Miracle-dz/UniFAR-FTUs huggingface dataset:
The Current Account and the Real Exchange Rate: A Structural VAR Analysis of Major Currencies

A sticky-price model is used to motivate a structural VAR analysis of the current account and the real exchange rate for seven major industrialized countries (the US, Canada, the UK, Japan, Germany, France and Italy). The analysis is distinguished from previous work in that it adopts minimal assumptions for identification. The empirical results are consistent with the theoretical model, as well as the sticky price intertemporal model of Obstfeld and Rogoff (1995). Permanent shocks to productivity have large long term effects on the real exchange rate, but relatively small effects on the current account; money shocks have large effects on the current account and exchange rate in the short run, but not on either variable in the long run.
Transcriptomic Evidence for a Dramatic Functional Transition of the Malpighian Tubules after a Blood Meal in the Asian Tiger Mosquito Aedes albopictus

Background The consumption of a vertebrate blood meal by adult female mosquitoes is necessary for their reproduction, but it also presents significant physiological challenges to mosquito osmoregulation and metabolism. The renal (Malpighian) tubules of mosquitoes play critical roles in the initial processing of the blood meal by excreting excess water and salts that are ingested. However, it is unclear how the tubules contribute to the metabolism and excretion of wastes (e.g., heme, ammonia) produced during the digestion of blood. Methodology/Principal Findings Here we used RNA-Seq to examine global changes in transcript expression in the Malpighian tubules of the highly-invasive Asian tiger mosquito Aedes albopictus during the first 24 h after consuming a blood meal. We found progressive, global changes in the transcriptome of the Malpighian tubules isolated from mosquitoes at 3 h, 12 h, and 24 h after a blood meal. Notably, a DAVID functional cluster analysis of the differentially-expressed transcripts revealed 1) a down-regulation of transcripts associated with oxidative metabolism, active transport, and mRNA translation, and 2) an up-regulation of transcripts associated with antioxidants and detoxification, proteolytic activity, amino-acid metabolism, and cytoskeletal dynamics. Conclusions/Significance The results suggest that blood feeding elicits a functional transition of the epithelium from one specializing in active transepithelial fluid secretion (e.g., diuresis) to one specializing in detoxification and metabolic waste excretion. Our findings provide the first insights into the putative roles of mosquito Malpighian tubules in the chronic processing of blood meals.
Comparative study of different artificial neural networks methodoiogies on static solar photovoltaic Module

The aim of this paper is to present a comparative study of the different artificial neural networks modeling approach on the static solar photovoltaic (SSPV) model under variable input parameters and conditions. Solar energy generation has widely based its power generation on static solar photovoltaic system generation due to its non-involvement in recurrent maintenance costs and non-replacement of tracking devices after initial installation. The artificial neural networks have proven to be a reliable software application tool capable of providing solutions to complex non-linear mathematical equations and complicated models. It provides accurate prediction and generalisation of the system at high speed. The results of the comparative artificial neural networks indicate the performance of the different methodologies and their respective output efficiency characteristics for evaluation. The autocorrelation coefficient obtained from each methodology gives an accuracy of approximately 99% with negligible mean square error (MSE) for the output variables. The performance of these methodologies are compared and presented on a very large scale for all operating conditions to confirm the validity of the model.
Projected cost-effectiveness of smoking cessation interventions in patients hospitalized with myocardial infarction.

BACKGROUND As many as 70% of smokers with acute myocardial infarction (AMI) continue to smoke after hospital discharge despite high rates of inpatient smoking cessation counseling. Supportive contact after discharge improves quit rates but is rarely used. METHODS Using data from a meta-analysis of randomized trials of smoking cessation interventions and other published sources, we developed a Monte Carlo model to project health and economic outcomes for a hypothetical US cohort of 327,600 smokers hospitalized with AMI. We compared routine care, consisting of advice to quit smoking, with counseling with supportive follow-up, consisting of routine care and follow-up telephone calls from a nurse after discharge. Primary outcomes were number of smokers, AMIs, and deaths averted; health care and productivity costs; cost per quitter; and cost per quality-adjusted life-year. RESULTS Implementation of smoking cessation counseling with follow-up contact for the 2010 cohort of hospitalized smokers would create 50,230 new quitters, cost $27.3 million in nurse wages and materials, and prevent 1380 nonfatal AMIs and 7860 deaths. During a 10-year period, it would save $22.1 million in reduced hospitalizations but increase health care costs by $166.4 million, primarily through increased longevity. Productivity costs from premature death would fall by $1.99 billion and nonmedical expenditures would increase by $928 million, for a net positive value to society of $894 million. The program would cost $540 per quitter considering only intervention costs. Cost-effectiveness would be $5050 per quality-adjusted life-year. Results were sensitive to the utility and incidence of nonfatal AMI and the potential effect of pharmacotherapies. CONCLUSION Smoking cessation counseling with supportive contact after discharge is potentially cost-effective and may reduce the incidence of smoking and its associated adverse health events and social costs.
Using Generative Programming to Visualise Hypercode in Complex and Dynamic Systems

The research presented here takes place in the context of the EC Funded ArchWare project which focuses on innovative architecture-centric languages, frameworks and tools for engineering evolvable software systems. Of particular interest are complex and dynamic systems characterised by the need to evolve to meet changing requirements without total shutdown or the loss of state information. The ArchWare approach uses the unique combination of a pi-calculus based architecture description language, persistence and hypercode. Hyper-code provides the essential base technology for composing and decomposing system components without losing state. The contribution of this work is an implementation of hypercode using generative programming techniques to produce different hypercode visualisations.
Tellipsoid: Exploiting inter-gene correlation for improved detection of differential gene expression

Motivation: Algorithms for differential analysis of microarray data are vital to modern biomedical research. Their accuracy strongly depends on effective treatment of inter-gene correlation. Correlation is ordinarily accounted for in terms of its effect on significance cut-offs. In this paper it is shown that correlation can, in fact, be exploited {to share information across tests}, which, in turn, can increase statistical power. Results: Vastly and demonstrably improved differential analysis approaches are the result of combining identifiability (the fact that in most microarray data sets, a large proportion of genes can be identified a priori as non-differential) with optimization criteria that incorporate correlation. As a special case, we develop a method which builds upon the widely used two-sample t-statistic based approach and uses the Mahalanobis distance as an optimality criterion. Results on the prostate cancer data of Singh et al. (2002) suggest that the proposed method outperforms all published approaches in terms of statistical power. Availability: The proposed algorithm is implemented in MATLAB and in R. The software, called Tellipsoid, and relevant data sets are available at http://www.egr. msu.edu/~desaikey
Surface EMG Network Analysis and Robotic Arm Control Implementation

743 Abstract— An implementation for surface EMG network analysis and vertical control system of robotic arm is presented in this paper. The transmembranes are simulated by equivalent circuit and cable equation for propagation to be converted to circuit networks. The implementation is realized to be derived from the detecting EMG signal from 3 electrodes, and EMG transmembrane signals of human arm muscles are detected by several surface electrodes, high performance amplifier and filtering, converting analog to digital data and driving a servomotor for spontaneous robotic arm. The system is experimented by monitoring multiple steps vertical control angles corresponding to biceps muscle movement. The experimental results are that the vertical moving control level is measured to around 2 degrees and mean error ranges are lower 5%.
The Java Memory Model: a Formal Explanation

This paper discusses the new Java Memory Model (JMM), introduced for Java 1.5. The JMM specifies the allowed executions of multithreaded Java programs. The new JMM fixes some security problems of the previous memory model. In addition, it gives compiler builders the possibility to apply a wide range of singlethreaded compiler optimisations (something that was nearly impossible for the old memory model). For program developers, the JMM provides the following guarantee: if a program does not contain any data races, its allowed behaviours can be described with an interleaving semantics. This paper motivates the definition of the JMM. It shows in particular the consequences of the wish to have the data race freeness guarantee and to forbid any out of thin air values to occur in an execution. The remainder of the paper then discusses a formalisation of the JMM in Coq. This formalisation has been used to prove the data race freeness guarantee. Given the complexity of the JMM definition, having a formalisation is necessary to investigate all aspects of the JMM.
The Economics of Private Voluntary Organizations and Collective Action in Deer Management

Game theory and other approaches have been used to characterize problems involving high-exclusion-cost goods which also have the characteristic that marginal cost of an additional user is zero over some range. These analytical tools have made valuable contributions to understanding voluntary organizations and collective action. Resource systems for which composition or scale of the resource is an important factor do not fit neatly into the types of problems which are typically analyzed. The Quality Deer Management Association (QDMA) in Southern Wisconsin is used as an example to illustrate where the existing literature must be modified to take account of particular features of this resource problem. Schelling's multi-person prisoner's dilemma model is modified to incorporate preferences and marginal benefits of deer quality to different types of hunters and to explore issues of resource sustainability. Against the odds, the private QDMA has successfully organized hunters to practice harvesting techniques consistent with improved herd quality.
Causes of discomfort in stereoscopic content: a review

This paper reviews the causes of discomfort in viewing stereoscopic content. These include objective factors, such as misaligned images, as well as subjective factors, such as excessive disparity. Different approaches to the measurement of visual discomfort are also reviewed, in relation to the underlying physiological and psychophysical processes. The importance of understanding these issues, in the context of new display technologies, is emphasized.
The Astrometric-Spectroscopic Binary System HIP 50796: An Overmassive Companion

We report spectroscopic observations of the star HIP 50796, previously considered (but later rejected) as a candidate member of the TW Hya association. Our measurements reveal it to be a single-lined binary with an orbital period of 570 days and an eccentricity of e = 0.61. The astrometric signature of this orbit was previously detected by Hipparcos in the form of curvature in the proper-motion components, although the period was unknown at the time. By combining our radial velocity measurements with the Hipparcos intermediate data (abscissa residuals) we are able to derive the full three-dimensional orbit and determine the dynamical mass of the unseen companion, as well as a revised trigonometric parallax that accounts for the orbital motion. Given our primary mass estimate of 0.73 M⊙ (mid-K dwarf), the companion mass is determined to be 0.89 M⊙, or ∼20% larger than the primary. The likely explanation for the larger mass without any apparent contribution to the light is that the companion is itself a closer binary composed of M dwarfs. The near-infrared excess and X-ray emission displayed by HIP 50796 support this. Our photometric modeling of the excess leads to a lower limit to the mass ratio of the close binary of q ∼ 0.8 and individual masses of 0.44-0.48 and 0.41-0.44 M⊙. The new parallax (π = 20.6 ± 1.9 mas) is significantly smaller than the original Hipparcos value and more precise.
Electoral Uncertainty, Fiscal Policies & Growth: Theory and Evidence from Germany, the UK and the Us

In this paper we study the link between elections, fiscal policy and economic growth/fluctuations. The set-up is a dynamic stochastic general equilibrium model of growth and endogenously chosen fiscal policy, in which two political parties can alternate in power. The party in office chooses jointly how much to tax and how to allocate its total expenditure between public consumption and production services. The main theoretical prediction is that forward-looking incumbents, with uncertain prospects of re-election, find it optimal to follow relatively shortsighted fiscal policies, and that this lowers economic growth. The model is estimated using quarterly data for Germany, the UK and the US from 1960 to 1999. Our econometric results provide clear support for the main theoretical prediction. They also give plausible and significant estimates for the productivity of public production services, the weight which households place on public consumption services relative to private consumption and the time discount rate. Moreover, we find that changes in electoral uncertainty produce the longest lasting fluctuations in the European economies followed by the US.
Evolution of Accretion Disks around Massive Black Holes: Constraints from the Demography of Active Galactic Nuclei

Observations have shown that the Eddington ratios (the ratio of the bolometric luminosity to the Eddington luminosity) in QSOs/active galactic nuclei (AGNs) cover a wide range. In this paper we connect the demography of AGNs obtained by the Sloan Digital Sky Survey with the accretion physics around massive black holes and propose that the diversity in the Eddington ratios is a natural result of the long-term evolution of accretion disks in AGNs. The observed accretion rate distribution of AGNs (with host galaxy velocity dispersion σ ≃ 70-200 km s-1) in the nearby universe (z < 0.3) is consistent with the predictions of simple theoretical models in which the accretion rates evolve in a self-similar way. We also discuss the implications of the results for the issues related to self-gravitating disks, coevolution of galaxies and QSOs/AGNs, and the unification picture of AGNs.
Experimental Study on Fire Extinguishing Characteristics of Automatic Sprinkler System

Sprinkling density and working pressure are two important parameters for automatic sprinkler system to control the fire effectively and quickly. In this paper, the fire extinguishing characteristics of sprinkler system is studied experimentally. We take traditional drop shaped glass bulb sprinkler with nominal diameter of 15 mm as example, letting the nozzle working pressure ranges between 0.05MP-0,16MP, extinguishing characteristics of various strength of spray density i n protected areas was studied through experiment. The experimental data were processed by Origin software and the temperature variation curves were obtained. Therefore, the characteristics of fire extinguishing under different pressure and sprinkling density were obtained.
Position Based Routing for Mobile Ad Hoc Networks

The goal is to utilize position information to provide more reliable as well as efficient routing for certain applications. Thus extensions to existing position based routing algorithm have been described to work more efficiently even in cases where they are not working at present. In this paper an algorithm is proposed, which removes some of the drawbacks of the existing GPSR (Greedy perimeter stateless routing) position based routing algorithm. In proposed algorithm different algorithm has been used to planarize the graph so that it will not disconnect the route in case of location inaccuracy in perimeter mode whereas in GPSR in certain cases of location inaccuracy it will disconnect the graph and hence the packets will not be routed thereby decreasing packet delivery ratio.
On the Adaptive Control of the False Discovery Rate in Multiple Testing With Independent Statistics

A new approach to problems of multiple significance testing was presented in Benjamini and Hochberg (1995), which calls for controlling the expected ratio of the number of erroneous rejections to the number of rejections–the False Discovery Rate (FDR). The procedure given there was shown to control the FDR for independent test statistics. When some of the hypotheses are in fact false, that procedure is too conservative. We present here an adaptive procedure, where the number of true null hypotheses is estimated first as in Hochberg and Benjamini (1990), and this estimate is used in the procedure of Benjamini and Hochberg (1995). The result is still a simple stepwise procedure, to which we also give a graphical companion. The new procedure is used in several examples drawn from educational and behavioral studies, addressing problems in multi-center studies, subset analysis and meta-analysis. The examples vary in the number of hypotheses tested, and the implication of the new procedure on the conclusions. In a large simulation study of independent test statistics the adaptive procedure is shown to control the FDR and have substantially better power than the previously suggested FDR controlling method, which by itself is more powerful than the traditional family wise error-rate controlling methods. In cases where most of the tested hypotheses are far from being true there is hardly any penalty due to the simultaneous testing of many hypotheses.
Integrated sensors for robotic laser welding

A welding head is under development with integrated sensory systems for robotic laser welding applications. Robotic laser welding requires sensory systems that are capable to accurately guide the welding head over a seam in three-dimensional space and provide information about the welding process as well as the quality of the welding result. In this paper the focus is on seam tracking. It is difficult to measure three-dimensional parameters of a ream during a robotic laser welding task, especially when sharp corners are present. The proposed sensory system is capable to provide the three dimensional parameters of a seam in one measurement and guide robots over sharp corners.
Unconstrained Handwritten Kannada Numeral Recognition

Handwritten Character Recognition (HCR) is very important in academic and production fields. The recognition system can be either online or offline. There is a large scope for optical character recognition on hand written documents. India is a multilingual and multi script country, where eighteen official scripts are accepted and have over hundred regional languages. Recognition of unconstrained hand written Indian scripts is difficult because of the presence of numerals, vowels, consonants, vowel modifiers and compound characters. In this paper we have implemented to recognize the unconstrained handwritten Kannada numeral characters and have proposed the projection distance metrics method for numeral recognition and General Regression Neural Network (GRNN) for the classification of the character image.
Exploiting building information from publicly available maps in graph-based SLAM

Maps are an important component of most robotic navigation systems and building maps under uncertainty is often referred to as simultaneous localization and mapping or SLAM. Most SLAM approaches start from scratch and build a map only based on their own observations and odometry information. In this paper, we address the problem of how additional information can be exploited, for example from OpenStreetMap. We extend the standard graph-based SLAM formulation by relating the nodes of the pose-graph with an existing map. As this paper suggests, we can relate the newly built maps with information from publicly available maps with the laser range finder data from the robot and in this way improve the map quality. We implemented and evaluated our approach using real world data taken in urban environments. We illustrate that our extension to graph-based SLAM provides better aligned maps and adds only a marginal computational overhead.
A new adaptive evidential reasoning approach for network alarm correlation

In computer networks, fault detection and identification techniques rely substantially on analyzing a set of observed alarms generated by different network entities due to unknown failures. However, network alarms are subject to becoming lost and spurious and their information is often incomplete, ambiguous, and inconsistent. In this paper, an adaptive distributed Dempster-Shafer evidential reasoning technique is proposed to effectively reduce the negative impact of the uncertainty properties which network alarms can exhibit. Each observed alarm is perceived as a piece of evidence and as such, the incomplete and ambiguous properties can be tackled within the framework of the evidential theory. A discounting mechanism by which the observed alarms are assigned certain weights is also presented. A given weight reflects the significance of the information in the corresponding alarm. Then, the alarms are correlated by the Dempster's rule of combination and the inconsistent alarms play a limited role in the alarm correlation process since they are given lower weights. Simulations confirm that the proposed scheme has a high detection rate even in the presence of defective alarms.
Discovering Purchasing Pattern of Sport Items Using Market Basket Analysis

One of the oldest problem in data mining is the market basket problem, the search for meaningful associations in customer purchase data. Currently, the Sport Company has an issue on sport items arrangement in accordance with customer purchasing pattern. They noticed that, the sales of certain products become decrease when they made some arrangement to the shelves. The Sport Company do not have any available computerized mechanism to provide the best arrangement of item store at the retail store. Everything is done manually by the owner of the shop according their own style. This study intends to identify purchasing pattern of sport items by adopting data mining technique which is Market Basket Analysis. This data mining pattern will help the retailer to make a better arrangement of the products at the premise. Historical data is analyzed to identify associated items from purchasing data of customer that involved sales data, items data and order data. As a result from this research, the sports items will be arranged according to the best rules identified and propose a new pattern.