Miracle-dz/UniFAR-FTUs huggingface dataset:
BANK CAPITAL AND MACROECONOMIC SHOCKS: A PRINCIPAL COMPONENTS ANALYSIS AND VECTOR ERROR CORRECTION MODEL

The recent financial turmoil has clearly highlighted the potential role of financial factors on amplification of macroeconomic developments and stressed the importance of analyzing the relationship between banks’ balance sheets and economic activity. This paper assesses the impact of the bank capital channel in the transmission of schocks in Europe on the basis of bank's balance sheet data. The empirical analysis is carried out through a Principal Component Analysis and in a Vector Error Correction Model.
Fundamental Analysis versus Technical Analysis: Which Matters More?

Whether fundamental analysis or technical analysis should be employed to predict stock returns is a longstanding debate in the literature. Incorporating a regime-switching mechanism, we establish a hybrid model with non-uniform weightings on each type of analysis to examine the debate. Our empirical results are consistent with the following notions. First, stock investors should give more weight to fundamental analysis for firms with incremental information involved in accounting reporting proxied by discretionary accruals. Second, for firms with high dispersion in financial analysts' forecasts, stock returns are more influenced by accounting data, which implies that stock investors care more about the intrinsic value of firms obtained with fundamental analysis when encountering information asymmetry or uncertainty. Third, the weight given to fundamental analysis should be increased for stocks with unusual volatility in prices. However, when the market is crashing, fundamental analysis might become invalid, and thus the weighting given to fundamental analysis should be decreased. For technical analysis, the reverse of these arguments holds true. The results are robust to alternative measures of the variables. JEL classification: G33, C51
Machine Learning-based Adaptive Migration Algorithm for Hybrid Storage Systems

Hybrid storage systems are prevalent in most large-scale enterprise storage systems since they balance storage performance, storage capacity and cost. The goal of such systems is to serve the majority of the I/O requests from high-performance devices and store less frequently used data in low-performance devices. A large data migration volume between tiers can cause a huge overhead in practical hybrid storage systems. Therefore, how to balance the trade-off between the migration cost and potential performance gain is a challenging and critical issue in hybrid storage systems. In this paper, we focused on the data migration problem of hybrid storage systems with two classes of storage devices. A machine learning-based migration algorithm called K-Means assisted Support Vector Machine (K-SVM) migration algorithm is proposed. This algorithm is capable of more precisely classifying and efficiently migrating data between performance and capacity tiers. Moreover, this K-SVM migration algorithm involves a K-Means clustering algorithm to dynamically select a proper training dataset such that the proposed algorithm can significantly reduce the volume of migrating data. Finally, the real implementation results indicate that the ML-based algorithm reduces the migration data volume by about 40% and achieves 70% lower latency than other algorithms.
Citation patterns in economics and beyond

Argument In this paper we comparatively explore three claims concerning the disciplinary character of economics by means of citation analysis. The three claims under study are: (1) economics exhibits strong forms of institutional stratification and, as a byproduct, a rather pronounced internal hierarchy; (2) economists strongly conform to institutional incentives; and (3) modern mainstream economics is a largely self-referential intellectual project mostly inaccessible to disciplinary or paradigmatic outsiders. The validity of these claims is assessed by means of an interdisciplinary comparison of citation patterns aiming to identify peculiar characteristics of economic discourse. In doing so, we emphasize that citation data can always be interpreted in different ways, thereby focusing on the contrast between a “cognitive” and an “evaluative” approach towards citation data.
D4.10 Algorithms and technology for data mediation state of the art

This document is deliverable D4.10 of the DISASTER project. It reports on the current state of the art regarding data mediation. The document defines and characterises mediation, and then it addresses the topics from three points of view: data format mediation, schema alignment and link discovery and data mediation techniques. Conclusions on the maturity of the tools available in the state of the art are given, as well as an overview of the most prominent open challenges.
Short Selling and Readability in Financial Disclosures: Evidence from a Natural Experiment

We examine how the relaxation of short-sale constraints affects annual report readability using a natural experiment, Regulation SHO. We find that the readability of 10-Ks for the pilot stocks significantly decreases during the program period. The relation between reductions in short-sale constraints and annual report readability is not uniform in the cross-section. We find results are more pronounced for firms that the short-sale constraints bind tighter; for firms with greater information asymmetry; and for firms with worse news or corporate governance. Furthermore, we document that pilot firms significantly increase the use of uncertainty words in 10-Ks during the experiment period. Our results suggest that pilot firms obscure valuation-relevant information by producing less readable and more ambiguous 10-Ks to prevent investors from selling short, especially when short-sale constraints are loose.
Mining frequent generalized patterns for Web personalization in the presence of topic taxonomies

The Web is a continuously evolving environment, since its content is updated on a regular basis. As a result, the traditional usage-based approach to generate recommendations that takes as input the navigation paths recorded on the web page level, is not as effective. Moreover, most of the content available online is either explicitly or implicitly characterized by a set of categories organized in a taxonomy. Using this information, the page-level navigation patterns can be generalized to a higher, aggregate level. In this direction, we present the Frequent Generalized Pattern (FGP) algorithm. FGP takes as input the transaction data and a hierarchy of categories that characterize them, and produces generalized association rules that contain transaction items and/or item categories. The algorithm can be applied to the log files of a typical web site; however, it can be more helpful in a Web 2.0 application where content is semantically annotated. Given a transaction database and a hierarchical organization of the browsed items, the algorithm generates frequent itemsets comprising of both web pages and categories. The results can be used to generate association rules and subsequently recommendations for the users. We also introduce FGP+, which is an extension of the FPG algorithm and can take as input more complex structures than taxonomies. This extension addresses the unique characteristics of Web 2.0 sites such as feed aggregators or digital libraries. In such sites, the topic or tag information attached in a page hardly forms a taxonomy. We experimentally evaluate the proposed algorithms using web log data collected from a newspaper web site.
Kamuee: An IP Packet Forwarding Engine for Multi-Hundred-Gigabit Software-based Networks

In Software Defined Network (SDN) and Network Function Virtualization (NFV) era, extensible, flexible, and yet high-performance software packet forwarding capability is desirable, as the core functionality of the future Internet. In this paper we present Kamuee: a software IP packet forwarding engine, and its core router version that builds only on commodity hardware. By scaling the number of forwarding CPU cores, Kamuee supports multiple 100GbE interfaces, with near wire-rate traffic. In our benchmarks that use two Intel Xeon Platinum 8180 processors, Kamuee could forward 349.60 Gbps 512B-sized random destination traffic in a BGP full route environment. Further intralaboratory evaluation resulted in 292.17 Mpps 64B forwarding capability, showing the potential of very high-speed software router.
Crossing numbers and related topics in combinatorial geometry

The field of crossing numbers deals with the problem of minimizing the number of edge intersections in a drawing of a graph in some surface (usually the plane). In order to investigate this question, we first must agree on exactly what is a drawing of a graph, and how intersections are counted. In most (but not all) models of graph drawing, the vertices are represented by points, the edges are represented by arcs (homeomorphic images of [0, 1]), and the endpoints of an arc are the two vertices incident with the corresponding edge. It is implicitly assumed that every two edges intersect each other a finite number of times. The issue of how intersections are counted is a very subtle one, and in fact it has given rise to some of the most fundamental and interesting open questions in the field. At the simplest and perhaps more natural level, one could propose to count the number of points that are intersections between edges (at a point other than a common vertex), avoiding drawings in which more than two edges intersect at a common point. The minimum number of such intersections over all drawings of a graph G is the most common definition of the crossing number cr(G) of G. The term crossing comes up because, as it is not difficult to verify, in a drawing with the minimum total number of intersections every intersection is a crossing, rather than tangential. There are, however, many other possible ways to define the crossing number of a graph, depending on the context and motivation. There are so many reasonable ways to propose a definition for the crossing number of a graph that this is the subject of a long, thorough monograph by Marcus Schaefer [25]. In this course we will mostly deal with crossing numbers
Does loneliness lurk in temp work? Exploring the associations between temporary employment, loneliness at work and job satisfaction

This research contributes to the limited literature concerning the determinants of loneliness at work, as well as to the literature on psychological outcomes associated with temporary work. More specifically, we are adding to the literature by exploring whether there is an association between working temporarily and loneliness at work and whether loneliness at work partly explains the association between working temporarily and job satisfaction. To this end, we analyse—by means of a mediation model—a unique sample of Flemish employees in the private sector. We find that employees with a temporary contract experience more loneliness at work as opposed to employees with a permanent contract. In addition, we discover that loneliness at work mediates the association between working temporarily and job satisfaction.
A hybrid method to categorize HTML documents

In this paper we introduce a hybrid method for classifying HTML documents. In this method the statistical, semantic and writing style features of text are used to categorize documents. Categorization can be done in both supervised and unsupervised modes and categories may be predefined or be created dynamically (clustering). The classification system exploits an ontology of interesting topics. The ontology which contains categories and their hierarchical relations can be updated automatically during the system’s lifetime. Newly defined categories can be added to the ontology and existing categories can be changed according to the documents received. The statistical part of the method is based on the Rocchio algorithm. The algorithm has been changed to cover the special conditions for dynamic category building, for categorizing with and without training data and for variable length feature vectors. The semantic part of the algorithm exploits Wordnet to substitute words with their corresponding concepts and does some word sense disambiguation tasks prior to clustering. This way documents will be clustered according to their concepts instead of words. The other part of the method considers writing style features of text such as writing in bold/italic style, writing with different (bigger) fonts or occurring words and concepts in special places of the document, such as the title, headers or hyperlinks. In this paper, after a brief overview on existing methods of document classification, the proposed method will be discussed and some experimental results of classifying documents will be shown. Experiments show that the hybrid method results in some improvements in performance (the accuracy).
Multi-Electron Dynamics in the Ionization of Molecules by Strong Laser Pulses

Shake-up of a two-electron system is investigated in the strong infrared laser field limit, both theoretically and experimentally. During tunnel ionization the electron shakes-up a second electron to an excited bound state. Theoretically, a complete analytical theory of shake-up in intense laser fields is developed. We predict that shake-up produces one excited au Dj state in ss 10 5 ionization events. Shake-up is measured experimentally by using the molecular clock provided by the internuclear motion. The number of measured events is found to be in excellent agreement with theory. Besides shake-up there are a wealth of multi-electron phenomena in strong laser fields that cannot be treated analytically. Therefore we introduce the multi-configuration time-dependent Hartree-Fock (MCTDHF) method as a new approach towards the numerical solution of the time-dependent Schrödinger equation arising in ultrafast laser dynamics. MCTDHF approximates the exact wave function by several Slater determinants. By doing so the method produces a lower dimensional, non-linear system of coupled differential equations compared to the original Schrödinger equation. MCTDHF is capable of modeling nonperturbative multi-electron dynamics including correlation effects of up to 10 active electrons. We discuss the theoretical foundations of our approach and describe our one dimensional implementation. To assess the reliability and efficiency of MCTDHF we test the method on two examples, using the harmonic quantum dot and the one-dimensional Helium in strong laser pulses as models. We find rapid convergence for quantities like ground state population, correlation coefficient, and single ionization towards the exact results. The method converges, where time-dependent Hartree-Fock fails qualitatively. By using one dimensional MCTDHF calculations we then investigate ionization of multi-electron systems. Our analysis reveals the key physical process underlying ionization of complex systems. The laser induced multi-electron dynamics depend on the ratio of laser frequency, ui, to plasmon frequency, o>m, discriminating two different regimes. In the over-resonant limit, u> ~%> Wm, tunnel ionization is destroyed. Ionization takes place by a classical over the barrier mechanism. In the under-resonant limit, w <§; wm, tunnel ionization remains dominant, but is weakened by a polarization induced growth of the tunneling barrier. X Parts of this work have been published as M. Kitzler et al. Phys. Rev. A, 70:041401(R), 2004 J. Zanghellini, M. Kitzler, T. Brabec, and A. Scrinzi. J. Phys. B, 37:763, 2004 J. Zanghellini et al. Laser Physics, 13:1064, 2003
Laccase Immobilisation on Poly(ethylene) Terephthalate Grafted with Maleic Anhydride (PET-g-MAH) Nanofiber Mat

A comparative study was carried out on three different enzyme immobilisation methods which were physical adsorptions (PA), covalent bonding (CV) and covalent bonding of cross-linked enzyme aggregates (CL) for laccase immobilisation on Poly(ethylene) Terephthalate (PET) grafted with Maleic Anhydride (MAH) nanofiber mats. The chemically inert PET was successfully grafted with MAH at temperature between 40 - 45 C and used as the carrier to immobilised laccase in the form of electrospun nanofiber mats. The peaks from carbonyl (C=O) and alkene (C=C) groups appeared on the spectral subtraction between PET and PET-g-MAH nanofiber mats. These groups might be the potential group to form covalent bond between the amine groups of laccase enzyme. Laccase immobilised on the PET-g-MAH nanofiber mats using CL methods using glutaraldehyde as crosslinker gave the best performance with the highest enzyme loading and immobilisation yield which were 40.88 µg/mg and 48.37 %. On top of that, the immobilised laccase on PET-g-MAH nanofiber mats also managed to retain 69.01 % of its initial activity after 10 repeated cycles of 2, 2-azino-bis 3-ethylbenzothiazoline-6-sulfonic acid (ABTS) oxidations. These results demonstrate that PET-g-MAH nanofiber is a good material to be considered as laccase carrier.
Corporate Governance Reform and Risk-Taking: A Quasi-Experiment from an Emerging Market

Does the adoption of corporate governance reform (CGR) substitute higher dividend payouts in mitigating agency problems of free cash flow in emerging markets? Further, does the adequacy of CGR sanctions play any role in explaining the substitution effect of CGR? We answer these questions by exploiting two regulatory shocks in the Indian capital market. The first shock relates to the adoption of CGR with reputational penalties and the second to the additional imposition of personal liability of corporate insiders for non-compliance with CGR. Our results show that firms that are affected by CGR reduce their dividend payouts, on average, by at least 3%. However, this CGR substitution effect is observed only after the imposition of additional personal liability in the form of stricter financial and criminal penalties. Our findings highlight the importance of expanding reputational penalties to include personal liability in regulatory interventions in order to improve the effectiveness of CGR in emerging markets.
Innovative Technologies in Current and Future TFSI Engines from Audi

As the pioneer and technology leader in TFSI, Audi has continually enhanced its TFSI technology since its first production fitting of a direct turbocharged engine in Europe and NAR in 2004. In 2011 Audi launched what is already its third generation of four-cylinder inline TFSI engines onto the market. Once again, this third generation incorporates many innovative technologies applied to an SI engine for the first time anywhere in the world.
Measuring eudaimonic wellbeing in sport: Validation of the Eudaimonic Wellbeing in Sport Scale

The purpose of this study was to create and validate a sport-specific eudaimonic wellbeing measure (EWBSS; Eudaimonic Wellbeing in Sport Scale) and included three phases. In Phase 1, an initial pool of 19 items was developed and five items were selected by five experts to represent eudaimonic wellbeing in sport (EWBSS). Four hundred athletes (Mage = 24.32, SD = 6.69) from various individual and team sports participated in Phase 2. Factorial validity and reliability scores were examined using confirmatory factor analysis and alpha coefficient calculations. Results indicated initial evidence for both factorial validity and internal consistency of the EWBSS. In Phase 3, further psychometric testing of the EWBSS with two independent samples (i.e., competitive and recreational athletes) ensued. The findings provided further evidence of sound validity and reliability scores of the EWBSS in competitive athletes. Partial support for the psychometric properties of the EWBSS was provided in recreational athletes. As the validation of an instrument is an ongoing process, more research is needed to further evaluate the validity of the EWBSS.
Banking the group: Impact of credit and linkages among Ugandan savings groups∗

Traditional banks and microfinance institutions lend directly to clients using individual or joint liability contracts, and generally have strict rules on selection and repayments. In most rural areas of sub-Saharan Africa, these formal institutions are uncommon. Financial services are more often provided by savings groups; however, these are often unable to fully meet local financial needs. In this paper, we study an alternative lending model with the potential to bridge the gap between formal and informal finance. In this delegated lending model, better known as linkage, a formal financial institution lends to savings groups and lets the group decide the allocation of borrowed funds. In our RCT, a random sample of existing savings groups gained access to linkage loans from a commercial bank in Uganda. We show that the bank loan stimulated an immediate and sizable increase in internal lending, which is sustained over time. Despite this benefit, we also find that linkages are a double-edged sword: On the one hand, members of treated groups had temporarily lower rates of food insecurity after two years, and point estimates suggest sizable increases in income and microenterprise size (which are not statistically significant). On the other hand, groups assigned to loans experienced significantly more turnover, suggesting that the possibility of external financing generates powerful selection effects. JEL classification: O12, O16
Impact of Hormone Use Perceptions on Consumer Meat Preferences

U.S. consumers see retail beef products with “no added hormones” (NAH) labels. However, similar labels appear on pork and chicken products, even though hormone use in their production is prohibited. This study assesses consumer perceptions of hormone use in different livestock species. Using choice experiment data, we then examine the impact of these perceptions on preferences for unlabeled meat products and willingness to pay for NAH-labeled meat products. Results suggest that consumer perceptions of hormone use in production are incorrect. Further, perceptions influence consumer preferences and willingness to pay for unlabeled products versus those with NAH labels.
Sesame production and composition compared with conventional forages

Sesamum indicum L. has the potential to be cultivated as a forage plant in hot and dry climate regions, and it can be used to increase the food security of a herd. The objective of this study was to evaluate growth, production, and chemical composition of S. indicum compared with conventional forages used for silage production. The experiment used a randomized complete block design with split-plots related to time and four replicates per treatment. The plots consisted of four treatments (Zea mays L., Helianthus annuus L., Pennisetum glaucum [L.] R. Br., and S. indicum), and the subplots were two evaluation periods (2014 and 2016 harvests). Dry forage biomass production differed among the species in the 2014 harvest with values of 25 530, 12 190, 9408, and 9250 kg ha-1 for Z. mays, S. indicum, H. annuus, and P. glaucum, respectively. Maize had a greater variation in forage production between the 2 yr, followed by S. indicum. There were higher dry matter (DM) contents (P < 0.0001) for Z. mays and S. indicum (404.5 and 251.7 g kg-1, respectively). Regarding crude protein, H. annuus and S. indicum had levels of 167.2 and 117.7 g kg-1, respectively. According to the results, it can be inferred that sesame, like millet, provides greater feeding security for ruminant herds in regions with irregular rainfall.