stories more efficiently.
FSS: A Flexible Scaling Scheme for Blockchain Based on Stale Block Rate

In blockchain, there has long been a contradiction between the limited ability and the uncertain requirements of processing transactions, which seriously restricts the practical application of blockchain. Therefore, how to improve the scalability of blockchain has become an urgent issue to be solved. Some existing works have achieved blockchain expansion through increasing the upper limit of block size permanently, which makes the trade-off of the “Mundellian Trilemma ” in blockchain (i.e. a blockchain system cannot be optimal in all the three dimensions of scalability, security and decentralization at the same time) fixed and thus not adapted to the dynamic environment. In this paper, we propose FSS, a flexible scaling scheme for blockchain based on stale block rate, which dynamically adjusts the upper limit of block size according to the stale block rate, not only expanding the blockchain when allowed, but also shrinking it when necessary. Experimental results indicate that FSS can reasonably improve the scalability of blockchain with required stale block rate.
Automatic Distributed Control Method for Indoor Low-Voltage Electricity Based on Modal Symmetry Algorithm

The traditional control method has a low margin of indoor voltage stability, which can easily lead to voltage collapse, and the control effect is not ideal. An automatic distributed control method for indoor low-voltage electricity system based on modal symmetry algorithm is proposed. In order to improve the voltage stability margin, the decoupling between the indoor low-voltage electricity characteristics and regions was analyzed. Based on the analysis results, the decoupling between regions and the robustness to faults of the distributed zone scheme were considered comprehensively, and the modularity and the optimal zoning scheme were screened. Based on the principle of modal symmetry, the original data of the distributed control matrix of low-voltage electricity was obtained. Mean standardization method was used to standardize the matrix, so as to realize the distributed control of indoor low-voltage electricity. The experimental results show that the proposed method improves the margin of voltage stability, overcomes the drawbacks of traditional methods, and reduces the probability of voltage accidents. It shows that this method has higher flexibility, higher reliability, and higher application value as well as improving the automatic control level of voltage.
Fast population transfer with a superconducting qutrit via non-Hermitian shortcut to adiabaticity

Non-Hermitian dissipation dynamics, capable of turning the conventionally detrimental decoherence effects to useful resources for state engineering, is highly attractive to quantum information processing. In this work, an effective scheme is developed for implementing fast population transfer with a superconducting qutrit via the non-Hermitian shortcut to adiabaticity (STA). We first deal with a Λ-configuration interaction between the qutrit and microwave drivings, in which the dephasing-assisted qubit state inversion requiring an overlarge dephasing rate is constructed non-adiabatically. After introducing a feasible ancillary driving that directly acts upon the qubit states, the target state transfer can be well realized but with an accessible qubit dephasing rate. Moreover, a high fidelity could be numerically obtained in the considered system. The strategy could provide a new route towards the non-Hermitian shortcut operations on superconducting quantum circuits.
Realistic conversion of single-mode squeezed vacuum state to large-amplitude high-fidelity Schrödinger cat states by inefficient photon number resolving detection

Abstract We theoretically propose an efficient way to generate optical analogs of both even and odd Schrӧdinger cat states (SCSs) of large amplitude with high fidelity and reasonable generation rate. The resources consumed are a single-mode squeezed vacuum state (SMSV) and possibly a single photon or nothing. We report the generation of even (odd) SCS with amplitude <?CDATA $4.2,$?> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mn>4.2</mml:mn> <mml:mo>,</mml:mo> </mml:math> fidelity higher than <?CDATA $0.99$?> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mn>0.99</mml:mn> </mml:math> with success probability a little more than <?CDATA ${10}^{-7}$?> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:msup> <mml:mrow> <mml:mn>10</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>7</mml:mn> </mml:mrow> </mml:msup> </mml:math> by subtraction of <?CDATA $30(31)$?> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mn>30</mml:mn> <mml:mo stretchy="false">(</mml:mo> <mml:mn>31</mml:mn> <mml:mo stretchy="false">)</mml:mo> </mml:math> photons from SMSV by ideal photon number detection. In order to reduce the requirements for the sensitivity of photon number resolving (PNR) detector, we show the implementation of even/odd SCSs with the same characteristics with two PNR detectors resolving only <?CDATA $15$?> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mn>15</mml:mn> </mml:math> photons each instead of <?CDATA $30.$?> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mn>30</mml:mn> <mml:mo>.</mml:mo> </mml:math> In the case of inefficient detector, SCS’s size and its fidelity can be kept close to perfect by using highly transmitting beam splitter, but at the cost of very dramatic reduction of the success probability. In order to have certain harmony between the characteristics (large amplitude, high fidelity and acceptable success probability) in the case of imperfect detection, highly transmitting beam splitters should not be used and number of the subtracted photons must be reduced to <?CDATA $10\left(11\right).$?> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mn>10</mml:mn> <mml:mrow> <mml:mfenced close=")" open="("> <mml:mrow> <mml:mn>11</mml:mn> </mml:mrow> </mml:mfenced> </mml:mrow> <mml:mo>.</mml:mo> </mml:math>
An Exploration of Cultivation Strategies of English Core Literacy--Based on the Transformation of the Traditional Primary Classroom

The primary classroom is an important occasion for cultivating English core literacy. Problems such as insufficiency of form and content of teaching materials, uneven level of teachers' informatization, the lack of classroom ecology and the lack of students' comprehensive quality, make teaching unable to meet the requirements of cultivating inter-disciplinary talents in the big data era. Efforts should be made to improve the effectiveness of English classroom teaching in primary school and to transform the classroom to adapt to the social development. According to the requirements of English core literacy, strategies will be proposed for the transformation of primary English classrooms in four aspects: building an ecological classroom, optimizing the content and form of teaching materials, establishing students' awareness of deep learning, and improving teachers' professional level, in order to provide references for classroom transformation as the request of times as well as promote the implementation of English core literacy.
Stages of development of the system of additional professional education of scientific and pedagogical personnel in Russian universities

Despite the urgency of the problem of staging the development of the system of additional professional education of scientific and pedagogical personnel of Russian universities, this issue has not been sufficiently developed in scientific and pedagogical research. The prerequisites and factors of the formation of the system of additional professional education of the teaching staff in domestic universities have not been fully studied; there is no clear idea of the criteria for the allocation of stages and the essential characteristics of each of the stages of the development of the system of additional professional education of teachers. The purpose of the study is to substantiate the stages of development of additional professional education of scientific and pedagogical personnel of Russian universities from the 20s of the twentieth century to the present on the basis of historical and retrospective analysis. Methodology and methods. The methodological basis of the study was the principles of historicism, systematicity development, ideas about the universal connection and interdependence of political, economic, social and educational processes and phenomena. The research methods are: analysis of research, historical-retrospective and historical–genetic analysis of the problem under study. Results. The paper shows the relationship between the development of the system of additional professional education of scientific and pedagogical personnel of Russian universities with socio-political and economic transformations in the country. The prerequisites for the emergence of a system of additional professional education in the USSR for the teaching staff of universities from the 1920-s to 1992 are presented. The essential characteristics of the formation stage of the system under study from 2002 to 2012, as well as the stage of its further development from 2012 to the present, are emphasized and disclosed.
MosaicSets: Embedding Set Systems into Grid Graphs

Visualizing sets of elements and their relations is an important research area in information visualization. In this paper, we present <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">MosaicSets</i> : a novel approach to create Euler-like diagrams from non-spatial set systems such that each element occupies one cell of a regular hexagonal or square grid. The main challenge is to find an assignment of the elements to the grid cells such that each set constitutes a contiguous region. As use case, we consider the research groups of a university faculty as elements, and the departments and joint research projects as sets. We aim at finding a suitable mapping between the research groups and the grid cells such that the department structure forms a base map layout. Our objectives are to optimize both the compactness of the entirety of all cells and of each set by itself. We show that computing the mapping is NP-hard. However, using integer linear programming we can solve real-world instances optimally within a few seconds. Moreover, we propose a relaxation of the contiguity requirement to visualize otherwise non-embeddable set systems. We present and discuss different rendering styles for the set overlays. Based on a case study with real-world data, our evaluation comprises quantitative measures as well as expert interviews.
A Weakly-supervised Method for Encrypted Malicious Traffic Detection

In order to defend against complex threats and attacks in cyberspace, IHEPSOC has been developed and deployed at the Institute of High Energy Physics Chinese Academy of Sciences (IHEP), which is considered as an integrated security operation platform to ensure a secure state of the network and scientific researches in IHEP.Nowadays the integration of the state-of-the-art cyber-attack detection algorithms for IHEPSOC has become an important task for enhancing the attack discovery capability of IHEPSOC.Meanwhile, malicious traffic detection comes to be increasingly challenging.With the extensive application of data encryption techniques to protect communication security and privacy, malicious software could also hide their attack information, making most of malicious traffic identification methods such as port-based methods and DPI (Deep Packet Inspection)-based methods ineffective.Machine learning based detection methods have been proposed to address the encrypted malicious traffic detection problem, which usually involve constructing statistical features of internet traffic flow and training classification models for detecting encrypted malicious traffic.There are some drawbacks in the above-mentioned detection methods.First of all, feature selection is a timeconsuming procedure that depends on expert experience.Secondly, most traffic classification schemes employ supervised learning methods, and the acquisition of large fine-grained labeled datasets is a tedious task.In this paper, we propose a weakly-supervised method for encrypted malicious traffic detection, which combines the generative adversarial network (GAN) and the multiple instance learning detector to achieve the fine-grained classification of encrypted traffic with a small number of coarse-grained labeled samples and a large number of unlabeled samples.Thus, we could focus on the accuracy of the malware detector instead of spending efforts on dataset annotation with the weakly-supervised learning approach.To start with, we convert the traffic data into single-channel grayscale images in the proposed method, and then input them into the GAN, so that the original traffic features can be learned without manual effort.Therefore, the improved semi-supervised learning generative adversarial network, which is based upon convolution neural network (CNN) architecture, generates more synthetic samples for data augmentation and addresses the insufficiency of labeled samples.In addition, a multi-instance detector with an attention mechanism is used to identify encrypted malicious traffic from coarsegrained labeled data.We validate the proposed approach on two public datasets.Compared with other malicious traffic detection methods, the experimental results show that our proposed framework can effectively perform fine-grained detection of encrypted malicious traffic.
Quantum Implementation of Reversible Logic Gates Using RCViewer+ Tool

To investigate the quantum implementation method for estimation of quantum cost of reversible logic gates, proposed quantum implementation method is used for estimation of quantum cost of reversible logic gates and further verification using RCViewer+tool to justify quantum cost. Proposed quantum implementation method is applied on R gate and tested using RCViewer+ tool to justify quantum cost. The quantum implementation and related quantum cost of many invented gates are still unknown in literature. This paper deals with the approach to determine quantum implementation of reversible logic gates so that it can be beneficial to utilize processes in investigation of new proposed reversible logic gates and their associated architectures.
Towards regional scientific integration in Africa? Evidence from co-publications

Regional scientific integration is a critical pathway for the development of an integrated African research area and knowledge-based society. On the African continent, progress in scientific production and integration has remained limited, mostly led by a global or international agenda, and bound to a few top publishing nations. The high-level policy commitments and the accumulated policies and strategies developed and pursued under the various intertwined sub-regional economic groupings have, to date, only diversely contributed to policy alignment and coordination in the area of science, technology, and innovation (STI) across Africa. In this context, this paper provides a first and hence original assessment of the role of region-specific factors in shaping scientific collaboration on the continent. For this purpose, our study builds upon the proximity approach to analyse the determinants of scientific collaboration between African countries, using co-publications data from Thomson Reuters' Web of Science database as a proxy of such collaboration. Our results suggest that the majority of African regional economic communities (RECs) have not yet had a significant effect on scientific co-publication. Nevertheless, some important region-specific factors do seem to be at play, such as a shared ethnical language, membership in the African and Malagasy Council for Higher Education (CAMES), and the presence of a common European partner as a third partner in co-publication. Existing policies aimed at the development of an Africa-wide research area should aim to leverage existing and emerging regional excellence networks and novel coordination models to accelerate the process of scientific integration in Africa.
A Conceptual Study on the Tole of Human Resources Practices on Employee Performance in the Yemeni Universities

The main objective of the current study is to conceptualize a framework that contains relationships between Compensation and benefits, Training and development, Performance appraisal, and Job satisfaction as Human Resources Practices with Employee Performance in the Yemeni Universities. To achieve this objective, 30 respondents were selected to participate in a pilot study. The results of the current study shows that the framework that contain Compensation and benefits, Training and development, Performance appraisal, and Job satisfaction with Employee Performance showed a sufficient Reliability and Validity, as the results of the Cronbach Alpha of the items scale were all above 0.7, while the Pearson Correlation between the variables were all significant at the level of 0.05.
New Strategy Based on RBF Network to Develop a Collaborative Filtering Recommender System

Collaborative filtering is a popular recommendation algorithm. It predicts user's interests according to the ratings or behaviour of other users in the system. However, the collaborative filtering recommender system suffers from several major limitations including scalability, sparsity, and cold start. In this paper, a collaborative filtering recommendation approach using radial basis function (RBF) network and power method is proposed. The proposed system has offline and online phases. In the offline phase, the sparse user-item rating matrix is completed by using RBF network based on Cover's theorem on the separability of patterns. RBF network learning is done by unsupervised kernel-based fuzzy c-means clustering algorithm for selecting RBF centers, and supervised gradient descend method for selecting RBF weights. In the offline phase, we predict non-rated items of a user. Then the full rating matrix is used to rank all the users. The ranking is done by solving an eigenvalue problem. This paper overcomes the scalability problem by clustering the users, the sparsity problem by completing the sparse rating matrix, and the new user cold start problem by recommending the top rated items of the high-ranked user. The results of the experiments, on the benchmark data sets, show that the proposed system produces high quality recommendation, in terms of accuracy and quality.
Data-driven lemma synthesis for interactive proofs

Interactive proofs of theorems often require auxiliary helper lemmas to prove the desired theorem. Existing approaches for automatically synthesizing helper lemmas fall into two broad categories. Some approaches are goal-directed, producing lemmas specifically to help a user make progress from a given proof state, but they have limited expressiveness in terms of the lemmas that can be produced. Other approaches are highly expressive, able to generate arbitrary lemmas from a given grammar, but they are completely undirected and hence not amenable to interactive usage. In this paper, we develop an approach to lemma synthesis that is both goal-directed and expressive. The key novelty is a technique for reducing lemma synthesis to a data-driven program synthesis problem, whereby examples for synthesis are generated from the current proof state. We also describe a technique to systematically introduce new variables for lemma synthesis, as well as techniques for filtering and ranking candidate lemmas for presentation to the user. We implement these ideas in a tool called lfind, which can be run as a Coq tactic. In an evaluation on four benchmark suites, lfind produces useful lemmas in 68% of the cases where a human prover used a lemma to make progress. In these cases lfind synthesizes a lemma that either enables a fully automated proof of the original goal or that matches the human-provided lemma.
Improved graph formalism for quantum circuit simulation

Improving the simulation of quantum circuits on classical computers is important for understanding quantum advantage and increasing development speed. In this paper, we explore a way to express stabilizer states and further improve the speed of simulating stabilizer circuits with a current existing approach. First, we discover a unique and elegant canonical form for stabilizer states based on graph states to better represent stabilizer states and show how to efficiently simplify stabilizer states to canonical form. Second, we develop an improved algorithm for graph state stabilizer simulation and establish limitations on reducing the quadratic runtime of applying controlled Pauli $Z$ gates. We do so by creating a simpler formula for combining two Pauli-related stabilizer states into one. Third, to better understand the linear dependence of stabilizer states, we characterize all linearly dependent triplets, revealing symmetries in the inner products. Using our controlled Pauli $Z$ algorithm, we improve runtime for inner product computation from $O({n}^{3})$ to $O(n{d}^{2})$, where $d$ is the maximum degree of the graph encountered during the calculation.
Improving Visual Search Tasks by Bending the Virtual City Twins: A Preliminary Study in Virtual Reality

Visually searching for physical entities can be challenging as other entities often block the targets. The rapid advancement of head-mounted displays (HMDs) and cyber-physical mappings in smart cities may offer an alternative solution, where users can quickly locate the target by manipulating the digital representations of their surrounding environments. For example, a user wearing an HMD can reveal the hidden target by “lifting” the cyber world to create a curved virtual map on top of the physical world.
Research on the Development Direction and Service Innovation of Foreign-funded Industries in Pudong New Area During COVID-19

In 2020, more than half of the top 100 foreign-invested enterprises in Shanghai came from Pudong.Foreign-invested enterprises have played a supporting role in Shanghai's economic development.The epidemic has a serious impact on foreign-funded enterprises in China, which may lead to the loss of foreign capital.Based on the theory of crisis management and service innovation, this study summarizes the strategic trends of three key industries in Pudong New Area, logistics and transportation, artificial intelligence and semiconductor industries in China, and puts forward the Countermeasures of service innovation based on the service status of Pudong New Area High Tech Park to foreign enterprises.