50 resultados para Non-point Source Pollution

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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In early spring the Baltic region is frequently affected by high-pollution events due to biomass burning in that area. Here we present a comprehensive study to investigate the impact of biomass/grass burning (BB) on the evolution and composition of aerosol in Preila, Lithuania, during springtime open fires. Non-refractory submicron particulate matter (NR-PM1) was measured by an Aerodyne aerosol chemical speciation monitor (ACSM) and a source apportionment with the multilinear engine (ME-2) running the positive matrix factorization (PMF) model was applied to the organic aerosol fraction to investigate the impact of biomass/grass burning. Satellite observations over regions of biomass burning activity supported the results and identification of air mass transport to the area of investigation. Sharp increases in biomass burning tracers, such as levoglucosan up to 683 ngm-3 and black carbon (BC) up to 17 μgm-3 were observed during this period. A further separation between fossil and non-fossil primary and secondary contributions was obtained by coupling ACSM PMF results and radiocarbon (14C) measurements of the elemental (EC) and organic (OC) carbon fractions. Non-fossil organic carbon (OCnf/ was the dominant fraction of PM1, with the primary (POCnf/ and secondary (SOCnf/ fractions contributing 26–44% and 13–23% to the total carbon (TC), respectively. 5–8% of the TC had a primary fossil origin (POCf/, whereas the contribution of fossil secondary organic carbon (SOCf/ was 4–13 %. Nonfossil EC (ECnf/ and fossil EC (ECf/ ranged from 13–24 and 7–13 %, respectively. Isotope ratios of stable carbon and nitrogen isotopes were used to distinguish aerosol particles associated with solid and liquid fossil fuel burning.

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The CIAO Study ("Complicated Intra-Abdominal infection Observational" Study) is a multicenter investigation performed in 68 medical institutions throughout Europe over the course of a 6-month observational period (January-June 2012).Patients with either community-acquired or healthcare-associated complicated intra-abdominal infections (IAIs) were included in the study.2,152 patients with a mean age of 53.8 years (range: 4-98 years) were enrolled in the study. 46.3% of the patients were women and 53.7% were men. Intraperitoneal specimens were collected from 62.2% of the enrolled patients, and from these samples, a variety of microorganisms were collectively identified.The overall mortality rate was 7.5% (163/2.152).According to multivariate analysis of the compiled data, several criteria were found to be independent variables predictive of patient mortality, including patient age, the presence of an intestinal non-appendicular source of infection (colonic non-diverticular perforation, complicated diverticulitis, small bowel perforation), a delayed initial intervention (a delay exceeding 24 hours), sepsis and septic shock in the immediate post-operative period, and ICU admission.Given the sweeping geographical distribution of the participating medical centers, the CIAO Study gives an accurate description of the epidemiological, clinical, microbiological, and treatment profiles of complicated intra-abdominal infections (IAIs) throughout Europe.

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Stray light contamination reduces considerably the precision of photometric of faint stars for low altitude spaceborne observatories. When measuring faint objects, the necessity of coping with stray light contamination arises in order to avoid systematic impacts on low signal-to-noise images. Stray light contamination can be represented by a flat offset in CCD data. Mitigation techniques begin by a comprehensive study during the design phase, followed by the use of target pointing optimisation and post-processing methods. We present a code that aims at simulating the stray-light contamination in low-Earth orbit coming from reflexion of solar light by the Earth. StrAy Light SimulAtor (SALSA) is a tool intended to be used at an early stage as a tool to evaluate the effective visible region in the sky and, therefore to optimise the observation sequence. SALSA can compute Earth stray light contamination for significant periods of time allowing missionwide parameters to be optimised (e.g. impose constraints on the point source transmission function (PST) and/or on the altitude of the satellite). It can also be used to study the behaviour of the stray light at different seasons or latitudes. Given the position of the satellite with respect to the Earth and the Sun, SALSA computes the stray light at the entrance of the telescope following a geometrical technique. After characterising the illuminated region of the Earth, the portion of illuminated Earth that affects the satellite is calculated. Then, the flux of reflected solar photons is evaluated at the entrance of the telescope. Using the PST of the instrument, the final stray light contamination at the detector is calculated. The analysis tools include time series analysis of the contamination, evaluation of the sky coverage and an objects visibility predictor. Effects of the South Atlantic Anomaly and of any shutdown periods of the instrument can be added. Several designs or mission concepts can be easily tested and compared. The code is not thought as a stand-alone mission designer. Its mandatory inputs are a time series describing the trajectory of the satellite and the characteristics of the instrument. This software suite has been applied to the design and analysis of CHEOPS (CHaracterizing ExOPlanet Satellite). This mission requires very high precision photometry to detect very shallow transits of exoplanets. Different altitudes and characteristics of the detector have been studied in order to find the best parameters, that reduce the effect of contamination. © (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

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Surgical robots have been proposed ex vivo to drill precise holes in the temporal bone for minimally invasive cochlear implantation. The main risk of the procedure is damage of the facial nerve due to mechanical interaction or due to temperature elevation during the drilling process. To evaluate the thermal risk of the drilling process, a simplified model is proposed which aims to enable an assessment of risk posed to the facial nerve for a given set of constant process parameters for different mastoid bone densities. The model uses the bone density distribution along the drilling trajectory in the mastoid bone to calculate a time dependent heat production function at the tip of the drill bit. Using a time dependent moving point source Green's function, the heat equation can be solved at a certain point in space so that the resulting temperatures can be calculated over time. The model was calibrated and initially verified with in vivo temperature data. The data was collected in minimally invasive robotic drilling of 12 holes in four different sheep. The sheep were anesthetized and the temperature elevations were measured with a thermocouple which was inserted in a previously drilled hole next to the planned drilling trajectory. Bone density distributions were extracted from pre-operative CT data by averaging Hounsfield values over the drill bit diameter. Post-operative [Formula: see text]CT data was used to verify the drilling accuracy of the trajectories. The comparison of measured and calculated temperatures shows a very good match for both heating and cooling phases. The average prediction error of the maximum temperature was less than 0.7 °C and the average root mean square error was approximately 0.5 °C. To analyze potential thermal damage, the model was used to calculate temperature profiles and cumulative equivalent minutes at 43 °C at a minimal distance to the facial nerve. For the selected drilling parameters, temperature elevation profiles and cumulative equivalent minutes suggest that thermal elevation of this minimally invasive cochlear implantation surgery may pose a risk to the facial nerve, especially in sclerotic or high density mastoid bones. Optimized drilling parameters need to be evaluated and the model could be used for future risk evaluation.

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This paper presents a kernel density correlation based nonrigid point set matching method and shows its application in statistical model based 2D/3D reconstruction of a scaled, patient-specific model from an un-calibrated x-ray radiograph. In this method, both the reference point set and the floating point set are first represented using kernel density estimates. A correlation measure between these two kernel density estimates is then optimized to find a displacement field such that the floating point set is moved to the reference point set. Regularizations based on the overall deformation energy and the motion smoothness energy are used to constraint the displacement field for a robust point set matching. Incorporating this non-rigid point set matching method into a statistical model based 2D/3D reconstruction framework, we can reconstruct a scaled, patient-specific model from noisy edge points that are extracted directly from the x-ray radiograph by an edge detector. Our experiment conducted on datasets of two patients and six cadavers demonstrates a mean reconstruction error of 1.9 mm

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Many meditation exercises aim at increased awareness of ongoing experiences through sustained attention and at detachment, i.e., non-engaging observation of these ongoing experiences by the intent not to analyze, judge or expect anything. Long-term meditation practice is believed to generalize the ability of increased awareness and greater detachment into everyday life. We hypothesized that neuroplasticity effects of meditation (correlates of increased awareness and detachment) would be detectable in a no-task resting state. EEG recorded during resting was compared between Qigong meditators and controls. Using LORETA (low resolution electromagnetic tomography) to compute the intracerebral source locations, differences in brain activations between groups were found in the inhibitory delta EEG frequency band. In the meditators, appraisal systems were inhibited, while brain areas involved in the detection and integration of internal and external sensory information showed increased activation. This suggests that neuroplasticity effects of long-term meditation practice, subjectively described as increased awareness and greater detachment, are carried over into non-meditating states.

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While several studies have investigated winter-time air pollution with a wide range of concentration levels, hardly any results are available for longer time periods covering several winter-smog episodes at various locations; e.g., often only a few weeks from a single winter are investigated. Here, we present source apportionment results of winter-smog episodes from 16 air pollution monitoring stations across Switzerland from five consecutive winters. Radiocarbon (14C) analyses of the elemental (EC) and organic (OC) carbon fractions, as well as levoglucosan, major water-soluble ionic species and gas-phase pollutant measurements were used to characterize the different sources of PM10. The most important contributions to PM10 during winter-smog episodes in Switzerland were on average the secondary inorganic constituents (sum of nitrate, sulfate and ammonium = 41 ± 15%) followed by organic matter (OM) (34 ± 13%) and EC (5 ± 2%). The non-fossil fractions of OC (fNF,OC) ranged on average from 69 to 85 and 80 to 95% for stations north and south of the Alps, respectively, showing that traffic contributes on average only up to ~ 30% to OC. The non-fossil fraction of EC (fNF,EC), entirely attributable to primary wood burning, was on average 42 ± 13 and 49 ± 15% for north and south of the Alps, respectively. While a high correlation was observed between fossil EC and nitrogen oxides, both primarily emitted by traffic, these species did not significantly correlate with fossil OC (OCF), which seems to suggest that a considerable amount of OCF is secondary, from fossil precursors. Elevated fNF,EC and fNF,OC values and the high correlation of the latter with other wood burning markers, including levoglucosan and water soluble potassium (K+) indicate that residential wood burning is the major source of carbonaceous aerosols during winter-smog episodes in Switzerland. The inspection of the non-fossil OC and EC levels and the relation with levoglucosan and water-soluble K+ shows different ratios for stations north and south of the Alps (most likely because of differences in burning technologies) for these two regions in Switzerland.

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Fine carbonaceous aerosols (CAs) is the key factor influencing the currently filthy air in megacities in China, yet few studies simultaneously focus on the origins of different CAs species using specific and powerful source tracers. Here, we present a detailed source apportionment for various CAs fractions, including organic carbon (OC), water-soluble OC (WSOC), water-insoluble OC (WIOC), elemental carbon (EC) and secondary OC (SOC) in the largest cities of North (Beijing, BJ) and South China (Guangzhou, GZ), using the measurements of radiocarbon and anhydrosugars. Results show that non-fossil fuel sources such as biomass burning and biogenic emission make a significant contribution to the total CAs in Chinese megacities: 56±4 in BJ and 46±5% in GZ, respectively. The relative contributions of primary fossil carbon from coal and liquid petroleum combustions, primary non-fossil carbon and secondary organic carbon (SOC) to total carbon are 19, 28 and 54% in BJ, and 40, 15 and 46% in GZ, respectively. Non-fossil fuel sources account for 52 in BJ and 71% in GZ of SOC, respectively. These results suggest that biomass burning has a greater influence on regional particulate air pollution in North China than in South China. We observed an unabridged haze bloom-decay process in South China, which illustrates that both primary and secondary matter from fossil sources played a key role in the blooming phase of the pollution episode, while haze phase is predominantly driven by fossil-derived secondary organic matter and nitrate.

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Background There is concern that non-inferiority trials might be deliberately designed to conceal that a new treatment is less effective than a standard treatment. In order to test this hypothesis we performed a meta-analysis of non-inferiority trials to assess the average effect of experimental treatments compared with standard treatments. Methods One hundred and seventy non-inferiority treatment trials published in 121 core clinical journals were included. The trials were identified through a search of PubMed (1991 to 20 February 2009). Combined relative risk (RR) from meta-analysis comparing experimental with standard treatments was the main outcome measure. Results The 170 trials contributed a total of 175 independent comparisons of experimental with standard treatments. The combined RR for all 175 comparisons was 0.994 [95% confidence interval (CI) 0.978–1.010] using a random-effects model and 1.002 (95% CI 0.996–1.008) using a fixed-effects model. Of the 175 comparisons, experimental treatment was considered to be non-inferior in 130 (74%). The combined RR for these 130 comparisons was 0.995 (95% CI 0.983–1.006) and the point estimate favoured the experimental treatment in 58% (n = 76) and standard treatment in 42% (n = 54). The median non-inferiority margin (RR) pre-specified by trialists was 1.31 [inter-quartile range (IQR) 1.18–1.59]. Conclusion In this meta-analysis of non-inferiority trials the average RR comparing experimental with standard treatments was close to 1. The experimental treatments that gain a verdict of non-inferiority in published trials do not appear to be systematically less effective than the standard treatments. Importantly, publication bias and bias in the design and reporting of the studies cannot be ruled out and may have skewed the study results in favour of the experimental treatments. Further studies are required to examine the importance of such bias.

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Objectives Posttraumatic stress disorder (PTSD) prospectively increases the risk of incident cardiovascular disease (CVD) independent of other risk factors in otherwise healthy individuals. Between 10% and 20% of patients develop PTSD related to the traumatic experience of myocardial infarction (MI). We investigated the hypothesis that PTSD symptoms caused by MI predict adverse cardiovascular outcome. Methods We studied 297 patients (61 ± 10 years, 83% men) who self-rated PTSD symptoms attributable to a previous index MI. Non-fatal CVD-related hospital readmissions (i.e. recurrent MI, elective and non-elective intracoronary stenting, bypass surgery, pacemaker implantation, cardiac arrhythmia, cerebrovascular event) were assessed at follow-up. Cox proportional hazard models controlled for demographic factors, coronary heart disease severity, major CVD risk factors, cardiac medication, and mental health treatment. Results Forty-three patients (14.5%) experienced an adverse event during a mean follow-up of 2.8 years (range 1.3–3.8). A 10 point higher level in the PTSD symptom score (mean 8.8 ± 9.0, range 0–47) revealed a hazard ratio (HR) of 1.42 (95% CI 1.07–1.88) for a CVD-related hospital readmission in the fully adjusted model. A similarly increased risk (HR 1.45, 95% CI 1.07–1.97) emerged for patients with a major or unscheduled CVD-related readmission (i.e. when excluding patients with elective stenting). Conclusions Elevated levels of PTSD symptoms caused by MI may adversely impact non-fatal cardiovascular outcome in post-MI patients independent of other important prognostic factors. The possible importance of PTSD symptoms as a novel prognostic psychosocial risk factor in post-MI patients warrants further study.

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Umbilical cord blood (UCB) is a source of hematopoietic stem cells that initially was used exclusively for the hematopoietic reconstitution of pediatric patients. It is now suggested for use for adults as well, a fact that increases the pressure to obtain units with high cellularity. Therefore, the optimization of UCB processing is a priority.

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Magnetic resonance spectroscopy enables insight into the chemical composition of spinal cord tissue. However, spinal cord magnetic resonance spectroscopy has rarely been applied in clinical work due to technical challenges, including strong susceptibility changes in the region and the small cord diameter, which distort the lineshape and limit the attainable signal to noise ratio. Hence, extensive signal averaging is required, which increases the likelihood of static magnetic field changes caused by subject motion (respiration, swallowing), cord motion, and scanner-induced frequency drift. To avoid incoherent signal averaging, it would be ideal to perform frequency alignment of individual free induction decays before averaging. Unfortunately, this is not possible due to the low signal to noise ratio of the metabolite peaks. In this article, frequency alignment of individual free induction decays is demonstrated to improve spectral quality by using the high signal to noise ratio water peak from non-water-suppressed proton magnetic resonance spectroscopy via the metabolite cycling technique. Electrocardiography (ECG)-triggered point resolved spectroscopy (PRESS) localization was used for data acquisition with metabolite cycling or water suppression for comparison. A significant improvement in the signal to noise ratio and decrease of the Cramér Rao lower bounds of all metabolites is attained by using metabolite cycling together with frequency alignment, as compared to water-suppressed spectra, in 13 healthy volunteers.

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The posterior circulation Acute Stroke Prognosis Early CT Score (pc-ASPECTS) quantifies the extent of early ischemic changes in the posterior circulation with a 10-point grading system. We hypothesized that pc-ASPECTS applied to CT angiography source images predicts functional outcome of patients in the Basilar Artery International Cooperation Study (BASICS).