Miracle-dz/UniFAR-FTUs huggingface dataset:
The sound of cooperation: Musical influences on cooperative behavior

Summary Music as an environmental aspect of professional workplaces has been closely studied with respect to consumer behavior while sparse attention has been given to its relevance for employee behavior. In this article, we focus on the influence of music upon cooperative behavior within decision‐making groups. Based on results from two extended 20‐round public goods experiments, we find that happy music significantly and positively influences cooperative behavior. We also find a significant positive association between mood and cooperative behavior. Consequently, while our studies provide partial support for the relevance of affect in relation to cooperation within groups, we also show an independently important function of happy music that fits with a theory of synchronous and rhythmic activity as a social lubricant. More generally, our findings indicate that music and perhaps other atmospheric variables that are designed to prime consumer behavior might have comparably important effects for employees and consequently warrant closer investigation. Copyright © 2016 The Authors Journal of Organizational Behavior Published by John Wiley & Sons Ltd.
Modelling high-frequency limit order book dynamics with support vector machines

We propose a machine learning framework to capture the dynamics of high-frequency limit order books in financial equity markets and automate real-time prediction of metrics such as mid-price movement and price spread crossing. By characterizing each entry in a limit order book with a vector of attributes such as price and volume at different levels, the proposed framework builds a learning model for each metric with the help of multi-class support vector machines. Experiments with real data establish that features selected by the proposed framework are effective for short-term price movement forecasts.
Bayesian Articulated Tracking Using Single Frame Pose Sampling

We propose a novel probabilistic tracking framework for articulated bodies that incorporates direct estimation of the pose posterior distribution. We derive a single frame articulated pose sampler, and perform Bayesian tracking over time via Monte Carlo integration. In contrast to traditional particle filtering approaches, which propagate individual samples through time and are sensitive to the sample distribution, we generate samples directly from the current observation. Our method has the initialization benefits of single frame pose detection approaches, and stability benefits of sequential Monte Carlo methods. We have experimented with simple 2D head, hand, and contour edge observation likelihoods; our method is able to infer a distribution of full articulated pose from these simple features.
Glucose Tolerance, MTHFR C677T and NOS3 G894T Polymorphisms, and Global DNA Methylation in Mixed Ancestry African Individuals

The aim of this study is to quantify global DNA methylation and investigate the relationship with diabetes status and polymorphisms in MTHFR C677T and NOS3 G894T genes in mixed ancestry subjects from South Africa. Global DNA methylation was measured, and MTHFR rs1801133 and NOS3 rs1799983 polymorphisms were genotyped using high throughput real-time polymerase chain reaction and direct DNA sequencing. Of the 564 participants, 158 (28%) individuals had T2DM of which 97 (17.2%) were screen-detected cases. Another 119 (21.1%) had prediabetes, that is, impaired fasting glucose, impaired glucose tolerance, or the combination of both, and the remainder 287 (50.9%) had normal glucose tolerance. Global DNA methylation was significantly higher in prediabetes and screen-detected diabetes than in normal glucose tolerance (both p ≤ 0.033) and in screen-detected diabetes compared to known diabetes on treatment (p = 0.019). There was no difference in global DNA methylation between known diabetes on treatment and normal glucose tolerance (p > 0.999). In multivariable linear regression analysis, only NOS3 was associated with increasing global DNA methylation (β = 0.943; 95% CI: 0.286 to 1.560). The association of global DNA methylation with screen-detected diabetes but not treated diabetes suggests that glucose control agents to some extent may be reversing DNA methylation. The association between NOS3 rs1799983 polymorphisms and DNA methylation suggests gene-epigenetic mechanisms through which vascular diabetes complications develop despite adequate metabolic control.
Getting it Right: How Fiscal Response Can Shorten Crisis Length and Raise Growth

The authors use an ordered logit model to assess the effects of fiscal stimulus packages during episodes of systemic banking crisis in advanced and emerging market countries over the period 1980-2008. The results show that timely countercyclical fiscal measures can help shorten crises by boosting aggregate demand and offsetting the collapse of private investments. Nevertheless, these outcomes are weaker for countries with limited budgetary room and where fiscal expansion is prevented by funding constraints or limited access to markets. The composition of fiscal responses is important: fiscal expansions based on government consumption and income tax cut are more effective in shortening the recession, while a larger share of public investment yields the strongest impact on output growth. These findings suggest a potential trade off between short-run aggregate demand support and medium-term productivity growth objectives. Two stylised facts emerge: i) the fiscal measures enacted by G-20 countries may have curtailed the crisis by up to one year and ii) they may have stimulated post-crisis growth by 1 per cent of GDP compared with the counterfactual scenario of no fiscal stimulus. Results can be larger for emerging market economies than for advanced countries, since the former devoted a greater share of the stimulus to infrastructure, while the latter made greater resort to tax cuts and transfer increases.
Locating A Projector Using The Strength of Beams Reflected on a Screen

In this paper, we propose a real-time calibration technique for a projector-camera system, which enables the system to locate the projector even while it is moving. Usually fiducial points are stuck on the screen and the camera tracks both the fiducial points and the quadrilateral illuminated by the projector. Then the projector is located by the tracking. Instead of the fiducial points, our real-time calibration technique uses the strength of the beams reflected on the screen. So, the projection area is not limited in size and position by fiducial points and also it can be extended over a wall as far as the reflected beams are observed. This advantage allows a user to turn the projector at any position on the screen to view the position-dependent image. We take the advantage to assemble a map viewer by connecting our projector-camera system to Google Earth, which enables a user to view the map by moving the projector.
Octamer-dependent transcription in T cells is mediated by NFAT and NF-κB

The transcriptional co-activator BOB.1/OBF.1 was originally identified in B cells and is constitutively expressed throughout B cell development. BOB.1/OBF.1 associates with the transcription factors Oct1 and Oct2, thereby enhancing octamer-dependent transcription. In contrast, in T cells, BOB.1/OBF.1 expression is inducible by treatment of cells with PMA/Ionomycin or by antigen receptor engagement, indicating a marked difference in the regulation of BOB.1/OBF.1 expression in B versus T cells. The molecular mechanisms underlying the differential expression of BOB.1/OBF.1 in T and B cells remain largely unknown. Therefore, the present study focuses on mechanisms controlling the transcriptional regulation of BOB.1/OBF.1 and Oct2 in T cells. We show that both calcineurin- and NF-κB-inhibitors efficiently attenuate the expression of BOB.1/OBF.1 and Oct2 in T cells. In silico analyses of the BOB.1/OBF.1 promoter revealed the presence of previously unappreciated combined NFAT/NF-κB sites. An array of genetic and biochemical analyses illustrates the involvement of the Ca2+/calmodulin-dependent phosphatase calcineurin as well as NFAT and NF-κB transcription factors in the transcriptional regulation of octamer-dependent transcription in T cells. Conclusively, impaired expression of BOB.1/OBF.1 and Oct2 and therefore a hampered octamer-dependent transcription may participate in T cell-mediated immunodeficiency caused by the deletion of NFAT or NF-κB transcription factors.
Effects of the Demethylating Agent, 5-Azacytidine, on Expression of the Kallikrein-Kinin Genes in Carcinoma Cells of the Lung and Pleura

Tissue kallikrein (KLK1) and plasma kallikrein (KLKB1) may regulate the growth and proliferation of tumours of the lung and pleura, through the generation of kinin peptides that signal through the kinin B1 (BDKRB1) and B2 (BDKRB2) receptors. The development and progression of cancer results from genetic mutations, as well as epigenetic changes that include methylation of DNA at CpG islands. The aim of this study was to assess whether expression of the kallikrein-kinin genes in lung cancer and mesothelioma cells is regulated by DNA methylation. Quantitative reverse transcriptase-PCR and immunocytochemistry showed differences in the basal expression of the kallikrein-kinin genes and proteins in lung carcinoma and mesothelioma cells, compared with non-malignant lung epithelial and mesothelial cells, respectively. Following treatment with the demethylating agent, 5-azacytidine (5-AZA), KLKB1 mRNA expression was consistently increased in both lung carcinoma and mesothelioma cells, whereas KLK1, BDKRB1 and BDKRB2 mRNA expression was decreased or unchanged. Increased expression of KLKB1 after 5-AZA treatment suggests it may function as a tumour suppressor gene in cancers of the lung and pleura. Studies on DNA methylation of the kallikrein-kinin genes will enhance understanding of their role in carcinogenesis and provide insights into the importance of kallikreins as tumour biomarkers.
A Note on the Estimation of the Frequency and Severity Distribution of Operational Losses

The Basel II Capital Accord requires banks to determine the capital charge to account for operational losses. Compound Poisson process with Lognormal losses is suggested for this purpose. The paper examines the impact of possibly censored and/or truncated data on the estimation of loss distributions. A procedure on consistent estimation of the severity and frequency distributions based on incomplete data samples is presented. It is also demonstrated that ignoring the peculiarities of available data samples leads to inaccurate Value-at-Risk estimates that govern the operational risk capital charge.
Electronic Media Law

Index The American Legal System Understanding the First Amendment Applying the Principles of Broadcast Regulation Cable and Satellite Regulation Media Ownership Rules Rules for Station Operations Libel Privacy Intrusive News-Gathering Methods Media Liability Cases Obscenity Indecency and Violence in the Media Copyright - The Basics Copyright - Fair Use Advertising Law Media and the Courts Privilege Media Access to Government Sources Table of Cases Appendix - FCC Station Inspection Checklist
Genetic Algorithm-based Text Clustering Technique: Automatic Evolution of Clusters with High Efficiency

In this paper, we propose a modified variable string length genetic algorithm (MVGA) for text clustering. Our algorithm has been exploited for automatically evolving the optimal number of clusters as well as providing proper data set clustering. The chromosome is encoded by a string of real numbers with special indices to indicate the location of each gene. More effective versions of operators for selection, crossover, and mutation are introduced in MVGA which can also automatically adjust the influence between the diversity of the population and selective pressure during generations. The superiority of the MVGA over conventional variable string length genetic algorithm (VGA) is demonstrated by providing proper Reuter text collection clusters in terms of number of clusters and clustering data sets.
All quiet in the outer halo:chemical abundances in the globular cluster Pal 3

Context. Globular clusters (GCs) in the outer halo are important probes of the composition and origin of the Galactic stellar halo. Aims. We derive chemical element abundance ratios in red giants belonging to the remote (R ~ 90 kpc) GC Pal 3 and compare our measurements to those for red giant stars in both inner and outer halo GCs. Methods. From high-resolution spectroscopy of four red giants, obtained with the Magellan/MIKE spectrograph at moderately high S/N, we derive chemical abundances for 25 $\alpha$-, iron peak-, and neutron-capture elements. These abundance ratios are confirmed by co-adding low S/N HIRES spectra of 19 stars along the red giant branch. Results. Pal 3 shows $\alpha$-enhanced abundance patterns, and also its Fe-peak and neutron-capture element ratios, are fully compatible with those found in halo field stars and representative inner halo GCs of the same metallicity (such as M 13). The heavy elements in Pal 3 appear to be governed by r-process nucleosynthesis. Our limited sample does not show any significant star-to-star abundance variations in this cluster, although a weak Na-O anti-correlation cannot be ruled out by the present data. Conclusions. Pal 3 thus appears as an archetypical GC with abundance ratios dissimilar to dwarf spheroidal stars, ruling out a direct connection to such external systems. This conclusion is underscored by the lack of significant abundance spreads in this GC, in contrast to the broad abundance distributions seen in the dwarf galaxies. Pal 3 appears to have evolved chemically in analogy to the majority of GCs belonging to the Galactic inner and outer halo, experiencing a similar enrichment history.
Depth from motion and defocus blur

Finding the distance of an object in a scene from intensity images is an essential problem in many applications. In this work, we present a novel method for depth recovery from a single motion and defocus blurred image. Under the assumption of uniform lateral motion of the camera during finite exposure time, both the pinhole model and the camera with a finite aperture are considered. It is shown that the image blur produced by uniform linear motion of the camera is inversely proportional to the distance of the object. Furthermore, if the speed of the relative motion is known, the depth of the object can be acquired by identifying the blur parameters. An image blur model is formulated based on geometric optics. The blur extent is estimated by intensity profile analysis and focus measurement of the deblurred images. The proposed method is verified experimentally using different types of test patterns in an indoor environment.
Exoskeleton with EMG based active assistance for rehabilitation

The development of a prototype robotic system to facilitate upper extremity (UE) rehabilitation in individuals who sustain neurological impairments such as cervical level spinal cord injuries (SCI), acquired brain injuries (ABIs) or stroke (CVA) is described. A control system based on electromyography (EMG) signals has been implemented to provide the appropriate amount of assistance or resistance necessary to progress a patient's movement recovery. Use of EMG signals has potential advantages over systems based only on torque and position sensors. The prototype system includes programmable mechanical impedance, adjustable thresholds and control gains. This robotic rehabilitation device would be used to provide repeated motor practice in an effort to promote neurological recovery and improve functional use of the UE.
Neural Predictors for Detecting and Removing Redundant Information

The components of most real-world patterns contain redundant information. However, most pattern classiiers (e.g., statistical classiiers and neural nets) work better if pattern components are nonredundant. I present various unsupervised nonlinear predictor-based \neural" learning algorithms that transform patterns and pattern sequences into less redundant patterns without loss of information. The rst part of the paper shows how a neural predictor can be used to remove redundant information from input sequences. Experiments with artiicial sequences demonstrate that certain supervised classiication techniques can greatly beneet from this kind of unsupervised preprocessing. In the second part of the paper, a neural predictor is used to remove redundant information from natural text. With certain short newspaper articles, the neural method can achieve better compression ratios than the widely used asymptotically optimal Lempel-Ziv string compression algorithm. The third part of the paper shows how a system of co-evolving neural predictors and neural code generating modules can build factorial (statistically nonredundant) codes of pattern ensembles. The method is successfully applied to images of letters randomly presented according to the probabilities of English language.
Guest Editorial : Machine Learning in Computer Vision

This paper has not been published elsewhere and it has not been submitted simultaneously elsewhere. 2 ABSTRACT In this editorial we briefly discuss interaction between two important areas of artificial intelligence: Computer Vision (CV) and Machine Learning (ML). Although the two fields have a long-standing tradition and can be considered technologically mature, past research in applying ML techniques to CV problems has been limited. After a short introduction on the fields of Computer Vision and Machine Learning, we highlight some important issues in the intersection of the two areas and sketch both current achievements and future research directions. Our goal is to help the reader to put the six contributions of this special issue into the proper context.
A multimodal approach to analysis of steady state visually evoked potentials

Steady state visually evoked potentials (SSVEPs), recorded from the central nervous system of humans using electroencephalography (EEG) in response to visual stimuli, have recently gained attention in cognitive and clinical neuroscience [1]. Here, we fuse EEG SSVEPs with recordings from functional magnetic resonance imaging data (fMRI) utilizing the millisecond temporal resolution of the former and the excellent spatial resolution of the latter. In particular, we propose a spatio-frequency EEG/fMRI fusion framework to recover the frequency content from the EEG and spatial information from the fMRI to enhance our understanding of SSVEPs. Notably, we consider fused analysis of fMRI and EEG data collected independently. We demonstrate that the proposed approach is a practical data-driven method to achieve spatio-frequency fusion of EEG and fMRI SSVEP responses.
A Generic Variational Framework for Demosaicking and Performance Analysis of Color Filter Arrays

We propose a novel method for image demosaicking from samples obtained with a completely arbitrary color ﬁlter array (CFA). We adopt a variational approach where the reconstructed image has maximal smoothness under the constraint of consistency with the available measurements. This optimization problem boils down to a large, sparse system of linear equations to solve, for which we propose an iterative algorithm. Although the proposed approach is linear, it yields visually pleasing demosaicked images and provides a robust framework for comparing the performances of CFAs.
Patch-based Statistical Performance Analysis of Upsampling for Precise Super-Resolution

All existent methods for statistical analysis of super–resolution approaches have stopped at the variance term, not accounting for the bias. In this paper we give an original derivation of the bias term. We propose to use a patch-based method inspired by the work of (P. Chatterjee and P. Milanfar, 2009). Our approach, however, is completely new as we derive a new affine bias model dedicated for the multi-frame super resolution framework. We apply the proposed statistical performance analysis to the Upsampling for Precise Super–Resolution (UP-SR) algorithm. This algorithm was shown experimentally to be a good solution for enhancing the resolution of depth sequences in both cases of global and local motions. Its performance is herein analyzed theoretically in terms of its approximated mean square error, using the proposed derivation of the bias. This analysis is validated experimentally on a simulated static and dynamic depth sequences with a known ground truth. This provides an insightful understanding of the effects of noise variance, number of observed low resolution frames, and super–resolution factor on the final and intermediate performance of UP–SR. Our conclusion is that increasing the number of frames should improve the performance while the error is increased due to local motions, and to the upsampling which is part of UP-SR.
Three-dimensional interactive pen based on Augmented Reality

In order to shorten the learning curve and simplify the complex in current CAD system, one direct approach is to provide a more intuitive way of interaction. This paper proposes an interactive pen tool, which transforms the actions in real space into the virtual three-dimensional CAD system space. Augmented Reality technology is used to track the operator's action in the real world. The design and principle of the interactive tool are introduced in detail. In addition, the experimental system is provided to illustrate a simple process of curves designing and the statistics result of tracking error is also given.
The Effect of Ultrasound Stimulation on the Cytoskeletal Organization of Chondrocytes Seeded In 3 D Matrices

The impact of low intensity diffuse ultrasound (LIDUS) stimulation on the cytoskeletal organization of chondrocytes seeded in 3D scaffolds was evaluated. Chondrocytes seeded on 3D chitosan matrices were exposed to LIDUS at 5.0 MHz (~15kPa, 51-secs, 4-applications/day) in order to study the organization of actin, tubulin and vimentin. The results showed that actin presented a cytosolic punctuated distribution, tubulin presented a quasi parallel organization of microtubules whereas vimentin distribution was unaffected. Chondrocytes seeded on 3D scaffolds responded to US stimulation by the disruption of actin stress fibers and were sensitive to the presence of ROCK inhibitor (Y27632). The gene expression of ROCK-I, a key element in the formation of stress fibers and mDia1, was significantly up-regulated under the application of US. We conclude that the results of both the cytoskeletal analyses and gene expression support the argument that the presence of punctuated actin upon US stimulation was accompanied by the upregulation of the RhoA/ROCK pathway.
Tuberculosis Incidence and Case Notification Rates in Kosovo and the Balkans in 2012: Cross-country Comparison

Aim: Tuberculosis (TB) continues to be a considerable burden especially for millions of young adults and disadvantaged people worldwide. The TB incidence and notification rates are good indicators of TB situation in a country. Our aim was to compare TB incidence and notification rates in Kosovo and in seven other Balkan countries. Methods: Retrospective epidemiologic analysis of published data on TB incidence and notification rates in eight Balkan countries in 2012. Notification rates were expressed per 100,000 inhabitants and were calculated based on the number of TB cases reported divided by the population of each country under analysis. Results: The TB incidence in Kosovo (47/100,000) was considerably higher compared to its four neighboring countries: Albania (16/100,000), Macedonia, Montenegro (18/100,000) and Serbia (23/100,000). The TB notification rates in Kosovo and other countries closely mimicked the incidence rates in these countries. Conclusion: The exceptionally high TB incidence rate in Kosovo could be due to many factors including low health and medical-seeking behaviors of the local population, poverty and low education levels. Effective interventions should be adapted to the local context in order to increase the chances of success.