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The close integration of modern cyber-physical systems with production and technological ones as well as with critical information infrastructure requires improving the monitoring process. The monitoring process is necessary with a constant increase in the possible points of entry into the system. The processing of a large amount of data coming from monitoring systems requires significant computing power. In this regard, it is relevant to reduce the dimension of the feature space while maintaining an acceptable monitoring accuracy. The proposed solution should be invariant to the dimension and orders of magnitude from which the time series supplied to the input of the monitoring system are composed. To obtain the most informative features in the formation of their set, it is proposed to use principal component analysis, and a method based on decision trees for their classification. A computational experiment was performed to confirm the applicability of the developed approach. The data of the network traffic for the research stand of the cyber-physical system water treatment were used in the experiment. The accuracy of the set of methods on the analyzed data was 98.74 %. The comparison with known studies showed an increase in the F-measure up to 0.925, which is 4.8 % higher than the most effective method used to date, namely the Isolation Forest method. The developed approach allows one to significantly increase the speed of identification and to detect anomalies of information security and functional safety of cyber-physical systems with high accuracy by reducing the dimension of the original feature space. The proposed approach can be used in event monitoring systems that deal with information security. The presented theoretical results can be useful for researchers of information security and functional safety of cyber-physical systems.

The lexicographic approach for solving multicriteria problems consists in the strict ordering of criteria concerning relative importance and allows to obtain optimization of more important criterion due to any losses of all another, to the criteria of less importance. Hence, a lot of problems including the ones of com­plex system optimization, of stochastic programming under risk, of dynamic character, etc. may be presented in the form of lexicographic problems of opti­mization. We have revealed conditions of existence and optimality of solutions of multicriteria problems of lexicographic optimization with an unbounded convex set of feasible solutions on the basis of applying properties of a recession cone of a convex feasible set, the cone which puts in order lexicographically a feasible set with respect to optimization criteria and local tent built at the boundary points of the feasible set. The properties of lexicographic optimal solutions are described. Received conditions and properties may be successfully used while developing algorithms for finding optimal solutions of mentioned problems of lexicographic optimization. A method of finding lexicographic of optimal solutions of convex lexicographic problems is built and grounded on the basis of ideas of method of linearization and Kelley cutting-plane method.

Gastric cancer (GC) is in top-five the most frequent cancers in Ukrainian males and is the third cause of death among patients with cancer. GC keeps its leading position in cancer ranks despite the decline in incidence and mortality over the last 50 years. Local epidemiological information will help in better targeting medical and public health interventions.The data about 8438 patients with newly diagnosed GC between 2009 and 2019 was obtained from Dnipro Cancer Registry.Incidence decreased from 24.5 to 22.6, mortality decreased from 21.4 to 15.7 (per 100000), death rate increased from 0.64 to 1.04 between 2009 and 2019. Over 11 years of observation incidence was 23.4, mortality was 19.4, death rate was 0.721. Standardised incidence ratio was 1.42, standardised mortality rate was 1.67; age-standardised incidence was 25.5, age-standardised mortality was 21.2 (European standard). Median (95% confidence interval (95% CI)) survival of the patients was 172 (165-178) days. One-year survival rate fluctuated between 27% and 34%. Male sex and older age were associated with higher risk of death (hazard ratio (95% CI) - 1.08 (1.03-1.13) vs females and 1.15 (1.12-1.17) per 10-years increase of age, respectively).The study describes the trends in epidemiology of gastric cancer in Dnipro region, Ukraine, between 2009 and 2019. The need for the national prevention strategy of GC in Ukraine was identified.

In this study the possibility of using potentiometric multisensor system (e-tongue) based on solid-state membrane electrodes for express evaluation of various quality parameters in vegetable oils was investigated. Optimization of oil sample preparation procedures for potentiometric analysis was performed. It was shown that developed multisensor system is capable to distinguish vegetable oil varieties prepared from different raw materials and pure oils from their mixture. Important edible oil quality indicators, such as peroxide value (PV), p-anisidine value (p-AV), and concentration of total tocopherols (TT) can be predicted from potentiometric multisensor system response using multivariate data processing. The parameters under study have the following ranges: PV (0.0–4.0); p-AV (0.4–3.8); TT (37.0–100.7). Application of multivariate regression tools yielded root mean square errors of prediction: 0.5 meq/kg for PV; 0.8 arbitrary units for p-AV; 10 mg/100 g for TT, thus showing a good promise for development of fast and simple method for express quality evaluation.

The state analysis of Industry 4.0 nodes and devices is an integral part of the process in order to ensure the safety of functioning. The imperfection of existing systems for monitoring and analyzing the state of hard-to-reach devices/nodes and dynamically running processes associated with them makes it necessary to analyze not just internal data, but also data sourced from side and external channels. One of the effective ways of resolving this problem is to use digitized data sequences grouped into behavioral patterns. Research objective: Development and improvement of the method of undertaking a state analysis of hard–to–reach Industry 4.0 mechatronic units and devices premised on incoming data. Methods: The use of behavioral patterns comprising of time-synchronized digitized sequences received from side and external channels for the state analysis of nodes and processes. Results: Based on the proposed method for the state analysis of Industry 4.0 nodes premised on behavioral patterns, an experiment has been carried out to obtain quantitative state estimates of the mechatronic element at any required point of time based on the analysis of existing parameter values. The underlying idea behind this experiment was to create a training sample of digitized sequences from several external channels followed by the subsequent analysis based on monitoring data. The state can be determined and monitored by quantitative estimates. The quality of the proposed approach is ascertained by making a direct comparison of results. The overall accuracy of the selected classifier for the full classification was found to be 0.90. Practical significance: The research findings allow for a significant reduction of uncertainty when making a decision on the technical state.

The article considers monitoring devices for software installed on automated system users’ personal computers. The shortcomings of such software solutions are substantiated and the developed approach to the identification of executable files using the computer-aided learning algorithm is presented, i.e. gradient boosting on decision trees, based on XGBoost, LightGBM, CatBoost libraries. Software identification has been performed using XGBoost and LightGBM. The obtained experimental results have been compared with previous studies by other authors. These results indicate that the developed approach reveals violations of the established security policy when processing information in automated systems.

In this paper, problematic issues in ensuring the cybersecurity of autonomous unmanned objects were considered. Moreover, prerequisites that determine the need for external monitoring systems were identified. The type and statistical characteristics used for the analysis and classification of sound signals were also shown. The proposed approach to the analysis of the cybersecurity condition of an autonomous object is based on classification methods and allows the identification of the current status based on digitized acoustic information processing. An experiment aimed at obtaining statistical information on various types of unmanned object maneuvers with various arrangements of an audio recorder was conducted. The data obtained was processed using two-layer feed-forward neural networks with sigmoid hidden neurons. Hence, the problem of identifying the cybersecurity condition of autonomous unmanned objects on the basis of processing acoustic signal information obtained through side channels was solved. Digitized information from an acoustic sensor (microphone) located statically in the experiment area was classified more accurately than from the microphone located directly on the autonomous object. With a minimum time of statistical information accumulation using the proposed approach, it becomes possible to identify differences in maneuvers performed by the unmanned object and, consequently, the cybersecurity condition of the object with a probability close to 0.7. The proposed approach for processing signal information can be used as an additional independent element to determine the cybersecurity condition of autonomous objects of unmanned systems. This approach can be quickly adapted using various mathematical tools and machine learning methods to achieve a given quality probabilistic assessment.

The paper deals with problematic issues of information security in cyber-physical systems. Performance analysis of autonomous objects has been carried out. An information security monitoring system model based on the characteristics resulting from the analysis of electromagnetic radiation from electronic components in standalone devices of cyber-physical systems is presented. A typical scheme for determining the state of a system is shown. Due to the features of equipment sustaining the infrastructure, assessment of an information security state is aimed at analyzing normal system operation rather than searching for signatures and characteristics of anomalies during various types of information attacks. An experiment that provides statistical information on the operation of remote devices of cyber-physical systems has been disclosed, whereby data for decision-making are accumulated by comparing statistical information. The experimental results on information influence on a typical system are presented. The proposed approach for analyzing statistical data of standalone devices based on a naive Bayesian classifier can be used to determine information security states. A special feature of the approach is the ability to rapid adaptation and application of various mathematical tools and machine learning methods to achieve a desired quality of probabilistic evaluation.

This article presents the results of excavations and multidisciplinary investigations of the extraordinary Oldowan site of Muhkai II in the northern Caucasus (Republic of Dagestan, Russia) from 2008 to 2012. Archaeological and palaeontological materials are summarized together with data from palaeomagnetic and palynological analyses, obtained from 34 cultural layers at the site. This gives an opportunity for a new approach to the question of the timing and route of the first human settlement of the middle latitudes of western Eurasian, including south-eastern Europe. Judging by the data obtained, this occurred around 2 million years BP and a route of migration was located along the western shore of the Caspian Sea.

Cathodically initiated Michael addition of thiols to levoglucosenone using small currents produces the previously unknown threo addition product in several instances. The normal erythro isomer, identified as the kinetic product, tends to be formed when large currents are used. The slow, low current electrolyses promote equilibration of the two forms so that erythro can be converted to threo by the retro reaction and readdition. Additions to R-(+)-apoverbenone and R-(-)-carvone are also reported.

Regioselective Michael addition of nitro compounds to levoglucosenone (LG) is effectively catalyzed by cathodic electrolysis under mild conditions.

A general scheme for the synthesis of azolium and azinium dinitromethylides, by nitrating N- acetonyl derivatives of aromatic N -heterocycles with sulfuric acid/nitric acid mixtures, has been developed.

Cathodically initiated Michael addition of thiols to levoglucosenone using small currents produces the previously unknown threo addition product in several instances. The normal erythro isomer, identified as the kinetic product, tends to be formed when large currents are used. The slow, low current electrolyses promote equilibration of the two forms so that erythro can be converted to threo by the retro reaction and readdition. Additions to R-(+)-apoverbenone and R-(-)-carvone are also reported.

A general scheme for the synthesis of azolium and azinium dinitromethylides, by nitrating N- acetonyl derivatives of aromatic N -heterocycles with sulfuric acid/nitric acid mixtures, has been developed.

The nitration of activated carbonyl compounds in a two-phase system gives novel possibilities for the synthesis of functional nitro derivatives.

Formylation of easily accessible heteroarylacetic acids (R-CH2COOH, R = imidazole, pyrazole, tetrazole, pyridine) afforded in high yields the corresponding trimethinium salts R-C(=CH-N(CH3)2)CH=N(CH3)2)n+ nX- which on alkaline hydrolysis were converted into N-diformylmethylazoles R-C(CHO)=CH-OH. Their quaternization gave cycloimonium diformyl methylides.

1-Diformylmethyl-4-nitropyrazole serves to show the potential synthetic utilization of N-diformylmethylazoles as suitable synthons for building heterocyclic systems.

Reactions de diformylmethyl-1 nitro-4 pyrazole avec des diamines ou des urees conduisant a des heterocycles azotes