Miracle-dz/UniFAR-FTUs huggingface dataset:
Inferring Metaphoric Structure from Financial Articles Using Bayesian Sparse Models

Inferring Metaphoric Structure from Financial Articles Using Bayesian Sparse Models Martin Salzle (saelzle_martin@ceu-budapest.edu) Department of Cognitive Science, Central European University Frankel Leo utca 30-34, Budapest, 1023, Hungary Mark T. Keane (mark.keane@ucd.ie) School of Computer Science & Informatics, University College Dublin Belfield, Dublin 4, Ireland Abstract Drawing from a large corpus (17,000+ articles) of financial news, we perform a Bayesian sparse model analysis of the argument-distributions of the UP and DOWN-verbs, used to describe movements in indices, stocks and shares. Previous work, by Gerow and Keane (2011a, 2011b, 2011c), has shown, using measures of overlap and k-means clustering, that metaphor hierarchies and antonymic relations can be found in this data; for instance, UP verbs have rise as a superordinate organizing a distinct set of subordinate verbs (soar, jump, climb, surge, rebound, advance). This work empirically realizes theories about the structuring of our conceptual systems with metaphors (Lakoff, 1992; Lakoff & Johnson, 1980) but does so using a distributional approach to meaning; namely, that words that occur in similar contexts have similar meanings (see Wittgenstein, 1953). However, Gerow and Keane’s analysis does not show the overall structure of how these metaphors semantically relate to one another. In the present paper, we re-analyzed their data using a Bayesian sparse model (Lake & Tenenbaum, 2010) in order to infer this metaphor space as a uniform representation, based on the argument distributions. Therefore, we treated arguments as features of metaphors. Our model learned three dimensional graphs in an unsupervised manner as sparse representations of the metaphoric structure over all argument distributions, in parallel. Doing so, it also successfully indicates the metaphoric hierarchies and antonymy relations, that were found by the previous models. In conclusion, we discuss the benefits of this approach. Keywords: Argument features; analogy; Bayesian inference; emergent structure; corpus analysis; metaphor hierarchies; semantic cognition; similarity; sparse representation; spatial metaphor; structure discovery; unsupervised learning. Gerow and Keane (2011a-c; henceforth abbreviated as GK LESS-IS-DOWN). GK the corpus contained over 10M words. After parsing the corpus, GK Landauer & Dumais, 1997; Turney, 2006; Turney & Pantel, 2010; Michel et al., 2010). This distributional approach to meaning takes the view that words that occur in similar contexts tend to have similar meanings (see Wittgenstein, 1953) and that by analyzing word usage we can recover meaning. For instance, Michel et al., (2010) argue that significant insights into human culture and behavior can be derived from analyzing very large corpora, such as the GoogleBooks repository. Argument Word Index Share Point Percent Price Stock Yield Cent Profit Rate % of Corpus
Pioglitazone inhibits high glucose-induced expression of receptor for advanced glycation end products in coronary artery smooth muscle cells

Receptor for advanced glycation end products (RAGE) is critical in inflammatory diseases, including diabetes and atherosclerosis. The mechanism underlying the effect of peroxisome proliferator-activated receptor γ (PPARγ) agonist pioglitazone (PIO) on RAGE expression in coronary artery smooth muscle cells (SMCs) stimulated by high glucose concentrations remains to be elucidated. In the present study, the effect and mechanism of action of PIO on RAGE expression in SMCs was investigated following treatment with high glucose concentrations. Rat coronary artery SMCs were pretreated with PIO alone, PIO and GW9662 (a PPARγ antagonist), diphenyleneiodonium (DPI; a nicotinamide adenine dinucleotide phosphate (NADPH) oxidase inhibitor) or the antioxidant pyrrolidine dithiocarbamate (PDTC; a nuclear factor-κB (NF-κB) inhibitor), followed by treatment with high glucose. RAGE mRNA and protein expression, reactive oxygen species (ROS) production and NF-κB nuclear translocation were investigated. Glucose induced RAGE expression in a dose-dependent manner, with maximal effect at a concentration of 25 mmol/l following treatment for 48 h. PIO, DPI and PDTC reduced high glucose-induced increases in RAGE protein and mRNA expression. PIO prominently downregulated RAGE expression and inhibited high glucose-induced increases in ROS production and NF-κB activation (P<0.05). Pretreatment with PIO and GW9662 did not exhibit this inhibitory effect. High glucose may stimulate RAGE expression in coronary artery SMCs through NADPH oxidase-mediated ROS generation and NF-κB activation. PIO downregulated RAGE expression and inhibited ROS production and NF-κB activation via PPARγ activation, which may prevent the inflammatory effect of AGE/RAGE system in diabetes.
From Visuo-Motor to Language

We propose a learning agent that ﬁrst learns concepts in an integrated, cross-modal manner, and then uses these as the semantics model to map language. We consider an abstract model for the action of throwing, modeling the entire trajectory. From a large set of throws, we take the trajectory images and and the throwing parameters. These are mapped jointly onto a low-dimensional non-linear manifold. Such models improve with practice, and can be used as the starting point for real-life tasks such as aiming darts or recognizing throws by others. How can such models can be used in learning language? We consider a set of videos involving throwing and rolling actions. These actions are analyzed into a set of contrastive semantic classes based on agent, action, and the thrown object (trajector). We obtain crowdsourced commentaries for these videos (raw text) from a number of adults. The learner attempts to associate labels using contrastive probabilities for the semantic class. Only a handful of high-conﬁdence words are found, but the agent starts off with this partial knowledge. These are used to learn incrementally larger syntactic patterns, initially for the trajector, and eventually for full agent-trajector-action sentences. We demonstrate how this may work for two completely different languages - English and Hindi, and also show how rudiments of agreement, synonymy and polysemy are detected.
Expander graphs in pure and applied mathematics

Expander graphs are highly connected sparse finite graphs. They play an important role in computer science as basic building blocks for network constructions, error correcting codes, algorithms, and more. In recent years they have started to play an increasing role also in pure mathematics: number theory, group theory, geometry, and more. This expository article describes their constructions and various applications in pure and applied mathematics.
Recommended Capacities for Educational Leadership: Pre-Reform Era Scholars Versus Reform-Era Scholars Versus National Standards

We reviewed the scholarship on capacities for educational leadership for the past decade of the pre-reform era (1976-1985), as well as a recent decade of the reform era (2005-2015), and compared scholarship from both decades with the current Professional Standards for Educational Leaders. We found that scholars in the past decade of the pre-reform era wrote most often about technical management and the application of behavioral and social science, the greatest priorities of scholars during a 10-year period of the reform era were school improvement and instructional leadership, and the capacities most often represented in the Standards were school improvement and technical management.
Application of Multi‐Objective Evolutionary Optimization Algorithms to Reactive Power Planning Problem

This paper presents a new approach to treat reactive power (VAr) planning problem using multi‐objective evolutionary algorithms (EAs). Specifically, strength Pareto EA (SPEA) and multi‐objective particle swarm optimization (MOPSO) approaches have been developed and successfully applied. The overall problem is formulated as a nonlinear constrained multi‐objective optimization problem. Minimizing the total incurred cost of the VAr planning problem and maximizing the amount of available transfer capability (ATC) are defined as the main objective functions. The aim is to find the optimal allocation of VAr devices in such a way that investment and operating costs are minimized and at the same time the amount of ATC is maximized. The proposed approaches have been successfully tested on IEEE 14 buses system. As a result a wide set of optimal solutions known as Pareto set is obtained and encouraging results show the superiority of the proposed approaches and confirm their potential to solve such a large‐scale multi‐objective optimization problem. Copyright © 2009 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
Book Review: Reaching the Resistant: Barriers and Bridges for Mission

whose duty it is to fetch water for the household who is the most likely to break the earthenware pots for fetching water. " In pursuing a good deed, one risks some errors and failings. So one also spots some errors here. Musama Disco Cristo Church is mistakenly located in Democratic Republic of the Congo (p, 97),when in fact it is in Ghana. There are typographical errors on pages 63, 85, and 104. Despite such blemishes, the book is an excellent introductory reader for students of social anthropology and the pastorate. It combines serious scholarship
Pyrone-Based Inhibitors of Metalloproteinase Types 2 and 3 May Work as Conformation-Selective Inhibitors

Matrix metalloproteinases are zinc‐containing enzymes capable of degrading all components of the extracellular matrix. Owing to their role in human disease, matrix metalloproteinase have been the subject of extensive study. A bioinorganic approach was recently used to identify novel inhibitors based on a maltol zinc‐binding group, but accompanying molecular‐docking studies failed to explain why one of these inhibitors, AM‐6, had approximately 2500‐fold selectivity for MMP‐3 over MMP‐2. A number of studies have suggested that the matrix‐metalloproteinase active site is highly flexible, leading some to speculate that differences in active‐site flexibility may explain inhibitor selectivity. To extend the bioinorganic approach in a way that accounts for MMP‐2 and MMP‐3 dynamics, we here investigate the predicted binding modes and energies of AM‐6 docked into multiple structures extracted from matrix‐metalloproteinase molecular dynamics simulations. Our findings suggest that accounting for protein dynamics is essential for the accurate prediction of binding affinity and selectivity. Additionally, AM‐6 and other similar inhibitors likely select for and stabilize only a subpopulation of all matrix‐metalloproteinase conformations sampled by the apo protein. Consequently, when attempting to predict ligand affinity and selectivity using an ensemble of protein structures, it may be wise to disregard protein conformations that cannot accommodate the ligand.
Strategies for effectively managing email at work

Remit: The remit for this programme of research was therefore to provide Acas with an overview of the current state of empirical research into email-use and to outline validated findings from psychology, management and HCI research domains about: (i) when work email may cause problems for people, (ii) when work email has beneficial outcomes for people, (iii) whether there are particular groups that are more or less impacted by issues associated with work email, and, (iv) what strategies are associated with positive and negative outcomes, relating to how people deal with work email. Our primary aim in this research programme was therefore to identify themes that would explain the emergence of work email strategies, which have positive and negative repercussions for productivity (including work performance and goal achievement) and wellbeing (including engagement and strain). We also aimed to provide evidence-based learning points about which strategies might be adopted by workers and organisations, to optimise the positive impact of work email, and reduce potentially negative outcomes.
Context-Based Arabic Text Processing System

In the last decades, the rapid growth of information increased the need for summarizing systems capable of processing large amounts of electronic texts. Implementing a system that allows a user to search a collection of documents, process them and extract relevant information is a non-trivial task especially if the system deals with dynamic and heterogeneous texts on the Web. This paper describes a system for summarizing domain-free texts written in Arabic. The idea is aiming at getting an idea of the text content without understanding its meaning. We are interested in discursive markers, which can give an idea of the sentences relevance
Does Institutional Setting Affect Legislators’ Use of Twitter?

This study investigates whether members of the European Parliament (MEPs) and members of national parliaments (MNPs) use social media in distinctive ways. Specifically, it examines whether institutional differences affect the frequency, quality, and nature of legislators’ Twitter communications. Controlling for factors that previous studies find significant, we select for two kinds of legislators: (i) MEPs who are serving in the 2014–19 term and who served as MNPs immediately before their election to the EP and (ii) MEPs who served in the 2009–14 term and have subsequently become MNPs. We compare selected legislators’ tweets over a three-month period during their EP tenures with their Twitter behaviors over an analogous period during their NP tenures. The statistical results demonstrate few significant differences between MEPs and MNPs. A preliminary qualitative probe suggests that legislators’ tweet patterns may owe less to the institution they serve and more to their policy responsibilities and leadership positions within particular institutions.
Routing Protocols for Wireless Ad Hoc Networks Hierarchical routing protocols

This paper presents two hierarchical routing protocols. Hierarchical state routing protocol and Fisheye state routing protocol. The former is a multilevel routing protocol that provides nodes’ clustering in multiple levels, while the latter uses the fisheye technique to reduce the routing overhead. They both employ a hierarchical control structure and try to provide better routing solutions.
The circumscription theory by Robert Carneiro in the socio-ontological and macrosociological context

The theory of origin of the state by Robert Carneiro (1970), no doubt, is one of brightest achievements in the 20 century macrosociology. From the methodological point of view, the theory is significant, first, because it is built with a high degree of logical correctness, and second, because, when faced with anomalies, it has been successfully improved in direct line with the concept of scientific research programs (Imre Lakatos). In my article, I will focus on the coherence criterion (between this theory and other theories and more general scientific and philosophical paradigms). Hempel's logical scheme of the nomological (based on laws) explanation and prediction (Hempel 1942), despite the decades of severe criticism turns out to be the core of the most successful research programs. According to Hempel's scheme, a full-fledged scientific theory must explain and predict phenomena by means of deductive judgments that connect initial conditions and universal laws. In his last article, Carneiro formulated the main thesis of his theory in the following way:
Bayesian Calibration of Generalized Pools of Predictive Distributions

Decision-makers often consult different experts to build reliable forecasts on variables of interest. Combining more opinions and calibrating them to maximize the forecast accuracy is consequently a crucial issue in several economic problems. This paper applies a Bayesian beta mixture model to derive a combined and calibrated density function using random calibration functionals and random combination weights. In particular, it compares the application of linear, harmonic and logarithmic pooling in the Bayesian combination approach. The three combination schemes, i.e . , linear, harmonic and logarithmic, are studied in simulation examples with multimodal densities and an empirical application with a large database of stock data. All of the experiments show that in a beta mixture calibration framework, the three combination schemes are substantially equivalent, achieving calibration, and no clear preference for one of them appears. The financial application shows that the linear pooling together with beta mixture calibration achieves the best results in terms of calibrated forecast.
Organizing master data management: findings from an expert survey

Master data management (MDM) is defined as an application-independent process which describes, owns and manages core business data entities. The establishment of the MDM process is a Business Engineering (BE) tasks which requires organizational design. This paper reports on the results of a questionnaire survey among large enterprises aiming at delivering insight into what tasks and master data classes MDM organizations cover ("scope") and how many people they employ ("size"). The nature of the study is descriptive, i.e. it allows for the identification of patterns and trends in organizing the MDM process.
Plasmid-Encoded Toxin of EnteroaggregativeEscherichia coli is Internalized by Epithelial Cells

ABSTRACT We have previously described a 104-kDa protein termed Pet (for plasmid-encoded toxin) secreted by some strains of enteroaggregativeEscherichia coli (EAEC). Through an unknown mechanism, this toxin (i) raises transepithelial short-circuit current (Isc) and decreases the electrical resistance of rat jejunum mounted in the Ussing chamber, (ii) causes cytoskeletal alterations in HEp-2 cells and HT29/C1 cells, and (iii) is required for histopathologic effects of EAEC on human intestinal mucosa. Pet is a member of the autotransporter class of secreted proteins and together with Tsh, EspP, EspC, ShMu, and SepA proteins comprises the SPATE subfamily. Here, we show that Pet is internalized by HEp-2 cells and that internalization appears to be required for the induction of cytopathic effects. Evidence supporting Pet internalization includes the facts that (i) the effects of Pet on epithelial cells were inhibited by brefeldin A, which interferes with various steps of intracellular vesicular transport; (ii) immunoblots using anti-Pet antibodies detected Pet in the cytoplasmic fraction of intoxicated HEp-2 cells; (iii) Pet was detected inside HEp-2 cells by confocal microscopy; and (iv) a mutant in the passenger domain cleavage site, which prevents Pet release from the bacterial outer membrane, did not produce cytopathic effects on epithelial cells, whereas the release of mutant Pet from the outer membrane with trypsin yielded active toxin. We have also shown that the Pet serine protease motif is required to produce cytopathic effects but not for Pet secretion. Our results suggest an intracellular mode of action for the Pet protease and are consistent with we our recent report suggesting an intracellular mode of action for Pet (J. M. Villaseca, F. Navarro-Garcı́a, G. Mendoza-Hernández, J. P. Nataro, A. Cravioto, and C. Eslava, Infect. Immun. 68:5920–5927, 2000).
Memory-Optimized Distributed Graph Processing through Novel Compression Techniques

A multitude of contemporary applications now involve graph data whose size continuously grows and this trend shows no signs of subsiding. This has caused the emergence of many distributed graph processing systems including Pregel and Apache Giraph. However, the unprecedented scale now reached by real-world graphs hardens the task of graph processing even in distributed environments and the current memory usage patterns rapidly become a primary concern for such contemporary graph processing systems. We seek to address this challenge by exploiting empirically-observed properties demonstrated by graphs that are generated by human activity. In this paper, we propose three space-efficient adjacency list representations that can be applied to any distributed graph processing system. Our suggested compact representations reduce respective memory requirements for accommodating the graph elements up to 5 times if compared with state-of-the-art methods. At the same time, our memory-optimized methods retain the efficiency of uncompressed structures and enable the execution of algorithms for large scale graphs in settings where contemporary alternative structures fail due to memory errors.
ML estimation and CRB for narrowband AR signals on a sensor array

This paper considers the exploitation of temporal correlation in incident sources in a narrowband array processing scenario. The MLE and CRB are derived for parameter estimation of spatially uncorrelated first order Gaussian autoregressive source signals with additive Gaussian spatially and temporally uncorrelated sensor noise. These are compared to the MLE and CRB for the usual uncorrelated (WN) sources model. The paper deals with the case where the number of data snapshots is small. Numerical simulations show that (i) there is no significant performance gain in the correlated signal case, and significantly, (ii) the WN MLE performance does degrade in the presence of source correlation, which appears to be in contrast to some recently published work.
A MULTI-PITCH TRACKING SYSTEM ( MIREX 2009 )

This extended abstract describes the system we submit for MIREX 2009 task “Multiple Fundamental Frequency Estimation and Tracking”. The task includes three subtasks: 1) Multi-pitch Estimation (MPE) at frame-level, 2) note events detection and 3) pitch tracking for each source. Our system consists of two parts: 1) MPE in each time frame and 2) pitch trajectory formation from these pitch estimates. We submit two versions of the system. The first one implements the whole system and does all the three subtasks. The second one only implements the MPE part and does the first subtask. For the first subtask the two versions output different results, since the first version refines MPE results with tracking results.
Alcoholic Steatosis in Different Strains of Rat: A Comparative Study

Background Different strains of rats have been used to study alcoholic liver disease (ALD) while the reason for selecting a particular rat strain was not apparent. Purpose The aim of our study was to compare outbred (Wistar) and inbred (Fischer) strains to evaluate pathological, biochemical changes, and gene expression differences associated with ethanol-induced early hepatic steatosis. Study Design Male Wistar and Fischer-344 rats were pair-fed for 6 weeks with or without 5% ethanol in Lieber-DeCarli liquid diet. Livers were analyzed for histological and lipid-related differences. Results Hepatic midzonal steatosis was mainly found in Wistar rats while Fischer rats showed mostly pericentral steatosis. Increased hepatic steatosis in ethanol-fed Wistar rats is supported by increases in lipids with related genes and transcription factors involved in fatty acid and triglyceride synthesis. Conclusion Our data showed that Fischer rats are relatively less prone to ethanol-mediated steatosis with pericentral lipid deposition pattern in the liver which is similar to humans and show no trace level of lipid accumulation in pair-fed controls as observed in Wistar (outbred) strain. Therefore, Fischer rats are better suited for lipid studies in an early development of ALD.