Intermediate Fusion Approach for Pneumonia Classification on Imbalanced Multimodal Data

In medical practice, the primary diagnosis of diseases should be carried out quickly and, if possible, automatically. The processing of multimodal data in medicine has become a ubiquitous technique in the classification, prediction and detection of diseases. Pneumonia is one of the most common lung diseases. In our study, we used chest X-ray images as the first modality and the results of laboratory studies on a patient as the second modality to detect pneumonia. The architecture of the multimodal deep learning model was based on intermediate fusion. The model was trained on balanced and imbalanced data when the presence of pneumonia was determined in 50% and 9% of the total number of cases, respectively. For a more objective evaluation of the results, we compared our model performance with several other open-source models on our data. The experiments demonstrate the high performance of the proposed model for pneumonia detection based on two modalities even in cases of imbalanced classes (up to 96.6%) compared to single-modality models’ results (up to 93.5%). We made several integral estimates of the performance of the proposed model to cover and investigate all aspects of multimodal data and architecture features. There were accuracy, ROC AUC, PR AUC, F1 score, and the Matthews correlation coefficient metrics. Using various metrics, we proved the possibility and meaningfulness of the usage of the proposed model, aiming to properly classify the disease. Experiments showed that the performance of the model trained on imbalanced data was even slightly higher than other models considered.In medical practice, the primary diagnosis of diseases should be carried out quickly and, if possible, automatically. The processing of multimodal data in medicine has become a ubiquitous technique in the classification, prediction and detection of diseases. Pneumonia is one of the most common lung diseases. In our study, we used chest X-ray images as the first modality and the results of laboratory studies on a patient as the second modality to detect pneumonia. The architecture of the multimodal deep learning model was based on intermediate fusion. The model was trained on balanced and imbalanced data when the presence of pneumonia was determined in 50% and 9% of the total number of cases, respectively. For a more objective evaluation of the results, we compared our model performance with several other open-source models on our data. The experiments demonstrate the high performance of the proposed model for pneumonia detection based on two modalities even in cases of imbalanced classes (up to 96.6%) compared to single-modality models’ results (up to 93.5%). We made several integral estimates of the performance of the proposed model to cover and investigate all aspects of multimodal data and architecture features. There were accuracy, ROC AUC, PR AUC, F1 score, and the Matthews correlation coefficient metrics. Using various metrics, we proved the possibility and meaningfulness of the usage of the proposed model, aiming to properly classify the disease. Experiments showed that the performance of the model trained on imbalanced data was even slightly higher than other models considered

Conceptual approach to the development of financial technologies in the context of digitalization of economic processes

The successful introduction of the digital economy into the information space of the Russian Federation involves the solution of several problems associated with the transition to a new paradigm of economic development based on the digitization of social and economic processes. At the same time, the existing regulatory mechanisms and legislation do not create optimal conditions for the development of the market of new financial instruments and technologies in Russia today. There are socio-economic risks, the key ones including an increase in the outflow of capital and innovative projects to other countries, a lack of confidence on the part of potential investors in new financial instruments, a decrease in the stability of traditional financial institutions. On this basis, the following tasks have been set in this article. To consider the terminology in the field of digital economy from the theoretical aspect; to identify trends and justify the need for digitalization of economic processes based on the use of new financial technologies; to reveal the informative characteristics of financial technologies promising for Russia. This article ends with a conclusion that the development of the digital economy in Russia is due to the need to ensure the information and economic security of the state, realize the potential of the new economy to improve the standard of living and national well-being through the introduction of innovative communication and financial technologies. The impact of the “digital economy” on socio-economic processes is multifaceted. It is sustainable and permeates all spheres of life, being an integral part of modern society.peer-reviewe

Studying Supply Chain and Tourism Cluster Development

Supply chain and tourism cluster are the two important ways to enhance the competitiveness of regions or industries. By discussing the differences and links between the two, this paper concludes that tourism cluster and supply chain carry features of compatibility and symbiosis. The importance of this research paper is determined by the fact that a significant number of tourism clusters established in the territory of the Russian Federation are not always successful as catalysts for the tourism sector development. This study aims to determine methods for conducting research on specialization as a factor in tourism cluster development, taking into consideration the existing research approaches and findings in this area. The systemic, structural, functional and analysis methods were used, along with a general theoretic approach to researching tourism cluster development. The selected methods made it possible to identify approaches to forming the relevant research methodologies. Based on the presented approaches, it is possible to choose research methods and the coherence of research activities in this area, with a view to identify key development indicators for tourism development and various tourism-related processes taking place within the territory of a tourism cluster. The research findings will provide necessary tools and mechanisms for developing tourism clusters based on the diversification of their specialization. The findings of the study are directed at increasing the effectiveness of decisions taken to assess and forecast tourism cluster development and can also be of use to all those interested in this field. The materials of the present study can be used by regional administrations to monitor and make effective management decisions aimed at improving regional tourism development programs. Experts and scholars could also benefit from the findings of this study to analyze and develop projections and to promote topic-related methodological approaches. The article will be of practical value for the specialists in tourism planning, tourism administration and tourism enterprise managers

Electron-ion plasma modification of Al-based alloys

The paper reports on the study where we analyzed the surface structure and strength properties of coated Al alloys modified by electron-ion plasma treatment. The Al alloys were deposited with a thin (≈0.5 μm) TiCu film coating (TiCu-Al system) and with a hard TiCuN coating (TiCuN–AlSi system) on a TRIO vacuum setup in the plasma of low-pressure arc discharges. The temperature fields and phase transformations in the film–substrate system were estimated by numerical simulation in a wide range of electron energy densities (5–30 J/cm2) and pulse durations (50–200 μs). The calculations allowed us to determine the threshold energy density and pulse duration at which the surface structure of the irradiated Al-based systems is transformed in a single-phase state (solid or liquid) and in a two-phase state (solid plus liquid). The elemental composition, defect structure, phase state, and lattice state in the modified surface layers were examined by optical, scanning, and transmission electron microscopy, and by X-ray diffraction analysis. The mechanical characteristics of the modified layers were studied by measuring the hardness and Young’s modulus. The tribological properties of the modified layers were analyzed by measuring the wear resistance and friction coefficient. It is shown that melting and subsequent high-rate crystallization of the TiCu–Al system makes possible a multiphase Al-based surface structure with the following characteristics: crystallite size ranging within micrometer, microhardness of more than 3 times that in the specimen bulk, and wear resistance ≈1.8 times higher compared to the initial material. Electron beam irradiation of the TiCuN–AlSi system allows fusion of the coating into the substrate, thus increasing the wear resistance of the material ≈2.2 times at a surface hardness of ∼14 GPa

Frequency of EGFR mutations in non-small cell lung cancer patients: screening data from West Siberia

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Glutamate Concentration in the Serum of Patients with Schizophrenia

Glutamate is the major neurotransmitter with multiple functions in the central nervous system. Glutamate-mediated excitotoxicity is involved in the pathophysiological processes in schizophrenia. The purpose of this study was to determine the concentration of glutamate in the serum of patients with paranoid schizophrenia compared with healthy individuals, and depending on the duration of the schizophrenic process and leading clinical symptoms. We investigated the level of glutamate in the serum of 158 patients with paranoid schizophrenia and 94 healthy persons. Higher concentrations of glutamate in schizophrenic patients compared with healthy persons have been found. The maximum concentrations of glutamate were detected in patients with disease duration of more than ten years. Glutamate level in the serum does not depend on the prevailing negative or positive clinical symptoms. The increased concentration of glutamate can hypothetically contribute to dopaminergic and glutamatergic imbalance, leading to the development of psychotic symptoms and cognitive dysfunction

Controlled Ultra-Thin Suboxide Films Generation in Metal-Oxide Systems by Ar+Ion Irradiation

A method of controlled generation of metal suboxide films is proposed, basing on low-current ion sputtering of native oxides of ultra-thin metallic films and XPS chemical and phase depth profiling. Niobium suboxide ultra-thin films are generated and controlled using this approach