Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessment of Students’ Higher-level Text Comprehension Skills in Basic School

Text comprehension is a sophisticated process that is influenced by the reader’s cognitive skills, prior knowledge and the type of texts. The aim of the present longitudinal study was to assess the students’ ability to analyse and evaluate the narrative text in Grades 4 and 5. A total of 831 Estonian students were tested in two consecutive years. The results indicated that fewer than half of the students succeeded in analysing and evaluating the contents of the text, while the students’ text comprehension skills in Grade 5 were significantly better than in Grade 4. Students had more difficulties answering the questions that examined their skill of evaluating the text, compared to their ability to analyse the text. This led to the conclusion that teachers should pay more attention to the students’ higher-level cognitive processes and support their text comprehension skills. Keywords: Analysis and evaluation skills; Basic school; Reading; Text comprehension
eWOM in Mobile Social Media : a study about Chinese Wechat use

Drawing upon Theory of Reasoned Action(TRA) and the perspective of the social influence theory(PSI), the paper proposes an integrated model to identify the impacts of tie strength and trust on eWOM and how eWOM constructs (opinion passing and opinion giving) affect purchase intentions via WeChat in China. Structural equation model was employed to confirm the validity of the model. The results reveal the significant influence of tie strength on subjective norm among WeChat users, and equal importance of opinion passing and opinion giving should also be considered in eWOM management. Our findings offer insight to how boosted trust in WeChat encourages engagement in eWOM which ultimately enhances purchase intention. Implications and contributions are discussed.
Tribology of plane strain compression tests on aluminium strip using ToF-SIMS analysis of transfer films

An experimental investigation of the tribology during plane strain compression of aluminium strip using steel tools is described. A formulated lubricant containing ester, and hexadecane containing 0, 0.05 and 0.5% stearic acid, are used as lubricants. The friction factor is measured for a wide variety of process conditions and correlated with surface analysis techniques including ToF-SIMS (time-of-flight secondary ion mass spectroscopy). The roughness of the tool is clearly seen imprinted on the strip, indicating that any hydrodynamic or hydrostatic film separating the tool and strip is very small. With clean tools and longitudinal strip roughness, the friction stress equals the shear yield stress of the metal. For transverse strip roughness, hydrodynamic or hydrostatic effects lead to a reduced friction factor. With these cleaned tools there is no effect of additive concentration. After a small number of indents a transfer film builds up on the tool, leading to a fall in friction factor. The strip takes on a smeared appearance with black lines running in the direction of relative slip between strip and tool. This transfer layer is of a ‘low friction slurry’ type, which is easily wiped-off using tissue paper. The effectiveness of this transfer layer in reducing friction increases with increasing indentation speed and additive concentration. ToF-SIMS analysis shows that this transfer layer contains aluminium and aluminium stearate—the latter being formed specifically by reaction of stearic acid with fresh metal surface formed during deformation. © 2002 Elsevier Science B.V. All rights reserved.
The Informativeness of Customer Order Flow following Macroeconomic Announcements : Evidence from Treasury Futures Markets

We study the effect of macroeconomic announcements on the 30 Year U.S. Treasury Bond futures. Virtually all trading in the 30 Year Treasury is concentrated in the futures (rather than the spot) market. Consistent with earlier studies, we find that (i) the announcement surprise has a significant contemporaneous effect on yields and (ii) customer order flow is significantly more informative on announcement days than on non-announcement days. Based on a unique feature of the data, we identify floor traders who execute customer trades but do not trade for their personal accounts (brokers) and floor traders who trade both for customers and their personal accounts in the same day (dual traders). We find that the customer order flow of dual traders is significantly more informative on announcement than on non-announcement days, but customer order flow of brokers is not. Moreover, dual traders make more profits from personal trading on announcement days compared to locals (i.e. floor traders who only trade for their personal accounts). Finally, we find that a dual trader’s profits on announcement days is significantly and positively correlated with its own customer order flow, even after controlling for market volatility, the degree of competition for customer order flow, and the announcement surprise. We conclude that the aggregate customer order flow following macroeconomic announcements is informative and that this information is profitable to floor traders who observe the order flow. Our results are consistent with the idea that either some customers are better able to interpret public news, or that the correlated trades of uninformed customers result in the aggregate customer order flow being informative.
Effect of structural parameters on the vibrational response of a viscoelastic rectangular plate with clamped ends

A mathematical model for predicting the vibrational response of a non-homogeneous visco-elastic rectangular plate was developed to assist design engineers and researchers. In the presented model, thermally induced vibrations of a four-sided clamped rectangular plate of non-uniform thickness is discussed. Non-homogeneity in the material is characterized exponentially in Poisson’s ratio while temperature variation is considered bi-parabolic. A boundary value fourth order partial differential equation of motion is formulated for the parabolic tapered rectangular plate. Visco-elastic properties of the material are of Kelvin type, and deflection is considered small and linear. This paper focuses on the effects of structural parameters, i.e. thermal gradient, taper constant, aspect ratio, and non-homogeneity constant on the vibrational behaviour of rectangular plates. The Rayleigh–Ritz method is used to obtain results for the time period and deflection for the first two modes of vibration. Comparison of the results of the present paper with others available in the literature is visualized with the help of graphs.
Stability Analysis of On-Policy Imitation Learning Algorithms Using Dynamic Regret

On-policy imitation learning algorithms iteratively improve policies by rolling them out and observing loss functions from expert demonstrations. The theoretical properties of onpolicy imitation learning algorithms are often studied from an online optimization or game-theoretic perspective. Of interest recently are conditions necessary for guaranteeing the stability of these algorithms. To analyze stability, we advocate the need for a dynamic regret analysis, which measures the loss of a policy compared to the best it could have done on its own distribution. Using this notion of regret, we investigate stability conditions for on-policy algorithms. We also show that in the infinite sample case the average dynamic regret rate of follow-the-leader under a stability condition and online gradient descent under slightly stronger conditions tend to zero in the number of iterations.
Corruption and Inequality as Correlates of Social Trust:

I argue that the fairness of a society affects its level of social trust more than does its homogeneity. Societies with fair procedural rules (democracy), fair administration of rules (freedom from corruption), and fair (relatively equal and unskewed) income distribution produce incentives for trustworthy behavior, develop norms of trustworthiness, and enhance interpersonal trust. Based on a multi-level analysis using the World Values Surveys data that cover 80 countries, I find that (1) freedom from corruption, income equality, and mature democracy are positively associated with trust, while ethnic diversity loses significance once these factors are accounted for; (2) corruption and inequality have an adverse impact on norms and perceptions of trustworthiness; (3) the negative effect of inequality on trust is due to the skewness of income rather than its simple heterogeneity; and (4) the negative effect of minority status is greater in more unequal and undemocratic countries, consistent with the fairness explanation.
Visual Saliency Detection and Semantic Segmentation

Visual saliency is the ability to select the most relevant data in the scene and reduce the amount of data that needs to be processed. We propose a novel unsupervised approach to detect visual saliency in videos. For this, we employ a hierarchical segmentation technique to obtain supervoxels of a video, and simultaneously, we build a dictionary from cuboids of the video. Then we create a feature matrix from coefficients of dictionary elements. Next, we decompose this matrix into sparse and redundant parts and obtain salient regions using group lasso. Our experiments provide promising results in terms of predicting eye movement. Moreover, we apply our method on action recognition task and achieve better results. Saliency detection only highlights important regions, in Semantic Segmentation, the aim is to assign a semantic label to each pixel in the image. Even though semantic segmentation can be achieved by simply applying classifiers to each pixel or a region, the results may not be desirable since general context information is not considered. To address this issue, we propose two supervised methods. First, an approach to discover interactions between labels and regions using a sparse estimation of precision matrix obtained by graphical lasso. Second, a knowledge-based method to incorporate dependencies among regions in the image during inference. High-level knowledge rules such as co-occurrenceare extracted from training data and transformed into constraints in Integer Programming formulation. A difficulty in the most supervised semantic segmentation approaches is the lack of enough training data. To address this, a semi supervised learning approach to exploit the plentiful amount of available unlabeled as well as synthetic images generated via Generative Adversarial Networks (GAN) is presented. Furthermore, an extension of the proposed model to use additional weakly labeled data is proposed. We demonstrate our approaches on three challenging bench-marking datasets.
Evaluation of methods for predicting axial capacity of jacked-in and driven piles in cohesive soils

This paper presents the evaluation of methods for predicting the ultimate axial bearing capacity of single piles based on the cone penetration test (CPT) results, and the evaluation of static methods based on the effective and total stress analysis. Seventeen jacked-in MEGA piles and eight Franki piles of different lengths are considered. The results show that the Bustamante & Gianeselli (LCPC) method is the most appropriate for the studied geotechnical conditions and pile types.
REFGOV Reflexive Governance in the Public Interest Institutional Frames for Markets Organizing prisons through public-private partnerships : Evidence from France , Brazil and the United States

In this paper, we analyze the private participation in prison services in three countries: Brazil, France and the United States. We highlight striking differences between these countries and argue that the explanation for these differences requires an understanding of the incentives provided by the distribution of property rights as well as the incentives resulting from other factors like decision and revenue rights distribution and institutions. The theoretical literature normally analyzes these blocks separately. We argue that the main driving factors for efficient arrangements do not rely on one particular element but rather on the way these elements are combined, giving rise to a superior governance structure.
Designing profitable joint product–service channels: case study on tablet and eBook markets

Consumers’ choice of services and the product platforms that deliver them, such as apps and mobile devices, or eBooks and eReaders, are becoming inextricably interrelated. Market viability demands that product–service combinations be compatible across multiple producers and service channels, and that the producers’ profitability must include both service and product design. Some services may be delivered contractually or physically, through a wider range of products than others. Thus, optimization of producers’ contingent products, services, and channel decisions becomes a combined decision problem. This article examines three common product–service design scenarios: exclusive, non-exclusive asymmetric, and non-exclusive symmetric. An enterprise-wide decision framework has been proposed to optimize integrated services and products for each scenario. Optimization results provide guidelines for strategies that are mutually profitable for partner–competitor firms. The article examines an example of an eBook service and tablet, with market-level information from four firms (Amazon, Apple, Barnes & Noble, and Google) and conjoint-based product–service choice data to illustrate the proposed framework using a scalable sequential optimization algorithm. The results suggest that firms in market equilibrium can markedly differ in the services they seek to provide via other firms’ products and demonstrate the interrelationship among marketing, services, and product design.
1 STOCK OPTIONS AND GENDER DIFFERENCES IN RISK TAKING : THE MODERATING ROLE OF CORPORATE HIERARCHY

This paper seeks to take a step forward in addressi ng the influence of stock options on executive risk-taking behavior, considering the mod erating role of the position held in the corporate hierarchy (CEOs compared with non-CEO exe cutives) and the gender of the executive. Using panel data for matched samples of S&P 1500 listed firms between 2006 and 2011, the results confirm an inverted U-shaped rela tionship between the wealth created by executive stock options (ESOs) and risk taking. But this relationship differs between CEOs and non-CEO executives. As executives move up the c orporate hierarchy (from non-CEO executives to CEOs), the maximum wealth at risk at which risk-increasing behavior changes to risk-reducing behavior increases, which supports the higher risk propensity of CEOs caused by their power and level of discretion. Unli ke non-CEO executive positions, the results also show that gender differences in the ES O risk taking effect are strongly present at the level of CEOs due to their greater decision-mak ing freedom to behave according to their respective risk preferences.
The experience of fun with graphic design

This paper argues that fun could be a useful concept in facilitating the interaction between people and graphic design towards effective communication, and attempts to gain a preliminary understanding of the experience of fun with graphic design that could provide designers with insights for experience-oriented graphic design that will inspire in people’s experience of fun. It begins by discussing the concept of fun and the relationship the concept has to graphic design, then presents an empirical study that utilises the combination of the probes and interviews to investigate people’s lived experience of fun in the context of graphic design. The results of the study show that people could experience fun with graphic design by engaging themselves in sensual, emotional and intellectual involvements that are intertwined into a unity of fun. The factors contributing to and influencing the experience of fun with graphic design include: “feeling attracted”, “challenge-achievement”, “out of expectation”, “positive emotions”, “social interaction” and “contextual factors”.
mixtox: An R Package for Mixture Toxicity Assessment

Mixture toxicity assessment is indeed necessary for humans and ecosystems that are continually exposed to a variety of chemical mixtures. This paper describes an R package, called mixtox, which offers a general framework of curve fitting, mixture experimental design, and mixture toxicity prediction for practitioners in toxicology. The unique features of mixtox include: (1) constructing a uniform table for mixture experimental design; and (2) predicting toxicity of a mixture with multiple components based on reference models such as concentration addition, independent action, and generalized concentration addition. We describe the various functions of the package and provide examples to illustrate their use and show the collaboration of mixtox with other existing packages (e.g., drc) in predicting toxicity of chemical mixtures.
Cognitive-motor interaction during virtual reality trail making

There is great interest in ecological virtual reality (VR-) based adaptations of traditional pen-and-paper neuropsychological tests. Such adaptations are designed to measure the same cognitive construct(s) as the original test but may also evaluate interactions between such constructs and other functions (e.g., motor), as occurs in daily life. Here we report on translation of the pen-and-paper Color Trails Test (CTT) to a VR-based head-mount device (HMD) implementation. Trails A is a measure of sustained attention, while Trails B measures divided attention. Participants were twenty-seven young (28.02±3.98 years) and twenty-nine middle-aged (55.41±6.60 years) healthy individuals. For young and middle-aged participants, respectively, mean VR-CTT Trails A completion times were 61.77 and 86.70 sec. Mean VR-CTT Trails B completion times were 113.25 and 154.00 sec, respectively. These completion times were significantly longer than those obtained for the pen-and-paper version (p<.001). The middle-aged group had longer completion times than young adults for both test formats (p<.001), with VR-CTT Trails B separating among the groups better than the corresponding pen-and-paper measure (p<.05). Supporting construct validity, completion times were correlated between pen-and-paper and VR-based versions (Trails A: r=.63; Trails B: r=.60, p’s<.001). VR-CTT motor performance was evaluated by quantifying the deviation of the actual reaching trajectories from the hand trajectories predicted by the minimal jerk model. For both age groups, deviations were greater for Trails B relative to Trails A (p<.001), consistent with a potential effect of divided attention on motor planning and execution. In sum, our VR-based HMD implementation of the CTT assesses similar cognitive constructs to the original pen-and-paper test (construct validity). Further, as suggested by longer completion times and substantial impact of cognitive demands upon motor performance, this VR-CTT affords enhanced ecological validity and added value by capturing cognitive-motor interactions associated with planning and execution of voluntary reaching movements during the task. We believe that such VR-based adaptations lie at the frontier of neuropsychological testing and will ultimately offer novel insights into our understanding of multimodal human function in the real world.
CFD MODELLING OF THE FLOW THROUGH A GRATE-KILN

As part of an investigation regarding secondary reduction of NOx emissions in a grate-kiln iron ore pelletizing plant, the aim of this specific research is to develop a CFD model that enhances the understanding of the aerodynamics and mixing of species inside the rotary kiln. At first, a parametric study of the pure airflow through the kiln is carried out and for certain conditions, a transient behaviour similar to that of vortex shedding was observed, with a dependence on momentum flux ratio between the secondary air jets. Further, the development of a preliminary coal combustion model is set out, which is in need of continued work in order to produce reliable predictions of various parameters relevant to the reduction process. However, the effect of the combustion on the flow field is limited, indicating that the pure airflow model can be used to broadly investigate the influence of the secondary air flow.
Title Potential for international spread of wild poliovirus viatravelers

Background: The endgame of polio eradication is hampered by the international spread of poliovirus via travelers. In response to ongoing importations of poliovirus into polio-free countries, on 5 May 2014, WHO’s Director-General declared the international spread of wild poliovirus a public health emergency of international concern. Our objective was to develop a mathematical model to estimate the international spread of polio infections. Methods: Our model took into account polio endemicity in polio-infected countries, population size, polio immunization coverage rates, infectious period, the asymptomatic-to-symptomatic ratio, and also the probability of a traveler being infectious at the time of travel. We applied our model to three scenarios: (1) number of exportations of both symptomatic and asymptomatic polio infections out of currently polio-infected countries, (2) the risk of spread of poliovirus to Saudi Arabia via Hajj pilgrims, and (3) the importation risk of poliovirus into India. Results: Our model estimated 665 polio exportations (>99 % of which were asymptomatic) from nine polio-infected countries in 2014, of which 78.3 % originated from Pakistan. Our model also estimated 21 importations of poliovirus into Saudi Arabia via Hajj pilgrims and 20 poliovirus infections imported to India in the same year. Conclusion: The extent of importations of asymptomatic and symptomatic polio infections is substantial. For countries that are vulnerable to polio outbreaks due to poor national polio immunization coverage rates, our newly developed model may help guide policy-makers to decide whether imposing an entry requirement in terms of proof of vaccination against polio would be justified.
Computational appearance models for quantitative dermatology

OF THE DISSERTATION Computational Appearance Models for Quantitative Dermatology by Parneet Kaur Dissertation Director: Prof. Kristin Dana Skin appearance modeling using high-resolution imaging has led to advances in recognition, rendering and analysis. In dermatology, workforce shortage and long patient wait time has motivated the need for computational methods to assist the dermatologists. In recent automated image recognition tasks, deep learning with convolutional neural nets (CNN) has achieved remarkable results. However in many clinical settings, training data is often limited and insufficient for CNN training. Furthermore, skin images have subtle differences and are very different from the typical images used for computer vision tasks. This motivates the need of developing methods that can be used for limited and unique datasets. In this research, we propose computational models using deep learning approaches for novel problems in quantitative dermatology. First, we develop a photo-realistic facial style transfer method (FaceTex), which transfers facial texture from a new style image while preserving most of the original facial
Analysis of Determinants Affecting Financial Inclusion in Indonesia

Financial institutions have a role to accelerate economic growth in a regionespecially in developing countries like Indonesia. This study use panel datacovering 22 provinces in Indonesia during the period 2013-2017 assess thebehavior and determinants of financial inclusion in the Indonesia. Increasedpopulation density has a beneficial impact on the deposit penetration. The level ofincome had a positive impact on the deposit penetration means that economicconditions are important to the improvement of financial inclusion. The proportionof the plant and its employees have a positive impact on financial inclusion meansthat income and employment creation or make people more active, aware andinterested in banking activities and contribute to financial inclusion.