Clumpy streams in a smooth dark halo: the case of Palomar 5

By means of direct N-body simulations and simplified numerical models, we study the formation and characteristics of the tidal tails around Palomar 5, along its orbit in the Milky Way potential. Unlike previous findings, we are able to reproduce the substructures observed in the stellar streams of this cluster, without including any lumpiness in the dark matter halo. We show that overdensities similar to those observed in Palomar 5 can be reproduced by the epicyclic motion of stars along its tails, i.e. a simple local accumulation of orbits of stars that escaped from the cluster with very similar positions and velocities. This process is able to form stellar clumps at distances of several kiloparsecs from the cluster, so it is not a phenomenon confined to the inner part of Palomar 5's tails, as previously suggested. Our models can reproduce the density contrast between the clumps and the surrounding tails found in the observed streams, without including any lumpiness in the dark halo, suggesting new upper limits on its granularity.Comment: 6 pages, 7 figures. A&A Letters, accepted. Top panel of Fig. A1 replaced, minor typos corrected. High resolution version available at http://mygepi.obspm.fr/~paola/Pal5

An enhancement of the warping shear functions of Refined Zigzag Theory

The paper presents an enhancement in Refined Zigzag Theory (RZT) for the analysis of multilayered composite plates. In standard RZT, the zigzag functions cannot predict the coupling effect of inplane displacements for anisotropic multilayered plates, such as angle-ply laminates. From a computational point of view, this undesirable effect leads to a singular stiffness matrix. In this work, the local kinematic field of RZT is enhanced with the other two zigzag functions that allow the coupling effect. In order to assess the accuracy of these new zigzag functions for RZT, results obtained from bending of angle-ply laminated plates are compared with the three-dimensional exact elasticity solutions and other plate models used in the open literature. The numerical results highlight that the enhanced zigzag functions extend the range of applicability of RZT to the study of general angle-ply multilayered structures, maintaining the same seven kinematic unknowns of standard RZT

A Family of C0 Quadrilateral Plate Elements Based on the Refined Zigzag Theory for the Analysis of Thin and Thick Laminated Composite and Sandwich Plates

The present work focuses on the formulation and numerical assessment of a family of C0 quadrilateral plate elements based on the refined zigzag theory (RZT). Specifically, four quadrilateral plate elements are developed and numerically tested: The classical bi-linear 4-node element (RZT4), the serendipity 8-node element (RZT8), the virgin 8-node element (RZT8v), and the 4-node anisoparametric constrained element (RZT4c). To assess the relative merits and drawbacks, numerical tests on bending (maximum deflection and stresses) and free vibration analysis of laminated composite and sandwich plates under different boundary conditions and transverse load distributions are performed. Convergences studies with regular and distorted meshes, transverse shear-locking effect for thin and very thin plates are carried out. It is concluded that the bi-linear 4- node element (RZT4) has performances comparable to the other elements in the range of thin plates when reduced integration is adopted but presents extra zero strain energy modes. The serendipity 8-node element (RZT8), the virgin 8-node element (RZT8v), and the 4-node anisoparametric constrained element (RZT4c) show remarkable performance and predictive capabilities for various problems, and transverse shear-locking is greatly relieved, at least for aspect ratio equal to 5 × 10^2, without using any reduced integration scheme. Moreover, RZT4c has well-conditioned element stiffness matrix, contrary to RZT4 using reduced integration strategy, and has the same computational cost of the RZT4 element

Fine-tuning on Clean Data for End-to-End Speech Translation: FBK @ IWSLT 2018

This paper describes FBK's submission to the end-to-end English-German speech translation task at IWSLT 2018. Our system relies on a state-of-the-art model based on LSTMs and CNNs, where the CNNs are used to reduce the temporal dimension of the audio input, which is in general much higher than machine translation input. Our model was trained only on the audio-to-text parallel data released for the task, and fine-tuned on cleaned subsets of the original training corpus. The addition of weight normalization and label smoothing improved the baseline system by 1.0 BLEU point on our validation set. The final submission also featured checkpoint averaging within a training run and ensemble decoding of models trained during multiple runs. On test data, our best single model obtained a BLEU score of 9.7, while the ensemble obtained a BLEU score of 10.24.Comment: 6 pages, 2 figures, system description at the 15th International Workshop on Spoken Language Translation (IWSLT) 201

Biaxial bending of SFRC slabs: Is conventional reinforcement necessary?

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Robustness of RC girder bridges: The case of half-joint bridges

Considerable research efforts have been made on the progressive collapse resistance of buildings. This effort is much more limited in the case of bridges, where robustness criteria are just as, or even more important than in buildings. Existing studies dealing with the robustness of bridges, although appreciable, often are limited to qualitative considerations that can provide designers with valuable pointers when designing new bridges. It is equally important to assess not only the safety but also the robustness of existing bridges through reliable metrics that can be used in the prioritization of interventions by the managing authority. According to this aim, this paper applies a selected measure of robustness to a particular type of reinforced concrete (RC) girder bridge, namely half-joint bridges. The Annone viaduct, which collapsed in 2016 after the passage of a heavy truck, is used as a case study

Correction to: Biaxial bending of SFRC slabs: Is conventional reinforcement necessary?

The article "Biaxial bending of SFRC slabs: Is conventional reinforcement necessary?", written by Marco di Prisco, Matteo Colombo and Ali Pourzarabi, was originally published electronically on the publisher's Internet portal (currently SpringerLink) on 22 December 2018 without open access

On Target Segmentation for Direct Speech Translation

Recent studies on direct speech translation show continuous improvements by means of data augmentation techniques and bigger deep learning models. While these methods are helping to close the gap between this new approach and the more traditional cascaded one, there are many incongruities among different studies that make it difficult to assess the state of the art. Surprisingly, one point of discussion is the segmentation of the target text. Character-level segmentation has been initially proposed to obtain an open vocabulary, but it results on long sequences and long training time. Then, subword-level segmentation became the state of the art in neural machine translation as it produces shorter sequences that reduce the training time, while being superior to word-level models. As such, recent works on speech translation started using target subwords despite the initial use of characters and some recent claims of better results at the character level. In this work, we perform an extensive comparison of the two methods on three benchmarks covering 8 language directions and multilingual training. Subword-level segmentation compares favorably in all settings, outperforming its character-level counterpart in a range of 1 to 3 BLEU points.Comment: 14 pages single column, 4 figures, accepted for presentation at the AMTA2020 research trac

End-to-End Speech-Translation with Knowledge Distillation: FBK@IWSLT2020

This paper describes FBK's participation in the IWSLT 2020 offline speech translation (ST) task. The task evaluates systems' ability to translate English TED talks audio into German texts. The test talks are provided in two versions: one contains the data already segmented with automatic tools and the other is the raw data without any segmentation. Participants can decide whether to work on custom segmentation or not. We used the provided segmentation. Our system is an end-to-end model based on an adaptation of the Transformer for speech data. Its training process is the main focus of this paper and it is based on: i) transfer learning (ASR pretraining and knowledge distillation), ii) data augmentation (SpecAugment, time stretch and synthetic data), iii) combining synthetic and real data marked as different domains, and iv) multi-task learning using the CTC loss. Finally, after the training with word-level knowledge distillation is complete, our ST models are fine-tuned using label smoothed cross entropy. Our best model scored 29 BLEU on the MuST-C En-De test set, which is an excellent result compared to recent papers, and 23.7 BLEU on the same data segmented with VAD, showing the need for researching solutions addressing this specific data condition.Comment: Accepted at IWSLT202