Mitigating Epidemics through Mobile Micro-measures

Epidemics of infectious diseases are among the largest threats to the quality of life and the economic and social well-being of developing countries. The arsenal of measures against such epidemics is well-established, but costly and insufficient to mitigate their impact. In this paper, we argue that mobile technology adds a powerful weapon to this arsenal, because (a) mobile devices endow us with the unprecedented ability to measure and model the detailed behavioral patterns of the affected population, and (b) they enable the delivery of personalized behavioral recommendations to individuals in real time. We combine these two ideas and propose several strategies to generate such recommendations from mobility patterns. The goal of each strategy is a large reduction in infections, with a small impact on the normal course of daily life. We evaluate these strategies over the Orange D4D dataset and show the benefit of mobile micro-measures, even if only a fraction of the population participates. These preliminary results demonstrate the potential of mobile technology to complement other measures like vaccination and quarantines against disease epidemics.Comment: Presented at NetMob 2013, Bosto

Alignment and Assembly:Inferring Networks from Noisy Observations

Over recent years, many large network datasets become available, giving rise to novel and valuable applications of data mining and machine learning techniques. These datasets include social networks, the structure of the Internet, and protein-interaction networks, to name just a few. Graph mining exploits information hidden in these data to shed light on such problems as finding relevant pages on the web, or identifying communities of strongly connected individuals. Clearly, to address such problems, we first need the complete and reliable network graph. In many real-world scenarios, the full graph is not available for free. For example, data-collection processes may be noisy and unreliable or node identifiers may be hidden for privacy protection. Therefore, we cannot rely on the node labels to infer the full graph. In this thesis, we address fundamental and practical questions of inferring a true full network from multiple ambiguous observations. We formulate two variations of this problem: network alignment and network assembly. In each variant, we address two types of questions: first, we characterize how graph features impact the fundamental feasibility of reconstruction; second, we seek efficient algorithms that can scale to very large networks. In the first part of this thesis, we consider network alignment. We assume two large, noisy observations of the true network that are not labeled. Network alignment refers to the problem of aligning the vertices of the two networks using only structural cues and it can be viewed as a generalization of the classic graph-isomorphism problem. We make the following contributions. First, we introduce a random bigraph model with parameters p, t and s that generates two correlated graphs. We characterize conditions on p, t and s for the feasibility of alignment of two graphs. Second, we create an algorithm named percolation graph-matching (PGM) that builds an alignment from a small set of pre-matched nodes S. We prove conditions on the parameters p, t , s and r for which PGM succeeds, and we establish a phase transition in |S|. In the second part of this thesis, we consider network assembly. We assume many small, noisy observations of the true network, called patches. The node labels are either absent or not unique. The network assembly problem consists in reconstructing the true graph from these patches. We make the following contributions. First, we introduce a novel random-graph model with parameters p and q that generates a network with high clustering. We characterize conditions on p and q for feasibility of assembly. Second, we propose a heuristic assembly algorithm to reconstruct the true graph from arbitrary patches with label ambiguity

Influence of the Risk-Based Approach on the Development of the Management of Organizations

The current state, processes and development trends of national and world economic systems require the development of fundamentally new theoretical economic models adequate to the market, reflecting real changes in the world in the near future and in the long term. The purpose of this study was to find the right risk management tools. For this, cases were analysed in which various methods of managing the socio-economic sphere were used. Myths and stereotypes about the behaviour of people in this area were identified. The authors emphasized that macro-indicators of the state of economic systems are not canceled and are used in existing calculation models, but their predicted “strength” should be supplemented by a new model analysis based on a risk-based approach, taking into account the distinguished trend of assessing the current economic development

Incremental and unifying modelling formalism for biological interaction networks

International audienc

Improving the Cost-Efficiency of Local Budgets in Today’s Environment

The article is aimed at analyzing the expenses of local budgets, their dynamics and specificity in the consolidated budget and developing recommendations to improve their efficiency in the modern conditions of financial decentralization. The necessity of increase of efficiency of expenses of local budgets is substantiated, an analysis of dynamics of their expenses is carried out and their specific weight in expenses of the Consolidated budget of Ukraine is analyzed according to each kind of budget expenditures depending on functions. The structure of expenditures of local budgets is also analyzed and priority directions of expenditure of the funds are defined, which are education, health care, and social protection of the population. It is specified that expenditure policy should play a key role in the conduct of the financial activities of the State. It is proposed to improve the system of the State financial and public control, to direct budget funds for the financing of actors in the production sector in order to stimulate the receipt of additional own income of local budgets

When Can Two Unlabeled Networks Be Aligned Under Partial Overlap?

Network alignment refers to the problem of matching the vertex sets of two unlabeled graphs, which can be viewed as a generalization of the classic graph isomorphism problem. Network alignment has applications in several fields, including social network analysis, privacy, pattern recognition, computer vision, and computational biology. A number of heuristic algorithms have been proposed in these fields. Recent progress in the analysis of network alignment over stochastic models sheds light on the interplay between network parameters and matchability. In this paper, we consider the alignment problem when the two networks overlap only partially, i.e., there exist vertices in one network that have no counterpart in the other. We define a random bigraph model that generates two correlated graphs $G_{1,2}$; it is parameterized by the expected node overlap $t^2$ and by the expected edge overlap $s^2$. We define a cost function for structural mismatch under a particular alignment, and we identify a threshold for perfect matchability: if the average node degrees of $G_{1,2}$ grow as $\omega\left( (s^{-2}t^{-1} \log(n) \right)$, then minimization of the proposed cost function results in an alignment which (i) is over exactly the set of shared nodes between $G_1$ and $G_2$, and (ii) agrees with the true matching between these shared nodes. Our result shows that network alignment is fundamentally robust to partial edge and node overlaps

ИСПОЛЬЗОВАНИЕ ГЕПАТОПРОТЕКТОРОВ У БОЛЬНЫХ РАКОМ ЯИЧНИКОВ

Objective: to evaluate the efficiency of pharmacological correction of endogenous intoxication in patients with Stages III—IV ovarian cancer (OC) in the perioperative period. Subjects and methods. Thirty-to-70-year old seventy patients with Stages III-IV OC who had been surgically treated under general anesthesia were examined. The bio chemical parameters of intoxication, such as middleweight molecules, the total, effective concentration and binding capacity of albumin, integral hematological indices of intoxication, and C-reactive protein, were studied in the perioperative period. Results. Analysis of the performed tests showed that the premorbid background in all the examinees was characterized by varying degrees of endogenous intoxication (EI), increased leukocytic index of intoxication, hematological index of intoxication, and modified hematological index of intoxication, an imbalance between the accumulation and binding of overproduced toxic ligands, the intensified production of acutephase inflammatory proteins by the activation of a systemic inflammatory response, and decreased systemic responsiveness. These changes occur with suppressed systemic responsiveness, inadequate intoxication compensation by physiological detoxification systems and hemostatic instability. Conclusion. The use of heptral and Remaxol as part of the metabolic pharmacological correction infusion program nonequivalently caused reductions in the activity of an inflammatory response and the efficiency of EI correction in patients with OC in the perioperative period. The administration of Remaxol for systemic hyporesponsiveness and pronounced intoxication in OC patients promoted the optimization of systemic responsiveness, by producing a reduced toxic effect of tumorassociated EI. Цель — оценить эффективность фармакологической коррекции эндогенной интоксикации у больных раком яичников III—IV стадии в периоперационном периоде. Материал и методы. Обследованы 70 больных раком яичников III—IV стадии, в возрасте от 30 до 70 лет, перенесших хирургический этап лечения в условиях общей анестезии. В периоперационном периоде изучены биохимические показатели интоксикации — молекулы средней массы, общая, эффективная концентрация и связывающая способность альбумина, гематологические интегральные индексы интоксикации, С-реактивный белок. Результаты. Анализ проведенных исследований показал, что у всех исследуемых больных преморбидный фон характеризовался разной степени выраженности эндогенной интоксикацией (ЭИ), ростом лейкоцитарного индекса интоксикации, гематологического показателя интоксикации, модифицированного гематологического показателя интоксикации, нарушением баланса накопления и связывания избыточно продуцируемых токсических лигандов, интенсификацией продукции белков острой фазы воспаления активизацией системного воспалительного ответа, снижением общей реактивности организма. Эти изменения происходят на фоне угнетения общей реактивности организма, неадекватной компенсации интоксикации физиологическими системами детоксикации и нестабильностью гомеостаза. Заключение. Использование в составе инфузионной программы метаболической фармакологической коррекции гептрала и Ремаксола неравнозначно способствовало уменьшению активности воспалительной реакции и эффективности коррекции ЭИ у больных РЯ в периоперационном периоде. Использование Ремаксола в условиях снижения общей реактивности организма и выраженной интоксикации у больных раком яичников способствует оптимизации общей реактивности организма, обеспечивая снижение токсического воздействия опухолевой ЭИ.