Nanoparticles in cigarette smoke; real-time undiluted measurements by a scanning mobility particle sizer

Cigarette smoke is a complex mixture of smoke constituents, often characterised by size-resolved particle distributions. Since descriptions of ultrafine particles <50 nm are absent, our aim was to explore the existence of these nanoparticles in fresh and undiluted cigarette smoke. We measured undiluted smoke particles real-time by a scanning mobility particle sizer with Faraday cup electrometer, integrated in our custom-made smoking machine. Cigarettes were smoked by 2 s puffs, 30 s puff intervals and 50 ml puff volume. We tested six different cigarettes (1–10 mg tar per cigarette) at ten particle size-ranges between 6 and 50 nm, and repeated measurements five times. The formation of nanoparticles in fresh cigarette smoke was observed over the entire range between 6 and 50 nm, and reproduced in all cigarettes. The highest mean yield was 8.8 × 109 (SD = 1.1 × 109) particles per cigarette at the largest particle size range by high-tar cigarettes. Nanoparticle counts appear to increase with particle size, claimed tar values and blocking of filter ventilation holes, and inversely with butt length. Fresh undiluted cigarette smoke contains large amounts of potentially toxic nanoparticles <50 nm. We recommend to further study nanoparticles in the characterisation of cigarette smoke

A broader role for AmyR in Aspergillus niger: regulation of the utilisation of d-glucose or d-galactose containing oligo- and polysaccharides

AmyR is commonly considered a regulator of starch degradation whose activity is induced by the presence of maltose, the disaccharide building block of starch. In this study, we demonstrate that the role of AmyR extends beyond starch degradation. Enzyme activity assays, genes expression analysis and growth profiling on d-glucose- and d-galactose-containing oligo- and polysaccharides showed that AmyR regulates the expression of some of the Aspergillus niger genes encoding α- and β-glucosidases, α- and β- galactosidases, as well as genes encoding α-amlyases and glucoamylases. In addition, we provide evidence that d-glucose or a metabolic product thereof may be the inducer of the AmyR system in A. niger and not maltose, as is commonly assumed

Study of the ZZ\gamma and Z\gamma\gamma Couplings in Z(\nu\nu)\gamma Production

We have measured the ZZ-gamma and Z-gamma-gamma couplings by studying p-bar p -> (missing ET) gamma + X events at sqrt(s)=1.8 TeV with the D0 detector at the Fermilab Tevatron Collider. This first study of hadronic Z-gamma production in the neutrino decay channel gives the most stringent limits on anomalous couplings available. A fit to the transverse energy spectrum of the photon in the candidate event sample, based on a data set corresponding to an integrated luminosity of 13.1 pb^(-1), yields 95% CL limits on the anomalous CP-conserving ZZ-gamma couplings of |h^Z_(30)|<0.9, |h^Z_(40)|<0.21, for a form-factor scale Lambda = 500 GeV. Combining these results with our previous measurement using Z -> ee and mu-mu yields the limits:|h^Z_(30)|<0.8, |h^Z_(40)|<0.19 (Lambda = 500 GeV) and |h^Z_(30)|<0.4, |h^Z_(40)|<0.06 (Lambda = 750 GeV).Comment: 10 pages, 2 figures, 2 table

Studies of Gauge Boson Pair Production and Trilinear Couplings

The gauge boson pair production processes Wg, WW, WZ, and Zg were studied using pbarp collisions corresponding to an integrated luminosity of ~14 pb-1 at a center-of-mass energy of sqrt(s) = 1.8 TeV. Analysis of Wg prod with subsequent W boson decay to lv (l=e,mu) is reported, including a fit to the pT spectrum of the photons which leads to limits on anomalous WWg couplings. A search for WW prod with subsequent decay to l-lbar-v-vbar (l=e,mu) is presented leading to an upper limit on the WW prod cross section and limits on anomalous WWg and WWZ couplings. A search for high pT W bosons in WW and WZ prod is described, where one W boson decays to an ev and the second W boson or the Z boson decays to two jets. A maximum likelihood fit to the pT spectrum of W bosons resulted in limits on anomalous WWg and WWZ couplings. A combined fit to the three data sets which provided the tightest limits on anomalous WWg and WWZ couplings is also described. Limits on anomalous ZZg and Zgg couplings are presented from an analysis of the photon ET spectrum in Zg events in the decay channels (ee, mu-mu, and v-vbar) of the Z boson.Comment: 77 Pages including 40 Figures. Submitted to PR

Limits on Anomalous WWγWW\gamma Couplings from ppˉ→Wγ+Xp\bar{p} \to W \gamma + X Events at s=1.8\sqrt{s}=1.8 TeV

We have measured the $WW\gamma$ gauge boson coupling parameters using $p\bar{p}\to \ell\nu\gamma+X$ ($\ell=e,\mu$) events at $\sqrt{s}=1.8$ TeV. The data, corresponding to an integrated luminosity of 89.1 pb^{-1}, were collected using the D0 detector at the Fermilab Tevatron Collider. The measured cross section times branching ratio for $p\bar{p} \to W\gamma+X$ with $p_T^\gamma$ > 10 GeV/c and $R_{\ell\gamma} > 0.7$ is ${11.8}^{+1.7}_{-1.6} \pm 2.0$ pb, in agreement with the Standard Model prediction. The one degree of freedom 95% confidence level limits on individual CP-conserving parameters are $-0.98<\Delta\kappa<1.01$ and $-0.33<\lambda<0.31$. Similar limits are set on the CP}violating coupling parameters.Comment: 10 pages, including two figures. Paper submitted to Phys. Rev. Let

Verbal and nonverbal indices of learning during problem-based learning (PBL) among first year medical students and the threshold for tutor intervention

Background: During problem-based learning (PBL), students brainstorm on a problem, generate hypotheses and formulate learning objectives. Certain verbal and non-verbal expressions are used by students in response to specific learning issues. Aims: This study examines the use of these expressions as indices of the learning taking place and the tutors’ threshold to intervene. Methods: Common verbal expressions used by students during PBL were identified and scored on a Likert scale to indicate the learning taking place. These expressions were categorised into the following groups of learning interactions: exploratory questioning, cumulative reasoning and handling conflicts relating to learning. The tutor's threshold for intervention was also scored on a Likert scale. Means for each learning interaction and observed non-verbal expressions were used to construct bar charts for comparison. Results: When the learning interactions involve exploratory questioning or cumulative reasoning, students tend to score high on learning and tutors have high threshold for intervention. When the learning interactions involve handling conflicts relating to knowledge, students score high on learning, but teachers have a low threshold for intervention. Conclusion: Verbal and non-verbal expressions from students during PBL are useful indices of learning and can be used to help tutors decide when and when not to intervene