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The morphology, species, and chemical composition of zeolites in agates from the Tevinskoye and Kinkilskoye deposits (Western Kamchatka, Russia) were studied in detail for the first time. Optical and scanning electron microscopy, EPMA, X-ray diffraction analysis, Raman spectroscopy, and X-ray computed microtomography were used. High-silica zeolites have been identified: clinoptilolite-Ca, clinoptilolite-Na, heulandite-Na, heulandite-K and mordenite. Agates from the Tevinskoye deposit were identified as intergrowths of orange and colorless prismatic clinoptilolite-Na crystals, forming a continuous rhythm up to 0.5 mm thick at the contact zone between the agate and the host rock. Numerous mordenite spherulites formed by radially radiating fine-acicular crystals approximately 1 mm long and rare intergrowths of prismatic clinoptilolite-Ca, clinoptilolite-Na, heulandite-Na, heulandite-K crystals were also diagnosed at the boundary between the agate and the host rock from the Kinkilskoye deposit. A typomorphic feature of clinoptilolite and heulandite in agates from both deposits is the admixture of BaO (0.22 to 0.73 wt.%). Silica minerals in the agates are represented by low-temperature cristobalite, chalcedony, quartzine, moganite, microgranular and coarse-crystalline quartz, including amethyst. The presence of "immature" forms of silica — moganite and low-temperature cristobalite — in the studied agates is associated with the young (Eocene) geological age of the volcanic formations. The formation of zeolites in the Tevinsky and Kinkilsky agates could have occurred with the participation of thermal neutral or alkaline. Crystallization of zeolites on the walls of gas cavities apparently occurred from supersaturated (Al, Na, K, Ca, Ba) aqueous solutions and preceded the precipitation of silica.

This article provides a review of the current state and prospects of low-cost seismic instruments. These devices enable the solution of a wide range of scientific and applied tasks, while their cost is one or two orders of magnitude lower than that of professional counterparts. The principal types of sensors are examined, including low-frequency geophones and MEMS accelerometers, with a focus on their design features, sensitivity range, and intrinsic noise levels. The typical architecture of recording equipment is described. Examples of the most common low-cost seismic instruments, such as the Raspberry Shake series and the P-Alert system, are provided, along with their technical specifications and application domains. Key application areas are analyzed, including earthquake early warning systems, volcano monitoring, passive seismic tomography using ambient noise records, experiments to measure the full wavefield from weak earthquakes, as well as educational and citizen science projects. The strengths and weaknesses of low-cost instruments are identified, encompassing limitations in recording weak signals and advantages related to network density. Promising future directions are outlined, such as improving measurement accuracy and employing machine learning methods for processing large volumes of data. It is concluded that, when intelligently combined with modern processing algorithms and dense network infrastructure, low-cost seismic instruments are capable of making a significant contribution to earthquake seismology, volcanology, and educational programs.

The article discusses methods for compressing information about the boundaries of areas generated by superpixel image segmentation. The representation of superpixel boundaries in the form of a four-digit image generated by boundary elements is proposed. A new compression method for this image is developed, based on constructing the trajectories of the boundary elements and then encoding them. An experimental study of the new method demonstrates its advantages over known methods of statistical coding and predictive coding, especially for large superpixel sizes.

A method of unmanned aerial vehicle trajectory planning has been developed. This method is based on the analysis of a video stream from a camera mounted on the vehicle, without using information from global navigation systems. The trajectory is planned using the determined parameters of an affine model of mutual spatial misalignment of adjacent video frames. The method utilizes the Shi-Tomassi singularity detection method, the Lucas-Kanade optical flow method, and the Kalman filter. The results of the method implementation on single-board computers and testing it under limited computing resources on real video sequences are presented.

The work is dedicated to the study of the formation and decoding of interference patterns to retrieve the phase of a probe wave. Algorithms for phase retrieval using plane and conical reference beams are considered. The paper also presents methods for improving the quality of the phase image when using a plane wave as a referent one.

The problem of effectively using domain-specific knowledge based on representative statistics is relevant from various perspectives. The methods used to utilize reliable a priori information are diverse and often specialized for each specific data analysis problem. The paper describes an approach to this problem in which solutions are developed from a unified perspective based on the use of a multidimensional analogue of the Hough transform. The approach offers new possibilities for solving two important problems: it proposes a unified method for constructing models of interactions between known particular regularities, and uses the minima of the discrepancy measure found in the Hough space as a tool for model optimization.

We consider the issues of creating algorithmic support for supervised classification problem which is the one of the central tasks of machine learning. Original procedures of logical analysis and classification of integer data represented as a set of elements of Cartesian product of finite partially ordered sets (product of partial orders) are constructed and investigated. At the training stage of the proposed procedures, the search for so-called regular representative elementary classifiers (special fragments in feature descriptions of precedents that distinguish objects belonging to different classes) is performed. An asymptotically optimal algorithm for enumerating the required elementary classifiers over a product of antichains is constructed and the results of its testing on real-world tasks are presented. Theoretical and experimental justifications for the efficiency of the new classification procedures are provided for the case when linear orders on sets of feature values are defined. The theoretical conclusions are based on the study of the metric (quantitative) properties of the set of regular representative elementary classifiers.

This paper presents the development of a neural network for predicting airfoil aerodynamic coefficients for use in the isolated-section method for calculating aircraft propeller blade characteristics. A key feature of this neural network is its ability to predict the lift and drag coefficients as functions of the angle of attack and flow Reynolds number in the form of two-dimensional raster images of pixel color distribution. This study aims to accelerate the calculation of airfoil aerodynamic coefficients while maintaining computational accuracy by replacing numerical models with a neural network. This study presents a method for airfoil parameterization, database development, and neural network architecture. The neural network training results and its ability to predict aerodynamic characteristics are presented.

The article describes the development and implementation of a microservice architecture upon which the functionality of an Intelligent Digital Twin of Plants (IDTP) is built. This system is designed for planning and simulation plant growth stages and forecasting yields, synchronized with the states of actual crops, based on ontologies and multi-agent technologies. The functional capabilities of the Manager, Ontology Constructor and Knowledge Base (OC and KB), Planning (multi-agent planner) services are examined, as well as the organization of interfaces for the interaction of the IDTP with external services and users. Examples are provided to represent the results of modeling the comprehensive state of a crop, based on real-time environmental data and forecasting the crop's condition at all stages of plant development up to harvest. The developed microservice architecture is open for integrating the IDTP with external services, such as environmental data collection, as well as recommendation systems and Agro-IoT platforms. The results of the IDTP prototype development have been passed on to several farms for experimental testing in different climatic conditions. The article discusses directions for improving the accuracy of IDTP forecasts and the potential for creating a decision support system for agronomic applications in precision agriculture based on the IDTP.

This article addresses the issue of territorial inequality in access to healthcare services in Sverdlovsk Oblast of Russia. The research hypothesis is that a modified gravity-based model of potential spatial accessibility, with an empirically calibrated distance decay parameter λ , can identify stable territorial disparities in structural inaccessibility of healthcare and associated medico-economic risks, statistically linked to staffing, logistical, and institutional constraints at the municipal level. The aim of the study is to develop a model for evaluating potential spatial accessibility that accounts for territorial heterogeneity and disparities in healthcare resource availability. To achieve this, a modified gravity model was applied, incorporating double normalization and empirical calibration of the distance decay parameter λ . The accessibility index A_i was calculated for 65 municipalities in Sverdlovsk Oblast. These values were used to classify territories into three accessibility levels: high, moderate, and low (risk zones). The results reveal consistent differences among these groups in terms of physician availability, frequency of medical consultations, and medical-economic indicators. Low accessibility in several municipalities is associated with structural inaccessibility, reflected in reduced disease detection rates, fewer preventive visits, uneven distribution of workload among healthcare professionals, and rising local economic losses. These findings are supported by statistical analysis. The proposed model can be applied for monitoring healthcare accessibility, guiding workforce and investment priorities, adjusting patient routing, and informing intergovernmental fiscal policies. The A_i index may serve as an indicator of territorial vulnerability and the resilience of local healthcare systems.