Miracle-dz/UniFAR-FTUs huggingface dataset:
Wage distribution in Chile: does gender matter? a quantile regression approach

This paper analyzes gender differentials in the returns to education, the returns to experience, and gender wage differentials in the Chilean case. It uses the standard Mincerian wage equation and estimates it separately by gender using the quantile regression method. Then, using the Oaxaca decomposition, we breakdown the total wage gap into an explained term (due to differences in endowments) and into a residual (or unexplained term). Chilean nation-wide data for the years 1990, 1992, 1994, 1996 and 1998 are used in the estimations. The results show systematic differences in the returns to education and to experience by gender along the conditional wage distribution. The paper also finds clear evidence that the unexplained wage differential is higher in the upper quantiles of the conditional wage distribution. The results are remarkably stable and consistent across years.
A panoply of quantum algorithms

This paper's aim is to explore improvements to, and applications of, a fundamental quantum algorithm invented by Grover[1]. Grover's algorithm is a basic tool that can be applied to a large number of problems in computer science, creating quantum algorithms that are polynomially faster than fastest known and fastest possible classical algorithms that solve the same problems. Our goal in this paper is to make these techniques readily accessible to those without a strong background in quantum physics: we achieve this by providing a set of tools, each of which makes use of Grover's algorithm or similar techniques, which can be used as subroutines in many quantum algorithms. The tools we provide are carefully constructed: they are easy to use, and in many cases they are asymptotically faster than the best tools previously available. The tools we build on include algorithms by Boyer, Brassard, Hoyer and Tapp[2], Buhrman, Cleve, de Witt and Zalka[3] and Durr and Hoyer[4]. After creating our tools, we create several new quantum algorithms, each of which is faster than the fastest known deterministic classical algorithm that accomplishes the same aim, and some of which are faster than the fastest possible deterministic classical algorithm. These algorithms solve problems from the fields of graph theory and computational geometry, and some employ dynamic programming techniques. We discuss a breadth-first search that is faster than Θ(edges) (the classical limit) in a dense graph, maximum-points-on-a-line in O(N3/2 lgN) (faster than the fastest classical algorithm known), as well as several other algorithms that are similarly illustrative of solutions in some class of problem. Through these new algorithms we illustrate the use of our tools, working to encourage their use and the study of quantum algorithms in general.
Negativity Bias in Dangerous Drivers

The behavioral and cognitive characteristics of dangerous drivers differ significantly from those of safe drivers. However, differences in emotional information processing have seldom been investigated. Previous studies have revealed that drivers with higher anger/anxiety trait scores are more likely to be involved in crashes and that individuals with higher anger traits exhibit stronger negativity biases when processing emotions compared with control groups. However, researchers have not explored the relationship between emotional information processing and driving behavior. In this study, we examined the emotional information processing differences between dangerous drivers and safe drivers. Thirty-eight non-professional drivers were divided into two groups according to the penalty points that they had accrued for traffic violations: 15 drivers with 6 or more points were included in the dangerous driver group, and 23 drivers with 3 or fewer points were included in the safe driver group. The emotional Stroop task was used to measure negativity biases, and both behavioral and electroencephalograph data were recorded. The behavioral results revealed stronger negativity biases in the dangerous drivers than in the safe drivers. The bias score was correlated with self-reported dangerous driving behavior. Drivers with strong negativity biases reported having been involved in mores crashes compared with the less-biased drivers. The event-related potentials (ERPs) revealed that the dangerous drivers exhibited reduced P3 components when responding to negative stimuli, suggesting decreased inhibitory control of information that is task-irrelevant but emotionally salient. The influence of negativity bias provides one possible explanation of the effects of individual differences on dangerous driving behavior and traffic crashes.
The impact of personality on employee job performance: an empirical study of non-academic employees of the universities in the eastern province of Sri Lanka

Personality is a potentially important predictor of work behavior. Matching people to jobs matters is very important because when people do not fir with their jobs or the organization, they are more likely to leave, it create more prolem to tha organization to replace them. Many researchers have attempted to investigate the influence of individual, group, and organizational variables on job performance, but enough researches have not been done in Sri Lanka relevant io this area. This study is to gain a better understanding of the impact of personality on employee job performance of with reference to the non-academic employees of the universities operating in the eastern province of Sri Lanka. The conceptual model was formulated to the influence of employee personality on employee job performance. The study generated about 81 percent response rate from 190 nonacademic employees who had worked at these two Universities. Responses from the survey were statistically analyzed with the software SPSS validity and reliability of the questionnaire was satisfactory. It was found that employee personality had a strong positive correlation with employee job performance (r = 0.558). The result of simple regression analysisrevealed that employee personality was the strongest predictor, which explains 31.1% of the variation in employee job performance. The remaining 68.9% of variation not explain by this variable. The finding revealed the employee personality was found to be the critical personal factor to improve the employee job performance.
Implementation of Application Layer Multicast in OverSim

This paper presents an overview of the implementation of Application Layer Multicast (ALM) in OverSim, a simulation framework designed specifically for simulating overlay networks. OverSim builds upon the OMNeT++ discrete event simulator. In addition, the paper presents guidelines for further research work based on reliable and Quality of Service (QoS)-aware multicast overlay networks. This research work is part of a bigger research project, called "Routing in Overlay Networks (ROVER)" which is focused on unicast and multicast routing in overlay networks with QoS guarantees and congestion control facilities on top of existing and future Peer-to-Peer (P2P) networks.
Child's recognition of emotions in robot's face and body

Social robots can comfort and support children who have to cope with chronic diseases. In previous studies, a “facial robot”, the iCat, proved to show well-recognized emotional expressions that are important in social interactions. The question is if a mobile robot without a face, the Nao, can express emotions with its body. First, dynamic body postures were created and validated that express fear, happiness, anger, sadness and surprise. Then, fourteen children had to recognize emotions, expressed by both robots. Recognition rates were relatively high (between 68% and 99% accuracy). Only for the emotion “sad”, the recognition was better for the iCat (95%) compared to the Nao (68%). Providing context increased the number of correct recognitions. In a second session, the emotions were significantly better recognized than during the first session for both robots. In sum, we succeeded to design Nao emotions, which were well recognized and learned, and can be important ingredients of the social dialogs with children.
How robust is the SVM wound segmentation?

This paper investigates the robustness of automatic wound segmentation. The work builds upon an automatic segmentation procedure by the support vector machine (SVM)-classifier presented in [M. Kolesnik et al. (2004), (2005)]. Here we extend the procedure by incorporating textural features and the deformable snake adjustment to refine SVM-generated wound boundary. The robustness of SVM-based segmentation is tested against different feature spaces using a long sample of training images featuring a broad variety of wounds' appearance. Recommendations drawn from these experiments provide a useful guideline for the development of a software support system for the visual monitoring of chronic wounds in wound care units
The Aalborg model: problem-based and project-organized learning

This is a quite unique book, as the problem-based and project-organized models are not primarily reflected upon on the basis of educational theories, but rather upon the basis of the theories and methods of the various university programmes. Thus this book contains a profession-based approach to the further development of the problem-based and project-organized educational practice at the university. This profession-based approach, which has gradually developed at Aalborg University, shows that the educational ideas are alive and well at the decentralised departments, and that the educational model is integrated in relation to the various professions. This is a development which takes time – it takes time to integrate the educational ideas and philosophies and to develop models – but it also demands reflection and experience to discuss and develop the project-based educational approach on the basis of both professional and educational argumentation.
In vivo autofluorescence imaging of the human and macaque retinal pigment epithelial cell mosaic.

PURPOSE Retinal pigment epithelial (RPE) cells are critical for the health of the retina, especially the photoreceptors. A recent study demonstrated that individual RPE cells could be imaged in macaque in vivo by detecting autofluorescence with an adaptive optics scanning laser ophthalmoscope (AOSLO). The current study extended this method to image RPE cells in fixating humans in vivo and to quantify the RPE mosaic characteristics in the central retina of normal humans and macaques. METHODS The retina was imaged simultaneously with two light channels in a fluorescence AOSLO; one channel was used for reflectance imaging of the cones while the other detected RPE autofluorescence. The excitation light was 568 nm, and emission was detected over a 40-nm range centered at 624 nm. Reflectance frames were registered to determine interframe eye motion, the motion was corrected in the simultaneously recorded autofluorescence frames, and the autofluorescence frames were averaged to give the final RPE mosaic image. RESULTS In vivo imaging demonstrated that with increasing eccentricity, RPE cell density, and mosaic regularity decreased, whereas RPE cell size and spacing increased. Repeat measurements of the same retinal location 42 days apart showed the same RPE cells and distribution. CONCLUSIONS The RPE cell mosaic has been resolved for the first time in alert fixating human subjects in vivo using AOSLO. Mosaic analysis provides a quantitative database for studying normal and diseased RPE in vivo. This technique will allow longitudinal studies to track disease progression and assess treatment efficacy in patients and animal models of retinal disease.
A self-calibration of the Leica ScanStation C10 scanner

Similar to other surveying instruments, the observed data from terrestrial laser scanner (TLS) can be impaired with errors. Then, calibration routine is necessary for the TLS to ensure the quality of the data and also to make it applicable for surveying applications. There are two calibration approaches available: 1) component, and 2) system calibration. Due to the requirement of special laboratories and tools to perform component calibration, then this approach cannot be implemented by most of the TLS users. In contrast, system calibration that can be performed through self-calibration is more convenient and the requirements (e.g. room with targets) are easier to be provided. Self-calibration bundle adjustment is carry out using measured spherical coordinates (e.g. distance, horizontal and vertical angles) as observations. In extension to the functional model of each observation, a set of calibration parameters was used, which were determined in a self-calibration procedure. These parameters are derived from wellknown error sources of geodetic instruments as constant (a0), collimation axis (b0), trunnion axis (b1) and vertical circle index (c0) errors. Self-calibration was performed for Leica ScanStation C10 at laboratory with dimension 9m × 7m × 2.6m and 130 black and white targets were fairly distributed. Data obtained from seven scan station were processed and statistical analysis (e.g. t-test) has shown that only collimation axis (77.1") and vertical circle index (-62.4") errors are significant for the calibrated scanner.
Evaluation of inconsistency in networks of interventions.

BACKGROUND The assumption of consistency, defined as agreement between direct and indirect sources of evidence, underlies the increasingly popular method of network meta-analysis. No evidence exists so far regarding the extent of inconsistency in full networks of interventions or the factors that control its statistical detection. METHODS In this paper we assess the prevalence of inconsistency from data of 40 published networks of interventions involving 303 loops of evidence. Inconsistency is evaluated in each loop by contrasting direct and indirect estimates and by employing an omnibus test of consistency for the entire network. We explore whether different effect measures for dichotomous outcomes are associated with differences in inconsistency, and evaluate whether different ways to estimate heterogeneity affect the magnitude and detection of inconsistency. RESULTS Inconsistency was detected in from 2% to 9% of the tested loops, depending on the effect measure and heterogeneity estimation method. Loops that included comparisons informed by a single study were more likely to show inconsistency. About one-eighth of the networks were found to be inconsistent. The proportions of inconsistent loops do not materially change when different effect measures are used. Important heterogeneity or the overestimation of heterogeneity was associated with a small decrease in the prevalence of statistical inconsistency. CONCLUSIONS The study suggests that changing the effect measure might improve statistical consistency, and that an analysis of sensitivity to the assumptions and an estimator of heterogeneity might be needed before reaching a conclusion about the absence of statistical inconsistency, particularly in networks with few studies.
Grammatical error correction using neural machine translation

This paper presents the first study using neural machine translation (NMT) for grammatical error correction (GEC). We propose a twostep approach to handle the rare word problem in NMT, which has been proved to be useful and effective for the GEC task. Our best NMTbased system trained on the CLC outperforms our SMT-based system when testing on the publicly available FCE test set. The same system achieves an F0.5 score of 39.90% on the CoNLL-2014 shared task test set, outperforming the state-of-the-art and demonstrating that the NMT-based GEC system generalises effectively.
Draft Genome Sequences of Streptococcus pneumoniae with High-Level Resistance to Respiratory Fluoroquinolones

ABSTRACT Streptococcus pneumoniae is the leading cause of community-acquired pneumonia. Levofloxacin is a fluoroquinolone used for treatment of severe community-acquired pneumonia. Here, we describe the draft genome sequences of S. pneumoniae with emerging resistance to levofloxacin, resulting in failure of treatment of pneumococcal pneumonia.
Feel what you hear: haptic feedback as an accompaniment to mobile music playback

The paper describes the creation of a mobile music player accompanied with synchronised haptic feedback to create a novel method of audio playback on a mobile device. There has been extensive research into the development of audio haptic systems to enhance user interaction on mobile devices as well as providing useful information about users' surroundings while way-finding. We investigated an alternative collaboration of haptics and audio feedback which we present here. We believe that this collaboration provides a novel and fun method of interaction with a music playback application. Our results show that users enjoyed the combination of audio and haptic feedback and that users would very much like to see this type of sensory collaboration being incorporated into their own mobile device.
Sparse Support Recovery with Phase-Only Measurements

Sparse support recovery (SSR) is an important part of the compressive sensing (CS). Most of the current SSR methods are with the full information measurements. But in practice the amplitude part of the measurements may be seriously destroyed. The corrupted measurements mismatch the current SSR algorithms, which leads to serious performance degeneration. This paper considers the problem of SSR with only phase information. In the proposed method, the minimization of the l1 norm of the estimated sparse signal enforces sparse distribution, while a nonzero constraint of the uncorrupted random measurements' amplitudes with respect to the reconstructed sparse signal is introduced. Because it only requires the phase components of the measurements in the constraint, it can avoid the performance deterioration by corrupted amplitude components. Simulations demonstrate that the proposed phase-only SSR is superior in the support reconstruction accuracy when the amplitude components of the measurements are contaminated.
(2,2)-Secret Sharing scheme with improved share randomness

Visual secret sharing (VSS) is a method to scatter a secret image into shares of random patterns that have to be stacked together to reconstruct the secret. Since each share is a random pattern of black and white pixels, it is not enough to rebuild the secret from just one share. Stacking two shares reconstructs the first secret whereas rotating the first share by 90deg counterclockwise and stacking reconstructs the second secret. A novel algorithm to create both shares from two secrets with improved randomness is proposed in this paper. Share creation algorithm selects extended patterns of random pixels to satisfy contrast requirements of both secrets reconstructed by normal and rotated stacking. Proposed method have desirable security properties because of the improved randomness of shares.
Hydrogen sulphide suppresses human atrial fibroblast proliferation and transformation to myofibroblasts

Cardiac fibroblasts are crucial in pathophysiology of the myocardium whereby their aberrant proliferation has significant impact on cardiac function. Hydrogen sulphide (H2S) is a gaseous modulator of potassium channels on cardiomyocytes and has been reported to attenuate cardiac fibrosis. Yet, the mechanism of H2S in modulating proliferation of cardiac fibroblasts remains poorly understood. We hypothesized that H2S inhibits proliferative response of atrial fibroblasts through modulation of potassium channels. Biophysical property of potassium channels in human atrial fibroblasts was examined by whole‐cell patch clamp technique and their cellular proliferation in response to H2S was assessed by BrdU assay. Large conductance Ca2+‐activated K+ current (BKCa), transient outward K+ current (Ito) and inwardly rectifying K+ current (IKir) were found in human atrial fibroblasts. Current density of BKCa (IC50 = 69.4 μM; n = 6), Ito (IC50 = 55.1 μM; n = 6) and IKir (IC50 = 78.9 μM; n = 6) was significantly decreased (P < 0.05) by acute exposure to NaHS (a H2S donor) in atrial fibroblasts. Furthermore, NaHS (100–500 μM) inhibited fibroblast proliferation induced by transforming growth factor‐β1 (TGF‐β1; 1 ng/ml), Ang II (100 nM) or 20% FBS. Pre‐conditioning of fibroblasts with NaHS decreased basal expression of Kv4.3 (encode Ito), but not KCa1.1 (encode BKCa) and Kir2.1 (encode IKir). Furthermore, H2S significantly attenuated TGF‐β1–stimulated Kv4.3 and α‐smooth muscle actin expression, which coincided with its inhibition of TGF‐β–induced myofibroblast transformation. Our results show that H2S attenuates atrial fibroblast proliferation via suppression of K+ channel activity and moderates their differentiation towards myofibroblasts.
COMPUTATIONAL METHODS FOR THE STUDY OF DYNAMIC ECONOMIES

This book, according to its introduction, aims “to help researchers who know how to formulate an economic model but need computational techniques to obtain quantitative solutions” (p. 6). In this it succeeds admirably, but it also does more. The ﬁnal three chapters give good surveys of speciﬁc economic issues that have been successfully studied using computational methods.
Permutation tests for phylogenetic comparative analyses of high‐dimensional shape data: What you shuffle matters

Evaluating statistical trends in high‐dimensional phenotypes poses challenges for comparative biologists, because the high‐dimensionality of the trait data relative to the number of species can prohibit parametric tests from being computed. Recently, two comparative methods were proposed to circumvent this difficulty. One obtains phylogenetic independent contrasts for all variables, and statistically evaluates the linear model by permuting the phylogenetically independent contrasts (PICs) of the response data. The other uses a distance‐based approach to obtain coefficients for generalized least squares models (D‐PGLS), and subsequently permutes the original data to evaluate the model effects. Here, we show that permuting PICs is not equivalent to permuting the data prior to the analyses as in D‐PGLS. We further explain why PICs are not the correct exchangeable units under the null hypothesis, and demonstrate that this misspecification of permutable units leads to inflated type I error rates of statistical tests. We then show that simply shuffling the original data and recalculating the independent contrasts with each iteration yields significance levels that correspond to those found using D‐PGLS. Thus, while summary statistics from methods based on PICs and PGLS are the same, permuting PICs can lead to strikingly different inferential outcomes with respect to statistical and biological inferences.
Topic Structure Affects Semantic Integration: Evidence from Event-Related Potentials

This study investigated whether semantic integration in discourse context could be influenced by topic structure using event-related brain potentials. Participants read discourses in which the last sentence contained a critical word that was either congruent or incongruent with the topic established in the first sentence. The intervening sentences between the first and the last sentence of the discourse either maintained or shifted the original topic. Results showed that incongruent words in topic-maintained discourses elicited an N400 effect that was broadly distributed over the scalp while those in topic-shifted discourses elicited an N400 effect that was lateralized to the right hemisphere and localized over central and posterior areas. Moreover, a late positivity effect was only elicited by incongruent words in topic-shifted discourses, but not in topic-maintained discourses. This suggests an important role for discourse structure in semantic integration, such that compared with topic-maintained discourses, the complexity of discourse structure in topic-shifted condition reduces the initial stage of semantic integration and enhances the later stage in which a mental representation is updated.