Black pine (Pinus nigra) barks: A critical evaluation of some sampling and analysis parameters for mercury biomonitoring purposes

Abstract Tree barks are increasingly used as biomonitors of airborne pollutants. However, many authors stress the poor comparability of the results achieved in different studies. This drawback is mainly caused by a poor understanding of the critical sampling parameters to be considered. To minimize the biases that could be introduced during sampling, in this study the barks of Pinus nigra J.F. Arnold from thirteen sites were investigated in the abandoned Mt. Amiata mercury (Hg) mining district (Southern Tuscany, Italy) and surroundings. The influence of some sampling and analyzing parameters on Hg content was critically assessed. At each site, a total of eight bark samples were taken from a single tree at two heights (70 cm and 150 cm from soil) and at four different sides of the trunk, corresponding to the four cardinal directions; a composite soil sample was also collected. Mercury contents in barks range from 0.1 to 28.8 mg/kg, and are correlated with soil Hg contents (1–480 mg/kg), indicating that barks record both gaseous Hg concentrations in air, and wind-transported Hg-bearing particulate. For each tree, samples at 70 cm and 150 cm show Hg contents of the same order of magnitude, even if values for 150 cm are slightly less dispersed, possibly because barks at 70 cm are more influenced by random soil particles. There is no statistically significant dependence of Hg content on direction and tree age. Simulated rain events cause a negligible loss of Hg from barks. Results suggest that a convenient sampling practice for Pinus nigra is to collect a bark slice (typically 1–2 mm) within the outermost 1.5 cm layer

CMS physics technical design report : Addendum on high density QCD with heavy ions

Peer reviewe

Electroweak measurements in electron–positron collisions at w-boson-pair energies at lep

Contains fulltext : 121524.pdf (preprint version ) (Open Access

Search for Charged Higgs bosons: Combined Results Using LEP Data

The four LEP collaborations, ALEPH, DELPHI, L3 and OPAL, have searched for pair-produced charged Higgs bosons in the framework of Two Higgs Doublet Models (2HDMs). The data of the four experiments are statistically combined. The results are interpreted within the 2HDM for Type I and Type II benchmark scenarios. No statistically significant excess has been observed when compared to the Standard Model background prediction, and the combined LEP data exclude large regions of the model parameter space. Charged Higgs bosons with mass below 80 GeV/c^2 (Type II scenario) or 72.5 GeV/c^2 (Type I scenario, for pseudo-scalar masses above 12 GeV/c^2) are excluded at the 95% confidence level

CMS physics technical design report: Addendum on high density QCD with heavy ions

This report presents the capabilities of the CMS experiment to explore the rich heavy-ion physics programme offered by the CERN Large Hadron Collider (LHC). The collisions of lead nuclei at energies ,will probe quark and gluon matter at unprecedented values of energy density. The prime goal of this research is to study the fundamental theory of the strong interaction - Quantum Chromodynamics (QCD) - in extreme conditions of temperature, density and parton momentum fraction (low-x). This report covers in detail the potential of CMS to carry out a series of representative Pb-Pb measurements. These include "bulk" observables, (charged hadron multiplicity, low pT inclusive hadron identified spectra and elliptic flow) which provide information on the collective properties of the system, as well as perturbative probes such as quarkonia, heavy-quarks, jets and high pT hadrons which yield "tomographic" information of the hottest and densest phases of the reaction.0info:eu-repo/semantics/publishe

ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19

The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use