Miracle-dz/UniFAR-FTUs huggingface dataset:
MACROECONOMIC DETERMINANTS OF PRIVATE TRANSFERS TO INDIA

After the implementation of economic reforms in 1991, private transfers to India have played a major role in financing the trade deficits and reducing the current account deficits. Most of the studies find that host country 3 macro-economic (push) factors play a more important role as compared to the home country macro-economic (pull) factors in determining the magnitude of private transfers. This study, covering the period from 1991-92Q4 to 2010-11Q4, examines various macroeconomic determinants of private transfers to India. While GDP of USA and Dubai Crude Oil prices are taken as proxies for the host-country macroeconomic factors, US $-INR bilateral nominal exchange rate and all India average CPI for industrial workers have been taken as proxies for the home country macroeconomic factors. The study conducts an econometric investigation by applying methodologies, viz., (i) Stationarity Tests; (ii) Johansen’s Cointegration Test; (iii) Johansen’s Vector Error Correction Model (VECM) in VAR; and, (iv) Impulse Response Function and Variance Decomposition Analysis. With all the variables in log terms being I(1), Johansen’s cointegration test confirms two long run relationships among the variables at 5% significance level. The Vector Error Correction Model (VECM) indicates that while private transfers may temporarily deviate from its long run equilibrium, the deviations adjust towards the equilibrium level in the long run. The elasticity of private transfers with respect to GDP of USA, Dubai crude oil prices, US $-INR bilateral nominal exchange rate and All-India CPI for industrial workers is found to be significant, which shows that both host as also home country macroeconomic factors have influenced the magnitude of private transfers to
The N Terminus of the Non-T Cell Activation Linker (NTAL) Confers Inhibitory Effects on Pre-B Cell Differentiation1

SLP-65 and the linker for activation of T cells (LAT) are central adaptor proteins that link the activated pre-BCR to downstream events in pre-B cells. Recently, a new transmembrane adaptor called NTAL/LAB/LAT2 (hereafter called NTAL for non-T cell activation linker) with striking functional and structural similarity to LAT has been identified in B cells. In this study, we compare the function of NTAL and LAT in pre-BCR signaling and show that, in contrast to LAT, NTAL does not induce pre-BCR down-regulation, calcium flux, or pre-B cell differentiation. To test whether differences between NTAL-mediated and LAT-mediated signaling are caused by the missing phospholipase C (PLC)-γ binding motif in NTAL, we inserted the PLC-γ1/2 binding motif of LAT into NTAL. This insertion rendered NTAL capable of activating pre-BCR down-regulation and calcium flux. Unexpectedly however, the ability of NTAL to induce calcium flux was not sufficient to promote pre-B cell differentiation, suggesting that the PLC-γ binding motif has only partial effects on NTAL-mediated pre-BCR signaling. By generating chimeric swap mutants, we identified the N terminus of NTAL as an inhibitory domain that prevents pre-B cell differentiation while allowing pre-BCR down-regulation and receptor-mediated calcium flux. Our data suggest that, in addition to the missing PLC-γ1/2 binding motif, the N terminus is responsible for the functional differences between NTAL and LAT in pre-B cells.
The identification of functional motifs in temporal gene expression analysis

The identification of transcription factor binding sites is essential to the understanding of the regulation of gene expression and the reconstruction of genetic regulatory networks. The in silico identification of cis-regulatory motifs is challenging due to sequence variability and lack of sufficient data to generate consensus motifs that are of quantitative or even qualitative predictive value. To determine functional motifs in gene expression, we propose a strategy to adopt false discovery rate (FDR) and estimate motif effects to evaluate combinatorial analysis of motif candidates and temporal gene expression data. The method decreases the number of predicted motifs, which can then be confirmed by genetic analysis. To assess the method we used simulated motif/expression data to evaluate parameters. We applied this approach to experimental data for a group of iron responsive genes in Salmonella typhimurium 14028S. The method identified known and potentially new ferric-uptake regulator (Fur) binding sites. In addition, we identified uncharacterized functional motif candidates that correlated with specific patterns of expression. A SAS code for the simulation and analysis gene expression data is available from the first author upon request.
A multi-timbre chord/harmony analyzer based on signal processing and neural networks

The automatic analysis of a polyphonic sound is still a very challenging task, not only for computational reasons but also because of the lack in suitable techniques and restrictions in the application field, or sometimes due to unrealistic goals. A remarkable progress has been made in the last decade, but still, a practical and generic solution for this problem is hard to find. In this paper, we propose a rather general solution for a chord/harmony analyzer, which is able provide good results for different instruments and polyphonic sounds. It is based on the combination of signal processing and neural networks. The sound is analyzed in both time and frequency domains by a hybrid original technique. A rather innovative approach is then used to classify the chords and extract their evolution time. The proposed overall method aims to implement a general purpose listening machine, whose approximated results and approach are nevertheless general enough to allow the implementation of very useful applications.
Magnesium enhances the beneficial effects of NK1 antagonist administration on blood-brain barrier permeability and motor outcome after traumatic brain injury.

The current study investigated whether adding magnesium to an NK1 tachykinin receptor antagonist after traumatic brain injury would enhance efficacy to further reduce blood-brain barrier permeability and improve functional recovery compared to either treatment alone. Sprague-Dawley rats were injured using the impact acceleration model of diffuse brain injury, and received either no treatment, MgSO4 (30 mg/kg IV), the NK1 antagonist n-acetyl L tryptophan (2.5 mg/kg IP), or both agents combined. Animals were then killed at either 1, 5, or 24 h postinjury for determination of blood-brain barrier permeability using previously administered Evans blue dye or assessed for functional outcome over a 1-week period using the rotarod motor test. As expected, both MgSO4 and n-acetyl L tryptophan significantly reduced blood-brain barrier permeability and improved functional outcome. However, combined n-acetyl L tryptophan and MgSO4 was more effective at reducing blood-brain barrier permeability (P < 0.05) and improving functional outcome (P < 0.001) compared to the individual compounds. Our results demonstrate that combination therapy with magnesium and an NK1 antagonist may be a more effective therapy for TBI than either compound administered alone.
KES: knowledge enabled services for better EO information use

Modem imaging sensors, especially those aboard satellites, continuously deliver enormous amounts of data. These represent typical cases, where users need automated tools to discover, explore and understand the contents of large image databases. The state-of-the-art image catalogues allow only queries based on data like geographical position, acquisition date, sensor type, etc. and not on image content. Once the search data have been defined, these catalogues show the associated image to the user, leaving the interpretation task to his specific knowledge. The call up a synergy between stochastic modeling, knowledge discovery, semantic representation, up to build a collaborative environment permitting to share the knowledge between heterogeneous user communities. In a previous project (Knowledge Driven Information Mining in Remote Sensing Image Archives - KIM) methods to associate concepts to images were developed for the ESA (European Space Agency). The consortium was composed by ACS (Advanced Computer Systems. Rome). DLR (German Aerospace Center) and ETH (Swiss Federal Institute of Technology. Zurich). This result has been achieved by extracting primitive image features (i.e.: texture, geometrical shapes, spectral information), and by providing the user with a simple, graphic interface to define weighted combinations of these features and to associate concepts (labels) to them through positive and negative examples. The weighted combinations of primitive image features and the associated semantic labels can then be applied to the entire dataset. and not only to the image from which they were defined
The relationship between plasminogen activator inhibitor-1 and proinflammatory and counterinflammatory mediators in children with meningococcal septic shock.

Proinflammatory cytokines (tumor necrosis factor [TNF]-alpha and interleukin [IL]-6 and -8), counterinflammatory compounds (IL-10 and soluble TNF receptors p55 and p75 [sTNFR-55 and -75]), and hemostatic parameters were determined in 38 patients with meningococcal septic shock. Eleven patients (29%) died. Serum levels of pro- and counterinflammatory compounds and plasma levels of plasminogen activator inhibitor (PAI)-1 were significantly higher in nonsurvivors. The interval between appearance of petechiae and blood sampling was shorter in nonsurvivors than in survivors (3.6 +/- 2.4 vs. 6.1 +/- 3.3 h; P = 0.4). This interval correlated strongly with the levels of TNF-alpha, IL-6, -8, and -10, sTNFR-55 and -75, and PAI-1. However, with the exception of PAI-1, differences between concentrations of these mediators disappeared after adjustment for the interval. PAI-1 levels correlated with TNF-alpha concentrations (r = .75; P < .001) and were 1.9 (P = .01) times higher in nonsurvivors at a similar TNF-alpha concentration. Thus, an increased PAI-1 response to TNF-alpha may be associated with fatality, probably because of polymorphism of the PAI-1 gene.
Source Separation Improves Music Emotion Recognition

Despite the impressive progress in music emotion recognition, it remains unclear what aspect of a song, i.e., singing voice and accompanied music, carries more emotional information. As an initial attempt to answer the question, we introduce source separation into a standard music emotion recognition system. This allows us to compare systems with and without source separation, and consequently reveal the influence of singing voice and accompanied music on emotion recognition. Classification experiments on a set of 267 songs with last.fm annotations verify the new finding that source separation improves song music emotion recognition.
Linear blind source separation: A dual state-parameter estimation approach

This paper presents a dual estimation approach for solving linear blind source separation (BSS) problem. The proposed dual state-parameter estimation approach estimates original source signals from their noisy mixtures. The approach based on Kalman filter formulation designed to estimate the states and the parameters of a linear dynamic system from a series of noisy measurements resembles that of linear blind source separation. The simulation has been carried out for different cases which shows the validity of the proposed algorithm.
Immunochemical characterization of Brucella lipopolysaccharides and polysaccharides

Purified lipopolysaccharide (LPS) extracted with phenol-water from smooth Brucella abortus was hydrolyzed with 1% acetic acid at 100 degrees C. The degraded polysaccharide (AH) released gave reactions of identity with the native polysaccharide hapten (NH) in phenol-water- or trichloroacetic acid-extracted endotoxin preparations of B. abortus and with the polysaccharide (poly B) extracted by trichloroacetic acid from rough B. melitensis strain B115. Poly B was present in the soluble cytoplasmic fraction but not in the membrane fraction, of disrupted B115 cells. It could not be extracted from three rough mutants of B. abortus or from B canis or B. ovis cells. Both AH and NH shared determinants present on smooth LPS and missing from poly B. Sugars found in purified LPS, NH, and AH included mannose, glucose, quinovosamine, glucosamine, and 2-keto-3-deoxyoctonate. Poly B contained only a trace amount of quinovosamine and no 2-keto-3-deoxyoctonate detectable by the thiobarbiturate assay. Sera from some rabbits immunized with pure smooth LPS and some, but not all, cows infected with field strains of B. abortus recognized the determinants missing from poly B. A subclass-specific enzyme-linked immunoassay showed that most of the antibody in sera from infected cows which binds to smooth LPS and to NH is of the immunoglobulin G1 subclass.
Predictors of transformational leadership of nurse managers

AIM The aim of this study was to examine the relationships among education, leadership experience, emotional intelligence and transformational leadership of nurse managers. BACKGROUND Nursing leadership research provides limited evidence of predictors of transformational leadership style in nurse managers. METHODS A predictive correlational design was used with a sample of nurse managers (n = 148) working in varied health care settings. Data were collected using the Genos Emotional Intelligence Inventory, the Multi-factor Leadership Questionnaire and a demographic questionnaire. Simple linear and multiple regression analyses were used to examine relationships. RESULTS A statistically significant relationship was found between emotional intelligence and transformational leadership (r = 0.59, P < 0.001) explaining 34% variance in transformational leadership. CONCLUSIONS Nurse managers should be well informed of the predictors of transformational leadership in order to pursue continuing education and development opportunities related to those predictors. IMPLICATIONS FOR NURSING MANAGEMENT The results of this study emphasise the need for emotional intelligence continuing education, leadership development and leader assessment programmes.
Journal of English for Academic Purposes에 나타난 연구 경향 분석

The present study reports a qualitative research synthesis of the studies published in the Journal of English for Academic Purposes from 2002 to 2010. A total number of 166 research articles published during this period were classified and coded according to an analytic framework in terms of research scope, objects, topics and methodology. The results show that much more research has focused on English for Specific Academic Purposes than English for General Academic Purposes and that corpus-based research has been on the steady increase in terms of research objects, topics and methodology. Suggestions for future research and limitations of the present study were also discussed.
High-resolution EEG using spline generated surface Laplacians on spherical and ellipsoidal surfaces

Spline generated surface Laplacians are introduced as an effective method for estimating neocortical source activity at moderate scales. The method appears to be robust to the unavoidable perturbations of measured potentials and errors of head geometry and resistivity that are certain to occur in clinical or research settings. In particular, the surface Laplacian is derived for general ellipsoidal surfaces in terms of the spline function. The spline-Laplacian accurately estimates isolated dipoles or distributed sources, is insensitive to subcortical sources and to sources which originate outside the boundaries of the electrode array, and acts as a bandpass spatial filter whose characteristics appear to provide a good match to the volume conduction of intracranial sources through human heads. As a result, spatial resolution is improved over that obtained with conventional EEG by at least a factor of three. This improvement is likely to have a significant impact on both medical and cognitive studies involving EEG. <<ETX>>
Cyanate utilization by and cryopreservation of Nitrospira moscoviensis

Stickstoff ist ein weit verbreitetes Element im Universum und essentiell fur alle bekannten Lebensformen auf unserem Planet. Der Stickstoffkreislauf spielt eine wichtige Rolle, wobei Stickstoff durch verschiedenste chemische Reaktionen in unterschiedlichsten Verbindungen eingebunden wird. Die Nitrifikation ist ein bedeutender Teilprozess des biogeochemischen Stickstoffkreislaufes und der biologischen Abwasseraufbereitung. Der Hauptprozess ist die biologische Oxidation von Ammonium uber Nitrit zu Nitrat, die von einer grosen mikrobiellen Lebensgemeinschaft beeinflusst wird. Nitrit-oxidierende Bakterien (NOB), wichtig fur den zweiten Schritt in der Nitrifikation, kommen in fast allen aquatischen und terrestrischen Okosystemen vor. Untersuchungen des Erbgutes von unterschiedlichen NOB haben gezeigt, dass diese alle ein cynS Gen besitzen. CynS kodiert fur das Enzym Zyanase, welches den biochemischen Abbau des zelltoxischen Zyanat in Ammonium und Kohlendioxid durchfuhrt. Die Verwendung von Zyanase ist vielseitig und reicht von Zyanat-Entgiftung der Zelle bis zu Freisetzung von NH3, welches als weitere Stickstoffquelle herangezogen werden kann. Freisetzung von Ammonium konnte als Energiequelle fur ammonium-oxidierende Mikroorganismen (AOM) dienen, die eng mit Nitritoxidierer zusammenleben. Der Abbau von Ammonium zu Nitrit wiederum konnte als Energiequelle fur NOB fungieren. In dieser Arbeit wurden physiologische Untersuchungen an N. moscoviensis, einem Vertreter der Nitritoxidierer, durchgefuhrt, um den biochemischen Zerfall von Zyanat zu Ammonium und Kohlendioxid durch das Enzym Cyanase zu untersuchen. Zusatzlich wurden Methoden fur eine erfolgreiche Kryokonservierung an N. moscoviensis getestet.
Synergistic effect of JQ1 and rapamycin for treatment of human osteosarcoma

Bromodomain and extra terminal domain (BET) proteins are important epigenetic regulators facilitating the transcription of genes in chromatin areas linked to acetylated histones. JQ1, a BET protein inhibitor, has antiproliferative activity against many cancers, mainly through inhibition of c‐MYC and upregulation of p21. In this research, we investigated the use of JQ1 for human osteosarcoma (OS) treatment. JQ1 significantly inhibited the proliferation and survival of OS cells inducing G1 cell cycle arrest, premature senescence, but little effect on apoptosis. Interestingly, c‐MYC protein levels in JQ1‐treated cells remained unchanged, whereas the upregulation of p21 protein was still observable. Although effective in vitro, JQ1 alone failed to reduce the size of the MNNG/HOS xenografts in immunocompromised mice. To overcome the resistance of OS cells to JQ1 treatment, we combined JQ1 with rapamycin, an mammalian target of rapamycin (mTOR) inhibitor. JQ1 and rapamycin synergistically inhibited the growth and survival of OS cells in vitro and in vivo. We also identified that RUNX2 is a direct target of bromodomain‐containing protein 4 (BRD4) inhibition by JQ1 in OS cells. Chromatin immunoprecipitation (ChIP) showed that enrichment of BRD4 protein around RUNX2 transcription start sites diminished with JQ1 treatment in MNNG/HOS cells. Overexpression of RUNX2 protected JQ1‐sensitive OS cells from the effect of JQ1, and siRNA‐mediated inhibition of RUNX2 sensitized the same cells to JQ1. In conclusion, our findings suggest that JQ1, in combination with rapamycin, is an effective chemotherapeutic option for OS treatment. We also show that inhibition of RUNX2 expression by JQ1 partly explains the antiproliferative activity of JQ1 in OS cells.
Study on High-side LDMOS energy capability Improvement

Improvement of Laterally Diffused Metal Oxide Semiconductor (LDMOS) energy capability, Unclamped inductive switching (UIS) is used to characterize ruggedness in terms of the maximum avalanche energy that device can handle prior to destructive breakdown. Maximum amount of UIS energy (EAS) sustained by device before failure is evaluated and have linear relationship with number of device finger and device-width. As we know that in multi-finger LDMOS the equivalent parasitic resistance gets lowered and MOS cells hence avoiding possibility of current failure. With lowered parasitic resistance Maximum energy of avalanche in single pulse (EAS) energy increases linearly with number of fingers. [l]
Quantifying apoprotein synthesis in rodents: coupling LC-MS/MS analyses with the administration of labeled water

Stable isotope tracer studies of apoprotein flux in rodent models present difficulties as they require working with small volumes of plasma. We demonstrate the ability to measure apoprotein flux by administering either 2H- or 18O-labeled water to mice and then subjecting samples to LC-MS/MS analyses; we were able to simultaneously determine the labeling of several proteolytic peptides representing multiple apoproteins. Consistent with relative differences reported in the literature regarding apoprotein flux in humans, we found that the fractional synthetic rate of apoB is greater than apoA1 in mice. In addition, the method is suitable for quantifying acute changes in protein flux: we observed a stimulation of apoB production in mice following an intravenous injection of Intralipid and a decrease in apoB production in mice treated with an inhibitor of microsomal triglyceride transfer protein. In summary, we demonstrate a high-throughput method for studying apoprotein kinetics in rodent models. Although notable differences exist between lipoprotein profiles that are observed in rodents and humans, we expect that the method reported here has merit in studies of dyslipidemia as i) rodent models can be used to probe target engagement in cases where one aims to modulate apoprotein production and ii) the approach should be adaptable to studies in humans.
LCD: A Fast Contrastive Divergence Based Algorithm for Restricted Boltzmann Machine

Restricted Boltzmann Machine (RBM) is the building block of Deep Belief Nets and other deep learning tools. Fast learning and prediction are both essential for practical usage of RBM-based machine learning techniques. This paper proposes Lean Contrastive Divergence (LCD), a modified Contrastive Divergence (CD) algorithm, to accelerate RBM learning and prediction without changing the results. LCD avoids most of the required computations with two optimization techniques. The first is called bounds-based filtering, which, through triangle inequality, replaces expensive calculations of many vector dot products with fast bounds calculations. The second is delta product, which effectively detects and avoids many repeated calculations in the core operation of RBM, Gibbs Sampling. The optimizations are applicable to both the standard contrastive divergence learning algorithm and its variations. Results show that the optimizations can produce several-fold (up to 3X for training and 5.3X for prediction) speedups.