Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effect of Age and Discourse Position on Referential Adequacy in Filipino Bilingual Children ’ s Oral Narratives in Mandarin

In producing comprehensible narratives, a narrator needs to introduce participants, maintain the reference, and show if a switch in the reference has been made. The present study examines the effect of age and discourse position on referential adequacy in bilingual (L1: Mandarin and L2: English) children’s storytelling in Mandarin and the specific referential expressions that are used in introducing, maintaining, and reintroducing a character, separately. Eighty children aged three, five, seven, and nine (20 children for each age range) were selected from Chinese International School in the Philippines and four wordless picture books were designed based on the three referential functions. Results showed that children’s referential ability developed as they aged. Three-year-olds could only adequately maintain major characters, whereas the nine-year-olds performed all referential functions near ceiling. Out of expectation, children tended to act better when reference occurred later in the discourse. Older children had the tendency to employ more different linguistic forms for each type of referential function than younger ones. Results seem to reflect children’s development of two sorts of cognitive presupposition: the addressee’s knowledge of the referent and the addressee’s attention toward it.
Using Perspective in Narrative Learning Environments

Several empathic applications have been developed over the last years but can we redirect that empathy to specific characters? This paper focuses on the intention to induce empathy in children and stimulate role taking by presenting a narrative through the perspective of a specific character. The use of perspective is achieved by showing the events that happen in the story but without impartiality. We will describe a narrative-based application designed to help children cope with bullying situations, the FearNot! demonstrator, and an embedded filter that provides the subjective point of view of its characters, by observing the personalities and the relationships between those characters.
Effects of various raw ingredients on bread quality

The purpose of the current research is to study the mechanisms behind how various raw ingredients affect the quality of bread. The objects of the research were the flour used in making the bread (consisting of gluten at 28.5%, and with an ash content of 0.55), with no added fats; tap water or activated water (treated in a USTA-0.4/22 OM ultrasonic processor (Volna, Russia), operating at a frequency of 22 ± 1.65 kHz and at 30% of maximum output power (400W) for mixing dough); and plant extract additives based on stevioside and fucoidan (fully replacing the sugar). Included in the analysis were the effects of using activated water and combined plant extract additives on organoleptic qualities (appearance, crust colour, crumb condition, taste, stickiness during mastication, and friability), as well as the physical and chemical qualities (moisture content, porosity, and acidity). Yeast activity was studied in dough which had been produced using activated water and combined plant extract additives. An Altami-136T optical microscope (Altami, Russia) was used to study the activity of yeast cells. The effects of activated water and combined plant extract additives were analysed by examining the microstructure. Microscopic studies were carried out using a Jeol JEM-2100 electron microscope (Jeol Ltd, Japan). The results confirm that activated water and combined plant extract additives may be used to improve the quality of fresh bread.
Increased lymphocyte sister chromatid exchange frequency in workers with exposure to low level of ethylene dichloride

The genotoxicity of low-level exposure to ethylene dichloride (EDC) and vinyl chloride monomer (VCM) in humans is not clear. We used lymphocyte sister chromatid exchange (SCE) frequency as a parameter to investigate the genotoxicity of low level EDC and VCM in VCM-manufacturing workers. The SCE frequency was determined for 51 male workers with exposure to VCM and/or EDC and for 20 male workers devoid of such exposure. Epidemiological data were obtained by questionnaire, and included history of smoking, drinking, and any medication taken, as well as a detailed occupational history. Personaland area-sampling and analysis were conducted in order to calculate the time-weighted average (TWA) contaminant-exposure level corresponding to different job categories. Moderate EDC exposure around 1 ppm corresponded to a significantly greater SCE frequency than was the case for the low EDC exposure group ( p<0.01). However, VCM exposure of similar level was not associated with increased SCE. We conclude that EDC may cause genotoxicity at a relatively low level of exposure. © 2000 Elsevier Science B.V. All rights reserved.
Effect of Rank Placement on Cray XC 30 Communication Cost

The newly released Cray XC30 supercomputer boasts the new Aries interconnect that incorporates a Dragonfly network topology. This hierarchical network topology has obvious advantages with respect to local communication. However, as communication patterns extend further down the hierarchy and grow more separated the overall impact of particular bottlenecks and trade-offs between bandwidth and latency become less apparent. In particular, applications may be more or less latency sensitive based on their communication pattern. The dynamic routing options, as a result, may affect some applications more severely than others. In this paper, we investigate the effect of process placement on the communication costs associated with typical communication patterns shared by many scientific applications. Observations concerning the communication performance of benchmarks and selected applications are presented and discussed. Keywords-Performance; Benchmarking; Computer architecture
Pre-and Postoperative Evaluation of the Effect of Atrial Septal Defect on Systemic Circulation Via Pulse Wave Velocity

321 Erciyes Med J 2019; 41(3): 321–6. • DOI: 10.14744/etd.2019. 06888 ORIGINAL ARTICLE – OPEN ACCESS This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. Şaban Keleşoğlu , Deniz Elçik , Aydın Tuncay , Ali Doğan , Mustafa Fehmi Bireciklioğlu , Zeki Çetinkaya , M. Tuğrul İnanç , Nihat Kalay , Ramazan Topsakal , Abdurrahman Oguzhan Preand Postoperative Evaluation of the Effect of Atrial Septal Defect on Systemic Circulation Via Pulse Wave Velocity Objective: The aim of the present study was to examine whether endothelial function is affected in patients with atrial septal defect (ASD) of secundum type and to determine the changes that might occur in endothelial function after the defect was closed by the transcatheter method by using the pulse wave velocity (PWV) technique. Materials and Methods: A total of 54 patients with ASD type and 40 healthy individuals were included in the study. All patients underwent transthoracic echocardiography and PWV measurements to evaluate the endothelial function prior to and 1 month after the closure procedure. Results: PWV values were significantly higher in patients with ASD than in healthy subjects (7.5±1.2 m/s vs. 6.1±1.0 m/s, p<0.001). Systolic pulmonary arterial pressure (PAP), right ventricular diameter, and PWV values were significantly lower at 1 month of follow-up after the procedure than at baseline (p<0.001). However left ventricular ejection fraction, left ventricular end-diastolic diameter (LVEDD), and tricuspid annular plane systolic excursion values increased significantly after the procedure component (p<0.001, p=0.002, and p<0.001, respectively). Conclusion: It was observed that following closure of the ASD by the transcatheter route, the PWV values were significantly reduced in the right cardiac chambers, and the systolic PAP was improved. This result has shown us that ASD closure may benefit from endothelial dysfunction.
A Model of Granular Tribocharging for Dielectric Mixtures with Continuous Size Distributions

Triboelectric charging, the phenomenon by which electrical charge accumulates during contact between two surfaces, has been known to cause significant charge separation in granular mixtures, even between chemically identical grains. This charging is a stochastic size-dependent process resulting from random collisions between grains. The prevailing models and experimental results suggest that, in most cases larger grains in a mixture acquire a positive charge, while smaller grains charge negatively. These models, and the experiments that use them, are typically restricted to mixtures of two discrete grain sizes, which are not representative of most naturally-occurring granular mixtures. We have developed a new model that predicts the average charge distribution in a granular mixture of any continuous size distribution. Expanding to continuous size distributions enables the prediction of charge separation in many natural granular phenomena, including terrestrial dust storms and mass wasting on the Moon and Mars. Furthermore, the expanded model makes new predictions about the charge distribution, including specific conditions under which the usual sizedependent polarity is reversed. We will also discuss experiments that are planned to test the grain charging predicted by our model.
The Role of Musical Experience in the Perceptual Weighting of Acoustic Cues for the Obstruent Coda Voicing Contrast in American English

This study examines the role of musical experience on listeners’ phoneme judgments across noise conditions. Individuals with 10+ years of musical training were compared with nonmusicians in their use of three acoustic cues in categorizing post-vocalic obstruent voicing: fundamental frequency, vowel duration, and spectral composition in two listening conditions (silence and multitalker babble, MTB). Results demonstrate that musicians display steeper phonemic categorization for coda /t/ and /d/ on the basis of all three cues of interest. Additionally, musicians and nonmusicians show different cue weighting patterns in MTB than in silence. The findings are discussed with reference to their implications for theories of experience-driven plasticity and individual differences in the perceptual organization of phonemes.
Regulation and role of endoglin in cholesterol-induced endothelial / vascular dysfunction in vivo and in vitro

1 Charles University, Faculty of Pharmacy in Hradec Kralove, Department of Biological and Medical Sciences, Hradec Kralove, Czech Republic 2 Charles University, Faculty of Medicine in Hradec Kralove, Department of Medical Biochemistry, Hradec Kralove, Czech Republic 3 Charles University, Faculty of Pharmacy in Hradec Kralove, Department of Biochemical Sciences, Hradec Kralove, Czech Republic 4 Jagiellonian Centre for Experimental Therapeutics (JCET), Bobrzynskiego 14, 30-348, Krakow, Poland 5 Center for Biological Research, Spanish National Research Council (CSIC) and Biomedical Research Networking Center on Rare Diseases (CIBERER), Madrid, Spain
Towards Understanding of Deep Learning in Profiled Side-Channel Analysis

Side-channel attacks (SCA) aim to extract a secret cryptographic key from a device, based on unintended leakage. Profiled attacks are the most powerful SCAs, as they assume the attacker has a perfect copy of the target device under his control. In recent years, machine learning (ML) and deep learning (DL) techniques have become popular as profiling tools in SCA. Still, there are many settings for which their performance is far from expected. In such occasions, it is very important to understand the difficulty of the problem and the behavior of the learning algorithm. To that end, one needs to investigate not only the performance of machine learning but also to provide insights into its explainability. In this work, we look at various ways to explain the behavior of ML and DL techniques. We study the bias–variance decomposition, where the predictive error in various scenarios is split in bias, variance and noise. While the results shed some light on the underlying difficulty of the problem, existing decompositions are not tuned for SCA. We propose the Guessing Entropy (GE) bias–variance decomposition, incorporating the domain-specific GE metric in a tool to analyze attack characteristics. Additionally, we show the relation between the mean squared error and guessing entropy. Our experiments show this decomposition is a useful tool in trade-offs such as model complexity. To dive deeper into the inner representations of neural networks (NNs), we use Singular Vector Canonical Correlation Analysis (SVCCA) to compare models used in SCA. We find that different datasets, or even leakage models, are represented very differently by neural networks. We apply SVCCA to a recent portability study, which shows one should be careful to overtrain their networks with too much data. Finally, do we even need complicated neural networks to conduct an efficient attack? We demonstrate that a small network can perform much better by mimicking the outputs of a large network, compared to learning from the original dataset.
Environmental Aspects of Tunnel Ventilation

A comprehensive methodology for computing the dispersion of air pollutants and immission levels for road tunnels is described. It is based on the combined use of a socalled Gaussian model and a three-dimensional simulation package. The combined model allows for a detailed analysis of very complex configurations, in particular within urban environments. A series of simulations carried out for Munich’s ring road (“Mittlerer Ring”) are used to illustrate the methodology and the results.
Algebraic Neural Architecture Representation, Evolutionary Neural Architecture Search, and Novelty Search in Deep Reinforcement Learning

Evolutionary algorithms have recently re-emerged as powerful tools for machine learning and artificial intelligence, especially when combined with advances in deep learning developed over the last decade. In contrast to the use of fixed architectures and rigid learning algorithms, we leveraged the open-endedness of evolutionary algorithms to make both theoretical and methodological contributions to deep reinforcement learning. This thesis explores and develops two major areas at the intersection of evolutionary algorithms and deep reinforcement learning: generative network architectures and behaviour-based optimization. Over three distinct contributions, both theoretical and experimental methods were applied to deliver a novel mathematical framework and experimental method for generative, modular neural network architecture search for reinforcement learning, and a generalized formulation of a behaviourbased optimization framework for reinforcement learning called novelty search. Experimental results indicate that both alternative, behaviour-based optimization and neural architecture search can each be used to improve learning in the popular Atari 2600 benchmark compared to DQN — a popular gradient-based method. These results are in-line with related work demonstrating that strictly gradient-free methods are competitive with gradient-based reinforcement learning. These contributions, together with other successful combinations of evolutionary algorithms and deep learning, demonstrate that alternative architectures and learning algorithms to those conventionally used in deep learning should be seriously investigated in an e↵ort to drive progress in artificial intelligence.
Environmental Standards and Trade: Evidence from a Natural Experiment∗

Exploiting a natural experiment involving the imposition of technical regulations on the Indian leather and textile industries, I use a firm-level dataset to study the trade, adaptation and discontinuity effects and how they vary by firm size. I find (a) evidence of a signalling effect —regulation significantly increases the exports of a firm through the use of new technology and high quality imported raw materials; (b) this gain is highest for the upper-middle and big size cohort of the firm distribution, i.e., in the 3rd and 4th quartile; (c) use of high-quality raw materials (both imported and domestic) and productivity significantly account for low exit probabilities of a firm; and (d) evidence of spillover effects, i.e., product innovation in case of the upstream (chemical) firms.
Hyperbolic discounting and growth : On the resolution of time inconsistency under continuous time

With a continuous-time, deterministic AK model, we consider the time-consistent intertemporal equilibrium with present-biased hyperbolic discounting (HD) in the absence of commitment. Building on Barro’s (1999) analysis of a ‘sophisticated’ short-termist, greater short-termism decreases the steady-state growth rate, while it increases the interest rate-growth rate wedge and the consumptioncapital ratio. Building on Antinolfi, Keister and Shell (2001), dynamically, as the interest rate fluctuates over the business cycle, a greater short-termism also causes the predicted consumptionoutput ratio to be more procyclical and volatile, thus helping to resolve the ‘consumption-output puzzle’. In addition, in the transitional dynamics, greater HD-related short-termism causes a lower steady state capital stock, a levels effect in addition to the steady-state growth rate effect. We show that on the whole all these effects are only present or at least more pronounced under HD than present value-equivalent exponential discounting.
ELECTROPHYSIOLOGICAL CORRELATES OF PROSODIC BOUNDARIES AT DIFFERENT LEVELS IN BRAZILIAN PORTUGUESE

In tasks involving spoken language comprehension, prosodic cues serve as a guide to correct linguistic processing. In a statement, for instance, a set of prosodic cues is used to segment and organize speech into intonational phrases (IP) and phonological utterances (U). Though these two highest prosodic constituents are delimited by the same set of cues, their respective boundaries coincide with different syntactic boundaries. The present study investigated phonetic differences between boundaries associated with these constituents and aimed to provide evidence of detection of these differences by way of an ERP experiment examining Closure Positive Shifts (CPS). The results revealed prosodic cue differences between IP and U boundaries, as reflected in acoustic parameters. CPSs were elicited in response to processing of these boundaries that were modulated as a function of the prosodic cue differences between them. This result is further evidence that, in speech comprehension, listeners are sensitive to prosodic cues.
DO FIIS IMPACT VOLATILITY OF INDIAN STOCK MARKET ?

The Foreign Institutional Investors (FIIs) have emerged as noteworthy players in the Indian stock market and their growing contribution adds as an important feature of the development of stock markets in India. To facilitate foreign capital flows, developing countries have been advised to strengthen their stock markets. As a result, the Indian Stock Markets have reached new heights and became more volatile making the researches work in this dimension of establishing the link between FIIs and Stock Market volatility. Hence, it‟s an interesting topic to ascertain the role of FIIs in Indian Capital Markets. This paper makes an attempt to develop an understanding of the dynamics of the trading behaviour of FIIs and effect on the Indian equity market. The study is conducted using daily data on BSE Sensex and FII activity over a period of 10 years spanning from 01 st Jan 2001 to 31 st Dec 2011. It provides the evidence of significant positive correlation between FII activity and effects on Indian Capital Market. The analysis also finds that the movements in the Indian Capital Market are fairly explained by the FII net inflows.
Determinants of academic achievements in university students : a cross-sectional study in the Gaza Strip

This study explored the factors that influence academic performance of medical and science students from two universities in the Gaza Strip, Palestine using a validated pilot-tested electronic questionnaire. The amount of studying hours, English proficiency and class attendance had a significant positive impact on academic performance. However, time spent on watching television, social networking and extra-curricular activities had no negative impact. Therefore, balancing study time with extracurricular activities, including social media use, is possible for high achieving students. Another factor with significant negative impact on academic performance, was responsibility for household work, mainly reported by female participants. This might remain one important factor, preventing women from excelling in the academic field and outperforming their male counterparts already early in their careers, especially in societies where women value early marriage and large families. Further research should look into the influence of the type of social media usage on academic performance.
At arm’s length: competing and complementary mechanisms

Three experiments utilised video stimuli, showing an agent presenting objects in a behavioural stimulus-response compatibility paradigm, implicitly measuring responses to the agent’s wrist orientation and hand of presentation. A vertical wrist orientation might cue a complementary action response in an ecological setting, thus testing spatial congruence against interactive and imitative responses. In experiment 1, there was a significant main effect of the actor’s arm, (p ( p Normal 0 false false false EN-GB ZH-CN AR-SA /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:. 0001pt; text-align:justify; mso-pagination:widow-orphan; font-size:10.0pt; mso-bidi-font-size:11.0pt; font-family:"Tahoma","sans-serif"; mso-bidi-font-family:Arial; mso-bidi-theme-font:minor-bidi; mso-fareast-language:EN-US;}
Measuring the Cost of a Tariff War: A Sufficient Statistics Approach

Tariff wars have attracted renewed interest, but measuring the prospective cost of a full-fledged tariff war remains a computationally burdensome task. Consequently, most studies on this topic are confined to a small set of countries and overlook input-output linkages. This paper develops a new methodology that measures the prospective cost of a full-fledged tariff war in one simple step, as a function of (a) observable trade values, (b) inputoutput shares, (c) industry-level trade elasticities, and (d) markup wedges. Applying this methodology to data on 44 economies and 56 industries, I find that (i) the prospective cost of a tariff war to global GDP has more-thandoubled over the past fifteen years, with small downstream economies being the most vulnerable. Moreover, (ii) many countries can lose significantly from a US-China tariff war even if they are not directly involved.
Intel Far-Field Speaker Recognition System for VOiCES Challenge 2019

This paper describes Intel’s speaker recognition systems for the VOiCES from a Distance Challenge 2019. Our submission consists of a Resnet50, and four Xvector systems trained with different data augmentation and input features. Our novel contributions include the use of additive margin softmax loss function and the use of invariant representation learning for some of our systems. To our knowledge, this has not been proposed for speaker recognition. We found that such complementary subsystems greatly improved the performance on the development set by late fusion on score level based on linear logistic regression. After fusion our system achieved on the development set EER, minDCF and actDCF of 2.2%, 0.27 and 0.27; and on the evaluation set 6.08%, 0.451 and 0.458, respectively. We discuss our results and give some insight on accuracy with respect to recording distance.