Miracle-dz/UniFAR-FTUs huggingface dataset:
Bank Capital and Lending Behaviour: Empirical Evidence for Italy

This paper investigates the existence of cross-sectional differences in the response of lending to monetary policy and GDP shocks owing to a different degree of bank capitalization. The effects on lending of shocks to bank capital that are caused by a specific (higher than 8 per cent) solvency ratio for highly risky banks are also analyzed. The paper adds to the existing literature in three ways. First, it considers a measure of capitalization (the excess capital) that is better able to control for the riskiness of banksi? ½ portfolios than the well-known capital-to-asset ratio. Second, it disentangles the effects of the "bank lending channel" from those of the "bank capital channel" in the case of a monetary shock; it also provides an explanation for asymmetric effects of GDP shocks on lending based on the link between bank capital and risk aversion. Third, it uses a unique dataset of quarterly data for Italian banks over the period 1992-2001; the full coverage of banks and the long sample period helps to overcome some distributional bias detected for other available public datasets. The results indicate that well-capitalized banks can better shield their lending from monetary policy shocks as they have easier access to non-deposit fund-raising consistently with the "bank lending channel" hypothesis. A "bank capital channel" is also detected, with stronger effects for cooperative banks that have a larger maturity mismatch. Capitalization also influences the way banks react to GDP shocks. Again, the credit supply of well-capitalized banks is less pro-cyclical. The introduction of a specific solvency ratio for highly risky banks determines an overall reduction in lending.
Language attrition: The next phase

The study of L1 attrition is currently entering its third decade. However, after twenty years of diligent investigation resulting in numerous theoretical and empirical papers the questions on this topic still greatly outweigh the answers. Findings from individual studies seem to indicate that it cannot even be said with any certainty whether an L1 in which a certain level of proficiency has been reached can ever undergo significant attrition, let alone how or why it might. This chapter will attempt to identify and clarify these issues, in order to establish the starting ground from which the individual papers will proceed. The first section will give a chronological overview of how the field of language attrition has developed over the past two decades, try to identify the concerns and forces that have shaped it, and point out developments and changes. The second section introduces those extralinguistic factors that have been shown to play important roles in attrition. The third section presents an overview of theoretical frameworks within which language attrition studies have been conducted, while the fourth section focuses on questions of research design. The final section is an outline of the structure and contents of this volume.
Rainfall Microstructural Analysis for Microwave Link Networks: Comparison at Equatorial and Subtropical Africa

The quest to understand the variation of rainfall microstructures at subtropical and equatorial regions is vital to rain attenuation studies. In this study, point rainfall datasets obtained at Butare (2 - 36 0 S, 29 - 44 0 E) and Durban (29 - 52 0 S, 30 - 58 0 E), are compared at the re∞ectivity threshold of 38dBZ. Joss-Walvogel (JW) distrometer measurements collected from these two locations represent physical rainfall data from equatorial and subtropical climates respectively. The re∞ectivity threshold enables the classiflcation of rainfall datasets into stratiform and convective (S-C) precipitation regimes. These thresholds, Rth, at Durban and Butare are analysed based on three known rainfall microphysical parameters: rain rate, rainfall Drop Size Distribution (DSD) and radar re∞ectivity. The results from rain rate distributions at the both regions are similar for both stratiform and convective classes. However, the sampled DSDs indicate the dominance of larger rain droplets at Butare compared to observations at Durban, irrespective of the rain classes. In addition, it is found that the re∞ectivity distributions at both regions, under stratiform and convective conditions, are distinct in their probability proflles. The overall S-C analysis implied that the re∞ectivity and DSD proflles at both regions | result in signiflcant variation of predicted speciflc attenuation | at microwave and millimeter band. In comparison with other global locations, it is a-rmed that the S-C transition occurs globally at rain rates between 6mm/h and 13mm/h.
Assessment of PROFIBUS networks using a fault injection framework

Industrial control systems architectures have been evolving to the decentralization of control tasks. This evolution associated with the time-critical nature of these tasks, increases the dependability requirements for one of their most critical components: the communication system. Therefore, this is an important aspect on the control system design which must be properly evaluated. In this paper the dependability of a PROFIBUS network is assessed. By using of a fault injection framework the network operation is disturbed with fault scenarios which are representative of industrial environments. From these experiments, the stability of the PROFIBUS logical ring is analyzed, the main outages causes are identified and their probabilities are obtained
The effect of time elapsed from milking to scoring on udder linear scores and estimation of genetic parameters.

The study was conducted on 51, 154 Holstein primiparous cows. The purpose of the study was to estimate the impact of time elapsed from last milking until scoring on the properties of udder conformation traits (fore udder attachment, rear udder height, rear udder width, udder depth, and central ligament). The purpose was also to consider the benefi ts of including this effect in statistical models for estimation of genetic parameters in dairycattle. A significant (P<0.001) positive linear relationship between scores of udder traits and the time of the scoring was determined. Rear udder height (b = 0.088) and rear udder width (b = 0.091) were affected the most, with the prolongation of time of scoring regarding previous milking. The investigated effect only affected the residual component of variance. Other components of variance did not change considerably when the time from milking to scoring was fi tted into a basic statistical model. Estimated heritabilities ranged from 0.15 to 0.27. Slightly higher estimates of heritabilities for all traits, except for the central ligamentum, were determined when this effect was fi tted into the model. Udder depth was found to be in strong negative genetic correlation with fore udder attachment (r = -0.436). An almost negligible negative genetic correlation between udder depth and rear udder width was determined (r = -0.086). Genetic correlations between all other traits were positive and low to moderate (r = 0.15 - 0.54). The investigated effect did not noticeably affect estimates of genetic correlations between udder conformation traits.
Motion- and aliasing-compensated prediction for hybrid video coding

In order to reduce the bit rate of video signals, the standardized coding techniques apply motion-compensated prediction in combination with transform coding of the prediction error. By mathematical analysis, it is shown that aliasing components are deteriorating the prediction efficiency. In order to compensate the aliasing, two-dimensional (2-D) and three-dimensional interpolation filters are developed. As a result, motion- and aliasing-compensated prediction with 1/4-pel displacement vector resolution and a separable 2-D Wiener interpolation filter provide a coding gain of up to 2 dB when compared to 1/2-pel displacement vector resolution as it is used in H.263 or MPEG-2. An additional coding gain of 1 dB can be obtained with 1/8-pel displacement vector resolution when compared to 1/4-pel displacement vector resolution. In consequence of the significantly improved coding efficiency, a Wiener interpolation filter and 1/4-pel displacement vector resolution is applied in H.264/AVC and in MPEG-4 (advanced simple profile).
Leverage, Beta Estimation, and the Size Effect

A measurement error in beta that arises from changes in leverage during the beta estimation window contributes in explaining the size effect. Simulations of asset returns show that the magnitude of the bias in equity returns is proportional to the stock market-induced changes in leverage. We propose a point-in-time beta that incorporates leverage at the end of the beta estimation window rather than the average leverage during this window. Using the point-in-time beta to compute expected stock returns for historical U.S. data, we document that the size effect is substantially reduced. In contrast to other explanations of the size effect, our approach does not introduce market frictions or additional risk factors.
Shapley Optical Survey – I. Luminosity functions in the supercluster environment

We present the Shapley Optical Survey, a photometric study covering a ∼2-deg 2 region of the Shapley supercluster core at z ∼ 0.05 in two bands (B and R). The galaxy sample is complete to B = 22.5 (>M* + 6, N gal = 16588) and R = 22.0 (>M* + 7, N gal = 28008). The galaxy luminosity function (LF) cannot be described by a single Schechter function due to dips apparent at B ∼ 17.5 (M B ∼ -19.3) and R ∼ 17.0 (M R ∼ -19.8) and the clear upturn in the counts for galaxies fainter than B and R ∼ 18 mag. We find, instead, that the sum of a Gaussian and a Schechter function, for bright and faint galaxies, respectively, is a suitable representation of the data. We study the effects of the environment on the photometric properties of galaxies, deriving the galaxy LFs in three regions selected according to the local galaxy density, and find a marked luminosity segregation, in the sense that the LF faint end is different at more than 3σ confidence level in regions with different densities. In addition, the LFs of red and blue galaxy populations show very different behaviours: while red sequence counts are very similar to those obtained for the global galaxy population, the blue galaxy LFs are well described by a single Schechter function and do not vary with the density. Such large environmentally dependent deviations from a single Schechter function are difficult to produce solely within galaxy merging or suffocation scenarios. Instead the data support the idea that mechanisms related to the cluster environment, such as galaxy harassment or ram-pressure stripping, shape the galaxy LFs by terminating star formation and producing mass-loss in galaxies at ∼M* + 2, a magnitude range where blue late-type spirals used to dominate cluster populations, but are now absent.
Impact of type 1 diabetes mellitus on academic performance

Objective To examine the effect of type 1 diabetes on academic performance. Methods Ethnically Saudi students with type 1 diabetes, and age, sex, ethnicity and socio-economic status-matched nondiabetic control students were recruited from eight schools. Overall academic grades were recorded, based on the scores obtained in written examinations in English, mathematics, physics, chemistry, biology and humanities. Results Students with type 1 diabetes (n = 36) obtained significantly lower academic grades compared with their nondiabetic control classmates (n = 36) (86.58 ± 1.48 vs 90.62 ± 1.36). Conclusions Overall academic performance is significantly lower in students with type 1 diabetes compared with their nondiabetic classmates. This decline in academic performance may be explained by an association between diabetes and cognitive function.
The Impact of Motivational Climate on Dance Students’ Achievement Goals, Trait Anxiety, and Perfectionism

This study examined whether dimensions of the perceived motivational climate in dance institutions could predict dancers’ levels of task and ego orientation, dimensions of trait anxiety, and dimensions of perfectionism. Participants were 181 English dance students (mean age: 18.5 years; SD: 2.0 years) from dance institutions in the United Kingdom. Participants completed surveys assessing their perceptions of the motivational climate, goal orientations for dance, trait anxiety, and perfectionist tendencies. Results of standard multiple regression analyses suggested that certain elements of the motivational climate were significant predictors of the dependent variables. Specifically, perceptions of dimensions of a performance-oriented climate were significant positive predictors of dancers’ ego orientation, elements of cognitive trait anxiety, and elements of neurotic perfectionism. Perceptions of dimensions of a mastery-oriented climate positively predicted dancers’ levels of task orientation. The findings are discussed with regard to the implications for dance pedagogy.
Finiteness results for Hilbert's irreducibility theorem

Soient k un corps de nombres, O k son anneau d'entiers et f(t, X) E k(t)[X] un polynome irreductible. Le theoreme d'irreductibilite de Hilbert fournit une infinite de specialisations entieres t → t ∈ O k telles que f(t,X) reste irreductible. Dans cet article, nous etudions l'ensemble Red f (O k ) des t ∈ O k tels que f(t,X) est reductible. Nous montrons que Red f (O k ) est un ensemble fini sous des hypotheses assez faibles. En particulier, certains de nos enonces generalisent des resultats anterieurs obtenus par des techniques d'approximations diophantiennes. Notre methode est differente. Nous utilisons de la theorie elementaire des groupes, la theorie des valuations et le theoreme de Siegel sur les points entiers des courbes algebriques. En utilisant en fait la generalisation de Siegel-Lang du theoreme de Siegel, la plupart de nos resultats sont valables sur des corps assez generaux. On peut obtenir d'autres resultats en faisant appel a la classification des groupes finis simples. Nous en donnons un apercu dans la derniere section.
Analysis and Design of Moderate Length Regular LDPC Codes with Low Error Floors

The traditional method to estimate code performance in the higher SNR region is to use a sum of the contributions of the most dominant error events to the probability of error. If an ML decoder is used, these events will be minimum distance codewords; the traditional decoder used in LDPC codes, some variant of the message passing algorithm, will introduce non-codeword error events known as trapping sets. For long LDPC codes it is difficult to enumerate all of these dominant error events. A procedure to efficiently find dominant error events by using the regular low-density structure of an LDPC code is presented here. The search method can be adapted to work with LDPC codes of various regular and irregular degree distributions, but is especially suited to a very practical subset of LDPC known as regular {3, 6} codes of moderate block length. We also show how codes with very low error floors can be created by utilizing this search method.
Development of directives in child language: A case study of Czech

Abstract In this article, the longitudinal development of directives in first-language acquisition is described, and examples of the development of directive speech acts in one Czech child from the ages of 2.8 to 4.1 are included. The results show that the child acquires communicative strategies gradually and that he usually prefers one concrete strategy initially, which is later replaced by a new strategy corresponding with the acquisition of morphological categories. The child’s grammatical development is divided into two stages: the stage of protomorphology, when the child acquires basic morphological categories, and the stage of morphology proper / modular morphology, when the child uses a variety of grammatical means. In the stage of morphology proper, pragmatic factors become more influential as the child is no longer limited by a lack of grammatical competence.
Evolving Game Skill-Depth using General Video Game AI agents

Most games have, or can be generalised to have, a number of parameters that may be varied in order to provide instances of games that lead to very different player experiences. The space of possible parameter settings can be seen as a search space, and we can therefore use a Random Mutation Hill Climbing algorithm or other search methods to find the parameter settings that induce the best games. One of the hardest parts of this approach is defining a suitable fitness function. In this paper we explore the possibility of using one of a growing set of General Video Game AI agents to perform automatic play-testing. This enables a very general approach to game evaluation based on estimating the skill-depth of a game. Agent-based play-testing is computationally expensive, so we compare two simple but efficient optimisation algorithms: the Random Mutation Hill-Climber and the Multi-Armed Bandit Random Mutation Hill-Climber. For the test game we use a space-battle game in order to provide a suitable balance between simulation speed and potential skill-depth. Results show that both algorithms are able to rapidly evolve game versions with significant skill-depth, but that choosing a suitable resampling number is essential in order to combat the effects of noise.
Genome-Wide and Gene-Based Association Studies of Anxiety Disorders in European and African American Samples

Anxiety disorders (ADs) are common mental disorders caused by a combination of genetic and environmental factors. Since ADs are highly comorbid with each other, partially due to shared genetic basis, studying AD phenotypes in a coordinated manner may be a powerful strategy for identifying potential genetic loci for ADs. To detect these loci, we performed genome-wide association studies (GWAS) of ADs. In addition, as a complementary approach to single-locus analysis, we also conducted gene- and pathway-based analyses. GWAS data were derived from the control sample of the Molecular Genetics of Schizophrenia (MGS) project (2,540 European American and 849 African American subjects) genotyped on the Affymetrix GeneChip 6.0 array. We applied two phenotypic approaches: (1) categorical case-control comparisons (CC) based upon psychiatric diagnoses, and (2) quantitative phenotypic factor scores (FS) derived from a multivariate analysis combining information across the clinical phenotypes. Linear and logistic models were used to analyse the association with ADs using FS and CC traits, respectively. At the single locus level, no genome-wide significant association was found. A trans-population gene-based meta-analysis across both ethnic subsamples using FS identified three genes (MFAP3L on 4q32.3, NDUFAB1 and PALB2 on 16p12) with genome-wide significance (false discovery rate (FDR] <5%). At the pathway level, several terms such as transcription regulation, cytokine binding, and developmental process were significantly enriched in ADs (FDR <5%). Our approaches studying ADs as quantitative traits and utilizing the full GWAS data may be useful in identifying susceptibility genes and pathways for ADs.
Effectiveness of Haemodiafiltration with Heat Sterilized High-Flux Polyphenylene HF Dialyzer in Reducing Free Light Chains in Patients with Myeloma Cast Nephropathy

Introduction In cases of myeloma cast nephropathy in need of haemodialysis (HD), reduction of free light chains using HD with High-Cut-Off filters (HCO-HD), in combination with chemotherapy, may be associated with better renal recovery. The aim of the present study is to evaluate the effectiveness of haemodiafiltration (HDF) in reducing free light chain levels using a less expensive heat sterilized high-flux polyphenylene HF dialyzer (HF-HDF). Methods In a single-centre prospective cohort study, 327 dialysis sessions were performed using a 2.2 m2 heat sterilized high-flux polyphenylene HF dialyzer (Phylther HF22SD), a small (1.1m2) or large (2.1 m2) high-cut-off (HCO) dialyzer (HCOS and HCOL) in a cohort of 16 patients presenting with dialysis-dependent acute cast nephropathy and elevated free light chains (10 kappa, 6 lambda). The outcomes of the study were the mean reduction ratio (RR) of kappa and lambda, the proportion of treatments with an RR of at least 0.65, albumin loss and the description of patient outcomes. Statistical analysis was performed using linear and logistic regression through generalized estimating equation analysis so as to take into account repeated observation within subjects and adjust for session duration. Results There were no significant differences in the estimated marginal mean of kappa RR, which were respectively 0.67, 0.69 and 0.70 with HCOL-HD, HCOS-HDF and HF-HDF (P = 0.950). The estimated marginal mean of the proportions of treatments with a kappa RR ≥0.65 were 68%, 63% and 71% with HCOL-HD, HCOS-HDF and HF-HDF, respectively (P = 0.913). The estimated marginal mean of lambda RR were higher with HCOL-HDF (0.78), compared to HCOL-HD and HF-HDF (0.62, and 0.61 respectively). The estimated marginal mean proportion of treatments with a lambda RR ≥0.65 were higher with HCOL-HDF (81%), compared to 57% in HF-HDF (P = 0.042). The median albumin loss were 7, 21 and 63 g/session with HF-HDF, HCOL-HD and HCOL-HDF respectively (P = 0.044). Among survivors, 9 out of 10 episodes of acute kidney injuries became dialysis-independent following a median time of renal replacement therapy of 40 days (range 7–181). Conclusion Therefore, in patients with acute dialysis-dependent myeloma cast nephropathy, in addition to chemotherapy, HDF with a heat sterilized high-flux polyphenylene HF dialyzer could offer an alternative to HCO dialysis for extracorporeal kappa reduction with lower albumin loss.
A survey of reinforcement learning in relational domains

Reinforcement learning has developed into a primary approach for learning control strategies for autonomous agents. However, most of the work has focused on the algorithmic aspect, i.e. various ways of computing value functions and policies. Usually the representational aspects were limited to the use of attribute-value or propositional languages to describe states, actions etc. A recent direction - under the general name of relational reinforcement learning - is concerned with upgrading the representation of reinforcement learning methods to the first-order case, being able to speak, reason and learn about objects and relations between objects. This survey aims at presenting an introduction to this new field, starting from the classical reinforcement learning framework. We will describe the main motivations and challenges, and give a comprehensive survey of methods that have been proposed in the literature. The aim is to give a complete survey of the available literature, of the underlying motivations and of the implications if the new methods for learning in large, relational and probabilistic environments.