Miracle-dz/UniFAR-FTUs huggingface dataset:
ReliefF-Based EEG Sensor Selection Methods for Emotion Recognition

Electroencephalogram (EEG) signals recorded from sensor electrodes on the scalp can directly detect the brain dynamics in response to different emotional states. Emotion recognition from EEG signals has attracted broad attention, partly due to the rapid development of wearable computing and the needs of a more immersive human-computer interface (HCI) environment. To improve the recognition performance, multi-channel EEG signals are usually used. A large set of EEG sensor channels will add to the computational complexity and cause users inconvenience. ReliefF-based channel selection methods were systematically investigated for EEG-based emotion recognition on a database for emotion analysis using physiological signals (DEAP). Three strategies were employed to select the best channels in classifying four emotional states (joy, fear, sadness and relaxation). Furthermore, support vector machine (SVM) was used as a classifier to validate the performance of the channel selection results. The experimental results showed the effectiveness of our methods and the comparison with the similar strategies, based on the F-score, was given. Strategies to evaluate a channel as a unity gave better performance in channel reduction with an acceptable loss of accuracy. In the third strategy, after adjusting channels’ weights according to their contribution to the classification accuracy, the number of channels was reduced to eight with a slight loss of accuracy (58.51% ± 10.05% versus the best classification accuracy 59.13% ± 11.00% using 19 channels). In addition, the study of selecting subject-independent channels, related to emotion processing, was also implemented. The sensors, selected subject-independently from frontal, parietal lobes, have been identified to provide more discriminative information associated with emotion processing, and are distributed symmetrically over the scalp, which is consistent with the existing literature. The results will make a contribution to the realization of a practical EEG-based emotion recognition system.
Forecast Evaluation in Call Centers: Combined Forecasts, Flexible Loss Functions and Economic Criteria

Accurate forecasts of incoming calls are crucial to optimal staffing decisions in call centers. This paper evaluates a wide range of models and forecast combination techniques by means of statistical and economic criteria. Relative to the previous literature, this paper is novel in several respects. In particular, the statistical evaluation of competing models is carried out by using a flexible loss function as input to pairwise and joint forecast diagnostic checks. Informative rankings across alternative single models and different groups of models are obtained. Moreover, models are evaluated from the perspective of a manager, who needs reliable forecasts to dimension the call center. Money metrics of forecasting performance are computed, which are based on the economic value of information and the certainty equivalent.
A Probabilistic Approach to Seismic Hazard in Metropolitan France

In this study, we applied a probabilistic methodology to seismic hazard assessment in metropolitan France. For that purpose we determined an attenuation law adapted to the French context. This law holds for peak ground acceleration on stiff bedrock for earthquakes with local magnitudes between 2.5 and 5.6 recorded in near field (at distances between 3 and 50 km). Geological conditions are taken into account by means of a three-categories classification of lithologies based on a 1/1,000,000 geological map. The seismotectonic zonation consists of areas of diffuse seismicity characterized by a frequency-magnitude distribution. In southeastern France, active faults are considered in a test case and are assumed to follow the characteristic earthquake model. We performed hazard curves for six French cities and maps of peak horizontal ground accelerations expected for return periods of 475, 975, and 1975 years in the country. Sensitivity tests have been performed. The uncertainty introduced by ground-motion variability seems minor compared with that due to the choice of the attenuation law. This study points to the importance of testing internal consistency of the various data and laws used in any seismic hazard analysis (in particular, here the type of magnitude used to predict ground motion). If not, some systematic bias is introduced that may result in systematic errors on peak ground acceleration determination. We also show that the introduction of possibly very large and infrequent events, known only from paleoseismic investigations, may have a dramatic impact on the hazard, especially when long periods of time are considered.
Government Tax Revenue, Expenditure and Causality: the Experience of India

The objective of the study is to analyse the dynamics of causal relationship between revenue and expenditure. Although a number of studies have shed light on this issue using Granger-Sims causality tests, the present study attempts to quantify various feedback between revenue and expenditure, along the lines suggested by Geweke and then the results are compared with Granger's causality test. The results showed the absence of co-integration between Government tax revenue and expenditure variables implying no evidence of a stable long run relationship between them. Geweke's test provided different inferences for the causal relationship between TR and GE. In the mdel with TR as the dependent variable, Geweke's test indicated the existence of bi-directional causality, while in the case of the model with GE as dependent variable, Geweke's test showed the absence of any causal relationship between the variables. The Granger's test suggests the uni-directional causality flowing from government expenditure to revenue. To conclude, the causal inferences were found to be sensitive to the specification of the model.
Entry and Prices: Evidence from the Chilean Supermarket Industry

One of the most significant developments in the last couple of decades in the retail industry has been the emergence of large supermarkets (hypermarkets). The purpose of this paper is to investigate the effect on prices of the entry of a large supermarket into a given location. We use a panel with data from fifteen cities in Chile for the period 1998:I – 2004:IV. The dependent variable is the price of a bundle of 52 food products in each city relative to Santiago. We find that the entry of a hypermarket to a given city reduces prices in that local market by ten percent. Most interestingly, we also find that half of this effect takes place the year before the supermarket actually opens for business.
Substructures in WINGS clusters

Aims. We search for and characterize substructures in the projected distribution of galaxies observed in the wide field CCD images of the 77 nearby clusters of the Wide-field Nearby Galaxy-cluster Survey (WINGS). This sample is complete in X-ray flux in the redshift range 0.04 < z < 0.07. Methods. We search for substructures in WINGS clusters with DEDICA, an adaptive-kernel procedure. We test the procedure on Monte-Carlo simulations of the observed frames and determine the reliability for the detected structures. Results. DEDICA identifies at least one reliable structure in the field of 55 clusters. 40 of these clusters have a total of 69 substructures at the same redshift of the cluster (redshift estimates of substructures are from color-magnitude diagrams). The fraction of clusters with subelusters (73%) is higher than in most studies. The presence of subclusters affects the relative luminosities of the brightest cluster galaxies (BCGs). Down to L ∼ 10 11 L ⊙ , our observed differential distribution of subeluster luminosities is consistent with the theoretical prediction of the differential mass function of substructures in cosmological simulations.
CHARACTERISTIC LENGTHS OF MAGNETIC FIELD IN MAGNETOHYDRODYNAMIC TURBULENCE

In the framework of turbulence dynamo, flow motions amplify a weak seed magnetic field through the stretching of field lines. Although the amplification process has been a topic of active research, less attention has been paid to the length scales of magnetic field. In this Letter, we describe a numerical study on characteristic lengths of magnetic field in magnetohydrodynamic turbulence. We considered the case of very weak or zero mean magnetic field, which is applicable to the turbulence in the intergalactic space. Our findings are as follows. (1) At saturation, the peak of magnetic field spectrum occurs at ∼L0/2, where L0 is the energy injection scale, while the most energy containing scale is ∼L0/5. The peak scale of spectrum of projected, two-dimensional field is ∼L0. (2) During the stage of magnetic field amplification, the energy equipartition scale shows a power law increase of ∼t1.5, while the integral and curvature scales show a linear increase. The equipartition, integral, and curvature scales saturate at ∼L0, ∼0.3L0, and ∼0.15L0, respectively. (3) The coherence length of magnetic field defined in the Faraday rotation measure (RM) due to the intergalactic magnetic field (IGMF) is related to the integral scale. We present a formula that expresses the standard deviation of RM, σRM, in terms of the integral scale and rms strength of the IGMF, and estimate that σRM would be ∼100 and ∼ a few rad m−2 for clusters and filaments, respectively.
Talagrand's Convolution Conjecture on Gaussian Space

Smoothing properties of the noise operator on the discrete cube and on Gaussian space have played a pivotal role in many fields. In particular, these smoothing effects have seena broad range of applications in theoretical computer science. We exhibit new regularization properties of the noise operator on Gaussian space. More specifically, we show that the mass on level sets of a probability density decays uniformly under the Ornstein-Uhlenbeck semi group. This confirms positively the Gaussian case of Talagrand's convolution conjecture (1989)on the discrete cube. A major theme is our use of an It o process (the "F"ollmer drift")which can be seen as an entropy-optimal coupling between the Gaussian measure and another given measure on Gaussian space. To analyze this process, we employ stochastic calculus and Girsanov's change of measure formula. The ideas and tools employed here provide a new perspective on hyper contractivity in Gaussian space and the discrete cube. In particular, our work gives a new way of studying "small" sets in product spaces (e.g., Sets of size 2o(n) in the discrete cube) using a form of regularized online gradient descent.
Variation of the Linkage of Root Function with Root Branch Order

Mounting evidence has shown strong linkage of root function with root branch order. However, it is not known whether this linkage is consistent in different species. Here, root anatomic traits of the first five branch order were examined in five species differing in plant phylogeny and growth form in tropical and subtropical forests of south China. In Paramichelia baillonii, one tree species in Magnoliaceae, the intact cortex as well as mycorrhizal colonization existed even in the fifth-order root suggesting the preservation of absorption function in the higher-order roots. In contrast, dramatic decreases of cortex thickness and mycorrhizal colonization were observed from lower- to higher-order roots in three other tree species, Cunninghamia lanceolata, Acacia auriculiformis and Gordonia axillaries, which indicate the loss of absorption function. In a fern, Dicranopteris dichotoma, there were several cortex layers with prominently thickened cell wall and no mycorrhizal colonization in the third- and fourth-order roots, also demonstrating the loss of absorptive function in higher-order roots. Cluster analysis using these anatomic traits showed a different classification of root branch order in P. baillonii from other four species. As for the conduit diameter-density relationship in higher-order roots, the mechanism underpinning this relationship in P. baillonii was different from that in other species. In lower-order roots, different patterns of coefficient of variance for conduit diameter and density provided further evidence for the two types of linkage of root function with root branch order. These linkages corresponding to two types of ephemeral root modules have important implication in the prediction of terrestrial carbon cycling, although we caution that this study was pseudo-replicated. Future studies by sampling more species can test the generality of these two types of linkage.
An Empirical Survey of Frontier Efficiency Measurement Techniques in Education

Educational institutions worldwide are increasingly the subject of analyses aimed at defining, measuring and improving efficiency. However, despite the importance of efficiency measurement in education, it is only relatively recently that the more advanced econometric and mathematical programming frontier techniques have been applied to primary and secondary schools, university departments and degree programmes, and universities as a whole. This paper attempts to provide a synoptic survey of the comparatively few empirical analyses in education using frontier efficiency measurement techniques. Both the measurement of inefficiency in education and the determinants of educational efficiency are examined.
Analyzing the Effect of Learning Styles and Study Habits of Distance Learners on Learning Performances: A Case of an Introductory Programming Course.

This study examined the relationships among learning styles, study habits, and learning performances in an online programming language course. Sixty-two sophomore students who enrolled in an online introductory programming course participated in the study. Kolb’s Learning Style Inventory (LSI) was used to measure the students’ learning styles. Another inventory developed by the researcher was used to determine learners’ study habits. An achievement test was used to put forward their learning performances. As a result, significant relationships between learning styles, study habits, and learning performances were revealed. The results present some ideas about distance learners’ learning styles and study habits for instructors who wish to incorporate synchronous courses and support learners.
European Policy Coordination: An Evaluation

According to the European Community Commission the present level of unemployment in Europe should not only last but worsen in the foreseeable future (see CCE 1984). By 1988 the overall unemployment rate in Europe should reach 11,4% if the « optimistic » assumptions retained for the labor supply are to be realized.These are of course average figures but on the whole they correctly reflect the extraordinary convergence of European deflationary policies. Given structural differences, which remain very limited when one compares them to the other Western economies, the European governments seem to have settled for the same macroeconomic strategies. Of course, they have chosen different timings. France, for example, has grown more than its partners in 1981-1982 but is now experiencing a prolonged recession. Whereas West Germany is doing better as far as GNP is concerned but grew very little in the early 80 s. On the whole however a back of the envelope calculation of « sacrifice ratios » for the leading European economies would yield quite similar results. All over Europe disinflation has been achieved at a high output cost and it is not clear that any country has really done better than its partners.
Tracking Dynamic Boundaries Using Sensor Network

We examine the problem of tracking dynamic boundaries occurring in natural phenomena using a network of range sensors. Two main challenges of the boundary tracking problem are accurate boundary estimation from noisy observations and continuous tracking of the boundary. We propose Dynamic Boundary Tracking (DBTR), an algorithm that combines the spatial estimation and temporal estimation techniques. The regression-based spatial estimation technique determines discrete points on the boundary and estimates a confidence band around the entire boundary. In addition, a Kalman Filter-based temporal estimation technique tracks changes in the boundary and aperiodically updates the spatial estimate to meet accuracy requirements. DBTR provides a low energy solution compared to similar periodic update techniques to track boundaries without requiring prior knowledge about the dynamics. Experimental results demonstrate the effectiveness of our algorithm; estimated confidence bands indicate a loss of coverage of less than 2 to 5 percent for a variety of boundaries with different spatial characteristics.
Calibration of financial models using quasi-Monte Carlo

Abstract In the area of financial mathematics Monte Carlo simulation is often successfully used to estimate the prices of certain products. However in many cases calibrating Monte Carlo based models to market prices turns out to be difficult due to stochastic noise arising in the objective functionals. This noise can be reduced by the use of fixed point-sets of random numbers which are reused for every new set of parameters (i.e. in every new step of the optimization algorithm used for calibration). In this paper we argue that the above technique can be enhanced by using fixed low discrepancy point-sets (quasi-Monte Carlo method) instead of ones originating from Pseudo-Random-Number generators. The method is applied to two different financial models and the results are compared with the classical one.
Policy Impact Analysis on Investments and Disinvestments under Competition: A Real Options Approach

In consequence of changes in general conditions, a higher level of investments and disinvestments in agriculture can be expected. To date, however, there are no policy impact analyses on both investments and disinvestments in competitive agricultural markets in a dynamic-stochastic context. This paper aims to develop a conceptual real options market model, which allows the impact assessment of different political schemes on investment and disinvestment thresholds and the sectoral welfare. Exemplarily, the effects of price floors, investment subsidies and production ceilings are analysed. The results show that the consideration of limited reversibility, that is disinvestments, is of relevance as it can impact the assessment of specific policies.
Association of genetic variants with dyslipidemia and chronic kidney disease in a longitudinal population-based genetic epidemiological study

We previously identified 9 genes and chromosomal region 3q28 as susceptibility loci for myocardial infarction, ischemic stroke, or chronic kidney disease (CKD) in Japanese individuals by genome-wide or candidate gene association studies. In the present study, we examined the association of 13 polymorphisms at these 10 loci with the prevalence of hypertriglyceridemia, hyper-low-density lipoprotein (LDL) cholesterolemia, hypo-high-density lipoprotein (HDL) cholesterolemia, or CKD in community-dwelling Japanese individuals. The study subjects comprised 6,027 individuals who were recruited to the Inabe Health and Longevity Study, a longitudinal genetic epidemiological study of atherosclerotic, cardiovascular and metabolic diseases. The subjects were recruited from individuals who visited the Health Care Center at Inabe General Hospital for an annual health checkup, and they were followed up each year (mean follow-up period, 5 years). Longitudinal analysis with a generalized estimating equation and with adjustment for covariates revealed that rs6929846 of butyrophilin, subfamily 2, member A1 gene (BTN2A1) was significantly associated with the prevalence of hypertriglyceridemia (P=0.0001), hyper-LDL cholesterolemia (P=0.0004), and CKD (P=0.0007); rs2569512 of interleukin enhancer binding factor 3 (ILF3) was associated with hyper-LDL cholesterolemia (P=0.0029); and rs2074379 (P=0.0019) and rs2074388 (P=0.0029) of alpha-kinase 1 (ALPK1) were associated with CKD. Longitudinal analysis with a generalized linear mixed-effect model and with adjustment for covariates among all individuals revealed that rs6929846 of BTN2A1 was significantly associated with the serum concentrations of triglycerides (P=0.0011), LDL cholesterol (P=3.3×10−5), and creatinine (P=0.0006), as well as with the estimated glomerular filtration rate (eGFR) (P=0.0004); rs2569512 of ILF3 was shown to be associated with the serum concentration of LDL cholesterol (P=0.0221); and rs2074379 (P=0.0302) and rs2074388 (P=0.0336) of ALPK1 were shown to be associated with the serum concentration of creatinine. Similar analysis among individuals not taking any anti-dyslipidemic medication revealed that rs6929846 of BTN2A1 was significantly associated with the serum concentrations of triglycerides (P=8.3×10−5) and LDL cholesterol (P=0.0004), and that rs2569512 of ILF3 was associated with the serum concentration of LDL cholesterol (P=0.0010). BTN2A1 may thus be a susceptibility gene for hypertriglyceridemia, hyper-LDL cholesterolemia and CKD in Japanese individuals.
The Use of Theoretical Constructs in Studying Health Information Technologies

Theoretical constructs are the foundational building blocks of theories and are utilized as a way of understanding and explaining phenomena. The use of theory and theoretical constructs to study health information technologies have varied based on research communities, research goals, and types of technology. Within the HCI community, there has been a long history of using theoretical constructs to help us understand the use of technology. In this position paper, drawing on our previous research in healthcare settings, I would like to discuss the role that theoretical constructs can play in helping us better understand the use of health information technologies. In particular, I am interested in exploring not only how these constructs can help us better understand issues but also how we can use these constructs in designing and implementing health information technologies. Author
Lightweight Fault Tolerance in Large-Scale Distributed Graph Processing

The success of Google's Pregel framework in distributed graph processing has inspired a surging interest in developing Pregel-like platforms featuring a user-friendly "think like a vertex" programming model. Existing Pregel-like systems support a fault tolerance mechanism called checkpointing, which periodically saves computation states as checkpoints to HDFS, so that when a failure happens, computation rolls back to the latest checkpoint. However, a checkpoint in existing systems stores a huge amount of data, including vertex states, edges, and messages sent by vertices, which significantly degrades the failure-free performance. Moreover, the high checkpointing cost prevents frequent checkpointing, and thus recovery has to replay all the computations from a state checkpointed some time ago. In this paper, we propose a novel checkpointing approach which only stores vertex states and incremental edge updates to HDFS as a lightweight checkpoint (LWCP), so that writing an LWCP is typically tens of times faster than writing a conventional checkpoint. To recover from the latest LWCP, messages are generated from the vertex states, and graph topology is recovered by replaying incremental edge updates. We show how to realize lightweight checkpointing with minor modifications of the vertex-centric programming interface. We also apply the same idea to a recently-proposed log-based approach for fast recovery, to make it work efficiently in practice by significantly reducing the cost of garbage collection of logs. Extensive experiments on large real graphs verified the effectiveness of LWCP in improving both failure-free performance and the performance of recovery.