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Detecting controversy in online discussions is critical for managing public relations, as it helps inform various processes from policymaking to business. This work aims to expand approaches to online controversy detection based on the expressed emotions. Controversy was defined as an online content phenomenon of provoking disagreements and conflict. This study builds upon prior semantic methods by analyzing estimates of emotional connotations of messages. Modern language models for emotion recognition and named entity recognition are explored as tools of controversy detection. The outputs of these models were aggregated by entity to estimate the entity’s emotional connotation. The emotional divergence score based on the dispersion of emotions was proposed to quantify controversy in user content. Then, entities with sufficiently high emotional divergence relative to the domain of discussions were selected as markers of controversy. A case study of Reddit data related to Sri-Lankan 2022 political crisis was conducted, showing the capabilities of emotional divergence score in controversy detection. A total of two datasets were collected with different methodologies: one aimed at collecting earlier messages and another aimed at collecting more recent ones. The collected data contained discussions of policy, public figures, organizations and locations tied to the crisis. When measured on manually annotated data samples, the proposed method achieved a recall value of 0.705 and a precision value close to 0.496 for the first dataset, while recall of 0.716 and precision of 0.436 were recorded for the second dataset. The main factors that limit the precision were found to be the quality of underlying models and false positives: highly discussed non-controversial markers. Lastly, it was identified that a study of regular emotional distribution of social media content may be helpful for improving controversy detection quality.

The transition from α-helices to β-strands under external mechanical force in fibrin molecule containing coiled-coils is studied and free energy landscape is resolved. The detailed theoretical modeling of each stage of coiled-coils fragment pulling process was performed. The plots of force (F) as a function of molecule expansion (X) for two symmetrical fibrin coiled-coils (each ∼17 nm in length) show three distinct modes of mechanical behaviour: (1) linear (elastic) mode when coiled-coils behave like entropic springs (F<100−125 pN and X<7−8 nm), (2) viscous (plastic) mode when molecule resistance force does not increase with increase in elongation length (F≈150 pN and X≈10−35 nm) and (3) nonlinear mode (F>175−200 pN and X>40−50 nm). In linear mode the coiled-coils unwind at 2π radian angle, but no structural transition occurs. Viscous mode is characterized by the phase transition from the triple α-spirals to three-stranded parallel β-sheet. The critical tension of α-helices is 0.25 nm per turn, and the characteristic energy change is equal to 4.9 kcal/mol. Changes in internal energy Δu, entropy Δs and force capacity c_f per one helical turn for phase transition were also computed. The observed dynamic behavior of α-helices and phase transition from α-helices to β-sheets under tension might represent a universal mechanism of regulation of fibrillar protein structures subject to mechanical stresses due to biological forces.

Virtual machines are usually associated with an ability to create them on demand by calling web services, then these machines are used to deliver resident services to their clients; however, providing clients with an ability to run an arbitrary programme on the newly created machines is beyond their power. Such kind of usage is useful in a high performance computing environment where most of the resources are consumed by batch programmes and not by daemons or services. In this case a cluster of virtual machines is created on demand to run a distributed or parallel programme and to save its output to a network attached storage. Upon completion this cluster is destroyed and resources are released. With certain modifications this approach can be extended to interactively deliver computational resources to the user thus providing virtual desktop as a service. Experiments show that the process of creating virtual clusters on demand can be made efficient in both cases.

In the development of the previously obtained result on modeling the dynamics of vegetation cover, due to variations in the temperature background, a new scheme for the interval analysis of the dynamics of floristic images of formations is presented in the case when the parameter of the response rate of the model of the dynamics of each counting plant species is set by the interval of scatter of its possible values. The detailed description of the functional parameters of macromodels of biodiversity, desired in fundamental research, taking into account the essential reasons for the observed evolutionary processes, may turn out to be a problematic task. The use of more reliable interval estimates of the variability of functional parameters “bypasses” the problem of uncertainty in the primary assessment of the evolution of the phyto-resource potential of the developed controlled territories. The solutions obtained preserve not only a qualitative picture of the dynamics of species diversity, but also give a rigorous, within the framework of the initial assumptions, a quantitative assessment of the degree of presence of each plant species. The practical significance of two-sided estimation schemes based on the construction of equations for the upper and lower boundaries of the trajectories of the scatter of solutions depends on the conditions and measure of proportional correspondence of the intervals of scatter of the initial parameters with the intervals of scatter of solutions. For dynamic systems, the desired proportionality is not always ensured. The given examples demonstrate the acceptable accuracy of interval estimation of evolutionary processes. It is important to note that the constructions of the estimating equations generate vanishing intervals of scatter of solutions for quasi-constant temperature perturbations of the system. In other words, the trajectories of stationary temperature states of the vegetation cover are not roughened by the proposed interval estimation scheme. The rigor of the result of interval estimation of the species composition of the vegetation cover of formations can become a determining factor when choosing a method in the problems of analyzing the dynamics of species diversity and the plant potential of territorial systems of resource-ecological monitoring. The possibilities of the proposed approach are illustrated by geoinformation images of the computational analysis of the dynamics of the vegetation cover of the Yamal Peninsula and by the graphs of the retro-perspective analysis of the floristic variability of the formations of the landscapelithological group “Upper” based on the data of the summer temperature background of the Salehard weather station from 2010 to 1935. The developed indicators of floristic variability and the given graphs characterize the dynamics of species diversity, both on average and individually in the form of intervals of possible states for each species of plant.

The probabilistic topic model of a text document collection finds two matrices: a matrix of conditional probabilities of topics in documents and a matrix of conditional probabilities of words in topics. Each document is represented by a multiset of words also called the “bag of words”, thus assuming that the order of words is not important for revealing the latent topics of the document. Under this assumption, the problem is reduced to a low-rank non-negative matrix factorization governed by likelihood maximization. In general, this problem is ill-posed having an infinite set of solutions. In order to regularize the solution, a weighted sum of optimization criteria is added to the log-likelihood. When modeling large text collections, storing the first matrix seems to be impractical, since its size is proportional to the number of documents in the collection. At the same time, the topical vector representation (embedding) of documents is necessary for solving many text analysis tasks, such as information retrieval, clustering, classification, and summarization of texts. In practice, the topical embedding is calculated for a document “on-the-fly”, which may require dozens of iterations over all the words of the document. In this paper, we propose a way to calculate a topical embedding quickly, by one pass over document words. For this, an additional constraint is introduced into the model in the form of an equation, which calculates the first matrix from the second one in linear time. Although formally this constraint is not an optimization criterion, in fact it plays the role of a regularizer and can be used in combination with other regularizers within the additive regularization framework ARTM. Experiments on three text collections have shown that the proposed method improves the model in terms of sparseness, difference, logLift and coherence measures of topic quality. The open source libraries BigARTM and TopicNet were used for the experiments.

Most biomechanical tasks of interest to clinicians can be solved only using personalized mathematical models. Such models allow to formalize and relate key pathophysiological processes, basing on clinically available data evaluate non-measurable parameters that are important for the diagnosis of diseases, predict the result of a therapeutic or surgical intervention. The use of models in clinical practice imposes additional restrictions: clinicians require model validation on clinical cases, the speed and automation of the entire calculated technological chain, from processing input data to obtaining a result. Limitations on the simulation time, determined by the time of making a medical decision (of the order of several minutes), imply the use of reduction methods that correctly describe the processes under study within the framework of reduced models or machine learning tools.

Personalization of models requires patient-oriented parameters, personalized geometry of a computational domain and generation of a computational mesh. Model parameters are estimated by direct measurements, or methods of solving inverse problems, or methods of machine learning. The requirement of personalization imposes severe restrictions on the number of fitted parameters that can be measured under standard clinical conditions. In addition to parameters, the model operates with boundary conditions that must take into account the patient’s characteristics. Methods for setting personalized boundary conditions significantly depend on the clinical setting of the problem and clinical data. Building a personalized computational domain through segmentation of medical images and generation of the computational grid, as a rule, takes a lot of time and effort due to manual or semi-automatic operations. Development of automated methods for setting personalized boundary conditions and segmentation of medical images with the subsequent construction of a computational grid is the key to the widespread use of mathematical modeling in clinical practice.

The aim of this work is to review our solutions for personalization of mathematical models within the framework of three tasks of clinical cardiology: virtual assessment of hemodynamic significance of coronary artery stenosis, calculation of global blood flow after hemodynamic correction of complex heart defects, calculating characteristics of coaptation of reconstructed aortic valve.

The paper considers the basic model of competitive interactions and its use for the analysis and description of social processes. The peculiarity of the model is that it describes the interaction of several competing actors, while actors can vary the strategy of their actions, in particular, form coalitions to jointly counter a common enemy. As a result of modeling, various modes of competitive interaction were identified, their classification was conducted, and their features were described. In the course of the study, the attention is paid to the so-called “rough” (according to A.A. Andronov) cases of the implementation of competitive interaction, which until now have rarely been considered in the scientific literature, but are quite common in real life. Using a basic mathematical model, the conditions for the implementation of various modes of competitive interactions are considered, the conditions for the transition from one mode to another are determined, examples of the implementation of these modes in the economy, social and political life are given. It is shown that with a relatively low level of competition, which is non-antagonistic in nature, competition can lead to an increase in the activity of interacting actors and to overall economic growth. Moreover, in the presence of expanding resource opportunities (as long as such opportunities remain), this growth may have a hyperbolic character. With a decrease in resource capabilities and increased competition, there is a transition to an oscillatory mode, when weaker actors unite to jointly counteract stronger ones. With a further decrease in resource opportunities and increased competition, there is a transition to the formation of stable hierarchical structures. At the same time, the model shows that at a certain moment there is a loss of stability, the system becomes “rough” according to A.A. Andronov and sensitive to fluctuations in parameter changes. As a result, the existing hierarchies may collapse and be replaced by new ones. With a further increase in the intensity of competition, the actor-leader completely suppresses his opponents and establishes monopolism. Examples from economic, social, and political life are given, illustrating the patterns identified on the basis of modeling using the basic model of competition. The obtained results can be used in the analysis, modeling and forecasting of socioeconomic and political processes.

Processing of large amounts of data often consists of several steps, e.g. pre- and post-processing stages, which are executed sequentially with data written to disk after each step, however, when pre-processing stage for each task is different the more efficient way of processing data is to construct a pipeline which streams data from one stage to another. In a more general case some processing stages can be factored into several parallel subordinate stages thus forming a distributed pipeline where each stage can have multiple inputs and multiple outputs. Such processing pattern emerges in a problem of classification of wave energy spectra based on analytic approximations which can extract different wave systems and their parameters (e.g. wave system type, mean wave direction) from spectrum. Distributed pipeline approach achieves good performance compared to conventional “sequential-stage” processing.

Photosynthetic apparatus of a plant cell consists of multiple photosynthetic electron transport chains (ETC). Each ETC is capable of capturing and utilizing light quanta, that drive electron transport along the chain. Light assimilation efficiency depends on the plant’s current physiological state. The energy of the part of quanta that cannot be utilized, dissipates into heat, or is emitted as fluorescence. Under high light conditions fluorescence levels gradually rise to the maximum level. The curve describing that rise is called fluorescence rise (FR). It has a complex shape and that shape changes depending on the photosynthetic apparatus state. This gives one the opportunity to investigate that state only using the non invasive measuring of the FR.

When measuring fluorescence in experimental conditions, we get a response from millions of photosynthetic units at a time. In order to reproduce the probabilistic nature of the processes in a photosynthetic ETC, we created a Monte Carlo model of this chain. This model describes an ETC as a sequence of electron carriers in a thylakoid membrane, connected with each other. Those carriers have certain probabilities of capturing light photons, transferring excited states, or reducing each other, depending on the current ETC state. The events that take place in each of the model photosynthetic ETCs are registered, accumulated and used to create fluorescence rise and electron carrier redox states accumulation kinetics. This paper describes the model structure, the principles of its operation and the relations between certain model parameters and the resulting kinetic curves shape. Model curves include photosystem II reaction center fluorescence rise and photosystem I reaction center redox state change kinetics under different conditions.

Many properties of ordinary differential equations systems solutions are determined by the properties of the equations in variations. An ODE system, which includes both the original nonlinear system and the equations in variations, will be called an extended system further. When studying the properties of the Cauchy problem for the systems of ordinary differential equations, the transition to extended systems allows one to study many subtle properties of solutions. For example, the transition to the extended system allows one to increase the order of approximation for numerical methods, gives the approaches to constructing a sensitivity function without using numerical differentiation procedures, allows to use methods of increased convergence order for the inverse problem solution. Authors used the Broyden method belonging to the class of quasi-Newtonian methods. The Rosenbroke method with complex coefficients was used to solve the stiff systems of the ordinary differential equations. In our case, it is equivalent to the second order approximation method for the extended system.

As an example of the proposed approach, several related mathematical models of the blood coagulation process were considered. Based on the analysis of the numerical calculations results, the conclusion was drawn that it is necessary to include a description of the factor XI positive feedback loop in the model equations system. Estimates of some reaction constants based on the numerical inverse problem solution were given.

Effect of factor V release on platelet activation was considered. The modification of the mathematical model allowed to achieve quantitative correspondence in the dynamics of the thrombin production with experimental data for an artificial system. Based on the sensitivity analysis, the hypothesis tested that there is no influence of the lipid membrane composition (the number of sites for various factors of the clotting system, except for thrombin sites) on the dynamics of the process.