Uncertainty Quantification of Heavy Gas Release Over a Barrier

In this study a procedure for input uncertainty quantification (UQ) in computational fluid dynamics (CFD) simulations is proposed. The suggested procedure has been applied to a test case. The test case concerns the modeling of a heavy gas release into an atmospheric boundary layer over a barrier. The following uncertain parameters are investigated in their respective intervals: release velocity (18 m/s, 22 m/s), release temperature (270 K, 310 K) and the atmospheric boundary layer velocity (3 m/s, 7 m/s). The Stochastic Collocation (SC) method is used to perform the probabilistic propagation of the uncertain parameters. The uncertainty analysis was performed with two sets of sampling grids (full and sparse grids) for the uncertain parameters. The results show which of the selected uncertain parameters have the largest impact on the dispersed gas plume and the local concentrations in the gas cloud. Additionally, using sparse grids shows potential to reduce the computational effort of the uncertainty analysis

Toward a Decision Support System for Mitigating Urban Heat

With the continuous rise of global urbanization, city planners and policymakers are increasingly concerned with urban heat islands (UHI), which are metropolitan areas that are significantly warmer than their surrounding rural areas. We address the United Nation’s Sustainable Development Goal 11 “Sustainable Cities and Communities,” and we design and develop a decision support system (DSS), which will help city planners and policymakers to overcome economic barriers to reach environmental sustainability goals

A Comparison of Fear of Childbirth and Labor Pain Intensity among Primiparous and Multiparous Women: A Cross-Sectional Study

Background & aim: Fear of Childbirth (FOC) can be seen as an anxiety disorder or as a phobia that women experience in relation to pregnancy and childbirth. We conducted this study to compare the intensity of labor pain with the FOC in multiparous and primiparous women. Methods: This cross-sectional study was conducted using convenience sampling on 432 pregnant women in Babol, Iran, between 2018 and 2019. All pregnant women completed the demographic and FOC questionnaires, as well as labor pain intensity, four times measured using a visual analog scale (VAS). Data were analyzed using SPSS version 16 software and descriptive and analytical indices. Results: FOC in primiparous women was significantly higher than in multiparous mothers (MD: 12.08<0.001, P). The multivariate linear regression test showed that after adjusting the intervening and obstetric variables, in terms of the intensity of pain in the active phase of labor (MD: 0.07; CI 95% -0.32, 0.47; P=0.71) and the expulsion of the fetus (MD: 0.02; CI 95% -0.38, 0.44; P=0.89), there was no statistically significant difference between primiparous and multiparous women. However, a statistically significant difference was found in placental discharge (MD: 0.52; CI 95% 0.01, 1.02; P = 0.043). Conclusion: FOC in primiparous women was significantly higher than that of multiparous women after adjusting the intervening variables. The results of this study provide basic information for policy makers to pay more attention to reducing the fear of childbirth, especially in primiparous women

Sensitivity of simulated regional Arctic climate to the choice of coupled model domain

The climate over the Arctic has undergone changes in recent decades. In order to evaluate the coupled response of the Arctic system to external and internal forcing, our study focuses on the estimation of regional climate variability and its dependence on large-scale atmospheric and regional ocean circulations. A global ocean–sea ice model with regionally high horizontal resolution is coupled to an atmospheric regional model and global terrestrial hydrology model. This way of coupling divides the global ocean model setup into two different domains: one coupled, where the ocean and the atmosphere are interacting, and one uncoupled, where the ocean model is driven by prescribed atmospheric forcing and runs in a so-called stand-alone mode. Therefore, selecting a specific area for the regional atmosphere implies that the ocean–atmosphere system can develop ‘freely’ in that area, whereas for the rest of the global ocean, the circulation is driven by prescribed atmospheric forcing without any feedbacks. Five different coupled setups are chosen for ensemble simulations. The choice of the coupled domains was done to estimate the influences of the Subtropical Atlantic, Eurasian and North Pacific regions on northern North Atlantic and Arctic climate. Our simulations show that the regional coupled ocean–atmosphere model is sensitive to the choice of the modelled area. The different model configurations reproduce differently both the mean climate and its variability. Only two out of five model setups were able to reproduce the Arctic climate as observed under recent climate conditions (ERA-40 Reanalysis). Evidence is found that the main source of uncertainty for Arctic climate variability and its predictability is the North Pacific. The prescription of North Pacific conditions in the regional model leads to significant correlation with observations, even if the whole North Atlantic is within the coupled model domain. However, the inclusion of the North Pacific area into the coupled system drastically changes the Arctic climate variability to a point where the Arctic Oscillation becomes an ‘internal mode’ of variability and correlations of year-to-year variability with observational data vanish. In line with previous studies, our simulations provide evidence that Arctic sea ice export is mainly due to ‘internal variability’ within the Arctic region. We conclude that the choice of model domains should be based on physical knowledge of the atmospheric and oceanic processes and not on ‘geographic’ reasons. This is particularly the case for areas like the Arctic, which has very complex feedbacks between components of the regional climate system

CCR2-V64I polymorphism is associated with increased risk of cervical cancer but not with HPV infection or pre-cancerous lesions in African women

<p>Abstract</p> <p>Background</p> <p>Cervical cancer, caused by specific oncogenic types of human papillomavirus (HPV), is the second most common cancer in women worldwide. A large number of young sexually active women get infected by HPV but only a small fraction of them have persistent infection and develop cervical cancer pointing to co- factors including host genetics that might play a role in outcome of the HPV infection. This study investigated the role of <it>CCR2-V64I </it>polymorphism in cervical cancer, pre-cancers and HPV infection in South African women resident in Western Cape. <it>CCR2-V64I </it>polymorphism has been previously reported to influence the progression to cervical cancer in some populations and has also been associated with decreased progression from HIV infection to AIDS.</p> <p>Methods</p> <p>Genotyping for <it>CCR2-V64I </it>was done by PCR-SSP in a case-control study of 446 women (106 black African and 340 mixed-ancestry) with histologically confirmed invasive cervical cancer and 1432 controls (322 black African and 1110 mixed-ancestry) group-matched (1:3) by age, ethnicity and domicile status. In the control women HPV was detected using the Digene Hybrid Capture II test and cervical disease was detected by cervical cytology.</p> <p>Results</p> <p>The <it>CCR2-64I </it>variant was significantly associated with cervical cancer when cases were compared to the control group (P = 0.001). Further analysis comparing selected groups within the controls showed that individuals with abnormal cytology and high grade squamous intraepitleial neoplasia (HSIL) did not have this association when compared to women with normal cytology. HPV infection also showed no association with <it>CCR2-64I </it>variant. Comparing SIL positive controls with the cases showed a significant association of <it>CCR2-64I </it>variant (P = 0.001) with cervical cancer.</p> <p>Conclusions</p> <p>This is the first study of the role of <it>CCR2-V64I </it>polymorphism in cervical cancer in an African population. Our results show that <it>CCR2-64I </it>variant is associated with the risk of cervical cancer but does not affect the susceptibility to HPV infection or HSIL in South African women of black and mixed-ancestry origin. This result implies that the role of CCR2 is important in invasive cancer of the cervix but not in HPV infection or in the development of pre-cancers.</p

Using Weighted Goal Programming Model for Planning Regional Sustainable Development to Optimal Workforce Allocation:An Application for Provinces of Iran

Due to the urbanization and economic growth, planning of regional sustainable development has become one of the major challenges in the world. The key indicators such as gross domestic product (GDP), electricity and energy consumption and greenhouse gas emission (GHG) are considered in sustainable development planning. This paper determines number of required workforce in diferent sectors of each province in Iran considering targets/goals for sustainable development indicators in the 2030 macroeconomic and regional planning. First, the relative goals are designed for GDP, electricity, energy and GHG emission and then, two weighted goal programming models are applied to allocate the optimal workforce among four sectors: agriculture, industry, services and transportation. The frst model minimizes recruitment of new workforce and allows current workforce exchange among the four sectors in each province in order to achieve the goals, while the second model indicates equitable distribution of new workforce recruitment in diferent sectors within each province. In both models, the workforce changes have been investigated based on achieving the desirable growth rates of GDP, GHG, electricity and energy consumption as planned by the government. Based on the results of this paper, policy makers can manage workforce and the government can make optimized decisions to macroeconomic and regional planning