В статье определяется роль стратегического ИТ-консалтинга в жизненном цикле консалтинговых услуг. Обсуждаются практические вопросы ее основные направления, такие как стратегический ИТ-аудит, ИТ-стратегии развития, организации ИТ-службы и перехода к аутсорсингу.
This study is dedicated to the introduction of a novel method that automatically extracts potential structural alerts from a data set of molecules. These triggering structures can be further used for knowledge discovery and classification purposes. Computation of the structural alerts results from an implementation of a sophisticated workflow that integrates a graph mining tool guided by growth rate and stability. The growth rate is a well-established measurement of contrast between classes. Moreover, the extracted patterns correspond to formal concepts; the most robust patterns, named the stable emerging patterns (SEPs), can then be identified thanks to their stability, a new notion originating from the domain of formal concept analysis. All of these elements are explained in the paper from the point of view of computation. The method was applied to a molecular data set on mutagenicity. The experimental results demonstrate its efficiency: it automatically outputs a manageable number of structural patterns that are strongly related to mutagenicity. Moreover, a part of the resulting structures corresponds to already known structural alerts. Finally, an in-depth chemical analysis relying on these structures demonstrates how the method can initiate promising processes of chemical knowledge discovery. © 2015 American Chemical Society.
We compare the Egalitarian rule (aka Egalitarian Equivalent) and the Competitive rule (aka Competitive Equilibrium with Equal Incomes) to divide bads (chores). They are both welfarist: the competitive disutility profile(s) are the critical points of their Nash product on the set of efficient feasible profiles. The C rule is Envy Free, Maskin Monotonic, and has better incentives properties than the E rule. But, unlike the E rule, it can be wildly multivalued, admits no selection continuous in the utility and endowment parameters, and is harder to compute. Thus in the division of bads, unlike that of goods, no rule normatively dominates the other.
Process mining – это технология, которая посредством извлечения данных из журнала событий предоставляет различные методы для исследования реального процесса, его улучшения и контроля над ним. В данной статье мы рассматриваем проблему проверки соответствия между высокоуровневой моделью процесса и журналом событий. Проверка соответствия интенсивно изучается в рамках process mining, но в литературе можно найти только методы, позволяющие измерить этот показатель между логом и моделью одного уровня. В статье мы представляем алгоритм проверки соответствия между высокоуровневой моделью процесса (построенной экспертами) и низкоуровневым журналом событий (сгенерированным системой), а также доказываем его применимость.
We present a study on co-authorship network representation based on network embedding together with additional information on topic modeling of research papers and new edge embedding operator. We use the link prediction (LP) model for constructing a recommender system for searching collaborators with similar research interests. Extracting topics for each paper, we construct keywords co-occurrence network and use its embedding for further generalizing author attributes. Standard graph feature engineering and network embedding methods were combined for constructing co-author recommender system formulated as LP problem and prediction of future graph structure. We evaluate our survey on the dataset containing temporal information on National Research University Higher School of Economics over 25 years of research articles indexed in Russian Science Citation Index and Scopus. Our model of network representation shows better performance for stated binary classification tasks on several co-authorship networks.
MiRNAs are essential mediators of many biological processes. The aim of this study was to investigate the dynamics of miRNA-mRNA regulatory networks during exercise and the subsequent recovery period.
Here we monitored the transcriptome changes using microarray analysis of the whole blood of eight highly trained athletes before and after 30 min of moderate exercise followed by 30 min and 60 min of recovery period. We combined expression profiling and bioinformatics and analysed metabolic pathways enriched with differentially expressed mRNAs and mRNAs which are known to be validated targets of differentially expressed miRNAs. Finally we revealed four dynamically regulated networks comprising differentially expressed miRNAs and their known target mRNAs with anti-correlated expression profiles over time. The data suggest that hsa-miR-21-5p regulated TGFBR3, PDGFD and PPM1L mRNAs. Hsa-miR-24-2-5p was likely to be responsible for MYC andKCNJ2 genes and hsa-miR-27a-5p for ST3GAL6. The targets of hsa-miR-181a-5p included ROPN1L and SLC37A3. All these mRNAs are involved in processes highly relevant to exercise response, including immune function, apoptosis, membrane traffic of proteins and transcription regulation.
We have identified metabolic pathways involved in response to exercise and revealed four miRNA-mRNA networks dynamically regulated following exercise. This work is the first study to monitor miRNAs and mRNAs in parallel into the recovery period. The results provide a novel insight into the regulatory role of miRNAs in stress adaptation.
This paper presents an approach to dynamic component composition that facilitates creating new composed components using existing ones at runtime and without any code generation. The dynamic abilities are supported by extended type notion and implementation based on additional superstructure provided with its Java API and corresponding JavaBeans components. The new component composition is performed by building the composed prototype object that can be dynamically transformed into the new instantiable type (component). That approach demonstrates interrelations between prototype-based and class-based component-oriented programming. The component model proposed can be used when implementing user-defined types in declarative languages for event-driven applications programming.