Resolution Proof Technique in Linear Temporal Logic.

This dissertation presents a resolution proof technique for Propositional Linear Temporal Logic of discrete time with the Until operator. The presented proof technique stems from the resolution method developed by L. Farinas del Cerro and A. Cavalli. However, their method is incomplete, and their completeness proof, as originally reported, is incorrect. Unlike Farinas\u27s method, our proof technique incorporated the Until operator, which is a very powerful and useful in describing complex temporal relationships which are common in many areas of computer science. Our technique is also proved complete. The presented resolution method for linear temporal logic is similar to classical resolutions: the main goal is to show unsatisfiability of a set of temporal clauses by locating, either directly or indirectly, a state which contains unsatisfiability. Subsequent resolvents of a refutation are obtained by resolving out complementary literals referring to the same instant of time. In order to increase the efficiency of the resolution proof technique, we have developed a refinement of the presented basic method. This refinement is similar to the well-known Ordered Linear (OL) strategy for classical resolution. We also present the lifting of the basic resolution method to predicate linear temporal logic. Unlike First Order Logic, clauses of predicate linear temporal logic may contain variables which are quantified existentially, because skolemization is not valid here. We use standard unification with substitution on universally quantified variables. However, if a term substituted in place of a variable contains any flexible symbols, a constant or a function is flexible if it has different translation in different states, then all occurrences of the substituted variable must refer to the same instant of time (state). Otherwise, the unification may lead to incorrect results. Resolution in predicate linear temporal logic, though very useful from a practical standpoint, is incomplete, since no predicate temporal logic with arithmetic model of time is complete

Timestep Stochastic Simulation of Computer Networks using Diffusion Approximation

Performance evaluation of modern computer networks is challenging because of their large sizes, high speeds of communication links, and complex state-dependent control mechanisms. In particular, TCP congestion control reacts in a nonlinear fashion to the state of the network at the time scale of round-trip times, making analysis intractable. Thus packet-level simulation is the only widely used method of performance evaluation. Although it can be accurate, it is computationally expensive and thus can be applied only to small networks and low link speeds. Timestep Stochastic Simulation (TSS) is a novel method for generating sample paths of computer networks, in increments of time steps rather than packet transmissions. TSS has a low computation cost independent of packet rates and provides adequate accuracy for evaluating general state-dependent control mechanisms. TSS generates the evolution of the system state S(t) on a sample path in time steps of size delta. At each step, S(t + delta) is randomly chosen according to S(t) and the probability distribution Pr[S(t+delta)|S(t)], obtained using the diffusion approximation. Because packet transmission and reception events are replaced by time steps, TSS generates sample paths at a fraction of the cost of packet-level simulation. Because TSS generates sample paths, it can accurately model state-dependent control mechanisms, including TCP congestion control, adaptive dynamic routing, and so on. We have a TSS implementation for general computer networks with state-dependent control. We have applied this to numerous networks with TCP and state-dependent UDP flows, and confirmed its accuracy against packet-level simulation

Text Summarization Techniques: A Brief Survey

In recent years, there has been a explosion in the amount of text data from a variety of sources. This volume of text is an invaluable source of information and knowledge which needs to be effectively summarized to be useful. In this review, the main approaches to automatic text summarization are described. We review the different processes for summarization and describe the effectiveness and shortcomings of the different methods.Comment: Some of references format have update

Транскордонна співпраця України та Польщі в енергетичній сфері

The theoretical bases and practical aspects of the countries transfrontal collaboration in modern terms are justified. In order to achieve the purpose and objectives of the research, general scientific and special methods of academic research, in particular, analysis and synthesis, induction and deduction, comparison, abstraction, modern modeling methods are applied. Maintenance and features of the projects realized within the framework of transfrontal collaboration of Ukraine and Poland in the sphere of energy are exposed. We conducted the SWOT- analysis of strengths and weaknesses in a transfrontal collaboration between Ukraine and Poland in energy sphere. Potential possibilities and threats of its development in a strategic prospect are identified. We specified generalized existent normatively-legal bases of transfrontal collaboration and potential of implementation of existent strategies of its efficiency increase. Directions of the institutionally-organizational providing of decision of strategic problems in collaboration in energy sphere between Ukraine and Poland are offered. The transfrontal collaboration of Ukraine and Poland are to come true from inhibition of principle of scientific public policy on principles of increase of Ukrainian economy energy efficiency, determination of objects for reconstruction and new building in energy sphere, application of financial instruments of investments bringing in for energy infrastructure updating, and development of management. It is well-proven that energy strategy of Ukraine must become soil of that on the terms of parity collaboration with the energy circuits of Poland to show out home markets on a new and qualitatively higher level. The suggestions set must promote to the increase of energy strength and independence as Ukraine and Poland and other countries of the European Union. Prospects for the latest scientific research are the study of priorities of transfrontal collaboration between Ukraine and neighbouring countries in the context of finding a balanced model of cooperation considering European integration and globalization trends.Обґрунтовано теоретичні засади транскордонної співпраці країн у сучасних умовах. Основою для подальшого окреслення стратегічних напрямів розвитку співпраці визначено підходи, сформульовані у Європейській рамковій конвенції про транскордонне співробітництво між територіальними громадами. Розкрито зміст та особливості проектів, реалізованих у рамках транскордонної співпраці України і Польщі у сфері енергетики. Проведено SWOT-аналіз сильних та слабких сторін у транскордонному співробітництві між Україною та Польщею в енергетиці. Обґрунтовано потенційні можливості та загрози його розвитку у стратегічній перспективі. Аргументовано, що врахування окреслених на основі проведеного аналізу можливостей України й Польщі на базі використання сильних сторін має бути підґрунтям для налагодження українсько-польського співробітництва в енергетичній сфері у контексті нових його реалій після активізації євроінтеграції. Узагальнено чинні нормативно-правові основи транскордонної співпраці та визначено потенціал реалізації стратегій підвищення її ефективності. Доведено, що важливим завданням для інтенсифікації транскордонної співпраці має бути активна співпраця між органами місцевої влади Польщі та України. Запропоновано напрями інституційно-організаційного забезпечення вирішення назрілих проблем та пріоритети стимулювання співпраці між Україною та Польщею в енергетичній сфері

Multiple Relations Classification using Imbalanced Predictions Adaptation

The relation classification task assigns the proper semantic relation to a pair of subject and object entities; the task plays a crucial role in various text mining applications, such as knowledge graph construction and entities interaction discovery in biomedical text. Current relation classification models employ additional procedures to identify multiple relations in a single sentence. Furthermore, they overlook the imbalanced predictions pattern. The pattern arises from the presence of a few valid relations that need positive labeling in a relatively large predefined relations set. We propose a multiple relations classification model that tackles these issues through a customized output architecture and by exploiting additional input features. Our findings suggest that handling the imbalanced predictions leads to significant improvements, even on a modest training design. The results demonstrate superiority performance on benchmark datasets commonly used in relation classification. To the best of our knowledge, this work is the first that recognizes the imbalanced predictions within the relation classification task.Comment:

Generation and analysis of conditional mouse mutants to investigate the interactions of beta7-Integrin and MAdCAM-1

Die vorliegende Arbeit beschreibt die Herstellung und Analyse von Mausmutanten zur Untersuchung der Interaktionen von beta7-Integrin und MAdCAM-1 bei lymphozytärer Migration und humoraler Immunantwort. Um die Rolle der zytoplasmatischen Domäne des beta7-Integrins zu identifizieren, wurden Mausmutanten mit spezifischen Mutationen erzeugt. Diese beinhalten zwei Deletionen, die den kompletten Verlust der zytoplasmatischen Domäne bzw. den Verlust der distalen Region verursachen, sowie zwei Punktmutationen in Bereichen, die vermutlich essentiell für die Signalweiterleitung sind. Alle vier Mutationen wurden erfolgreich mittels gezieltem gene targeting in murinen embryonalen Stammzellen etabliert. Mit diesen Stammzellen wurde für drei der Mutationen die Besiedelung der Keimbahn erreicht, was letztlich die Generierung homozygoter Mausmutanten und das in vivo Studium der veränderten beta7-Integrine ermöglichte. Mit Hilfe der MAdCAM-1 defizienten Mausmutante wurde gezeigt, dass dieses Adhäsionsmolekül sowohl bei der Migration von Lymphozyten als auch bei der humoralen Immunantwort eine wichtige Rolle spielt. In MAdCAM-1 defizienten Mäusen können die Peyer`schen Platten des Darms nicht effizient mit Lymphozyten besiedelt werden. Wird kein MAdCAM-1 exprimiert kommt es zu einer signifikanten Reduktion der IgA-Plasmazellen in der intestinalen Lamina Propria. In Immunisierungsexperimenten stellte sich heraus, dass der Verlust von MAdCAM-1 mit einer verringerten spezifischen IgA-Immunantwort einhergeht. Diese Beobachtungen deuten auf eine essentielle Rolle der spezifischen MAdCAM-1-beta7-Integrin Interaktion für das homing von IgA-Plasmazellen hin. Weiterhin konnte belegt werden, dass sowohl das homing von naiven als auch immunkompetenten T-Lymphozyten die von MAdCAM-1 vermittelten Wechselwirkungen benötigt. Die Interaktionen von MAdCAM-1 und beta7-Integrin sind daher entscheidend für die Migration von Lymphozyten in die induktiven Kompartimente und die Effektorkompartimente des GALT und somit essentiell für die Aufrechterhaltung der mukosalen Immunität.The present work describes the generation and analysis of mouse mutants to investigate the interactions of beta7-Integrin and MAdCAM-1 during lymphocyte migration and humoral immune response. To identify the role of the cytoplasmic domain of beta7-Integrin, different mouse mutants with specific mutations were generated. The mutations contain two deletions, which cause the loss of the complete cytoplasmic domain and the loss of the distal region respectively, and two point mutations in regions of the domain presumably essential for signal transduction. By gene targeting the mutations were successfully established in murine ES cells, which allowed the generation of homozygous mouse mutants to study the effects of the different mutations. The analysis of the MAdCAM-1 deficient mouse mutant showed that MAdCAM-1 is essential as well for the migration of lymphocytes to the GALT as for the humoral immune response. In MAdCAM-1 deficient mice the Peyer`s patches of the gut are not efficiently populated by lymphocytes. The loss of MAdCAM-1 leads to a significant reduction of IgA plasma cells in the intestinal lamina propria. Moreover it was shown that MAdCAM-1 deficient mice are not able to mount a specific IgA immune response in the gut after oral immunization. Therefore we strongly suggest that the specific interactions of MAdCAM-1 and beta7-Integrin are crucial for the homing of IgA plasma cells to the GALT. Furthermore it could be shown that the migration of naïve and effector T cells is also depending on MAdCAM-1 mediated interactions. Therefore the interactions of MAdCAM-1 and beta7-Integrin are crucial for the migration of lymphocytes to the inductive and effector compartments of the GALT and are consequently essential for the maintenance of mucosal immunity

A Knowledge-Based Topic Modeling Approach for Automatic Topic Labeling

Probabilistic topic models, which aim to discover latent topics in text corpora define each document as a multinomial distributions over topics and each topic as a multinomial distributions over words. Although, humans can infer a proper label for each topic by looking at top representative words of the topic but, it is not applicable for machines. Automatic Topic Labeling techniques try to address the problem. The ultimate goal of topic labeling techniques are to assign interpretable labels for the learned topics. In this paper, we are taking concepts of ontology into consideration instead of words alone to improve the quality of generated labels for each topic. Our work is different in comparison with the previous efforts in this area, where topics are usually represented with a batch of selected words from topics. We have highlighted some aspects of our approach including: 1) we have incorporated ontology concepts with statistical topic modeling in a unified framework, where each topic is a multinomial probability distribution over the concepts and each concept is represented as a distribution over words; and 2) a topic labeling model according to the meaning of the concepts of the ontology included in the learned topics. The best topic labels are selected with respect to the semantic similarity of the concepts and their ontological categorizations. We demonstrate the effectiveness of considering ontological concepts as richer aspects between topics and words by comprehensive experiments on two different data sets. In another word, representing topics via ontological concepts shows an effective way for generating descriptive and representative labels for the discovered topics