## Natural Sciences

We propose a novel machine-learning-based approach to detect bid leakage in first-price sealed-bid auctions. We extract and analyze the data on more than 1.4 million Russian procurement auctions between 2014 and 2018. As bid leakage in each particular auction is tacit, the direct classification is impossible. Instead, we reduce the problem of bid leakage detection to Positive-Unlabeled Classification. The key idea is to regard the losing participants as fair and the winners as possibly corrupted. This allows us to estimate the prior probability of bid leakage in the sample, as well as the posterior probability of bid leakage for each specific auction. We find that at least 16% of auctions are exposed to bid leakage. Bid leakage is more likely in auctions with a higher reserve price, lower number of bidders and lower price fall, and where the winning bid is received in the last hour before the deadline.

The International Workshop on Enterprise and Organizational Modeling and Simulation (EOMAS) represents a forum where researchers and practitioners exchange and mutually enrich their views, approaches, and obtain results in the field of enterprise engineering and enterprise architecture. The most valuable asset of every conference and workshop is its community. The community of EOMAS is small, but it consists of founding members, long-term contributors, and every year it attracts new innovative participants. This year, EOMAS reached its 15th edition and took place in Rome, Italy, during June 3–4, 2019. Traditionally, we can offer a balanced assortment of papers addressing formal foundations of enterprise modeling and simulation, conceptual modeling approaches, higher-level insights and applications bringing novel ideas to traditional approaches, as well as new emerging trends. Out of 24 submitted papers, 12 were accepted for publication as full papers and for oral presentation, and each paper was carefully selected, reviewed, and revised. In additional to this we reflected on the interest of last year’s invited workshop on usability and invited the experts to make a sequel. You can find a short report in this issue. This year, we included a novel outlet of Master and Doctoral Consortium, which attracted young talent to present their work. The presented work was then discussed, and feedback, advice, and encouragement was given. We were really surprised by the relevance, methodological quality, and results of their work – you may find their contributions on our website https://eomas-workshop.org. We would like to express our sincere thanks to the entire EOMAS community: the authors, the Program Committee and the CAiSE organizers, the chairs for their enthusiasm and devotion, as well as all participants for their contributions. We look forward to the 16th edition of EOMAS!

Workshop concentrates on an interdisciplinary approach to modelling human behavior incorporating data mining and expert knowledge from behavioral sciences. Data analysis results extracted from clean data of laboratory experiments will be compared with noisy industrial datasets from the web e.g. Insights from behavioral sciences will help data scientists. Behavior scientists will see new inspirations to research from industrial data science. Market leaders in Big Data, as Microsoft, Facebook, and Google, have already realized the importance of experimental economics know-how for their business.

In Experimental Economics, although financial rewards restrict subjects preferences in experiments, exclusive application of analytical game theory is not enough to explain the collected data. It calls for the development and evaluation of more sophisticated models. The more data is used for evaluation, the more statistical significance can be achieved. Since large amounts of behavioral data are required to scan for regularities, along with automated agents needed to simulate and intervene in human interactions, Machine Learning is the tool of choice for research in Experimental Economics. This workshop is aimed at bringing together researchers from both Data Analysis and Economics in order to achieve mutually beneficial results.

This volume contains the refereed proceedings of the 8th International Conference on Analysis of Images, Social Networks, and Texts (AIST 2019). The previous conferences during 2012–2018 attracted a significant number of data scientists – students, researchers, academics, and engineers working on interdisciplinary data analysis of images, texts, and social networks.

This is an advanced text on ordinary differential equations (ODES) in Banach and more general locally convex spaces, most notably the ODEs on measures and various function spaces. It yields the concise exposition of the fundamentals with the fast, but rigorous and systematic transition to the up-fronts of modern research in linear and nonlinear partial and pseudo-differential equations, general kinetic equations and fractional evolutions. The level of generality is chosen to be suitable for the study of the most important nonlinear equations of mathematical physics, such as Boltzmann, Smoluchovskii, Vlasov, Landau-Fokker-Planck, Cahn-Hilliard, Hamilton-Jacobi-Bellman, nonlinear Schroedinger, McKean-Vlasov diffusions and their nonlocal extensions, mass-action-law kinetics from chemistry. It also covers nonlinear evolutions arising in evolutionary biology and mean-field games, optimization theory, epidemics and system biology, in general models of interacting particles or agents describing splitting and merging, collisions and breakage, mutations and the preferential-attachment growth on networks. The book is meant for final year undergraduate and postgraduate students and researchers in differential equations and their applications. A significant amount of attention is paid to the interconnections between various topics revealing where and how a particular result is used in other chapters or may be used in other contexts, as well as to the clarification of the links between the languages of pseudo-differential operators, generalized functions, operator theory, abstract linear spaces, fractional calculus and path integrals.

This two volume constitutes the refereed proceedings of the Fourth International Conference on Digital Transformation and Global Society, DTGS 2019, held in St. Petersburg, Russia, in June 2019.

**Provides an overview of the developments and advances in the field of network clustering and blockmodeling over the last 10 years**

This book offers an integrated treatment of network clustering and blockmodeling, covering all of the newest approaches and methods that have been developed over the last decade. Presented in a comprehensive manner, it offers the foundations for understanding network structures and processes, and features a wide variety of new techniques addressing issues that occur during the partitioning of networks across multiple disciplines such as community detection, blockmodeling of valued networks, role assignment, and stochastic blockmodeling.

Written by a team of international experts in the field, *Advances in Network Clustering and Blockmodeling *offers a plethora of diverse perspectives covering topics such as: bibliometric analyses of the network clustering literature; clustering approaches to networks; label propagation for clustering; and treating missing network data before partitioning. It also examines the partitioning of signed networks, multimode networks, and linked networks. A chapter on structured networks and coarsegrained descriptions is presented, along with another on scientific coauthorship networks. The book finishes with a section covering conclusions and directions for future work. In addition, the editors provide numerous tables, figures, case studies, examples, datasets, and more.

*Advances in Network Clustering and Blockmodeling *is an ideal book for graduate and undergraduate students taking courses on network analysis or working with networks using real data. It will also benefit researchers and practitioners interested in network analysis.

This edition of Procedia Computer Science represents the proceedings of the 23rd International Conference on Knowledge - Based and Intelligent Information & Engineering Systems (KES 2019), organised by KES International and held at the Danubius Health Spa Resort, Budapest over 4-6 September 2019. KES 2019 was the 23rd event in a series of broad-spectrum intelligent systems conferences first held in Adelaide, Australia in 1997. The main aim of this KES conference series is to provide an internationally respected forum for the dissemination of research results and the discussion of issues relating to the theory, technologies and applications of intelligent engineering and information systems. This truly international conference attracted submissions from a substantial number of researchers and practitioners from all over the world, who submitted their papers to three general tracks, one thematic track and 34 special sessions on specific topics. A large number of submissions was received and each paper was peer reviewed by at least two members of the International Program Committee. From them, 274 high-quality papers were accepted for oral presentation and publication in Procedia Computer Science, submitted for indexing in Conference Proceedings Citation Index (CPCI) and Scopus. The conference chairs would like to express their gratitude to the Keynote Speakers: Prof Dana Barry, Clarkson University, USA, title of talk: 'STEM and ICT Education in Intelligent Environments'; Dr Carlos Toro, ARTC (Advanced Remanufacturing and Technology Centre) - A*Star, Singapore, title of talk: 'Smart Manufacturing coming of age'; Prof Katsutoshi Yada, Kansai University, Japan, title of talk: 'Sensor Marketing and Data Mining'; Prof Cecilia Zanni-Merk, INSA Rouen Normandie / LITIS Laboratory, France, title of talk 'On the need of an Explainable Artificial Intelligence'; and Prof Sergey Zykov, National Research University Higher School of Economics, Russia, title of talk: 'IT Crisisology: the New Discipline for Managing Software Development in Crisis'. We would like to acknowledge also the Programme Co-Chairs, the General Track Chairs, the International Programme Committee members and reviewers for their valuable efforts in the review process, helping us to guarantee the highest quality possible for the conference. We would also like to thank the organisers and chairs of the special sessions which make an essential contribution to the success of the conference. Lastly, we would like to thank all the authors, presenters and delegates for their valuable contribution in making this an extraordinary event. KES International hopes and intends that KES2019 will make a significant contribution to international research collaboration and understanding, an essential task for the promotion of scientific joint work and excellence.

The goal of this International Roadmap for Devices and Systems (IRDS) chapter is to survey, catalog, and assess the status of technologies in the areas of cryogenic electronics and quantum information processing. Application drivers are identified for sufficiently developed technologies and application needs are mapped as a function of time against projected capabilities to identify challenges requiring research and development effort. Cryogenic electronics (also referred to as low-temperature electronics or cold electronics) is defined by operation at cryogenic temperatures (below −150 °C or 123.15 K) and includes devices and circuits made from a variety of materials including insulators, conductors, semiconductors, superconductors, or topological materials. Existing and emerging applications are driving development of novel cryogenic electronic technologies. Information processing refers to the input, transmission, storage, manipulation or processing, and output of data. Information processing systems to accomplish a specific function, in general, require several different interactive layers of technology. A top-down list of these layers begins with the required application or system function, leading to system architecture, micro- or nano-architecture, circuits, devices, and materials. A fundamental unit of information (e.g., a bit) is represented by a computational state variable, for example, the position of a bead in the ancient abacus calculator or the voltage (or charge) state of a node capacitance in CMOS logic. A binary computational state variable serves as the foundation for von Neumann computational system architectures that dominated conventional computing. Quantum information processing is different in that it uses qubits, two-state quantum-mechanical systems that can be in coherent superpositions of both states at the same time, which can have computational advantages. Measurement of a qubit in a given basis causes it to collapse to one of the basis states. Technology categories covered in this report include: • Superconductor electronics (SCE) • Cryogenic semiconductor electronics (Cryo-Semi) • Quantum information processing (QIP)

We study the Maximum Happy Vertices and Maximum Happy Edges problems. The former problem is a variant of clusterization, where some vertices have already been assigned to clusters. The second problem gives a natural generalization of Multiway Uncut, which is the complement of the classical Multiway Cut problem. Due to their fundamental role in theory and practice, clusterization and cut problems has always attracted a lot of attention. We establish a new connection between these two classes of problems by providing a reduction between Maximum Happy Vertices and Node Multiway Cut. Moreover, we study structural and distance to triviality parameterizations of Maximum Happy Vertices and Maximum Happy Edges. Obtained results in these directions answer questions explicitly asked in four works: Agrawal ’17, Aravind et al. ’16, Choudhari and Reddy ’18, Misra and Reddy ’17.

The Third Workshop on Computer Modelling in Decision Making (CMDM 2018) was held in Saratov State University (Saratov, Russia) within the VII International Youth Research and Practice Conference ‘Mathematical and Computer Modelling in Economics, Insurance and Risk Management’. The workshop 's main topic is computer and mathematical modeling in decision making in finance, insurance, banking, economic forecasting, investment and financial analysis. Researchers, postgraduate students, academics as well as financial, bank, insurance and government workers participated in the Workshop.

ICUMT is an IEEE premier an annual international congress providing an open forum for researchers, engineers, network planners and service providers targeted on newly emerging algorithms, systems, standards, services, and applications, bringing together leading international players in telecommunications, control systems, automation and robotics. The event is positioned as a major international annual congress for the presentation of original results achieved from fundamental as well as applied research and engineering works.

We study synchronization aspects in parallel discrete event simulation (PDES) algorithms. Our analysis is based on the recently introduced model of virtual times evolution in an optimistic synchronization algorithm. This model connects synchronization aspects with the properties of the profile of the local virtual times. The main parameter of the model is a “growth rate” q = 1/(1 + b), where b is a mean rollback length. We measure the average utilization of events and the desynchronization between logical processes as functions of the parameter q. We found that there is a phase transition between an “active phase”, i.e. when the utilization of the average processing time is finite, and an “absorbing state” with zero utilization, vanishing at a critical point qc ≈ 0.136. The average desynchronization degree (i.e. the vari- ance of local virtual times) grows with the parameter q. We also investi- gate the influence of the sparse distant communications between logical processes and found that they do not change drastically the synchronization properties in the optimistic synchronization algorithm, which is the sharp contrast with the conservative algorithm [1]. Finally, we compare our results with the existing case-study simulations.

Modal logics, both propositional and predicate, have been used in computer science since the late 1970s. One of the most important properties of modal logics of relevance to their applications in computer science is the complexity of their satisﬁability problem. The complexity of satisﬁability for modal logics is rather high: it ranges from NP-complete to undecidable for propositional logics and is undecidable for predicate logics. This has, for a long time, motivated research in drawing the borderline between tractable and intractable fragments of propositional modal logics as well as between decidable and undecidable fragments of predicate modal logics. In the present thesis, we investigate some very natural restrictions on the languages of propositional and predicate modal logics and show that placing those restrictions does not decrease complexity of satisﬁability. For propositional languages, we consider restricting the number of propositional variables allowed in the construction of formulas, while for predicate languages, we consider restricting the number of individual variables as well as the number and arity of predicate letters allowed in the construction of formulas. We develop original techniques, which build on and develop the techniques known from the literature, for proving that satisﬁability for a ﬁnite-variable fragment of a propositional modal logic is as computationally hard as satisﬁability for the logic in the full language and adapt those techniques to predicate modal logics and prove undecidability of fragments of such logics in the language with a ﬁnite number of unary predicate letters as well as restrictions on the number of individual variables. The thesis is based on four articles published or accepted for publication. They concern propositional dynamic logics, propositional branchingand alternating-time temporal logics, propositional logics of symmetric rela tions, and ﬁrst-order predicate modal and intuitionistic logics. In all cases, we identify the “minimal,” with regard to the criteria mentioned above, fragments whose satisﬁability is as computationally hard as satisﬁability for the entire logic.

This book deals with mathematical modeling, namely, it describes the mathematical model of heat transfer in a silicon cathode of small (nano) dimensions with the possibility of partial melting taken into account. This mathematical model is based on the phase field system, i.e., on a contemporary generalization of Stefan-type free boundary problems. The approach used is not purely mathematical but is based on the understanding of the solution structure (construction and study of asymptotic solutions) and computer calculations. The book presents an algorithm for numerical solution of the equations of the mathematical model including its parallel implementation. The results of numerical simulation concludes the book. The book is intended for specialists in the field of heat transfer and field emission processes and can be useful for senior students and postgraduates.

We consider quantum logical gates on Majorana qubits implemented in chain structures of ordinary qubits, spins, or pseudospins. We demonstrate that one can implement a two-qubit operation via local manipulations, using an extra coupler spin in a *T*-junction geometry, so that this coupler spin remains disentangled from the qubit. Furthermore, we identify a set of symmetry operations, which not only allow us to determine the resulting two-qubit gate, but also to demonstrate robustness of the resulting gate to inaccuracies in the manipulations, known for topological quantum computation.

Defects in crystal structure of layered material can modify the surface states. Ion bombardment is a simple way to introduce defects into a crystal lattice in the surface region. Comprehensive scanning tunneling microscopy (STM), low-energy electron diffraction (LEED), and photoemission studies are presented to uncover the impact of ion etching and thermal annealing on the atomic and electronic structure of Sb (111) surface. We reveal the unusual behavior of the Sb(111) surface after Ar+ sputtering at 300 K (RT). The 3 nm-sized terraces formed even after a prolonged ion bombardment are established by LEED. Also, an increase in density of states (DOS) at the Fermi edge is detected for the etched Sb(111) surface due to the ruptured covalent bonds (CBs).

We show that automorphism groups of Hopf and Kodaira surfaces have unbounded finite subgroups. For elliptic fibrations on Hopf, Kodaira, bielliptic, and K3 surfaces, we make some observations on finite groups acting along the fibers and on the base of such a fibration.

Given a holomorphic conic bundle without sections, we show that the orders of finite groups acting by its fiberwise bimeromorphic transformations are bounded. This provides an analog of a similar result obtained by Bandman and Zarhin for quasi-projective conic bundles.

We propose an accelerated gradient-free method with a non-Euclidean proximal operator associated with the *p*-norm (1 ⩽ *p* ⩽ 2). We obtain estimates for the rate of convergence of the method under low noise arising in the calculation of the function value. We present the results of computational experiments.

We discuss the quantization of the ̂ sl 2 coset vertex operator algebra W D(2,1;α) using the bosonization technique. We show that after quantization, there exist three families of commuting integrals of motion coming from three copies of the quantum toroidal algebra associated with gl 2 .

On a Fock space constructed from mn free bosons and lattice Z mn , we give a level n action of the quantum toroidal algebra E m associated to gl m , together with a level m action of the quantum toroidal algebra E n associated to gl n . We prove that the E m transfer matrices commute with the E n transfer matrices after an appropriate identification of parameters.

We consider a generalization of the classical game of Nim called hypergraph Nim. Given a hypergraph H on the ground set V={1,…,n} of *n* piles of stones, two players alternate in choosing a hyperedge H∈H and strictly decreasing all piles i∈H. The player who makes the last move is the winner. In this paper we give an explicit formula that describes the Sprague-Grundy function of hypergraph Nim for several classes of hypergraphs. In particular we characterize all 2-uniform hypergraphs (that is graphs) and all matroids for which the formula works. We show that all self-dual matroids are included in this class.

We consider two-person zero-sum stochastic mean payoff games with perfect information, or BWR-games, given by a digraph G=(V,E), with local rewards r:E→Z, and three types of positions: black VB, white VW, and random VR forming a partition of *V*. It is a long-standing open question whether a polynomial time algorithm for BWR-games exists, or not, even when |VR|=0. In fact, a pseudo-polynomial algorithm for BWR-games would already imply their polynomial solvability. In this paper,1 we show that BWR-games with a constant number of random positions can be solved in pseudo-polynomial time. More precisely, in any BWR-game with |VR|=O(1), a saddle point in uniformly optimal pure stationary strategies can be found in time polynomial in |VW|+|VB|, the maximum absolute local reward, and the common denominator of the transition probabilities.