Features Of Relations Research Articles

Towards Discriminability with Distribution Discrepancy Constrains for Multisource Domain Adaptation

Multisource domain adaptation (MDA) is committed to mining and extracting data concerning target tasks from several source domains. Many recent studies have focused on extracting domain-invariant features to eliminate domain distribution differences. However, there are three aspects that require further consideration. (1) Efforts should be made to ensure the maximum correlation in the potential subspace between the source and target domains. (2) While aligning the marginal distribution, the conditional distribution must also be considered. (3) Merely aligning the source distribution and target distribution cannot guarantee sufficient differentiation for classification tasks. To address these problems, we propose a novel approach named towards discriminability with distribution discrepancy constrains for multisource domain adaptation (TD-DDC). Specifically, TD-DDC first mines features of maximal relations learned from all domains while constructing domain data distribution mean distance metrics for interdomain distribution adaptation. Simultaneously, we integrate discriminability into domain alignment, which means increasing the distance among labels that are distinct from one another while reducing the distance among labels that are the same. Our proposed method not only reduces the interdomain distributional differences but also takes into account the preservation of interdomain correlation and inter-category discrimination. Numerous experiments have shown that TD-DDC performs much better than its competitors on three visual benchmark test databases.

The Spatial Structure of the Tumor Immune Microenvironment Can Explain and Predict Patient Response in High-Grade Serous Carcinoma.

Ovarian cancer is the deadliest gynecologic malignancy, and therapeutic options and mortality rates over the last three decades have largely not changed. Recent studies indicate that the composition of the tumor immune microenvironment (TIME) influences patient outcomes. To improve spatial understanding of the TIME, we performed multiplexed ion beam imaging on 83 human high-grade serous carcinoma tumor samples, identifying approximately 160,000 cells across 23 cell types. From the 77 of these samples that met inclusion criteria, we generated composition features based on cell type proportions, spatial features based on the distances between cell types, and spatial network features representing cell interactions and cell clustering patterns, which we linked to traditional clinical and IHC variables and patient overall survival (OS) and progression-free survival (PFS) outcomes. Among these features, we found several significant univariate correlations, including B-cell contact with M1 macrophages (OS HR = 0.696; P = 0.011; PFS HR = 0.734; P = 0.039). We then used high-dimensional random forest models to evaluate out-of-sample predictive performance for OS and PFS outcomes and to derive relative feature importance scores for each feature. The top model for predicting low or high PFS used TIME composition and spatial features and achieved an average AUC score of 0.71. The results demonstrate the importance of spatial structure in understanding how the TIME contributes to treatment outcomes. Furthermore, the present study provides a generalizable roadmap for spatial analyses of the TIME in ovarian cancer research.

Evasion on general GAN-generated image detection by disentangled representation

Images generated by the Generative Adversarial Network (GAN) are too realistic to be distinguished by humans. Recently, some detection methods have been proposed to distinguish between generated and real images. However, these methods rely on specific detection techniques and can be easily detected by other types of detection methods. This study aims to investigates the security of the GAN-generated image detection method by devising a method to evade general detection. The features related and unrelated to differentiating between real and generated images are disentangled by a GAN model in our model. The unrelated features contain information about the image content, while the related feature provides useful information for identifying generated images. Our method then camouflages a generated image by using its unrelated features and the related features of real images. The main advantages of our model include its ability to generalize to different detectors and adapt to the prior information about detectors. Experimental results confirm the superior evasion capability of our proposed method compared to other detector-dependent and independent methods across different popular detection methods.

A cross-omics data analysis strategy for metabolite-microbe pair identification.

Given the pivotal roles of metabolomics and microbiomics, numerous data mining approaches aim to uncover their intricate connections. However, the complex many-to-many associations between metabolome-microbiome profiles yield numerous statistically significant but biologically unvalidated candidates. To address these challenges, we introduce BiOFI, a strategic framework for identifying metabolome-microbiome correlation pairs (Bi-Omics). BiOFI employs a comprehensive scoring system, incorporating intergroup differences, effects on feature correlation networks, and organism abundance. Meanwhile, it establishes a built-in database of metabolite-microbe-KEGG functional pathway linking relationships. Furthermore, BiOFI can rank related feature pairs by combining importance scores and correlation strength. Validation on a dataset of cesarean-section infants confirms the strategy's validity and interpretability. The BiOFI R package is freely accessible at https://github.com/chentianlu/BiOFI.

OMS-SLAM: dynamic scene visual SLAM based on object detection with multiple geometric feature constraints and statistical threshold segmentation

Abstract SLAM technology is crucial to robot navigation. Despite the good performance of traditional SLAM algorithms in static environments, dynamic objects typically exist in realistic operating environments. These objects can lead to misassociated features, which in turn considerably impact the system’s localization accuracy and robustness. To better address this challenge, we have proposed the OMS-SLAM. In OMS-SLAM, we adopted the YOLOv8 target detection network to extract object information from environment and designed a dynamic probability propagation model that is coupled with target detection and multiple geometric constrains to determine the dynamic objects in the environment. For the identified dynamic objects, we have designed a foreground image segmentation algorithm based on depth image histogram statistics to extract the object contours and eliminate the feature points within these contours. We then use the GMS (Grid-based Motion Statistics) matching pair as the filtering strategy to enhance the quality of the feature points and use the enhanced feature points for tracking. This combined method can accurately identify dynamic objects and extract related feature points, significantly reducing its interference and consequently enhancing the system's robustness and localization accuracy. We also built static dense point cloud maps to support advanced tasks of robots. Finally, through testing on the high-speed dataset of TUM RGB-D, it was found that the root mean square error of the Absolute Trajectory Error (ATE) in this study decreased by an average of 97.10%, compared to ORB-SLAM2. Moreover, tests in real-world scenarios also confirmed the effectiveness of the OMS-SLAM algorithm in dynamic environments.

DCP-Net: A Distributed Collaborative Perception Network for Remote Sensing Semantic Segmentation

Collaborative perception enhances onboard perceptual capability by integrating features from other platforms, effectively mitigating the compromised accuracy caused by a restricted observational range and vulnerability to interference. However, current implementations of collaborative perception overlook the prevalent issues of both limited and low-reliability communication, as well as misaligned observations in remote sensing. To address this problem, this article presents an innovative distributed collaborative perception network (DCP-Net) specifically designed for remote sensing applications. Firstly, a self-mutual information match module is proposed to identify collaboration opportunities and select suitable partners. This module prioritizes critical collaborative features and reduces redundant transmission for better adaptation to weak communication in remote sensing. Secondly, a related feature fusion module is devised to tackle the misalignment between local and collaborative features due to the multiangle observations, improving the quality of fused features for the downstream task. We conduct extensive experiments and visualization analyses using three semantic segmentation datasets, namely Potsdam, iSAID, and DFC23. The results demonstrate that DCP-Net outperforms the existing collaborative perception methods comprehensively, improving mIoU by 2.61% to 16.89% at the highest collaboration efficiency and achieving state-of-the-art performance.

Predicting behavior in extinct reptiles from quantitative analysis of trigeminal osteological correlates

IntroductionVertebrate sensory systems are in close contact with surrounding tissues, often leaving bony signatures behind. These bony features are the keys to assessing variation in sensory systems in fossil taxa. The trigeminal sensory system (e.g., trigeminal ganglion, ophthalmic, maxillary, and mandibular divisions) has osteological correlates throughout the skull, including the braincase (e.g., trigeminal fossa, prootic notch, ophthalmic and maxillomandibular foramina) and rostrum (e.g., mandibular canal, neurovascular foramina).MethodsHere we measured and compared these features among a morphologically, phylogenetically, and ecologically diverse sample of sauropsids to determine strength of osteological correlates and to explore ecomorphological trends. We determined several suitable osteological correlates for trigeminal soft tissue features and discounted foramen count alone as a suitable osteological correlate. However, when size was accounted for, foramen count becomes a useful indicator of sensory ecology.Results and discussionAmong extant taxa, those engaging in tactile sensory behaviors with the face exhibit relatively larger trigeminal tissues and osteological correlates than those not engaging in tactile sensory behaviors. Though patterns are unclear among several clades, both relative feature sizes and models used to predict sensory capacity reveal a trend of increasing tactile sensitivity along the pseudosuchian lineage. Overall, a quantitative assessment of ecomorphological trends of trigeminal osteological correlates proves informative for the hypotheses of sensory behavior in extinct taxa and supports the use of similar assessment methods for other osteological correlates.

Drive-by bridge damage detection by vehicle-bridge interaction neural operator

Drive-by bridge damage detection using vibrations of vehicles for damage detection of bridges has been studied since it needs no instrumentation on bridges. However, it is still a challenge to be able to extract features that are sensitive to bridge damage and relevant to the responses of the bridge. To address the challenges of drive-by bridge damage detection, machine learning-based approaches have also been actively investigated in recent research. With supervised learning methods, it is almost impossible to obtain training data on the damage state of a bridge. On the other hand, unsupervised learning approaches have been considered, but they only provide changes in relative features rather than physical properties that are useful for estimating the structural performance. To address the above issues, this study aims to propose and investigate the feasibility of drive-by bridge damage detection using a vehicle-bridge interaction neural operator (VINO). In the proposed method, numerical simulations of vehicle-bridge interactions considering the damage field of the bridge are first carried out to generate physically informed training data. The VINO is then constructed using the physically informed training data. However, VINOs are still insufficient to model real bridges. Therefore, in order to improve the practicality of the physically-informed VINO, data-informed fine-tuning is carried out using available data from real bridges. It is noted that no damage data is required in the fine-tuning stage. The feasibility of the drive-by bridge damage detection using VINO is discussed using an in-house experiment on a model bridge under a moving vehicle.

RCFNet: Related Cross-level Feature Network with Cascaded Self-distillation for Monocular Depth Estimation

Monocular depth estimation (MDE) is a challenging yet crucial computer vision task, which aims to generate accurate depth maps from a single image. Existing MDE approaches mainly rely on extracting and fusing diverse information from multi-level features to improve prediction accuracy. However, these methods often apply a traditional feature pyramid structure, neglecting a comprehensive exploration of feature fusion paths across multiple levels. Moreover, a single-feature fusion strategy has limited ability to optimize the network. We propose a novel related cross-level feature network (RCFNet) with cascaded self-distillation for monocular depth estimation, including a cross-level feature enhancement (CLFE) module, a hierarchical feature cross refinement (HFCR) module, and a cascaded self-distillation (CSD) module. The CLFE module integrates cross-level features to further exploit the highest-level features, where a channel attention mechanism with hybrid weight operations is deployed to enhance the initial features. The HFCR module adaptively captures strongly correlated complementary information through a window-based multi-head cross-attention mechanism to generate refined features. Meanwhile, the CSD module with a hierarchical feature transformation loss is proposed, which can be viewed as a virtual teacher to progressively extract discriminative features within the network for better gradient flow improvement. Extensive experiments on NYUv2 and KITTI datasets demonstrate that our method outperforms existing SOTA MDE methods in terms of accuracy capacity and robustness.

Legal responsibility in agricultural relations

In modern conditions of modernization of state agricultural policy, the role of agricultural law, subject of legal regulation, protection of the interests of the entities of agricultural sector, and ensuring food security of the republic is increasing. The goal is to study the features of agricultural legal relations, identifying main problems associated with the application of legal liability. Analysis of the state, use of rules and norms of agricultural legislation and development of measures aimed to support, stimulate, and protect the rights of agricultural producers in Kazakhstan. The methods are based on materials from domestic and foreign scientists, scientific publications, and changes in legislative regulations. A comparative analysis and assessment of legal relations in agro-industrial production were used. Results - the state of affairs is considered and important issues of application of legal responsibility in the context of lawful actions and its features are identified. Various types of violations of legal obligations are analyzed: non-compliance with land use rules, sanitary and hygienic requirements, environmental standards - illegal use of pesticides, abuse of antibiotics in raising livestock, violation of environmental standards that can pollute water or damage the soil. Conclusions - the authors propose a number of effective measures to improve legal behavior in agricultural entities: strengthening control by the state law enforcement agencies, creating more effective punishment mechanisms, increasing awareness of participants in agricultural legal relations, which will prevent unfair practices and will promote conservation of natural resources and environment. Agricultural law presupposes land, property, labor, financial, and management relations in agriculture. This contributes to organizational, production and economic activities of agricultural production entities in accordance with the goals of entrepreneurship in agricultural sector.

FORMATION OF SPATIAL FACTORS ENSURING THE INVESTMENT ATTRACTIVENESS OF REGIONAL LANDS

It has been proven that modern directions and features of land relations at the regional level require a rethinking of approaches to their formation in the context of ensuring the investment attractiveness of regional lands. The purpose of the study is to identify spatial factors in ensuring the investment attractiveness of the lands of the regions. To achieve the goal, the following tasks were solved: to analyze the state and trends of changes in spatial factors; to substantiate the spatial factors of ensuring the investment attractiveness of the lands of the regions. In order to solve the problematic aspects, it is necessary to define and justify the spatial factors of ensuring the investment attractiveness of the lands of the regions, which is an urgent and timely task. A categorical apparatus for determining the investment attractiveness of the lands of the regions was formed, which is based on a set of interrelated spatial, economic, urban planning, ecological, innovative, security, regulatory and legal factors and modern tools of geo-information systems, methods, models, which made it possible to build a quantitative basis for the development of adoption reasoned decisions regarding the attraction of investments in the field of land relations at the regional level. As a result of the study, the factors of land formation and use that affect the investment attractiveness of the lands of the regions and build the foundation for the creation of spatial support are determined. Spatial factors ensuring the investment attractiveness of land at the regional level are determined. The presented factors are an element of a multi-level system of indicators for assessing the level of ensuring the investment attractiveness of the lands of the regions in the context of the development of the integral assessment method. Spatial factors as an important element of investment attractiveness of regional land use are used in mathematical modeling to establish cause-and-effect relationships and create a basis for characterizing further changes. This makes it possible to develop scientifically based recommendations for ensuring the investment attractiveness of regional land use. Keywords: land use, investment attractiveness of land, regions, spatial factor.

An infrared and visible light video fusion method based on chaos theory and PID control

Differences in the imaging mechanisms of infrared and visible light images lead to differences in the way their visually meaningful gradients are formed. Existing fusion methods use the same feature extractor to extract features from the source video frames, which ignores the differences in the gradients of video frames from different modalities. In this paper, we propose an infrared and visible light video fusion method based on chaos theory and proportional integral differential (PID) control. Firstly, for the Lorentz chaotic system, we give it initial values and parameters, and iterate it to obtain three scrambling sequences, through which the source video frames are scrambled in the rows, columns, and diagonal directions respectively to eliminate their visually meaningful gradients, so that the features extracted are of comparable scales in the same layer, and the fusion process can be carried out in the scale-consistent space. Second, we propose a structure-aware relative total variation feature extraction method (saRTV) for the two-scale decomposition of source video frames, which can transfer more features of source video frames to the detail layer. Then, based on our previous work, this paper introduces PID control to construct a closed-loop control system through transfer function design, controller design and measurement function design. This control system is used to fuse the detail layer, so as to realize the real-time guidance of the source video frames to the fusion process. Experiments on public datasets demonstrate that our method has better performance compared to some state-of-the-art methods.

Монастирі та чернецтво Київської єпархії синодального періоду: регламентація діяльності в системі російського церковного законодавства

The article aims to specify the status of Orthodox monasteries and monasticism in the Kyiv eparchy between the 19th and early 20th centuries within the framework of the then-existing Russian church legislation. Research methodology is grounded in the principles of historicism and scientific objectivity, using critical, systematic and comparative analysis of sources. These methods and principles have enabled a comprehensive study of various phenomena in their dynamics and totality, taking into account all conflicting factors. By employing these diverse methods, the study has traced the impact of Russian church legislation on events and processes regulating the activities of monasteries and monasticism in the Kyiv eparchy during the synodal period. Conclusions. The 18th-century reforms in the Russian Empire’s ecclesiastical sphere designated the Holy Governing Synod as the legislative authority over the Orthodox Church, fully subordinating it to the Russian imperial government. During this century, church legislation was established, which, with minor modifications and additions, remained in effect throughout the 19th and early 20th centuries and applied to Ukrainian Orthodox eparchies. The 18th century marked a period of profound and comprehensive transformations in the history of monasteries and monasticism, characterized by strict regulation of monastic life, daily routines and the rights of the inhabitants. The primary feature of church-state relations in the 19th and early 20th centuries was the state’s total control over the Church’s affairs. The Holy Synod controlled matters such as the establishment of new monasteries, granting them status, accepting individuals into monasticism and determining the number of monastics. The monasteries of the Kyiv eparchy during this period were managed by the eparchial bishop and were entitled to elect an abbot, who was then approved by the Holy Synod through its decree. Monasteries, both male and female, were classified into three categories, either communal or non-communal, with a clearly defined monastic staff determined by the Synod.

Similarity-based Graph Convolution Collaborative Recommendation Approach

With the rapid and iterative development of science and technology, a large amount of information exceeds the range that can be accepted, processed, or effectively utilized by an individual or a system, and recommendation algorithms can, to a certain extent, solve such problems, but traditional recommendation algorithms do not have a good solution to the problems related to data sparsity and recommendation accuracy. A similarity-based graph convolutional neural collaborative recommendation method (GCSCF) is proposed. The similarity algorithm based on the attributes of the item is used to find the item with the highest similarity and has not interacted with the current user, and this item is set to interact with the current user. The relevant interaction information of the user and the item is converted into relative feature vectors; the feature vectors are propagated using a graph convolutional neural network to aggregate the localized information, and the weight coefficients based on the item ratings are normalized to reduce the noise caused by the information aggregation. Comparative experiments are conducted on two public datasets, MovieLens-1M and Movielens-100K, with five baseline models on the set, and using Recall, Normalized Discounted Cumulative Gain (NDCG), and Precision as the evaluation metrics, and the results of the experiments show that the performance of the proposed social recommendation model better than other models.

Features of bond-slip relations: 3D finite element analysis based on tests of short RC ties

The interaction between concrete and reinforcement is highly complex and is of fundamental importance for predicting the behaviour of reinforced concrete (RC) structures. While the interaction of the two materials is often characterised by a bond – slip law, there are currently no such laws capable of accurately predicting serviceability characteristics, such as deflection, crack spacing, and width. This paper examines the effect of various parameters on the shape of bond – slip relation at loads before yielding of reinforcement. The study is based on a mesoscopic numerical analysis, utilizing the finite element method along with a friction cohesive zone model to explore the bond-slip phenomena in short RC ties. The numerical model is combined with an experimental campaign involving six short concrete ties reinforced with 20 mm bars. Steel strain profiles were monitored within the reinforcement using electrical strain gauges. These experimental steel strain profiles served as a robust tool for controlling and calibrating numerical models. The numerical models employed solid finite elements to simulate both reinforcement and concrete, with special zero-thickness plain elements applied to simulate the friction cohesive contact at the steel-concrete interface. Bond-slip relations were obtained from the numerically modelled reinforcement strain profiles. It was shown that concrete strains can be ignored when assessing slip. The effect of the embedded length of reinforcement under the fully confined conditions was demonstrated to have little effect on bond-slip relations. It was also shown that the maximum bond stress is strongly related to the thickness of the concrete cover. The effect of load intensity on the bond – slip behaviour was investigated. It was shown that under full confinement, the initial bond stiffness was not affected by load intensity. However, degradation of bond stiffness with increasing load due to internal cracking took place in the RC ties with a small cover/diameter ratio.

Limits of self and Other xenosophic responsiveness: Including complex emotions, power differences and possible futures

In a complementary commentary on Streib, we highlight complexities of self and Other responsiveness when researching and attempting to enact xenosophic alternatives to xenophobic relations with a wide range of others and including related problematic forms of personal and group ‘egocentricity’. Using our similar attempts to be reflexive in theory and practice about self and Other responsiveness in our own social, political, community and cultural psychology research (extending Streib’s focus on developmental psychology), we use the later philosophical approach of Ludwig Wittgenstein – rather than the phenomenological philosophy of Waldenfels – to explore instances of self and ‘extraordinary Other’ relations via examples of everyday and form-of-life disagreements. We then focus on complex emotions and investigations of affective and discursive patterned features of self and Other relations to highlight features of responsiveness and collective wisdom evident in a dynamic typology of group-based and collective pride, shame and guilt relations in contexts of celebration, competition, challenge and conflict. The need to explore the limits of self and extraordinary Other responsiveness is shown by considering how possible futures and power considerations might lead us to step back from potentially becoming other to ourselves.

Chromatin profiling identifies putative dual roles for H3K27me3 in regulating transposons and cell type-specific genes in choanoflagellates.

Gene expression is tightly controlled during animal development to allow the formation of specialized cell types. Our understanding of how animals evolved this exquisite regulatory control remains elusive, but evidence suggests that changes in chromatin-based mechanisms may have contributed. To investigate this possibility, here we examine chromatin-based gene regulatory features in the closest relatives of animals, choanoflagellates. Using Salpingoeca rosetta as a model system, we examined chromatin accessibility and histone modifications at the genome scale and compared these features to gene expression. We first observed that accessible regions of chromatin are primarily associated with gene promoters and found no evidence of distal gene regulatory elements resembling the enhancers that animals deploy to regulate developmental gene expression. Remarkably, a histone modification deposited by polycomb repressive complex 2, histone H3 lysine 27 trimethylation (H3K27me3), appeared to function similarly in S. rosetta to its role in animals, because this modification decorated genes with cell type-specific expression. Additionally, H3K27me3 marked transposons, retaining what appears to be an ancestral role in regulating these elements. We further uncovered a putative new bivalent chromatin state at cell type-specific genes that consists of H3K27me3 and histone H3 lysine 4 mono-methylation (H3K4me1). Together, our discoveries support the scenario that gene-associated histone modification states that underpin development emerged before the evolution of animal multicellularity.

Relative frequencies and clinical features of Guillain-Barré Syndrome before and during the COVID-19 pandemic in North China

ObjectiveMost studies investigated the relationship between COVID-19 and Guillain-Barré syndrome (GBS) by comparing the incidence of GBS before and during the pandemic of COVID-19. However, the findings were inconsistent, probably owing to varying degrees of the lockdown policy. The quarantine requirements and travel restrictions in China were lifted around December 7, 2022. This study aimed to explore whether the relative frequency of GBS increased during the major outbreak in the absence of COVID-19-mandated social restrictions in China.MethodsGBS patients admitted to the First Hospital, Shanxi Medical University, from December 7, 2022 to February 20, 2023, and from June, 2017 to August, 2019 were included. The relative frequencies of GBS in hospitalized patients during different periods were compared. The patients with and without SARS-CoV-2 infection within six weeks prior to GBS onset formed the COVID-GBS group and non-COVID-GBS group, respectively.ResultsThe relative frequency of GBS among hospitalized patients during the major outbreak of COVID-19 (13/14,408) was significantly higher than that before the COVID-19 epidemic (29/160,669, P < 0.001). More COVID-GBS patients (11/13) presented AIDP subtype than non-COVID-GBS cases (10/27, P = 0.003). The mean interval between onset of infective symptoms and GBS was longer in COVID-GBS (21.54 ± 11.56 days) than in non-COVID-GBS (5.76 ± 3.18 days, P < 0.001).ConclusionsCOVID-19 significantly increased the incidence of GBS. Most COVID-GBS patients fell into the category of AIDP, responded well to IVIg, and had a favorable prognosis.

Features of Civil Procedural Legal Relations Arising in the Course of Judicial Management of the Process

The judicial management of the civil process is considered through the legal category “civil procedural legal relationship”, the elements of the structure of individual civil procedural legal relations arising from the implementation of the court’s leading procedural activities are determined. The methodological basis of the study was system analysis, formal logical method, analysis and synthesis. According to the results of the study, the definition of judicial leadership as a subsystem of special procedural legal relations is formulated, the object, subject composition, content, and grounds for the emergence of a single (elementary) legal relationship that develops when the court implements guiding procedural actions are identified.

КУЛЬТУРНЫЕ КОНТАКТЫ МЕЖДУ РОССИЕЙ И КИТАЕМ НА ДАЛЬНЕВОСТОЧНЫХ ТЕРРИТОРИЯХ В XIX – НАЧАЛЕ XX в.

The paper analyzes the formation and development of cultural relations between Russia and China in the 19th – early 20th centuries in the Far Eastern territories. The issues of the origin of Russian-Chinese cultural interaction, the contact between Russian and Chinese cultures, as well as the peculiarities of contacts between the two ethnic groups are covered. The work uses a historical-chronological research method, which made it possible to trace the formation and development of contacts in the field of culture between the two countries in the Far Eastern border region in the mid-19th – early 20th centuries (from the signing of the Aigun and Beijing treaties to the October Revolution of 1917), as well as a systematic approach, the use of which led to the consideration of cultural ties as a component of the overall system of Russian-Chinese relations at the interstate and interregional levels. Materials in Chinese in the author's translation were introduced into scientific circulation. When studying cultural contacts between the two countries, the concept of sociocultural interaction developed by N.A. Samoilov was applied, which made it possible to analyze the features of relations between the two countries in the field of culture and highlight the forms of interaction. According to the authors, the development of mutual contacts in the field of culture was determined by foreign policy and socio-economic conditions, significant transformations in the political, economic and cultural spheres that took place in the mid-19th – early 20th centuries in the Russian state and the Qing Empire, as well as the meeting of Chinese migration and Russian colonization flows in the Russian Far Eastern borderland. In general, Russian-Chinese sociocultural interaction during the period under study went through several stages, during which the Russian and Chinese peoples mutually recognized each other and learned to interact. At the same time, in the Far Eastern territories at the turn of the century, a contact zone of relations between two ethnic groups was formed, a special environment of Russian-Chinese interaction was formed, and at the same time, the difference between the two cultures and the impossibility of their mixing and mutual assimilation became increasingly obvious.