Miracle-dz/UniFAR-FTUs huggingface dataset:
The Processing of Malformed Formulaic Language

The prevalence of formulaicity in naturally occurring language use points to an important role in the way language is acquired, processed, and used. It is widely recommended that second-language instruction should ensure that learners develop a rich repertoire of formulaic sequences. If this is justified, it follows that learner failure to use formulaic sequences should present some barrier to communication. However, it seems that few researchers have sought to objectively evaluate how learner deviations from the target-language (formulaic or otherwise) impact on online processing. Operationalizing formulaic sequence through collocation, this article reports the combination of corpus-based approaches and psycholinguistic experimentation to investigate the processing by native speakers of learner collocations that deviate from target-language norms. Results show that such deviations are associated with an increased and sustained processing burden. These findings support the widely asserted claim that formulaic sequences offer processing advantages and provide empirical support for the importance of formulaic sequences in language learning. Usage-based models form the basis for some hypotheses concerning cognitive processes that underlie the increase in processing demands.
The global distribution of magnetic helicity in the solar corona

By defining an appropriate field line helicity, we apply the powerful concept of magnetic helicity to the problem of global magnetic field evolution in the Sun's corona. As an ideal-magnetohydrodynamic invariant, the field line helicity is a meaningful measure of how magnetic helicity is distributed within the coronal volume. It may be interpreted, for each magnetic field line, as a magnetic flux linking with that field line. Using magneto-frictional simulations, we investigate how field line helicity evolves in the non-potential corona as a result of shearing by large-scale motions on the solar surface. On open magnetic field lines, the helicity injected by the Sun is largely output to the solar wind, provided that the coronal relaxation is sufficiently fast. But on closed magnetic field lines, helicity is able to build up. We find that the field line helicity is non-uniformly distributed, and is highly concentrated in twisted magnetic flux ropes. Eruption of these flux ropes is shown to lead to sudden bursts of helicity output, in contrast to the steady flux along the open magnetic field lines.
The relation between radio flux density and ionizing ultra-violet flux for HII regions and supernova remnants in the Large Magellanic cloud

We present a comparison between the Parkes radio surveys (Filipovic et al 1995) and Vacuum Ultra-Violet (VUV) surveys (Smith et al. 1987) of the Large Magellanic Clouds (LMC). We have found 72 sources in common in the LMC which are known HII regions (52) and supernova remnants (SNRs) (19). Some of these radio sources are associated with two or more UV stellar associations. A comparison of the radio flux densities and ionizing UV flux for HII regions shows a very good correlation, as expected from theory. Many of the Magellanic Clouds (MCs) SNRs are embedded in HII regions, so there is also a relation between radio and UV which we attribute to the surrounding HII regions.
A Comparative Analysis Of The Impact Of Corporate Taxation On Company’s Reserve and Dividend Policy In Nigeria: 2000-2011

This study critically examines the different selected sectors of the Nigerian Stock Market transaction profile to study the impact of corporate taxation on company’s reserves and dividends in Nigeria covering thirty five (35) companies drawn across seven (7) sectors for a period of 12 years (2000-2011). The variables of interest are: Aggregate Cumulative Total Dividend Payment (ACTDPT) dependent variable, and Aggregate Cumulative Total Cooperate Tax (ACTCPT), Aggregate Cumulative Total Earning per Share (ACTEPS) and Aggregate Cumulative Total Retained Earnings Per Share (ACTRES) independent variables. Ordinary Least Squares Estimation (OLSE), Coefficient of Variability (CV), Granger Causality and Autocorrelation Function/Partial Autocorrelation Function (ACF/PACF) were the different tests from E-view 4.1 and Microfit 4.0 models used to evaluate the sectoral data to determine the comparative impact. The empirical results from the OLS revealed varying degree of directional and magnitude response from ACTCPT, ACTRES, and ACTEPS to the ACTDPT for the seven sectors. The measure of dispersion using coefficient of variability approach shows that by virtual of performance ranking of the sectors, banking has the highest performance of sectors in terms of dividend policy and its impact on corporate taxation on company’s reserve in the last decade, followed by the banking, breweries petroleum and marketing, conglomerates, insurance, construction and allied, and food and beverages. The findings from the Granger Causality effect shows that there is no causality effect, no runs relationship, neither short run or long run and it is not significant at all. This implies that the implementation of corporate tax in Nigeria does not affect the payment policy among the various quoted companies under the stock exchange. Findings recommend implementation of ongoing restructuring policy on the sectors performance so as to increase the Aggregate Cumulative Total Cooperate Tax (ACTCPT), Aggregate Cumulative Total Earning Per Share (ACTEPS) and Aggregate Cumulative Total Return Earning Per Share (ACTRES) thereby improving the Aggregate Cumulative Total Dividend Payment Policy (ACTDPT) in Nigeria among the identified non performing sectors. Keywords: Cumulative, Sectors, Performance, CV, Dividend Policy, significant, Cumulative
Estimating potentials of renewable energy technologies using GIS analytics and social survey data on public acceptance – A working paper

This working paper first will explore how social-survey data on social acceptance of windpower can be integrated in GIS analytics to estimate renewable energy technology potentials. While first attempts have been made to couple public acceptance data with other parameters using GIS, our research effort stands out by offering a first exploration of how to combine bottom-up actual public acceptance data for specific areas, rather than proxies, with relevant GIS-based parameters. Following a visual exploration of plotted spatially referenced social acceptance data we outline some of the insights that can be generated from the possibilities of GIS-analyses and georeferenced social survey data. After presenting a first set of limited results the discussion then moves to discuss more intricate analyses using GIS and their theoretical foundation in the social acceptance and environmental psychology literature.
Prevalence and Factor Related to Ritalin Abuse among Iranian Medical College Student: An Application of Theory of Planned Behavior

Ritalin is a derivative structurally related to amphetamine and with known abuse potential; the aim of this study was determined of prevalence and factor related to Ritalin abuse among college students based on theory of planned behavior. This cross sectional study was carried out on 385 college students of Kermanshah University of medical sciences which recruited with a random sampling method. The datagathering tool consisted of a questionnaire based on the TPB. Data analyze by SPSS-16. Almost 5.4% of the participants last one Ritalin abuse in lifetime. Able to concentrate better while studying most reason to Ritalin abuse. The TPB variable, accounted for 21% of the variation in the outcome measure of the intention to Ritalin abuse. The best predictor for Ritalin abuse was attitude with odds ratio estimate of 1.485 [95% CI: 1.304, 1.692]. Based on our result, it seems that designing and implementation of educational programs to increase negative attitude toward Ritalin abuse may be usefulness of the results in order to prevent of Ritalin abuse.
Étude de MutS à l'échelle de la molécule unique

Par micromanipulation et mesure de force sur molecule unique, avec un piege magnetique, ce travail a porte en partie sur l'etude du systeme de reparation « a longue distance » de l'ADN. Cette reparation fait intervenir pour son initiation les proteines MutS, MutL, et MutH et utilise un mecanisme non identifie precisement, qui lui permet d'agir a distance, entre un site de mesappariement de l'ADN (du par exemple a une erreur de replication), et un site proximal distant (hemi-methylation de sequence GATC), ce qui permet de diriger la reparation sur le brin neosynthetise. Certains modeles de l'action de la proteine MutS font intervenir une boucle dans l'ADN. Nous avons cherche a mettre en evidence une telle action sur un ADN double brin, contenant (ou ne contenant pas) un mesappariement. Nous n'avons pas mis en evidence de formation de boucle par MutS, qui soit specifiquement liee a la presence d'un mesappariement. Ce resultat negatif semble donc exclure ce modele de boucle specifique. Dans une deuxieme partie, nous avons effectue des experiences de micromanipulation sur une jonction de Holliday (ADN en forme de croix, intermediaire de recombinaison). Nous avons montre directement qu'il est possible d'extruder une jonction de Holliday, en sous-enroulant mecaniquement une molecule d'ADN comportant une sequence palindromique, et avons aussi deduit de ces experiences une mesure du pas de l'helice de l'ADN. Dans une derniere partie, nous avons etudie l'influence du bromure d'ethidium sur l'ADN. Nous avons montre que la presence de cet agent intercalant peut induire une attraction non-specifique, intra- ou inter- simple brins d'ADN.
Prédiction de suites individuelles et cadre statistique classique : étude de quelques liens autour de la régression parcimonieuse et des techniques d'agrégation

Cette these s'inscrit dans le domaine de l'apprentissage statistique. Le cadre principal est celui de la prevision de suites deterministes arbitraires (ou suites individuelles), qui recouvre des problemes d'apprentissage sequentiel ou l'on ne peut ou ne veut pas faire d'hypotheses de stochasticite sur la suite des donnees a prevoir. Cela conduit a des methodes tres robustes. Dans ces travaux, on etudie quelques liens etroits entre la theorie de la prevision de suites individuelles et le cadre statistique classique, notamment le modele de regression avec design aleatoire ou fixe, ou les donnees sont modelisees de facon stochastique. Les apports entre ces deux cadres sont mutuels : certaines methodes statistiques peuvent etre adaptees au cadre sequentiel pour beneficier de garanties deterministes ; reciproquement, des techniques de suites individuelles permettent de calibrer automatiquement des methodes statistiques pour obtenir des bornes adaptatives en la variance du bruit. On etudie de tels liens sur plusieurs problemes voisins : la regression lineaire sequentielle parcimonieuse en grande dimension (avec application au cadre stochastique), la regression lineaire sequentielle sur des boules L1, et l'agregation de modeles non lineaires dans un cadre de selection de modeles (regression avec design fixe). Enfin, des techniques stochastiques sont utilisees et developpees pour determiner les vitesses minimax de divers criteres de performance sequentielle (regrets interne et swap notamment) en environnement deterministe ou stochastique.
Diagnosis of osteoporosis using cortex mandibular indices based on cortex thickness and morphology in comparison with visual assessment of the cortex

Introduction : Osteoporosis is a common condition causing significant morbidity and mortality. There is some evidence of a correlation between bone mineral density of the mandible and that of the lumbar spine and hip. The ability to accurately detect osteoporosis based on routine dental imaging would allow early diagnosis. The aim of this study was to compare the diagnostic accuracy for low bone mineral density using mandibular radio morphometric indices versus simple visual inspection of the mandibular cortex. Materials and Methods : Four independent investigators evaluated radio morphometric indices (mental index, antigonial index and morphology of the cortex) as well as assigning a rating of thin or normal cortex based on their initial impression on the panoramic radiographs of 49 post menopausal women with decreased bone mineral density and 42 unaffected controls. The sensitivity, specificity and positive predictive value for each index was evaluated. Results : The mental and antegonial index had better sensitivity than specificity and positive predictive value. However the opposite was true for the morphology index and simple visual inspection of cortical thickness. External agreement was moderate to perfect (0.41 -0.93) for cortex morphology, and moderate to substantial (0.49-0.76) for simple visual inspection of cortical thickness but excellent for mandibular and antegonial index (> 0.8). Conclusion : We found that the mandibular cortical thickness is affected in postmenopausal women with low bone mineral density when compared to controls. Furthermore radio morphometric indices and morphology are more accurate in the diagnosis of osteoporosis than simple visual assessment of cortical thickness. Key words : Cortex, Mandible, Osteoporosis, Radiography.
Implementation of DNN-HMM Acoustic Models for Phoneme Recognition

Gaussian Mixture Model-Hidden Markov Models (GMM-HMMs) are the state-of-theart for acoustic modeling in speech recognition. HMMs are used to model the sequential structure and the temporal variability in speech signals. However, GMMs are used to model the local spectral variability in the sound wave at each HMM state. Attempts to use Artificial Neural Networks (ANNs) to substitute GMMs in HMM-based acoustic models led to dismal results for many years. In fact, ANNs could not significantly outperform GMMs due to their shallow architectures. In addition, it was difficult to train networks with many hidden layers on large amount of data using the back-propagation learning algorithm. In recent years, with the establishment of deep learning technique, ANNs with many hidden layers have been reintroduced as an alternative to GMMs in acoustic modeling, and have shown successful results. The deep learning technique consists of a two-phase procedure. First, the ANN is generatively pre-trained using an unsupervised learning algorithm. Then, it is discriminatively fine-tuned using the back-propagation learning algorithm. The generative pre-training intends to initialize the weights of the network for better generalization performance during the discriminative phase. Combining Deep Neural Networks (DNNs) and HMMs within a single hybrid architecture for acoustic modeling have shown promising results in many speech recognition tasks. This thesis aims to empirically confirm the capability of DNNs to outperform GMMs in acoustic modeling. It also provides a systematic procedure to implement DNN-HMM acoustic models for phoneme recognition, including the implementation of a GMM-HMM baseline system. This thesis starts by providing a thorough overview of the fundamentals and background of speech recognition. The thesis then discusses DNN architecture and learning technique. In addition, the problems of GMMs and the advantages of DNNs in acoustic modeling are discussed. Finally, DNN-HMM hybrid acoustic modes for phoneme recognition are implemented. The deployed DNN is generatively pre-trained and finetuned to produce a posterior distribution over the states of mono-phone HMMs. The developed DNN-HMM phoneme recognition system outperform the GMM-HMM baseline on the TIMIT core test set. An in-depth investigation into the major factors behind the success of DNNs is carried out.
TOLL-LIKE RECEPTORS AND THEIR CONTRIBUTION TO INNATE IMMUNITY : FOCUS ON TLR 4 ACTIVATION BY LIPOPOLYSACCHARIDE

Mechanisms of innate immunity are triggered as a result of recognition of evolutionarily conserved structures of microorganisms, named pathogen-associated molecular patterns. Their recognition is mediated by specialized receptors which initiate signalling cascades leading to expression of pro-inflammatory mediators and regulation of acquired immunity. Among several classes of such receptors, Toll-like receptors (TLRs) are extensively studied as they can sense an array of microbial cell wall and membrane components as well as singleand double-stranded RNA and DNA motifs typical for microorganisms. Each TLR consists of a ligand-binding domain containing leucine-rich repeats, a single transmembrane domain and a signalling TIR domain. After ligand binding, TLRs dimerize which facilitates the interaction of their TIR domains with adaptor proteins triggering signalling cascades. TLRs engage four common adaptor proteins, about ten signalling kinases, and a few transcription factors including NFκB, IRF and AP-1. In this review, special attention is paid to TLR4 activated by lipopolysaccharide (LPS), a component of the outer membrane of Gram-negative bacteria, since an exaggerated response to LPS may lead to potentially deadly septic shock. In recent years considerable progress has been made in the understanding of how the cooperation of several proteins, including CD14, TLR4/MD-2 complex and scavenger receptors, modulates the cell response to LPS. These studies have also revealed a dichotomy of signalling pathways triggered by TLR4 which depends on the participation of MyD88 and TRIF adaptor proteins and leads to the expression of genes encoding pro-inflammatory cytokines and type I interferons, respectively. The key event in the TRIF-dependent pathway is the internalization of activated TLR4.
Evolution of Balmer jump selected galaxies in the ALHAMBRA survey

We present a new color-selection technique, based on the Bruzual & Charlot models convolved with the bands of the ALHAMBRA survey, and the redshifted position of the Balmer jump to select star-forming galaxies in the redshift range 0.5 < z < 1.5. These galaxies are dubbed Balmer jump Galaxies BJGs. We apply the iSEDfit Bayesian approach to fit each detailed SED and determine star-formation rate (SFR), stellar mass, age and absolute magnitudes. The mass of the haloes where these samples reside are found via a clustering analysis. Five volume-limited BJG sub-samples with different mean redshifts are found to reside in haloes of median masses $\sim 10^{12.5 \pm 0.2} M_\odot$ slightly increasing toward z=0.5. This increment is similar to numerical simulations results which suggests that we are tracing the evolution of an evolving population of haloes as they grow to reach a mass of $\sim 10^{12.7 \pm 0.1} M_\odot$ at z=0.5. The likely progenitors of our samples at z$\sim$3 are Lyman Break Galaxies, which at z$\sim$2 would evolve into star-forming BzK galaxies, and their descendants in the local Universe are elliptical galaxies.Hence, this allows us to follow the putative evolution of the SFR, stellar mass and age of these galaxies. From z$\sim$1.0 to z$\sim$0.5, the stellar mass of the volume limited BJG samples nearly does not change with redshift, suggesting that major mergers play a minor role on the evolution of these galaxies. The SFR evolution accounts for the small variations of stellar mass, suggesting that star formation and possible minor mergers are the main channels of mass assembly.
Fractional Fourier detection of L\'evy Flights: application to Hamiltonian chaotic trajectories

A signal processing method designed for the detection of linear (coherent) behaviors among random fluctuations is presented. It is dedicated to the study of data recorded from nonlinear physical systems. More precisely the method is suited for signals having chaotic variations and sporadically appearing regular linear patterns, possibly impaired by noise. We use time-frequency techniques and the Fractional Fourier transform in order to make it robust and easily implementable. The method is illustrated with an example of application: the analysis of chaotic trajectories of advected passive particles. The signal has a chaotic behavior and encounter Levy flights (straight lines). The method is able to detect and quantify these ballistic transport regions, even in noisy situations.
Evaluating high-resolution forecasts of atmospheric CO and CO2 from a global prediction system during KORUS-AQ field campaign

Abstract. Accurate and consistent monitoring of anthropogenic combustion is imperative because of its significant health and environmental impacts, especially at city-to-regional scale. Here, we assess the performance of the Copernicus Atmosphere Monitoring Service (CAMS) global prediction system using measurements from aircraft, ground sites, and ships during the Korea-United States Air Quality (KORUS-AQ) field study in May to June 2016. Our evaluation focuses on CAMS CO and CO2 analyses as well as two higher-resolution forecasts (16 and 9 km horizontal resolution) to assess their capability in predicting combustion signatures over east Asia. Our results show a slight overestimation of CAMS CO2 with a mean bias against airborne CO2 measurements of 2.2, 0.7, and 0.3 ppmv for 16 and 9 km CO2 forecasts, and analyses, respectively. The positive CO2 mean bias in the 16 km forecast appears to be consistent across the vertical profile of the measurements. In contrast, we find a moderate underestimation of CAMS CO with an overall bias against airborne CO measurements of −19.2 (16 km), −16.7 (9 km), and −20.7 ppbv (analysis). This negative CO mean bias is mostly seen below 750 hPa for all three forecast/analysis configurations. Despite these biases, CAMS shows a remarkable agreement with observed enhancement ratios of CO with CO2 over the Seoul metropolitan area and over the West (Yellow) Sea, where east Asian outflows were sampled during the study period. More efficient combustion is observed over Seoul (dCO/dCO2=9 ppbv ppmv−1) compared to the West Sea (dCO/dCO2=28 ppbv ppmv−1). This “combustion signature contrast” is consistent with previous studies in these two regions. CAMS captured this difference in enhancement ratios (Seoul: 8–12 ppbv ppmv−1, the West Sea: ∼30 ppbv ppmv−1) regardless of forecast/analysis configurations. The correlation of CAMS CO bias with CO2 bias is relatively high over these two regions (Seoul: 0.64–0.90, the West Sea: ∼0.80) suggesting that the contrast captured by CAMS may be dominated by anthropogenic emission ratios used in CAMS. However, CAMS shows poorer performance in terms of capturing local-to-urban CO and CO2 variability. Along with measurements at ground sites over the Korean Peninsula, CAMS produces too high CO and CO2 concentrations at the surface with steeper vertical gradients (∼0.4 ppmv hPa−1 for CO2 and 3.5 ppbv hPa−1 for CO) in the morning samples than observed (∼0.25 ppmv hPa−1 for CO2 and 1.7 ppbv hPa−1 for CO), suggesting weaker boundary layer mixing in the model. Lastly, we find that the combination of CO analyses (i.e., improved initial condition) and use of finer resolution (9 km vs. 16 km) generally produces better forecasts.