Miracle-dz/UniFAR-FTUs huggingface dataset:
The Production of Health, an Exploratory Study

The relationship of mortality of whites to both medical care and environmental variables is examined in a regression analysis across states in 1960. Medical care is alternatively measured by expenditures and by the output of a Cobb-Douglas production function combining the services of physicians, paramedical personnel, capital, and drugs. Simultaneous equation bias resulting from the influence of factor supply curves and demand for medical care is dealt with by estimating a more complete model. Both two-stage least squares and ordinary least squares estimates are presented. The elasticity of the age-adjusted death rate with respect to medical services is about -0.1. Environmental variables are far more important than medical care. High education is associated with relatively low death rates. High income, however, is associated with high mortality when Richard Auster is an Assistant Professor, City College of the City University of New York. Irving Leveson is Chief Research Specialist, Office of Comprehensive Planning, New York City Department of City Planning. Deborah Sarachek is testing her local postnatal care facilities. * The research was done under the auspices of the National Bureau of Economic Research "Productivity in the Service Industries" project, financed by a grant from the Ford Foundation; the "Health" project, financed by a grant from the Commonwealth Fund; with a grant of computer time from IBM Corporation. The authors wish to express thanks to Victor R. Fuchs for his encouragement and support as well as for his extensive comments and suggestions. Without his pioneering work, this study would not have been possible. Also appreciated is the assistance rendered in the form of comments and criticisms by Gary Becker, Philip Enterline, Michael Grossman, Reuben Gronau, Herbert Klarman, Sidney Leveson, John Meyer, Robert Michael, Jacob Mincer, David O'Neill, Melvin Reder, and Morris Silver. Finally, thanks are due to Robin Ringler, Ira Silver, Lorraine Wolch, and especially Henrietta Lichtenbaum for research assistance. All appendixes referred to and additional tables are available from the authors upon request. The Journal of Human Resources * IV * 4 This content downloaded from 207.46. 13.159 on Sat, 22 Oct 2016 04:34:19 UTC All use subject to http://about.jstor. org/terms 412 | THE JOURNAL OF HUMAN RESOURCES medical care and education are controlled for. This may reflect unfavorable diets, lack of exercise, psychological tensions, etc. The positive association of mortality with income may explain the failure of death rates to decline rapidly in recent years. Adverse factors associated with the growth of income may be nullifying beneficial effects of increases in the quantity and quality of care. If so, the view that we have reached a biological limit to the death rate is not valid.
A distributed attack detection and mitigation framework

Despite the efforts of security communities, the gap between the available protection against cyber-attacks and the number of successful attacks remains significant. The need for new countermeasures is clear and urgent as cyber-attacks are more than ever capable of causing loss of human life; destroying the environment, and causing a high level of disruption to critical infrastructures. The impact of cyber-attacks is sometimes comparable to the impact of traditional military actions. However, the lack of understanding of the scope of attacks and how they operate could lead to unsuccessful protection mechanisms. We have analysed attacks targeting IT and business network, and Critical infrastructure, as a result we present four levels of visibility of attacks that need to be considered when designing or implementing security mechanisms. In our discussion of these four levels of visibility of attacks, we particularly focus on one level where malicious users actions are direct threats to the targeted system but yet not visible by the targeted systems. We conclude by presenting our detection and mitigation framework concept.
An Economic Analysis of Emerging Urban Institutions in China

By summarizing relevant literature and introducing a theoretical framework for analyzing urban institutions, this paper studies emerging urban institutions in China from an efficiency perspective. In the last decade, homeowners associations have been booming across Chinese cities, especially through the promotion of Ministry of Construction. In the meanwhile, Ministry of Civil Affairs has been promoting community service centers. Facing these two newly emerging urban institutions, the traditional hierarchical structure of Chinese urban government (municipality, district, street office, residents' committee) is also undergoing transformation. Through an integrated analysis of these three main types of urban institutions in China, it is argued that the devolution of some land use controls to districts or even street offices may be desirable and many so-called community services may be more efficiently provided at larger scale or by private companies. Although gated communities may not be socially desirable, homeowners association is a promising new institutional form that may become important catalyst for political reform and democracy. In spite of bureaucratic turf-fighting and political manipulation, China's urban institutions are showing signs of responding to the efficiency needs of a market economy.
Blind watermark algorithm based on HVS and RBF neural network in DWT domain

This paper proposes a new blind watermarking scheme based on discrete wavelet transform(DWT) domain. The method uses the HVS model, and radial basis function neural networks(RBF). RBF will be implemented while embedding and extracting watermark. The human visual system (HVS) model is used to determine the watermark insertion strength. The neural networks almost exactly recover the watermarking signals from the watermarked images after training and learning. The experimental results show that the watermark proposed in this paper is invisible (the PSNR is higher than 41) and is robust in the case of against some normal at tacks such as JPEG compression, additive noise and filtering, etc.
Open2Edit: A peer-to-peer platform for collaboration

Peer-to-peer systems owe much of their success to user contributed resources like storage space and bandwidth. At the same time, popular collaborative systems like Wikipedia or StackExchange are built around user-contributed knowledge, judgement, and expertise. In this paper, we combine peer-to-peer and collaborative systems to create Open2Edit, a peer-to-peer platform for collaboration. Open2Edit provides the means for users to publish, modify, comment on, and categorize content. Content-centric collaboration in Open2Edit takes place within communities. A flexible permission system allows each community to customize the privileges users receive for interacting with content. Any user can create a new community, and Open2Edit facilitates their discovery. Furthermore, Open2Edit allows users to vote for communities, and keeps track of community popularity. We deploy Open2Edit in Tribler, a BitTorrent-based peer-to-peer application, in order to create a YouTube-like media sharing system. Through Open2Edit, users in Tribler can collaboratively improve media metadata using a wiki-Iike approach. We present results from 7.5 months of usage that show Open2Edit is a viable, sustainable platform that leads to the emergence of collaboration.
Speed Control Of Three Phase Induction Motor By Fuzzy Sliding Mode And Genetic algorithm

This paper describes the use of robust control systems using fuzzy sliding mode and genetic algorithm (FSMC-GA) to control the speed of a three phase induction motor. First, sliding mode control that incorporates a fuzzy tuning technique (FSMC) is used to overcome the high control gains and chattering of the classical SMC. However, the fuzzy control rules are always built by designers with trial and error. We propose an optimization technique of FSMC using genetic algorithm. GA is used for determination of different controller parameters due to their fast convergence and their reasonable accuracy. The effectiveness of the complete proposed control scheme is verified by numerical simulation. The results of simulation showed that (FSMCGA) presents better performances compared to the (FSMC).
Finger Vein Image Enhancement Algorithm Based on the Grayscale Morphology

As the information security technology constantly develops, finger vein feature technology has become a new technology. The paper proposes a Finger Vein Image Enhancement Algorithm Based on the Grayscale Morphology (FVGM). The algorithm first uses a group of structural elements with the four directions for respective dilation operation of the image, and gets the smoothed finger vein image by weighting method. Simulation results show that FVGM algorithm can effectively improve the definition of intravenous lines in the finger vein image.
Cardiac plasticity in fishes: environmental influences and intraspecific differences

SUMMARY Fish cardiac physiology and anatomy show a multiplicity of intraspecific modifications when exposed to prolonged changes in environmentally relevant parameters such as temperature, hypoxia and food availability, and when meeting the increased demands associated with training/increased activity and sexual maturation. Further, there is evidence that rearing fish under intensive aquaculture conditions significantly alters some, but not all, aspects of cardiac anatomy and physiology. This review focuses on the responses of cardiac physiology and anatomy to these challenges, highlighting where applicable, the importance of hyperplastic (i.e. the production of new cells) vs hypertrophic (the enlargement of existing cells) growth to the adaptive response of the heart. In addition, we summarize recent studies that have explored the relationship between the myocardial protection afforded by preconditioning and myocardial hypoxia tolerance. This latter research clearly demonstrates the capacity of the fish heart to adjust to short-term perturbations, and shows that it can be difficult to predict how short-term and long-term alterations in cardiac physiology will interact.
miROrtho: computational survey of microRNA genes

MicroRNAs (miRNAs) are short, non-protein coding RNAs that direct the widespread phenomenon of post-transcriptional regulation of metazoan genes. The mature ∼22-nt long RNA molecules are processed from genome-encoded stem-loop structured precursor genes. Hundreds of such genes have been experimentally validated in vertebrate genomes, yet their discovery remains challenging, and substantially higher numbers have been estimated. The miROrtho database (http://cegg.unige.ch/mirortho) presents the results of a comprehensive computational survey of miRNA gene candidates across the majority of sequenced metazoan genomes. We designed and applied a three-tier analysis pipeline: (i) an SVM-based ab initio screen for potent hairpins, plus homologs of known miRNAs, (ii) an orthology delineation procedure and (iii) an SVM-based classifier of the ortholog multiple sequence alignments. The web interface provides direct access to putative miRNA annotations, ortholog multiple alignments, RNA secondary structure conservation, and sequence data. The miROrtho data are conceptually complementary to the miRBase catalog of experimentally verified miRNA sequences, providing a consistent comparative genomics perspective as well as identifying many novel miRNA genes with strong evolutionary support.
Identity-Based Signcryption

A signcryption scheme is a scheme that provides private and authenticated delivery of messages between two parties. It does this in a more eecient manner than a straightforward composition of an encryp-tion scheme with a signature scheme. An identity-based cryptosystem is one in which the public key may be any string (or may be derived from any string). In this paper we propose an identity-based signcryption scheme. We give a security model for such a scheme and sketch the details of how our scheme may be proved secure in this model.
Experiments with Cooperative Aerial-Ground

Heterogeneous robot groups are a promising research direction for automating diverse tasks. A functional diierence between individual robot capabilities is likely to allow task-based specialization within the group. We report on experiments with a mechanically heterogeneous robot group consisting of a robotic helicopter and multiple wheeled ground robots. We present a behavior-based control system architecture for each robot. The overall system architecture for the group is discussed. Three case studies are presented in increasing order of group autonomy. We conclude with a discussion of our approach, a survey of related literature, and directions for ongoing and future work. A Introduction This chapter describes experiments in the design and construction of a cooperative, heterogeneous robot group comprised of one semi-autonomous aerial robot and two autonomous ground robots. While several applications for such a group exist, we are motivated in particular by the automated surveillance and reconnaissance of an urban outdoor area using onboard sensing. in robot groups largely focussed on architectural issues for robot control and coordination. However, heterogeneous robot groups have not been studied in much detail. Notable exceptions include the work reported in 25]. We consider a robot group to be heterogeneous if at least one member of the group is diierent from the others in one or more of the following attributes: 1. mechanics, 2. sensing, 3. computing hardware or 4. nature of onboard computation. This relatively loose condition is easily met by the system we describe in this paper. For a systematic analysis and metrics of robot group diversity the reader is referred to 5]. Our experimental testbed (shown in Figure 1) is composed of a robot helicopter and two mobile ground robots, thus making it a morphologically heterogeneous group. The advantages of using a group of robots to perform coordinated activity have been discussed extensively in the literature 13, 3, 6, 25]. These include speedup of task completion time, fault tolerance , and exibility, to name a few. Heterogeneous groups, in particular, allow for the possibility
Dependency-Based Semantic Role Labeling using Convolutional Neural Networks

We describe a semantic role labeler with stateof-the-art performance and low computational requirements, which uses convolutional and time-domain neural networks. The system is designed to work with features derived from a dependency parser output. Various system options and architectural details are discussed. Incremental experiments were run to explore the benefits of adding increasingly more complex dependency-based features to the system; results are presented for both in-domain and out-of-domain datasets.
Robot and locomotion-controller design optimization for a reconﬁgurable quadruped

—We present an automated approach to robot and locomotion-controller design optimization, using reinforcement learning methods that have been successfully demonstrated to teach a real prototype quadruped various walking gaits. The same machine learning methods are used here for a different purpose: to optimize robot and locomotion-controller design. Optimization can be used before or after building the robot, to reconﬁgure it for improved performance in a speciﬁc terrain or learning task. We propose measures for evaluating: (1) different controller symmetry assignments – couplings among the robot’s motors; (2) different lower-leg lengths. The measures are constructed with respect to the reward function of a simple learning task – better designs are those that achieve higher rewards. Averaged learning curves of each design are also used as an evaluation measure. We also present manual design considerations of the quadruped, which was mainly created as a test bed for machine learning methods for rugged terrain locomotion.
On the Impact of Fault-Tolerance Mechanisms in a Peer-to-Peer Middleware

We address the problem of integrating real-time fault-tolerance mechanisms into peer-to-peer systems, with specific architecture and deployment constraints. For this purpose we implemented a prototype hierarchical peer-to-peer framework in which the leaf peers are sensors that generate different kinds of traffic such as mesh management, events, video and audio. We evaluate the framework by measuring packet loss, response time, jitter and mesh overhead for each type of traffic under peer failure. We report significant gains in QoS for all types of traffic, when using the fault-tolerance mechanisms, with minimal response time and mesh management overhead. Abstract— We address the problem of integrating real-time fault-tolerance mechanisms into peer-to-peer systems, with specific architecture and deployment constraints. For this purpose we implemented a prototype hierarchical peer-to-peer framework in which the leaf peers are sensors that generate different kinds of traffic such as mesh management, events, video and audio. We evaluate the framework by measuring packet loss, response time, jitter and mesh overhead for each type of traffic under peer failure. We report significant gains in QoS for all types of traffic, when using the fault-tolerance mechanisms, with minimal response time and mesh management overhead. We address the problem of integrating real-time fault-tolerance mechanisms into peer-to-peer systems, with specific architecture and deployment constraints. For this purpose we implemented a prototype hierarchical peer-to-peer framework in which the leaf peers are sensors that generate different kinds of traffic such as mesh management, events, video and audio. We evaluate the framework by measuring packet loss, response time, jitter and mesh overhead for each type of traffic under peer failure. We report significant gains in QoS for all types of traffic, when using the fault-tolerance mechanisms, with minimal response time and mesh management overhead.
CLARM: an integrative approach for functional modules discovery

Functional module discovery aims to find well-connected subnetworks which can serve as candidate protein complexes. Advances in High-throughput proteomic technologies have enabled the collection of large amount of interaction data as well as gene expression data. We propose, CLARM, a clustering algorithm that integrates gene expression profiles and protein protein interaction network for biological modules discovery. The main premise is that by enriching the interaction network by adding interactions between genes which are highly co-expressed over a wide range of biological and environmental conditions, we can improve the quality of the discovered modules. Protein protein interactions, known protein complexes, and gene expression profiles for diverse environmental conditions from the yeast Saccharomyces cerevisiae were used for evaluate the biological significance of the reported modules. Our experiments show that the CLARM approach is competitive to well-established module discovery methods.
Simulating Cerebellar Learning of Internal Models

Many motor system impairments are debilitating not because they destroy previously acquired motor control policies but because they impair the ability to learn and incorporate error signals in moving. The cerebellum is of chief importance in nearly all motor learning tasks, and is a hypothesized location of storage for internal models important to movement. This model hypothesizes that plasticity in the parallel fibers that connect granule cells and Purkinje cells in the cerebellar cortex are the biological mechanism of policy learning. The model implements the granule cells and Purkinje cells as a neural network connected to a 2-degreeof-freedom simulated arm and two plasticity rules, one for long-term potentiation and one for long-term depression. The activity of the network and behavior of the simulated arm are captured and analyzed.
SHREC’08 entry: 3D face recognition using moment invariants

3D face scans often contain too much noise and other irregularities in them. Geometric processing techniques such as smoothing and hole filling are employed to preprocess this kind of data. Each face model is then segmented to get a series of partial surfaces and curves. We use surface moment invariants and curve moment invariants as shape descriptors for the shape retrieval of them.
Taurolidine and oxidative stress: a rationale for local treatment of mesothelioma

Malignant mesothelioma is an asbestos-related, aggressive tumour, resistant to most anticancer therapies. Akt is a key mediator of mesothelioma cell survival and chemoresistance. This study aimed to clarify the mechanism by which taurolidine (TN), a known synthetic compound with antimicrobial and antineoplastic properties, leads to mesothelioma cell death. Apoptosis was studied by annexin V binding, cell cycle analysis, caspase-8 activation, poly(ADP-ribose) polymerase (PARP) cleavage and terminal deoxynucleotidyl transferase-mediated deoxyuridine triphosphate nick-end labelling (TUNEL). Oxidative stress was measured by nitrite production and DNA oxidative damage. Protein expression and phosphorylation were evaluated by immunoprecipitation and immunoblotting. TN induces cell death of mesothelioma cells, but not of non-neoplastic human mesothelial cells. After TN treatment of mesothelioma cells, Akt but not extracellular signal-regulated kinase (Erk) 1/2 activity is inhibited a in time- and dose-dependent manner. Protein phosphatase (PP)1α and PP2A are activated several hours after drug addition. Apoptosis induced by TN is driven by oxidative stress and cell exposure to sulfydryl donors, such as glutathione monoethylester and l-N-acetylcysteine, significantly reduced pro-apoptotic effects and Akt inhibition. Conversely, expression of constitutively activated Akt did not affect cytoxicity elicited by TN, which retained its ability to inhibit the kinase. TN induces mesothelioma cell death via oxidative stress, accompanied by inhibition of Akt signalling. This provides a promising molecular rationale for TN as local treatment of malignant mesothelioma.
Systemic Crises : Policies and Institutions by

We analyze the role of policy and institutions in resolving a systemic crisis for a broad sample of countries. As others have documented before, we find that extensive liquidity support, (unlimited) government guarantees on financial institutions’ liabilities and forbearance from prudential regulations add to the fiscal costs of resolution. Although these accommodative policies are costly, they do not accelerate the recovery from a crisis. Better institutions—lower corruption, greater law and order, better legal system, and a better bureaucracy—do, however, lower costs and accelerate economic recovery. We find these results using both country and industry level data and to be relatively robust to estimation techniques and samples. They suggest that countries best use strict policies to resolve a crisis and focus on structural reforms, which, as has been shown elsewhere, will also help avoid future systemic crises. ________________________________________________________________________ * Claessens is with the University of Amsterdam and CEPR and Klingebiel and Laeven are with the World Bank. We would like to thank Jerry Caprio and Patrick Honohan for very useful comments and Guillermo Noguera for excellent research assistance. Prepared for the conference “Systemic Financial Distress: Containment and Resolution” to be held at the World Bank, October 8-9, 2003. The views expressed in this paper are those of the authors and do not necessarily represent those of the World Bank. Email addresses: stijn@fee.uva. nl, dklingebiel@worldbank.org, and llaeven@worldbank.org.