Miracle-dz/UniFAR-FTUs huggingface dataset:
The effect of frequency distribution of language input on the acquisition of English phrasal construction by Chinese EFL learners

This study investigates the effect of frequency distribution(i.e. skewed vs. flatter) in language input on the acquisition of English phrasal construction by Chinese EFL learners. Learning and testing materials are English novel APPROACH constructions. Ninety-two middle students at respective lower- and upper-intermediate proficiency levels have participated in the study. After the data analysis via LMM, the following findings have been yielded:(1) The process of participants' acquisitional pattern of the APPROACH construction is somewhat similar to that of English children. The skewed frequency is significantly more facilitative than the flatter one at the beginning of the constructional learning. (2) Participants' English proficiency appeared to function significantly during constructional learning process, yet they were all more sensitive to the skewed frequency than the flatter one in language input.
Factors that influence Tax Evasion in Australia and Turkey : A Structural Equation Model Study

The tax literature indicates that many factors impact upon and influence tax evasion and noncompliant behavior. In particular it is well documented in the tax literature, that fairness of the tax system (Cowell, 1992), compliance and enforcement (Slemrod 1992) and taxpayer’s morals and ethics (Wenzel, 2003, Murphy, 2004), all play a key role in determining the level of tax evasion. In the economic literature there has been evidence of the factors which have impacted upon economic growth and the well-being of a country’s citizens. These include, the issues of rivalry amongst individuals regarding income levels, over estimation of the benefits of increased consumption and generally a level of inequality in society (Griffith (2004). These later economic factors have also influenced tax evasion behavior.
A Case Study on Non-Visual Pen-Based Interaction with the Numerical Data

A widespread tabular format still poses great problems for screen readers because of diversity and complexity of the cells’ content. How to access the numerical data presented in tabular form in a quick and intuitive way in the absence of visual feedback? We have implemented and assessed the algorithm supporting an exploration of the tabular data in the absence of visual feedback. This algorithm helps to solve the most commonly encountered problems: retrieving the position of extreme values and the target value that can also be linked to the specific content of the virtual table. The performance of 11 blindfolded subjects was evaluated when they used the StickGrip kinesthetic display and when they relied on the Wacom pen and auditory signals. The results of the comparative study are reported.
FONTS True Manifold FONTS Learned Manifold EMNIST Learned Manifold F-MNIST Learned Manifold CelebA

Obtaining deep networks that are robust against adversarial examples and generalize well is an open problem. A recent hypothesis [102, 95] even states that both robust and accurate models are impossible, i.e., adversarial robustness and generalization are conflicting goals. In an effort to clarify the relationship between robustness and generalization, we assume an underlying, low-dimensional data manifold and show that: 1. regular adversarial examples leave the manifold; 2. adversarial examples constrained to the manifold, i.e., on-manifold adversarial examples, exist; 3. on– manifold adversarial examples are generalization errors, and on-manifold adversarial training boosts generalization; 4. regular robustness and generalization are not necessarily contradicting goals. These assumptions imply that both robust and accurate models are possible. However, different models (architectures, training strategies etc.) can exhibit different robustness and generalization characteristics. To confirm our claims, we present extensive experiments on synthetic data (with known manifold) as well as on EMNIST [19], Fashion-MNIST [106] and CelebA [58].
Annual cycles of middle atmosphere temperature trends determined from long-term rocket measurements

The linear trends of the monthly mean temperature at altitudes of 25–75 km were obtained from the weekly atmospheric sounding by meteorological rockets M-100B during 1969–1995 at the Heiss Island (80.6◦N), Volgograd (48.7◦N), Tumba (8.5◦N), and Molodezhnaya (67.7◦S) stations. It is shown that the temperature trend in the mesosphere demonstrates a well pronounced annual behavior but is negative at all latitudes during all seasons. The temperature trend in the stratosphere is positive over the Heiss Island and Volgograd in winter and over the Molodezhnaya station in spring. The data obtained were compared with the results of numerical simulations from the three-dimensional models of global atmospheric circulation under changing concentrations of radiation-active minor gas constituents. Comparison of the observation and model results shows that changes of annual temperature behavior in the middle atmosphere during recent decades (in the most visual way manifested in the occurrence of seasonal positive anomalies of the annual mean negative trend of the temperature in the middle and upper stratosphere) may be a consequence of chemical composition changes and related changes in radiation and dynamical processes in the Earth’s atmosphere. The results obtained are also compared with radiophysical and lidar observations.
From abstract to concrete: some tips to develop an empirical SFC model

The main purpose of this paper is to show how a simple (medium-scale) empirical stock–flow consistent dynamic model can be developed from scratch. Eurostat data and conventional statistical packages (notably EViews, Excel and R) are used. On the theoretical side, the work builds upon the pioneering work of Godley/Lavoie (2007). Sectoral transactions–flow matrices and balance sheets are explicitly modelled and their evolution over time under different scenarios is analysed. On the empirical side, the model draws upon the applied work of Burgess et al. (2016). The case of Italy is considered, but the model can be replicated for other countries. Eurostat annual data (from 1995 to 2016) are used to estimate or calibrate most model parameter values (for example, consumption function and housing investment parameters). Remaining parameters are borrowed from the available literature or taken from a range of realistic values (for example, weight on past errors in agents' expectations). The model is then used to impose and compare alternative scenarios for Italian sectoral financial balances, based on different shocks to government spending.
Solving Ring-LWE over Algebraic Integer Rings

Many cryptographic schemes have been proposed from learning with errors problems over some rings (Ring-LWE). Polynomial time quantum reduction from the approximating Shortest Independent Vectors Problem (SIV Pγ) for fractional ideal lattices in any algebraic number field to the average-case decision Ring-LWE for any modulus over the integer ring in this number field was established in the Peikert-Regev-Stephens-Davidowitz STOC 2017 paper. However the hardness of approximating SIV Ppoly(n) in quantum computing was only a folklore conjecture. In this paper we prove that decision RingLWE for arbitrary number fields can be solved within polynomial time for infinitely many modulus parameters under a suitable bound on widths (with respect to the canonical embedding). We construct some algebraic number fields such that the decision versions of Ring-LWE with parameters in the range of Peikert-Regev-Stephens-Davidowitz K − SIV P to Ring-LWE reduction result can be solved within polynomial time. Our results indicate that approximating SIV Ppoly(n) for fractional ideal lattices in these algebraic number fields can be solved by a polynomial time quantum algorithm.
Entry , markup and unemployment in an estimated DSGE model

How important is the role of endogenous market structure to the fluctuations in unemployment ? Do search and matching frictions in the labor market generate countercyclical markups? We estimate a monetary DSGE model with endogenous firm entry as in Bilbiie et al. (2012) and search and matching friction in the spirit of Mortensen and Pissarides (1994) for the labor market using Bayesian methods. The model is estimated using US data over the period 1992Q3 to 2016Q4. We find that the presence of the net business formation has a key role in jointly determining labor market variables (vacancies, finding rate and the Beveridge Curve). Furthermore, based on a historical and variance decomposition we find that entry shocks contribute to explaining unemployment fluctuations. Finally, we also find that the presence of labor market frictions enhances the counter-cyclical nature of markups.
Injury in Australian female competitive gymnasts : A psych 0 I ogi cal perspective

A nationwide sample of 162 Australian elite andnon-elite competitive female gymnasts was administered aquestionnaire to coIlectpersonal and training data, as well as information about injuries sustained in the previous 12 months. In addition, to assess the role of psychological variables in injury, the subjects were requested to complete measures of Iife stress, competitive anxiety, self-esteem, and locus of control. The sample reported 321 injuries, a rate of 1.98 Injuriesper gymnast (2.36 fartheeIitegymnasts and 1.83 for the non-elite gymnasts). It was found that for the overall sample and for the non-elite gymnasts, life stress was asignificant predictor of injury. For the elite gymnasts, a more internal locus of control significantly predicted injury. The findings indicate the importance of the sports physiotherapist's awareness of the role of stress both as a predisposing factor to injury and also as a variable that should be considered during the rehabiIitation process.
Using a U-Shaped Neural Network for minutiae extraction trained from refined , synthetic fingerprints

Minutiae extraction is an important step for robust fingerprint identification. However, existing minutia extraction algorithms rely on time consuming and fragile image enhancement steps in order to work robustly. We propose a new approach, combining enhancement and extraction into a Convolutional Neural Network (CNN). This network is trained from scratch using synthetic fingerprints. To bridge the gap between synthetic and real fingerprints, refinements are used. Here, an approach based on Generative Adversarial Networks (GANs) is used to generate fingerprints suited for training such a network and improving its matching score on real fingerprints.
Determining the sensitivity of grassland area burned to climate variation in Xilingol, China, with an autoregressive distributed lag approach

We examined the relationship between climate variables and grassland area burned in Xilingol, China, from 2001 to 2014 using an autoregressive distributed lag (ARDL) model, and describe the application of this econometric method to studies of climate influences on wildland fire. We show that there is a stationary linear combination of non-stationary climate time series (cointegration) that can be used to reliably estimate the influence of different climate signals on area burned. Our model shows a strong relationship between maximum temperature and grassland area burned. Mean monthly wind speed and monthly hours of sunlight were also strongly associated with area burned, whereas minimum temperature and precipitation were not. Some climate variables like wind speed had significant immediate effects on area burned, the strength of which varied over the 2001–14 observation period (in econometrics terms, a ‘short-run’ effect). The relationship between temperature and area burned exhibited a steady-state or ‘long-run’ relationship. We analysed three different periods (2001–05, 2006–10 and 2011–14) to illustrate how the effects of climate on area burned vary over time. These results should be helpful in estimating the potential impact of changing climate on the eastern Eurasian Steppe.
Effect of Work-family Role Conflicts on Employees’ Commitment and Organizational Performance: A Study of Aklad Interlink Concept, Nigeria

The commitment of workers in their place of work is some worth dependent on their marital status. Owing to the above statement, this study examines the effect of work-family role on the level of employees’ commitment and organizational performance in AKLAD Interlink concept, Ibadan, Nigeria. The research design adopted was a survey type, based on a population of 1047. A total of 155 employees was subsequently selected using stratified random sampling techniques. A pilot study was performed to test the validity and reliability of the instrument (questionnaire). Consequently, validity and reliability were ascertained and confirmed via face, content, Cronbach alpha, average variance extracted and composite validity. The six (6) hypotheses of the study were tested using both multiple and simple linear regression, and the analysis of variance. The result of the study reveals a significant influence of work-family role conflicts on both employee commitment and organizational performance. In addition, the mediating influence of employees’ commitment in prediction organizational performance as a result of workfamily role conflicts was also validated by our findings. Moreover, work-family role conflict also had significant influence on gender. Lastly, the independent variable (work-family role conflict) also significantly influenced both married and single employees, as well as, the difference between the job commitment of both male and female staff of the organisation. The study therefore concludes that work-family conflicts affect the organizational performance and effectiveness of the organisation. Thus, our study strongly recommended strict adherence to balanced social lives, by organizational leaders and that special attention should be given to gender and marital issues of their employees so as to balance their family-work relationship. This study, therefore, contributes to extant literature, by showing the nexus between work-family conflict and workers commitment and organizational performance. The study also validated the theoretical framework.
Beyond poverty escapes – social mobility in the Global South: A survey article

While social mobility in advanced economies has received extensive scholarly attention, crucial knowledge gaps remain about patterns and drivers of social mobility in the Global South. Addressing intergenerational income, educational and occupational mobility, we presently lack in-depth understanding of the multiple hurdles to more pronounced progress, which go beyond poverty escapes, and are captured by what we describe as moderate and large ascents. Similar knowledge gaps exist for large descents, which raise additional concerns in low income settings. Innovative research requires critical engagement with theory and with methodology and data challenges that deviate notably from those encountered in Western contexts.
Health promotion – post-truth contexts and times

This paper concerns the events that occurred in the span of thirty years – from the 1986 Ottawa Charter for Health Promotion to the 2016 Vienna Declaration supporting it. The purpose, however, is not to discuss the substance of these events, but what should be defined as their context, in particular the political one. The text is divided into two parts relating to both of the documents mentioned, where the content of the message about health promotion formulated at that time is presented, together with the context in which it was created and received, and – briefly – its consequen ces. With reference to the context of the Vienna document, the issue of post-truth era will be discussed in more detail. The analyses devoted to the two parts will include addressing two problems that affect the issues under consideration: the concept of Health in All Policies and the issue of the susceptibility of various social classes to the arguments presented in health promotion programmes.
Evaluation of Wheat ( Triticum aestivum L . ) genotypes for enhanced productivity through identification of Zn-efficient genotypes

The relative zinc (Zn) efficiencies of 20 wheat genotypes were determined by growing them in chelate-buffered hydroponic culture solutions. Zinc efficiency of the test genotypes were determined by comparing their growth in a Zn-deficient solution (2 pM Zn 2+ ) relative to that in a medium containing an adequate concentration of Zn (40 pM Zn 2+ ) and varied between 41to 84%. The results depicted that eight genotypes proved Zn-efficient, 4 medium and 8 inefficient ones. The SD-8006, SD-8012 and SD-669 were the most efficient wheat genotypes with the efficiency of 84, 83, and 76%, respectively; whereas, T21 and T11 were the least efficient genotypes with 41 and 42% efficiency, respectively. All the cultivars accumulated higher concentrations of iron (Fe), copper (Cu), manganese (Mn) and phosphorus (P) at deficient levels of Zn, compared with adequate Zn concentrations. The Zn-inefficient cultivars accumulated higher concentrations of these elements compared to efficient cultivars. Zinc efficiency of these genotypes under field conditions varied between 57 to 96%, which was quite higher than determined in hydroponics study. Zn-efficient genotypes produced 23% higher grain yield and more extracted Zn (38%) compared to Zn-inefficient genotypes.
Further Study on Identifying Anomalous Large-Scale Rainfall Regimes in Phase Space ∗

Using a 40-yr daily precipitation dataset including 134 stations from 1962 to 2001, the large-scale distribution patterns of precipitation anomalies over East China are investigated in the present paper. In the phase space spanned by the first 8 EOFs generated from the 20-day low-pass filtered data, the six rainfall regimes (RRs) are identified by applying a cluster analysis method, namely, the northeastern China regime, Yellow River regime, Qinling Mountain-Huaihe River regime, Yangtze River with its south regime, South China regime, and rainless regime. Analyses show that the new RRs exhibit good persistence and evident physical sense, and excellently represent both of countrywide and regional features, which also demonstrate the inhomogeneity of multi-dimensional phase space. Furthermore, it is more important that the new RRs can describe intraseasonal dynamic characteristics of large-scale rainfall anomalies, which is the most significant difference between the new RRs and the conventional seasonal mean rainfall patterns. On the other hand, the climatic characteristics of daily distributions of the RRs events, as well as the 40-year panorama of the RRs occurring are also investigated, which further document rationality and objectivity of the RRs with intraseasonal variability, and are likely to present more helpful information for short-term climate prediction, compared with other previous classical rainfall patterns.
A Joint Theory of Polarization and Deunionization

Over the past 50 years, the U.S. and several European labor markets have undergone two most incisive developments: job market polarization and deunionization. In this paper, we argue that routine-biased technical change is not only the driving force behind polarization, as prevalently assumed, but that routine-biased technical change is the common driving force behind both deunionization and polarization. In a search and matching framework with endogenous occupational and endogenous union membership choices, we show that the shift in employment and income shares in favor of high-skill and low-skill occupations worsens the bargaining position of unions, which crucially depends on the occupational structure inside a firm. This directly affects the membership choice of workers, who base their decision on the potential union wage premium. The ensuing deunionization provides further incentives for middle-wage workers to switch occupations and thus amplifies both job market polarization and the increasing income inequality.
Flipping the Coin : Applying a Network Approach to Quality of Life

Quality of Life (QoL) research has applied a latent trait approach for over two decades. In this approach, QoL is a latent variable that determines characteristics such as feeling exhausted and the ability to walk or bathe, which themselves are assumed to be independent given the level of QoL. This assumption is problematic in QoL research. For example, it is not logical that the ability to “climb several flights of stairs” and the ability to “climb one flight of stairs” are independent given the level of QoL. In this paper we show that a network approach, in which QoL emerges as a result from a system of causally linked characteristics, provides a fruitful alternative to QoL research. Networks were constructed based on 195 Dutch cancer patients who completed the SF-36 Health Survey. To identify the most central and thus most important items within the network, centrality measures were calculated. Also, causal relations between items were investigated using the inferred causation algorithm. Results show that a network model displays plausible and logical relations between items. The item “did you feel full of pep” was deemed most important. These results do require validation in a larger sample in order to make genuine inferences about the psychological process that is underlying QoL.
A model developed for teaching an adaptive system of recognising cyberattacks among non-uniform queries in information systems

The study presents results aimed at further development of models for intelligent and self-educational systems of recognising abnormalities and cyberattacks in mission-critical information systems (MCIS). It has been proven that the existing systems of cyberdefence still significantly rely on using models and algorithms of recognising cyberattacks, which allow taking into account information about the structure of incoming streams or the attackers’ change of the intensity of queries, the speed of the attack, and the duration of the impulse. A mathematical model has been suggested for the system module of intelligent identification of cyberattacks in heterogeneous flows of queries and network forms of cyberattacks. The model recognises heterogeneous incoming flows of queries and any possible change in the query intensity and other parameters of a targeted cyberattack aimed at a MCIS. Simulation models, which had been created in MATLAB and Simulink, were used to research the dynamics of changes in the states of the subsystem of blocking queries in the process of detecting cyberattacks in a MCIS. The probability of solving the problem of recognising cyberattacks in heterogeneous flows of queries and network forms of cyberattacks is 85–98 %, depending on the type of the cyberattack. The results of the modelling allow selection of ways to counter and neutralize the effects of the impact of such targeted attacks and help analyse more sophisticated cyberattacks. The suggested model of recognising complex cyberattacks if attackers use non-uniform flows of queries is more accurate, by 5–7 %, than the other existing models. The developed simulation models enable a 25–30 % decrease in the setup time for projects of cyberdefence systems, including SIRCA for CIS or MCIS.