Polycyclic aromatic hydrocarbons (PAHs) and some of their nitrated derivatives, NPAHs, are seemingly ubiquitous in the atmospheric environment. Atmospheric lifetimes may nevertheless vary within a wide range, and be as short as a few hours. The sources and sinks of NPAH in the atmosphere are not well understood. With a Lagrangian field experiment and modeling, we studied the conversion of the semivolatile PAHs fluoranthene and pyrene into the 2-nitro derivatives 2-nitrofluoranthene and 2-nitropyrene in a cloud-free marine atmosphere on the time scale of hours to 1 day between a coastal and an island site. Chemistry and transport during several episodes was simulated by a Lagrangian box model i.e., a box model coupled to a Lagrangian particle dispersion model, FLEXPART-WRF. It is found that the chemical kinetic data do capture photochemical degradation of the 4-ring PAHs under ambient conditions on the time scale of hours to 1 day, while the production of the corresponding NPAH, which sustained 2-nitrofluoranthene/fluoranthene and 2-nitropyrene/pyrene yields of (3.7 ± 0.2) and (1.5 ± 0.1)%, respectively, is by far underestimated. Predicted levels of NPAH come close to observed ones, when kinetic data describing the reactivity of the OH-adduct were explored by means of theoretically based estimates. Predictions are also underestimated by 1-2 orders of magnitude, when NPAH/PAH yields reported from laboratory experiments conducted under high NOx conditions are adopted for the simulations. It is concluded that NPAH sources effective under low NOx conditions, are largely underestimated.
Blind deconvolution, which comprises simultaneous blur and image estimations, is a strongly ill-posed problem. It is by now well known that if multiple images of the same scene are acquired, this multichannel (MC) blind deconvolution problem is better posed and allows blur estimation directly from the degraded images. We improve the MC idea by adding robustness to noise and stability in the case of large blurs or if the blur size is vastly overestimated. We formulate blind deconvolution as an l(1) -regularized optimization problem and seek a solution by alternately optimizing with respect to the image and with respect to blurs. Each optimization step is converted to a constrained problem by variable splitting and then is addressed with an augmented Lagrangian method, which permits simple and fast implementation in the Fourier domain. The rapid convergence of the proposed method is illustrated on synthetically blurred data. Applicability is also demonstrated on the deconvolution of real photos taken by a digital camera.
- MeSH
- Algorithms MeSH
- Artifacts MeSH
- Image Interpretation, Computer-Assisted methods MeSH
- Reproducibility of Results MeSH
- Pattern Recognition, Automated methods MeSH
- Sensitivity and Specificity MeSH
- Image Enhancement methods MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Research Support, U.S. Gov't, Non-P.H.S. MeSH
On Zugspitze (2670 m a.s.l.), Alps, higher concentrations were observed during a winter than during a summer measurement campaign of PAHs, chlorobenzenes (43.6 vs. 2.0 pg m(-3)) and DDTs (3.7 vs. 1.2 pg m(-3)), while hexachlorocyclohexanes and PCBs were found at similar levels. The PCB, HCH and DDT levels are among the lowest ever reported from outside the Arctic. Mostly lower levels were found in samples collected in summer than in winter despite a significant boundary layer air influence, but no such influence on samples collected during the winter campaign. Boundary layer influence was quantified by Lagrangian particle dispersion model retroplume analyses. Photochemical lifetimes corresponding to k(OH) < 1.5 x 10(-12) cm(3) molec(-1) s(-1) are found for p,p'-DDT, k(OH) < 0.75 x 10(-12) cm(3) molec(-1) s(-1) for p,p'-DDE and k(OH) < 1.0 x 10(-12) cm(3) molec(-1) s(-1) for p,p'-DDD.
Atrial fibrillation (AF) is a serious heart arrhythmia leading to a significant increase of the risk for occurrence of ischemic stroke. Clinically, the AF episode is recognized in an electrocardiogram. However, detection of asymptomatic AF, which requires a long-term monitoring, is more efficient when based on irregularity of beat-to-beat intervals estimated by the heart rate (HR) features. Automated classification of heartbeats into AF and non-AF by means of the Lagrangian Support Vector Machine has been proposed. The classifier input vector consisted of sixteen features, including four coefficients very sensitive to beat-to-beat heart changes, taken from the fetal heart rate analysis in perinatal medicine. Effectiveness of the proposed classifier has been verified on the MIT-BIH Atrial Fibrillation Database. Designing of the LSVM classifier using very large number of feature vectors requires extreme computational efforts. Therefore, an original approach has been proposed to determine a training set of the smallest possible size that still would guarantee a high quality of AF detection. It enables to obtain satisfactory results using only 1.39% of all heartbeats as the training data. Post-processing stage based on aggregation of classified heartbeats into AF episodes has been applied to provide more reliable information on patient risk. Results obtained during the testing phase showed the sensitivity of 98.94%, positive predictive value of 98.39%, and classification accuracy of 98.86%.
- MeSH
- Algorithms MeSH
- Databases, Factual MeSH
- Diagnosis, Computer-Assisted MeSH
- Electrocardiography methods MeSH
- Atrial Fibrillation diagnosis physiopathology MeSH
- Humans MeSH
- Signal Processing, Computer-Assisted MeSH
- Heart Rate physiology MeSH
- Support Vector Machine MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
The bilinear receptor model positive matrix factorization (PMF) was used to apportion particulate matter with an aerodynamic diameter of 1-10 microm (PM1-10) sources in a village, Brezno, situated in an industrial region of northern Bohemia in Central Europe. The receptor model analyzed the data sets of 90- and 60-min integrations of PM1-10 mass concentrations and elemental composition for 27 elements. The 14-day sampling campaigns were conducted in the village in summer 2008 and winter 2010. Also, to ensure seasonal and regional representativeness of the data sets recorded in the village, the spatial-temporal variability of the 24-hr PM10 and PM1-10 within 2008-2010 in winter and summer across the multiple sites was evaluated. There were statistically significant interseasonal differences of the 24-hr PM data, but not intrasummer or intrawinter differences of the 24-hr PM1-10 data across the multiple sites. PMF resolved seven sources of PM1-10. They were high-temperature coal combustion; combustion in local heating boilers; marine aerosol; mineral dust; primary biological/wood burning; road dust, car brakes; and gypsum. The main summer factors were assigned to mineral dust (38.2%) and primary biological/wood burning (33.1%). In winter, combustion factors dominated (80%) contribution to PM1-10. The conditional probability function (CPF) helped to identified local sources of PM1-10. The source of marine aerosol from the North Sea and English Channel was indicated by the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT).
- MeSH
- Particulate Matter analysis MeSH
- Seasons MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Geographicals
- Czech Republic MeSH
Polychlorinated biphenyls (PCBs) are persistent hazardous chemicals that are still detected in the atmosphere and other environmental media, although their production has been banned for several decades. At the long-term monitoring site, Zeppelin at Spitsbergen, different PCB congeners have been continuously measured for more than a decade. However, it is not clear what factors determine the seasonal and interannual variability of different (lighter versus heavier) PCB congeners. To investigate the influence of atmospheric transport patterns on PCB-28 and PCB-101 concentrations at Zeppelin, we applied the Lagrangian Particle Dispersion Model FLEXPART and calculated "footprints" that indicate the potential source regions of air arriving at Zeppelin. By means of a cluster analysis, we assigned groups of similar footprints to different transport regimes and analyzed the PCB concentrations according to the transport regimes. The concentrations of both PCB congeners are affected by the different transport regimes. For PCB-101, the origin of air masses from the European continent is primarily related to high concentrations; elevated PCB-101 concentrations in winter can be explained by the high frequency of this transport regime in winter, whereas PCB-101 concentrations are low when air is arriving from the oceans. For PCB-28, in contrast, concentrations are high during summer when air is mainly arriving from the oceans but low when air is arriving from the continents. The most likely explanation of this finding is that local emissions of PCB-28 mask the effect of long-range transport and determine the concentrations measured at Zeppelin.
- MeSH
- Atmosphere MeSH
- Air Pollutants * MeSH
- Environmental Monitoring * MeSH
- Oceans and Seas MeSH
- Polychlorinated Biphenyls * MeSH
- Publication type
- Journal Article MeSH
- Geographicals
- Oceans and Seas MeSH
- Svalbard MeSH
Imbalanced datasets are prominent in real-world problems. In such problems, the data samples in one class are significantly higher than in the other classes, even though the other classes might be more important. The standard classification algorithms may classify all the data into the majority class, and this is a significant drawback of most standard learning algorithms, so imbalanced datasets need to be handled carefully. One of the traditional algorithms, twin support vector machines (TSVM), performed well on balanced data classification but poorly on imbalanced datasets classification. In order to improve the TSVM algorithm's classification ability for imbalanced datasets, recently, driven by the universum twin support vector machine (UTSVM), a reduced universum twin support vector machine for class imbalance learning (RUTSVM) was proposed. The dual problem and finding classifiers involve matrix inverse computation, which is one of RUTSVM's key drawbacks. In this paper, we improve the RUTSVM and propose an improved reduced universum twin support vector machine for class imbalance learning (IRUTSVM). We offer alternative Lagrangian functions to tackle the primal problems of RUTSVM in the suggested IRUTSVM approach by inserting one of the terms in the objective function into the constraints. As a result, we obtain new dual formulation for each optimization problem so that we need not compute inverse matrices neither in the training process nor in finding the classifiers. Moreover, the smaller size of the rectangular kernel matrices is used to reduce the computational time. Extensive testing is carried out on a variety of synthetic and real-world imbalanced datasets, and the findings show that the IRUTSVM algorithm outperforms the TSVM, UTSVM, and RUTSVM algorithms in terms of generalization performance.
- MeSH
- Algorithms * MeSH
- Support Vector Machine * MeSH
- Publication type
- Journal Article MeSH
BACKGROUND: Cardiovascular magnetic resonance (CMR) 2D feature tracking (FT) left ventricular (LV) myocardial strain has seen widespread use to characterize myocardial deformation. Yet, validation of CMR FT measurements remains scarce, particularly for regional strain. Therefore, we aimed to perform intervendor comparison of 3 different FT software against tagging. METHODS: In 61 subjects (18 healthy subjects, 18 patients with chronic myocardial infarction, 15 with dilated cardiomyopathy, and 10 with LV hypertrophy due to hypertrophic cardiomyopathy or aortic stenosis) were prospectively compared global (G) and regional transmural peak-systolic Lagrangian longitudinal (LS), circumferential (CS) and radial strains (RS) by 3 FT software (cvi42, Segment, and Tomtec) among each other and with tagging at 3T. We also evaluated the ability of regional LS, CS, and RS by different FT software vs tagging to identify late gadolinium enhancement (LGE) in the 18 infarct patients. RESULTS: GLS and GCS by all 3 software had an excellent agreement among each other (ICC = 0.94-0.98 for GLS and ICC = 0.96-0.98 for GCS respectively) and against tagging (ICC = 0.92-0.94 for GLS and ICC = 0.88-0.91 for GCS respectively), while GRS showed inconsistent agreement between vendors (ICC 0.10-0.81). For regional LS, the agreement was good (ICC = 0.68) between 2 vendors but less vs the 3rd (ICC 0.50-0.59) and moderate to poor (ICC 0.44-0.47) between all three FT software and tagging. Also, for regional CS agreement between 2 software was higher (ICC = 0.80) than against the 3rd (ICC = 0.58-0.60), and both better agreed with tagging (ICC = 0.70-0.72) than the 3rd (ICC = 0.57). Regional RS had more variation in the agreement between methods ranging from good (ICC = 0.75) to poor (ICC = 0.05). Finally, the accuracy of scar detection by regional strains differed among the 3 FT software. While the accuracy of regional LS was similar, CS by one software was less accurate (AUC 0.68) than tagging (AUC 0.80, p < 0.006) and RS less accurate (AUC 0.578) than the other two (AUC 0.76 and 0.73, p < 0.02) to discriminate segments with LGE. CONCLUSIONS: We confirm good agreement of CMR FT and little intervendor difference for GLS and GCS evaluation, with variable agreement for GRS. For regional strain evaluation, intervendor difference was larger, especially for RS, and the diagnostic performance varied more substantially among different vendors for regional strain analysis.
- MeSH
- Ventricular Function, Left MeSH
- Gadolinium MeSH
- Contrast Media * MeSH
- Humans MeSH
- Magnetic Resonance Imaging, Cine * MeSH
- Magnetic Resonance Spectroscopy MeSH
- Predictive Value of Tests MeSH
- Reproducibility of Results MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
