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Closing the gap towards super-long suspension bridges using computational morphogenesis.

ABSTRACT: Girder design for suspension bridges has remained largely unchanged for the past 60 years. However, for future super-long bridges, aiming at record-breaking spans beyond 3?km, the girder weight is a limiting factor. Here we report on a design concept, inspired by computational morphogenesis procedures, demonstrating possible weight savings in excess of 28 percent while maintaining manufacturability. Although morphogenesis procedures are rarely used in civil engineering, often due to complicated designs, we demonstrate that even a crude extraction of the main features of the optimized design, followed by a simple parametric optimization, results in hitherto unseen weight reductions. We expect that further studies of the proposed design, as well as applications to other structures, will lead to even greater weight savings and reductions in carbon footprint in a construction industry, currently responsible for 39 percent of the world's CO2 emissions.

SUBMITTER: Baandrup M

PROVIDER: S-EPMC7264174 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Closing the gap towards super-long suspension bridges using computational morphogenesis.

Baandrup Mads M Sigmund Ole O Polk Henrik H Aage Niels N

Nature communications 20200601 1

Girder design for suspension bridges has remained largely unchanged for the past 60 years. However, for future super-long bridges, aiming at record-breaking spans beyond 3 km, the girder weight is a limiting factor. Here we report on a design concept, inspired by computational morphogenesis procedures, demonstrating possible weight savings in excess of 28 percent while maintaining manufacturability. Although morphogenesis procedures are rarely used in civil engineering, often due to complicated ...[more]

PMID: 32483204

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Project description:Background The rising economic burden of cancer on patients is an important determinant of access to treatment initiation and adherence in India. Several publicly financed health insurance (PFHI) schemes have been launched in India, with treatment for cancer as an explicit inclusion in the health benefit packages (HBPs). Although, financial toxicity is widely acknowledged to be a potential consequence of costly cancer treatment, little is known about its prevalence and determinants among the Indian population. There is a need to determine the optimal strategy for clinicians and cancer care centers to address the issue of high costs of care in order to minimize the financial toxicity, promote access to high value care and reduce health disparities. Methods A total of 12,148 cancer patients were recruited at seven purposively selected cancer centres in India, to assess the out-of-pocket expenditure (OOPE) and financial toxicity among cancer patients. Mean OOPE incurred for outpatient treatment and hospitalization, was estimated by cancer site, stage, type of treatment and socio-demographic characteristics. Economic impact of cancer care on household financial risk protection was assessed using standard indicators of catastrophic health expenditures (CHE) and impoverishment, along with the determinants using logistic regression. Results Mean direct OOPE per outpatient consultation and per episode of hospitalization was estimated as ₹8,053 (US$ 101) and ₹39,085 (US$ 492) respectively. Per patient annual direct OOPE incurred on cancer treatment was estimated as ₹331,177 (US$ 4,171). Diagnostics (36.4%) and medicines (45%) are major contributors of OOPE for outpatient treatment and hospitalization, respectively. The overall prevalence of CHE and impoverishment was higher among patients seeking outpatient treatment (80.4% and 67%, respectively) than hospitalization (29.8% and 17.2%, respectively). The odds of incurring CHE was 7.4 times higher among poorer patients [Adjusted Odds Ratio (AOR): 7.414] than richest. Enrolment in PM-JAY (CHE AOR = 0.426, and impoverishment AOR = 0.395) or a state sponsored scheme (CHE AOR = 0.304 and impoverishment AOR = 0.371) resulted in a significant reduction in CHE and impoverishment for an episode of hospitalization. The prevalence of CHE and impoverishment was significantly higher with hospitalization in private hospitals and longer duration of hospital stay (p < 0.001). The extent of CHE and impoverishment due to direct costs incurred on outpatient treatment increased from 83% to 99.7% and, 63.9% to 97.1% after considering both direct and indirect costs borne by the patient and caregivers, respectively. In case of hospitalization, the extent of CHE increased from 23.6% (direct cost) to 59.4% (direct+ indirect costs) and impoverishment increased from 14.1% (direct cost) to 27% due to both direct and indirect cost of cancer treatment. Conclusion There is high economic burden on patients and their families due to cancer treatment. The increase in population and cancer services coverage of PFHI schemes, creating prepayment mechanisms like E-RUPI for outpatient diagnostic and staging services, and strengthening public hospitals can potentially reduce the financial burden among cancer patients in India. The disaggregated OOPE estimates could be useful input for future health technology analyses to determine cost-effective treatment strategies.

Project description:Total-evidence dating (TED) allows evolutionary biologists to incorporate a wide range of dating information into a unified statistical analysis. One might expect this to improve the agreement between rocks and clocks but this is not necessarily the case. We explore the reasons for such discordance using a mammalian dataset with rich molecular, morphological and fossil information. There is strong conflict in this dataset between morphology and molecules under standard stochastic models. This causes TED to push divergence events back in time when using inadequate models or vague priors, a phenomenon we term 'deep root attraction' (DRA). We identify several causes of DRA. Failure to account for diversified sampling results in dramatic DRA, but this can be addressed using existing techniques. Inadequate morphological models also appear to be a major contributor to DRA. The major reason seems to be that current models do not account for dependencies among morphological characters, causing distorted topology and branch length estimates. This is particularly problematic for huge morphological datasets, which may contain large numbers of correlated characters. Finally, diversification and fossil sampling priors that do not incorporate all the available background information can contribute to DRA, but these priors can also be used to compensate for DRA. Specifically, we show that DRA in the mammalian dataset can be addressed by introducing a modest extra penalty for ghost lineages that are unobserved in the fossil record, for instance by assuming rapid diversification, rare extinction or high fossil sampling rate; any of these assumptions produces highly congruent divergence time estimates with a minimal gap between rocks and clocks. Under these conditions, fossils have a stabilizing influence on divergence time estimates and significantly increase the precision of those estimates, which are generally close to the dates suggested by palaeontologists.This article is part of the themed issue 'Dating species divergences using rocks and clocks'.

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Closing the gap towards super-long suspension bridges using computational morphogenesis.

Publications

Closing the gap towards super-long suspension bridges using computational morphogenesis.

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