Miracle-dz/UniFAR-FTUs huggingface dataset:
A GENERAL GALERKIN FINITE ELEMENT METHOD FOR TURBULENT COMPRESSIBLE FLOW

In this paper we present a General Galerkin (G2) method for the compressible Euler equations, including turbulent flow. The G2 method presented in this paper is a finite element method with linear approximation in space and time, with componentwise stabilization in the form of streamline diffusion and shock-capturing modifications. The method conserves mass, momentum and energy, and we prove an a posteriori version of the 2nd Law of thermodynamics for the method. We illustrate the method for a laminar shock tube problem for which there exists an exact analytical solution, and also for a turbulent flow problem.
P o S ( M Q W 6 ) 0 0 4 X-ray spectroscopy of GRO J 1655-40

After seven years in quiescence, GRO J1655-40 started a new outburst in February 2005, rising to a high/soft state in March 2005. We report here the results of four XMM-Newton observations performed on 27 February 2005 in the low/hard state, and on three consecutive days in March 2005 during the rise of the source to its high/soft state. The X-ray spectrum of GRO J1655-40 was dominated in the high/soft state by the thermal emission from the accretion disk, with a maximum temperature of 1.3 keV. We detected two absorption lines in the EPIC-pn spectra at 6.7–6.8 and 7.8–8.0 keV, which could be identified as the Kα and Kβ lines of either blended Fe XXV and Fe XXVI or blueshifted Fe XXV. We found no orbital dependence on the X-ray properties, which provides an upper limit for the inclination of the system of 73.
Proteomic analysis of the human KEOPS complex identifies C 14 ORF 142 as a core subunit homologous to yeast Gon 7

The KEOPS/EKC complex is a tRNA modification complex involved in the biosynthesis of N6-threonylcarbamoyladenosine (t6A), a universally conserved tRNA modification found on ANN-codon recognizing tRNAs. In archaea and eukaryotes, KEOPS is composed of OSGEP/Kae1, PRPK/Bud32, TPRKB/Cgi121 and LAGE3/Pcc1. In fungi, KEOPS contains an additional subunit, Gon7, whose orthologs outside of fungi, if existent, remain unidentified. In addition to displaying defective t6A biosynthesis, Saccharomyces cerevisiae strains harboring KEOPS mutations are compromised for telomere homeostasis, growth and transcriptional coactivation. To identify a Gon7 ortholog in multicellular eukaryotes as well as to uncover KEOPSinteracting proteins that may link t6A biosynthesis to the diverse set of KEOPS mutant phenotypes, we conducted a proteomic analysis of human KEOPS. This work identified 152 protein interactors, one of which, C14ORF142, interacted strongly with all four KEOPS subunits, suggesting that it may be a core component of human KEOPS. Further characterization of C14ORF142 revealed that it shared a number of biophysical and biochemical features with fungal Gon7, suggesting that C14ORF142 is the human ortholog of Gon7. In addition, our proteomic analysis identified specific interactors for different KEOPS subcomplexes, hinting that individual KEOPS subunits may have additional functions outside of t6A
Wavelength Conversion of DP-QPSK Signals in a Silicon Polarization Diversity Circuit

Multichannel wavelength conversion is experimentally demonstrated for high-speed 128 Gb/s dual-polarization quadrature phase-shift keying signals using four-wave mixing in a polarization diversity circuit with silicon nanowires as nonlinear elements. The wavelength conversion performance is investigated for both single- and three-channel input signals, showing quality factors well >9.8 dB (corresponding to bit-error-ratios better than 10-3) and with a negligible power penalty compared with the back-to-back case.
NOVEL FEMTOSECOND LEVEL SYNCHRONIZATION OF TITANIUM SAPPHIRE LASER AND RELATIVISTIC ELECTRON BEAMS

Laser driven plasma accelerators are offering high gradient (∼10-100 GV/m), high quality (low emittance, short bunch length) electron beams, which can be suitable for future compact, bright and tunable light sources. In the framework of the Laboratory for Laser-and beam-driven plasma Acceleration (LAOLA) collaboration at Deutsches Elektronen-Synchrotron (DESY) the external injection experiment for injecting electron bunches from a conventional RF accelerator into the linear plasma wave is in progress. External injection experiments at REGAE (Relativistic Electron gun for Atomic Exploration) require sub-20fs precision synchronization of laser and electron beams in order to perform a beam scan into the plasma wave by varying the delay between electron beam and laser pulses. In this paper we present a novel optical to microwave synchronization scheme, based on a balanced single output integrated MachZehnder Modulator (MZM). The scheme offers a highly sensitive phase detector between a pulsed 800 nm Ti:Sa. laser and a 3 GHz microwave reference source. It is virtually independent of input laser power fluctuations and it offers femtosecond long-term precision. Together with the principal of operation of this setup, we will present promising preliminary experimental measurements of the new detector stability.
An Integrated System for Multichannel Neuronal Recording With Spike/LFP Separation, Integrated A/D Conversion and Threshold Detection

A mixed-signal front-end processor for multichannel neuronal recording is described. It receives 12 differential-input channels of implanted recording electrodes. A programmable cutoff High Pass Filter (HPF) blocks dc and low-frequency input drift at about 1 Hz. The signals are band-split at about 200 Hz to low-frequency Local Field Potential (LFP) and high-frequency spike data (SPK), which is band limited by a programmable-cutoff LPF, in a range of 8-13 kHz. Amplifier offsets are compensated by 5-bit calibration digital-to-analog converters (DACs). The SPK and LFP channels provide variable amplification rates of up to 5000 and 500, respectively. The analog signals are converted into 10-bit digital form, and streamed out over a serial digital bus at up to 8 Mbps. A threshold filter suppresses inactive portions of the signal and emits only spike segments of programmable length. A prototype has been fabricated on a 0.35-mum CMOS process and tested successfully, demonstrating a 3-muV noise level. Special interface system incorporating an embedded CPU core in a programmable logic device accompanied by real-time software has been developed to allow connectivity to a computer host
Production Techniques for 3D Printed Inflatable Elastomer Structures: Part I—Fabricating Air-Permeable Forms and Coating with Inflatable Silicone Membranes via Spray Deposition

Abstract This article is the first in a two-part series describing a process for conformal three-dimensional (3D) printing on to inflatable substrates. Details for fabricating seamless, tubular elastomeric membranes by spray deposition on a double-curved air-permeable mandrel are presented in Part I. The mandrels are created by casting gypsum into a desired form, and they are made permeable by applying pressurized air to the central core of the gypsum body during its crystallization phase. The membranes—in this case made from silicone—are created by spray deposition onto the mandrel by using a constant surface angular velocity approach. These membranes are inflated so as to impart mechanical pre-strain in the rubber by stretching. The techniques described are particularly suited to the fabrication of 3D printed pneumatic artificial muscles and dielectric elastomer actuators. They can also be used to create removable substrates on which a 3D print can be extruded, or alternatively integrated into a four-di.
Parallel Methods of Solving of Supply Problem Using Ant Colony Optimization

Presented work focuses on solving of the vehicle routing problem, which is considered as a basic supply problem. The main motivation is to achieve high quality solutions of the vehicle routing problem in the shortest possible time. It tries to achieve this goal via parallelization of the ant colony optimization metaheuristics, which is suitable for calculating of combinatorial problems. The vehicle routing problem is an NP-complete problem, therefore usage of heuristics is the only way to solve it on large instances. The author proposes and compares different settings and solving methods of the vehicle routing problem using the ant colony optimization in sequence and parallel execution. He determines appropriate application of the local search methods, which improves solution quality and applies the elite approach. On selected communication topology, he proposes and compares several synchronization and communication strategies, all from achieved quality and speedup point of view, on different number of multi-core processors. The author presents his own optimization tool, which is based on execution of the ant colony optimization in a parallel environment. The author applies proposed parallel method to the very large scale vehicle routing problem instances with as many as 1200 customers.
Power and Limits of Recurrent Neural Networks for Symbolic Sequences Processing

A recurrent neural network is a class of neural network where connections between neurons form a directed cycle. These so-called recurrent connections allow spreading information about past neural activities in network, which enables to process temporal inputs. Although they are theoretically equivalent to Turing machines, widespread use is restricted due to computational expensive training and lack of knowledge of internal representation mechanism in this class of networks. Our thesis studies properties of recurrent neural networks while processing symbolic inputs. We focused mainly on their relation and description of their behavior in terms of dynamical systems. We describe the dynamics of randomly initialized neural network and its relation to Markov prediction models of variable length. In the main part of our work, we present usability of methods for visualization, clusterization and the state space analysis as an effective tool for thorough study of recurrent networks capabilities on prediction tasks. In experimental part of our thesis, we focus on studying changes that emerge in training. We are mostly interested in the change of näıve Markovian dynamics of randomly initialized network during training in relation to various factors such as input sequence, training algorithm, network architecture, number of hidden units, etc. We focused not only on simple recurrent network before and after training, but also on the computational capabilities of the new approach called echo state networks. It uses large randomly initialized neural reservoir, which dynamics is the subject of our interest. We demonstrate ∗Recommended by thesis supervisor: Assoc. Prof. L’ubica Beňušková Defended at Faculty of Informatics and Information Technologies, Slovak University of Technology in Bratislava on July 8, 2009. c © Copyright 2009. All rights reserved. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies show this notice on the first page or initial screen of a display along with the full citation. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, to redistribute to lists, or to use any component of this work in other works requires prior specific permission and/or a fee. Permissions may be requested from STU Press, Vazovova 5, 811 07 Bratislava, Slovakia. benefits and constrains of this currently popular approach based on the results of our experiments and differences identified after recurrent networks training.
Experimental Noise Spectroscopy and the Measurement of Periodic Material Structures

The authors discuss the application of a broadband noise signal in the research of periodic structures and present the basic testing related to the described problem. Generally, noise spectroscopy tests are carried out to verify the behaviour of the response of periodic structures, and their objective consists in recording the properties of microscopic structures in natural and artificial materials. The aim is to find a metrological method utilizable for the investigation of structures and materials in the frequency range between 100 MHz and 10 GHz; this paper therefore characterizes the design of a suitable measuring technique based on noise spectroscopy and introduces the first tests conducted on a periodic structure. In this context, the applied equipment is also shown to complete the underlying theoretical analysis.
STELLAR-AIDED INERTIAL NAVIGATION SYSTEMS FOR LUNAR AND MARS EXPLORATION

Accurate, robust navigation for the exploration of the Moon and Mars is required for a variety of applications, including manned and unmanned lander descent/ascent, landing site survey/registration, and surface operations. In this paper, we examine the use of a stellar-aided inertial navigation system (SAINS) for use on the surface of the Moon and Mars. The goal is to show that SAINS can enable global, continuous, autonomous navigation for surface vehicles (landers, rovers or aircraft) and astronauts. The theory and SAINS model were originally developed for a study of Mars celestial navigation and will be presented as such. The lunar results are based on a model developed with the same theory which included the more complex rotational dynamics of the Moon. An extended Kalman filter was used to process simulated star position measurements to provide high-accuracy navigation solutions. High-fidelity models of the planetary environments and inertial measurement unit (IMU) were employed. The results were verified by a Monte Carlo analysis, and the predominant sources of error were identified with an error budget. It is shown that a SAINS can achieve accuracies of approximately 300 m on Mars and 400 m on the Moon with a high quality IMU. Although the Moon lacks an atmosphere and has a smaller radius than Mars, the larger ratio of the IMU accelerometer bias to the surface gravity accounts for the less accurate results on the Moon. This paper has many applications to lunar surface navigation in support of the Robotic Lunar Exploration Program.
Raw Tweets Emoji Tweets Word 2 Vec Sentence Representation Model Word Embeddings Representation Learning : Source Language Representation Learning : Target Language Labeled English Docs Supervised Learning Emoji Tweets Word 2 Vec Word EmbeddingsMachine Translate Classification Model New Document in 

Sentiment classification typically relies on a large amount of labeled data. In practice, the availability of labels is highly imbalanced among different languages, e.g., more English texts are labeled than texts in any other languages, which creates a considerable inequality in the quality of related information services received by users speaking different languages. To tackle this problem, crosslingual sentiment classification approaches aim to transfer knowledge learned from one language that has abundant labeled examples (i.e., the source language, usually English) to another language with fewer labels (i.e., the target language). The source and the target languages are usually bridged through off-the-shelf machine translation tools. Through such a channel, cross-language sentiment patterns can be successfully learned from English and transferred into the target languages. This approach, however, often fails to capture sentiment knowledge specific to the target language, and thus compromises the accuracy of the downstream classification task. In this paper, we employ emojis, which are widely available in many languages, as a new channel to learn both the cross-language and the language-specific sentiment patterns. We propose a novel representation learning method that uses emoji prediction as an instrument to learn respective sentiment-aware representations for each language. The learned representations are then integrated to facilitate cross-lingual sentiment classification. The proposed method demonstrates state-of-the-art performance on benchmark datasets, which is sustained even when sentiment labels are scarce.
3 D Imaging Using Photon Counting Lidar on a Moving Platform

The problem of constructing high quality point clouds based on measurements from a moving and rotating single-photon counting lidar is considered in this report. The movement is along a straight rail while the lidar sensor rotates side to side. The point clouds are constructed in three steps, which are all studied in this master’s thesis. First, point clouds are constructed from raw lidar measurements from single sweeps with the lidar. In the second step, the sensor transformation between the point clouds constructed in the first step are obtained in a registration step using iterative closest point (ICP). In the third step the point clouds are combined to a coherent point cloud, using the full measurement. A method using simultaneous localization and mapping (SLAM) is developed for the third step. It is then compared to two other methods, constructing the final point cloud only using the registration, and to utilize odometric information in the combination step. It is also investigated which voxel discretization that should be used when extracting the point clouds. The methods developed are evaluated using experimental data from a prototype photon counting lidar system. The results show that the voxel discretization need to be at least as large as the range quantization in the lidar. No significant difference between using registration and SLAM in the third step is observed, but both methods outperform the odometric method.
Contribution Association of Prenatal Exposure to Polybrominated Diphenyl Ethers and Infant Birth Weight

Polybrominated diphenyl ethers (PBDEs) are a class of persistent compounds that have been used as flame retardants in vehicles, household furnishings, and consumer electronics. This study examined whether concentrations of PBDEs in maternal serum during pregnancy were associated with infant birth weight, length, head circumference, and length of gestation. Participants were pregnant women (n 1⁄4 286) enrolled in the Center for the Health Assessment of Mothers and Children of Salinas (CHAMACOS) Study, a longitudinal cohort study of low-income, predominantly Mexican families living in the Salinas Valley, California. Blood samples were collected near the 26th week of pregnancy in 1999–2000, and concentrations of 10 PBDE congeners (BDE-17, -28, -47, -66, -85, -99, -100, -153, -154, and -183) were measured. Multiple linear regression models were used to investigate the association of lipid-adjusted, log10-transformed PBDE concentrations and birth outcome. In adjusted analyses, negative associations with birth weight were seen with BDE-47 (b 1⁄4 115 g, 95% confidence interval (CI): 229, 2), BDE-99 (b 1⁄4 114 g, 95% CI: 225, 4), and BDE-100 (b 1⁄4 122 g, 95% CI: 235, 9). These findings were diminished slightly and were no longer statistically significant when maternal weight gain was included in the models. PBDE congeners were not associated with birth length, head circumference, or gestational duration.
Transcriptional Repressor HIC 1 Contributes to Suppressive Function of Human Induced Regulatory T Cells

Powered by TCPDF (www.tcpdf.org) This material is protected by copyright and other intellectual property rights, and duplication or sale of all or part of any of the repository collections is not permitted, except that material may be duplicated by you for your research use or educational purposes in electronic or print form. You must obtain permission for any other use. Electronic or print copies may not be offered, whether for sale or otherwise to anyone who is not an authorised user. Ubaid Ullah, Ullah; Andrabi, Syed Bilal Ahmad; Tripathi, Subhash Kumar; Dirasantha, Obaiah; Kanduri, Kartiek; Rautio, Sini; Gross, Catharina C. ; Lehtimäki, Sari; Bala, Kanchan; Tuomisto, Johanna; Bhatia, Urvashi; Chakroborty, Deepankar; Elo, Laura L. ; Lähdesmäki, Harri; Wiendl, Heinz; Rasool, Omid; Lahesmaa, Riitta
GLM models for ordered and unordered categorical response variables

The proportional odds model can most simply be understood as an extension of logistic regression. This technique allows one to model ordered data by analysing it as number of dichotomies. A binary logistic regression model compares one dichotomy (for example, passed—failed, died—survived, etc.) whereas the proportional odds model compares a number of dichotomies by arranging the ordered data into a series of binary comparisons. For example, a four category ordered variable Y (coded using j categories, 1, 2, 3, 4) can be represented as three binary comparisons.
The Space of Capital: A Latent Class Analysis of Capital Portfolios in Germany

The aim of this paper is to construct the “space of capital” based on disaggregated measures of capital portfolios and to analyze the dynamics of class mobility over time. Drawing on Pierre Bourdieu’s concept of the “social space”, we argue that it is possible to directly assess the structural dimensions of the social space as a space of (economic and cultural) capital, including wealth as an important but often neglected form of economic capital. Using household panel data from 2002-2012 (SOEP), we apply latent class analysis in order to detect distinct classes based on specific capital portfolios. We find nine classes with diverging capital portfolios. When interpreting the nine latent classes, we find clear evidence for the two main axis of the social space, namely the vertical axis of the overall volume of capital, and the horizontal axis representing the composition of capital in terms of the relative weight of economic and cultural capital. Further exploration of class mobility reveals that the horizontal axis is even more stable over time. Most mobility occurs along the vertical axis of the social space, while there is only little horizontal mobility indicating that individuals rarely change their investment and accumulation strategies. This research adds to Bourdieu inspired class analysis as well as sociological perspectives on wealth and accumulation.
North Atlantic marine cores are the only archive to register Heinrich events stricto senso ( i . e . the IRD layer ) together with their impact on ocean circulation characteris

M. Guillevic, L. Bazin, A. Landais, C. Stowasser, V. Masson-Delmotte, T. Blunier, F. Eynaud, S. Falourd, E. Michel, B. Minster, T. Popp, F. Prié, and B. M. Vinther Laboratoire des Sciences du Climat et de l’environnement, UMR CEA/CNRS/UVSQ 8212, Gif-sur-Yvette, France Centre for Ice and Climate, Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark Laboratoire EPOC, UMR CNRS 5805 EPOC-OASU, Université Bordeaux 1, Talence, France
Extreme Convective Storms Over High‐Latitude Continental Areas Where Maximum Warming Is Occurring

Deep convective storms play a key role in severe weather, the hydrological cycle, and the global atmospheric circulation. Historically, little attention has been paid to the intense convective storms in the high latitudes. These regions have been experiencing the largest increases of mean surface temperature over the last century. The Global Precipitation Measurement core satellite, which features a space‐borne Dual‐frequency Precipitation Radar providing near‐global coverage (65°S to 65°N), has made it possible to establish the occurrence of convective storms at high latitudes. Analysis of the three‐dimensional radar echoes seen by Global Precipitation Measurement over a 5‐year period (2014–2018) shows that extremely intense deep convective storms do occur often during the warm season (April–September) in the high‐latitude continents where the increase of surface temperature has been greatest. The associated thermodynamical environments suggest that high‐latitude extreme convection could be more common in a continually warming world.