Miracle-dz/UniFAR-FTUs huggingface dataset:
Automated Text Simplification as a Preprocessing Step for Machine Translation into an Under-resourced Language

In this work, we investigate the possibility of using fully automatic text simplification system on the English source in machine translation (MT) for improving its translation into an under-resourced language. We use the state-of-the-art automatic text simplification (ATS) system for lexically and syntactically simplifying source sentences, which are then translated with two state-of-the-art English-to-Serbian MT systems, the phrase-based MT (PBMT) and the neural MT (NMT). We explore three different scenarios for using the ATS in MT: (1) using the raw output of the ATS; (2) automatically filtering out the sentences with low grammaticality and meaning preservation scores; and (3) performing a minimal manual correction of the ATS output. Our results show improvement in fluency of the translation regardless of the chosen scenario, and difference in success of the three scenarios depending on the MT approach used (PBMT or NMT) with regards to improving translation fluency and post-editing effort.
Multiresolution Wavelet Transform Based Anisotropic Diffusion for Removing Speckle Noise in a Real-Time Vision-Based Database

In﻿this﻿research﻿article,﻿a﻿novel﻿algorithm﻿is﻿introduced﻿to﻿identify﻿the﻿noisy﻿pixels﻿in﻿video﻿frames﻿and﻿ correct﻿them﻿to﻿enhance﻿video﻿quality. ﻿The﻿technique﻿consists﻿of﻿three﻿stages:﻿fragmentation﻿of﻿the﻿ video﻿sequences﻿to﻿respective﻿2D﻿frames,﻿noisy﻿pixel﻿identification﻿in﻿the﻿2D﻿frames,﻿and﻿denoising﻿the﻿ pixels﻿to﻿obtain﻿original﻿pixels. ﻿Due﻿to﻿the﻿complexity﻿in﻿the﻿background﻿and﻿the﻿change﻿in﻿appearance﻿ of﻿the﻿body﻿in﻿motion,﻿noise﻿variation﻿occurs. ﻿Various﻿researchers﻿discuss﻿that﻿in﻿order﻿to﻿denoise﻿ the﻿video﻿sequences,﻿spatio-temporal﻿filtering﻿is﻿required﻿which﻿identifies﻿noise﻿and﻿preserves﻿the﻿ edges. ﻿In﻿the﻿first﻿stage,﻿the﻿video﻿sequences﻿are﻿analyzed﻿for﻿the﻿removal﻿of﻿redundant﻿frames. ﻿This﻿ is﻿done﻿by﻿using﻿the﻿video﻿fragmentation﻿process﻿in﻿the﻿MATLAB﻿toolbox. ﻿In﻿the﻿next﻿stage,﻿color﻿ smoothing﻿is﻿applied﻿to﻿the﻿target﻿frames﻿for﻿processing﻿the﻿flat﻿regions﻿and﻿identifying﻿all﻿the﻿noisy﻿ pixels. ﻿In﻿the﻿final﻿stage,﻿an﻿improvised﻿multiresolution﻿wavelet﻿transform﻿based﻿anisotropic﻿diffusion﻿ filtering﻿is﻿applied﻿which﻿enhances﻿the﻿denoising﻿process﻿in﻿horizontal,﻿vertical,﻿and﻿diagonal﻿sub﻿ bands﻿of﻿the﻿video﻿frame﻿signal. ﻿The﻿proposed﻿technique﻿can﻿remove﻿the﻿speckle﻿noise﻿and﻿estimate﻿ the﻿motion﻿by﻿preserving﻿the﻿minute﻿details﻿of﻿the﻿processed﻿video﻿frames. KEyWoRDS Anisotropic Diffusion Filter, Gaussian Filter, Laplacian Filter, Multiresolution Wavelet Transform, PSNR, SSNR, Wavelet Based Anisotropic Diffusion, Wavelet Based Filter, Weiner Filter
DEEP NETWORK REPRESENTATION LEARNING FOR MARKET STRUCTURE DISCOVERY

With rapid technological developments, product-market boundaries have become more dynamic. Competition for products and services may emerge from outside of what is traditionally defined as product-market boundaries based on the SIC and NAICS codes. Identifying product-market boundaries is critical for firms to not only compete effectively within a market, but also to identify lurking threats and latent opportunities amidst the fluid boundaries. Extant literature in marketing has long examined defining market structure using different methodologies with data ranging from surveys on customer perceptions to observations on consideration sets and purchases, with data coming from mostly the purchase stage of the customer journey. Recently, big data on social media engagement has given us the opportunity to overcome many of the negatives of extant methods and uncover newer and important product-market insights. In this paper, we propose a deep network representation learning framework to capture latent relationships among thousands of brands across many categories using millions of social media userbrand engagement data. We first build a heterogeneous brand-user network, compress the network into a lower dimensional space using a deep Autoencoder technique while preserving both the first order (direct connection) and the second order (indirect connection) similarities between brand-user nodes. We validate our technique using a novel link-prediction method and show the superiority of method as compared to extant methodologies. We visualize the learned representations pictorially providing additional face validity. We also illustrate how our method can capture the dynamic changes of product market boundaries using two well-known events: Amazon acquiring Whole Foods and Tesla introducing Model 3.
Efficient Top-k Document Retrieval

Over the past few decades, the IR community has been making a continuous eﬀort to improve the eﬃciency of search in large collections of documents. Query processing is still one of the main bottlenecks in large-scale search systems. The top-k document retrieval problem, which can be deﬁned as reporting the k most relevant documents from a collection for a given query, can be extremely expensive, as it involves scoring large amounts of documents. In this work, we investigate the top-k document retrieval problem from several angles with the aim of improving the eﬃciency of this task in large-scale search systems. Finally, we brieﬂy describe our initial ﬁndings and conclude by proposing future directions to follow.
LIMSI@WMT’17

This paper describes LIMSI’s submissions to the news shared task at WMT’17 for English into Czech and Latvian, as well as related experiments. This year’s novel-ties consist in the use of a neural machine translation system with a factored output predicting simultaneously a lemma deco-rated with morphological information and a ﬁne-grained part-of-speech. Such a type of system drew our attention to the spe-ciﬁc step of reinﬂection, where lemmas and parts-of-speech are transformed into fully inﬂected words. Finally, we ran experiments showing an efﬁcient strategy for parameter initialization, as well as data ﬁl-tering procedures.
Improving Named Entity Linking Corpora Quality

Gold standard corpora and competitive evaluations play a key role in benchmarking named entity linking (NEL) performance and driving the development of more sophisticated NEL systems. The quality of the used corpora and the used evaluation metrics are crucial in this process. We, therefore, assess the quality of three popular evaluation corpora, identifying four major issues which affect these gold standards: (i) the use of different annotation styles, (ii) incorrect and missing annotations, (iii) Knowledge Base evolution, (iv) and differences in annotating co-occurrences. This paper addresses these issues by formalizing NEL annotations and corpus versioning which allows standardizing corpus creation, supports corpus evolution, and paves the way for the use of lenses to automatically transform between different corpus configurations. In addition, the use of clearly defined scoring rules and evaluation metrics ensures a better comparability of evaluation results.
Conceptualizing the Role of Emotional Intelligence in Influencing Person with Disabilities’ Job Embeddedness

Persons with disabilities (PWD) and workplace issues have always been an endless field of challenges yet gives rise to many interesting topics. They have to face many challenges starting from the initial phase of looking for a job up till they start working. As a result, the turnover rate among them is very high. There are many studies carried out on the factors that prevent disabled people from joining the working force but few studies have discovered the role of emotional intelligence in the influencing of disabled employees’ decision to stay at work. Hence, the purpose of this paper is to propose a framework which conceptualizes the influence job embeddedness among employed PWD. Emotional intelligence was proposed to have a significant influence on job embeddedness of PWD. A conceptual framework was developed using the Conservation of Resource (COR) Theory to describe emotional intelligence which is then used to support its connection to job embeddedness. Based on the variables engaged, it is argued that emotional intelligence among the disabled is an important element to be inculcated towards the aim of decreasing the probability of job quitting. It is believed that the limitations might be derived from the theory selected. However, this paper concludes with the proposition of further study to being conducted and this paper’s implication for future research. Practitioners could use the outlined framework as a hiring strategy to guide the employment of PWD in their company and to promote their job retention. This paper improves on a practical instrument to conceptualize a new way of looking at PWD’s emotional intelligence and extending the conception to confirm its effect on their job embeddedness.
Numerical Analysis on Trap of Credit C in Macroeconomics under Zero-Interest-Rate Policy

Protracted recession in Japan for the last twenty years is characterized by persistent deflation and negative output gap. Recently, Inoue et al. presented the concept of which represents mechanism of the persistent deflation based on zero-interest-rate economy. Three new Keynesian DGE models by Inoue et al. explain this type of deflation as a steady state of a system. The DGE models, which are based on optimization for utility function, derive simultaneous nonlinear differential equations. In the present paper, we study dynamical features on the steady states of the three DGE models (i.e. Model I, II, and III), using numerical calculation: i.e. we analyze stability of steady states, using Jacobian matrices. Model I and II correspond to models for positive-interest-rate economy, and Model III suggests mechanism of the recession characterized as trap of credit creation under zero-interest-rate economy. We show each of the models have a stable steady state. This result supports adequacy of the present models, which can shed light on mechanism of the protracted recession. © 2013 The Authors. Published by Elsevier B.V. Selection and/or peer-review under responsibility of the Program Committee of IES2013.
TITLE: Determining best strategies for maternally-targeted pertussis vaccination using an individual-based model RUNNING HEAD: Modeling maternally-targeted pertussis vaccination AUTHORS:

TITLE: Determining best strategies for maternally-targeted pertussis vaccination using an individual-based model RUNNING HEAD: Modeling maternally-targeted pertussis vaccination AUTHORS: Patricia Therese Campbell*, Jodie McVernon, Nicholas Geard * corresponding author AUTHOR AFFILIATIONS: Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia (Patricia Therese Campbell, Jodie McVernon, Nicholas Geard); Infection and Immunity, Murdoch Childrens Research Institute, Royal Children’s Hospital, Parkville, Victoria, Australia (Patricia Therese Campbell, Jodie McVernon)
Controlling the deformation space of soft membranes using fiber reinforcement

Recent efforts in soft-body control have been hindered by the infinite dimensionality of soft bodies. Without restricting the deformation space of soft bodies to desired degrees of freedom, it is difficult, if not impossible, to guarantee that the soft body will remain constrained within a desired operating range. In this article, we present novel modeling and fabrication techniques for leveraging the reorientation of fiber arrays in soft bodies to restrict their deformation space to a critical case. Implementing this fiber reinforcement introduces unique challenges, especially in complex configurations. To address these challenges, we present a geometric technique for modeling fiber reinforcement on smooth elastomeric surfaces and a two-stage molding process to embed the fiber patterns dictated by that technique into elastomer membranes. The variable material properties afforded by fiber reinforcement are demonstrated with the canonical case of a soft, circular membrane reinforced with an embedded, intersecting fiber pattern such that it deforms into a prescribed hemispherical geometry when inflated. It remains constrained to that configuration, even with an additional increase in internal pressure. Furthermore, we show that the fiber-reinforced membrane is capable of maintaining its hemispherical shape under a load, and we present a practical application for the membrane by using it to control the buoyancy of a bioinspired autonomous underwater robot developed in our lab. An additional experiment on a circular membrane that inflates to a conical frustum is presented to provide additional validation of the versatility of the proposed model and fabrication techniques.
Unified algorithms for polylogarithm, L-series, and zeta variants

We describe a general computational scheme for evaluation of a wide class of number-theoretical functions. We avoid asymptotic expansions in favor of manifestly convergent series that lend themselves naturally to rigorous error bounds. By employing three fundamental series algorithms we achieve a unified strategy to compute the various functions via parameter selection. This work amounts to a compendium of methods to establish extreme-precision results as typify modern experimental mathematics. A fortuitous byproduct of this unified approach is automatic analytic continuation over complex parameters. Another byproduct is a host of converging series for various fundamental constants. Center for Advanced Computation, Reed College. crandall@reed.edu Also available in a new collection from PSIpress, Algorithmic reflections: Selected works 2
Testing OCP-labial Effect on Japanese Rendaku

Japanese rendaku is a morphophonological phenomenon in which a morpheme-initial voiceless obstruent becomes voiced when it is the non-initial member of a compound. It is well known that rendaku is blocked by Lyman’s Law if the second member of a compound already contains a voiced obstruent. In addition to Lyman’s Law, there are other factors that inhibit rendaku. One of them is that, although /h/ usually becomes labial /b/ when rendaku applies (e.g., hako ‘box’ + hune ‘ship’ → hakobune ‘ark’; hude ‘pencil’ + hako ‘box’ → hudebako ‘pencil case’), the rendaku application of /h/ is blocked if the following consonant is labial /m/ (e.g., suna ‘sand’ + hama ‘beach’ → sunahama ‘sand beach’/*sunabama; kuʦu ‘shoe’ + himo ‘lace’ → kuʦuhimo ‘shoelace’/*kuʦubimo) (Kawahara et al. 2006; Kawahara 2015). One contributing factor to this rendaku blocking is that, if /h/ became labial /b/, it would beget a sequence of homorganic consonants /b.m. / (labial.labial), which would violate the OCP effect on consecutive labial consonants (OCP-labial) as observed in various languages (see, e.g., Alderete & Frisch 2007; Bye 2011; Odden 1994; Selkirk 1993; Zuraw & Lu 2009 for examples of OCP-labial effects). As far as I know, there is no wug-test study reported on the OCP-labial effect on Japanese rendaku. The current paper is the first report of an experiment that examined whether this restriction applies productively to nonce words that contain labial consonants. The results show that 1) the OCP-labial effect can be generalized in rendaku; 2) it works locally rather than non-locally; and 3) the applicability of rendaku is gradient according to the following labial consonant: /m/ shows a stronger blocking effect on the applicability of rendaku than /Φ, w/. The last finding is what is observed in various languages: The more similar two consonants are, the more strongly they are disfavored (e.g., Berent & Shimron 2003; Berent et al. 2004; Buckley 1997; Frisch et al. 2004; Greenberg 1950; Pierrehumbert 1993). To account for this gradient effect, I argue that the process involves two OCP-labial constraints: OCP (labial) and OCP (labial, continuant), and that they show a ganging-up effect with other faithfulness constraints on blocking rendaku. The organization of the current paper is as follows: Section 2 explicates the restriction on rendaku that this paper focuses on. Section 3 explains the experimental design and reports the results of the current experiment. Section 4 provides an analysis of the results in the Harmonic Grammar (HG) framework (e.g., Legendre et al. 1990, 2006; Pater 2009, 2016; Potts et al. 2010). Section 5 discusses the issue of the nature of the OCP-labial effect. Section 6 gives a brief conclusion.
EXPERIMENTAL CHARACTERIZATION OF HIGH VISCOSITY DROPLET EJECTION

Additive Manufacturing via Microarray Deposition (AMMD) expands the allowable range of physical properties of printed fluids to include important, high-viscosity production materials (e.g., polyurethane resins). This technique relies on a piezoelectrically-driven ultrasonic printhead that generates continuous streams of droplets from 45 mm orifices while operating in the 0.5 to 3.0 MHz frequency range. Unique to this new printing technique are the high frequency of operation, use of fluid cavity resonances to assist ejection and acoustic wave focusing to generate the pressure gradient required to form and eject droplets. Specifically, we found that peaks in the ejection quality corresponded to predicted device resonances. Our results indicate that the micromachined ultrasonic print-head is able to print fluids up to 3000 mN-s/m 2 , far above the typical printable range.
Informationally Robust Welfare Predictions Under Second-Degree Price Discrimination

In an environment that features second-degree price discrimination, this paper fully characterizes the set of surplus divisions that can arise from all possible information consumers have about their valuation. By extending the techniques developed in a companion paper (Yang, 2019a), I show that the set of feasible surplus divisions can be characterized by a family of information structures that induce Pareto-distributed interim expected values. Unlike the linear model as in Roesler & Szentes (2017) where posted price is always optimal, the efficient frontier is generically not attainable under any information structures and there are environments in which a (nontrival) subset of the feasible surplus divisions collapses to a one-dimensional set. Nevertheless, the sets of feasible surplus divisions are stable around the linear environments.
A COMPARATIVE STUDY OF MODE I FATIGUE CRACK PROPAGATION IN FOAM CORES FOR SANDWICH STRUCTURES BY USING DIFFERENT TEST SPECIMENS

This paper summarizes results on mode I fatigue crack growth (FCG) in foam core materials for sandwich structures. The studies deal with characterization of the FCG in the face/core interface in sandwich beams and in the virgin foam core. The core material properties, test specimens and experimental procedures are briefly described. Stress intensity factors ∆K in the vicinity of the crack tips are computed using the finite element method. The obtained FCG rates da/dN in the investigated specimen configurations are combined in standard da/dN versus ∆K curves. Fatigue behaviour of the cellular foams appear to conform to the classical Paris’ law. The influence of face/core interface on mode I FCG rates is discussed in comparison to the FCG rates in the virgin core. The FCG rates in the face/core interface in sandwich beams are verified using the Tilted Debond Sandwich (TDS) specimen.
Development of an Experimental Optimization Method in Laser-Assisted Cold Spray

Current experimental optimization methods take extended periods of time and do not have a systematic way to get closer to the optimum. As a result, the team set out to generate a new, systematic approach to experimental optimization that costs time and cost. First, a theoretical goodness equation was used to predict the influential trends of parameters in the Laser-Assisted Cold Spray (LACS) process on three material properties. This was also used to select the algorithm used, Mine Blast Algorithm. The equation and algorithm was then modified for the experimental process which included a fourth variable. The team was able to achieve a goodness of 0.66 after only 5 iterations of the estimated 25 iterations necessary to achieve optimization (30 samples).
Improvement of the Content and Uptake of Micronutrients in Spring Rye Grain DM Through Nitrogen and Sulfur Supplementation

The aim of this field experiment was to analyze the influence of different nitrogen and sulfur doses on yield as well as the content and uptake of iron (Fe), manganese (Mn), copper (Cu) and zinc (Zn) by spring rye grain. The study was conducted in south-eastern Poland (2009–2011) on Cambisols (WRB 2015), in conditions of low sulfur content in soil. The experiment included four doses of N fertilization (0, 30, 60 and 90 kg ha−1) and two doses of S supplementation (0 and 40 kg ha−1). The analysis showed that fertilization with N and S had a positive effect on the studied features of spring rye. The highest grain yields were found after use of 90 kg N ha−1. The grain of rye fertilized with these doses of N was characterized by the highest concentration and uptake of tested microelements. The supplementation of sulfur in a dose of 40 kg S ha−1 improved the nitrogen effect, because the rye grain yield and the content and uptake of micronutrients (except Mn) by rye grain dry mass increased. The highest yield of spring rye grain and accumulation of Mn and Zn and intake of Mn, Zn and Cu by grain dry mass (DM) were obtained in the vegetation season of 2011, which was characterized by an optimal rainfall distribution. The highest accumulation of Fe and Cu and intake of Fe were obtained in the vegetation season of 2009. Significant correlations were found also between grain yield and the content and uptake of all studied micronutrients. The supplementation of NPK fertilization with sulfur can be a good means of agronomic biofortification for spring rye in order to increase the content and uptake of Fe, Mn, Zn and Cu.
TNT-MOLECULARLY IMPRINTED MEMBRANES VIA PHASE INVERSION METHOD

This paper aims to provide novel molecularly imprinted membranes with TNT as template (TNT-MIMs) prepared via wet phase inversion. Two PAN -coacrylic acid matrix systems, obtained by free emulsion polymerization, were used to prepare copolymer solutions in dimethylformamide in order to establish the appropriate parameters for membrane preparation (rheological study). Additionally, experimental FT-IR spectroscopy has been conducted to validate both TNT imprinting and extraction. The TNT-MIMs can be further used as sensing receptors to prepare a versatile sensor. 1 University POLITEHNICA of Bucharest, Faculty of Applied Chemistry and Materials Science, Polizu no.1-7, 011061, Bucharest, Romania, anaflorea22@yahoo.com 2 National Research and Development Institute for Chemistry and Petrochemistry ICECHIM Bucharest, Splaiul Independentei 202, 060021, Romania, andr.sarbu@gmail.com 3 National Research and Development Institute for Chemistry and Petrochemistry ICECHIM Bucharest, Splaiul Independentei 202, 060021, Romania, nicolescu_vera@yahoo.com 4 National Research and Development Institute for Chemistry and Petrochemistry ICECHIM Bucharest, Splaiul Independentei 202, 060021, Romania, anamaria.lungu1984@gmail.com 5 National Research and Development Institute for Chemistry and Petrochemistry ICECHIM Bucharest, Splaiul Independentei 202, 060021, Romania, raduanita@gmail.com 6 National Research and Development Institute for Chemistry and Petrochemistry ICECHIM Bucharest, Splaiul Independentei 202, 060021, Romania, steluta.apostol@yahoo.com 7 National Research and Development Institute for Chemistry and Petrochemistry ICECHIM Bucharest, Splaiul Independentei 202, 060021, Romania, stela_iancu@yahoo.com 8 National Research and Development Institute for Chemistry and Petrochemistry ICECHIM Bucharest, Splaiul Independentei 202, 060021, Romania, em_duldner@yahoo.com 9 National Institute for Research and Development in Electrochemistry and Condensed Matter Timisoara, Plautius Andronescu 1, 300224, Romania, L_carmen@icmct.uvt. ro 10 University POLITEHNICA of Bucharest, Faculty of Applied Chemistry and Materials Science, Polizu no.1-7, 011061, Bucharest, Romania, gheorghe_hubca@yahoo.com A-M. FLOREA, A. SÂRBU, T-V. IORDACHE, A. ZAHARIA, A-L. RADU, S. APOSTOL, S. IANCU, M. DULDNER, C. LAZĂU, G. HUBCA 2