Chuvash State University

Ethoxy derivatives of pyrrolo[3,4-c]pyridine have been synthesized by dehydroxyalkoxylation of the corresponding hydroxy derivatives on heating in boiling ethanol in the presence of sulfuric acid. The synthesized compounds have been studied as reagents for the fluorometric determination of mercury(II) ions. Leading compounds containing a 4-chloro- or 4-bromophenyl substituent showed Hg(II) detection limits of 0.43×10–6 or 0.92×10–6 M, respectively, these values are comparable with those of existing small molecule-based reagents.

The article examines the metrological assurance of wastewater monitoring, specifically, at chemical industry facilities. Automated monitoring, which involves assessing the initial quality of effluents and the quality of their treatment prior to discharge into natural water bodies, helps to reduce water pollution. In order to improve the monitoring efficiency, it is necessary to address a priority innovation issue faced by water-intensive chemical industry facilities, i.e., to ensure reliable comparability of measurement results for various parameters of water composition and properties, as well as subsequent selective reduction in the concentration of particularly hazardous toxicants. It is shown that a need exists to improve the procedure for identifying pollutants (with their subsequent removal) that cause a hazardous increase in the informative indicators of anthropogenic water pollution. In hygiene, hydrochemistry, and ecology, such indicators include chemical and biochemical oxygen demand. The authors conducted a comparative analysis of methods for processing data (the results of measuring wastewater parameters at industrial facilities) since by selecting the most effective treatment method, the identification of particularly hazardous toxicants and a selective reduction in their concentration can be improved. On the example of studying the sewage wastewater of Kemerovo AZOT enterprise, the following processing methods were analyzed: predictive mathematics, conventional regression analysis, and neural network simulation. Neural networks proved to be highly effective, as they helped to identify the largest (maximum) number of causal relationships, as compared to other methods, including nonlinear relationships between pollutants and chemical and biochemical oxygen demand. According to the results of comparing the data processing methods for analysis of the causal relationships between the measured parameters of water composition and properties, it is recommended to use neural networks. The obtained results can be used to provide metrological support for environmental management, monitoring, and emission/discharge control (accounting) systems at nitrogen fertilizer facilities.

Tax administration is a system of state management of the tax process with the purpose of building certain relations between the state, represented by tax authorities, and taxpayers in order to improve the efficiency of the tax system. The subject of tax administration is tax production, the object is the process of managing tax production, the subject is tax administrations. The mains task of tax administration are to regulate economic processes and legal relationships in the field of taxes and fees in order to achieve an optimal ratio of fiscal and distribution functions of taxes at minimal costs, to meet the state’s financial needs with a reasonable burden on the taxpayer, to stimulate honest payment of taxes than tax evasion. This is the relevance of the research topic. The purpose of the research is to study the mechanism and methods of tax administration used by tax authorities in their activities. The objectives of the study are to analyse the effectiveness of tax administration methods, their compliance with current legislation, and to develop proposals for their improvement. The following methods are used: analysis and synthesis, grouping, generalisation, the tabular method, etc. The information base of the study is the tax and budget legislation, official data of the Federal State Statistics Service, reports of the Federal Tax Service of the Russian Federation. In order to ensure the validity of the conclusions and proposals, we provide arbitration practice of dispute resolution. The practical significance of the study is that its results can be used in the practical activities of regulatory authorities as well as in further research on the topic under study.

Training complex, biologically plausible Spiking Neural Networks (SNNs) with local learning rules is a significant challenge for theoretical analysis. Here we address this problem by developing a comprehensive analytical theory for the learning dynamics of CoLaNET, a recently proposed columnar SNN. In particular, we consider a simplified model that captures the core algorithmic logic of CoLaNET’s training process. We derive closed-form expressions that accurately predict the number of emergent microcolumns, the complete temporal evolution of synaptic weights, and the model’s learning curve. Our theoretical predictions show excellent quantitative agreement with numerical simulations of the simplified model and successfully capture the qualitative behavior of the full spiking CoLaNET. Furthermore, our analysis reveals that the spike-based, asynchronous competition in the full model delays neuronal specialization and slows down the training process relative to its simplified counterpart. This work provides a scalable theoretical foundation for understanding and configuring biologically inspired SNNs and highlights a key difference introduced by spike-based dynamics.

Abstract Chronic endometritis (CE) is a localized inflammatory disorder of the endometrium characterized by plasma cell infiltration, most often identified by CD138 immunostaining. Its diagnosis remains problematic due to the absence of standardized thresholds, variability in biopsy timing, and inconsistent histologic interpretation, which results in heterogeneous prevalence reports. CE has been proposed as a potential contributor to recurrent implantation failure (RIF); however, the available evidence remains limited. True RIF, defined as repeated implantation failure despite transfer of euploid embryos, affects only 2–5% of patients. Some recent comparative studies suggest that the prevalence of CE in women with RIF is not higher than in control populations. These findings indicate that the contribution of CE to implantation failure may be less prominent than previously assumed. Interpretation of existing data is further complicated by variability in diagnostic criteria, thresholds for plasma cell detection, biopsy timing, and study design. In this context of diagnostic uncertainty, management remains empirical, with antibiotics frequently prescribed without confirmed causative pathogens. This practice raises concern given the limited and inconsistent evidence of therapeutic benefit, the risk of overdiagnosis and overtreatment, and concerns regarding unnecessary antibiotic exposure and antimicrobial resistance. This narrative review synthesizes current evidence on the diagnosis, clinical relevance, and management of CE in the context of RIF and provides a clinical algorithm to guide selective screening and clinical decision-making. Overall, available data support a cautious, individualized, and selective approach. Further prospective studies are required to establish standardized diagnostic criteria and clarify whether treatment of CE improves reproductive outcomes. Lay summary Chronic endometritis is a persistent inflammation of the inner lining of the uterus that has been suspected as a cause of repeated failure of embryo implantation during fertility treatment. However, diagnosis is challenging because there are no clear medical standards, and results vary between studies. Recent research shows that true repeated implantation failure affects only about 2–5% of patients, and chronic endometritis does not appear to be more common in these cases than in others. Despite this uncertainty, antibiotics are often prescribed without clear evidence of benefit. This may expose patients to unnecessary side effects and contributes to growing antibiotic resistance. This review summarizes current evidence and presents a clinical algorithm to guide careful and selective testing. A more cautious and individualized approach may help avoid unnecessary treatment and support safer, more effective fertility care.