Multidimensional Statistical Analysis Research Articles

Uncovering Patterns of Fintech Behavior in Italian Banks: A Multidimensional Statistical Analysis

Fintech is changing the financial system and increasing the possibility of access to financial services. Considering the centrality of the banking world in providing financial services, this study aims to offer an analysis of banks' adoption of Fintech. Exploiting a sample of Italian listed banks, this study investigates their adoption of Fintech. Multiple correspondence analysis and hierarchical clustering classification are used to study Fintech factors in Italian banks, starting from significant variables highlighted by the literature: disclosure, financial investments, and collaborations in Sandboxes. Results show that different bank subgroups have specific Fintech features based on various structural characteristics. The implications are both academic and practical. On the one hand, we highlight how these measures make it possible to have homogeneous clusters. On the other hand, we have indications of policies and best practices.

The effect of rehabilitation measures on the severity of endotoxicosis and its relationship with changes in hemorheology in acute poisoning

Introduction. The use of multidimensional statistical analysis methods (factorial and cluster methods) to study the pathogenesis and sanogenesis of acute poisoning (AP) with psychopharmacological agents (pPPhA), neurotoxicants (pNT) and corrosive substances (pCS) did not allow us to judge the presence of a direct connection between the hemorhealogy system (HR). We received a positive answer to this question earlier with the help of pair correlation analysis (PCA). New data on the sanogenetic effect of the applied methods of rehabilitation treatment in terms of changes in the indicators of HR and endotoxicosis (ET) and the relationship between them are also interesting. The purpose of the work is to assess the initial state of the indicators of HR and ET and the effect on them of a combination of medicinal and non–medicinal products used as part of rehabilitation measures for AP. Material and methods. Paired correlation analysis of the block structure of the obtained correlation matrices was applied to 52 patients with severe pPPhA, pNT and pCS. This analysis established the relationship between two indicators – both before the start of rehabilitation measures (the use of ethylmethylhydroxypyridine succinate, laser hemotherapy, hyperbaric oxygenation and mesodiencephalic modulation in accordance with the type of AP), and after their completion, before the discharge of patients from the hospital. Results. Statistically significant correlations were established between the indicators of HR and ET both before the start of treatment (0.44–0.94, without sign) and after its completion (0.49–0.99, without sign), which allowed us to confirm at a higher level a direct link between the development of HR and ET disorders, as well as to draw a conclusion about the sanogenetic effect of rehabilitation treatment. Limitations. The study has no limitations for further use of this methodological approach. Conclusion. The obtained data can serve as a justification for the introduction into practice of the proposed methods of mathematical analysis of the results of treatment measures.

Follicular fluid lipidomics analysis reveals altered lipid signatures in patients with polycystic ovary syndrome

Background This research investigates the metabolic profiles of follicular fluid (FF) samples from patients with polycystic ovary syndrome (PCOS) undergoing in vitro fertilisation and aims to identify diagnostic and therapeutic biomarkers for PCOS through lipidomic analysis. Methods We performed non-targeted lipid analysis of FF samples from women with PCOS (n = 6) and normal controls (n = 6) using ultra-high-performance liquid chromatography–tandem mass spectrometry. Differential lipids between the two groups were screened using multidimensional statistical analysis, followed by fold change analysis and t-tests to identify potential PCOS biomarkers. Results Multivariate statistical analysis revealed significant differences in FF lipid levels between the PCOS and control groups. Five different lipids were selected as standards, with p < .05. Phosphatidylcholine (PC), the main differentially expressed lipid, was significantly increased in the FF of the POCS group and was closely related to other lipids. Conclusions Using ultra-high-performance liquid chromatography–tandem mass spectrometry, we investigated lipid biomarkers based on FF lipidomics to provide useful information for the discovery of diagnostic markers for PCOS. Our study identified five distinct lipids as potential markers of PCOS, with PC being the primary aberrant lipid found in the FF of patients with PCOS.

Multidimensional statistical analysis of social inequalities in Italy

The analysis of social inequalities is a topic of current interest and is studied as a factor in the evolution and measurement of the level of well-being. A fundamental prerequisite for a correct statistical analysis of this phenomenon is the need to share a univocal definition of the concept of social inequalities. This work starts from the need to identify territorial areas and/or population subgroups characterized by situations of hardship or strong social exclusion through the construction of indicators that can estimate situations of social inequalities in small areas. Scientific research options have been oriented towards the establishment of a multidimensional approach, sometimes renouncing dichotomous logic to go as far as fuzzy classifications in which each unit simultaneously belongs and does not belong to the selected category. Multidimensional statistical analysis methodologies (TFR method) and Density Based Spatial Clustering methods (DBSCAN) will therefore be used to aggregate adjacent spatial units with high intensity of social inequalities.

Effects of deep coal mining on groundwater hydrodynamic and hydrochemical processes in a multi-aquifer system: Insights from a long-term study of mining areas in ecologically fragile western China

The groundwater hydrodynamic and hydrochemical process of the multi-aquifer system will experience complicated and serious influence under deep coal mining disturbance. There is relatively little research that has integrated hydrodynamic and hydrochemical properties of groundwater to investigate the spatiotemporal distribution characteristics and evolution patterns of hydrogeochemistry and hydrodynamic information in deep multi-aquifer systems. The study of the groundwater hydrodynamic and hydrochemical spatiotemporal coupling response of multi-aquifer systems under the deep and special thick coal seam mining-motivated effect in ecologically fragile western mining areas is of great significance for the safe mining of coal resources and ecological environment protection. In this research, the hydrochemical analysis data composed of 218 groundwater samples from Tangjiahui coalfield, Northwest China with 1526 measurements and a 6-year (2016–2021) sampling period were collected for studying the hydrogeochemical spatiotemporal evolution process and governing mechanism of the multi-aquifer system using hierarchical cluster analysis, ion-ratio method, saturation index and multidimensional statistical analysis. Additionally, wavelet analysis and cross-wavelet coherence analysis were implemented to quantitatively recognize the spatiotemporal variation characteristics of hydrodynamic information and analyze the coherence relationships between time series. The results demonstrate that the hydrochemical characteristics exhibit significant spatial differences, while the temporal variation of hydrochemical characteristics in the Permian Shanxi Formation fractured sandstone aquifer (PSFFA), mine water (MW), and Ordovician karst limestone aquifer (OKA) is not significant. The water-rock interaction is the predominant control mechanism for the spatial evolution of hydrogeochemistry in the research area. Moreover, the large-scale mining of deep coal seams controls the type and degree of water-rock interactions by damaging the structure of aquifers and altering the hydrodynamic conditions of groundwater. The period from 2016 to 2021 exhibits multi-time scale characteristics in time series of precipitation, mine water discharge, and the water level of PSFFA and OKA. The mine water discharge has a positive correlation with the water level of PSFFA and OKA, whereas the significant period of precipitation and the water level of PSFFA coherence is not obvious. The research findings not only provide in-depth insights to protect the groundwater resources in water-shortage mining areas but also promote the secure mining of deep coal resources.

Evaluation of changes caused by HR-HPV infection in squamous cell carcinoma of the head and neck using Raman microspectroscopy in combination with multivariate statistical analysis

Abstract Introduction: Squamous cell carcinoma of the head and neck region (HNSCC), with a positive status for high oncogenic potential human papillomavirus (HR-HPV), represents a clinically distinct disease entity compared to HPV-independent cases. Patients exhibit variations in prognosis and proposed therapy regimens. A prompt and reliable diagnosis of the presence of HPV infection could optimize the treatment for these patients. Currently employed treatment methods are long-term, expensive, and lack specificity, especially when administered separately. Material and methods: The research objective of this study is to explore significant differences in the Raman spectra of biological samples taken from patients with HNSCC, facilitating the confirmation of HPV virus presence. Study groups were delineated based on histopathological diagnosis and molecular biology tests, confirming the biological activity of the virus and the presence of the HR-HPV form with a diagnosis of a specific subtype. Results: To identify high oncogenic potential human papillomavirus (HR-HPV) infection as a crucial factor in squamous cell carcinoma of the head and neck region, an effective automatic data analysis system was established, relying on Raman microspectroscopy and multivariate analysis. Our results showed clear ranges of the Raman spectrum that differentiated between HPV-associated and non-HPV-associated cancers. Conclusions: In conclusion, our experience shows a great diagnostic potential of Raman confocal microscopy with multidimensional statistical analysis. In the future, the use of this method may allow for the creation of an effective and automated HR-HPV detection system in neoplastic tissue.

Nontargeted metabolomics and enzyme inhibitory and antioxidant activities for chemical and biological characterization of jujube (Ziziphus jujuba) extracts

The chemical and biologically active characterization of jujube samples (fruits, cores, and leaves) were carried out by the integrated nontargeted metabolomics and bioassay. Firstly, collision cross-section values of active compounds in jujubes were determined by ultrahigh-performance liquid chromatography coupled with ion mobility quadrupole time-of-flight mass spectrometry. Then, a multidimensional statistical analysis that contained principal component analysis, partial least squares-discriminant analysis and hierarchical clustering analysis was employed to effectively cluster different tissues and types of jujubes, making identification more scientific. Furthermore, angiotensin-converting enzyme (ACE) and 2, 2-diphenyl-1-picrylhydrazyl (DPPH) were used to evaluate the quality of jujubes from a double activity dimension. The analytical results obtained by using ACE and DPPH to evaluate the quality of jujube were different from multivariate statistics, providing a reference for the application of jujube. Therefore, integrating chemical and biological perspectives to evaluate the quality of jujube provided a more comprehensive evaluation and effective reference for clinical needs.

Results of the XI-th International Conference &amp;quot;Multidimensional statistical analysis, Econometrics and modeling of real processes&amp;quot; named after S. A. Ayvazyan

On June 24-25, 2024, Moscow hosted the XI-th International conference &amp;quot;Multidimensional Statistical Analysis, Econometrics and Modeling of Real Processes&amp;quot; named after S. A. Ayvazyan, organized by the Central Economic and Mathematical Institute of the Russian Academy of Sciences in cooperation with the Moscow School of Economics of Lomonosov Moscow State University, Yerevan State University and the Armenian Mathematical Society. The review describes the main results presented in the breakout reports in two sections.

RootInteractive tool for multidimensional statistical analysis, machine learning and analytical model validation

The ALICE experiment [1] at CERN’s LHC is specifically designed for investigating heavy ion collisions. The upgraded ALICE accommodates a tenfold increase in Pb–Pb luminosity and a two-order-of-magnitude surge in minimum bias events. To address the challenges of high detector occupancy and event pile-ups, advanced multidimensional data analysis techniques, including machine learning (ML), are indispensable. Despite ML’s popularity, the complexity of its models presents interpretation challenges, and oversimplification in analysis often leads to inaccuracies. Our objective was to develop RootInteractive, a tool for multidimensional statistical analysis. This tool simplifies data analysis across dimensions, visualizes functions with uncertainties, and validates assumptions and approximations. In RootInteractive, it is crucial to easily define the functional composition of analytical parametric and non-parametric functions, exploit symmetries, and define multidimensional "invariant" functions and corresponding alarms. RootInteractive [2] adopts a declarative programming paradigm, ensuring userfriendliness for experts, students, and educators. It facilitates interactive visualization, n-dimensional histogramming/projection, and information extraction on both Python/C++ server and Javascript client. The tool supports client/server applications in Jupyter or standalone client-side applications. Through data compression, datasets with O(107) entries and O(25) attributes can be interactively analyzed in a browser with O(0.500-1 GB) size. Representative downsampling and reweighting/pre-aggregation enable the effective analysis of one year of ALICE data for various purposes.

Analysis of Users Balance Between Private and Public -- One Case from the TikTok

Information privacy is of paramount importance to everyone, but there are many Internet users privacy leaks. But inevitably, internet users need to provide some information of their own to satisfy a better web experience. Therefore, it is necessary to study the balance between personal information sharing and personal privacy. The studys goal is to develop a mathematical model that quantifies the trade-offs between individuals and society regarding the disclosure of private information. In the process of research, researchers use targeted questionnaires to obtain first-hand raw data, analyze users choices between sharing personal data and protecting personal privacy, and obtain users preferences for privacy protection measures. Through multi-dimensional statistical analysis of the questionnaire results, this paper reflects the current users awareness of personal privacy protection and the publics attitude towards the current phenomenon of privacy acquisition on social media. Furthermore, based on the original data of the questionnaire, it provides effective suggestions for researchers to modify the privacy protection policies of media platforms.

The potential of intellectual capital as a source of competitive advantage for banks using CART classification trees

Motivation: Most of the available analyzes on building banks’ competitiveness were based on typical financial ratios. The challenge for every modern bank is not just understanding the meaning of intellectual capital, but defining its elements and determining measures that enable its effective management, leading to the improvement and maintenance of a strong competitive position. Empirical research concerning the competitiveness of banks in Poland is increasingly focused not only on efficiency and financial indicators but more often on emphasizing the significance of the components describing the IC subsystems, which include: service quality, bank reputation, customer confidence in the financial service of a given bank and the attractiveness and comprehensiveness of its offer as significant determinants of the overall assessment of a given entity.Aim: The aim of the article is to systematize the definition of a bank’s intellectual capital and to indicate its role in building a bank’s long-term competitive position using multidimensional statistical analysis — classification tree (CART method).Results: The conducted analysis will allow to find rules (based on diagnostic indicators) classifying banks into separate groups (A, B, C). This will lead to the conclusion which indicators from the economic (EC) and intellectual (IC) capital layers have the greatest impact on the competitiveness of banks (2009–2020).

A systematic knowledge graph-based smart management method for operations: A case study of standardized management

Standardized routine operation management (SROM) has been widely accepted and applied by kinds of enterprises and played a key supporting role. With full use of the emerging knowledge-based smart management technology, SROM will further increase comprehensive efficiency and save human resources greatly at the same time, especially for small and medium enterprises (SMEs). Hence, we propose a systematic knowledge-based smart management method to transfer SROM activities from human operations to automatic response by means of knowledge explicitation, organization, sharing and reusing, which can be further achieved by employing knowledge graph. We took a typical SROM instance, ISO 9000 implementation management, as an example to validate the transformation from human activities to knowledge graph-based automatic operation. We firstly analyzed characteristics of domain knowledge and constructed an ontology model according to the knowledge stability. Secondly, a hybrid knowledge graph construction and dynamic updating framework together with related algorithms were designed by deliberately integrating semantic similarity calculation and natural language processing. Thirdly, we developed a question-answering mechanism and reasoning system based on the ISO 9000 implementation knowledge graph to support automatic decision and feedback for ISO 9000 routine operation management including knowledge learning and processes auditing. Finally, the practicability and effectiveness of SROM knowledge graph has been validated in a SME in China, realizing the application of question-answering, job responsibility recommendation, conflict detection, semantic detection, multidimensional statistical analysis. The proposed method can also be generalized to support auxiliary optimization decision, vertical risk control, operation mode analysis, optimization model improvement experience and so on.

Национальная стратегическая сила стран, международная торговля и экономическая успешность стран в нестабильном мире

This research is part of a larger project on modeling national power and security indicators. It involved the method of multidimensional statistical analysis as an integral indicator that characterizes the total potential of each country, as well as the strategic development of its socio-ecological and economic system. The national economic potential in the international trade network was represented as a graph that illustrates the trade flows between countries. The centrality index marked the importance of a particular country in the international trade network, i.e., its ability to affect other countries, and its vulnerability, i.e., its dependence on other countries. The graph took into account the national power of the country, its partner countries, and the commodity circulation between them. The authors used the case of the global pandemic crisis and the local sanctions imposed on Russia in 2014 to study the adaptive ability of powerful national economies. The research resulted in two regression models. The model of the economic bloc of the national power took into account the trade volume and the vulnerability index in the international trade network. The model of national GDP growth relied on the growth of the economic bloc of national power, the trade volume, and the increase in exports, as well as the vulnerability index in the international trade network.

Mechanical properties and microscopic characteristics of steel fiber coal gangue concrete

Incorporation of coal gangue in the concrete mixes can realize utilization of the solid waste and reduce extraction/use of natural aggregates. To improve the mechanical properties of coal gangue concrete, this paper studies use of steel fibre together with coal gangue coarse aggregate, coal gangue fine aggregate/sand in various concrete mixes. The effect of volume dosages of steel fibre and different levels of replacing nature coarse aggregate and river sand with coal gangue aggregates on concrete compressive strength was first investigated. Then, a design of experiment using orthogonal test was adopted to study concrete mixes with 3 factors, namely, coal gangue coarse aggregate, coal gangue sand and steel fibre, and each at 3 levels. Through multidimensional statistical data analysis of the test results, the primary and secondary factors and the optimal composition of the steel fibre reinforced coal gangue concrete were identified, and a grey prediction model for compressive strength of the concrete mixes established. The microstructural characteristics and failure mechanism of steel fiber reinforced coal gangue concrete was also studied and discussed.

Evaluation of the Statistical Distribution of Indexes of the Structure of Budget Investments

The purpose of the study is to substantiate methodological approaches for conducting a statistical study of the structure of budget investments and their approbation at the level of the regions of the Russian Federation on the basis of an assessment of data available in official statistical and administrative records on indexes of the composition of budget investments, analyzing scientific papers devoted to the study of the structure of investments, identifying and systematizing signs of gradation of budget investments for development and analysis their complex structure. The methodological proposals formed were the basis for the application of methods of multidimensional statistical analysis of the distribution of the regions of the Russian Federation by indexes of the structure of budget investments to determine territorial differences in the implementation of state investment programs of socio-economic development.Materials and methods. The study used theoretical methods: analysis, synthesis, comparison of sources of information about budget investments, as well as mathematical and statistical research methods: structural and dynamic analysis, descriptive statistics, multidimensional grouping, cluster analysis.Results. Based on the analysis of regulatory and legal documentation, scientific literature on the research topic, author’s publications, a classification of indexes of the structure of budget investments was formed. The structural and dynamic analysis of the index “Investments in fixed assets by sources of financing” (in the total amount of funds, in comparison with budget funds, by levels of budget expenditures of investments in fixed assets: federal budget, funds from the budget of the regions of the Russian Federation, local budget) was carried out for 2005-2009 and 2013-2021. The variability of the share of expenditures from the federal and regional budgets is revealed, which may be related to the implementation of state regulation measures in the redistribution of investment resources at the federal and regional levels. Using the methods of descriptive statistics, multidimensional grouping, clustering, a comprehensive analysis of the statistical distribution of indexes of budget investments by regions for the period 2015-2021 is presented, resulting in four clusters, an assessment of qualitative differences in the structure of budget investments by selected clusters is given.Conclusion. In this paper, a methodological toolkit is proposed for a full-system representation of the composition of budget investments, provided with the capabilities of official statistical and administrative accounting and allowing organizing the totality of indexes of the structure of budget investments by territorial division, by sources of financing, by spending directions. The practical significance of the study consists in a proven assessment of the statistical distribution of indexes of the structure of budget investments by the share of budget investments in the total volume of investments in fixed assets (own and attracted funds), as well as by budget levels (federal, regional and local levels), identified spatial and dynamic changes in the selected cluster groups of the Russian Federation regions. Executive authorities and local self-government bodies in the formation and implementation of budgets in the areas of spending budget investments in order to increase their socio-economic effectiveness can apply the results obtained.

A dataset of origin motifs of major Chinese mythological characters

Myths is an important carrier of traditional Chinese culture. There are numerous myths of different ethnic minorities, rich in content and diverse in form. Many mythological characters have become precious memories in the course of human history and Chinese civilization. With the analysis of mythical figures as the starting point, we take relevant mythological texts and narratives as research topics and important data sources in the field of humanities and social sciences, which is of great cultural significance and academic value in promoting the construction of big data in humanities, deepening the analysis of traditional Chinese cultural data, and innovating new methods of humanities and social science research. In this paper, we took the origin narrative motif of 50 core mythological characters in China as the research object, and collected 1,620 valid data from them, including the standard fields of motif, example, nationality, place of spread and source of literature. Meanwhile, we systematically analyzed and explained the data sources, data collection methods, data classification and structure. Moreover, we described the data samples in detail; and on the basis of listing relevant dataset examples, we further carried out a multi-dimensional statistical analysis of the way of generation, ethnic groups and geographical location, etc. Finally, we provided some suggestions on the application of the dataset in exploring the connotation of China’s multi-ethnic culture, cross regional cultural research and analysis of Chinese traditional culture.

M&amp;A Goodwill in Chinese A-share listed companies: Findings from Industrial and Regional Perspectives

Based on the data of China's A-share listed companies from 2007 to 2021, this paper conducts a multidimensional statistical analysis on the confirmation and impairment of M&amp;A(M&amp;A) goodwill of listed companies from the perspective of industry and region. The results of statistical analysis show that:(1) On the whole, the changes of goodwill related indicators can be divided into three stages: small M&amp;A in the budding stage; the sharp increase of goodwill and risk of its impariment in the boom stage; the order and standardization in the stable stage.(2) In terms of industry, the number of listed companies in the Manufacturing Industry was the largest, and their goodwill changes were the most representative. Goodwill in Culture, Sport and Entertainment and Health and Social Work was of low quality and high risk. Hotel and Catering Sectors, Mining and Transportation, Storage and Postal Services were the "goodwill-high-quality" industries. Agriculture, Forestry, Animal Husbandry and Fishery, Scientific Research and Technical Services, and Comprehensive Service belonged to the "goodwill-conservative" industries.(3) In terms of region, North China, led by the Beijing-Tianjin-Hebei economic circle, was the leader in China's M&amp;A market. In the budding stage, there was little confirmation for goodwill and provision for goodwill impairment in regions outside North China. During the boom stage, goodwill related indicators rose sharply in all regions. In the stable stage, the value of goodwill in each region did not change much, but the average value of provision for goodwill impairment increased, especially in northeast China and central China.

MEAT PRODUCTION INDUSTRIES OF KAZAKHSTAN AND RUSSIA: COMPARATIVE ANALYSIS AND TRENDS DEVELOPMENT

The purpose of the study. To analyze the state of meat production in the Republic of Kazakhstan and the Russian Federation with the allocation of promising points of balanced growth and sustainable development in order to form clear prerequisites for improving the quality of nutrition of the population of these countries.Methodology. The following scientific methods are used in the work: statistical observation; comparative analysis; meta-analysis; multidimensional statistical analysis; analogy; synthesis; formalization; summary and grouping of statistical observation materials; absolute and relative statistical values; expert evaluation; retrospective.The originality / value of the research is to identify promising directions for the development and sustainable growth of the sectoral sectors of the agro-industrial complex (AIC) of the Republic of Kazakhstan and the Russian Federation.Findings. Today in the Russian Federation and the Republic of Kazakhstan, a large number of industry programs have been approved and are being implemented quite successfully, aimed at ensuring the sustainable and effective development of meat-product subcomplexes; promising forms of organization of the industry market are: contracting of raw materials; sale of products at wholesale sites; sale through commodity distribution networks of farmers' cooperation; supplies at the intersectoral level; stock exchanges; sale from farms; in Kazakhstan today, feed is produced almost 2 times less than the zootechnical norm; specialized enterprises for fattening cattle, sheep, pigs and poultry should become the basis of the meat industry of Kazakhstan; specialization, compared with diversified production, provides 1.5-2 times higher productivity and reduces the cost of livestock production by 25-40% in Kazakhstan; mechanized shepherd brigades should become the main organizational form of lamb production in steppe, semi-desert areas; one of the most significant risks in the development of modern animal husbandry in Russia is the threat of the spread of dangerous and especially dangerous diseases among; today in the Russian Federation there is a serious spread between the initial price of agricultural producers and the final price in the retail segment for meat products; the level of resource provision in the Russian Federation has quite high indicators and a steady growth trend is inherent in it; today the industry sector in Russia is functioning steadily, and the points of growth should be: export; entrepreneurship; investment; digitalization; veterinary control; the basis for the sustainable development of the industrial sectors of the Republic of Kazakhstan and the Russian Federation should be specialized enterprises for fattening cattle, sheep, pigs and poultry.

Provincial Legal Culture of the Northern Peasantry in the Context of the Implementation of Bourgeois Reforms of the Second Half of the XIX Century in Russia

The subject of the study is the legal culture of the northern peasantry of post-reform Russia in the period from 1861 to 1917. The implementation of the bourgeois reforms of the second half of the XIX century was due to the absence of private feudal dependence of the majority of the northern peasantry and bright regional aspects of the peasant community. Under the influence of the history of settlement, occupation, climatic and socio-economic conditions of existence, as well as state regulation of the peasant community in the European North, the provincial legal culture of the northern peasantry was formed. Through the prism of bourgeois reforms carried out in the second half of the XIX century, the article analyzes its qualitative state and external manifestation. The study uses a formal legal method, as well as a multidimensional statistical analysis by identifying, interpreting the content and interrelationships of semantic units of protocols of parish courts, regulatory legal acts, norms of customary law. Based on the understanding of archival material and information from pre-revolutionary periodicals introduced into scientific circulation for the first time, conclusions are substantiated about a sufficiently high level of legal culture of the peasantry and the readiness of the population to be included in the legal culture of Russian society common to all estates. The study of the main results of peasant, judicial and zemstvo reforms in the northern provinces leads to the conclusion about the inconsistency and inefficiency of the policy of the government of the Russian Empire in the field of the peasant question, the unresolved nature of which led to problems not only economic, but also political. The contradictory nature of the reforms and their uneven implementation have slowed down democratic processes and violated the principle of equality of all before the law.

Comparing the Volatile and Soluble Profiles of Fermented and Integrated Chinese Bayberry Wine with HS-SPME GC–MS and UHPLC Q-TOF

To evaluate the flavor characteristics of Chinese bayberry alcoholic beverages, fermented bayberry wine (FBW) and integrated bayberry wine (IBW) were investigated for their volatile and soluble profiles using HS-SPME GC-MS and UHPLC Q-TOF and were analyzed with multidimensional statistical analysis, including PCA and OPLS-DA. The volatile compounds 1-pentanol, β-caryophyllene and isopentanol were only detected in IBW. β-caryophyllene, the key flavor component of bayberry, was found to be the most abundant volatile compound in IBW (25.89%) and was 3.73 times more abundant in IBW than in FBW. The levels of ethyl octanoate, ethyl nonanoate, and ethyl decanoate were also several times higher in IBW than in FBW. These compounds contributed to the strong bayberry aroma and better fruity flavor of IBW. On the other hand, high levels of ethyl acetate and octanoic acid in FBW, representing pineapple/overripe or sweat odor, were key contributors to the fermented flavor of FBW. Soluble sugars, such as sucrose, D-glucose, and D-tagatose, as well as amino acids, such as L-glutamate and L-aspartate, had much higher levels in IBW. The anthocyanin pigment cyanidin 3-glucoside, which generates red color, was also higher in IBW. On the other hand, most of the differentially expressed alcohols, acids, amino acids, purines/pyrimidines and esters were present in higher concentrations in FBW compared to IBW. This demonstrated that IBW has a much sweeter and more savory taste as well as a better color generated by more anthocyanins, while FBW presents a more acidic and drier taste as well as a complex formation of alcohols and esters. The study also prompts the need for further research on the flavor profiles of IBW and its potential application and market value.