Warsaw University of Technology

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The Compact Muon Solenoid (CMS) detector is described. The detector operates at the Large Hadron Collider (LHC) at CERN. It was conceived to study proton-proton (and lead-lead) collisions at a centre-of-mass energy of 14 TeV (5.5 TeV nucleon-nucleon) and at luminosities up to 1034 cm−2 s−1 (1027 cm−2 s−1). At the core of the CMS detector sits a high-magnetic-field and large-bore superconducting solenoid surrounding an all-silicon pixel and strip tracker, a lead-tungstate scintillating-crystals electromagnetic calorimeter, and a brass-scintillator sampling hadron calorimeter. The iron yoke of the flux-return is instrumented with four stations of muon detectors covering most of the 4π solid angle. Forward sampling calorimeters extend the pseudorapidity coverage to high values (|η| ≤ 5) assuring very good hermeticity. The overall dimensions of the CMS detector are a length of 21.6 m, a diameter of 14.6 m and a total weight of 12500 t.

Multilevel converters have been under research and development for more than three decades and have found successful industrial application. However, this is still a technology under development, and many new contributions and new commercial topologies have been reported in the last few years. The aim of this paper is to group and review these recent contributions, in order to establish the current state of the art and trends of the technology, to provide readers with a comprehensive and insightful review of where multilevel converter technology stands and is heading. This paper first presents a brief overview of well-established multilevel converters strongly oriented to their current state in industrial applications to then center the discussion on the new converters that have made their way into the industry. In addition, new promising topologies are discussed. Recent advances made in modulation and control of multilevel converters are also addressed. A great part of this paper is devoted to show nontraditional applications powered by multilevel converters and how multilevel converters are becoming an enabling technology in many industrial sectors. Finally, some future trends and challenges in the further development of this technology are discussed to motivate future contributions that address open problems and explore new possibilities.

Rough set theory, introduced by Zdzislaw Pawlak in the early 1980s [11, 12], is a new mathematical tool to deal with vagueness and uncertainty. This approach seems to be of fundamental importance to artificial intelligence (AI) and cognitive sciences, especially in the areas of machine learning, knowledge acquisition, decision analysis, knowledge discovery from databases, expert systems, decision support systems, inductive reasoning, and pattern recognition.

Cascaded multilevel inverters synthesize a medium-voltage output based on a series connection of power cells which use standard low-voltage component configurations. This characteristic allows one to achieve high-quality output voltages and input currents and also outstanding availability due to their intrinsic component redundancy. Due to these features, the cascaded multilevel inverter has been recognized as an important alternative in the medium-voltage inverter market. This paper presents a survey of different topologies, control strategies and modulation techniques used by these inverters. Regenerative and advanced topologies are also discussed. Applications where the mentioned features play a key role are shown. Finally, future developments are addressed.

The aim of this paper is to present a review of current control techniques for three-phase voltage-source pulsewidth modulated converters. Various techniques, different in concept, have been described in two main groups: linear and nonlinear. The first includes proportional integral (stationary and synchronous) and state feedback controllers, and predictive techniques with constant switching frequency. The second comprises bang-bang (hysteresis, delta modulation) controllers and predictive controllers with on-line optimization. New trends in current control-neural networks and fuzzy-logic-based controllers-are discussed, as well. Selected oscillograms accompany the presentation in order to illustrate properties of the described controller groups.

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.

Predictive control is a very wide class of controllers that have found rather recent application in the control of power converters. Research on this topic has been increased in the last years due to the possibilities of today's microprocessors used for the control. This paper presents the application of different predictive control methods to power electronics and drives. A simple classification of the most important types of predictive control is introduced, and each one of them is explained including some application examples. Predictive control presents several advantages that make it suitable for the control of power converters and drives. The different control schemes and applications presented in this paper illustrate the effectiveness and flexibility of predictive control.

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 .

ALICE (A Large Ion Collider Experiment) is a general-purpose, heavy-ion detector at the CERN LHC which focuses on QCD, the strong-interaction sector of the Standard Model. It is designed to address the physics of strongly interacting matter and the quark-gluon plasma at extreme values of energy density and temperature in nucleus-nucleus collisions. Besides running with Pb ions, the physics programme includes collisions with lighter ions, lower energy running and dedicated proton-nucleus runs. ALICE will also take data with proton beams at the top LHC energy to collect reference data for the heavy-ion programme and to address several QCD topics for which ALICE is complementary to the other LHC detectors. The ALICE detector has been built by a collaboration including currently over 1000 physicists and engineers from 105 Institutes in 30 countries, Its overall dimensions are 16 x 16 x 26 m(3) with a total weight of approximately 10 000 t. The experiment consists of 18 different detector systems each with its own specific technology choice and design constraints, driven both by the physics requirements and the experimental conditions expected at LHC. The most stringent design constraint is to cope with the extreme particle multiplicity anticipated in central Pb-Pb collisions. The different subsystems were optimized to provide high-momentum resolution as well as excellent Particle Identification (PID) over a broad range in momentum, up to the highest multiplicities predicted for LHC. This will allow for comprehensive studies of hadrons, electrons, muons, and photons produced in the collision of heavy nuclei. Most detector systems are scheduled to be installed and ready for data taking by mid-2008 when the LHC is scheduled to start operation, with the exception of parts of the Photon Spectrometer (PHOS), Transition Radiation Detector (TRD) and Electro Magnetic Calorimeter (EMCal). These detectors will be completed for the high-luminosity ion run expected in 2010. This paper describes in detail the detector components as installed for the first data taking in the summer of 2008.

The T2K experiment observes indications of ν(μ) → ν(e) appearance in data accumulated with 1.43×10(20) protons on target. Six events pass all selection criteria at the far detector. In a three-flavor neutrino oscillation scenario with |Δm(23)(2)| = 2.4×10(-3) eV(2), sin(2)2θ(23) = 1 and sin(2)2θ(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 7×10(-3), equivalent to 2.5σ significance. At 90% C.L., the data are consistent with 0.03(0.04) < sin(2)2θ(13) < 0.28(0.34) for δ(CP) = 0 and a normal (inverted) hierarchy.

One of the obstacles in research activities concentrating on environmental sound classification is the scarcity of suitable and publicly available datasets. This paper tries to address that issue by presenting a new annotated collection of 2000 short clips comprising 50 classes of various common sound events, and an abundant unified compilation of 250000 unlabeled auditory excerpts extracted from recordings available through the Freesound project. The paper also provides an evaluation of human accuracy in classifying environmental sounds and compares it to the performance of selected baseline classifiers using features derived from mel-frequency cepstral coefficients and zero-crossing rate.

This paper presents a review of recently used direct torque and flux control (DTC) techniques for voltage inverter-fed induction and permanent-magnet synchronous motors. A variety of techniques, different in concept, are described as follows: switching-table-based hysteresis DTC, direct self control, constant-switching-frequency DTC with space-vector modulation (DTC-SVM). Also, trends in the DTC-SVM techniques based on neuro-fuzzy logic controllers are presented. Some oscillograms that illustrate properties of the presented techniques are shown.

The existing shortage of therapists and caregivers assisting physically disabled individuals at home is expected to increase and become serious problem in the near future. The patient population needing physical rehabilitation of the upper extremity is also constantly increasing. Robotic devices have the potential to address this problem as noted by the results of recent research studies. However, the availability of these devices in clinical settings is limited, leaving plenty of room for improvement. The purpose of this paper is to document a review of robotic devices for upper limb rehabilitation including those in developing phase in order to provide a comprehensive reference about existing solutions and facilitate the development of new and improved devices. In particular the following issues are discussed: application field, target group, type of assistance, mechanical design, control strategy and clinical evaluation. This paper also includes a comprehensive, tabulated comparison of technical solutions implemented in various systems.

AAindex is a database of numerical indices representing various physicochemical and biochemical properties of amino acids and pairs of amino acids. We have added a collection of protein contact potentials to the AAindex as a new section. Accordingly AAindex consists of three sections now: AAindex1 for the amino acid index of 20 numerical values, AAindex2 for the amino acid substitution matrix and AAindex3 for the statistical protein contact potentials. All data are derived from published literature. The database can be accessed through the DBGET/LinkDB system at GenomeNet (http://www.genome.jp/dbget-bin/www_bfind?aaindex) or downloaded by anonymous FTP (ftp://ftp.genome.jp/pub/db/community/aaindex/).

In this paper linear systems with delays in state and/or control variables are considered. The objective is to design a feedback law which yields a finite spectrum of the closed-loop system, located at an arbitrarily preassigned set of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</tex> points in the complex plane. It is shown that in case of systems with delays in control only the problem is solvable if and only if some function space controllability criterion is met. The solution is then easily obtainable by standard spectrum assignment methods, while the resulting feedback law involves integrals over the past control. In case of delays in state variables it is shown that a technique based on the finite Laplace transform, related to a recent work on function space controllability, leads to a constructive design procedure. The resulting feedback consists of proportional and (finite interval) integral terms over present and past values of state variables. Some indications on how to combine these results in case of systems including both state and control delays are given. Sensitivity of the design to parameter variations is briefly analyzed.

Metal-organic frameworks (MOFs) have received attention for a myriad of potential applications including catalysis, gas storage, and gas separation. Coordinatively unsaturated metal ions often enable key functional behavior of these materials. Most commonly, MOFs have been metalated from the condensed phase (i.e., from solution). Here we introduce a new synthetic strategy capable of metallating MOFs from the gas phase: atomic layer deposition (ALD). Key to enabling metalation by ALD In MOFs (AIM) was the synthesis of NU-1000, a new, thermally stable, Zr-based MOF with spatially oriented -OH groups and large 1D mesopores and apertures.

Identified charged-particle spectra of ${\ensuremath{\pi}}^{\ifmmode\pm\else\textpm\fi{}}$, ${K}^{\ifmmode\pm\else\textpm\fi{}}$, $p$, and $\overline{p}$ at midrapidity ($|y|&lt;0.1$) measured by the $\mathit{dE}/\mathit{dx}$ method in the STAR (solenoidal tracker at the BNL Relativistic Heavy Ion Collider) time projection chamber are reported for $\mathit{pp}$ and $d+\mathrm{Au}$ collisions at $\sqrt{{s}_{\mathit{NN}}}=200$ GeV and for $\mathrm{Au}+\mathrm{Au}$ collisions at 62.4, 130, and 200 GeV. Average transverse momenta, total particle production, particle yield ratios, strangeness, and baryon production rates are investigated as a function of the collision system and centrality. The transverse momentum spectra are found to be flatter for heavy particles than for light particles in all collision systems; the effect is more prominent for more central collisions. The extracted average transverse momentum of each particle species follows a trend determined by the total charged-particle multiplicity density. The Bjorken energy density estimate is at least several GeV/${\mathrm{fm}}^{3}$ for a formation time less than 1 fm/$c$. A significantly larger net-baryon density and a stronger increase of the net-baryon density with centrality are found in $\mathrm{Au}+\mathrm{Au}$ collisions at 62.4 GeV than at the two higher energies. Antibaryon production relative to total particle multiplicity is found to be constant over centrality, but increases with the collision energy. Strangeness production relative to total particle multiplicity is similar at the three measured RHIC energies. Relative strangeness production increases quickly with centrality in peripheral $\mathrm{Au}+\mathrm{Au}$ collisions, to a value about 50% above the $\mathit{pp}$ value, and remains rather constant in more central collisions. Bulk freeze-out properties are extracted from thermal equilibrium model and hydrodynamics-motivated blast-wave model fits to the data. Resonance decays are found to have little effect on the extracted kinetic freeze-out parameters because of the transverse momentum range of our measurements. The extracted chemical freeze-out temperature is constant, independent of collision system or centrality; its value is close to the predicted phase-transition temperature, suggesting that chemical freeze-out happens in the vicinity of hadronization and the chemical freeze-out temperature is universal despite the vastly different initial conditions in the collision systems. The extracted kinetic freeze-out temperature, while similar to the chemical freeze-out temperature in $\mathit{pp}$, $d+\mathrm{Au}$, and peripheral $\mathrm{Au}+\mathrm{Au}$ collisions, drops significantly with centrality in $\mathrm{Au}+\mathrm{Au}$ collisions, whereas the extracted transverse radial flow velocity increases rapidly with centrality. There appears to be a prolonged period of particle elastic scatterings from chemical to kinetic freeze-out in central $\mathrm{Au}+\mathrm{Au}$ collisions. The bulk properties extracted at chemical and kinetic freeze-out are observed to evolve smoothly over the measured energy range, collision systems, and collision centralities.

Abstract This article describes the Survivable Network Design Library (SNDlib), a data library for fixed telecommunication network design available at http://sndlib.zib.de . In the current version 1.0, the library contains data related to 22 networks which, combined with a set of selected planning parameters, leads to 830 network design problem instances. In this article, we discuss the data concepts of SNDlib and describe a mathematical model for each design problem considered in the library. We also provide information on characteristic features and the origin of the SNDlib problem instances. © 2009 Wiley Periodicals, Inc. NETWORKS, 2010

This paper evaluates the potential of convolutional neural networks in classifying short audio clips of environmental sounds. A deep model consisting of 2 convolutional layers with max-pooling and 2 fully connected layers is trained on a low level representation of audio data (segmented spectrograms) with deltas. The accuracy of the network is evaluated on 3 public datasets of environmental and urban recordings. The model outperforms baseline implementations relying on mel-frequency cepstral coefficients and achieves results comparable to other state-of-the-art approaches.