Reviewerly/exHarmony huggingface dataset:
A Polytechnic University on the Modern Market of Online Education (the Case of Peter the Great St. Petersburg Polytechnic University)

The article deals with the current situation and the prospects for changing the role of Russian technical universities on the domestic and world markets of online education. The study was carried out taking into account a number of relevant factors that determine the development of e-learning in leading Russian technical universities, in particular, the provisions of the “Priority 2030” program, as well as the introduction of distance and blended learning formats in the context of preventing the spread of COVID-19 in 2020–2021. The empirical base of the study is the results of processing the data from leading Russian and international online educational platforms, as well as published sociological surveys of teachers and students from Russian universities. The key conclusion of the study is in stating the need of revision of the development directions of a distributed e-learning system in Russian universities and the development/implementation of online programs. Moreover, the authors emphasize the need to increase the number and quality of online modules on domestic and international platforms, to master up-to-date online educational products and thoroughly renovate the content of the courses and programs being implemented, and to improve digital competencies and the involvement of the faculty in the development of e-learning.
To the Question of Humanistic Paradigm Synthesis in Innovative Engineering Education

The article considers, in the context of civilizational synthesis, some possibilities for achieving the harmonization of engineering education in the innovative cultural and educational university space based on the synthesis of personality-oriented and humanistic-hermeneutic paradigms in order to substantiate the ontological and methodological status of hermeneutic pedagogy. The explication of heuristic and aesthetic experience is considered as a condition for modern humanistic and conceptual thinking, which is necessary in the era of digital technologies, which develops at the level of the cultural and educational space of the university through collaboration with cultural institutions and on the basis of humanistic and aesthetically oriented educational programs. On the basis of a humanistic paradigm synthesis, a dynamically developing range of competencies of future engineers is presented: the special competencies of engineers are supplemented not only by modern technological competencies, but also by universal competencies: hermeneutic culture, creativity, communication, value orientation of the visionary, strategic thinking, modeling, design, moderation; intercultural competencies: knowledge of foreign languages, the basics of intercultural communication, taking into account the peculiarities of ethnic culture and mentality; social competencies: conflict resolution skills, finding compromises, learning and teaching skills, coaching, feedback, empowerment; personal competencies: flexibility, tolerance for frustration and ambiguous opinions, empathy, self-reflection, honesty and authenticity; cultural and aesthetic competencies in literature, music, fine arts, as well as ethical and environmental competencies.
Methodological Prerequisites for the Integration of Modern Paradigms of Engineering and Humanities Education

The article presents an analysis of modern research aimed at improving existing and building new theoretical models of education. In the context of the industrial revolution “Industry 4.0” in science, along with the most common models, such as personality-oriented, engineering, etc., many other models are used that meet the specifics of education. The literature review also shows that innovation models are an improvement on one of the existing basic paradigms, which brings them closer and increases the possibility of subsequent integration. This indicates the relevance of the formation of a new holistic paradigm of education. The logic of scientific and technological progress also leads to the unification of engineering and humanitarian paradigms. A feature of the methodology of the 6th technological order (Glazyev) is that its key factors, in addition to technical sciences, are cognitive sciences and socio-humanitarian knowledge. The study confirms the need to include the humanities in the content of modern professional engineering education. As a result of the study, it was concluded that further productive technological development of society requires the unification of disparate educational models into a single modern educational paradigm. The fundamental prerequisites for combining models built on the basis of various theoretical directions are contained in scientific methodology, starting with the definition of a single goal of education.
Conflictological Competence of First-Year Technical Students as a Necessity of the Higher Engineering Education

To build a career and adapt in a new team, a young specialist should have a certain level of conflictological competence which can be developed within educational process at the university. Conflictological specialist’s competence is their ability to make decisions in a real conflict situation and take steps to deal with it effectively. The paper describes the issues of insufficient using of educational possibility of academic disciplines which are aimed at developing the third higher education competence and the limited extent of their capabilities in developing the conflictological first-year student’s competence for effective social interaction and professional growth. The article analyzes the methods for developing the students’ conflictological competence. It outlines the necessity of establishing some assessment criteria to determine the level of conflictological competence development in all three stages of the research process. It introduces the methodology of teaching students through training courses. It describes monitoring methods of the research effectiveness by preliminary, periodic and final testing of the control and pilot groups. On the basis of the research, it is concluded that it is possible to increase effectively the level of conflictological competence of first-year students by implementing classes which include cycle training courses and triple monitoring of its result dynamics.
Built-in Sound in an Educational Multimedia Presentation

The article describes research related to students' skills from pedagogical specialties and their work with various software products for designing and creating complete multimedia didactic content (PowerPoint presentation), which can be applied in the organizational forms of music in kindergarten and primary school. The students' opinions are analysed in terms of the complexity of a specific task, its implementation time and pedagogical usefulness.
Using ICTs for Teaching General English and Professional English to Students of Technical Majors

Information and Communication Technologies have traditionally been used to organise the process of distance teaching/learning. However, recently educators have resorted to employing ICTs for teaching various subjects in all possible forms and formats. The article aims to show how ICTs can be used to organize the system of adaptive teaching of foreign languages to students of non-linguistic majors (on the example of students majoring in ICT at the Financial university under the Government of the Russian Federation, Saint-Petersburg branch). There are no entrance requirements for the levels of foreign language competencies for students of non-linguistic majors, so the language levels of first-year students vary greatly, their professional and educational needs differ a lot as well. In order to meet the requirements of the State Educational Standards as well as take into account the needs and interests of the students, organize the teaching/learning process in an efficient way, the system of adaptive teaching is applied. With the help of ICTs students are provided with learning materials that suit their language levels and their learning and future professional needs, constructive feedback is given timely, quality assurance of the teaching/learning process is provided, and assessment procedures are held. The article also demonstrates how the use of ICTs can affect the development of learning skills and soft skills such as collaboration and communication skills.
Kindergarden quantum mechanics graduates (...or how I learned to stop  gluing LEGO together and love the ZX-calculus)

This paper is a `spiritual child' of the 2005 lecture notes Kindergarten Quantum Mechanics, which showed how a simple, pictorial extension of Dirac notation allowed several quantum features to be easily expressed and derived, using language even a kindergartner can understand. Central to that approach was the use of pictures and pictorial transformation rules to understand and derive features of quantum theory and computation. However, this approach left many wondering `where's the beef?' In other words, was this new approach capable of producing new results, or was it simply an aesthetically pleasing way to restate stuff we already know? The aim of this sequel paper is to say `here's the beef!', and highlight some of the major results of the approach advocated in Kindergarten Quantum Mechanics, and how they are being applied to tackle practical problems on real quantum computers. We will focus mainly on what has become the Swiss army knife of the pictorial formalism: the ZX-calculus. First we look at some of the ideas behind the ZX-calculus, comparing and contrasting it with the usual quantum circuit formalism. We then survey results from the past 2 years falling into three categories: (1) completeness of the rules of the ZX-calculus, (2) state-of-the-art quantum circuit optimisation results in commercial and open-source quantum compilers relying on ZX, and (3) the use of ZX in translating real-world stuff like natural language into quantum circuits that can be run on today's (very limited) quantum hardware. We also take the title literally, and outline an ongoing experiment aiming to show that ZX-calculus enables children to do cutting-edge quantum computing stuff. If anything, this would truly confirm that `kindergarten quantum mechanics' wasn't just a joke.
Partition Rank and Analytic Rank are Uniformly Equivalent

We prove that the partition rank and the analytic rank of tensors are equal up to a constant, over finite fields of any characteristic and any large enough cardinality, independently of the number of variables. Moreover, a quantitative improvement of our field cardinality requirement would imply that the ranks are equal up to 1+o(1) in the exponent over every finite field. At the core of the proof is a technique for lifting decompositions of multilinear polynomials in an open subset of an algebraic variety, and a technique for finding a large subvariety that retains all rational points such that at least one of these points satisfies a finite-field analogue of genericity with respect to it. Proving the equivalence between these two ranks is a central question in additive combinatorics, and was reiterated by multiple authors. As a corollary we prove, over any mildly large field, the Polynomial Gowers Inverse Conjecture in the d vs. d-1 case.
Colored Kimia Path24 Dataset: Configurations and Benchmarks with Deep  Embeddings

The Kimia Path24 dataset has been introduced as a classification and retrieval dataset for digital pathology. Although it provides multi-class data, the color information has been neglected in the process of extracting patches. The staining information plays a major role in the recognition of tissue patterns. To address this drawback, we introduce the color version of Kimia Path24 by recreating sample patches from all 24 scans to propose Kimia Path24C. We run extensive experiments to determine the best configuration for selected patches. To provide preliminary results for setting a benchmark for the new dataset, we utilize VGG16, InceptionV3 and DenseNet-121 model as feature extractors. Then, we use these feature vectors to retrieve test patches. The accuracy of image retrieval using DenseNet was 95.92% while the highest accuracy using InceptionV3 and VGG16 reached 92.45% and 92%, respectively. We also experimented with "deep barcodes" and established that with a small loss in accuracy (e.g., 93.43% for binarized features for DenseNet instead of 95.92% when the features themselves are used), the search operations can be significantly accelerated.
On the Theory of Implicit Deep Learning: Global Convergence with  Implicit Layers

A deep equilibrium model uses implicit layers, which are implicitly defined through an equilibrium point of an infinite sequence of computation. It avoids any explicit computation of the infinite sequence by finding an equilibrium point directly via root-finding and by computing gradients via implicit differentiation. In this paper, we analyze the gradient dynamics of deep equilibrium models with nonlinearity only on weight matrices and non-convex objective functions of weights for regression and classification. Despite non-convexity, convergence to global optimum at a linear rate is guaranteed without any assumption on the width of the models, allowing the width to be smaller than the output dimension and the number of data points. Moreover, we prove a relation between the gradient dynamics of the deep implicit layer and the dynamics of trust region Newton method of a shallow explicit layer. This mathematically proven relation along with our numerical observation suggests the importance of understanding implicit bias of implicit layers and an open problem on the topic. Our proofs deal with implicit layers, weight tying and nonlinearity on weights, and differ from those in the related literature.
Cryptocurrency Solutions to Enable Micro-payments in Consumer IoT

The successful amalgamation of cryptocurrency and consumer Internet of Things (IoT) devices can pave the way for novel applications in machine-to-machine economy. However, the lack of scalability and heavy resource requirements of initial blockchain designs hinders the integration as they prioritized decentralization and security. Numerous solutions have been proposed since the emergence of Bitcoin to achieve this goal. However, none of them seem to dominate and thus it is unclear how consumer devices will be adopting these approaches. Therefore, in this paper, we critically review the existing integration approaches and cryptocurrency designs that strive to enable micro-payments among consumer devices. We identify and discuss solutions under three main categories; direct integration, payment channel network and new cryptocurrency design. The first approach utilizes a full node to interact with the payment system. Offline channel payment is suggested as a second layer solution to solve the scalability issue and enable instant payment with low fee. New designs converge to semi-centralized scheme and focuson lightweight consensus protocol that does not require highcomputation power which might mean loosening the initial designchoices in favor of scalability. We evaluate the pros and cons ofeach of these approaches and then point out future researchchallenges. Our goal is to help researchers and practitioners tobetter focus their efforts to facilitate micro-payment adoptions.
Long time dynamics of a single-particle extended quantum walk on a one-dimensional lattice with complex hoppings: a generalized hydrodynamic description

We study a single-particle continuous-time quantum walk on a one-dimensional spatial lattice with complex nearest neighbour (NN) and next-nearest neighbour (NNN) hopping amplitudes. We show that the model allows for controlled information transfer and directional biasing without a biased initial state. Specifically, we show that for an unbiased initial state, complex couplings lead to chiral propagation and a causal cone structure asymmetric about the origin. We provide a hydrodynamic description for the dynamics in the large space–time limit. We obtain a global ‘quasi-stationary state’ which can be described in terms of the local quasi-particle densities satisfying Euler type of hydrodynamic equations and characterized by an infinite set of conservation laws. Further, we show that higher-order hydrodynamic equations can be used to describe the anomalous sub-diffusive scaling near the extremal fronts. The long-time behaviour for any complex NNN hopping with a nonzero real component is similar to that of purely real hopping; at a critical coupling strength, there is a Lifshitz transition where the topology of the causal structure changes from a regime with one causal cone to a regime with two nested (asymmetric) causal cones. For purely imaginary NNN hopping, there is a transition from one causal cone to a regime with two partially overlapping cones which can be attributed to the existence of degenerate maximal fronts. Both the nature of the Lifshitz transition and the scaling behaviour at the critical coupling are different in the two cases. We also discuss possible experimental realizations of such a model.
RomeBERT: Robust Training of Multi-Exit BERT

BERT has achieved superior performances on Natural Language Understanding (NLU) tasks. However, BERT possesses a large number of parameters and demands certain resources to deploy. For acceleration, Dynamic Early Exiting for BERT (DeeBERT) has been proposed recently, which incorporates multiple exits and adopts a dynamic early-exit mechanism to ensure efficient inference. While obtaining an efficiency-performance tradeoff, the performances of early exits in multi-exit BERT are significantly worse than late exits. In this paper, we leverage gradient regularized self-distillation for RObust training of Multi-Exit BERT (RomeBERT), which can effectively solve the performance imbalance problem between early and late exits. Moreover, the proposed RomeBERT adopts a one-stage joint training strategy for multi-exits and the BERT backbone while DeeBERT needs two stages that require more training time. Extensive experiments on GLUE datasets are performed to demonstrate the superiority of our approach. Our code is available at https://github.com/romebert/RomeBERT.
Bridge the Vision Gap From Field to Command: A Deep Learning Network Enhancing Illumination and Details

Low-light image enhancement aims to improve the brightness of images captured in low-light conditions, which has various applications in surveillance, remote sensing and computational photography. However, low-light images often suffer from poor visibility and blurring, and simply brightening the dark regions may amplify blurring and cause detail loss. In this paper, we propose a simple yet effective two-stream framework called NEID that can enhance the brightness and the details simultaneously without introducing much computational cost. Specifically, our method consists of three modules: Light Enhancement (LE), Detail Refinement (DR) and Feature Fusing (FF), that aggregates composite features for multiple tasks using a channel attention mechanism. Extensive experiments on several benchmark datasets show the effectiveness of our method and its superiority over state-of-the-art methods.
Detection of Insider Attacks in Distributed Projected Subgradient  Algorithms

The gossip-based distributed algorithms are widely used to solve decentralized optimization problems in various multi-agent applications, while they are generally vulnerable to data injection attacks by internal malicious agents as each agent locally estimates its decent direction without an authorized supervision. In this work, we explore the application of artificial intelligence (AI) technologies to detect internal attacks. We show that a general neural network is particularly suitable for detecting and localizing the malicious agents, as they can effectively explore nonlinear relationship underlying the collected data. Moreover, we propose to adopt one of the state-of-art approaches in federated learning, i.e., a collaborative peer-to-peer machine learning protocol, to facilitate training our neural network models by gossip exchanges. This advanced approach is expected to make our model more robust to challenges with insufficient training data, or mismatched test data. In our simulations, a least-squared problem is considered to verify the feasibility and effectiveness of AI-based methods. Simulation results demonstrate that the proposed AI-based methods are beneficial to improve performance of detecting and localizing malicious agents over score-based methods, and the peer-to-peer neural network model is indeed robust to target issues.
Exposing Collections through Interaction Ecologies: A Prototype for Architectural Ephemera

This study introduces a model for the observation and design of digital collections exhibitions rooted on three concepts: interaction ecologies, exposing collections, and architectural ephemera. The study examines how to go beyond the “one user, one device” approach in GLAMs, what it means to expose a collection, and what it means to consider architectural elements as ephemera. We define interaction ecologies as the approach to a context in which individuals of different species (devices and humans included) entertain rich and floating relationships appropriate to the roles, activities, and postures they assume. This perspective offers novel possibilities on the exhibition of digital collections. In addition, we discuss the concepts of exposing a collection and the translation of architectural elements to transient artifacts to preserve memory. This discussion allows a series of qualities to emerge that together constitute a model for the observation of collection exhibitions. The study includes the presentation of the exhibition “Ankara Balcony Balustrades 1950–75,” which, by focusing on these aspects, acts as a prototype of the model and helps in verifying the application and its results.
Data Privacy Enhancing in the IoT User/Device Behavior Analytics

The Internet of Things (IoT) is generating and processing a huge amount of data that are then used and shared to improve services and applications in various industries. The collected data are always including sensitive information (sensitive data, users/devices/applications behaviors, etc.), which can be exchanged over the IoT to third-party for storing, processing, and sharing with associated applications. It is important to protect data privacy from compromising using consistently privacy preserving techniques. In this work, we propose a privacy-preserving solution for both structured data and unstructured data by using data anonymization techniques, which are able to enhance privacy associated with IoT services, applications, and users/device behavior. This can allow IoT users/devices to access privacy-enhanced data protecting sensitive data against re-identification risks. The experimental results demonstrate that the proposed solution can provide privacy-enhanced data for third-party services and applications over the IoT.
Security Evaluation Criteria of Open-Source Libraries

The use of freely available, open-source code to reduce the time needed to create new software or add functionality to existing software is a common practice. With analysis of recent high-profile cases of open-source software packages being corrupted by the original developer, or the introduction of remote back-door functionality by malicious actors, it has been shown that there is much that can be done to help with simplifying the decision-making process of using any open-source code. This paper provides the basis for a simple-to-use checklist that can be used to quickly analyze open-source libraries for its suitability within an individual’s or organization’s code base. Fourteen projects were selected at random from a popular code hosting site that made use of specific biometric security libraries. The conclusions derived from the use of the checklist and the analysis of the selected projects will help with simplifying the decision-making process of using open-source code for software projects.