972 resultados para Gas sensing device
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BACKGROUND AND PURPOSE: A right-to-left shunt can be identified by contrast transcranial Doppler ultrasonography (c-TCD) at rest and/or after a Valsalva maneuver (VM) or by arterial blood gas (ABG) measurement. We assessed the influence of controlled strain pressures and durations during VM on the right-to-left passage of microbubbles, on which depends the shunt classification by c-TCD, and correlated it with the right-to-left shunt evaluation by ABG measurements in stroke patients with patent foramen ovale (PFO). METHODS: We evaluated 40 stroke patients with transesophageal echocardiography-documented PFO. The microbubbles were recorded with TCD at rest and after 4 different VM conditions with controlled duration and target strain pressures (duration in seconds and pressure in cm H2O, respectively): V5-20, V10-20, V5-40, and V10-40. The ABG analysis was performed after pure oxygen breathing in 34 patients, and the shunt was calculated as percentage of cardiac output. RESULTS: Among all VM conditions, V5-40 and V10-40 yielded the greatest median number of microbubbles (84 and 95, respectively; P<0.01). A significantly larger number of microbubbles were detected in V5-40 than in V5-20 (P<0.001) and in V10-40 than in V10-20 (P<0.01). ABG was not sensitive enough to detect a shunt in 31 patients. CONCLUSIONS: The increase of VM expiratory pressure magnifies the number of microbubbles irrespective of the strain duration. Because the right-to-left shunt classification in PFO is based on the number of microbubbles, a controlled VM pressure is advised for a reproducible shunt assessment. The ABG measurement is not sensitive enough for shunt assessment in stroke patients with PFO.
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This paper identifies the key sectors in greenhouse gas emissions of the Uruguayan economy through input-output analysis. This allows to precisely determine the role played by the different productive sectors and their relationship with other sectors in the relation between the Uruguayan productive structure and atmospheric pollution. In order to guide policy design for GHG reduction, we decompose sectors liability between the pollution generated through their own production processes and the pollution indirectly generated in the production processes of other sectors. The results show that all the key polluting sectors for the different contaminants considered are relevant because of their own emissions, except for the sector Motor vehicles and oil retail trade, which is relevant in CO2 emissions because of its pure, both backward and forward, linkages. Finally, the best policy channels for controlling and reducing GHGs emissions are identified, and compared with the National Climate Change Response Plan (NCCRP) lines of action.
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OBJECTIVE: Home blood pressure (BP) monitoring is recommended by several clinical guidelines and has been shown to be feasible in elderly persons. Wrist manometers have recently been proposed for such home BP measurement, but their accuracy has not been previously assessed in elderly patients. METHODS: Forty-eight participants (33 women and 15 men, mean age 81.3±8.0 years) had their BP measured with a wrist device with position sensor and an arm device in random order in a sitting position. RESULTS: Average BP measurements were consistently lower with the wrist than arm device for systolic BP (120.1±2.2 vs. 130.5±2.2 mmHg, P<0.001, means±SD) and diastolic BP (66.0±1.3 vs. 69.7±1.3 mmHg, P<0.001). Moreover, a 10 mmHg or greater difference between the arm and wrist device was observed in 54.2 and 18.8% of systolic and diastolic measures, respectively. CONCLUSION: Compared with the arm device, the wrist device with position sensor systematically underestimated systolic as well as diastolic BP. The magnitude of the difference is clinically significant and questions the use of the wrist device to monitor BP in elderly persons. This study points to the need to validate BP measuring devices in all age groups, including in elderly persons.
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PURPOSE: We investigated the incidence and distribution of post-mortem gas detected with multidetector computed tomography (MDCT) to identify factors that could distinguish artifactual gas from cardiac air embolism. MATERIAL AND METHODS: MDCT data of 119 cadavers were retrospectively examined. Gas was semiquantitatively assessed in selected blood vessels, organs, and body spaces (82 total sites). RESULTS: Seventy-four of the 119 cadavers displayed gas (62.2%; CI 95% 52.8-70.9), and 56 (75.7%) displayed gas in the heart. Most gas was detected in the hepatic parenchyma (40%), right heart (38% ventricle, 35% atrium), inferior vena cava (30% infrarenally, 26% suprarenally), hepatic veins (26% left, 29% middle, 22% right), and portal spaces (29%). Male cadavers displayed gas more frequently than female cadavers. Gas was detected 5-84 hours after death; therefore, the post-mortem interval could not reliably predict gas distribution (rho = 0.719, p < 0.0001). We found that a large amount of putrefaction-generated gas in the right heart was associated with aggregated gas bubbles in the hepatic parenchyma (sensitivity = 100%, specificity = 89.7%). In contrast, gas in the left heart (sensitivity = 41.7%, specificity = 100%) or in periumbilical subcutaneous tissues (sensitivity = 50%, specificity = 96.3%) could not predict gas due to putrefaction. CONCLUSION: This study is the first to show that the appearance of post-mortem gas follows a specific distribution pattern. An association between intracardiac gas and hepatic parenchymal gas could distinguish between post-mortem-generated gas and vital air embolism. We propose that this finding provides a key for diagnosing death due to cardiac air embolism.
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The identification of compositional changes in fumarolic gases of active and quiescent volcanoes is one of the mostimportant targets in monitoring programs. From a general point of view, many systematic (often cyclic) and randomprocesses control the chemistry of gas discharges, making difficult to produce a convincing mathematical-statisticalmodelling.Changes in the chemical composition of volcanic gases sampled at Vulcano Island (Aeolian Arc, Sicily, Italy) fromeight different fumaroles located in the northern sector of the summit crater (La Fossa) have been analysed byconsidering their dependence from time in the period 2000-2007. Each intermediate chemical composition has beenconsidered as potentially derived from the contribution of the two temporal extremes represented by the 2000 and 2007samples, respectively, by using inverse modelling methodologies for compositional data. Data pertaining to fumarolesF5 and F27, located on the rim and in the inner part of La Fossa crater, respectively, have been used to achieve theproposed aim. The statistical approach has allowed us to highlight the presence of random and not random fluctuations,features useful to understand how the volcanic system works, opening new perspectives in sampling strategies and inthe evaluation of the natural risk related to a quiescent volcano
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To the Editor: The value of angiotensin-converting– enzyme (ACE) inhibitors, beta-blockers, and spironolactone has been well established by the results of numerous clinical trials. About 70 percent of the patients described by Rose et al. were treated with ACE inhibitors or angiotensin II–receptor antagonists; 35 to 40 percent received spironolactone, and only about 20 percent received beta-blockers. Thus, this population cannot have been considered to be optimally treated from the point of view of medical therapy.
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A new analytical approach for measuring methane in tissues is presented. For the first time, the use of in situ-produced, stably labelled CDH(3) provides a reliable and precise methane quantification. This method was applied to postmortem samples obtained from two victims to help determine the explosion origin. There was evidence of methane in the adipose tissue (82 nmol/g) and cardiac blood (1.3 nmol/g) of one victim, which corresponded to a lethal methane outburst. These results are discussed in the context of the available literature to define an analysis protocol for application in the event of a gas explosion.
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[Traditions. Europe. Roumanie]
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Most ventricular assist devices (VADs) currently used in infants are extracorporeal. These VADs require long-term anticoagulation therapy and extensive surgery, and two devices are needed for biventricular support. We designed a biventricular assist device based on shape memory alloy that reproduces the hemodynamic effects of cardiomyoplasty, supporting the heart with a compressing movement, and evaluated its performance in a dedicated mockup system. Nitinol fibers are the device's key component. Ejection fraction (EF), cardiac output (CO), and generated systolic pressure were measured on a test bench. Our test bench settings were a preload range of 0-15 mm Hg, an afterload range of 0-160 mm Hg, and a heart rate (HR) of 20, 30, 40, and 60 beats/min. A power supply of 15 volts and 3.5 amperes was necessary. The EF range went from 34.4% to 1.2% as the afterload and HR increased, along with a CO from 180 to 6 ml/min. The device generated a maximal systolic pressure of 25 mm Hg. Cardiac compression for biventricular assistance in child-sized heart using shape memory alloy is technically feasible. Further testing remains necessary to assess this VAD's in vivo performance range and its reliability.
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Saffaj et al. recently criticized our method of monitoring carbon dioxide in human postmortem cardiac gas samples using Headspace-Gas Chromatography-Mass Spectrometry. According to the authors, their demonstration, based on the latest SFSTP guidelines (established after 2007 [1,2]) fitted for the validation of drug monitoring bioanalytical methods, has put in evidence potential errors. However, our validation approach was built using SFSTP guidelines established before 2007 [3-6]. We justify the use of these guidelines because of the post-mortem context of the study (and not clinical) and the gaseous state of the sample (and not solid or liquid). Using these guidelines, our validation remains correct.
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Differential scanning calorimetry (DSC) was used to study the dehydrogenation processes that take place in three hydrogenated amorphous silicon materials: nanoparticles, polymorphous silicon, and conventional device-quality amorphous silicon. Comparison of DSC thermograms with evolved gas analysis (EGA) has led to the identification of four dehydrogenation processes arising from polymeric chains (A), SiH groups at the surfaces of internal voids (A'), SiH groups at interfaces (B), and in the bulk (C). All of them are slightly exothermic with enthalpies below 50 meV/H atoms , indicating that, after dissociation of any SiH group, most dangling bonds recombine. The kinetics of the three low-temperature processes [with DSC peak temperatures at around 320 (A),360 (A'), and 430°C (B)] exhibit a kinetic-compensation effect characterized by a linea relationship between the activation entropy and enthalpy, which constitutes their signature. Their Si-H bond-dissociation energies have been determined to be E (Si-H)0=3.14 (A), 3.19 (A'), and 3.28 eV (B). In these cases it was possible to extract the formation energy E(DB) of the dangling bonds that recombine after Si-H bond breaking [0.97 (A), 1.05 (A'), and 1.12 (B)]. It is concluded that E(DB) increases with the degree of confinement and that E(DB)>1.10 eV for the isolated dangling bond in the bulk. After Si-H dissociation and for the low-temperature processes, hydrogen is transported in molecular form and a low relaxation of the silicon network is promoted. This is in contrast to the high-temperature process for which the diffusion of H in atomic form induces a substantial lattice relaxation that, for the conventional amorphous sample, releases energy of around 600 meV per H atom. It is argued that the density of sites in the Si network for H trapping diminishes during atomic diffusion
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Nowadays, the joint exploitation of images acquired daily by remote sensing instruments and of images available from archives allows a detailed monitoring of the transitions occurring at the surface of the Earth. These modifications of the land cover generate spectral discrepancies that can be detected via the analysis of remote sensing images. Independently from the origin of the images and of type of surface change, a correct processing of such data implies the adoption of flexible, robust and possibly nonlinear method, to correctly account for the complex statistical relationships characterizing the pixels of the images. This Thesis deals with the development and the application of advanced statistical methods for multi-temporal optical remote sensing image processing tasks. Three different families of machine learning models have been explored and fundamental solutions for change detection problems are provided. In the first part, change detection with user supervision has been considered. In a first application, a nonlinear classifier has been applied with the intent of precisely delineating flooded regions from a pair of images. In a second case study, the spatial context of each pixel has been injected into another nonlinear classifier to obtain a precise mapping of new urban structures. In both cases, the user provides the classifier with examples of what he believes has changed or not. In the second part, a completely automatic and unsupervised method for precise binary detection of changes has been proposed. The technique allows a very accurate mapping without any user intervention, resulting particularly useful when readiness and reaction times of the system are a crucial constraint. In the third, the problem of statistical distributions shifting between acquisitions is studied. Two approaches to transform the couple of bi-temporal images and reduce their differences unrelated to changes in land cover are studied. The methods align the distributions of the images, so that the pixel-wise comparison could be carried out with higher accuracy. Furthermore, the second method can deal with images from different sensors, no matter the dimensionality of the data nor the spectral information content. This opens the doors to possible solutions for a crucial problem in the field: detecting changes when the images have been acquired by two different sensors.