Warsaw University of Technology

About: Warsaw University of Technology is a education organization based out in Warsaw, Poland. It is known for research contribution in the topics: Microstructure & Optical fiber. The organization has 14293 authors who have published 34362 publications receiving 492211 citations. The organization is also known as: Warsaw Polytechnic & Politechnika Warszawska.

Indication of Electron Neutrino Appearance from an Accelerator-produced Off-axis Muon Neutrino Beam

Abstract: The T2K experiment observes indications of nu(mu) -> nu(mu) e appearance in data accumulated with 1.43 x 10(20) protons on target. Six events pass all selection criteria at the far detector. In a three-flavor neutrino oscillation scenario with |Delta m(23)(2)| = 2.4 x 10(-3) eV(2), sin(2)2 theta(23) = 1 and sin(2)2 theta(13) = 0, the expected number of such events is 1.5 +/- 0.3(syst). Under this hypothesis, the probability to observe six or more candidate events is 7 x 10(-3), equivalent to 2.5 sigma significance. At 90% C.L., the data are consistent with 0.03(0.04) < sin(2)2 theta(13) < 0.28(0.34) for delta(CP) = 0 and a normal (inverted) hierarchy.

State of the Art of Finite Control Set Model Predictive Control in Power Electronics

Abstract: This paper addresses to some of the latest contributions on the application of Finite Control Set Model Predictive Control (FCS-MPC) in Power Electronics. In FCS-MPC , the switching states are directly applied to the power converter, without the need of an additional modulation stage. The paper shows how the use of FCS-MPC provides a simple and efficient computational realization for different control objectives in Power Electronics. Some applications of this technology in drives, active filters, power conditioning, distributed generation and renewable energy are covered. Finally, attention is paid to the discussion of new trends in this technology and to the identification of open questions and future research topics.

Three-dimensional Epigenome Statistical Model: Genome-wide Chromatin Looping Prediction.

Abstract: This study aims to understand through statistical learning the basic biophysical mechanisms behind three-dimensional folding of epigenomes. The 3DEpiLoop algorithm predicts three-dimensional chromatin looping interactions within topologically associating domains (TADs) from one-dimensional epigenomics and transcription factor profiles using the statistical learning. The predictions obtained by 3DEpiLoop are highly consistent with the reported experimental interactions. The complex signatures of epigenomic and transcription factors within the physically interacting chromatin regions (anchors) are similar across all genomic scales: genomic domains, chromosomal territories, cell types, and different individuals. We report the most important epigenetic and transcription factor features used for interaction identification either shared, or unique for each of sixteen (16) cell lines. The analysis shows that CTCF interaction anchors are enriched by transcription factors yet deficient in histone modifications, while the opposite is true in the case of RNAP II mediated interactions. The code is available at the repository https://bitbucket.org/4dnucleome/3depiloop .

Credit Risk: Modeling, Valuation and Hedging

Abstract: The main objective of Credit Risk: Modeling, Valuation and Hedging is to present a comprehensive survey of the past developments in the area of credit risk research, as well as to put forth the most recent advancements in this field. An important aspect of this text is that it attempts to bridge the gap between the mathematical theory of credit risk and the financial practice, which serves as the motivation for the mathematical modeling studied in the book. Mathematical developments are presented in a thorough manner and cover the structural (value-of-the-firm) and the reduced (intensity-based) approaches to credit risk modeling, applied both to single and to multiple defaults. In particular, the book offers a detailed study of various arbitrage-free models of defaultable term structures with several rating grades. This volume will serve as a valuable reference for financial analysts and traders involved with credit derivatives. Some aspects of the book may also be useful for market practitioners engaged in managing credit-risk sensitive portfolios. Graduate students and researchers in areas such as finance theory, mathematical finance, financial engineering and probability theory will benefit from the book as well. On the technical side, readers are assumed to be familiar with graduate level probability theory, theory of stochastic processes, and elements of stochastic analysis and PDEs some aquaintance with arbitrage pricing theory is also expected. A systematic exposition of mathematical techniques underlying the intensity-based approach is however provided.