Ways for reducing mortality from cardiovascular diseases: A review

Ways for reducing mortality from cardiovascular diseases The article analyzes the possible ways to further reduce cardiovascular disease mortality in the Russian Federation by eliminating shortcomings and pitfalls, introducing known but not used opportunities, and new organizational and medical technologies based on the accumulated experience of "best practice"

Проектирование и разработка имитационной модели мультиклиентского кластера баз данных

One of the main trends of recent years in software design is a shift to a Software as a Service (SaaS) paradigm which brings a number of advantages for both software developers and end users. However, along with these benefits this transition brings new architectural challenges. One of such challenges is the implementation of a data storage that would meet the needs of a service-provider, at the same time providing a fairly simple application programming interface for software developers. In order to develop effective solutions in this area, the architectural features of cloud-based applications should be taken into account. Among others, such key features are the need for scalability and quick adaptation to changing conditions. This paper provides a brief analysis of the problems in the field of cloud data storage systems based on the relational model and it proposes the concept of database cluster designed for applications with a multi-tenant architecture. Besides, the article describes a simulation model of such a cluster, as well as the main stages of its development and the main principles forming its foundation.Одной из главных тенденций последних лет в проектировании программного обеспечения стал переход к парадигме Software as a Service (SaaS), которая несет ряд неоспоримых преимуществ как для компаний-разработчиков ПО, так и для конечных пользователей. Однако вместе с этими преимуществами данный переход несет и новые архитектурные вызовы, одним из которых является организация хранилища данных, которое могло бы удовлетворить нужды компании-провайдера услуг, обеспечив достаточно простой прикладной интерфейс для разработчиков. Для разработки эффективного решения в данной области следует принимать во внимание особенности архитектуры облачных приложений, ключевыми из которых являются потребность в простом масштабировании и быстрой адаптации к меняющимся условиям. В данной работе проводится краткий анализ существующих проблем в области организации облачных систем хранения данных, основанных на реляционной модели, а также предлагается концепция кластера РСУБД, предназначенного для обслуживания приложений с мультиклиентской архитектурой. Кроме того, в статье дается описание имитационной модели подобного кластера, а также основных этапов ее разработки и принципов, заложенных в ее основу

Применение стохастических метаэвристик в задаче управления данными в мультиклиентском кластере баз данных

A multi-tenant database cluster is a concept of a data-storage subsystem for cloud applications with the multi-tenant architecture. The cluster is a set of relational database servers with the single entry point, combined into one unit with a cluster controller. This system is aimed to be used by applications developed according to Software as a Service (SaaS) paradigm and allows to place tenants at database servers so that providing their isolation, data backup and the most effective usage of available computational power. One of the most important problems about such a system is an effective distribution of data into servers, which affects the degree of individual cluster nodes load and faulttolerance. This paper considers the data-management approach, based on the usage of a load-balancing quality measure function. This function is used during initial placement of new tenants and also during placement optimization steps. Standard schemes of metaheuristic optimization such as simulated annealing and tabu search are used to find a better tenant placement.Мультиклиентский кластер баз данных – это концепция хранилища данных для облачных приложений с мультиклиентской архитектурой. Кластер представляет собой набор серверов реляционных баз данных с единой точкой входа, объединенных в одно целое и работающих под управлением контроллера кластера. Данная система нацелена на использование приложениями, разрабатываемыми в соответствии с парадигмой Software as a Service (SaaS), и позволяет разместить на предоставленных серверах данные большого количества клиентов таким образом, чтобы обеспечить их изоляцию, резервирование и наиболее эффективное использование предоставленных вычислительных мощностей. Одной из наиболее важных задач при разработке системы подобного рода является эффективное распределение данных по серверам, которое определяет степень загруженности отдельных узлов, а также устойчивость системы к сбоям. В работе рассматривается подход к управлению данными, основанный на применении функции оценки эффективности балансировки нагрузки. Данная функция применяется как при первичном размещении клиентов, так и для оптимизации уже имеющегося распределения клиентов. Оптимизация размещения ведется по стандартным схемам стохастических метаэвристик: имитации отжига (simulated annealing) и поиска с запретами (tabu search)

Possibilities of dispensary observation in reducing mortality from coronary heart disease

Dispensary observation of patients with coronary artery disease can significantly reduce the likelihood of cardiovascular complications onset. Active outpatient monitoring allows to correct the main risk factors for cardiovascular complications, to estimate the risk of unfavorable cardiovascular events onset and to identificate patients who will get benefit of coronary revascularization. The introduction of a comprehensive assessment of cardiovascular risk and the development of remote monitoring technologies will improve the long-term results of outpatient follow-up of patients with coronary artery disease at high cardiovascular risk

Enriching a Situation Awareness Framework for IoT with Knowledge Base and Reasoning Components

Theimportanceofsystem-levelcontext-andsituationaware- ness increases with the growth of the Internet of Things (IoT). This paper proposes an integrated approach to situation awareness by providing a semantically rich situation model together with reliable situation infer- ence based on Context Spaces Theory (CST) and Situation Theory (ST). The paper discusses benefits of integrating the proposed situation aware- ness framework with knowledge base and efficient reasoning techniques taking into account uncertainty and incomplete knowledge about situa- tions. The paper discusses advantages and impact of proposed context adaptation in dynamic IoT environments. Practical issues of two-way mapping between IoT messaging standards and CST are also discussed

Prospects for development of initiative budgeting in mobilization economy

In modern Russia, the initiative budgeting mechanism has been developing systematically since 2015. The practice has been launched in 51 out of 85 constituent entities of the Russian Federation. This phenomenon is an urgent topic for research, in connection with its priority for the state as one of the important directions for the openness of the budget system development and degree of citizens’ satisfaction with the results of the budget policy improvement. The purpose of this study is to analyze the possibilities of the initiative budgeting practice development in the mobilization economy, which, apparently, for a certain time will become the main model of economic development in Russia. Such general scientific methods of research as comparison, analysis, statistics, and induction were used in the article. The study concludes that the initiative budgeting should be developed in the current state of the Russian economy as the social and managerial positive effects exceed the possible costs of the suspension of the practice

SberQuAD – Russian Reading Comprehension Dataset: Description and Analysis

The paper presents SberQuAD – a large Russian reading comprehension (RC) dataset created similarly to English SQuAD. SberQuAD contains about 50K question-paragraph-answer triples and is seven times larger compared to the next competitor. We provide its description, thorough analysis, and baseline experimental results. We scrutinized various aspects of the dataset that can have impact on the task performance: question/paragraph similarity, misspellings in questions, answer structure, and question types. We applied five popular RC models to SberQuAD and analyzed their performance. We believe our work makes an important contribution to research in multilingual question answering. © 2020, Springer Nature Switzerland AG.We thank Peter Romov, Vladimir Suvorov, and Ekaterina Arte-mova (Chernyak) for providing us with details about SberQuAD preparation. We also thank Natasha Murashkina for initial data processing. PB acknowledges support by Ural Mathematical Center under agreement No. 075-02-2020-1537/1 with the Ministry of Science and Higher Education of the Russian Federation

Reasoning over Knowledge-based Generation of Situations in Context Spaces to Reduce Food Waste

Abstract. Situation awareness is a key feature of pervasive computing and requires external knowledge to interpret data. Ontology-based reasoning approaches allow for the reuse of predefined knowledge, but do not provide the best reasoning capabilities. To overcome this problem, a hybrid model for situation awareness is developed and presented in this paper, which integrates the Situation Theory Ontology into Context Space Theory for inference. Furthermore, in an effort to rely as much as possible on open IoT messaging standards, a domain-independent framework using the O-MI/O-DF standards for sensor data acquisition is developed. This framework is applied to a smart neighborhood use case to reduce food waste at the consumption stage