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September 9, 2026
‘Balkan Hospitality Opens Doors: Studying Dialects on the Verge of Extinction
You cannot study spoken dialects from books. Instead, you need to go to a village, seek out its elders, and earn the trust of local residents before you can record hours of spontaneous stories. This is how Natalia Muravleva, Associate Professor at the Faculty of Humanities, conducts her research. Her internship in Serbia continued her long-standing study of dialects spoken by Macedonian settlers. In this interview, she discusses how diaspora cultural centres help researchers reach informants, why native speakers need to be interviewed only in their own language (otherwise, as she puts it, they may 'break'), and how a single field season helped her finalise her monograph. She also shares warm memories of autumn in Belgrade and of colleagues with whom grammar can be discussed in three languages at once.
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Scientists Train Neural Network to Generate Process Plans from 3D Models
Researchers at the HSE FCS AI and Digital Science Institute have developed CAD2TechSpec, a framework that converts 3D models of mechanical parts into machining process plans—step-by-step instructions for machine tools. The solution aims to reduce the time required for the design and preparation of technical process documentation in mechanical engineering, aircraft manufacturing, and other high-tech industries. The study findings have been published in PeerJ Computer Science.
September 7, 2026
Biologists Discover 'Molecular Fingerprint' of Preeclampsia
Researchers at HSE University employed a new method to model hypoxia in placental cells during pregnancies complicated by preeclampsia and identified molecular markers of tissue hypoxia. Since hypoxia is one of the key mechanisms underlying preeclampsia, these findings are important for a more accurate and timely diagnosis of the disease and for the development of effective treatment methods. The paper has been published in Placenta.

 

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?

Прогнозирование банкротства средних и малых российских компаний

.
Тихонова А. С., Demeshev B.
Language: Russian
Keywords: прогнозирование банкротства предприятия

In book

Труды X Международной конференции "Применение многомерного статистического анализа в экономике и оценке качества"
М.: ЦЭМИ РАН, 2014.
Similar publications
Прогнозирование банкротства организаций с государственным участием
Khrustova L., Fedorova E., В кн.: Управленческие науки в современном мире = Management Sciences in the Modern World: Сб. докл. науч.-практ. конф.: Финансовый университет при Правительстве Российской Федерации; научный журнал «Стратегические решения и риск-менеджмент».Т. 1.: СПб.: ООО "Издательский Дом "Реальная экономика", 2018. С. 494–497.
Рассмотрены вопросы прогнозирования банкротства организаций с государственным участием в законодательстве Российской Федерации. В основу исследования легла методика, утвержденная Приказом Росимущества от 30.12.2014 № 530 [3]. Применение технологии CART (Classification and Regression Tree) к финансовым показателям [3], рекомендуемым Приказом, позволило уточнить их нормативные значения с учетом специфики организаций с государственным участием. Эмпирическая проверка полученных результатов на ...
Added: October 2, 2019
Особенности прогнозирования банкротства организаций с государственным участием в законодательстве Российской Федерации
Fedorova E., Khrustova L., Финансы и кредит 2019 Т. 25 № 6 (786) С. 1266–1279
Subject The article discusses legislative principles for predicting the bankruptcy of Stateowned entities in Russia. Objectives The study is aimed to refine the methodology that the Russian regulations prescribe to predict the bankruptcy of State-owned entities in line with their specifics. It specifies the applicable financial indicators and economic guidance for their evaluation. As per ...
Added: August 27, 2019
Отраслевые особенности применения моделей прогнозирования банкротства предприятия
Fedorova E., Khrustova L., Чекризов Д. В., Стратегические решения и риск-менеджмент 2018 № 1 (104) С. 64–71
The aim of the research is to develop the methodology of bankruptcy prediction applying the specified statutory values of the existing models with a glance to company’s industry and developing the author’s prediction model. Initially authors estimated the forecast accuracy of the existing models for the enterprises of 8 industries. Using CART (Classification And Regression ...
Added: October 23, 2018
МОДЕЛИРОВАНИЕ ВЕРОЯТНОСТИ БАНКРОТСВА РОССИЙСКИХ НЕФИНАНСОВЫХ КОМПАНИЙ
Makushina E., Шихлярова И. А., Финансы и кредит 2018 Т. 24 № 1 С. 95–110
The main goal of the article is to create a model for predicting a bankruptcy of Russian non-financial companies one year in advance with a minimum accuracy of 80% based on the most significant financial and non-financial variables. To obtain this goal the following tasks were issued: legal and economic approaches to determine the bankruptcy ...
Added: July 15, 2018
Анализ влияния корпоративного управления на банкротство российских компаний на основе метода Partial Least Squares Path Modeling
Fedorova E., Zelenkov Y., Чекризов Д. В. et al., Корпоративные финансы 2016 Т. 10 № 2 С. 108–123
Цель данной работы: выявление наиболее значимых факторов внешней и внутренней среды (к которой относятся финансовые показатели и качество корпоративного управления) для прогнозирования вероятности банкротства российских предприятий. Параметры (иногда их называют также латентными переменными)"внешняя среда", "корпоративное управление" и "финансовое состояние" невозможно измерить непосредственно, поскольку они недостаточно четко определены. В таком случае обычно используют измеряемые индикаторы, которые ...
Added: October 29, 2017
Подход к прогнозированию финансового состояния предприятия с учетом изменения макроэкономических показателей
Биджоян Д. С., Аудит и финансовый анализ 2016 № 4 С. 195–200
Analysis and forecasting the financial statement of company play a very important role in decision-making process as for investors and management to implement good governance. For 80 years, the study of this problem was proposed huge number of models fundamentally different from each other methodologically. This article analyzes the main approaches to forecasting bankruptcy and ...
Added: December 3, 2016
Современные особенности применения экономических моделей диагностики вероятности наступления банкротства юридических лиц
Жукова Т. М., Kondrateva K., Вестник Пермского университета. Юридические науки 2014 № 1(23) С. 197–205
In article the questions connected with application of economic models and methods for forecasting of bankruptcy of legal entities are analysed. According to the current legislation about bankruptcy the limited amount of criteria is applied to diagnostics of insolvency of legal entities: coefficients of the current liquidity, security with own working capital and restoration (loss) of ...
Added: December 19, 2014
Динамика прогнозной силы моделей банкротства для средних и малых российских компаний оптовой и розничной торговли
Demeshev B., Тихонова А. С., Корпоративные финансы 2014 Т. 31 № 3 С. 4–22
The chief aim of this paper is to analyse dynamics of linear and non-linear methods to predict bankruptcy for Russian private small and medium-sized retail and wholesale trade  companies. We use financial and non-financial data prior and subsequent to the economic crisis of 2008—2009. We use the following methods: logistic regression and random forest. This research ...
Added: November 22, 2014
Прогнозирование банкротства российских компаний: межотраслевое сравнение
Demeshev B., Тихонова А. С., Экономический журнал Высшей школы экономики 2014 Т. 18 № 3 С. 359–386
The primary aim of this research is to compare diverse statistical models to predict critical financial state for Russian private small and medium-sized companies belonging to different sectors of economy. We use the following methods: Linear Discriminant Analysis, Quadratic Discriminant Analysis, Mixture Discriminant Analysis, Logistic Regression, Probit Regression, Tree and Random Forest. Our dataset consists of ...
Added: November 22, 2014
Прогнозирование банкротства российских компаний: межотраслевое сравнение.
Тихонова А. С., Demeshev B., / Высшая школа экономики. Серия WP2 "Количественный анализ в экономике". 2014. № 4.
The primary aim of this research is to compare diverse statistical models to predict critical financial statefor Russian private small and medium-sized companies belonging to different sectors of economy. We use the following methods: Linear Discriminant Analysis, Quadratic Discriminant Analysis, Mixture Discriminant Analysis, Logistic Regression, Probit Regression, Tree and Random Forest.Our dataset consists of approximately ...
Added: September 22, 2014
Моделирование прогнозирования банкротства предприятий обрабатывающего производства
Данилова Ю. А., Аудит и финансовый анализ 2011 Т. 1 С. 107–113
This article provides the results of development of bankruptcy prediction static model and its testing on the sample of more than thousand companies of manufacturing industry. The main scenarios of bankruptcy are identified and it is shown that depending on the bankruptcy scenario possible insolvency can be predicted one or four years before. ...
Added: September 19, 2012
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