Miracle-dz/UniFAR-FTUs huggingface dataset:
Anti-inflammatory activity of macrolide antibiotics.

The effect of four macrolide antibiotics (roxithromycin, clarithromycin, erythromycin, and azithromycin) on the generation of some mediators and cytokines involved in the inflammatory process has been studied both in vivo and in vitro. Rat carrageenin pleurisy was used as a model of acute inflammation, and the macrolides were administered (10, 20, and 40 mg/kg p.o.) 1 h before the carrageenin challenge. Exudate volume and leukocyte accumulation were both dose-dependently reduced by roxithromycin, clarithromycin and erythromycin in either normal or adrenalectomized animals. Furthermore, in normal rats, prostaglandin (PG)E(2), nitrate plus nitrite, and tumor necrosis factor-alpha levels in pleural exudate were significantly reduced by these macrolides. Roxithromycin appeared more effective than erythromycin and clarithromycin, whereas azithromycin only slightly affected the inflammatory reaction. None of the macrolides were able to modify leukotriene B(4) exudate levels. In vitro experiments have shown that the four macrolides (5-80 microM) reduced in a concentration-dependent manner the production of 6-keto-PGF(1alpha), NO(2)(-), tumor necrosis factor-alpha, interleukin-1beta, and interleukin-6 by lipopolysaccharide-stimulated J774 macrophages. In J774 cells, the inhibition of 6-keto-PGF(1alpha) and NO(2)(-) production by roxithromycin and erythromycin was not dependent on direct inhibition of cyclooxygenase-2 and inducible nitric oxide synthase activity because it appears to be related to the inhibition of cyclooxygenase-2 and inducible nitric oxide synthase protein expression. In conclusion, the present study shows that macrolide antibiotics have anti-inflammatory activity, which likely depends on their ability to prevent the production of proinflammatory mediators and cytokines, and suggest that these agents, particularly roxithromycin, can exert therapeutic effects independently of their antibacterial activity.
Advances of cone penetration testing in earthquake engineering applications

The Cone Penetration Test (CPT), because of its precision, accuracy, and utility has been increasingly used in earthquake engineering applications in the last decade. This paper provides a brief survey of recent advances in applying the CPT to; liquefaction triggering, post-liquefaction deformations, cyclic failure of clays, dynamic slope stability, and seismic site response. In granular soils the continuous CPT measurements of tip and sleeve resistance are well correlated with the engineering properties of relative density and friction angle. In clay soils the CPT tip resistance is directly proportional to the undrained shear strength. CPT measurements are ideal for weak or soft soil layers, which are the primary culprits in seismic soil failure. The CPT is commonly instrumented with an accelerometer so that shear wave velocity measurements can be made concurrently with penetration measurements. This allows for the measure of the small strain stiffness of the soil for dynamic modeling and site response analysis. For tailings dams and earth slopes the combination of penetration measurements to estimate soil strength and small strain stiffness to assess the modal response provides a complete set of measurements for assessing the dynamic slope stability. For site response analysis the CPT provides the quickest and most cost effective means of layer-specific shear wave velocity imaging of the foundation conditions. A number or recent methods and projects are described in this paper to demonstrate the utility of the CPT in earthquake engineering applications.
Finding diverse needles in a haystack of comments: social media exploration for news

Use of social media platforms to express opinion and discuss various topics has been increasingly popular. Consequently, huge volume of social media data is generated by users across all these platforms, e.g. users comment on a variety of content items such as news articles, videos, images on social media. These comments are often noisy and sparse, therefore, identifying sub-topics within them to explore social media is a challenge. In this paper, we develop an effective way to distill sub-topics from all the comments related to a textual query and apply two different diversification techniques to select comments. We conduct experiments to validate our idea using seven years of Reddit comments and news events from Wikipedia Current Events Portal as queries.
Determinants of Credit Default Swap Spread: Evidence from Japan

In this paper, we investigate the determinants of credit default swap (CDS) spread for the Japanese market, which is one of the major CDS markets in the world. Our assessment of literature indicates that there is a lack of related empirical research using data from the Japanese market. By analyzing data from 2001 to 2004, the empirical results show that the theoretical determinants, including leverage, historical volatility, and risk-free rate, perform well in explaining cross-sectional variation in the level of CDS spread. We also find that the effects of the theoretical determinants are more sensitive for lower credit rating firms than those with a higher credit rating. Finally, our findings remain robust for different sub-sample periods. JEL Classification: G00; G19
Eecient Bayesian Local Computation for Dynamic Forecasting of Competitive Markets

SUMMARY The problem of forecasting high-dimensional time series with a hierarchical structure and cross-correlated components is considered. The methodology is illustrated in the context of forecasting weekly sales of a large number of competing products from a wholesale retail depot, but similar structures arise in many nancial and economic contexts, where monitoring of a large number of system variables is required. Fully Bayesian speciication and updating for dynamic multivariate models is a formidable task, and therefore a Bayes linear approach is adopted, rendering speciication requirements manageable, and updating tractable. Bayes linear updating for problems with very large numbers of variables is tackled by locally computing adjustments, utilising the structure of an appropriately constructed conditional independence graph. 1. INTRODUCTION Bayesian speciication and updating for multivariate dynamic models is a formidable task. Rather than attempting a full distributional Bayesian analysis, in this paper a Bayes linear approach is adopted. Bayes linear methods are an alternative to conventional Bayesian statistics , which acknowledge the diiculties associated with the full modelling, speciication, and conditioning required by the distributional Bayesian approach. Instead best possible use is made of partial speciications, based on means, variances and covariances. Unsurpris-ingly, much of the theory is formally identical to inference in multivariate Gaussian Bayesian networks (where the distributions are determined by rst and second moments), but interpretation of results is generally diierent. A generalised conditional independence property based on zero partial correlations can be used to deene Bayes linear graphical models which may then be used as the basis for local computation (Pearl 1988). As for the full Bayesian case, local computation actually takes place on the clique tree of the triangulated moral graph corresponding to the directed acyclic graph (DAG) of the Bayes linear graphical model. The updating is illustrated in the context of weekly sales data for a collection of soft drink and potato crisp products. The soft drink products compete, as do the diierent crisp products. However, the demands for drinks and crisps are positively related. A model is developed for this type of competitive structure, and it is shown how this model can be used for eecient forecasting. A pair of coupled dynamic linear models are used to capture the structure of the problem, and Bayes linear local computation is used for updating.
Road sign text detection from natural scenes

Texts on road signs contain important information which is quite useful for potential applications. We proposed a robust method for detecting road sign text from urban street scenes under different weather conditions. First, color Segmentation and morphological operations are employed to obtain candidate regions, and contours of candidate regions are mainly concern. Then, a linear support vector machine (SVM) classifier is followed for shape classification after shape features based on edge orientation histogram (EOH) of contours are extracted. Finally, binarization of road sign images is achieved by k-means clustering in the S channel, multi-scale rules and strokes merging are referenced to extract texts. Experiment results on a large amount of images demonstrate the effectiveness of the proposed method.
Calibration of WorldView-2 satellite imagery to reflectance data using an empirical line method

Obtaining accurate quantitative information from multispectral satellite data requires the conversion of raw digital numbers (DN) to reflectance. Sensor characteristics, illumination geometry and atmospheric conditions affect the signal received by a multispectral satellite sensor. In this paper an empirical line method is used to calibrate an eight band multispectral WorldView-2 image. Correction for illumination geometry and atmospheric attenuation in the imagery was achieved by developing a non-linear relationship between top of atmosphere (TOA) spectral radiance and surface reflectance values measured from field targets, using an (ASD Inc) FieldSpecPro spectrometer. An accuracy assessment was undertaken by comparing image reflectance values against the surface reflectance values of 17 field targets. The overall accuracy based on the RMSE for the eight bands ranged between 0.69 – 2.35% with the greatest variance in the near infrared bands. The results of this study show that empirical line methods can be used to successfully calibrate WorldView-2 satellite imagery to reflectance data.
A Null-Space based Behavioural control approach to coordinated motion of a humanoid robot

In this paper the Null-Space based Behavioural control is used to coordinate the motion of the highly redundant kinematic structure of a humanoid robot. A set of elementary behaviours is considered, which are differently composed in nature and priority so as to accomplish some typical basic actions. A sequence of actions is then considered in a simulation case study to execute a grasp-move-and-release mission.
Studying Hate Crime with the Internet: What Makes Racists Advocate Racial Violence?

We conducted semistructured interviews with 38 participants in White racist Internet chat rooms, examining the extent to which people would, in this unique environment, advocate interracial violence in response to purported economic and cultural threats. Capitalizing on the anonymity and candor of chat room interactions, this study provides an unusual perspective on extremist attitudes. We experimentally manipulated the nature and proximity of the threats. Qualitative and quantitative analyses indicate that the respondents were most threatened by interracial marriage and, to a lesser extent, Blacks moving into White neighborhoods. In contrast, job competition posed by Blacks evoked very little advocacy of violence. The study affords an assessment of the advantages and limitations of Internet-based research with clandestine populations.
Integrated approach of skin-color detection and depth information for hand and face localization

Real-time hand and face localization is a challenging problem in many application scenarios such as face and gesture recognition in computer vision and robotics. This paper proposes a robust method which can locate multiple faces and hands simultaneously under the changing environment of light illumination and complex background in real time by using skin-color detection and K-means in conjunction with stereoscopic depth information. Skin-color detection in color image with elliptical boundary model to identify possible areas of human skin-color. The depth map captured from three-dimensional depth sensor Kinect is used to segment human body to remove the skin-color noise in the background and separate hands from face based on their positions. Then K-means algorithm clusters the detected skin-color pixels into three blobs to obtain the center points of hands and face. Experimental results demonstrate that the proposed method in localization of human hands and face is robust over various body postures and complex environmental circumstances in video sequences.
ROBUST SPEECH DETECTION WITH HETEROSCEDASTIC DISCRIMINANT ANALYSIS APPLIED TO THE TIME-FREQUENCY ENERGY

In this paper, we propose a robust speech detection algorithm with Heteroscedastic Discriminant Analysis (HDA) applied to the Time-Frequency Energy (TFE). The TFE consists of the log energy in time domain, the log energy in the fixed band 2503500 Hz, and the log Mel-scale frequency bands energy. The bottom-up algorithm with automatic threshold adjustment is used for accurate word boundary detection. Compared to the algorithms based on the energy in time domain [1], the ATF parameter [2], the energy and the LDA-MFCC parameter [3], the proposed algorithm shows better performance under different types of noise.
Invited Paper: Bare-Bones Dependency Parsing – A Case for Occam’s Razor?

If all we want from a syntactic parser is a dependency tree, what do we gain by first computing a different representation such as a phrase structure tree? The principle of parsimony suggests that a simpler model should be preferred over a more complex model, all other things being equal, and the simplest model is arguably one that maps a sentence directly to a dependency tree – a bare-bones dependency parser. In this paper, I characterize the parsing problem faced by such a system, survey the major parsing techniques currently in use, and begin to examine whether the simpler model can in fact rival the performance of more complex systems. Although the empirical evidence is still limited, I conclude that bare-bones dependency parsers fare well in terms of parsing accuracy and often excel in terms of efficiency.
Multi-loci Molecular Characterisation of Endophytic Fungi Isolated from Five Medicinal Plants of Meghalaya, India

The phylogenetic relationships of the most dominant and morphologically cryptic endophytic fungal isolates from each of five selected medicinal plants, namely Potentilla fulgens, Osbeckia stellata, Osbeckia chinensis, Camellia caduca, and Schima khasiana of the biodiversity rich state of Meghalaya, were assessed with random amplification of polymorphic DNA and PCR-restriction fragment length polymorphism profiles. Sequencing of the internal transcribed spacer 1, small subunit rRNA and partial β-tubulin gene fragments was also conducted to determine the phylogenetic relationships of these isolates with fungal sequences available in Genbank, NCBI. The identity of the fungal isolates is suggested based on the molecular phylogenetic data.
Polarization Observations of 1720 MHz OH Masers toward the Three Supernova Remnants W28, W44, and IC 443

We present arcsecond resolution observations from the VLA with full Stokes polarimetry of the ground-state satellite line of the hydroxyl molecule (OH) at 1720.53 MHz (2Π3/2, J = 3/2, F = 2 → 1) toward three Galactic supernova remnants: W28, W44, and IC 443. The total number of individual OH (1720 MHz) "spots" we detect in each of these three remnants is 41, 25, and 6, respectively. The OH (1720 MHz) features appear to lie along the edge of radio continuum emission from the supernova remnants, but they are displaced behind the leading edge of the shock as traced by the synchrotron emission. The brightness temperatures of the OH (1720 MHz) emission features range from 2 × 104 to 108 K, convincingly demonstrating the maser nature of the OH (1720 MHz) features. We argue that the partially resolved angular diameters that we measure for the masers are neither intrinsic sizes nor scattering disks, but result from a blend of several unresolved maser features near the same velocity. Thus, our computed brightness temperatures are lower limits to the true values. The characteristic antisymmetric S profile, indicative of Zeeman splitting in the weak-field case, is identified in the Stokes V spectrum of several of the brighter maser spots. The derived line-of-sight magnetic fields are of order 0.2 mG and are remarkably constant in both direction and magnitude over regions several parsecs apart. These are the first measurements of postshock magnetic fields in supernova remnants and demonstrate the importance of magnetic pressure in these molecular shocks. The velocity dispersion of the maser features is typically less than a few km s-1, and, except in the special case of W28, the mean maser velocity is equal to the systemic velocity of the remnant. We suggest that the maximum amplification of the maser transition will occur when the acceleration produced by the shock is transverse to the line of sight. Additional support for this point comes from the location of the masers in IC 443, and from molecular observations that allow the shock geometry to be determined. All of our observations are consistent with a model in which the OH (1720 MHz) is collisionally excited by H2 molecules in the postshock gas heated by a nondissociative shock. Finally, we end with a discussion of the importance of supernova remnants with OH (1720 MHz) maser emission as promising candidates to conduct high-energy searches for the sites of cosmic-ray acceleration.
THE MELTING POT ’ ’ : CULTURAL TRANSMISSION , MARRIAGE , AND THE EVOLUTION OF ETHNIC AND RELIGIOUS TRAITS

This paper presents an economic analysis of the intergenerational transmission of ethnic and religious traits through family socialization and marital segregation decisions. Frequency of intragroup marriage (homogamy), as well as socialization rates of religious and ethnic groups, depend on the group’s share of the population: minority groups search more intensely for homogamous mates, and spend more resources to socialize their offspring. This pattern generally induces a dynamics of the distribution of ethnic and religious traits which converges to a culturally heterogeneous stationary population. Existing empirical evidence bearing directly and indirectly on the implications of the model is discussed.
Associations of depression and anxiety with gender, age, health-related quality of life and symptoms in primary care COPD patients.

BACKGROUND Under-diagnosis of anxiety and depression in Chronic Obstructive Pulmonary Disease (COPD) patients may have a negative impact on patient quality of life and result in disparity between prevalence and the recognition and treatment of these symptoms. OBJECTIVE To reveal associations of depression and anxiety with demographic, health-related quality of life and clinical characteristics of COPD patients seen in UK primary care. METHODS Cross-sectional population-based postal survey of COPD patients comprising the EQ-5D visual analogue scale (EQ-5D(VAS)), the COPD symptom control questionnaire, the Hospital Anxiety and Depression Scale, the Medical Research Council dyspnea index. Demographic and spirometric data were collected from general practice records. RESULTS A total of 170 (57%) patients consented to take part. Data are reported on 110 of these patients for whom up-to-date spirometry was available. Approximately one in five participants reported 'caseness' for depression (20.8%) and one in three reported anxiety (32.7%). Age and high levels of symptoms were independent predictors of anxiety and depression, as was the EQ-5D(VAS) of depression. CONCLUSIONS These data suggest that in UK primary care, depressive and anxious symptoms in COPD are related to age and high levels of symptoms. Depression is also associated with lower patient-reported generic health status. The data suggest that assessment and treatment for depression and anxiety should be considered for all COPD patients, not just those with more severe clinical levels of disease. The potential of the EQ-5D(VAS) as a screening tool for anxiety and depression in primary care COPD patients also merits study.
Automatic Harmonization Using a Hidden Semi-Markov Model

Hidden Markov Models have been used frequently in the audio domain to identify underlying musical structure. Much less work has been done in the purely symbolic realm. Recently, a substantial amount of expert-labelled symbolic musical data has been injected into the research community. The new availability of data allows for the application of machine learning models to purely symbolic tasks. Similarly, the continued expansion of the field of machine learning provides new perspectives and implementations of machine learning methods, which are powerful tools when approaching complex musical challenges. This research explores the use of an extended probabilistic model such as the Hidden Semi-Markov Model (HSMM) to approach the task of automatic harmonization. One distinct advantage of the HSMM is that it is able to automatically differentiate harmonic boundaries, through its inclusion of an extra parameter: duration. In this way, a melody can be harmonized automatically in the style of a particular corpus. In the case of this research, the corpus was in the style of Rock 'n' Roll.
Degrees-of-Freedom Regions for $K$-User MISO Time-Correlated Broadcast Channel

In this paper, we study the achievable degrees-of-freedom (DoF) regions of the $K$-user multiple-input-single-output (MISO) time correlated broadcast channel (BC). The time correlation induces knowledge of the current channel state information at transmitter (CSIT) with an estimation error $P^{-\alpha}$, where $P$ is the signal-to-noise ratio (SNR). We consider the following two scenarios: $(i)$ $K$-user with $K$-antenna base station (BS) and $(ii)$ $3$-user with $2$-antenna BS. In case of symmetric DoF tuples, where all the users obtain the same DoF, we derive the total DoF equal to $\frac{K(1-\alpha)}{1+\frac{1}{2}+\cdots+\frac{1}{K}}+K\alpha$ for the first scenario and $\frac{3+\alpha}{2}$ for the second one. In particular, we provide the achievability schemes for these two DoF tuples. Nevertheless, we also consider the asymmetric case where one of the users is guaranteed {\it one} DoF, and provide the achievability scheme. Notably, the consistency of the proposed DoF regions with an already published outer bound , as well as with the Maddah-Ali-Tse (MAT), which assumes only perfect delayed CSIT, and the ZF beamforming schemes (perfect current CSIT) consents to the optimality of the proposed achievability schemes.
A Priority Scheme for IEEE 802. 11 DCF Access Method

IEEE 802.11 is a standard for wireless LANs. The basic access method in its MAC layer protocol is the distributed coordination function (DCF) for the ad hoc networks. It is based on the mechanism of carrier sense multiple access with collision avoidance (CSMA/CA). DCF is used to support asynchronous data transmission. However, frames in DCF do not have priorities, making it unsuitable for real-time applications. With a little bad luck, a station might have to wait arbitrarily long to send a frame. In this paper, we propose a method to modify the CSMA/CA protocol such that station priorities can be supported. The method is simple, efficient and easy to implement in comparison to point coordination function (PCF), another access method in IEEE 802.11 based on access points (base stations). Simulations are conducted to analyze the proposed scheme. The results show that DCF is able to carry the prioritized traffic with the proposed scheme. key words: wireless LAN, CSMA/CA, multimedia applications,