Miracle-dz/UniFAR-FTUs huggingface dataset:
A review of the pension systems in Latin America

Latin America is one of the pioneers in introducing individual capitalization schemes as part of their compulsory component of their pension systems. Thirty years have passed since Chile took the ! irst step. Now what reforms have been achieved today? What challenges lie ahead? This paper reviews the motivations of the reforms and their progress, using the experience of Colombia, Chile, Mexico and Peru. The main results are presented in terms of coverage, replacement rates, and ! iscal sustainability, with projections to 2050. The results show that while the reforms of both the public and private pension systems have been key to providing ! iscal sustainability and have strengthened retirement savings for groups with greater permanence in the labour market, there are still many pending challenges in order to address the signi! icant percentage of people who are self-employed, within the informal sector or frequently unemployed. In that sense, for each of the countries studied, recommendations have been explored that could help reduce the level of vulnerability at the retirement stage, incentivize savings, focus resources on the truly poor, and maintain ! iscal balance.
Correcting posteriors by using a feedback synthesis loop in robust ASR

Current Automatic Speech Recognition (ASR) systems are not efficient in noisy speech conditions. We propose a new strategy to reinforce ASR robustness, based on a feedback loop from recognition of posteriors to signal synthesis. The key idea is to use phonemes' posteriors generated by recognition to calculate an acoustic image (AI) at each frame and to calculate its correlation with the input signal. AI is the weighted sum phonemes clean speech spectrum, where weights are directly taken as the corresponding phonemes' posteriors. Correlation between AI and the input spectrum gives a Recognition Index (RI). We then show how a simple correction function of posteriors' distribution using RI improves the Word Error Rate in a continuous speech recognition task compared to a state of the art ASR system (Jrasta).
CoMET: Compressing Microcontroller Execution Traces to Assist System Understanding

Recent technology advances have made possible the retrieval of execution traces on microcontrollers. However, even after a short execution time of the embedded program, the collected execution trace contains a huge amount of data. This is due to the cyclic nature of embedded programs. The huge amount of data makes extremely difficult and time-consuming the understanding of the program behavior. Software engineers need a way to get a quick understanding of execution traces. In this paper, we present an approach based on an improvement of the Sequitur algorithm to compress large execution traces of microcontrollers. By leveraging both cycles and repetitions present in such execution traces, our approach offers a compact and accurate compression of execution traces. This compression may be used by software engineers to understand the behavior of the system, for instance, identifying cycles that appears most often in the trace or comparing different cycles. Our evaluations give two major results. On one hand our approach gives high compression rate on microcontroller execution traces. On the other hand software engineers mostly agree that generated outputs (compressions) may help reviewing and understanding execution traces.
An ω-Algebra for Real-Time Energy Problems

We develop a *-continuous Kleene ω-algebra of real-time energy functions. Together with corresponding automata, these can be used to model systems which can consume and regain energy (or other types of resources) depending on available time. Using recent results on *-continuous Kleene ω-algebras and computability of certain manipulations on real-time energy functions, it follows that reachability and Buchi acceptance in real-time energy automata can be decided in a static way which only involves manipulations of real-time energy functions.
Annexin I is phosphorylated in the multivesicular body during the processing of the epidermal growth factor receptor

We have previously shown that an active epidermal growth factor receptor (EGF-R) kinase is necessary for efficient sorting of the EGF-R to the lysosome, and we have shown that this occurs in the multivesicular body (MVB), where EGF-R are sorted away from recycling receptors by being removed to the internal vesicles of the MVB. The aim of the present study was to identify substrates of the EGF-R kinase associated with MVBs which might play a role in this sorting process. We used a density shift technique to isolate MVBs and show that the major substrates phosphorylated in vitro within MVBs which contain an active EGF-R kinase are the EGF-R itself and annexin I. Annexin I is associated with both plasma membrane and MVBs in a calcium-independent manner but can be phosphorylated in vitro only in MVBs. Phosphorylation of calcium-independent annexin I in isolated MVBs converts it to a form that requires calcium for membrane association. In cells with an active EGF-R kinase the amount of calcium-independent annexin I in MVBs is reduced, suggesting that a phosphorylation-induced conversion of the calcium independent to the calcium-dependent form also occurs in vivo. Our observations, together with the known properties of annexin I in mediating membrane fusion, suggest that inward vesiculation in MVBs is induced by the EGF-R and is mediated by phosphorylated annexin I.
Regulating for Public Health: Motivations for and Efficacy of State Alcohol Regulations

Copyright 2006 by Michelle Mullins, Jeffrey Milyo, and Michael Sykuta. All rights reserved. Readers may not make any copies of this document or use any part of this document without prior consent of the authors. This is a working, preliminary document. For an updated draft please contact Michelle Mullins at mlmfcb@mizzou.edu.
Intuitive visualization of vehicle distance, velocity and risk potential in rear-view camera applications

Many serious collisions on highways happen while changing lanes. One of the main causes for these accidents is the driver's incorrect assessment of the current rear traffic situation. To support the driver, we propose a framework to intuitively visualize distance, speed and risk potential of approaching vehicles in a rear-view camera application. The proposed visualization techniques are based on color coding, artificial motion blur and depth-of-field rendering, which are motivated by sensory effects of the human eye and interpreted intuitively by the human visual system. The impact on the human assessment of the moving speed of an object rendered with artificial motion enhancement is evaluated in a user study. The required distance and motion estimation of the vehicles are extracted out of monocular video images, by combining lane recognition, vehicle detection and segmentation machine vision algorithms.
How the enlargement challenges the institutions - or the existence - of the European Economic Area

In May 2004 the European Union (EU) was enlarged to include ten new member states. In this article, I discuss how the EU enlargement affects the member states of the European Free Trade Association (EFTA). The empirical focus is the impact on the Agreement on the European Economic Area (EEA), which is of key importance in regulating the relationship between the EU and EFTA. I argue that the enlargement process has not challenged fundamentally the existenceof the EEA Agreement nor its institutions. The legality of the agreement has not been challenged, nor has enlargement triggered protests or strong desires for terminating the Agreement. On thecontrary, the enlargement of the EU has been followed by a parallel enlargement of the EEA, and has been warmly supported by the EFTA states. However, I discuss three issues that in the longer run could make the legitimacy and the fulfillment of the principal aims of the EEA more difficult. First, I argue that the enlargement has increased the costs for the EFTA countries. Second, I argue that the enlargement is likely to further reduce the possibility of the EFTAcountries to influence EU decision making. Finally, I argue that the enlargement has increased the administrative heterogeneity in the EU to such an extent that it is likely to challenge the notion of homogeneous implementation and application of rules and regulations.
A Dual-core Embedded System-on-Chip Architecture for Multimedia Signal Processing Applications

This paper presents a dual-core embedded System-on-Chip for a wide range of application fields with particularly high processing demands, including general signal processing, video and audio processing, and a combination of these tasks. It integrates two processor cores and various interfaces onto a single chip, all tied to a 32-bit AMBA AHB bus. The RISC core coordinates the system and performs some reactive tasks, and the DSP core performs transformational tasks with more deterministic and regular behaviors, such as the small and well-defined workloads in multimedia signal processing applications. The DSP core is designed based on Transport Triggered Architecture (TTA) to reduce hardware complexity, get high flexibility and shorten market time. The processor is fabricated in 0.18um standard-cell technology, occupies about 9.7mm, and operates at 266MHz while consuming 670mW average power.
A Reinforcement Learning-based Data-Link Protocol for Underwater Acoustic Communications

We consider an underwater acoustic link where a sender transmits a flow of packets to a receiver through a channel with time varying quality. We address the problem of scheduling packets transmission, forward error correction (FEC) code selection, and channel probing to achieve the best trade-off between energy consumption and latency. Unlike previous works, which assume complete knowledge of the statistics of the underwater acoustic environment, we make the protocol learn the optimal behavior based on experience, without relying on any prior knowledge on the environment. We design a Reinforcement-Learning (RL)-based protocol which learns how to minimize a cost function which is a combination of delay and energy consumption, at the same time ensuring packet delivery. Starting from a basic Q-learning strategy, we design two learning algorithms to speed up learning time, and compare the performance of the proposed solutions with the Q-learning-based strategy and with an aggressive strategy which always transmits all the packets in the buffer. The results show that the proposed techniques outperform the aggressive policy and Q-learning, and are successful in achieving good tradeoffs between energy consumption and packet delivery latency (PDL).
ointing to two imaginary targets at the same time : Bimanual allocentric and gocentric localization in visual form agnosic

We have previously shown the visual form agnosic patient D.F. has spared sensorimotor utilization of visual information relative to her poor perceptual processing of the same stimulus attributes. Her visuomotor skills are, however, only normal when egocentric visual coding can be used in the task. In other words, her egocentric sensorimotor processing is intact while her ‘allocentric’ coding of spatial position is
A STUDY OF THE LOW-MASS X-RAY BINARY DIP SOURCES XB 1916 − 053, XB 1323 − 619, X 1624 − 490 AND 4U 1746 − 371 OBSERVED WITH INTEGRAL

We detect dipping activity/modulations in the light curve of the four low-mass X-ray binaries in the 3–10 keV and 20–40 keV energy ranges. The spectral parameters derived from the fits to the International Gamma-Ray Astrophysics Laboratory data are consistent with hot coronal structures in these systems where we find a range of plasma temperatures 3.0–224.9 keV. The unabsorbed X-ray to soft gamma-ray fluxes between 4 keV and 200 keV are 5.9 × 10−10 erg s−1 cm−2 for XB 1916 − 053, 3.3 × 10−10 erg s−1 cm−2 for XB 1323 − 619, 21.6 × 10−10 erg s−1 cm−2 for X 1624 − 490, and 11.0 × 10−10 erg s−1 cm−2 for 4U 1746 − 371. The optical depth to Compton scattering, τ, varies in a range 4.4–0.002 consistent with electron densities ne < 1.4 × 1015 cm−3. In general, we find no significant difference in the dip and non-dip spectra in the ISGRI energy range (above 20 keV) for all the four sources. We only detect absorption differences between dipping and non-dipping intervals for XB 1916 − 053 and X 1624 − 490 in the JEM-X energy range. Fits in the 4–200 keV range including an additional photoionized absorber model for the two sources show that XB 1916 − 053 has the highest ionized absorber among the two.
Engaging with engagement in an ICT Context

Reviews of research into the educational use of ICT have regularly concluded that there are benefits in terms of increased student engagement. The evidence basis for these claims is varied with engagement being defined in a variety of ways so as to capture elements of student behaviour, interest, motivation, sense of self and much more. Given this variety of definition it is perhaps likely that the evidence base for the claims of positive engagement effects will be equally varied. This paper forms the opening part of a symposium concerned with an exploration of the nature of the claims concerning the benefits of ICT use for the development of student engagement in school and college settings
Optimization of Nested Queries in a Distributed Relational Database

This paper describes how nested queries in the SQL language are processed by R*, an experimental adaptation to the distributed environment of the well-known centralized relational DBMS, System R. Nested queries are queries in which a predicate references the result of another query block (SELECT.FROM.WHERE.), called a subquery block (subQB). SubQBs may themselves contain one or more subQBs. Depending upon whether a subQB references values in other query blocks, it is processed differently, as either an Evaluate-at-Open or Evaluate-at-Application subQB type. Three tasks comprise execution of each query block: initiation, evaluation, and application. When the query’s tables are distributed among multiple sites, optimization of nested queries requires determining for each subQB: the site to perform each task, the protocols controlling interactions between those tasks, and the costs of each option, so that a minimal-cost plan can be chosen. R* optimizes each query block independently, “bottom up”, using only the cost, cardinal&y, and result site of the subQB in the optimization of its containing query block.
The comparision of different visual features on RGB-D mapping

The availability of a map surrounding the robots' workspace is a significant requirement for the autonomous execution of the tasks, such as localization, navigation, and planning. RGB-D cameras can capture the RGB images along with per-pixel depth information from the environment. In this paper, we compare the influence of common visual features (SIFT, SURF, FAST, and GridFAST) with the latest ORB feature in RGB-D mapping system, which is built by combining the optimization algorithm with the visual features, in terms of the processing time, matching capability, and precision, and make exhaustive evaluations using the publicly available datasets. The results of experiments demonstrate that the performances of ORB feature, both in the processing time and the matching accuracy, are better than other features, and RGB-D mapping system based on ORB feature achieves the best real-time and relocalization, which is very important for robots to locate and navigate.
International Exchange Off-Campus. Foreign Students and Local Communities. IIE Research Report Number 13.

international exchange off-campus international exchange off-campus International exchange off-campus. Summary Every year, more than 300,000 foreign students are enrolled in colleges and universities across the United States, yet very little is known about their contacts with the resident population. International exchanges off campus could be significant for both parties. This study examines the amount, type, goals, and consequences of contacts between foreign students and the residents of a local community. Using the case-study approach, we have selected a town and two campuses with attributes that are not uncommon to the foreign student experience. The study site is a college town in the Northeast. It has a homogenous population of about 33,000 residents. There are two campuses in town, a large public university and a small private college. The large school has more than 1,000 foreign students while the small school has fewer than 50 foreign students. Foreign students from many nations have studied in this college town for many decades. Several types of data on contacts between foreign students and townspeople were collected in the period from January to June 1986. A mail survey of the foreign student population produced more than 455 responses. Ten "focus groups" were conducted, involving a total of 89 foreign students. About 50 personal interviews with foreign students, townspeople, campus staff, faculty, and American students also took place. We thus gathered both systematic survey data and qualitative, in-depth information. The key findings are as follows: • Fewer than one in three foreign students surveyed knew "a lot" or "some" town residents by name, although 85 percent perceived town residents as "friendly. " • More than half the foreign students surveyed did not recollect either pleasant or unpleasant encounters with townspeople. One in four mentioned pleasant encounters only, one in eight cited both pleasant and unpleasant contacts, and 7 percent could remember only unpleasant encounters. • Foreign students with town contacts were no more likely than others to have plans to remain in the United States after training was completed. Despite the lack of town encounters, most students said they would recommend the school and area to others from their nation. • Townspeople generally are unaware of the foreign student presence. The vast majority of contacts are business-related, and these casual encounters are largely friendly. A group of about 100 townspeople participate in more regular, formalized activities with foreign students. These activities include a host-family program, a …
QoE-aware Rate-Conservative dynamic HTTP streaming over mobile cellular networks

In this paper we investigate the design of DASH stream-switching solution suitable for mobile cellular video streaming consumers. Our goal is to design a solution that reduces the amount of downloaded content while adhering to user preferences regarding received video quality. We firstly present a graphical (trellis-like) representation of a stream-switching process, and then investigate different approaches to search for an optimal path through a “stream-switching graph” using suitably defined utility function. We target our search towards the path that will: i) respect underlying wireless-link rate limitations, ii) maintain segment selection that is efficient in terms of the quality vs the amount of the downloaded data, and iii) reduce disturbing quality variations. The simulation results demonstrate the performance of the proposed QoE-aware Rate-Conservative (QaRC) DASH as compared to the recently proposed baseline stream-switching solution.
Computational Community Interest and Comments Centric Analysis Ranking

Ranking is an important subject in information retrieval, and a variety of techniques and algorithms have been developed to rank the retrieved documents and web pages for a given query. However, ranking is also a challenging task, since it is a dynamic problem, namely a user’s interest toward each query changes from time to time and it is difficult to accurately extract user interest over time. In this paper, we propose an innovative method to extract and weight real time community interested topic for ranking. By generating community interest vector (CIV), we compute the probability score that community interests in specific document or web page in the search results based on daily or past few hours user-oriented data, and use this score for ranking.
Minimizing Value-at-Risk methodology under fuzzy-stochastic approach

This paper describes new models for portfolio selection under uncertainty with risk and vagueness aspects which are solved by fuzzy-stochastic methodology. And the corresponding optimal portfolio is derived using minimizing Value-at-risk(VaR). The VaR concept has been extended to the portfolio value-at-risk measure used for managing risk and returns under a multiple-asset portfolio. An approach to modeling risks by VaR under imprecise and fuzzy conditions is discussed. It is supposed that the input data and problem conditions is difficult to determine as real numbers or as some precise distribution functions. Thus, vagueness is modeling through the fuzzy numbers. A numerical example of a portfolio selection problem is given to illustrate our proposed approaches.
Regulatory Burdens and International Income Performance

Many studies indicate that excessive regulatory burdens can hamper national economic performances. In spite of that, there are relatively few empirical estimates of the potential income gains that may accrue to countries that deregulate their business sectors. This paper partially fills that gap in the literature by using World Bank data to estimate the relationships between various measures of national regulatory burdens and per capita incomes. Potential impacts of deregulation and greater transparency on income performance are also estimated for the various countries in the sample.
Depth-Scaled Biased Stochastic Sampling

Several techniques have recently been developed that are based on discrepancy analysis in heuristic-based search trees. We offer a comparison of two of these proposed techniques: depth-bounded discrepancy search (DDS) and heuristic-biased stochastic sampling (HBSS), and one new technique, depth-scaled biased stochastic sampling (DSBSS). The new technique uses the framework of HBSS, but takes into account that mistakes are less likely to occur deep in a search tree. Through this comparison, we show that DSBSS performs systematically better than HBSS, and quickly approaches DDS when finding a goal in a limited amount of search.
Multiplicative Dynamics Underlie the Emergence of the Log-Normal Distribution of Spine Sizes in the Neocortex In Vivo

What fundamental properties of synaptic connectivity in the neocortex stem from the ongoing dynamics of synaptic changes? In this study, we seek to find the rules shaping the stationary distribution of synaptic efficacies in the cortex. To address this question, we combined chronic imaging of hundreds of spines in the auditory cortex of mice in vivo over weeks with modeling techniques to quantitatively study the dynamics of spines, the morphological correlates of excitatory synapses in the neocortex. We found that the stationary distribution of spine sizes of individual neurons can be exceptionally well described by a log-normal function. We furthermore show that spines exhibit substantial volatility in their sizes at timescales that range from days to months. Interestingly, the magnitude of changes in spine sizes is proportional to the size of the spine. Such multiplicative dynamics are in contrast with conventional models of synaptic plasticity, learning, and memory, which typically assume additive dynamics. Moreover, we show that the ongoing dynamics of spine sizes can be captured by a simple phenomenological model that operates at two timescales of days and months. This model converges to a log-normal distribution, bridging the gap between synaptic dynamics and the stationary distribution of synaptic efficacies.