Miracle-dz/UniFAR-FTUs huggingface dataset:
The Relationship between Bank Capital, Risk-Taking, and Capital Regulation: A Review of the Literature

Bank capital regulation seems to be today's most accepted regulatory instrument. The reasoning is that limited liability and deposit insurance appear to give banks incentives for excessive risk-taking. Capital requirements can alleviate this problem as banks are obliged to hold more capital which forces them to have more of their own funds at risk. But the theoretical literature has much more to say on how banks determine their capital structure and portfolio risk and how capital regulation influences this decision. This paper attempts to give an overview of the literature in order to see what theory suggests, what empirics seem to tell us, and what there is still to do for future research.
Performance study of classification techniques for phishing URL detection

In the constantly evolving World Wide Web environment, the end-users are subjected to many threats. Phishing is the most relentless of all the attacks. Detection of phishing URLs from genuine ones is a paramount task to minimize the financial loss incurred. By applying pattern recognition capabilities of machine learning to phishing detection domain, we can achieve significant performance improvements. This paper provides a survey of research works conducted on classification techniques by various researchers for phishing URL detection. The experiments were performed using 4,500 URLs and several classification algorithms. The observed results showed that tree-based classifiers provide maximum accuracy.
Abundances In Very Metal-Poor Dwarf Stars

We discuss the detailed composition of 28 extremely metal-poor (EMP) dwarfs, 22 of which are from the Hamburg/ESO Survey (HES), based on Keck echelle spectra. Our sample has a median [Fe/H] of -2.7 dex, extends to -3.5 dex, and is somewhat less metal-poor than was expected from [Fe/H](HK, HES) determined from low-resolution spectra. Our analysis supports the existence of a sharp decline in the distribution of halo stars with metallicity below [Fe/H] = -3.0 dex. So far no additional turnoff stars with [Fe/H] < -3.5 have been identified in our follow-up efforts. For the best-observed elements between Mg and Ni, we find that the abundance ratios appear to have reached a plateau, i.e., [X/Fe] is approximately constant as a function of [Fe/H], except for Cr, Mn, and Co, which show trends of abundance ratios varying with [Fe/H]. These abundance ratios at low metallicity correspond approximately to the yield expected from Type II supernovae (SNe) with a narrow range in mass and explosion parameters; high-mass Type II SN progenitors are required. The dispersion of [X/Fe] about this plateau level is surprisingly small and is still dominated by measurement errors rather than intrinsic scatter. These results place strong constraints on the characteristics of the contributing SNe. The dispersion in neutron-capture elements and the abundance trends for Cr, Mn, and Co are consistent with previous studies of evolved EMP stars. We find halo-like enhancements for the α-elements Mg, Ca, and Ti, but solar Si/Fe ratios for these dwarfs. This contrasts with studies of EMP giant stars, which show Si enhancements similar to other α-elements. Sc/Fe is another case where the results from EMP dwarfs and from EMP giants disagree; our Sc/Fe ratios are enhanced compared to the solar value by ~0.2 dex. Although this conflicts with the solar Sc/Fe values seen in EMP giants, we note that α-like Sc/Fe ratios have been claimed for dwarfs at higher metallicity. Two dwarfs in the sample are carbon stars, while two others have significant C enhancements, all with 12C/13C ~7 and with C/N between 10 and 150. Three of these C-rich stars have large enhancements of the heavy neutron capture elements, including lead, which implies a strong s-process contribution, presumably from binary mass transfer; the fourth shows no excess of Sr or Ba.
Interval arithmetic implementations: using floating point arithmetic

This paper presents some algorithms implementing interval arithmetic using floating point arithmetic. The algorithms apply to almost any digital computer supporting normalized floating point arithmetic and provide better performance than conventional interval arithmetic program libraries. For reasons of generality and machine independence, algorithms are presented in a high-level language. They are intended to be used as an implementation guide for interval arithmetic. This paper outlines the requirements for the algorithms, presents the employed techniques and some of the algorithms, and reports on various performance experiments. A detailled description can be found in a seperate document (Clemmesen [1982]) available at the above address.
Computing the Action of the Matrix Exponential, with an Application to Exponential Integrators

A new algorithm is developed for computing $e^{tA}B$, where $A$ is an $n\times n$ matrix and $B$ is $n\times n_0$ with $n_0 \ll n$. The algorithm works for any $A$, its computational cost is dominated by the formation of products of $A$ with $n\times n_0$ matrices, and the only input parameter is a backward error tolerance. The algorithm can return a single matrix $e^{tA}B$ or a sequence $e^{t_kA}B$ on an equally spaced grid of points $t_k$. It uses the scaling part of the scaling and squaring method together with a truncated Taylor series approximation to the exponential. It determines the amount of scaling and the Taylor degree using the recent analysis of Al-Mohy and Higham [SIAM J. Matrix Anal. Appl. , 31 (2009), pp. 970-989], which provides sharp truncation error bounds expressed in terms of the quantities $\|A^k\|^{1/k}$ for a few values of $k$, where the norms are estimated using a matrix norm estimator. Shifting and balancing are used as preprocessing steps to reduce the cost of the algorithm. Numerical experiments show that the algorithm performs in a numerically stable fashion across a wide range of problems, and analysis of rounding errors and of the conditioning of the problem provides theoretical support. Experimental comparisons with MATLAB codes based on Krylov subspace, Chebyshev polynomial, and Laguerre polynomial methods show the new algorithm to be sometimes much superior in terms of computational cost and accuracy. An important application of the algorithm is to exponential integrators for ordinary differential equations. It is shown that the sums of the form $\sum_{k=0}^p \varphi_k(A)u_k$ that arise in exponential integrators, where the $\varphi_k$ are related to the exponential function, can be expressed in terms of a single exponential of a matrix of dimension $n+p$ built by augmenting $A$ with additional rows and columns, and the algorithm of this paper can therefore be employed.
A Perceptual Aesthetics Measure for 3D Shapes

While the problem of image aesthetics has been well explored, the study of 3D shape aesthetics has focused on specific manually defined features. In this paper, we learn an aesthetics measure for 3D shapes autonomously from raw voxel data and without manually-crafted features by leveraging the strength of deep learning. We collect data from humans on their aesthetics preferences for various 3D shape classes. We take a deep convolutional 3D shape ranking approach to compute a measure that gives an aesthetics score for a 3D shape. We demonstrate our approach with various types of shapes and for applications such as aesthetics-based visualization, search, and scene composition.
A method of remote fault diagnosis based on multilayer SOM

This paper establishes the model of remote fault detect system, using typical fault data of a type of planepsilas undercarriage braking system to implement the diagnosis. The result shows that he Ensemble Method of Remote Fault Diagnosis based on PCA and ICA and Multi-layer SOM, integrates the advantage of PCA in low noise and ICA in high noise. Multilayer SOM can classify the input data rapidly with associative memory and parallel processing. The computing results accord with the actual situation and indicate that the ensemble PCA-ICA-MSOM method has large potential in recognizing remote patterns.
CURRENT DEVELOPMENTS IN READING ABILITIES THROUGH PHONOLOGICAL PROCESSING SKILLS AND PROFICIENCY IN A SECOND LANGUAGE

During the past decades, the way that researchers and educators understand and describe the process of reading has been revolutionised. The present article examines the current developments in reading abilities among second language readers. The developments are further discussed in terms of a theory of general second language proficiency encompassing both oral and written language. Implications on the nature of second language reading, the database in second language reading, text-and knowledge-driven operations in second language reading, and second language reading classroom factors have been provided. Assessment of comprehension is briefly reviewed, and recommendations are provided for theoretical, cultural, and educational implications. An overview of an experimental fluency programme that attempts to address multiple components in the development of reading abilities has also been discussed.
Enrichment textures for detailed cutting of shells

We present a method for simulating highly detailed cutting and fracturing of thin shells using low-resolution simulation meshes. Instead of refining or remeshing the underlying simulation domain to resolve complex cut paths, we adapt the extended finite element method (XFEM) and enrich our approximation by customdesigned basis functions, while keeping the simulation mesh unchanged. The enrichment functions are stored in enrichment textures, which allows for fracture and cutting discontinuities at a resolution much finer than the underlying mesh, similar to image textures for increased visual resolution. Furthermore, we propose harmonic enrichment functions to handle multiple, intersecting, arbitrarily shaped, progressive cuts per element in a simple and unified framework. Our underlying shell simulation is based on discontinuous Galerkin (DG) FEM, which relaxes the restrictive requirement of C1 continuous basis functions and thus allows for simpler, C0 continuous XFEM enrichment functions.
Tying Down Loose Ends in the Chlamydomonas Genome: Functional Significance of Abundant Upstream Open Reading Frames

The Chlamydomonas genome has been sequenced, assembled, and annotated to produce a rich resource for genetics and molecular biology in this well-studied model organism. The annotated genome is very rich in open reading frames upstream of the annotated coding sequence (‘uORFs’): almost three quarters of the assigned transcripts have at least one uORF, and frequently more than one. This is problematic with respect to the standard ‘scanning’ model for eukaryotic translation initiation. These uORFs can be grouped into three classes: class 1, initiating in-frame with the coding sequence (CDS) (thus providing a potential in-frame N-terminal extension); class 2, initiating in the 5′ untranslated sequences (5UT) and terminating out-of-frame in the CDS; and class 3, initiating and terminating within the 5UT. Multiple bioinformatics criteria (including analysis of Kozak consensus sequence agreement and BLASTP comparisons to the closely related Volvox genome, and statistical comparison to cds and to random sequence controls) indicate that of ∼4000 class 1 uORFs, approximately half are likely in vivo translation initiation sites. The proposed resulting N-terminal extensions in many cases will sharply alter the predicted biochemical properties of the encoded proteins. These results suggest significant modifications in ∼2000 of the ∼20,000 transcript models with respect to translation initiation and encoded peptides. In contrast, class 2 uORFs may be subject to purifying selection, and the existent ones (surviving selection) are likely inefficiently translated. Class 3 uORFs are found in more than half of transcripts, frequently multiple times per transcript; however, they are remarkably similar to random sequence expectations with respect to size, number, and composition, and therefore may in most cases be selectively neutral.
A narrative analysis of the stories told by female foreign care workers in Bologna, Italy

This thesis investigates the lived experience of economic migration of eleven female foreign care workers (FCWs) working in Bologna, Italy. The principal aim of the study is to examine how these women construct their experience of migrating through the stories they tell. The methodology involves semi-structured interviews in which participants reflect on the migration process, their motivations for the move and the difficulties they faced once in Italy. The interviews were audio-recorded, transcribed and then analysed. In the first stage of analysis, similarities and differences in the narratives were identified in order to identify common themes. Subsequently, stories told in the interviews were identified. Positioning theory was employed to explore both what was said and the way in which it was said with close attention paid to the interactive nature of the stories and how they relate to wider societal discourses, especially those regarding care workers in Italy. The findings of this study demonstrate that, even though each migration experience is different, the interviewees share awareness of certain discourses regarding both immigration in Italy and care workers in particular. Through positioning theory I demonstrate how the women resist certain negative discourses in order to alternatively position themselves as making agentive career choices. The findings are discussed with reference to the efficacy of this methodological approach and suggestions for future research.
Toxicity Testing of Bensulfuron-Methylto Anabaena azotica

In order to determinate the effect of 10% bensulfuron-methyl wet table powder on growth effects, photosynthetic pigments and antioxidant enzymes activity of Anabaena azotica, a new test of Bensulfuron-methyl to Anabaena azotica based on spectrophotometric method is provided in this paper. The testing results indicate that 10% bensulfuron-methyl in high concentrations (1 mg/l and 10 mg/l) significantly inhibit the growth and photosynthetic pigments of A.azotica, and the change of antioxidant enzyme activity was obvious. Low-dose bensulfuron-methyl application (<; 0.1 mg/1)enables growth of A.azotica as biofertilizer, and its growth rates exhibited wave patterns of different magnitudes.
The face predicts the brain: An investigation of facial morphology associated with autism

Previous studies have indicated that testosterone may be associated with cognitive masculinisation in individuals with autism. Testosterone also exerts masculinising effects on facial morphology. This converging evidence suggests that the facial structures of individuals with autism may be hypermasculinised. While several studies have provided evidence for the hypermasculinisation account, others presented contrasting findings and proposed that physical features of autism should, instead, be characterised as androgynous. The overarching goal of the thesis was to investigate the hypermasculinisation and androgyny accounts of autism in relation to facial masculinity/femininity. To achieve this, three specific aims were formulated and addressed over five studies (Chapters 2 to 6) that employed either groups differing in levels of autistic-like traits or groups with and without Autism Spectrum Disorder (ASD). The first aim was to examine whether facial masculinity/femininity differs among neurotypical men and women with varying levels of autistic-like traits measured using the Autism-spectrum Quotient (AQ). In Chapter 2, we utilised subjective ratings of facial photographs to examine facial masculinity/femininity in highand low-AQ groups. Chapter 3 reports a replication and extension of Chapter 2, with the inclusion of adults with mid-range scores on the AQ. In Chapter 4, we extended our investigations by employing three-dimensional (3D) photogrammetry, objective facial measurements, and computational algorithms to identify sexually dimorphic facial features. Across the three studies, women with higher levels of autistic-like traits were consistently less feminine than women with lower trait levels. As the hypermasculinisation and androgyny accounts generate similar predictions for females (being less feminine [hypermasculinised] is synonymous with being more androgynous) but contrasting predictions for males, the directionality of outcomes involving males is crucial in weighing up the level of support for each account. However, the relationship between facial masculinity and autistic-like traits in men was less clear. In Chapters 2 and 3, there was no difference in the masculinity ratings of highand low-AQ men. The inclusion of mid-AQ men revealed a U-shape trend whereby mid-AQ men were rated lowest on facial masculinity. While these findings do not provide clear support for either account, we found that objectively-measured facial features of high-AQ men were less masculine
Selection of a fault model for fault diagnosis based on unique responses

We describe a preprocessing step to fault diagnosis of an observed response obtained from a faulty chip. In this step, a fault model for diagnosing the observed response is selected. This step allows fault diagnosis to be performed based on a single fault model after identifying the most appropriate one. We describe a specific implementation of this preprocessing step based on what is referred to as the unique output response of a fault model. As an example, we apply it to the diagnosis of multiple stuck-at faults, selecting between single and double stuck-at faults as the fault model for diagnosis. Experimental results demonstrate improvements compared to diagnosis based on single stuck-at faults, and compared to diagnosis based on both single and double stuck-at faults.
Antigenic and immunogenic analysis of group A and group B respiratory syncytial virus G proteins expressed from recombinant baculoviruses.

The attachment glycoprotein G plays a major role in the antigenic variability of respiratory syncytial (RS) virus. We have expressed from recombinant baculoviruses antigenic group A and group B RS virus G proteins (designated bacAG for the group A and bacBG for the group B virus G protein). The insect cell-produced G proteins migrated more rapidly in SDS-PAGE as compared to HEp-2 cell derived G proteins owing to glycosylation differences. Antigenicity was tested by immunofluorescence; five or five group cross-reactive, five or six group A-specific, and six of six group B-specific MAbs reacted appropriately with bacAG and/or bacBG. In addition, bacAG and bacBG reacted with human polyclonal antibodies to RS virus. Cotton rats were immunized with bacAG, bacBG or a control lysate and challenged intranasally with a group A RS virus. The bacAG-immunized group had a statistically significant reduction in viral replication in the lungs (lung titres as mean log10 p.f.u./g +/- SD, bacAG = 3.1 +/- 1.2; control = 4.8 +/- 0.6, P = 0.013). The bacBG-immunized group showed less reduction in viral titres (bacBG lung titres = 4.1 +/- 0.6, P = 0.13 for bacBG compared to control). Thus, as expected, homologous protein (bacAG) immunization provided more protection against viral replication than immunization with the heterologous protein (bacBG). The G protein of RS virus expressed in insect cells had antigenic and immunogenic features which were similar to that of the G protein expressed in mammalian cells. The baculovirus-expressed G proteins should be useful for the study of immune responses to RS viruses.
Self-Scaled Cones and Interior-Point Methods in Nonlinear Programming

This paper provides a theoretical foundation for efficient interior-point algorithms for nonlinear programming problems expressed in conic form, when the cone and its associated barrier are self-scaled. For such problems we devise long-step and symmetric primal-dual methods. Because of the special properties of these cones and barriers, our algorithms can take steps that go typically a large fraction of the way to the boundary of the feasible region, rather than being confined to a ball of unit radius in the local norm defined by the Hessian of the barrier.
Quantum symmetry, the cosmological constant and Planck scale phenomenology

We present a simple algebraic mechanism for the emergence of deformations of Poincar? symmetries in the low-energy limit of quantum theories of gravity. The deformations, called ? -Poincar? algebras, are parametrized by a dimensional parameter proportional to the Planck mass, and imply modified energy? momentum relations of a type that may be observable in near future experiments. Our analysis assumes that the low energy limit of a quantum theory of gravity must also involve a limit in which the cosmological constant is taken very small with respect to the Planck scale, and makes use of the fact that in some quantum theories of gravity the cosmological constant results in the (anti)de Sitter symmetry algebra being quantum deformed. We show that deformed Poincar? symmetries inevitably emerge in the small-cosmological-constant limit of quantum gravity in 2 + 1 dimensions, where geometry does not have local degrees of freedom. In 3 + 1 dimensions we observe that, besides the quantum deformation of the (anti)de Sitter symmetry algebra, one must also take into account that there are local degrees of freedom leading to a renormalization of the generators for energy and momentum of the excitations. At the present level of development of quantum gravity in 3 + 1 dimensions, it is not yet possible to derive this renormalization from first principles, but we establish the conditions needed for the emergence of a deformed low energy limit symmetry algebra also in the case of 3 + 1 dimensions.
A classification method of fuzzy association rules

Partition method of interval is adopted in current classification based on associations (CBA), but this method cannot reflect the actual distribution of data and exists the problem of sharp boundary. Quantitative attributes are partitioned into several fuzzy sets by fuzzy c-means algorithm, and search technology of Apriori algorithm is improved to discover interesting fuzzy association rules, which are used to build classification system. Because fuzzy c-means algorithm can embody the actual distribution of the data and fuzzy sets can soften partition boundary, the classification system of the fuzzy association rules can obtain better classification accuracy than two popular classification methods: C4.5 and CBA
A case study of Twitter as a research tool

Abstract This paper documents the process of utilizing Twitter for a doctoral dissertation in rugby governance, and highlights the key benefits of using Twitter as a research tool. Research followed a case study approach to delve into the four major uses of Twitter: (1) a warning system for dramas or incidents relating to one’s research field; (2) data collection; (3) finding and recruiting research subjects; and (4) building a personal research brand. The research design used a mixed method approach that combined qualitative and quantitative analysis methods. The findings serve as the basis for the pursuit of more detailed future research with Twitter as the principal medium in focus within the area of sport.