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In this paper, a review of the low-rank factorization method is presented, with emphasis on their application to multiscale problems. Low-rank matrix factorization methods exploit the rankdeficient nature of coupling impedance matrix blocks between two separated groups. They are widely used, because they are purely algebraic and kernel free. To improve the computation precision and efficiency of low-rank based methods, the improved sampling technologies of adaptive cross approximation (ACA), post compression methods, and the nested low-rank factorizations are introduced. O(N) and O (NlogN) computation complexity of the nested equivalence source approximation can be achieved in low and high frequency regime, which is parallel to the multilevel fast multipole algorithm, N is the number of unknowns. Efficient direct solution and high efficiency preconditioning techniques can be achieved with the low-rank factorization matrices. The trade-off between computation efficiency and time are discussed with respect to the number of levels for low-rank factorizations. ; This work was supported in part by the Natural Science Foundation of China under Grant 61871222, Grant 62025109, Grant 61890541, Grant 61931021, and Grant 61721001; and in part by the Spanish Government under Project TEC 2017-83343-C4-2-R and Project MDM-2016-0600. ; Peer Reviewed ; Postprint (published version)

Short-term exposure to air pollution has been associated with ischemic stroke (IS) hospitalizations, but the evidence of its effects on IS in low- and middle-income countries is limited and inconsistent. We aimed to quantitatively estimate the association between air pollution and hospitalizations for IS in Chongqing, China. This time series study included 2,299 inpatients with IS from three hospitals in Chongqing from January 2015 to December 2016. Generalized linear regression models combined with a distributed lag nonlinear model (DLNM) were used to investigate the impact of air pollution on IS hospitalizations. Stratification analysis was further implemented by sex, age, and season. The maximum lag-specific and cumulative percentage changes of IS were 1.2% (95% CI: 0.4–2.1%, lag 3 day) and 3.6% (95% CI: 0.5–6.7%, lag 05 day) for each 10 μg/m(3) increase in PM(2.5); 1.0% (95% CI: 0.3–1.7%, lag 3 day) and 2.9% (95% CI: 0.6–5.2%, lag 05 day) for each 10 μg/m(3) increase in PM(10); 4.8% (95% CI: 0.1–9.7%, lag 4 day) for each 10 μg/m(3) increase in SO(2); 2.5% (95% CI: 0.3–4.7%, lag 3 day) and 8.2% (95% CI: 0.9–16.0%, lag 05 day) for each 10 μg/m3 increase in NO(2); 0.7% (95% CI: 0.0–1.5%, lag 6 day) for each 10 μg/m(3) increase in O(3). No effect modifications were detected for sex, age, and season. Our findings suggest that short-term exposure to PM(2.5), PM(10), SO(2), NO(2), and O(3) contributes to more IS hospitalizations, which warrant the government to take effective actions in addressing air pollution issues.

The effect of gradually replacing the branched alkyl side chains of a diketopyrrolopyrrole (DPP) conjugated polymer by linear side chains containing branched siloxane end groups on the photovoltaic performance of blends of these polymers with a common fullerene acceptor is investigated. With an increasing proportion of siloxane side chains, the molecular weight and solubility of the polymers decreases. While the siloxane containing polymers exhibit a higher hole mobility in field-effect transistors, their performance in solar cells is less than the polymer with only alkyl sides chains. Using grazing-incidence wide-angle X-ray scattering, transmission electron microscopy, and fluorescence spectroscopy we identify two main reasons for the reduced performance of siloxane containing polymers in solar cells. The first one is a somewhat coarser phase-separated morphology with slightly wider polymer fibers. This is unexpected as often the fiber width is inversely correlated with polymer solubility. The second one is stronger non-radiative decay of the pristine polymers containing siloxane side chains. ; G. H. L. Heintges acknowledges the Agency for Innovation by Science and Technology in Flanders (IWT). This project has further received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 747422, from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013)/ERC Grant Agreement No. 339031 and from the Ministry of Education, Culture and Science (Gravity program 024.001.035).