Miracle-dz/UniFAR-FTUs huggingface dataset:
Fuzzy Granular Evolving Modeling for Trading Strategies with Exchange Rates

This work addresses a fuzzy set based evolving modeling (FBeM) approach and the task of trading strategies performance. FBeM is a granular computing technique that uses fuzzy information granules to model nonstationary functions providing functional and linguistic approximations. As an application, we consider the BRL/USD exchange rate for the period from January 2000 to October 2012. Caparisons based on trading performance indicators includes the granular model against a Multi-Layer Perceptron (MLP), an autoregressive moving average (ARMA), a naïve strategy and some state-of-the-art evolving fuzzy systems. Computational results suggest that the FBeM model outperforms the alternative approaches.
CSE 250 B Project Assignment 4

The goal of this project is to implement the Semi-Supervised Recursive Autoencoders (RAE) with random word initialization and reproduce the result of Socher et. al [1] using the Movie Reviews dataset. With a correct understanding of gradient meaning in semi-supervised RAE, our implementation achieves 76.9% accuracy with only 0.1% difference to the authors’ result. The experiments also show that including supervised information for each word’s representation is important for RAE to succeed with random word initialization, while applying normalization to the reconstruction output nodes makes the algorithm less sensitive to the weighting between the supervised information and the reconstruction performance.
Unified compact modelling strategies for process and statistical variability in 14-nm node DG FinFETs

This paper presents a principal component analysis (PCA)-based unified compact modelling strategy for process-induced and statistical variability in 14-nm double gate SOI FinFET technology. There is strong interplay between process and statistical variability in FinFET technology and failure to capture the correlations between them can lead to an inaccurate estimation of overall statistical variability with errors of up to 30%. Therefore a new unified compact modelling strategy for variability, based on comprehensive atomistic simulations within the CD corner space, is presented. First, an extended uniform compact model is built to capture CD process variation using a set of parameters, and then statistical variability is extracted using another small set of `statistical' parameters. Later, the response of the extracted statistical parameters over the CD space is characterised, and finally used in a PCA method to generate the unified compact models capturing both process and statistical variability over the whole CD variation space.
Complete Sequencing and Pan-Genomic Analysis of Lactobacillus delbrueckii subsp. bulgaricus Reveal Its Genetic Basis for Industrial Yogurt Production

Lactobacillus delbrueckii subsp. bulgaricus (Lb. bulgaricus) is an important species of Lactic Acid Bacteria (LAB) used for cheese and yogurt fermentation. The genome of Lb. bulgaricus 2038, an industrial strain mainly used for yogurt production, was completely sequenced and compared against the other two ATCC collection strains of the same subspecies. Specific physiological properties of strain 2038, such as lysine biosynthesis, formate production, aspartate-related carbon-skeleton intermediate metabolism, unique EPS synthesis and efficient DNA restriction/modification systems, are all different from those of the collection strains that might benefit the industrial production of yogurt. Other common features shared by Lb. bulgaricus strains, such as efficient protocooperation with Streptococcus thermophilus and lactate production as well as well-equipped stress tolerance mechanisms may account for it being selected originally for yogurt fermentation industry. Multiple lines of evidence suggested that Lb. bulgaricus 2038 was genetically closer to the common ancestor of the subspecies than the other two sequenced collection strains, probably due to a strict industrial maintenance process for strain 2038 that might have halted its genome decay and sustained a gene network suitable for large scale yogurt production.
Evaluate the Sensitivity and Specificity Echocardiography in Trans-Doppler and Tissue Doppler Method in the Estimation of Left Ventricular End-Diastolic Pressure

Background: Non-invasive survey of left ventricular end-diastolic pressure (LVEDP) by transmitral Doppler echocardiography and tissue Doppler imaging carries important information about left ventricular diastolic function in chosen subsets of patients. This study is planned to assess whether mitral annular velocities (lateral annulus) as assessed by tissue Doppler imaging and transmitral Doppler echocardiography are associated with invasive measures of left ventricular end diastolic pressure and also the estimation of sensitivity and specificity of these methods. Methods: One hundred ten consecutive patients admitted to cardiac catheterization underwent simultaneous Doppler interrogation measurements of left ventricular pressure were obtained with fluid-filled pressure. The E/Ea ratio associated well with LVEDP (P<0.005 r=0.4) and the correlation more marked in the patients with reduced contractile function. This correlation was independent of gender. Results: The E/Ea ration of <8 best discriminated elevated (LVEDP>12) from normal LVEDP with a sensitivity of 73.5% and specificity 57.8%, PPV and NPV were 75.75% and 55% respectively. Our study results also showed that quantitative estimation of LVEDP could be suggested by the equation of LVEDP=1.2 E/Ea+6.67± 8 mmHg P<0.005 B=0.4. Male-LVEDP=0.9 E/Ea + 7.78±7.67 mmHg (r=0.4 Pa<0.005) EF>_50% -+LVEDP=1.48 E/Ea + 9.05±5.23 (r=0.4 P<0.05) EF<50% -+LVEDP=0.76 E/Ea + 8.4±2.3 (r=0.5 P<0.005)
Impaired Outcome-Specific Devaluation of Instrumental Responding in Mice with a Targeted Deletion of the AMPA Receptor Glutamate Receptor 1 Subunit

The present study evaluated the proposal that mice with a targeted deletion of the glutamate receptor 1 (GluR1) subunit of the AMPA receptor are impaired in using an instrumental or pavlovian signal to gain access to a representation of the sensory-specific motivational properties of a primary reward. In experiment 1, mice were trained to approach two goal boxes in a plus-maze; each goal box contained a different reward (sucrose solution vs food pellet). After acquisition, one of the rewards was devalued by an outcome-specific satiety procedure. Subsequent test trials performed in extinction showed an increase in the latency to enter the devalued goal arm, relative to the nondevalued goal arm in control but not GluR1-/- mice. In experiment 2, a similar outcome-specific satiety procedure was used to examine the effects of reward devaluation on an instrumental nose-poke response. During testing, control but not GluR1-/- mice decreased their rate of responding on a nose poke associated with a devalued reward. A subsequent choice test showed that GluR1-/- mice were able to discriminate between the devalued and nondevalued outcomes used in both experiments. These deficits mirror those seen after lesions of the basolateral amygdala and suggests that GluR1-mediated neurotransmission in this region contributes to encoding the relationship between sensory-specific aspects of reward and their incentive value.
Rainfall-runoff modelling using genetic programming

The problem of accurately determining river flows from rainfall, evaporation and other factors, occupies an important place in hydrology. The rainfall-runoff process is believed to be highly non-linear, time varying, spatially distributed and not easily described by simple models. Practitioners in water resources have embraced data-driven modelling approaches enthusiastically, as they are perceived to overcome some of the difficulties associated with physics-based approaches. Such approaches have proved to be an effective and efficient way to model the rainfallrunoff process in situations where enough data on physical characteristics of catchment is not available or when it is essential to predict the flow in the shortest possible time to enable sufficient time for notification and evacuation procedures.
Angiotensin-converting enzyme inhibitors and cognitive decline in older adults with hypertension: results from the Cardiovascular Health Study.

BACKGROUND Hypertension (HTN) is a risk factor for dementia, and animal studies suggest that centrally active angiotensin-converting enzyme (ACE) inhibitors (those that cross the blood-brain barrier) may protect against dementia beyond HTN control. METHODS Participants in the Cardiovascular Health Study Cognition Substudy with treated HTN and no diagnosis of congestive heart failure (n = 1054; mean age, 75 years) were followed up for a median of 6 years to determine whether cumulative exposure to ACE inhibitors (as a class and by central activity), compared with other anti-HTN agents, was associated with a lower risk of incident dementia, cognitive decline (by Modified Mini-Mental State Examination [3MSE]), or incident disability in instrumental activities of daily living (IADLs). RESULTS Among 414 participants who were exposed to ACE inhibitors and 640 who were not, there were 158 cases of incident dementia. Compared with other anti-HTN drugs, there was no association between exposure to all ACE inhibitors and risk of dementia (hazard ratio [HR], 1.01; 95% confidence interval [CI], 0.88-1.15), difference in 3MSE scores (-0.32 points per year; P = .15), or odds of disability in IADLs (odds ratio [OR], 1.06; 95% CI, 0.99-1.14). Adjusted results were similar. However, centrally active ACE inhibitors were associated with 65% less decline in 3MSE scores per year of exposure (P = .01), and noncentrally active ACE inhibitors were associated with a greater risk of incident dementia (adjusted HR, 1.20; 95% CI, 1.00-1.43 per year of exposure) and greater odds of disability in IADLs (adjusted OR, 1.16; 95% CI, 1.03-1.30 per year of exposure) compared with other anti-HTN drugs. CONCLUSIONS While ACE inhibitors as a class do not appear to be independently associated with dementia risk or cognitive decline in older hypertensive adults, there may be within-class differences in regard to these outcomes. These results should be confirmed with a randomized clinical trial of a centrally active ACE inhibitor in the prevention of cognitive decline and dementia.
Floating Exchange Rates: Theories and Evidence

1. Introduction: Some Basic Concepts and Stylised facts and the Case For (and Against) Floating Exchange Rates 2. Purchasing Power Parity and the PPP Puzzle 3. The Economics of the PPP Puzzle 4. The Flexible Price Monetary Model 5. The Sticky Price Monetary Model 6. Empirical Evidence on the Monetary Exchange Rate Model 7. Currency Substitution and Portfolio Balance Models 8. Real Exchange Rate Determination: Theory and Evidence 9. Equilibrium Exchange Rates: Measurement and Misalignment 10. The New Open Economy Macroeconomics and Exchange Rate Behaviour 11. The New Open Economy Macroeconomics: Pricing to Market and Exchange Rate Volatility Redux 12. The Economics of Fixed Exchange Rates, Part 1: Target Zone Models 13. The Economics of Fixed Exchange Rates, Part 2: Speculative Attack Models and Contagion 14. The Market Microstructure Approach to the Foreign Exchange Market 15. Spot and Forward Exchange Rates and the Forward Premium Puzzle
Extended Family Networks in Rural Mexico: A Descriptive Analysis

We provide descriptive evidence on the characteristics of a household's extended family network using data from the Progresa social assistance program in rural Mexico. We exploit information on the paternal and maternal surnames of household heads and their spouses and the patronymic naming convention to identify the inter and intra generational family links of each household to others in the village. This provides an almost complete mapping of extended family networks structures across 506 Mexican villages, covering 22,000 households and over 130,000 individuals. We then provide evidence on (i) whether husbands and wives differ in the extent to which members of their extended family are located in geographic proximity; (ii) the characteristics that predict the existence of extended family links; (iii) the similarity of households within the same family network in terms of their poverty, and how this differs within and between generations of the extended family.
Discriminative Bi-Term Topic Model for Headline-Based Social News Clustering

Social news are becoming increasingly popular. News organizations and popular journalists are starting to use social media more and more heavily for broadcasting news. The major challenge in social news clustering lies in the fact that textual content is only a headline, which is much shorter than the fulltext. Previous works showed that the bi-term topic model (BTM) is effective in modeling short text such as tweets. However, the drawback is that all non-stop terms are considered equally in forming the bi-terms. In this paper, a discriminative bi-term topic model ($d$-BTM) is presented, which tries to exclude less indicative bi-terms by discriminating topical terms from general and document-specific ones. Experiments on {TDT4} and Reuter-21578 show that using merely headlines, the $d$-BTM model is able to induce latent topics that are nearly as good as that are generated by LDA using news fulltext as evidence. The major contribution of this work lies in the empirical study on the reliability of topic modeling using merely news headlines.
Magical thinking in predictions of negative events: Evidence for tempting fate but not for a protection effect

In this paper we test two hypotheses regarding magical thinking about the perceived likelihood of future events. The first is that people believe that those who “tempt fate” by failing to take necessary precautions are more likely to suffer negative outcomes. The second is the “protection effect”, where reminding people of precautions they have taken leads them to see related risks as less likely. To this end, we describe the results from three attempted direct replications of a protection effect experiment reported in Tykocinski (2008) and two replications of a tempting fate experiment reported in Risen and Gilovich (2008) in which we add a test of the protection effect. We did not replicate the protection effect but did replicate the tempting fate effect.
Determination of Zygosity in Adult Chinese Twins Using the 450K Methylation Array versus Questionnaire Data

Previous studies have shown that both single nucleotide polymorphisms (SNPs) and questionnaires-based method can be used for twin zygosity determination, but few validation studies have been conducted using Chinese populations. In the current study, we recruited 192 same sex Chinese adult twin pairs to evaluate the validity of using genetic markers-based method and questionnaire-based method in zygosity determination. We considered the relatedness analysis based on more than 0.6 million SNPs genotyping as the golden standards for zygosity determination. After quality control, qualified twins were left for relatedness analysis based on identical by descent calculation. Then those same sex twin pairs were included in the zygosity questionnaire validation analysis. Logistic regression model was applied to assess the discriminant ability of age, sex and the three questions in zygosity determination. Leave one out cross-validation was used as a measurement of internal validation. The results of zygosity determination based on 65 SNPs in 450k methylation array were all consistent with genotyping. Age, gender, questions of appearance confused by strangers and previously perceived zygosity consisted of the most predictable model with a consistency rate of 0.8698, cross validation predictive error of 0.1347. For twin studies with genotyping and\or 450k methylation array, there would be no need to conduct other zygosity testing for the sake of costs consideration.
Fixed Effects Regression Methods In SAS ®

Fixed effects regression methods are used to analyze longitudinal data with repeated measures on both independent and dependent variables. They have the attractive feature of controlling for all stable characteristics of the individuals, whether measured or not. This is accomplished by using only within-individual variation to estimate the regression coefficients. This paper surveys the wide variety of fixed effects methods and their implementation in SAS, specifically, linear models with PROC GLM, logistic regression models with PROC LOGISTIC, models for count data with PROC GENMOD, and survival models with PROC PHREG.
CLUSTER PRIORITY BASED SENTENCE RANKING

This paper presents a cluster priority ranking based approach for extractive automatic text summarization that aggregates different cluster ranks for final sentence scoring. This approach does not require any learning, feature weighting and semantic processing. Surface level features combinations are used for individual cluster scoring. Proposed approach produces quality summaries without using title feature. Experimental results on DUC 2002 dataset proves robustness of proposed approach as compared to other surface level approaches using ROUGE evaluation matrices.
Particles with coordinated patches or windows from oil-in-water emulsions

In this paper, we demonstrated a unique and simple method for fabricating colloidal particles of complex structures using oil-in-water emulsion droplets as confined geometries. A variety of structural motifs were produced using binary colloids of microspheres of polystyrene (PS) or silica and nanosized particles as the second component. When PS or silica microspheres and PS macromolecules were dispersed in oil-in-water emulsion droplets, particles with well-coordinated patches were obtained because the PS macromolecules partially covered the microsphere clusters. When silica or gold nanoparticles were dispersed together with the PS microspheres in oil-in-water emulsion droplets instead of PS macromolecules, composite particles with patches were obtained. In this case, silica or gold shell structures with well-coordinated windows were produced by selectively removing the large PS microspheres from the organic−inorganic composite clusters.
Quantum field kinetics of QCD: Quark-gluon transport theory for light-cone-dominated processes.

A quantum kinetic formalism is developed to study the dynamical interplay of quantum and statistical-kinetic properties of non-equilibrium multi-parton systems produced in high-energy QCD processes. The approach provides the means to follow the quantum dynamics in both space-time and energy-momentum, starting from an arbitrary initial conguration of high-momentum quarks and gluons. Using a generalized functional integral representation and adopting the ‘closed-time-path’ Green function techniques, a self-consistent set of equations of motions is obtained: a GinzburgLandau equation for a possible color background eld, and Dyson-Schwinger equations for the 2-point functions of the gluon and quark elds. By exploiting the ‘two-scale nature’ of light-cone dominated QCD processes, i.e. the separation between the quantum scale that species the range of short-distance quantum fluctuations, and the kinetic scale that characterizes the range of statistical binary interactions, the quantum-eld equations of motion are converted into a corresponding set of ‘renormalization equations’ and ‘transport equations’. The former describe renormalization and dissipation eects through the evolution of the spectral density of individual, dressed partons, whereas the latter determine the statistical occurrence of scattering processes among these dressed partons. The renormalization equations and the transport equations are coupled, and hence must be solved self-consistently. This amounts to evolving the multi-parton system, from a specied initial conguration, in time and full 7-dimensional phase-space, constrained by the Heisenberg uncertainty principle. This quantum-kinetic description provides a probabilistic interpretation and is therefore of important practical value for the solution of the dynamical equations of motion, suggesting for instance the possibility of simulating the multi-particle dynamics with Monte Carlo methods.
UNITOR: Aspect Based Sentiment Analysis with Structured Learning

In this paper, the UNITOR system participating in the SemEval-2014 Aspect Based Sentiment Analysis competition is presented. The task is tackled exploiting Kernel Methods within the Support Vector Machine framework. The Aspect Term Extraction is modeled as a sequential tagging task, tackled through SVM hmm . The Aspect Term Polarity, Aspect Category and Aspect Category Polarity detection are tackled as a classification problem where multiple kernels are linearly combined to generalize several linguistic information. In the challenge, UNITOR system achieves good results, scoring in almost all rankings between the 2 nd and the 8 th position within about 30 competitors.
Strategic Renewal and its Effect on Small Firm Performance

In this paper, we investigate the relationship between strategic renewal and the performance of smaller firms (less than 100 employees). We use a panel of micro data on about 1000 Dutch firms. The dataset contains information on aspects of strategic renewal, including process innovation and knowledge management. In our regression analyses we explain the variation in firm performance and we explicitly control for reversed causality, business cycle effects, sector effects, and firm age. We find that market research, an active external network for knowledge acquisition and strategic efforts into the improvement of internal processes are positively related to turnover growth. Furthermore, codification of knowledge, cooperation with partner firms and the provision of training to employees directly relates to employment growth. The results emphasize the importance of both knowledge absorption and knowledge creation to the success of innovative efforts in small firms. We find that the impact of the various measures varies with firm size. One further notable finding is that the ownership of patents negatively impacts small firm performance, particularly for the smallest firms in our sample.
Increased arterial stiffness in children on haemodialysis.

BACKGROUND Measures of aortic stiffness--aortic pulse wave velocity (PWV) and augmentation index (AIx)--have been shown to be powerful predictors of survival in adult haemodialysis (HD) patients. Very few data have been reported regarding arterial stiffness in paediatric renal populations. METHODS PWV and aortic AIx were determined from contour analysis of arterial waveforms recorded by applanation tonometry using a SphygmoCor device in 14 children on HD (age = 14.1 years) and in 15 age, height matched children controls. RESULTS Pre-HD AIx (29.7 +/- 15.4%) and PWV (6.6 +/- 1.0 m/s) were significantly higher compared with children controls (8.3 +/- 8.0% and 5.4 +/- 0.6 m/s, respectively, P < 0.0001). The only significant difference between normal and HD children was BP level: 103/61 vs 114/72 mmHg, P < 0.05. In children of HD patients, a multiple linear regression model including BP, age, height, weight, Ca and P levels as independent variables accounted for 57% of the variability in AIx. Dialysis had no impact on AIx (post-HD: 28.5 +/- 12.7%) or on PWV (post-HD: 6.7 +/- 0.8 m/s). CONCLUSIONS We show, in this first-ever report of increased arterial stiffness in children on dialysis, that end-stage renal disease is associated with abnormalities in arterial wall elastic properties, comparable with adult levels, even in childhood. Most importantly, the absence of a discernible amelioration with dialysis implies that purely structural and not functional alterations lie behind the increased arterial stiffness.