Miracle-dz/UniFAR-FTUs huggingface dataset:
General Equilibrium Implications of the Capital Adequacy Regulation for Banks

Capital adequacy regulations specify a minimum capital-to-assets ratio for banks in the economy. The effects of these regulations on the level of economic activity have not been thoroughly studied by the banking regulation literature. Specifically, the fact that as proposed by the Basle Accords, a constant ratio tying bank lending to bank equity may reinforce macroeconomic fluctuations has been looked at by only a few existing theoretical papers. This paper proposes a stochastic dynamic general equilibrium model to study the interactions between the banking sector and the aggregate level of economic activity. Banks behavior is fully micro-founded. Banks financing decisions (equity versus deposits) are constrained not only by the regulation but also by a financial imperfection arising from the fact that during bad times banks find it difficult to recapitalize by raising equity. Thus, higher borrower bankruptcy rates during recessions imply that banks have to cut new loans until the ratio is restored to the required level. Since production firms can only imperfectly substitute bank lending with other forms of financing, a negative macroeconomic shock affects production and investment both directly and indirectly through the bank loan supply. This banking regulation and the financial imperfection imply two different constraints to the banks problem that bind only occasionally in the stochastic steady state. This prevents the use of standard linearization techniques to solve the model numerically. Alternatively, using some discretization of the state space methods such as Value Function Iteration is difficult because the model cannot be written in terms of a central planner problem. Following Fackler (2003) I solve the decentralized general equilibrium problem by using a very general Function Approximation technique that nests the Parameterized Expectation Approach as a particular case. The method allows to approximate numerically either the policy functions or the expectation functions. It is also flexible as regards the choice of approximating functions, including Chebyshev polynomials and piecewise polynomial splines. The technique relies on the Collocation Method to solve for the polynomial coefficients in combination with either generic root-finding algorithms or a fixed-point iteration scheme. Numerical results suggest that banks try to anticipate aggregate shocks by accumulating a buffer of capital over the regulatory minimum. Nevertheless, a series of bad shocks may be strong enough to eventually undermine these "reserves" and to make banks cut back on lending. This suggests the existence of a financial accelerator, since the supply of loans shrinks together with the demand during recessions. This mechanism has interesting policy implications and provides grounds for a procyclical value of the required capital-to-assets ratio
Image Clustering Based on the Human Intelligence

Current clustering algorithms mainly base on calculating distance between items that provides similarity information. But the distance cannot reflect all the correct information between items, which may lead to significant errors. We study the problem of seeking pairwise constraints with crowdsourcing in order to improve clustering results. Crowdsourcing is an emerging and powerful paradigm, which enables the use of background knowledge collecting from users, and image clustering is a relevant and appropriate use case. We propose a framework bringing in human intelligence during the clustering process. The key point of the framework is to choose best questions to perform on the crowdsourcing platform, gather pairwise constraints, and melt the existing algorithm and human input together. As the computation is extensive, we also provide some heuristic optimal methods, including natural transitive relations, to reduce the number of HITs of asking people. We evaluate the framework on real image dataset. The experiment result demonstrates the algorithm achieves a fairly good performance comparing to the other state-of-theart methods, and the optimized strategies significantly reduce the number of HIT.
On perfect competition in an economy with a coalitional structure

This paper is devoted to the description and the analysis of perfectly competitive economies. From the literature there emerge two main appropaches to perfect competition, both of which try to explain why agents in an exchange economy with a marketsystem or -mechanism are acting as price takers. The Cournotian approach is based on limit results, which state that in growing economies the Cournotand~or Bertrand-competitive oligopolistic equilibria are converging to perfectly competitive Walrasian equilibria. The Edgeworthan approach is based on the Core-Walras-equivalence theory, which investigates under which conditions certain core-like cooperative equilibrium concepts are equivalent to the Walrasian competitive equilibrium concept. Our paper is written from the Edgeworthan point of view. We analyse the conditions under which the semi-core, as developed in our previous paper Gilles (198~), and the Walrasian equilibrium in a pure exchange economy with a coalitional structure of agents are equivalent. We compare the atomlessness condition with a property directly describing the notion of perfect competition. Thus we are testing Aumann's statement that an atomless economy is the natural expression of a perfectly competitive economy. (Aumann (1964). ) Through this comparison we introduce the Cournotian approach into our analysis. We are able to prove, as one would expect, that both approaches to perfect competition are equivalent. It also turns out that atomlessness is usually a much stronger condition than perfectly competitiveness only.
10 th International Workshop on Uncertainty Reasoning for the Semantic Web ( URSW 2014 )

OWL ontologies have gained great popularity as a context modelling tool for intelligent environments due to their expressivity. However, they present some disadvantages when it is necessary to deal with uncertainty, which is common in our daily life and affects the decisions that we take. To overcome this drawback, we have developed a novel framework to compute fact probabilities from the axioms in an OWL ontology. This proposal comprises the definition and description of our probabilistic ontology. Our probabilistic ontology extends OWL 2 DL with a new layer to model uncertainty. With this work we aim to overcome OWL limitations to reason with uncertainty, developing a novel framework that can be used in intelligent environments.
Correctness Proof of a BDD Manager in the Context of Satisfiability Checking

We present a compositional proof of correctness for a binary decision diagram (BDD) manager used in the context of a propositional satissability checker implemented using Single-Threaded Objects (stobjs) in ACL2. The use of stobjs aaords the deenition of an eecient BDD manager which ensures unique construction, allows constant-time comparison, and caches previously computed results. The use of ACL2 means we can prove that the BDD manager implements the prescribed task of building a normal-form representation of a boolean formula. We divide the proof requirements into (1) showing that a simpler set of BDD functions is correct, and (2) showing that the stobj-based BDD functions return values consistent with these simpler functions. We conclude the paper with a discussion of future extensions and reenements to the BDD manager presented.
ERROR CONCEALMENT TECHNIQUES IN MPEG-2

The MPEG-2 compression algorithm, due to the use of variable length coding, is very sensitive to channel disturbances. A single bit error during transmission leads to noticeable degradation of the decoded sequence quality in that part or entire slice information is lost until the next resynchronization point is reached. Error concealment (EC) methods are employed at the decoder side to deal with this problem. A novel concealment scheme is proposed in this paper that uses spatial or, when available, temporal information to reconstruct the corrupted frames. The concealment strategy is embedded in the MPEG-2 decoder model to avoid further concealment of propagation errors. The proposed scheme is proved to be of better performance compared to that achieved by other error concealment (EC) methods. Furthermore, the quality of the concealed sequence seems to ameliorate with time.
Emotions in Finance: Booms, Busts and Uncertainty

1. Modern money, modern conflicts 2. Corporate suspicion in the kingdom of rationality 3. Financial press as trust agencies 4. Required distrust and the onus of a bonus 5. Managing credibility in central banks 6. Hierarchies of distrust from trust to bust 7. Overwhelmed by numbers 8. The time-utopia in finance.
Eyes Wide Open

Research from evolutionary psychology suggests that the mere presence of eye images can promote prosocial behavior. However, the “eye images effect” is a source of considerable debate, and findings across studies have yielded somewhat inconsistent support. We suggest that one critical factor may be whether the eyes really need to be watching to effectively enhance prosocial behavior. In three experiments, we investigated the impact of eye images on prosocial behavior, assessed in a laboratory setting. Participants were randomly assigned to view an image of watching eyes (eyes with direct gaze), an image of nonwatching eyes (i.e., eyes closed for Study 1 and averted eyes for Studies 2 and 3), or an image of flowers (control condition). Upon exposure to the stimuli, participants decided whether or not to help another participant by completing a dull cognitive task. Three independent studies produced somewhat mixed results. However, combined analysis of all three studies, with a total of 612 participants, showed that the watching component of the eyes is important for decision-making in this context. Images of watching eyes led to significantly greater inclination to offer help as compared to images of nonwatching eyes (i.e., eyes closed and averted eyes) or images of flowers. These findings suggest that eyes gazing at an individual, rather than any proxy to social presence (e.g., just the eyes), serve as a reminder of reputation. Taken together, we conclude that it is “eyes that pay attention” that can lift the veil of anonymity and potentially facilitate prosocial behavior.
A mechanically coupled reaction–diffusion model for predicting the response of breast tumors to neoadjuvant chemotherapy

There is currently a paucity of reliable techniques for predicting the response of breast tumors to neoadjuvant chemotherapy. The standard approach is to monitor gross changes in tumor size as measured by physical exam and/or conventional imaging, but these methods generally do not show whether a tumor is responding until the patient has received many treatment cycles. One promising approach to address this clinical need is to integrate quantitative in vivo imaging data into biomathematical models of tumor growth in order to predict eventual response based on early measurements during therapy. In this work, we illustrate a novel biomechanical mathematical modeling approach in which contrast enhanced and diffusion weighted magnetic resonance imaging data acquired before and after the first cycle of neoadjuvant therapy are used to calibrate a patient-specific response model which subsequently is used to predict patient outcome at the conclusion of therapy. We present a modification of the reaction–diffusion tumor growth model whereby mechanical coupling to the surrounding tissue stiffness is incorporated via restricted cell diffusion. We use simulations and experimental data to illustrate how incorporating tissue mechanical properties leads to qualitatively and quantitatively different tumor growth patterns than when such properties are ignored. We apply the approach to patient data in a preliminary dataset of eight patients exhibiting a varying degree of responsiveness to neoadjuvant therapy, and we show that the mechanically coupled reaction–diffusion tumor growth model, when projected forward, more accurately predicts residual tumor burden at the conclusion of therapy than the non-mechanically coupled model. The mechanically coupled model predictions exhibit a significant correlation with data observations (PCC = 0.84, p < 0.01), and show a statistically significant >4 fold reduction in model/data error (p = 0.02) as compared to the non-mechanically coupled model.
SuperSQL: an extended SQL for database publishing and presentation

SuperSQL is an extension of SQL that allows query results presented in various media for publishing and presentations with simple but sophisticated formatting capabilities. SuperSQL query can generate various kinds of materials, for example, a LaTeX source file to publish query results in a nested table, HTML or Java source files to present the result on WWW browsers, and other media including MS-Excel worksheet, Tcl/Tk, O2C, etc. O2C is a data manipulation language of O2 and thus useful to migrate data in a relational database to an object oriented database. SuperSQL is meant to provide a theoretical and practical foundation for 4GL-type applications such as report writers and DB/WWW coordinators. In this demonstration, we show how TFE reorganize the query results into various media in a universal way, first by grouping tuples according to an arbitrary tree structured schema, and by translating them with the constructors available in the target media.
F ¨ Ur Mathematik in Den Naturwissenschaften Leipzig Lower Semi-continuity and Existence of Minimizers in Incremental Finite-strain Elastoplasticity

Lower semi–continuity and existence of minimizers in incremental finite-strain elastoplasticity Abstract We study incremental problems in geometrically nonlinear elastoplasticity. Using the multiplicative decomposition Dϕ = F el F pl we consider general energy functionals of the form which occur as the sum of the stored energy and the dissipation in one time step. Here G(F pl) is the dislocation tensor which takes the form 1 det F pl curl 3 (F pl) F T pl in dimension d = 3. Imposing the usual constraint det F pl ≡ 1 and suitable growth and polyconvexity conditions on U we show that the minimum of I is attained in the natural Sobolev spaces. Moreover, we are able to treat multiple time steps by controlling the stored and dissipated energies. We also address the relation of the incremental problem to the time-continuous energetic formulation of elastoplasticity.
Building the public city : the politics, governance, and finance of public infrastructure

Building the Public City - David C Perry An Introduction Politics and the Engineering Mind - Jameson W Doig O H Ammann and the Hidden Story of the George Washington Bridge Economic Development and Infrastructure - Robert Mier Planning in the Context of Progressive Politics Conditions of Confusion and Conflict - Claire L Felbinger Rethinking the Infrastructure-Economic Development Linkage Public Infrastructure and Special Purpose Governments - James Leigland Who Pays and How Public Works and Public Dollars - Heywood T Sanders Federal Infrastructure Aid and Local Investment Policy Building the City through the Backdoor - David C Perry The Politics of Debt, Law and Public Infrastructure
Drug-metabolism-based automatic segmentation of dynamic scintigraphic images

Quantitative dynamic scintigraphic image studies provide in vivo measurements of dynamic physiological and biochemical processes in humans. Segmentation of scintigraphic images is one of the most important steps to distinguish organs of interest from the background. However, poor spatial resolution and signal-to-noise ratio (SNR) of scintigraphic images make accurate organ boundary segmentation difficult. In scintigraphic image studies, areas of specific binding are usually segmented by manually drawing regions of interest (ROIs), which is a time-consuming and subjective process. In this work, we describe a method to automatically segment 99mTc-GSA dynamic scintigraphic images based on the prior knowledge of drug metabolism, including the drug flow mechanism and the time of activity curves (TACs). Our results suggest that drug-metabolism-based segmentation can automatically segment tissues in dynamic scintigraphic images studies and has the potential to replace manual ROI segmentation for our application.
Title Stata.com Arfima — Autoregressive Fractionally Integrated Moving-average Models

Syntax Menu Description Options Remarks and examples Stored results Methods and formulas References Also see Syntax arfima depvar indepvars if in , options options Description Model noconstant suppress constant term ar(numlist) autoregressive terms ma(numlist) moving-average terms smemory estimate short-memory model without fractional integration mle maximum likelihood estimates; the default mpl maximum modified-profile-likelihood estimates constraints(numlist) apply specified linear constraints collinear do not drop collinear variables SE/Robust vce(vcetype) vcetype may be oim or robust Reporting level(#) set confidence level; default is level(95) nocnsreport do not display constraints display options control column formats, row spacing, line width, display of omitted variables and base and empty cells, and factor-variable labeling
Methods for human evaluation of machine translation

Evaluation of machine translation (MT) is a difficult task, both for humans, and using automatic metrics. The main difficulty lies in the fact that there is not one single correct translation, but many alternative good translation options. MT systems are often evaluated using automatic metrics, which commonly rely on comparing a translation to only a single human reference translation. An alternative is different types of human evaluations, commonly ranking between systems or estimations of adequacy and fluency on some scale, or error analyses. We have explored four different evaluation methods on output from three different statistical MT systems. The main focus is on different types of human evaluation. We compare two conventional evaluation methods, human error analysis and automatic metrics, to two lesser used evaluation methods based on reading comprehension and eyetracking. These two methods of evaluations are performed without the subjects seeing the source sentence. There have been few previous attempts of using reading comprehension and eye-tracking for MT evaluation. One example of a reading comprehension study is Fuji (1999) who conducted an experiment to compare Englishto-Japanese MT to several versions of manual corrections of the system output. He found significant differences between texts with large differences on reading comprehension questions. Doherty and O’Brien (2009) is the only study we are aware of using eye-tracking for MT evaluation. They found that the average gaze time and fixation counts were significantly lower for sentences judged as excellent in an earlier evaluation, than for bad sentences. Like previous research we find that both reading comprehension and eye-tracking can be useful for MT evaluation. The results of these methods are consistent with the other methods for comparison between systems with a big quality difference. For systems with similar quality, however, the different evaluation methods often does not show any significant differences.
Instanton induced open string superpotentials and branes at singularities

We study different aspects of the non-perturbative superpotentials induced by Euclidean E3-branes on systems of D3/D7-branes located at Abelian orbifold singularities. We discuss in detail how the induced couplings are consistent with the U(1) symmetries carried by the D3/D7 branes. We construct different compact and non-compact examples, and show phenomenologically relevant couplings like μ-terms or certain Yukawa couplings generated by these E3 instantons. Some other novel effects are described. We show an example where E3 instantons combine with standard gauge instantons to yield new multi-instanton effects contributing to superpotential, along the lines of ref. [28]. In the case of non-SUSY ZN tachyon-free singularities it is shown how E3-instantons give rise to non perturbative scalar couplings including exponentially suppressed scalar bilinears.
Automated decomposition of access control policies

Modern dynamic distributed information systems need access control policies to address controlling access to multiple resources that are distributed. The resources may be considered as a single abstract hierarchical resource. An access control policy at a high level should be able to define who is allowed to use the resources. At tower levels, the policy will address controlling access to concrete resources. By modelling the resource hierarchy, it is possible that low level policies can be automatically produced from the high level policy. These low level policies can then be distributed to the concrete resources that use an existing policy based access control decision system so that the high level policy can be enforced throughout the system. In this paper a model for representing and refining high level policies is presented. Other relevant issues and examples for demonstrating the capability of the policy decomposition (refinement) process are also presented.
Intent feature discovery using Q&A corpus and web data

User intent in Web search environment is defined as user's information need, and believed to be found by analyzing past data such as queries, click histories and user profiles. However, users may have different intents even in the same queries. In this paper, we attempt to discover the characteristics of intent through finding its features. Our assumption is that if a user expresses the query which clearly points out to certain intent, s/he can reach an intended Web page using that query. We conceptualize this functionality of intent features using intent evolution procedure, called multiple intent model. We collect candidate intent features using Web Q&A corpus analysis, and suggest the automated judgment method using search engine indexes powered by Click Chain Model to demonstrate the adaptability of candidate intent features. Experimental results show that intent features can be extracted efficiently and provide evidences toward intent discovery without human supervision.
Clustering source code files to predict change propagation during software maintenance

This paper addresses the question that is frequently considered by software developers performing maintenance tasks on large systems: "If I make a change in this file, are there other files that need to change too? " If a development tool could automatically answer this question, then time and money could be saved during software maintenance. The proposed solution follows trends from past research results in using data mining techniques and information extracted from the CVS change repository. We define a distance measure using both the revision history of files and text-based information, cluster change sets of files, and then calculate a membership value of each file to each cluster to create groupings of files that are likely to be changed together in the future. Our approach predicts files that may need to be modified based on these clusters, and we evaluate these predictions on portions of the open-source Eclipse project.