Quantifying energy transition pathways: an integrated framework approach

This thesis provides quantitative insights into energy transition pathways using a framework approach (i.e., IESA), which links bottom-up and top-down energy and economy models, covers the whole demand, supply, infrastructure and trade of energy, has a low entry-barrier, and features advanced capabilities, such as, wide range of flexibility options and hourly temporal resolution, tailored to answer future policy questions. Moreover, the current study shows the implications of model improvements on required data at specific resolutions and how data availability restrains such improvements. Finally, the thesis demonstrates how the higher modeling capabilities and resolutions inform Dutch energy transition scenarios with respect to environmental policies, direction and timing of investments, and its impact on the economy

Designing Stochastic Cell Formation Problem Using Queuing Theory

This paper presents a new nonlinear mathematical model to solve a cell formation problem which assumes that processing time and inter-arrival time of parts are random variables. In this research, cells are defined as a queue system which will be optimized via queuing theory. In this queue system, each machine is assumed as a server and each part as a customer. The grouping of machines and parts are optimized based on the mean waiting time. For solving exactly, the proposed model is linearized. Since the cell formation problem is NP-Hard, two algorithms based on genetic and modified particle swarm optimization (MPSO) algorithms are developed to solve the problem. For generating of initial solutions in these algorithms, a new heuristic method is developed, which always creates feasible solutions. Also, full factorial and Taguchi methods are used to set the crucial parameters in the solutions procedures. Numerical experiments are used to evaluate the performance of the proposed algorithms. The results of the study show that the proposed algorithms are capable of generating better quality solutions in much less time. Finally, a statistical method is used which confirmed that the MPSO algorithm generates higher quality solutions in comparison with the genetic algorithm (GA)

Optimization of green and environmentally-benign synthesis of isoamyl acetate in the presence of ball-milled seashells by response surface methodology

Ball-milled seashells, as a nano-biocomposite catalyst and natural source of CaCO3 in its aragonite microcrystalline form with fixed CO2, was optimized for the synthesis of isoamyl acetate (3-methylbutyl ethanoate) by response surface methodology with a five-level three-factor rotatable circumscribed central composite design. The seashells nano-biocomposite has proved to be an excellent heterogeneous multifunctional catalyst for the green and environmentally-benign synthesis of isoamyl acetate from acetic acid and isoamyl alcohol under solvent-free conditions. A high yield of 91% was obtained under the following optimal conditions: molar ratio of alcohol: acetic acid (1:3.7), catalyst loading (15.7 mg), the reaction temperature (98 °C), and the reaction time (219 min). The outstanding advantages of this protocol are the use of an inexpensive, naturally occurring and easily prepared nano-biocomposite material having appropriate thermal stability and without any modifications using hazardous reagents, lower catalyst loading and reaction temperature, no use of corrosive Bronsted acids as well as toxic azeotropic solvents or water adsorbents, and simplicity of the procedure

Depression, anxiety and quality of life in caregiver spouses of veterans with chronic spinal cord injury

Objective: We were curious about the degree of anxiety and depression and their effect on the quality of life of the caregivers of veterans with spinal cord injury (SCI). Methods: A convenience sample of 72 out of 120 caregiver spouses of veterans with spinal cord injury participated in our study. The Hospital Anxiety and Depression Scale (HADS) were considered as a measure of depression and anxiety. The World Health Organization Quality of Life BREF questionnaire (WHOQOL-BREF) was considered to evaluate the quality of life. To compare the caregivers, we enrolled 74 matched caregiver spouses of patients without spinal cord injury. Results: The average age of the spouses was 44.7±6.5. The average time elapsed from the injury was 26.4±3.1 years. There was a significant difference in all domains of quality of life and depression between the caregivers and the control group, but there was not a significant difference in terms of anxiety. There was a negative correlation between depression and age, level of education and quality of life. Conclusion: Mental care support should be implemented for veterans and their spouses in addition to the provided facilities

Application of Group Method of Data Handling and New Optimization Algorithms for Predicting Sediment Transport Rate under Vegetation Cover

Planting vegetation is one of the practical solutions for reducing sediment transfer rates. Increasing vegetation cover decreases environmental pollution and sediment transport rate (STR). Since sediments and vegetation interact complexly, predicting sediment transport rates is challenging. This study aims to predict sediment transport rate under vegetation cover using new and optimized versions of the group method of data handling (GMDH). Additionally, this study introduces a new ensemble model for predicting sediment transport rates. Model inputs include wave height, wave velocity, density cover, wave force, D50, the height of vegetation cover, and cover stem diameter. A standalone GMDH model and optimized GMDH models, including GMDH honey badger algorithm (HBA) GMDH rat swarm algorithm (RSOA)vGMDH sine cosine algorithm (SCA), and GMDH particle swarm optimization (GMDH-PSO), were used to predict sediment transport rates. As the next step, the outputs of standalone and optimized GMDH were used to construct an ensemble model. The MAE of the ensemble model was 0.145 m3/s, while the MAEs of GMDH-HBA, GMDH-RSOA, GMDH-SCA, GMDH-PSOA, and GMDH in the testing level were 0.176 m3/s, 0.312 m3/s, 0.367 m3/s, 0.498 m3/s, and 0.612 m3/s, respectively. The Nash Sutcliffe coefficient (NSE) of ensemble model, GMDH-HBA, GMDH-RSOA, GMDH-SCA, GMDH-PSOA, and GHMDH were 0.95 0.93, 0.89, 0.86, 0.82, and 0.76, respectively. Additionally, this study demonstrated that vegetation cover decreased sediment transport rate by 90 percent. The results indicated that the ensemble and GMDH-HBA models could accurately predict sediment transport rates. Based on the results of this study, sediment transport rate can be monitored using the IMM and GMDH-HBA. These results are useful for managing and planning water resources in large basins.Comment: 65 pages, 10 figures, 5 table

Effects of systemic administration of HESA-A on the expression of cyclin D1 and EGFR and E-cadherin in the induced tongue dysplasia in rats

Background. HESA-A has herbal and marine bases, containing minerals and rare elements such as Zr, Cr, Ga, Mn, Mg, Ca, Sr, Cu, Ti, etc. Its mechanism of action includes antioxidant, antiinflammatory and adjustment of the immune system. The aim of this study was to evaluate the effects of HESA-A systemic drug on expression of cyclin D1, EGFR and E-cadherin in induced tongue dysplasia in rats. Methods. In this experimental study, the effects of the systemic drug HESA-A on the expression of cyclin D1, EGFR, and E-cadherin molecular markers were examined in induced tongue dysplasia in rats. Results. The incidence rate of cyclin D1 in groups receiving HESA-A was lower than the group that did not receive the drug (77.78% in the 0‒5% range versus 77.78% in the 5‒50% range). In the case of expression of E-cadherin in group D, which did not receive HESA-A, a decrease was observed in the expression of this cell adhesion marker as compared to the other two groups. The incidence of E-cadherin was dependent on HESA-A dose, while with 500 mg/kg it was higher than other groups (>75% in 55.55% versus >75% in 11.11%). Concerning the incidence of EGFR in all the three groups most cases were grade 0. Conclusion. The results of the present research indicated that considering changes in the expression of cyclin D1 and E-cadherin markers in groups treated with HESA-A, HESA-A® has preventive effects on development of cancer in dysplastic lesions through regulation of expression of these molecules

Global, regional, and national burden of colorectal cancer and its risk factors, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Funding: F Carvalho and E Fernandes acknowledge support from Fundação para a Ciência e a Tecnologia, I.P. (FCT), in the scope of the project UIDP/04378/2020 and UIDB/04378/2020 of the Research Unit on Applied Molecular Biosciences UCIBIO and the project LA/P/0140/2020 of the Associate Laboratory Institute for Health and Bioeconomy i4HB; FCT/MCTES through the project UIDB/50006/2020. J Conde acknowledges the European Research Council Starting Grant (ERC-StG-2019-848325). V M Costa acknowledges the grant SFRH/BHD/110001/2015, received by Portuguese national funds through Fundação para a Ciência e Tecnologia (FCT), IP, under the Norma Transitória DL57/2016/CP1334/CT0006.proofepub_ahead_of_prin

Estimates, trends, and drivers of the global burden of type 2 diabetes attributable to PM2.5 air pollution, 1990-2019 : an analysis of data from the Global Burden of Disease Study 2019

Background Experimental and epidemiological studies indicate an association between exposure to particulate matter (PM) air pollution and increased risk of type 2 diabetes. In view of the high and increasing prevalence of diabetes, we aimed to quantify the burden of type 2 diabetes attributable to PM2.5 originating from ambient and household air pollution.Methods We systematically compiled all relevant cohort and case-control studies assessing the effect of exposure to household and ambient fine particulate matter (PM2.5) air pollution on type 2 diabetes incidence and mortality. We derived an exposure-response curve from the extracted relative risk estimates using the MR-BRT (meta-regression-Bayesian, regularised, trimmed) tool. The estimated curve was linked to ambient and household PM2.5 exposures from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019, and estimates of the attributable burden (population attributable fractions and rates per 100 000 population of deaths and disability-adjusted life-years) for 204 countries from 1990 to 2019 were calculated. We also assessed the role of changes in exposure, population size, age, and type 2 diabetes incidence in the observed trend in PM2.5-attributable type 2 diabetes burden. All estimates are presented with 95% uncertainty intervals.Findings In 2019, approximately a fifth of the global burden of type 2 diabetes was attributable to PM2.5 exposure, with an estimated 3.78 (95% uncertainty interval 2.68-4.83) deaths per 100 000 population and 167 (117-223) disability-adjusted life-years (DALYs) per 100 000 population. Approximately 13.4% (9.49-17.5) of deaths and 13.6% (9.73-17.9) of DALYs due to type 2 diabetes were contributed by ambient PM2.5, and 6.50% (4.22-9.53) of deaths and 5.92% (3.81-8.64) of DALYs by household air pollution. High burdens, in terms of numbers as well as rates, were estimated in Asia, sub-Saharan Africa, and South America. Since 1990, the attributable burden has increased by 50%, driven largely by population growth and ageing. Globally, the impact of reductions in household air pollution was largely offset by increased ambient PM2.5.Interpretation Air pollution is a major risk factor for diabetes. We estimated that about a fifth of the global burden of type 2 diabetes is attributable PM2.5 pollution. Air pollution mitigation therefore might have an essential role in reducing the global disease burden resulting from type 2 diabetes. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd.Peer reviewe

Estimates, trends, and drivers of the global burden of type 2 diabetes attributable to PM2.5 air pollution, 1990-2019 : An analysis of data from the Global Burden of Disease Study 2019

Background Experimental and epidemiological studies indicate an association between exposure to particulate matter (PM) air pollution and increased risk of type 2 diabetes. In view of the high and increasing prevalence of diabetes, we aimed to quantify the burden of type 2 diabetes attributable to PM2·5 originating from ambient and household air pollution. Methods We systematically compiled all relevant cohort and case-control studies assessing the effect of exposure to household and ambient fine particulate matter (PM2·5) air pollution on type 2 diabetes incidence and mortality. We derived an exposure–response curve from the extracted relative risk estimates using the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. The estimated curve was linked to ambient and household PM2·5 exposures from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019, and estimates of the attributable burden (population attributable fractions and rates per 100 000 population of deaths and disability-adjusted life-years) for 204 countries from 1990 to 2019 were calculated. We also assessed the role of changes in exposure, population size, age, and type 2 diabetes incidence in the observed trend in PM2·5-attributable type 2 diabetes burden. All estimates are presented with 95% uncertainty intervals. Findings In 2019, approximately a fifth of the global burden of type 2 diabetes was attributable to PM2·5 exposure, with an estimated 3·78 (95% uncertainty interval 2·68–4·83) deaths per 100 000 population and 167 (117–223) disability-adjusted life-years (DALYs) per 100 000 population. Approximately 13·4% (9·49–17·5) of deaths and 13·6% (9·73–17·9) of DALYs due to type 2 diabetes were contributed by ambient PM2·5, and 6·50% (4·22–9·53) of deaths and 5·92% (3·81–8·64) of DALYs by household air pollution. High burdens, in terms of numbers as well as rates, were estimated in Asia, sub-Saharan Africa, and South America. Since 1990, the attributable burden has increased by 50%, driven largely by population growth and ageing. Globally, the impact of reductions in household air pollution was largely offset by increased ambient PM2·5. Interpretation Air pollution is a major risk factor for diabetes. We estimated that about a fifth of the global burden of type 2 diabetes is attributable PM2·5 pollution. Air pollution mitigation therefore might have an essential role in reducing the global disease burden resulting from type 2 diabetes