Miracle-dz/UniFAR-FTUs huggingface dataset:
A basic social security competition model

We determine the conditions for social security competition in a standard Dixit-Stiglitz two-region model of international trade in which we allow for endogenous unemployment and governments subject to an Atkinson equity-efficiency trade-off. We show that whether social policies are strategic complements or subsitutes depends on the inequality aversion of the governments and the substitution elasticity of the goods. When trade in goods is the only mechanism of economic integration and the number of varieties is exogenously given, the interaction between the social policies occurs through the regional price indices. Hence, economic integration allows to externalise part of the price increase that higher social allowances imply. As a consequence, in this framework a social planner would opt for lower taxes and benefits. ∗Ghent University, Faculty of Economics and Business Administration and SHERPPA, Belgium †Ghent University, Faculty of Economics and Business Administration, Belgium Corresponding author : Glenn Rayp, Ghent University, Faculty of Economics and Business Administration, Hoveniersberg 24, B-9000 Ghent, Belgium
Living in the Garden of Eden: Mineral Resources Foster Individualism

Using mineral resources discoveries in the United States since 1800, we argue that mineral mining fosters individualism. Measuring individualism and the demand for redistribution by questions of the General Social Survey (GSS), we show that: (i) individuals living in states with mineral resources are more individualistic and support less redistribution by the government ; (ii) the higher the number of mines in a states, the lower the support for governmental redistribution and the higher the individualism ; (iii) individuals that experienced mineral discoveries during their early adulthood are more individualistic and support less redistribution ; (iv) this effect vanishes over time. These results are robust to the introduction of various explanatory variables that may explain the formation of individualistic values.
Optimizing brain tissue contrast with EPI: A simulated annealing approach

A new magnetization preparation and image acquisition scheme was developed to obtain high‐resolution brain images with optimal tissue contrast. The pulse sequence was derived from an optimization process using simulated annealing, without prior assumptions with regard to the number of radiofrequency (RF) pulses and flip angles. The resulting scheme combined two inversion pulses with the acquisition of three images with varying contrast. The combination of the three images allowed separation of gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) based on T1, contrast. It also enabled the correction of small errors in the initial T1 estimates in postprocessing. The use of three‐dimensional (3D) sensitivity‐encoded (SENSE) echo‐planar imaging (EPI) for image acquisition made it possible to achieve a 1.153 mm3 isotropic resolution within a scan time of 10 min 21 s. The cortical GM signal‐to‐noise ratio (SNR) in the calculated GM‐only image varied between 30 and 100. The novel technique was evaluated in combination with blood oxygen level‐dependent (BOLD) functional magnetic resonance imaging (fMRI) on human subjects, and provided for excellent coregistration of anatomical and functional data. Magn Reson Med 54:373–385, 2005. Published 2005 Wiley‐Liss, Inc.
Bayesian Optimization using Student-t Processes

Finding the global minimum of a function is often difficult. We consider efficiently minimizing functions which are computationally expensive to evaluate. A Bayesian approach to the global function optimization problem places a prior distribution on the function and chooses where to evaluate the function based on its posterior distribution given a set of observations. While many recent applications use Gaussian processes as a prior for the objective function, here we show that a Student-t process is an ideal prior for such a problem, as it is also nonparametric, but naturally models heavy tailed behaviour and has a predictive covariance which explicitly depends on observations. 1 The Student-t Process We begin by deriving the Student-t process1, and its marginal likelihood and predictive distribution, starting from a hierarchical Gaussian process model. We define a prior over continous functions using the following generative model r−1 ∼ Γ (ν 2 , ρ 2 ) y|r ∼ GP ( 0, r(ν − 2)k/ρ ) , (1) where ν > 2, ρ > 0 and k : R × R → R is a kernel function. If we marginalize over r, y is a scaled mixture of Gaussian processes. Suppose y = (y1, ., yN ) is a finite collection of observations at input points x1, . ,xN ∈ R and let K be the Gram matrix such that Kij = k(xi,xj). We can compute the marginal probability of these observations under the generative prior above as follows p(y) = ∫ p(y|r)p(r)dr = (π(ν − 2)) −N/2(ρ/2) ν+N 2 |K|1/2Γ(ν/2) ∫ r−(ν+N)/2−1 exp ( − ρ 2r ( 1 + y>K−1y ν − 2 )) dr = (π(ν − 2))−N/2 Γ((ν +N)/2) Γ(ν/2) |K|−1/2 ( 1 + y>K−1y ν − 2 )−(ν+N)/2 . (2) The Student-t process [O’Hagan, 1991, O’Hagan et al., 1999] has been used in a number of applications [Yu et al., 2007, Zhang and Yeung, 2010, Xu et al., 2011]. Our parameterization differs slightly from previous constructions.
Consistent Specification Tests for Semiparametric / Nonparametric Models Based on Series Estimation Methods ∗

This paper considers the problem of consistent model specification tests using series estimation methods. The null models we consider in this paper all contain some nonparametric components. A leading case we consider is to test for an additive partially linear model. The null distribution of the test statistic is derived using a central limit theorem for Hilbert valued random arrays. The test statistic is shown to be able to detect local alternatives that approach the null models at the order of Op(n−1/2). We suggest to use the wild bootstrap method to approximate the critical values of the test. A small Monte Carlo simulation is reported to examine the finite sample performance of the proposed test. We also show that the proposed test can be easily modified to obtain series-based consistent tests for other semiparametric/nonparametric models.
Global Tactical Sector Allocation: A Quantitative Approach

Doeswijk and vanVliet examine seven variables for global tactical sector allocation (GTSA) purposes. They construct 10 global sector indices over the extended sample period from 1970 to 2008, enabling them to test previously documented variables on a global basis and to examine whether they continued to work after their publication dates. Doeswijk and van Vliet document significant returns for the following strategies: momentum (1-month and 12–1 month), earnings revisions, and sell-in-May seasonal, also after their publication dates. By contrast, monetary policy and valuation (mean reversion and dividend yield) fail to predict global sector returns. The authors’ out-of-sample tests reveal an average decay in performance of about one-third. A long–short GTSA strategy that combines momentum with seasonal has an annual success ratio of 82% and delivers a compounded annual return of 9.9% after transaction costs. The authors believe that a global sector allocation study with such a long sample period and with such a broad range of variables has not been conducted before.
Estimation of a dynamic discrete choice model of irreversible investment

In this paper we propose and estimate a dynamic structural model of fixed capital investment at the firm level. Our dataset consists of an unbalanced panel of Spanish manufacturing firms. Two important features are present in this dataset. There are periods in which firms decide not to invest and periods of large investment episodes. These empirical evidence of infrequent and lumpy investment provides evidence in favour of irreversibilities and nonconvex capital adjustment costs. We consider a dynamic discrete choice model of irreversible investment with a general specification of adjustment costs including convex and nonconvex components. We use a two stage estimation procedure. In a first stage, we obtain GMM estimates of technological parameters. In the second stage, we obtain partial maximum likelihood estimates for the adjustment cost parameters. The estimation strategy builds on the representation of conditional value functions as a computable function of conditional choice probabilities. It is in the line of structural estimation techniques which avoid the solution of the dynamic programming problem.
Stemming resource-poor Indian languages

Stemming is a basic method for morphological normalization of natural language texts. In this study, we focus on the problem of stemming several resource-poor languages from Eastern India, viz., Assamese, Bengali, Bishnupriya Manipuri and Bodo. While Assamese, Bengali and Bishnupriya Manipuri are Indo-Aryan, Bodo is a Tibeto-Burman language. We design a rule-based approach to remove suffixes from words. To reduce over-stemming and under-stemming errors, we introduce a dictionary of frequent words. We observe that, for these languages a dominant amount of suffixes are single letters creating problems during suffix stripping. As a result, we introduce an HMM-based hybrid approach to classify the mis-matched last character. For each word, the stem is extracted by calculating the most probable path in four HMM states. At each step we measure the stemming accuracy for each language. We obtain 94% accuracy for Assamese and Bengali and 87%, and 82% for Bishnupriya Manipuri and Bodo, respectively, using the hybrid approach. We compare our work with Morfessor [Creutz and Lagus 2005]. As of now, there is no reported work on stemming for Bishnupriya Manipuri and Bodo. Our results on Assamese and Bengali show significant improvement over prior published work [Sarkar and Bandyopadhyay 2008; Sharma et al. 2002, 2003].
A Transition-Based Parser for 2-Planar Dependency Structures

Finding a class of structures that is rich enough for adequate linguistic representation yet restricted enough for efficient computational processing is an important problem for dependency parsing. In this paper, we present a transition system for 2-planar dependency trees -- trees that can be decomposed into at most two planar graphs -- and show that it can be used to implement a classifier-based parser that runs in linear time and outperforms a state-of-the-art transition-based parser on four data sets from the CoNLL-X shared task. In addition, we present an efficient method for determining whether an arbitrary tree is 2-planar and show that 99% or more of the trees in existing treebanks are 2-planar.
REPLICATE PATTERNS OF SPECIES RICHNESS, HISTORICAL BIOGEOGRAPHY, AND PHYLOGENY IN HOLARCTIC TREEFROGS

Abstract In recent decades, the field of historical biogeography has become increasingly divorced from evolutionary biology, ecology, and studies of species richness. In this paper, we explore the evolutionary causes of patterns of biogeography and species richness in Northern Hemisphere treefrogs, combining phylogenetics, ancestral area reconstruction, molecular dating methods, and ecological niche modeling. We reconstructed phylogenetic relationships among 58 hylid taxa using data from two mitochondrial genes (12S, ND1) and two nuclear genes (POMC, c-myc). We find that parallel patterns of species richness have developed in Europe, Asia, and in two separate clades of North American hylids, with the highest richness at midtemperate latitudes (30–35°) on each continent. This pattern is surprising given that hylids overall show higher species richness in the New World tropics and given many standard ecological explanations for the latitudinal diversity gradient (e.g., energy, productivity, mid-domain effect). The replicate pattern in Holarctic hylids seems to reflect specialized tolerance for temperate climate regimes or possibly the effects of competition. The results also suggest that long-range dispersal between continental regions with similar climatic regimes may be easier than dispersal between geographically adjacent regions with different climatic regimes. Our results show the importance of ecology and evolution to large-scale biogeography and the importance of large-scale biogeography to understanding patterns of species richness.
Experiments with three approaches to recognizing lexical entailment

Abstract Inference in natural language often involves recognizing lexical entailment (RLE), that is, identifying whether one word entails another. For example, buy entails own. Two general strategies for RLE have been proposed: One strategy is to manually construct an asymmetric similarity measure for context vectors (directional similarity) and another is to treat RLE as a problem of learning to recognize semantic relations using supervised machine-learning techniques (relation classification). In this paper, we experiment with two recent state-of-the-art representatives of the two general strategies. The first approach is an asymmetric similarity measure (an instance of the directional similarity strategy), designed to capture the degree to which the contexts of a word, a, form a subset of the contexts of another word, b. The second approach (an instance of the relation classification strategy) represents a word pair, a: b, with a feature vector that is the concatenation of the context vectors of a and b, and then applies supervised learning to a training set of labeled feature vectors. In addition, we introduce a third approach that is a new instance of the relation classification strategy. The third approach represents a word pair, a: b, with a feature vector in which the features are the differences in the similarities of a and b to a set of reference words. All three approaches use vector space models of semantics, based on word–context matrices. We perform an extensive evaluation of the three approaches using three different datasets. The proposed new approach (similarity differences) performs significantly better than the other two approaches on some datasets and there is no dataset for which it is significantly worse. Along the way, we address some of the concerns raised in past research, regarding the treatment of RLE as a problem of semantic relation classification, and we suggest, it is beneficial to make connections between the research in lexical entailment and the research in semantic relation classification.
Memory-system Design Considerations For Dynamically-scheduled Processors

In this paper, we identify performance trends and design relationships between the following components of the data memory hierarchy in a dynamically-scheduled processor: the register file, the lockup-free data cache, the stream buffers, and the interface between these components and the lower levels of the memory hierarchy. Similar performance was obtained from all systems having support for fewer than four in-flight misses, irrespective of the register-file size, the issue width of the processor, and the memory bandwidth. While providing support for more than four in-flight misses did increase system performance, the improvement was less than that obtained by increasing the number of registers. The addition of stream buffers to the investigated systems led to a significant performance increase, with the larger increases for systems having less in-flight-miss support, greater memory bandwidth, or more instruction issue capability. The performance of these systems was not significantly affected by the inclusion of traffic filters, dynamic-stride calculators, or the inclusion of the per-load non-unity stride-predictor and the incremental-prefetching techniques, which we introduce. However, the incremental prefetching technique reduces the bandwidth consumed by stream buffers by 50% without a significant impact on performance.
Electromigration of single-layer clusters

Single-layer atom or vacancy clusters in the presence of electromigration are studied theoretically assuming an isotropic medium. A variety of distinctive behaviors distinguish the response in the three standard limiting cases of periphery diffusion (PD), terrace diffusion, and evaporation-condensation. A general model provides power laws describing the size dependence of the drift velocity in these limits, consistent with established results in the case of PD. The validity of the widely used quasistatic limit is calculated. Atom and vacancy clusters drift in opposite directions in the PD limit but in the same direction otherwise. In absence of PD, linear stability analysis reveals a different type of morphological instability, not leading to island breakdown. For strong electromigration, Monte Carlo simulations show that clusters then destabilize into slits, in contrast to splitting in the PD limit. Electromigration affects the diffusion coefficient of the cluster and morphological fluctuations, the latter diverging at the instability threshold. An intrinsic attachment-detachment bias displays the same scaling signature as PD in the drift velocity.
One line and <italic>ε</italic>

We analyze a randomized pivoting process involving one line and <italic>n</italic> points in the plane. The process models the behavior of the <italic>Random-Edge</italic> simplex algorithm on simple polytopes with <italic>n</italic> facets in dimension <italic>n-2</italic>. We obtain a tight <italic>O(\log^2 n)</italic> bound for the expected number of pivot steps. This is the first nontrivial bound for <italic>Random-Edge</italic> which goes beyond bounds for specific polytopes. The process itself can be interpreted as a simple algorithm for certain 2-variable linear programming problems, and we prove a tight <italic>&thgr;(n)</italic> bound for its expected runtime. The combinatorial structure behind the process is a directed graph over pairs of points, with arc orientations induced by the pivot steps. We characterize the class of graphs arising from one line and <italic>n</italic> points, up to oriented matroid realizability.
Dynamic Procurement, Quantity Discounts, and Supply Chain Efficiency

We study a model with a single supplier and a single buyer who interact multiple times before the buyer sells her product in the end‐consumer market. We show that when the supplier uses a wholesale price contract, even under perfect foresight, the supplier, the buyer, and the end consumers benefit from multiple trading opportunities versus a one‐shot procurement agreement.
Time-predictable chip-multiprocessor design

Real-time systems need time-predictable platforms to enable static worst-case execution time (WCET) analysis. Improving the processor performance with superscalar techniques makes static WCET analysis practically impossible. However, most real-time systems are multi-threaded applications and performance can be improved by using several processor cores on a single chip. In this paper we present a time-predictable chip-multiprocessor system that aims to improve system performance while still enabling WCET analysis. The proposed chip-multiprocessor (CMP) uses a shared memory with a time-division multiple access (TDMA) based memory access scheduling. The static TDMA schedule can be integrated into the WCET analysis. Experiments with a JOP based CMP showed that the memory access starts to dominate the execution time when using more than 4 processor cores. To provide a better scalability, more local memories have to be used. We add a processor local scratchpad memory and split data caches, which are still time-predictable, to the processor cores.
Real-time visual system for interaction with a humanoid robot

We describe a real-time visual system that enables a humanoid robot to learn from and interact with humans. The core of the visual system is a probabilistic tracker that uses shape and color information to find relevant objects in the scene. Multiscale representations, windowing and masking are employed to accelerate the data processing. The perception system is directly coupled with the motor control system of our humanoid robot DB. We present an example of on-line interaction with a humanoid robot: mimicking of human hand motion. The generation of humanoid robot motion based on the human motion is accomplished in real-time. The study is supported by experimental results on DB.
Sleepy Eye's Recognition for Drowsiness Detection

With the progress of science technology and the vehicle industry, there are more and more vehicles on the road. As a result, the heavy traffic often leads to more and more traffic accidents. In common traffic accident, the driver's inattention is usually a main reason. To avoid this situation, this paper proposes a sleepy eye's recognition system for drowsiness detection. First, a cascaded Adaboost classifier with the Haar-like features is utilized to find out the face region. Second, the eyes region is located by Active Shape Models(ASM) search algorithm. Then the binary pattern and edge detection are adopted to extract the eyes feature and determine the eye's state. Experimental results demonstrate the comparative performance, even without the training stage, with other methods.
Sources of variation of articulation rate in native and non-native speech: comparisons of French and German

This paper describes our exploratory work in applying the Automatic ToBI annotation system (AuToBI), originally developed for Standard American English, to European Portuguese. This work is motivated by the current availability of large amounts of (highly spontaneous) transcribed data and the need to further enrich those transcripts with prosodic information. Manual prosodic annotation, however, is almost impractical for exten-sive data sets. For that reason, automatic systems such as AuToBi stand as an alternate solution. We have started by applying the AuToBI prosodic event detection system using the existing English models to the prediction of prominent prosodic events (accents) in European Portuguese. This approach achieved an overall accuracy of 74% for prominence detection, similar to state-of-the-art results for other languages. Later, we have trained new models using prepared and spontaneous Portuguese data, achieving a considerable improvement of about 6% accuracy (absolute) over the existing English models. The achieved results are quite encouraging and provide a starting point for automatically predicting prominent events in European Portuguese.
Allais-anonymity as an alternative to the discounted-sum criterion in the calculus of optimal growth I: Consensual optimality

The objective of this work is to try to define and calculate the optimal growth path, in the presence of exogenous technical change, without resorting to the discounted-sum criterion. The solution suggested is to consider an optimality criterion expressing an Allais-anonymous intergenerational consensus. The partial characterization of consensual optimality was made possible thanks to the decomposition of the dual of the space of sub-geometric sequences of reason p. The main finding is a relation between the marginal rate of substitution between bequest and heritage, and the growth rate, relation which is a necessary condition for consensual optimality. The necessary study of the Pareto-optimality of the consensual optimum is the subject of a forthcoming paper "Allais-anonymity as an alternative to the discounted-sum criterion in the calculus of optimal growth II: Pareto optimality and some economic interpretations".
A holistic approach for statistical SRAM analysis

We present a new method and its implementation that enables design-phase assessment of statistical performance metrics of semiconductor memories under random local and global process variations. Engineers use the tool to reduce design margins and to maximize parametric yield. Results on industry grade 45nm SRAM designs show that this holistic approach is significantly more accurate than the alternatives based on global corners or critical path netlist, which can lead to unexpected yield loss.