Цифровые инновации и права человека: дилеммы международной правоохранительной практики

The subject of the study is the legal nature of personal data, as well as a set of legal norms governing relations in the field of their processing and circulation in the Russian Federation and foreign countries. The article uses a comparative method, a system analysis method, as well as a forecasting method.The purpose of the article is to confirm or refute the hypotheses about the further strengthening of the contradictions between the emergence and implementation of new technologies for processing personal data versus ensuring the protection of human rights, as well as the expediency and possibility of using foreign legislative experience in domestic practice to counter these threats and reduce the risks arising from this and damage.Main results, scope. The article examines the legislative experience of legal regulation of the types, scope, and nature of personal data in the People's Republic of China, the United States of America, the Republic of Belarus, and the Russian Federation. At the same time, Chinese legislation most quickly responds to the challenges of the criminal use of biometric technologies, American legal norms are less acceptable for our practice due to the peculiarities of case law, and Belarusian law has only recently entered into force, opening the era of legal regulation in this area. The facts of the use of new technologies (such as deepfake) for the processing of biometric information for criminal purposes and the problems of law enforcement in this area, as well as legal disputes of citizens who have suffered damage from the use of these technologies, are analyzed. It is predicted that it will be impossible to fully ensure the protection of human rights in the context of the emergence of new technologies for processing personal data. The importance of the desire to predict threats to the protection of personal information at the stage of emergence of new technologies for processing personal data in order to neutralize them in a timely manner is indicated.Conclusion. An analysis of the legislation of foreign countries will make it possible to give preference to the Chinese experience, which promptly counteracts the risks of using new technologies for criminal purposes. An analysis of domestic and global law enforcement practice will make it possible to predict the spread of new ways of committing crimes, the misuse of personal data, and vulnerabilities in their storage and protection. At the same time, excessive restrictions on access to data, their processing and their circulation can make it difficult for law enforcement agencies to solve the tasks of ensuring state security and the protection of public order. It requires constant monitoring of threats and risks and timely technical and legal response to their manifestation. The purpose of the study has been achieved, ways to improve legislation in order to protect human rights in the context of the introduction of digital innovations in all spheres of human activity are proposed. Security, combating crime.Предпринимается попытка проведения сравнительного анализа правового регулирования защиты персональных данных в четырех странах: Китае, Беларуси, США и России – и формулирования соответствующих рекомендаций в контексте глобальных информационно-коммуникационных трендов. Рассматриваются существующие в настоящее время противоречия между возможностями, предоставляемыми инновационными цифровыми технологиями идентификации физических лиц и обработки их персональных данных, с одной стороны, и правами человека – с другой. Делаются выводы относительно необходимых в настоящее время изменений законодательства Российской Федерации по защите персональных данных с учетом технологических возможностей

The effectiveness of a complex microbial preparation when used in the vineyards of the Crimean Peninsula

A multicenter study of the application of the microbiological preparation Embiko® in vineyards with its introduction with drip irrigation in the Western foothill-seaside viticultural zone of Crimea was carried out. Granulometric analysis of the soil showed that in the experimental version with the use of Embiko®, the specific content of its fine fractions increased by 5%, i.e. the soil became looser. The introduction of Embico® in liquid form with drip irrigation gave an increase in yield by 1.3 kg per bush, while the sugar content of the berry juice improved by at least 8%. An antistress effect on plants under the influence of treatment with a biological preparation was also revealed, which manifests itself in a significant functional improvement of the leaf apparatus and an increase in the growth rates of grape shoots. When using the biological preparation Embico®, the profit or net income at the pilot site increased compared with the control option (without application) and, accordingly, the profitability of production increased by 79%

The Use of Machine Learning for Comparative Analysis of Amperometric and Chemiluminescent Methods for Determining Antioxidant Activity and Determining the Phenolic Profile of Wines

This paper presents an analysis of modern methods used to determine antioxidant activity. According to research by the World Health Organization, the deficiency of such important nutrients as antioxidants leads to a decrease in body resistance and the development of chronic diseases. When it comes to diet, the inclusion of foods with a high content of antioxidants helps to increase life expectancy. As a result of this research, the mass concentration of phenolic substances and the antioxidant activity of phenolic antioxidants in young white and red table wine materials were determined using amperometric and chemiluminescent methods in order to determine antioxidant activity. Regression equations reflecting the relationship between the indicator of antioxidant activity and the value of the mass concentration of phenolic substances in young table wine materials were derived. The conversion coefficient for determining the mass concentration of phenolic substances when using Trolox-C and gallic acid as standards was established, which was—3.75. Based on a multiple linear regression model, the total antioxidant activity of the samples (F9.5 = 19.10 and p = 0.0023) can be fairly accurately predicted with an R2 of 0.921 for the calibration data set. A neural network regression model (NNRM) was chosen for the machine-learning regression analysis of the antioxidant activity of the wine samples due to its effectiveness in predicting outcomes in various applications. The implementation was performed using the fitrnet function provided in the Statistics and Machine Learning Toolbox in MATLAB R2021b. The MSE of the calibration model was 0.056; however, the MSE for the three validation samples was much higher, at 0.272