Utilidad de la electrocardiografía en la clínica veterinaria de animales de compañía

The electrocardiography is a diagnostic tool for the veterinary clinic of companion animals. In patients with cardiologic signs is the best non invasive means to evaluate the electric activity of the heart. It allows us to evaluate the present of arrhythmias, the pre-surgical state, assess the anaesthetic risk and check the pharmacologic treatments in cardiac patients amongst other. The objective of the present work was to illustrate the advantage of the electrocardiographic assess in canine and felíne patients, and its limitations and contraindications as well.La electrocardiografía es una herramienta diagnóstica de utilidad básica en la clínica veterinaria de animales de compañía. En pacientes con signos clínicos cardiológicos constituye la mejor alternativa diagnóstica para evaluar la actividad eléctrica del corazón de forma no invasiva El electrocardiograma permite demostrar la presencia de arritmias, colabora en la evaluación prequirúrgica y en la valoración del riesgo anestésico, ayuda a monitorear los tratamientos farmacológicos de pacientes cardiópatas, sugiere la presencia de sobrecargas camerales atriales y ventriculares cardíacas y complementa el diagnóstico en patologías de origen metabólico y endócrino. El objetivo del presenta trabajo es mostrar las distintas ventajas que presenta la evaluación electrocardiográfica en pacientes caninos y felinos, así como las límitaciones y contraindicaciones que presenta su estudio

SoFi, an IGOR-based interface for the efficient use of the generalized multilinear engine (ME-2) for the source apportionment: ME-2 application to aerosol mass spectrometer data

Source apportionment using the bilinear model through a multilinear engine (ME-2) was successfully applied to non-refractory organic aerosol (OA) mass spectra collected during the winter of 2011 and 2012 in Zurich, Switzerland using the aerosol chemical speciation monitor (ACSM). Five factors were identified: low-volatility oxygenated OA (LV-OOA), semivolatile oxygenated OA (SV-OOA), hydrocarbon-like OA (HOA), cooking OA (COA) and biomass burning OA (BBOA). A graphical user interface SoFi (Source Finder) was developed at PSI in order to facilitate the testing of different rotational techniques available within the ME-2 engine by providing a priori factor profiles for some or all of the expected factors. ME-2 was used to test the positive matrix factorization (PMF) model, the fully constrained chemical mass balance (CMB) model, and partially constrained models utilizing a values and pulling equations. Within the set of model solutions determined to be environmentally reasonable, BBOA and SV-OOA factor mass spectra and time series showed the greatest variability. This variability represents the uncertainty in the model solution and indicates that analysis of model rotations provides a useful approach for assessing the uncertainty of bilinear source apportionment models.ISSN:1867-1381ISSN:1867-854

Highly Time- and Size-Resolved Measurements of Trace Elements during ClearfLo

The identification and quantification of particle sources has long proven challenging due to the complex composition ofambient aerosol. Measurements of trace elements provide unique source-specific information; e.g. barium and copper areemitted by traffic sources, while vanadium and nickel are linked to heavy oil combustion. Here we present highly time- andsize-resolved measurements of trace elements as part of the ClearfLo (Clean Air for London) 2012 field campaign, amultinational collaborative effort to investigate boundary layer pollution in and around London, UK

Highly time-resolved trace Element Concentrations in Aerosols during the MEGAPOLI Paris Campaign

Trace elements contribute typically only a few percent to the total mass of air pollutants, however, they canaffect the environment in significant ways, especially those that are toxic. Furthermore, they are advantageouswith respect to a refinement of source apportionment when measured with high time resolution and appropriatesize segregation. This approach is especially advantageous in an urban environment with numerous time-variantemission sources distributed across a relatively narrow space, as is typically the setting of a megacity.Two 1-month long field campaigns took place in the framework of the Megapoli project in Paris, France, in thesummer of 2009 and in the winter of 2010. Rotating drum impactors (RDI) were operated at two sites in eachcampaign, one urban, the other one suburban. The RDI segregated the aerosols into three size ranges (PM10-2.5,PM2.5-1 and PM1-0.1) and sampled with 2-hour time resolution. The samples were analyzed with synchrotronradiation induced X-ray fluorescence spectrometry (SR-XRF) at the synchrotron facilities of Paul ScherrerInstitute (SLS) and Deutsches Elektronen-Synchrotron (HASYLAB), where a broad range of elements (Na, Mg,Al, Si, P, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Se, Sr, Zr, Cd, Sn, Sb, Ba, Pb) was analyzed for each sizerange.Time series of the analyzed elements for the different sites and campaigns were prepared to characterize theaerosol trace element composition and temporal behavior for the different weather situations and urban environments.They allow for the distinction of regional vs. local sources and transport, and provide a basis for sourceapportionment calculations. Local and regional contributions of traffic, including re-suspension, break wear andexhaust, wood burning, marine and other sources will be discussed. Indications of long-range transport fromPolish coal emissions in the city center of Paris were also found

A new method for long-term source apportionment with time-dependent factor profiles and uncertainty assessment using SoFi Pro: application to 1 year of organic aerosol data

A new methodology for performing long-term source apportionment (SA) using positive matrix factorization (PMF) is presented. The method is implemented within the SoFi Pro software package and uses the multilinear engine (ME-2) as a PMF solver. The technique is applied to a 1-year aerosol chemical speciation monitor (ACSM) dataset from downtown Zurich, Switzerland. The measured organic aerosol mass spectra were analyzed by PMF using a small (14 d) and rolling PMF window to account for the temporal evolution of the sources. The rotational ambiguity is explored and the uncertainties of the PMF solutions were estimated. Factor-tracer correlations for averaged seasonal results from the rolling window analysis are higher than those retrieved from conventional PMF analyses of individual seasons, highlighting the improved performance of the rolling window algorithm for long-term data. In this study four to five factors were tested for every PMF window. Factor profiles for primary organic aerosol from traffic (HOA), cooking (COA) and biomass burning (BBOA) were constrained. Secondary organic aerosol was represented by either the combination of semi-volatile and low-volatility organic aerosol (SV-OOA and LV-OOA, respectively) or by a single OOA when this separation was not robust. This scheme led to roughly 40 000 PMF runs. Full visual inspection of all these PMF runs is unrealistic and is replaced by predefined user-selected criteria, which allow factor sorting and PMF run acceptance/rejection. The selected criteria for traffic (HOA) and BBOA were the correlation with equivalent black carbon from traffic (eBC(tr)) and the explained variation of m/z 60, respectively. COA was assessed by the prominence of a lunchtime concentration peak within the diurnal cycle. SV-OOA and LV-OOA were evaluated based on the fractions of m/z 43 and 44 in their respective factor profiles. Seasonal pre-tests revealed a noncontinuous separation of OOA into SV-OOA and LV-OOA, in particular during the warm seasons. Therefore, a differentiation between four-factor solutions (HOA, COA, BBOA and OOA) and five-factor solutions (HOA, COA, BBOA, SVOOA and LV-OOA) was also conducted based on the criterion for SV-OOA. HOA and COA contribute between 0.4-0.7 mu g m(-3) (7.8 %-9.0 %) and 0.7-1.2 mu g m(-3) (12.2 %-15.7 %) on average throughout the year, respectively. BBOA shows a strong yearly cycle with the lowest mean concentrations in summer (0.6 mu g m(-3), 12.0 %), slightly higher mean concentrations during spring and fall (1.0 and 1.5 mu g m(-3), or 15.6% and 18.6 %, respectively), and the highest mean concentrations during winter (1.9 mu g m(-3), 25.0 %). In summer, OOA is separated into SV-OOA and LV-OOA, with mean concentrations of 1.4 mu g m(-3) (26.5 %) and 2.2 mu g m(-3) (40.3 %), respectively. For the remaining seasons the seasonal concentrations of SV-OOA, LV-OOA and OOA range from 0.3 to 1.1 mu g m(-3) (3.4 %-15.9 %), from 0.6 to 2.2 mu g m(-3) (7.7 %33.7 %) and from 0.9 to 3.1 mu g m(-3) (13.7 %-39.9 %), respectively. The relative PMF errors modeled for this study for HOA, COA, BBOA, LV-OOA, SV-OOA and OOA are on average +/- 34 %, +/- 27 %, +/- 30 %, +/- 11 %, +/- 25 % and +/- 12 %, respectively