Miracle-dz/UniFAR-FTUs huggingface dataset:
Heavy-Tailed Features and Empirical Analysis of the Limit Order Book Volume Profiles in Futures Markets

This paper poses a few fundamental questions regarding the attributes of the volume profile of a Limit Order Books stochastic structure by taking into consideration aspects of intraday and interday statistical features, the impact of different exchange features and the impact of market participants in different asset sectors. This paper aims to address the following questions: 1. Is there statistical evidence that heavy-tailed sub-exponential volume profiles occur at different levels of the Limit Order Book on the bid and ask and if so does this happen on intra or interday time scales ? 2.In futures exchanges, are heavy tail features exchange (CBOT, CME, EUREX, SGX and COMEX) or asset class (government bonds, equities and precious metals) dependent and do they happen on ultra-high (
“Cavitation in rubber: The role of elasticity”

Under certain conditions, large enclosed cavities may suddenly “appear” in the interior of rubber. This phenomenon has come to be popularly known as cavitation. It corresponds, at heart, to nothing more than to the growth of defects inherent in rubber. Such defects can be of various natures (e.g., weak regions of the polymer network, actual holes, particles of dust) and of various geometries ranging from submicron to supramicron in length scale [1]. Roughly speaking, when rubber is subjected to critically large mechanical (or possibly other type of) forces, these underlying defects may suddenly grow elastically up to the point at which the surrounding polymeric chains reach their maximum elongation. Beyond that point, the defects may continue to grow inelastically by a fracture process, i.e., by the irreversible creation of new surfaces.
Some Multi-Country Evidence on the Effects of Real Exchange Rates on Output

The simultaneous occurrence of devaluation and recession in Mexico in 1995, as well as in the East Asian economies more recently, appears to contradict the conventional view that devaluations are expansionary. Moreover, a sizeable theoretical and empirical literature also argues that, contrary to the predictions of textbook analysis, exchange rate devaluations may be contractionary rather than expansionary. However, prior statistical analyses of the effects of exchange rate devaluation on output have been subject to several limitations: (i) they have failed to distinguish adequately between short and long-run effects; (ii) they have not controlled for the full range of external shocks; and (iii) they have not considered whether the effects of devaluation might differ between different regions of the world. The purpose of this paper is to estimate the impact of devaluation on output for 27 countries while attempting to address these limitations in previous empirical analyses. We find no evidence that devaluations are contractionary in the long run. Additionally, controlling for sources of spurious correlation and reverse causality appears to mute the measured contractionary effect of devaluation in the short run, although this effect remains even after these controls are introduced. Finally, while the literature on contractionary devaluation has focused primarily on developing countries, we found no evidence that this effect is stronger in developing countries than in industrialised countries.
Framing Big Data: The discursive construction of a radio cell query in Germany

The article examines the construction of “Big Data” in media discourse. Rather than asking what Big Data really is or is not, it deals with the discursive work that goes into making Big Data a socially relevant phenomenon and problem in the first place. It starts from the idea that in modern societies the public understanding of technology is largely driven by a media-based discourse, which is a key arena for circulating collectively shared meanings. This largely ignored dimension invites us to appreciate what matters to journalists and the wider public when discussing the collection and use of data. To this end, our study looks at how Big Data is framed in terms of the governmental use of large datasets as a contentious area of data application. It reconstructs the perspectives surrounding the so-called “Handygate” affair in Germany based on broadcast news and social media conversations. In this incident, state authorities collected and analyzed mobile phone data through a radio cell query during events to commemorate the Dresden bombing in February 2011. We employ a qualitative discourse analysis that allows us to reconstruct the conceptualizations of Big Data as a proper instrument for criminal prosecution or an unjustified infringement of constitutional rights.
Plasma physics and related challenges of millimeter-wave-to-terahertz and high power microwave generationa)

Homeland security and military defense technology considerations have stimulated intense interest in mobile, high power sources of millimeter-wave (mmw) to terahertz (THz) regime electromagnetic radiation, from 0.1 to 10THz. While vacuum electronic sources are a natural choice for high power, the challenges have yet to be completely met for applications including noninvasive sensing of concealed weapons and dangerous agents, high-data-rate communications, high resolution radar, next generation acceleration drivers, and analysis of fluids and condensed matter. The compact size requirements for many of these high frequency sources require miniscule, microfabricated slow wave circuits. This necessitates electron beams with tiny transverse dimensions and potentially very high current densities for adequate gain. Thus, an emerging family of microfabricated, vacuum electronic devices share many of the same plasma physics challenges that are currently confronting “classic” high power microwave (HPM) generators i.
Majorizing measures and proportional subsets of bounded orthonormal systems

In this article we prove that for any orthonormal system ('j) n=1 ⊂ L2 that is bounded in L∞, and any 1 < k < n, there exists a subset I of cardinality greater than n − k such that on span{'i}i∈I, the L1 norm and the L2 norm are equivalent up to a factor µ(logµ) 5/2 , where µ = p n/k √ logk. The proof is based on a new estimate of the supremum of an empirical process on the unit ball of a Banach space with a good modulus of convexity, via the use of majorizing measures.
Exploiting un-transcribed foreign data for speech recognition in well-resourced languages

Manual transcription of audio databases for automatic speech recognition (ASR) training is a costly and time-consuming process. State-of-the-art hybrid ASR systems that are based on deep neural networks (DNN) can exploit un-transcribed foreign data during unsupervised DNN pre-training or semi-supervised DNN training. We investigate the relevance of foreign data characteristics, in particular domain and language. Using three different datasets of the MediaParl and Ester databases, our experiments suggest that domain and language are equally important. Foreign data recorded under matched conditions (language and domain) yields the most improvement. The resulting ASR system yields about 5% relative improvement compared to the baseline system only trained on transcribed data. Our studies also reveal that the amount of foreign data used for semi-supervised training can be significantly reduced without degrading the ASR performance if confidence measure based data selection is employed.
A New design of a dual mode bioassay detection analyzer for digital microfluidic biochips

Digital microfluidic biochips in recent years have been emerged as an alternative platform for performance of real time biochemical analysis and safety critical biomedical operations. Detection and analysis is a major task for biochemical analysis required to be performed on completion of a specific bioassay protocol in a digital microfluidic system. With the development of heterogeneous photonic component integration technologies it has become possible to integrate miniaturized optical sensing technologies that enable complex optical detection functions to be incorporated within the microfluidic platform. In this paper we have proposed a novel design of dual mode droplet detection analyzer to be coupled with a targeted biochip for providing automated detailed analysis based on the data acquired through optical detection. The proposed design employed in two modes - for both homogeneous and heterogeneous samples enables automated detection and analysis of different samples based on predefined characterized results. The architecture, synthesis and simulation of the proposed droplet analyzer for signals obtained for different bioassay protocols has been described in this paper - and the results are found to be quite encouraging.
Low-Luminosity Extragalactic Water Masers toward M82, M51, and NGC 4051

Subarcsecond observations using the Very Large Array (VLA) are presented for low-luminosity H2O maser emission in M82, M51, and NGC 4051. New maser features have been detected within the M82 starburst complex. They are largely associated with star-forming activity such as optically identified starburst-driven winds, H II regions, or the early phase of star formation in the galaxy. The H2O maser in M51 consists of blueshifted and redshifted features relative to the systemic velocity of the galaxy. The redshifted features are measured to the northwest of the nuclear radio source, while the location of the blueshifted counterpart is displaced by ∼2″ from the radio source. A small velocity gradient closely aligned with the radio jet is detected from the redshifted features. The redshifted maser most likely amplifies the background radio continuum jet, while the blueshifted counterpart marks off-nuclear star formation in the galaxy. All of the detected maser features in the narrow-line Seyfert 1 galaxy NGC 4051 remain unresolved by new VLA observations. Due to the low luminosity of the maser, the maser excitation is not directly related to the active galactic nucleus.
Youth Risk-Taking Behavior in Brazil: Drug Use and Teenage Pregnancies

Using an extensive survey that addresses risk factors faced by the population in the shantytowns (favelas) of Fortaleza, Brazil, the aim of this paper is to study risk-taking behavior by youth, focusing on drug use and teenage pregnancy. The paper analyzes the impact of factors such as exposure to mass media, the existence of support networks, self-esteem, and the occurrence of violence at home and in the neighborhood, on the probability of risk-taking behavior. A bivariate probit model is estimated. The findings indicate that reliance on support networks and exposure to mass media are associated with a lower probability of either type of risk behavior. Living in a violent home increases drug consumption. Race does not have a significant impact on either type of behavior.
On the Thermodynamics of Classical MicroCanonical Systems

We give two arguments why the thermodynamic entropy of non-extensive systems involves Rényi’s entropy function rather than that of Tsallis. The first argument is that the temperature of the configurational subsystem of a mono-atomic gas is equal to that of the kinetic subsystem. The second argument is that the instability of the pendulum, which occurs for energies close to the rotation threshold, is correctly reproduced.
"Evolutionary, my dear Watson" - Investigating Committee-based Evolution of Fuzzy Rules for the Detection of Suspicious Insurance Claims

Fraud is causing huge losses to our financial world. This work describes the use of a committee decision system using genetic programming to evolve fuzzy logic rules capable of detecting suspicious home insurance claims. Details of the evolutionary-fuzzy system, the committee decision maker and the data preprocessing are provided. Finally, a series of experiments are described, showing that the complete system is capable of attaining good accuracy and intelligibility levels for real home insurance data.
Comparison of different cortical connectivity estimators for high‐resolution EEG recordings

The aim of this work is to characterize quantitatively the performance of a body of techniques in the frequency domain for the estimation of cortical connectivity from high‐resolution EEG recordings in different operative conditions commonly encountered in practice. Connectivity pattern estimators investigated are the Directed Transfer Function (DTF), its modification known as direct DTF (dDTF) and the Partial Directed Coherence (PDC). Predefined patterns of cortical connectivity were simulated and then retrieved by the application of the DTF, dDTF, and PDC methods. Signal‐to‐noise ratio (SNR) and length (LENGTH) of EEG epochs were studied as factors affecting the reconstruction of the imposed connectivity patterns. Reconstruction quality and error rate in estimated connectivity patterns were evaluated by means of some indexes of quality for the reconstructed connectivity pattern. The error functions were statistically analyzed with analysis of variance (ANOVA). The whole methodology was then applied to high‐resolution EEG data recorded during the well‐known Stroop paradigm. Simulations indicated that all three methods correctly estimated the simulated connectivity patterns under reasonable conditions. However, performance of the methods differed somewhat as a function of SNR and LENGTH factors. The methods were generally equivalent when applied to the Stroop data. In general, the amount of available EEG affected the accuracy of connectivity pattern estimations. Analysis of 27 s of nonconsecutive recordings with an SNR of 3 or more ensured that the connectivity pattern could be accurately recovered with an error below 7% for the PDC and 5% for the DTF. In conclusion, functional connectivity patterns of cortical activity can be effectively estimated under general conditions met in most EEG recordings by combining high‐resolution EEG techniques, linear inverse estimation of the cortical activity, and frequency domain multivariate methods such as PDC, DTF, and dDTF. Hum. Brain Mapp, 2007. © 2006 Wiley‐Liss, Inc.
Global Analysis of the HrpL Regulon in the Plant Pathogen Pseudomonas syringae pv. tomato DC3000 Reveals New Regulon Members with Diverse Functions

The type III secretion system (T3SS) is required for virulence in the gram-negative plant pathogen Pseudomonas syringae pv. tomato DC3000. The alternative sigma factor HrpL directly regulates expression of T3SS genes via a promoter sequence, often designated as the “hrp promoter. ” Although the HrpL regulon has been extensively investigated in DC3000, it is not known whether additional regulon members remain to be found. To systematically search for HrpL-regulated genes, we used chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-Seq) and bulk mRNA sequencing (RNA-Seq) to identify HrpL-binding sites and likely hrp promoters. The analysis recovered 73 sites of interest, including 20 sites that represent new hrp promoters. The new promoters lie upstream of a diverse set of genes encoding potential regulators, enzymes and hypothetical proteins. PSPTO_5633 is the only new HrpL regulon member that is potentially an effector and is now designated HopBM1. Deletions in several other new regulon members, including PSPTO_5633, PSPTO_0371, PSPTO_2130, PSPTO_2691, PSPTO_2696, PSPTO_3331, and PSPTO_5240, in either DC3000 or ΔhopQ1-1 backgrounds, do not affect the hypersensitive response or in planta growth of the resulting strains. Many new HrpL regulon members appear to be unrelated to the T3SS, and orthologs for some of these can be identified in numerous non-pathogenic bacteria. With the identification of 20 new hrp promoters, the list of HrpL regulon members is approaching saturation and most likely includes all DC3000 effectors.
Two dimensional magnetised plasma turbulence

Two dimensional magnetised plasma turbulence G. G. PLUNK1,2,3 †, S. C. COWLEY4,5, A. A. SCHEKOCHIHIN6,7 AND T. TATSUNO7 Department of Physics, University of California, Los Angeles, CA 90095, USA Wolfgang Pauli Institute, University of Vienna, A-1090 Vienna, Austria IREAP, University of Maryland, College Park, MD 20742, USA EURATOM/UKAEA Fusion Association, Culham Science Centre, Abington OX 143DB, UK Plasma Physics, Blackett Laboratory, Imperial College, London SW7 2AZ, UK Rudolf Peierls Centre for Theoretical Physics, University of Oxford, Oxford OX1 3NP, UK Institut Henri Poincaré, Université Pierre et Marie Curie, 75231 Paris Cedex 5, France
Paramedic rapid sequence induction (RSI) in a South African emergency medical service: a retrospective observational study.

BACKGROUND Early access to critical care interventions may improve outcomes for severely ill and injured patients. South Africa (SA) faces the unique challenges of prolonged pre-hospital times and limited access to physicians. In 2008, the Health Professions Council of SA introduced paramedic rapid sequence induction (RSI), the gold standard critical care intervention for emergency airway management; however, the risk to benefit ratio in this context is unclear. OBJECTIVE We conducted a pilot study to identify if paramedic RSI in the SA pre-hospital care setting is effective and safe. METHODS We undertook a retrospective observational study of paramedic RSI performed by an emergency medical service, between 12 December 2009 and 12 December 2011. RESULTS Eighty-six RSIs were performed during the study period. No failed intubations were reported. Heart rate was significantly reduced from a median baseline value of 112 to 90 bpm, and oxygen saturations improved from 92% to 99% at handover following RSI. Nineteen patients (22%), however, had an adverse event (AE). Female patients (odds ratio (OR) 18.3; 95% confidence interval (CI) 3.46 - 99.38; p=0.001) and patients subsequently transported by helicopter (OR 7.24; 95% CI 1.44 - 36.32; p=0.016) remained independently associated with AEs after adjusting for confounders. CONCLUSIONS RSI performed by specially trained paramedics is effective in terms of self-reported success. However, the 1 in 5 AE rate highlights safety concerns. The importance of a robust clinical governance programme to identify problems, refine practice and improve the quality of care is underscored.
Increasing incidence of hip arthroplasty for primary osteoarthritis in 30- to 59-year-old patients

Background and purpose The use of hip arthroplasties is evidently increasing, but there are few published data on the incidence in young patients. Methods We used data on total and resurfacing hip arthroplasties (THAs and RHAs) from the Finnish Arthroplasty Register and population data from Statistics Finland to analyze the incidences of THA and RHA in patients aged 30–59 years in Finland, for the period 1980 through 2007. Results The combined incidences of THAs and RHAs among 30- to 59-year-old inhabitants increased from 9.5 per 105 inhabitants in 1980 to 61 per 105 inhabitants in 2007. Initially, the incidence of THA was higher in women than men, but since the mid-90s the incidences were similar. The incidence increased in all age groups studied (30–39, 40–49, and 50–59 years) but the increase was 6-fold and 36-fold higher in the latter two groups than in the first. The incidence of THA was constant; the increased incidence of overall hip arthroplasty was due to the increasing number of RHAs performed. Interpretation We have found a steady increase in the incidence of hip arthroplasty in patients with primary hip osteoarthritis in Finland, with an accelerating trend in the past decade, due to an increase in the incidence of RHA. As the incidence of hip osteoarthritis has not increased, the indications for hip arthroplasty appear to have become broader.
Recent changes in distribution and relative abundance of cetaceans in the Norwegian Sea and their relationship with potential prey

This study aimed to assess possible shifts in distributional patterns of cetaceans residing in the Norwegian Sea, and if possible relate the distribution to their feeding ecology during the summer seasons of 2009, 2010 and 2012. During this same period, historically large abundances in the order of 15 million tonnes pelagic planktivorous fish such as Norwegian spring-spawning herring (Clupea harengus), northeast Atlantic mackerel (Scomber scombrus) and blue whiting (Micromesistius poutassou), have been reported feeding in the Norwegian Sea during the summer. There is also observed elevated average surface temperatures and a reduction in zooplankton biomasses. Such changes might influence species composition, distribution patterns and feeding preferences of cetaceans residing the region. Our results show higher densities of toothed whales, killer whales (Orcinus orca) and pilot whales (Globicephala melas), than the previous norm for these waters. Baleen whales, such as minke whales (Balaenoptera acutorostrata) and fin whales (Balaenoptera physalus), which is often associated with zooplankton, displayed a distribution overlap with pelagic fish abundances. Humpback whales (Megaptera novaeangliae) were observed in low numbers, indicating shift in habitat preference, compared to sighting data collected only few years earlier. Our study illustrate that both small and large cetaceans that reside in the Norwegian Sea have the capability to rapidly perform shifts in distribution and abundance patterns dependent of the access to different types and behaviour of prey species.
Some methods to address the problem of unbalanced sentiment classification in an arabic context

The rise of social media (such as online web forums and social networking sites) has attracted interests to mining and analyzing opinions available on the web. The online opinion has become the object of studies in many research areas; especially that called “Opinion Mining and Sentiment Analysis”. Several interesting and advanced works were performed on few languages (in particular English). However, there were very few studies on some languages such as Arabic. This paper presents the study we have carried out to address the problem of unbalanced data sets in supervised sentiment classification in an Arabic context. We propose three different methods to under-sample the majority class documents. Our goal is to compare the effectiveness of the proposed methods with the common random under-sampling. We also aim to evaluate the behavior of the classifier toward different under-sampling rates. We use two different common classifiers, namely Naïve Bayes and Support Vector Machines. The experiments are carried out on an Arabic data set that we have built from Aljazeera's web site and labeled manually. The results show that Naïve Bayes is sensitive to data set size, the more we reduce the data the more the results degrade. However, it is not sensitive to unbalanced data sets on the contrary of Support Vector Machines which is highly sensitive to unbalanced data sets. The results show also that we can rely on the proposed techniques and that they are typically competitive with random under-sampling.