Miracle-dz/UniFAR-FTUs huggingface dataset:
Health Shocks and Compliance in Chile ’ s Defined-Contribution Pension Program ∗

In this paper, I explore the interaction between two of Chile’s main social protection institutions — its defined-contribution pension program and its public insurance program. Although all adults are required to purchase health insurance and contribute 10 percent of their income to their privately administered pension funds by law, the imperfect monitoring characteristic of middle-income countries allows individuals to shirk these requirements. After formulating a model that posits whether health insurance and retirement savings are substitutes or complements, I employ Chile’s under-utilized EPS dataset to estimate the effects of insurance status and health shocks on time-to-noncompliance and find that Chile’s public health insurance fails to fully insure individuals against health shocks but lengthens individuals’ time-to-noncompliance — indicating that health insurance is a complement of retirement savings in good health but a substitute otherwise. Finally, I analyze the policy implications of the results to assess the impact of linking health insurance to pension contributions. ∗This paper and its author owe a tremendous debt of gratitude to Charles Becker for his unwavering support and guidance. I also thank Atila Abdulkadiroglu, David Bravo, Maria Eugenia Genoni, Timur Kuran, Frank Sloan, Alessandro Tarozzi, and Javiera Vásquez Núñez for their helpful comments and suggestions. All errors contained within this paper are mine and mine alone. †Department of Economics, Duke University, 213 Social Sciences Building, PO Box 90097, Durham, NC 27708, email: scott.lustig@duke.edu.
A Publish/Subscribe Middleware for Body and Ambient Sensor Networks that Mediates between Sensors and Applications

Continuing development of an increasing variety of sensors has led to a vast increase in sensor-based telemedicine solutions. A growing range of modular sensors, and the need of having several applications working with those sensors, has led to an equally extensive increase in efforts for system development. In this paper, we present an event-driven middleware for on-body and ambient sensor networks that allows multiple applications to define information types of their interest in a publish/subscribe manner. Incoming sensor data is hereby transformed into the desired data representation which lifts the burden of adapting the application with respect to the connected sensors off the developer's shoulders. Furthermore, an unsupervised on-the-fly reloading of transformation rules from a remote server allows the system's adaptation to future applications and sensors at run-time. Application-specific event channels provide tailor-made information retrieval as well as control over the dissemination of critical information. The system is evaluated based on an Android implementation, with transformation rules implemented as OSGi bundles that are retrieved from a remote web server. Evaluation shows a low impact of running the transformation rules on a phone and highlights the reduced energy consumption by having fewer sensors serving multiple applications. It also points out the behavior and limits of the application-specific event channels with respect to CPU utilization, delivery ratio, and memory usage.
The effect of acute coronary perfusion change on cardiac function measured by Shear Wave Elasticity Imaging

The possibility of measuring cardiac function noninvasively has generated wide interest in elastography imaging techniques. Shear Wave Elasticity Imaging (SWEI) is an ultrasound-based elastography technique used to measure stiffness of tissues. While this technique has been studied extensively in static homogenous tissues such as liver, breast or prostate, there is still a significant need to study its capabilities to measure cardiac stiffness and function. In this research, we have studied the potential of SWEI to evaluate the coronary perfusion pressure effect on systolic and diastolic stiffness referred to as elastance and compliance of the heart. Five isolated rabbit hearts were used in this study in a Langendorff preparation. SWEI measurements of stiffness were recorded in two steps. In the first step, coronary perfusion was set to normal and then was reduced to half-normal. After 40 minutes of half-normal perfusion, it was returned to normal perfusion for the second step. SWEI velocity decreased from 6.003 m/s to 4.713 m/s in systole and from 1.948 m/s to 1.507 m/s in diastole in the first step. During the second step raising the perfusion to normal, SWEI stiffness showed an increase from 3.760 m/s to 5.468 m/s in systole and from 1.678 m/s to 2.156 m/s during diastole. Our results show that SWEI measurements of stiffness can characterize the cross talk between coronary perfusion and cardiac stiffness and also has the potential to measure compliance and elastance of the heart in systole and diastole.
Recycling Energy to Restore Impaired Ankle Function during Human Walking

Background Humans normally dissipate significant energy during walking, largely at the transitions between steps. The ankle then acts to restore energy during push-off, which may be the reason that ankle impairment nearly always leads to poorer walking economy. The replacement of lost energy is necessary for steady gait, in which mechanical energy is constant on average, external dissipation is negligible, and no net work is performed over a stride. However, dissipation and replacement by muscles might not be necessary if energy were instead captured and reused by an assistive device. Methodology/Principal Findings We developed a microprocessor-controlled artificial foot that captures some of the energy that is normally dissipated by the leg and “recycles” it as positive ankle work. In tests on subjects walking with an artificially-impaired ankle, a conventional prosthesis reduced ankle push-off work and increased net metabolic energy expenditure by 23% compared to normal walking. Energy recycling restored ankle push-off to normal and reduced the net metabolic energy penalty to 14%. Conclusions/Significance These results suggest that reduced ankle push-off contributes to the increased metabolic energy expenditure accompanying ankle impairments, and demonstrate that energy recycling can be used to reduce such cost.
Understanding Challenges of Information Security Culture: A Methodological Issue

Although, many organisations have implemented technical solutions to protect information resources from adverse events, internal security breaches continue to occur. Therefore an approach that emphasises an information security culture within the organisation is required to make security a part of employees’ daily work routines. In order to develop a successful information security culture within an organisation, it is a need to understand both technical and non-technical aspects of information security. Thus, this paper aims to investigate and discuss the conceptual and methodological issues pertaining the challenges in information security culture. MAMPU (Malaysian Administrative Modernisation and Management Planning Unit) was chosen as the subject of analysis and to serve as the specific in-depth case study for the investigation. In terms of epistemological approach, the interpretivism paradigm has been adopted as the main strategy in inquiry. For data collection, this research used questionnaire survey, semi-structured interviews, reviews of information security documents and observations. A conceptual framework based on Schein’s (1992) model of organisational culture was also being established to guide the data collection techniques. This paper, basically, is an attempt to academically overview and justifies the conceptual and methodological decisions in each procedure, which is outlined above.
Locally Estimated Hemodynamic Response Function and Activation Detection Sensitivity in Heroin-Cue Reactivity Study

Introduction: A fixed hemodynamic response function (HRF) is commonly used for functional magnetic resonance imaging (fMRI) analysis. However, HRF may vary from region to region and subject to subject. We investigated the effect of locally estimated HRF (in functionally homogenous parcels) on activation detection sensitivity in a heroin cue reactivity study. Methods: We proposed a novel exploratory method for brain parcellation based on a probabilistic model to segregate the brain into spatially connected and functionally homogeneous components. Then, we estimated HRF and detected activated regions in response to an experimental task in each parcel using a joint detection estimation (JDE) method. We compared the proposed JDE method with the general linear model (GLM) that uses a fixed HRF and is implemented in FEAT (as a part of FMRIB Software Library, version 4.1). Results: 1) Regions detected by JDE are larger than those detected by fixed HRF, 2) In group analysis, JDE found areas of activation not detected by fixed HRF. It detected drug craving a priori “regions-of-interest” in the limbic lobe (anterior cingulate cortex [ACC], posterior cingulate cortex [PCC] and cingulate gyrus), basal ganglia, especially striatum (putamen and head of caudate), and cerebellum in addition to the areas detected by the fixed HRF method, 3) JDE obtained higher Z-values of local maxima compared to those obtained by fixed HRF. Conclusion: In our study of heroin cue reactivity, our proposed method (that estimates HRF locally) outperformed the conventional GLM that uses a fixed HRF.
@bullet @bullet @bullet @bullet Bayesian Case Studies in Nonparametrics

Elements of Bayesian nonparametric statistical thought are explored in a series of case studies. Interpretation of a measurement as continuous, ordered, polychotomous, or dichotomous provides a framework in which examples are presented. Bayesian analogues to frequentist nonparametrics and overt Bayesian techniques are employed. Examples included are as follows: (1) averaging over families of distributions, (2) estimation of a single distribution function, (3) comparing several distribution functions, (4) estimating the coefficient of a concomitant variable affecting a distribution function, (5) monitoring compliance with a dichotomous measurement, and (6) using the multinomial for a categorization of any measurement's range. Lindley (1972, §12.2) provides an intitial sketch. Hill's (1968) nonparametric Bayesian construct and Berliner and Hill's (1988) application to survival are also reviewed. A commonality in the mechanics of these examples is the calculation of a marginal distribution over model parameters. Many are predictive distributions, resulting from an average over a likelihood and vague prior, and leaving observables for the calculations, as described by Roberts (1965) and advocated by Geisser (1971). Other specific observations from these efforts include the following points: (1) nonparametrics is typified by a proliferation of parameters; (2) biased estimation may provide smaller mean squared errors; (3) point null hypotheses are intrinsically unlikely; (4) the practical aspects of conditional inference with proportional hazards are embraced by Bayesian considerations; and (5) Fisher's Exact Test is a predictive distribution.
Morally Judging Entertainment: A Case Study of Live Tweeting During Downton Abbey

In this study, we propose that the massive, unsolicited, real-time data generated by social media might provide media psychologists with new paths for examining the role that morality and moral thinking play during the consumption of entertainment. Our broad goal was to explore a potentially new methodological approach to the study of morality and media and to offer an initial case study in applying that approach. The case study examined if, and if so how, viewers used Twitter to express their moral thoughts during the Season 3 finale of Downton Abbey. Based on moral foundation theory and affective disposition theory, we derived and examined a set of propositions. Specifically, we observed and discussed the importance of tweets (a) reflecting language from five moral domains, (b) for a beloved character who suffers pain and loss, and (c) about a character who regularly violates moral norms. We conclude that social TV analysis offers a promising new way for researchers to explore issues of morality and media reception.
Las prácticas de lectoescritura en los hogares de inmigrantes mexicanos

Resumen Pese a que existe un corpus de literatura bien establecido acerca del bilingüismo escolar en español e inglés de los niños latinos en los Estados Unidos, el desarrollo del bialfabetismo y las prácticas relacionadas con la lectoescritura en el hogar han recibido escasa atención por parte de la comunidad de investigación educativa. Es necesario un cambio en esta situación por la utilidad que puede tener para los educadores el conocimiento sobre los recursos lingüísticos y de lectoescritura que hay en el hogar a la hora de mejorar los curricula escolares y de atender mejor las necesidades de un alumnado de gran diversidad cultural y lingüística. Esta investigación sobre las prácticas lingüísticas y de lectoescritura de dos familias mexicanas en el contexto del hogar es nuestra contribución a ese empeño. Los resultados de este estudio sugieren que las interacciones familiares, así como el contexto del hogar en general, son factores cruciales para el impulso al desarrollo del lenguaje oral y de la lecto- escritura tanto en español como en inglés. Una observación importante y repetida a lo largo de nuestro estudio es el andamiaje que los padres emplean en español como parte de sus prácticas de lectoescritura. Además, los niños actúan como agentes en su propio aprendizaje del español, y en el establecimiento de nexos entre éste y sus conocimientos del inglés.
High Performance Associative Memory and Sign Constraints

The consequences of imposing a sign constraint on the standard Hopfield architecture associative memory model, trained using perceptron like learning rules, is examined. Such learning rules have been shown to have capacity of at most half of their unconstrained versions. This paper reports experimental investigations into the consequences of constraining the sign of the network weights in terms of: capacity, training times and size of basins of attraction. It is concluded that the capacity is roughly half the theoretical maximum, the training times are much increased and that the attractor basins are significantly reduced in size. Key-Words: Associative Memory, Hopfield Networks, Sign Constraints, Capacity, Basins of Attraction.
Improved efficiency, IP3-bandwidth and robustness of a microwave Darlington amplifier using 0.5/spl mu/m ED PHEMT and a new circuit topology

This paper reports on the first results of a self-biased e-mode PHEMT Darlington amplifier. The e-mode PHEMTs enable a FET Darlington implementation while a new Darlington active bias topology reduces bias variation over temperature and supply, and improves overall efficiency by reducing supply operation. A 3.3V-75mA amplifier achieves a BW of 0.1-14GHz, 12.3dB gain, NF of 3.5dB, IP3 and P1dB of 33.1dBm and 16dBm @ 2GHz, respectively. A 5V-75mA amplifier achieves a 0.1-10 GHz BW, 20.2 dB gain, NF of 2.9 dB, IP3 and P1dB of 34.2dBm and 21.8dBm @ 2 GHz, respectively. The new PHEMT Darlington amplifier design enables a factor of 2 better IP3-bandwidth product and lower voltage operation capability compared to InGaP-based Darlington amplifiers.
Bank Failure Prediction and Financial Data Reconstruction using Novel Soft-Computing Approaches

Bank failure prediction is important for the regulators (such as the central banks and the finance ministries) of the banking industries. The collapse and failure of a bank could have devastating consequences to the entire banking system and a widespread repercussion effect on other banks and financial institutions. Some of the negative impacts are the massive bail out cost for a failing bank and the negative sentiments and loss of confidence developed by investors and depositors. Very often, bank failures do not occur over night and are usually due to a prolonged period of financial distress. Hence, it is desirable to have an early warning system that identifies potential failing or high-risk banks through financial distress. Various traditional statistical models have been employed to study bank failures [1]-[4]. However, these models have not identified the symptoms of financial distress leading to eventual bank failure. This paper attempts to identify the financial distress (the symptoms) that leads to a bank failure using financial covariates derived from publicly available financial statements using a novel neural fuzzy system named the Generic Selforganising Fuzzy Neural Network (GenSoFNN) [5]. Subsequently, the performance of the Cox proportional hazards model [3][4] is benchmarked against that of the GenSoFNN in predicting bank failures based on a population of 3635 US banks observed over a 21 years period. In addition, it is believed that the event of financial distress does not develop out of the blue. The deterioration of the financial conditions of distressed banks can be observed over time. Thus, the performance of a bank can be tracked and studied from its annual financial statements over a period of time, which essentially is time-series modeling. However, it may not be possible to obtain all the financial statements or there may be missing information in the observed period of a bank. Hence, as part of the study, the Pseudo-Outer-Product Fuzzy Neural Network (POPFNN) [6] is used to reconstruct missing financial data that tracks the solvency (financial health) of banking institutions. The performances of both the GenSoFNN as a bank failure classification system and the POPFNN network as a tool to reconstruct missing financial data are encouraging.
Ant-based adaptive message forwarding scheme for challenged networks with sparse connectivity

We propose a new class of message routing schemes for mobile wireless networks with intermittent network connectivity. The proposed schemes are based on swarm intelligence (SI) and exploit the statistical properties of time-varying network connectivity for opportunistic message forwarding. We also consider a special form of our proposed schemes which can be viewed as a marriage between the SI and the backpressure algorithm and investigate its stability. We demonstrate that there is a fundamental trade-off between the adaptation rate and the stability region of the proposed scheme.
The Change from Respelling to IPA in English Dictionaries: Increase in Accuracy or Increase in Prescriptivism?

Abstract The extent to which a guide to the pronunciation of words is included in English monolingual dictionaries as well as the method used to render pronunciation varies across publishers as well as through time. This paper compares the respelling systems used between the late 1960s and the early 1980s and the motivation for the use of respelling as well as the reasons for a change to IPA in the last quarter of the twentieth century. It shows that, while the change to computer editing played a role, the main reason is the change in the market for monolingual English dictionaries, which shifted from native speakers to non-native learners. The paper argues that the change entailed an increase in prescriptivism, as respelling systems allowed an interpretation in different regional accents, which was lost with the change to IPA.
Towards Improved Control and Troubleshooting for Operational Networks

Over the past decade, operational networks, have grown tremendously in size, performance and importance. This concerns particularly the Internet, the ultimate “network of networks. ” We expect this trend to continue as more and more services traditionally provided by the local computer move to the cloud, e.g., file storage services and office applications. In spite of this, our ability to control and manage these networks remains painfully inadequate, and our visibility into the network limited. This has been exemplified by several recent outages that have caused significant disruption of important Internet services [24, 14, 149, 126]. Part of the challenges for controlling and troubleshooting networks stem from the nature of the problem: Networks are intrinsically highly distributed systems with distributed state and configuration. Consequently, a consistent view of the network state is often difficult to attain. They are also highly heterogeneous: Their scale ranges from small home-networks to data center networks that transfer enormous amounts of data at high speeds between thousands of hosts. Their geographic spread may be confined to a single rack, or span the globe. The Internet combines all these different kinds of networks, and thus their individual challenges. In addition, the network architecture and the available toolset has evolved little if at all over the past decade. In fact, the Internet core and architecture has been diagnosed with ossification [48]. Thus, debugging problems in an operational network still comes down to guesswork, as the architecture provides little support for fault localization and troubleshooting, and available tools like NetFlow, traceroute and tcpdump provide either only coarse-grained statistical insight, or are confined to single vantage points and do not provide consistent information across the network. In this thesis, we explore how to improve our control over networks and our abilities to debug and troubleshoot problems. Due to the extreme diversity of the environments, we do not strive for a one-size-fits-all solution, but propose and evaluate several approaches tailored to specific important scenarios and environments. We emphasize network centric approaches that can be implemented locally and are transparent to the end hosts. In the spirit of trusting “running code”, we implement all our approaches “on the metal” and evaluate them in real networks. We first explore the Potential of Flow Routing as an approach available to end users to self-improve their Internet Access. We find Flow-Routing to be a viable, costefficient approach for communities to share and bundle their access lines for improved reliability and performance.
A PARALLEL MULTIGRID METHOD USING THE FULL DOMAIN PARTITION

The combination of adaptive refinement, multigrid and parallel computing for solving partial differ- ential equations is considered. In the full domain partition approach, each processor contains a partition of the grid plus the minimum number of additional coarse elements required to cover the whole domain. A parallel multigrid algorithm using the full domain partition is presented. Multigrid rates of convergence have been observed while communicating between processors only twice per V-cycle. Numerical computations on a network of up to 32 workstations show that parallel efficiency rates of 50% to 90% can be obtained.