Analysis of the Economic Security of the Power Grid Complex in Russia Based on an Assessment of the Likelihood of Bankruptcy of Enterprises

Natural monopolies are one of the most profitable sectors of the economy. However, due to the lack of competition, the government has to regulate prices through rigid tariffs, thereby limiting the amount of revenue. This trend plays a huge role for the end consumer, as prices are fixed by the public sector. This negatively affects the economic security of the monopolist enterprise. Improper management of an enterprise in conditions of government regulation, limited investment resources, high consumer requirements for the quality of electricity can lead to the bankruptcy of the power grid company.To identify the risk of bankruptcy in the article, calculations were performed using multiple discriminant analysis models (MDA models: Altman's two-factor model and Fedotova's two-factor model) and logistic models (Logit models: Gruzchinsky's model (2003) and Lin-Piesse's model (2004)) of the annual financial reports of enterprises of the electric grid complex of Russia (subsidiaries of PJSC Rosseti, such as: OJSC IDGC of Urals, PJSC IDGC of Center and Volga Region, PJSC Rosseti Volga, PJSC Rosseti Kuban, PJSC TRK) for the last five years (2016-2020, this period characterizes the financial situation of enterprises before and during the Covid-19 pandemic).

Age and sex estimation using fractal analysis in Brazilian adults: a discriminant analysis

This study assessed the accuracy of fractal analysis (FA) to estimate chronological age and sex in Brazilian adults for forensic investigations. The gender-balanced sample comprised lateral cephalometric radiographs of 120 individuals, stratified according to age (20-29, 30-39, 40-49, 50-59 years) and sex (female and male). A trained calibrated examiner measured the fractal dimension (FD) of the mandibular ramus and mandibular angle. Linear regression and multiple logistic discriminant analysis were carried out to explore the accuracy of FA. For all analyses, p-values < .05 indicated statistical significance. Overall, mean FD values were 1.49±0.10 for the mandibular ramus and 1.48±0.09 for mandibular angle. Results were more accurate in males than females for discriminating age and sex. The multiple discriminant analysis indicated that FA distinguished sex in 61.7% males and 58.3% females. In addition, the mean difference between actual and predicted value was 9.5 years and 10.1 years for men and women, respectively. Fractal analysis accurately identified sex- and age-related differences in the trabecular pattern of the mandible of Brazilian adults, confirming its utility for forensic investigations. Further studies investigating other populations are needed to assess the accuracy of FA for Forensic Dentistry.

Investigating the Persuasive Writing Performance of Moroccan Advanced EFL Students: Is it a problem of “Language” or ‘Reasoning” Acquisition Device?

This study investigates the extent to which the results of rhetorical comparisons of persuasive essays by US English native speakers and others by Moroccan advanced EFL students will provide empirical evidence for Kaplan‘s (1966) contrastive rhetoric hypothesis. This is especially regarding the fact that EFL students-writing problems are a byproduct of the negative transfer of rhetorical strategies from their first language (L1). This hypothesis is tested by comparing 20 EFL and Arabic L1 persuasive essays by the same EFL students to essays in English as L1 by native speakers to identify the extent to which the language of composing and one’s cultural background affects the writing quality of their essays. The study hypothesizes that if Kaplan’s contrastive rhetoric claims were accurate, then Moroccan advanced EFL writers would produce essays that tend to be rhetorically less accurate when judged by standard English rhetorical criteria. Moreno’s (2005) approach to match comparable corpora of persuasive essays from two different cultural and linguistic backgrounds was adopted. As for the study participants, 40 advanced student-writers from two discrepant language and cultural backgrounds were recruited to take part in the study. While the results of a stepwise multiple regression analysis provides further evidence corroborating the validity of the rhetorical measures used in the study, group mean scores comparisons and a Multiple Discriminant analysis of the data indicates that those writers from various cultural backgrounds seem to face far more similar than different rhetorical problems and their writing inadequacies are equally distributed regardless of which language the study participants used to write their essays.

Dynamic financial distress prediction based on class-imbalanced data batches

This study proposes two approaches for dynamic financial distress prediction (FDP) based on class-imbalanced data batches by considering both concept drift and class imbalance. One is based on sliding time window and synthetic minority over-sampling technique (SMOTE) and the other is based on sliding time window and majority class partition. Support vector machine, multiple discriminant analysis (MDA) and logistic regression are used as base classifiers in the experiments on a real-world dataset. The results indicate that the two approaches perform better than the pure dynamic FDP (DFDP) models without class imbalance processing and the static FDP models either with or without class imbalance processing.

The Use of Discriminant Analysis to Assess the Risk of Bankruptcy of Enterprises in Crisis Conditions Using the Example of the Tourism Sector in Poland

The aim of this article is to use multiple discriminant analysis (MDA) and logit models to assess the risk of bankruptcy of companies in the Polish tourism sector in the crisis conditions caused by the COVID-19 pandemic. A review of the literature is used to select models appropriate to analyze the risk of bankruptcy of tourism enterprises listed on the Warsaw Stock Exchange (WSE). The data are from half-year financial statements (the first half of 2019 and 2020, respectively). The obtained results are compared with the current values of the Altman EM-score model and selected financial ratios. An analysis allowed the estimation of the risk of bankruptcy of enterprises from the tourism sector in Poland as well as the assessment of the prognostic value of these models in the tourism sector and the risk of a collapse of this market in Poland. The article fills the research gap created by the negligible use of solvency analysis of the tourism sector and constitutes the basis for estimating the risk of collapse of the tourism sector in a crisis situation.

What Characteristics Do the Firms Have That Go Beyond Compliance with Regulation in Environmental Protection? A Multiple Discriminant Analysis

This paper is focused on analyzing the characteristics of firms that have environmental performance beyond the requirements of regulation in environmental protection. To identify such characteristics, we propose a value and context model building on environmental paradigms as conceptualized by Dryzek’s environmental discourse theory. Using multiple discriminant analysis (MDA) to analyze data collected from a multi-respondent survey of Argentinean polluting firms, we identify distinctive characteristics of firms going beyond regulation and firms that do not comply with regulation. In particular, comparing with other five environmental discourses, endorsement of green growth is evaluated in its connection with compliance patterns. We find that supporting green growth discourse (also known as ecological modernization) is one of the characteristics of those firms that go beyond compliance in their environmental performance.

Improved Precipitation Typing using POSS Spectral Modal Analysis

The Precipitation Occurrence Sensor System (POSS) is a small X-band Doppler radar that measures the Doppler velocity spectra from precipitation falling in a small volume near the sensor. The sensor records a 2-D frequency of occurrence matrix of the velocity and power at the mode of each spectrum measured during one minute. The centroid of the distribution of these modes, along with other spectral parameters, defines a data vector input to a Multiple Discriminant Analysis (MDA) for classification of the precipitation type. This requires the a priori determination of a training set for different types, particle size distributions (PSDs), and wind speed conditions. A software model combines POSS system parameters, particle scattering cross section, and terminal velocity models, to simulate the real time Doppler signal measured by the system for different PSDs and wind speeds. This is processed in the same manner as the system hardware to produce bootstrap samples of the modal centroid distributions for the MDA training set. MDA results are compared to images from the Multi-Angle-Snowflake-Camera (MASC) at the MASCRAD site near Easton, Colorado, and to the CSU-CHILL X-Band observations from Greeley, Colorado. In the four case studies presented, POSS successfully identified precipitation transitions through a range of types (rain, graupel, rimed dendrites, aggregates, unrimed dendrites). Also two separate events of hail were reported and confirmed by the images.