94 research outputs found
Effect of particle size on silver nanoparticle deposition onto dielectric barrier discharge (DBD) plasma functionalized polyamide fabric
The effect on the deposition of three different size silver nanoparticles (AgNPs) onto a polyamide 6,6 (PA) fabric pre-treated using air dielectric barrier discharge (DBD) plasma was investigated. The SEM, EDS, and XPS analysis confirm that the smaller is the diameter of AgNPs, the higher the amount of adsorbed NPs on the PA. The DBD treatment on PA induces a threefold increase in Ag adsorption. The result confirms a dual effect on the wettability of the plasma treated PA substrate. AgNPs slightly enhance hydrophobicity of the PA surface and, at the same time, protect it against the plasma aging effect. The effect on the deposition of three different size silver nanoparticles (AgNPs) onto a Polyamide 6,6 (PA) fabric pre-treated using air dielectric barrier discharge (DBD) plasma was investigated. The smaller is the size, the higher the loaded AgNPs. The DBD treatment induces a threefold increase in Ag adsorption. AgNPs enhance hydrophobicity of the PA surface and reduce the plasma aging effect.Fundação para a Ciência e a Tecnologia (FCT
Hadronic Mass Moments in Inclusive Semileptonic B Meson Decays
We have measured the first and second moments of the hadronic mass-squared
distribution in B -> X_c l nu, for P(lepton) > 1.5 GeV/c. We find <M_X^2 -
M_D[Bar]^2> = 0.251 +- 0.066 GeV^2, )^2 > = 0.576 +- 0.170
GeV^4, where M_D[Bar] is the spin-averaged D meson mass.
From that first moment and the first moment of the photon energy spectrum in
b -> s gamma, we find the HQET parameter lambda_1 (MS[Bar], to order 1/M^3 and
beta_0 alpha_s^2) to be -0.24 +- 0.11 GeV^2. Using these first moments and the
B semileptonic width, and assuming parton-hadron duality, we obtain |V_cb| =
0.0404 +- 0.0013.Comment: 11 pages postscript, also available through
http://w4.lns.cornell.edu/public/CLNS, submitted to PR
Observation of the Charmed Baryon at CLEO
The CLEO experiment at the CESR collider has used 13.7 fb of data to
search for the production of the (css-ground state) in
collisions at {\rm GeV}. The modes used to
study the are ,
, , , and
. We observe a signal of 40.49.0(stat) events
at a mass of 2694.62.6(stat)1.9(syst) {\rm MeV/}, for all modes
combined.Comment: 10 pages postscript, also available through
http://w4.lns.cornell.edu/public/CLN
Evidence of New States Decaying into
Using 13.7 of data recorded by the CLEO detector at CESR, we report
evidence for two new charmed baryons: one decaying into
with the subsequent decay , and its
isospin partner decaying into followed by
. We measure the following mass differences
for the two states: =318.2+-1.3+-2.9 MeV,
and =324.0+-1.3+-3.0 MeV. We interpret
these new states as the particles, the charmed-strange
analogs of the .Comment: 10 pages postscript, also available through
http://w4.lns.cornell.edu/public/CLN
First Observation of the Decays and B^{0}\to D^{*-}p\bar{n}$
We report the first observation of exclusive decays of the type B to D^* N
anti-N X, where N is a nucleon. Using a sample of 9.7 times 10^{6} B-Bbar pairs
collected with the CLEO detector operating at the Cornell Electron Storage
Ring, we measure the branching fractions B(B^0 \to D^{*-} proton antiproton
\pi^+) = ({6.5}^{+1.3}_{-1.2} +- 1.0) \times 10^{-4} and B(B^0 \to D^{*-}
proton antineutron) = ({14.5}^{+3.4}_{-3.0} +- 2.7) times 10^{-4}. Antineutrons
are identified by their annihilation in the CsI electromagnetic calorimeter.Comment: 9 pages postscript, also available through
http://w4.lns.cornell.edu/public/CLN
A Search for
We report results of a search for in a sample of 9.7 million
charged meson decays. The search uses both and
decay modes of the , and demands exclusive reconstruction of the
companion decay to suppress background. We set an upper limit on the
branching fraction at 90%
confidence level. With slight modification to the analysis we also establish
at 90% confidence
level.Comment: 10 ages postscript, also available through
http://w4.lns.cornell.edu/public/CLN
Mixtures of xenoestrogens disrupt estradiol-induced non-genomic signaling and downstream functions in pituitary cells
A dose escalation and pharmacokinetic study of biweekly pegylated liposomal doxorubicin, paclitaxel and gemcitabine in patients with advanced solid tumours
To determine the maximum tolerated doses (MTDs) and dose-limiting toxicities (DLTs) of pegylated liposomal doxorubicin (PLD), paclitaxel (PCX) and gemcitabine (GEM) combination administered biweekly in patients with advanced solid tumours. Twenty-two patients with advanced-stage solid tumours were treated with escalated doses of PLD on day 1 and PCX plus GEM on day 2 (starting doses: 10, 100 and 800 mg m−2, respectively) every 2 weeks. DLTs and pharmacokinetic (PK) parameters of all drugs were determined during the first cycle of treatment. All but six (73%) patients had previously received at least one chemotherapy regimen. The DLT dose level was reached at PLD 12 mg m−2, PCX 110 mg m−2 and GEM 1000 mg m−2 with neutropaenia being the dose-limiting event. Of the 86 chemotherapy cycles delivered, grade 3 and 4 neutropaenia occurred in 20% with no cases of febrile neutropaenia. Non-haematological toxicities were mild. The recommended MTDs are PLD 12 mg m−2, PCX 100 mg m−2 and GEM 1000 mg m−2 administered every 2 weeks. The PK data revealed no obvious drug interactions. Biweekly administration of PLD, PCX and GEM is a well-tolerated chemotherapy regimen, which merits further evaluation in various types of solid tumours
Inhaled corticosteroid use is associated with increased circulating T regulatory cells in children with asthma
Combined artificial bee colony algorithm and machine learning techniques for prediction of online consumer repurchase intention
A novel paradigm in the service sector i.e. services through the web is a progressive mechanism for rendering offerings over diverse environments. Internet provides huge opportunities for companies to provide personalized online services to their customers. But prompt novel web services introduction may unfavorably affect the quality and user gratification. Subsequently, prediction of the consumer intention is of supreme importance in selecting the web services for an application. The aim of study is to predict online consumer repurchase intention and to achieve this objective a hybrid approach which a combination of machine learning techniques and Artificial Bee Colony (ABC) algorithm has been used. The study is divided into three phases. Initially, shopping mall and consumer characteristic’s for repurchase intention has been identified through extensive literature review. Secondly, ABC has been used to determine the feature selection of consumers’ characteristics and shopping malls’ attributes (with > 0.1 threshold value) for the prediction model. Finally, validation using K-fold cross has been employed to measure the best classification model robustness. The classification models viz., Decision Trees (C5.0), AdaBoost, Random Forest (RF), Support Vector Machine (SVM) and Neural Network (NN), are utilized for prediction of consumer purchase intention. Performance evaluation of identified models on training-testing partitions (70-30%) of the data set, shows that AdaBoost method outperforms other classification models with sensitivity and accuracy of 0.95 and 97.58% respectively, on testing data set. This study is a revolutionary attempt that considers both, shopping mall and consumer characteristics in examine the consumer purchase intention.N/
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