Miracle-dz/UniFAR-FTUs huggingface dataset:
Sequential Pre-Marital Investment Games: Implications for Unemployment

Agents on the same side of a two-sided matching market (such as the marriage or labor market) compete with each other by making self-enhancing investments to improve their worth in the eyes of potential partners. Because these expenditures generally occur prior to matching, this activity has come to be known in recent literature (Peters, 2007) as pre-marital investment. This paper builds on that literature by considering the case of sequential pre-marital investment, analyzing a matching game in which one side of the market invests first, followed by the other. Interpreting the first group of agents as workers and the other group as firms, the paper provides a new perspective on the incentive structure that is inherent in labor markets. It also demonstrates that a positive rate of unemployment can exist even in the absence of matching frictions. Policy implications follow, as the prevailing set of equilibria can be altered by restricting entry into the workforce, providing unemployment insurance, or subsidizing pre-marital investment.
Determination of a and b site defects on graphite using C 60-adsorbed STM tips

Scanning tunneling microscope images of graphite surfaces obtained using 60 STM tips revealed electron scattering patterns generated by localized defects. For the case where the localized defects are most likely to be single point vacancies, we show that it is possible to distinguish between localized defects at a and b sites, the two inequivalent sites on a graphite lattice. By modeling the graphite with a bilayered carbon cluster using the tight-binding approach, excellent agreement is established between experimentally obtained images and theoretical calculations of electron scattering at a and b site defects. © 1998 Elsevier Science B.V. All rights reserved.
Who Selects the ‘Right’ Directors? An Examination of the Association between Board Selection, Gender Diversity and Outcomes

Using a sample of companies from the top 500 listed firms in Australia, we investigate whether the presence of a designated nomination committee and female representation on the nomination committee affect board gender diversity. We also examine whether gender diversity on the board affects firm risk and financial performance. We find that board gender diversity is significantly and positively associated with the presence of a designated nomination committee and that female representation on the nomination committee is a significant explanatory factor of increasing board gender diversity following the release of the 2010 Australian Securities Exchange Corporate Governance Council (ASXCGC) recommendations. Further, our results support the business case for board gender diversity as we find greater gender diversity moderates excessive firm risk which in turn improves firms' financial performance. Our results are robust after correcting for selection bias and controlling for other board, firm and industry characteristics.
λ-geometry clock tree construction with wirelength and via minimization

λ-geometry routing provides more available routing directions on different metal layers for chip interconnection to reduce wirelength. However, it can lead to a significant increase in via cost. In this paper, we consider lambda-geometry zero-skew clock tree construction with wirelength and via minimization. Our lambda-geometry clock router achieves, on average, a 7.57% wirelength reduction in the Y-architecture and 9.68% in the X-architecture when compared with results in the Manhattan architecture. In addition, we also propose a dynamic programming approach to determine the one-bend routes of the clock edges to optimize the total node via cost of the whole clock tree. Our via minimization algorithm can reduce the total via cost by an average of 17% in the Y-architecture and 37% in the X architecture.
Double edge class BD hybrid DPWM implementation using linearized LBDD algorithm

In the paper we propose a novel architecture and implementation of 10-bit Digital Pulse Width Modulator (DPWM) circuit based on previously known building blocks. Linearized Class-BD Double-sided (LBDD) algorithm has been used to calculate the DPWM signals of the 10-bit resolution hybrid DPWM for a Class-D digital audio amplifier. Noise-shaping process is used to support high fidelity with feasible values of time resolution. The proposed DPWM circuit is composed of two 6-bit counters and one Analog Delay Locked Loop (ADLL) using 4-bit tapped delay line. A dual ADLL employing coarse and fine programmable delay elements has been presented elsewhere [12]. The proposed 10-bit DPWM circuit, at switching frequency of 352.8 kHz, clock frequency of 45 MHz allows to attain SNR of 120 dB and THD of the output signal less than 0,1% within the audio baseband and modulation index of 0.98. Basic verification of circuit manufacturability and simulation results (Monte Carlo analysis) for one CMOS process are presented.
The Case of a Precognition Optical Packet Switch

This paper describes simulation analysis of an optical packet switch that has a limited capability to "see" packets that have not yet arrived at the input port. The goal of the effort is to design a variable-length optical packet switch without random access buffering. Relying on this future information, the switch tries to maximize the number of bytes switched. While we found that this optimization does not improve the throughput significantly, we are currently studying improvements of this architecture that hold greater promise.
Is Rational Speculation in the Presence of Positive Feedback Traders Destabilizing

DeLong (1990a) et al. show that in the presence of positive feedback traders rational speculation can be destabilizing, in that it drives the price of a risky asset above its expected value. A generalization of their seminal model with additional trading dates and an additional informative signal yields further interesting insights: it helps clarify when prices overreact, underreact, or even move in the "wrong" direction; when rational speculation is destabilizing or stabilizing; and whether overreaction is a symptom of market inefficiency or a manifestation of informational efficiency.
Simultaneous Safe Screening of Features and Samples in Doubly Sparse Modeling

The problem of learning a sparse model is conceptually interpreted as the process of identifying active features/samples and then optimizing the model over them. Recently introduced safe screening allows us to identify a part of nonactive features/samples. So far, safe screening has been individually studied either for feature screening or for sample screening. In this paper, we introduce a new approach for safely screening features and samples simultaneously by alternatively iterating feature and sample screening steps. A significant advantage of considering them simultaneously rather than individually is that they have a synergy effect in the sense that the results of the previous safe feature screening can be exploited for improving the next safe sample screening performances, and vice-versa. We first theoretically investigate the synergy effect, and then illustrate the practical advantage through intensive numerical experiments for problems with large numbers of features and samples.
The welfare of poorer older people in Belgium and the Netherlands:An application of quantile regression

On the basis of the SHARE data, we estimate age-conditional quantiles at the 5th, 10th, 15th, 20th, 25th and 50th percentile levels for equivalised gross income, net financial assets and consumption levels, as well as for a (remaining) lifetime utility indicator of people over the age of 50 in Belgium and the Netherlands. We conclude that the poor performance of Belgium in terms of older people’s income, compared with the Netherlands, is mitigated when the consumption figures are considered. However, the picture presented by the wealth figures is more diverse: the median net financial assets position for the 55-70 age group in Belgium is higher than that in the Netherlands, but their relative ranking on the basis of the first quartile value is reversed for several age groups. In terms of lifetime utility, the two countries do equally well. Income and asset poverty do not seem closely related to consumption poverty. Remarkably, the income distribution of the poorer half of older people in Belgium turns out to be skewed to the left, but income inequality is lower in Belgium than in the Netherlands. The reverse holds true for consumption inequality. Wealth inequality is highly skewed to the right in both countries, but no clear conclusions can be drawn about their relative ranking in terms of inequality.
Correlating CDR with other data sources

Currently, the world of digital forensics analysis is dividing into multiple branches, with each branch needing its own specific set of skills and competences. A growing number of best practices for analysing the different media are reported in many publications, such as the Scientific Working Group on Digital Evidence website [1]. The forensics analysis of a video, for example, shares nothing in common (except scientific procedure) with the examination of a mobile content extraction. This ongoing fragmentation of the digital forensics specialisations impacts on the ability to acquire a comprehensive global overview of the entire investigation. The range of data is vast, and thus, selecting the right insight is vital, for example, using a known procedure or tested tool to conduct the investigation, as described in the Computer Forensic Tool Testing Program (CFTT NIST) documentation [2]. CDR (Call Detail Record) analysis is a great source of information, but is sometimes overlooked; the volume of the data seems overwhelming and the lack of a standard model could be discouraging. Combining this massive amount of useful data with other data sources, such as GPS positions, BTS log files, mobile extractions, highway and traffic logs, will provide the investigator with a complete picture of the events. CDR analysis can be the keystone of the digital forensics world, pulling all the elements together to effectively counteract anti-forensics.
Glycobiology of the Olfactory System

The olfactory system is a highly plastic region of the nervous system. Continuous remodeling of neuronal circuits in the olfactory bulb takes place throughout life as a result of constant turnover of primary sensory olfactory neurons in the periphery. Glycoconjugates are very important in olfactory development, regeneration and function. This article deals with different aspects of glycobiology relevant for the olfactory system. Various anatomical, developmental and functional subdivisions of the olfactory system have been labeled with exogenous lectins. The application of reverse lectin histochemistry resulted in the visualization of endogenous lectins, involved in fasciculation of olfactory axons. Numerous glycoproteins, among them members of the immunoglobulin superfamily, the cadherins and integrins as well as different glycolipids and proteoglycans can act as surface adhesion molecules in the olfactory system. The olfactory-specific form of the sialoglycoprotein neural cell adhesion molecule is implicated in olfactory neuronal and axonal guidance. Glycoconjugates including laminin, fibronectin and proteoglycans are abundant components of the olfactory extracellular matrix, influencing neurite outgrowth and cellular migration. Immunohistochemical labeling has revealed occurrence of the carbohydrate differentiation antigen, playing a role in neurulation and morphogenesis of the very early olfactory system. The synaptic vesicle glycoprotein, appearing also early in olfactory development, is used as a marker of olfactory tumors. Finally, membrane and transmembrane glycoconjugates as well as secreted glycoconjugates may act as olfactory receptor molecules.
The Rosenblatt Bayesian Algorithm Learning in a Nonstationary Environment

In this letter, we study online learning in neural networks (NNs) obtained by approximating Bayesian learning. The approach is applied to Gibbs learning with the Rosenblatt potential in a nonstationary environment. The online scheme is obtained by the minimization (maximization) of the Kullback-Leibler divergence (cross entropy) between the true posterior distribution and the parameterized one. The complexity of the learning algorithm is further decreased by projecting the posterior onto a Gaussian distribution and imposing a spherical covariance matrix. We study in detail the particular case of learning linearly separable rules. In the case of a fixed rule, we observe an asymptotic generalization error egpropalpha-1 for both the spherical and the full covariance matrix approximations. However, in the case of drifting rule, only the full covariance matrix algorithm shows a good performance. This good performance is indeed a surprise since the algorithm is obtained by projecting without the benefit of the extra information on drifting
La sociedad a pesar del estado : movimientos sociales y recuperación democrática en el Paraguay

pluralidad de movimientos cuyo carácter diverso les hace vivir en espacios y, en ocasiones, también en tiempos diferentes? ". Las preguntas están planteadas y Arditi y Rodríguez intentan responderlas desde una perspectiva. Al editar este trabajo, EL LECTOR no pretende sino contribuir al gran debate nacional sobre nuestra realidad y tiene abiertas sus puertas para otros, puntos de w»eí*» «^*M» m*»ÍA*>í*t fí*• — . —* *
Acceleration algorithm for CUDA-based face detection

For the traditional CPU facial detection program is difficult to meet the requirements of real-time detection over high definition images, we propose a fast face detection acceleration algorithm based on the Viola-Jones cascade classifier in the Compute Unified Device Architecture (CUDA) platform. We implemented and improved novel parallel methodologies of image integral calculation, scan window processing and the amplification and correction of classifiers. The unbalanced workload problem of irregular tree structure applications could be effectively solved by the window re-mapping technology using in the scan window processing. The experimental results show that, the CUDA program running on an Nvidia GTX 570 graphics card could respectively achieve 17.04, 3.22 times speedup compared with the CPU and Open Source Computer Vision (OpenCV) programs running on an Intel core i7 processor for the 1080p image, while maintaining a similar detection quality.
Acoustic Modeling of Subword Units for Large Vocabulary Speaker Independent Speech Recognition

The field of large vocabulary, continuous speech recognition has advanced to the point where there are several systems capable of attaining between 90 and 95% word accuracy for speaker independent recognition of a 1000 word vocabulary, spoken fluently for a task with a perplexity (average word branching factor) of about 60. There are several factors which account for the high performance achieved by these systems, including the use of hidden Markov models (HMM) for acoustic modeling, the use of context dependent sub-word units, the representation of between-word phonemic variation, and the use of corrective training techniques to emphasize differences between acoustically similar words in the vocabulary. In this paper we describe one of the large vocabulary speech recognition systems which is being developed at AT&T Bell Laboratories, and discuss the methods used to provide high word recognition accuracy. In particular, we focus on the techniques used to obtain acoustic models of the sub-word units (both context independent and context dependent units), and discuss the resulting system performance as a function of the type of acoustic modeling used.
Modeling Personal Preference Using Shopping Behaviors in Ubiquitous Information Environment

We have been developing an experimental prototype system -- Smart Shop, an application of personal information assistance in a shopping context, (1) to find items of users' interest and/or preferences through data observed from users' behaviors in a ubiquitous information environment, (2) to automatically build a user preference model, and (3) to apply the model and provide suitable information service in the real world. Utilizing ubiquitous sensors, we apply three types of observation scopes to model each user's preference. They are microscopic, mezzoscopic, and macroscopic observation scopes. Our system can inject suitable and controlled messages to a user to build up his precise preference model without putting any stress on him. Keyword Information Services, Personal Preference, Smart Shop, Shopping Assistance, Ubiquitous
Vehicle-to-Vehicle Propagation Models With Large Vehicle Obstructions

Vehicle-to-vehicle (V2V) communication is an enabler for improved traffic safety and congestion control. As for any wireless system, the ultimate performance limit is determined by the propagation channel. A particular point of interest is the shadowing effect of large vehicles such as trucks and buses, as this might affect the communication range significantly. In this paper we present measurement results and model the propagation channel, in which a bus acts either as a shadowing object or as a relay between two passenger cars. The measurement setup is based on a Wireless Open-Access Research Platform (WARP) Field-Programmable Gate Array (FPGA) software radio as transmitter and a Tektronix RSA5106A real-time complex spectrum analyzer as receiver. We analyze the influence of the bus location and car separation distance on the path loss, shadowing, small-scale fading, delay spread, and cross correlation. The main effect of the bus is that it is acting as an obstruction creating an additional 15- to 20-dB attenuation and an increase in the root-mean-square delay spread by roughly 100 ns. A Nakagami distribution is found to well describe the statistics of the small-scale fading, by using Akaike's Information Criterion and the Kolmogorov-Smirnov test. The distance dependence of the path loss is analyzed and a stochastic model is developed.
A Survey of Model Reduction by Balanced Truncation and Some New Results

Balanced truncation is one of the most common model reduction schemes. In this note, we present a survey of balancing related model reduction methods and their corresponding error norms, and also introduce some new results. Five balancing methods are studied: (1) Lyapunov balancing, (2) stochastic balancing, (3) bounded real balancing, (4) positive real balancing and (5) frequency weighted balancing. For positive real balancing, we introduce a multiplicative-type error bound. Moreover, for a certain subclass of positive real systems, a modified positive-real balancing scheme with an absolute error bound is proposed. We also develop a new frequency-weighted balanced reduction method with a simple bound on the error system based on the frequency domain representations of the system gramians. Two numerical examples are illustrated to verify the efficiency of the proposed methods.
An Empirical Analysis of the Mexican Term Structure of Interest Rates

Briefly, in one embodiment, the invention is a method for eliminating common subexpressions in an initial SSA intermediate language representation of at least a portion of a computer program. The method includes (a) inserting a phi-node for an unambiguous definition used in an unambiguous subexpression reaching a join point in the initial intermediate language subsequent to the join point; (b) inserting a phi-node for the unambiguous common subexpression; (c) renaming the unambiguous definition and a subsequent use reached by the definition; and (d) renaming the unambiguous common subexpression.
An interactive technique for three-dimensional image registration: validation for PET, SPECT, MRI and CT brain studies.

UNLABELLED A multipurpose three-dimensional registration technique was validated with PET, SPECT, CT and MRI scans, which had been obtained under normal clinical conditions. In contrast to fully automated procedures, this coregistration method is highly interactive, which has the advantage that it does not impose rigid restrictions by data type and by alterations in normal anatomy or brain function resulting from disease. METHODS Basically, a computer program provides a variety of tools to examine the accuracy of coregistration visually and to specify necessary translations and rotations in all three dimensions. Tools and criteria to accept coregistration were applied according to a standardized protocol. Reproducibility was assessed with five independent users on nine pairs of image sets. In two pairs of these image sets, coregistration was repeated three times by each user. RESULTS Depending on the resolution of the images involved, the reproducibility of translation distances ranged from 0.32 to 2.22 mm (s.d.) and of rotation angles from 0.32 to 1.70 degrees. It was always much smaller than the point-spread full-width half maximum of the device with the lower resolution. The accuracy of coregistration was examined using two arbitrarily misplaced image sets. Interindividual and intraindividual variance were similar, which suggested that the influence of subjectivity was not significant. Average displacements after coregistration were 0.43 and 0.29 mm or less for PET and MRI data, respectively, which indicated the absence of a systematic bias. CONCLUSION The results indicate the high reproducibility and accuracy of this three-dimensional coregistration technique, which is comparable or superior to those of automated techniques and methods based on external artificial landmarks.
Real Time Control of a Khepera Robot using Genetic Programming

A computer language is a very general form of representing and specifying an autonomous agent's behavior. The task of planning feasible actions could then simply be reduced to an instance of automatic programming. We have evaluated the use of an evolutionary technique for automatic programming called Genetic Programming (GP) to directly control a miniature robot. To our knowledge, this is the rst attempt to control a real robot with a GP based learning method. Two schemes are presented. The objective of the GP system in our rst approach is to evolve real-time obstacle avoiding behavior. This technique enables real-time learning with a real robot using genetic programming. It has, however, the drawback that the learning time is limited by the response dynamics of the environment. To overcome this problems we have devised a second method, learning from past experiences which are stored in memory. This new system allows a speed-up of the algorithm by a factor of more than 2000. Obstacle avoiding behavior emerges much faster, approximately 40 times as fast, allowing learning of this task in 1.5 minutes. This learning time is several orders of magnitudes faster then comparable experiments with other control architectures. Furthermore, the GP algorithm is very compact and can be ported to the micro-controller of the autonomous mobile miniature robot.