Bioethanol is an attractive renewable energy resource that can be produced from agricultural feed stocks such as sugarcane, corn, sugar beet, wheat, barley and many types of waste biomass materials. It can be used as ...Bioethanol is an attractive renewable energy resource that can be produced from agricultural feed stocks such as sugarcane, corn, sugar beet, wheat, barley and many types of waste biomass materials. It can be used as a transport fuel, mainly as a biofuel additive for gasoline called ＂gasohol＂. In this study the possibility of using ethanol as a gasoline additive from economic, environmental and agricultural point of view in Iran is investigated. Daily gasoline consumption of Iran is about 66 million liters and 340 of this amount is imported. We consider the production of sugarcane-derived ethanol to displace 15% of gasoline use in lran. With existing technology, 450,000 hectares of land, 21 standard distillery and US $3,600 million investment will be required to produce this amount of ethanol. This is just about 60% of the money that currently Iran expends annually for importing about 5.8 million tones of gasoline.展开更多
Globally,economies have become complex and new technologies have transformed and facilitated the modernization of economies.In the previous literature,economic complexity approach has become one of the popular tools i...Globally,economies have become complex and new technologies have transformed and facilitated the modernization of economies.In the previous literature,economic complexity approach has become one of the popular tools in the development and innovation studies of economic geography.Researchers have found that green technology and eco-innovation approaches should be used to decisively reduce the effects of carbon emissions on the environment.However,debates about the impact of economic complexity on environment remain unsettled since some emerging production technologies have far-reaching pollution effects.This study explored the impacts of economic complexity on environmental sustainability in Turkey using the novel Fourier-based approaches,namely:Fourier Augmented Dickey-Fuller(FADF)and Fourier Autoregressive-Distributed Lag(FARDL)models.The Fourier-based approaches indicated that all variables(economic complexity index(ECI),GDP,energy consumption,and CO_(2)emission(CO_(2)E))are cointegrated in the long run.Additionally,the FARDL model implied that(i)in the long run,the effect of ECI(as a proxy for economic complexity),GDP(as a proxy for economic growth),and energy consumption on CO_(2)E(as a proxy for environmental quality)are important;(ii)economic complexity decreases environmental degradation in Turkey;and(iii)economic growth and energy consumption negatively affect environmental quality.The results also showed that economic complexity could be used as a policy tool to tackle environmental degradation.The findings also revealed that the fossil fuelbased economy will continue to expand and undermine Turkey’s efforts to meet its net zero emission target by 2053.Therefore,policy-makers should take actions and establish diversified economic,environmental,and energy strategies.For policy insights,the Turkish governments can use the combination of tax exemptions and technical support systems to support knowledge creation and the diffusion of environmentally friendly technologies The governments can also impose strict environmental regulations on the knowledge development phases.展开更多
This research sheds light on the causal link between commodity price indexes,i.e.,the Agricultural Raw Materials Price Index,Industry Input Price Index,Metal Price Index,and Energy Price Index,in the global market,usi...This research sheds light on the causal link between commodity price indexes,i.e.,the Agricultural Raw Materials Price Index,Industry Input Price Index,Metal Price Index,and Energy Price Index,in the global market,using wavelet coherence,Toda–Yamamoto causality,and gradual shift causality tests over the period 1992M1 to 2019M12.Findings from the wavelet power spectrum and partial wavelet coherence reveal that:(1)there was significant volatility in the Agricultural Raw Materials Price Index,Industry Input Price Index,Metal Price Index,and Energy Price Index between 2004 and 2014 at different frequencies;and(2)commodity price indexes significantly caused the energy price index at different time periods and frequencies.It is noteworthy that the outcomes of the Toda–Yamamoto causality and gradual-shift causality tests are in line with the results of wavelet coherence.展开更多
This paper, using multiple-Hubbert model, forecasts oil production trend of Iran with special focus on Iran＇s insufficient investment for developing recently discovered oilfields and overproduction from mature oilfie...This paper, using multiple-Hubbert model, forecasts oil production trend of Iran with special focus on Iran＇s insufficient investment for developing recently discovered oilfields and overproduction from mature oilfields. This is mostly due to Iran＇s political and technical limitations to carry out oil and gas projects. The trend of Iran＇s oil production has been forecasted based on a multi-cycle modified Hubbert. Three different scenarios have been assumed. In the first scenario, it is assumed that Iran does not have any limitations to carry out oil and gas projects and develop its oilfields. International sanctions and lack of foreign investment have been taken into account in the second scenario. Overproduction from currently producing mature oilfields and its effect on production trend is investigated in the third scenario. The most important parameter to forecast oil production trend is URR （ultimate recoverable resource）. URR of Iran has been estimated by parabolic fractal curve. Here, based on the plotted parabolic fractal curve for the oil fields, amount of URR of Iran has been calculated that is around 200 Gb. First scenario has two peaks while the second and third scenarios have three peaks. All of the scenarios have forecasted Iran＇s first peak in 1975 at annual production rate of 2 Gb/Year. Based on first scenario, Iran＇s second peak will occur in 2029 at 2.334 Gb/Year. Second scenario has forecasted Iran＇s second and third peaks in 2011 at 1.575 Gb/Year and in 2064 at 2.205 Gb/Year respectively, and third scenario＇s peaks have been estimated to occur in 2011 at 1.573 Gb/Year and in 2061 at 2.030 Gb/Year.展开更多
Offshore support operations must balance safety and sustainability under highly variable sea conditions.Deterministic motion analyses can underestimate extreme vessel responses,leading to insufficient operational limi...Offshore support operations must balance safety and sustainability under highly variable sea conditions.Deterministic motion analyses can underestimate extreme vessel responses,leading to insufficient operational limits and increased environmental impact.We develop a fuzzy‐enhanced multi‐body dynamics framework in which key inputs significant wave height,peak period,added mass,and radiation damping are represented as fuzzy numbers.Anα-cut decomposition yields interval bounds at each confidence level,and a fourth-order Runge-Kutta scheme integrates the six-degree-of-freedom equations of motion for both lower and upper“vertex”systems.A case study off the Karnataka coast applies both full 6-DoF and single-DOF heave approximations to demonstrate methodology.The heave response envelopes under calm(nominalα=1:0.73 m;full range atα=0:0.64–1.64 m)and severe(nominal 1.58 m;range 1.32–2.36 m)sea states reveal potential underestimations of 124%and 49%,respectively,when using only nominal values.By selecting an operationalα-level(e.g.,α^(*)=0.35 to cap heave≤1.8 m),decision-makers can balance risk tolerance and conservatism.Sensitivity analysis identifies significant wave height as the dominant uncertainty driver.Computational trade-offs and adaptiveα-sampling strategies are discussed.This work provides a self-contained,uncertainty-aware tool for deriving operational envelopes that improve risk-informed planning and enable fuel-efficiency optimization.By embedding fuzzy uncertainty quantification into vessel dynamics,the methodology supports safer,more sustainable marine operations and can be extended to real-time sensor fusion,multi-vessel interactions,and frequency-dependent hydrodynamics.展开更多
This study addresses the critical need for decarbonization in offshore marine logistics by developing an integrated modeling framework to support low-emission operations across complex,multi-echelon vessel networks.It...This study addresses the critical need for decarbonization in offshore marine logistics by developing an integrated modeling framework to support low-emission operations across complex,multi-echelon vessel networks.It focuses on port-to-platform supply chains serving offshore wind farms,oil rigs,and floating logistics hubs.A hybrid analytical approach was adopted,combining Mixed-Integer Linear Programming(MILP)for optimizing emission-minimizing routing,Discrete-Event Simulation(DES)to evaluate offshore scheduling performance under variability,and a Multi-Criteria Decision Analysis(MCDA)model using AHP-TOPSIS to rank alternative marine fuel types.Monte Carlo simulation was also employed to assess cost and delivery fluctuations across uncertain operational scenarios.Data inputs were compiled from real-world offshore fleet specifications,port emissions records,and marine fuel technology benchmarks.MILP-based network flow optimization reduced CO₂emissions by 22%while maintaining service reliability across all demand points.DES simulations revealed congestion-driven scheduling delays during peak vessel utilization.MCDA analysis ranked bio-LNG and hydrogen propulsion systems as optimal choices based on emission,cost,and availability trade-offs.Hypothesis testing confirmed significant relationships between fuel type,network structure,and emission performance.The study demonstrates how multi-echelon logistics planning,integrated with emissions-based modeling,can facilitate environmentally responsible marine supply chain design.The framework offers practical guidance for offshore fleet managers,port authorities,and policy regulators aiming to align operational efficiency with decarbonization objectives under IMO and EU directives.展开更多
Vessel motions in offshore operations are heavily influenced by uncertain wave loads and hydrodynamic parameters.Yet,traditional deterministic or probabilistic models often fail to capture epistemic ambiguity when dat...Vessel motions in offshore operations are heavily influenced by uncertain wave loads and hydrodynamic parameters.Yet,traditional deterministic or probabilistic models often fail to capture epistemic ambiguity when data are scarce.We introduce a fuzzy–set framework usingα-cut interval analysis to represent imprecise wave heights,periods,added mass,damping,and stiffness as fuzzy numbers.These are incorporated into the multi-body equations of motion and solved via a fuzzy Runge–Kutta scheme across nestedα-levels.A simulation architecture iterates overα-cuts and time-steps to produce interval bounds on heavy responses.A case study off the Karnataka coast,with realistic sea-state data for moderate and severe scenarios,yields heave-amplitude envelopes whose widths quantify response uncertainty.At mid-confidence(α=0.5),moderate seas produce amplitudes of 8.30–9.65 m(±15%),while severe seas yield 7.15–8.90 m(±22%).Envelope narrowing asα→1 confirms that increased parameter confidence reduces prediction spread,and bias analysis against crisp baselines highlights the impact of imprecision on mean responses.This non-probabilistic approach provides interpretable,worst-and best-case motion bounds without requiring large datasets,offering marine engineers robust safety margins and guidance for targeted data collection and real-time uncertainty updating.展开更多
As offshore wind infrastructure becomes more important to global efforts to reduce carbon emissions,it is becoming more important to connect lifecycle cost management with circular economy(CE)principles.When looking a...As offshore wind infrastructure becomes more important to global efforts to reduce carbon emissions,it is becoming more important to connect lifecycle cost management with circular economy(CE)principles.When looking at the long-term costs of infrastructure,traditional lifecycle cost models often fail to account for residual value recovery,material circularity,or environmental externalities.This study creates a unified analytical framework that adds CE strategies to lifecycle cost modelling for offshore wind systems,such as turbines,substructures,moorings,and floating platforms.The method uses multi-objective optimization and system dynamics simulation along with net present value(NPV)modelling,material flow analysis,and carbonadjusted cost accounting.We modelled project-level datasets over 25 years to look at the trade-offs between economic and environmental factors in both linear and circular lifecycle scenarios.We use Python,MATLAB,and OpenLCA to look at key metrics like the Material Circularity Indicator(MCI),estimates of residual value,and internalized carbon costs.The results show that circular infrastructure strategies greatly lower lifecycle costs while also increasing material recovery and carbon efficiency.Scenario simulations showed that CE-based configurations could cut costs by up to 18%and emissions over the life of the product by 22%.Regression and sensitivity analyses showed that MCI,CAPEX,and circular design strategies are good at predicting residual value and long-term economic performance.This study adds a new,evidence-based model for making decisions about infrastructure that takes into account financial,environmental,and material circularity.展开更多
AIM:To determine the relationship of pulmonary abnormalities and bowel disease activity in inflammatory bowel disease(IBD).METHODS:Thirty ulcerative colitis(UC)and nine Crohn's disease patients,and 20 control subj...AIM:To determine the relationship of pulmonary abnormalities and bowel disease activity in inflammatory bowel disease(IBD).METHODS:Thirty ulcerative colitis(UC)and nine Crohn's disease patients,and 20 control subjects were enrolled in this prospective study.Detailed clinical information was obtained.Extent and activity of the bowel disease were established endoscopically.Each patient underwent pulmonary function tests and high-resolution computed tomography(HRCT).Blood samples for measurement of C-reactive protein(CRP),erythrocyte sedimentation rate(ESR),angiotensin converting enzyme and total IgE were delivered by the patients.RESULTS:Ten(25.6%)patients had respiratory symptoms.A pulmonary function abnormality was present in 22 of 39 patients.Among all patients,the most prevalent abnormalities in lung functions were a decrease in forced expiratory volume in 1 s(FEV1),FEV1/forced vital capacity(FVC),forced expiratory flow(FEF)25%-75%,transfer coefficient for carbon monoxide(DLCO),DLCO/alveolar volume.Increased respiratory symptoms score was associated with high endoscopic activity index in UC patients.Endoscopic and clinical activities in UC patients were correlated with FEV1,FEV1/FVC,and FEF 25%-75%.Smoking status,duration of disease and medication were not correlated with pulmonary physiological test results,HRCT abnormalities,clinical/endoscopic disease activity,CRP,ESR or total IgE level or body mass index.CONCLUSION:It is important that respiratory manifestations are recognized and treated early in IBD.Otherwise,they can lead to destructive and irreversible changes in the airway wall.展开更多
This paper addresses the state estimation problem for linear systems with additive uncertainties in both the state and output equations using a moving horizon approach. Based on the full information estimation setting...This paper addresses the state estimation problem for linear systems with additive uncertainties in both the state and output equations using a moving horizon approach. Based on the full information estimation setting and the game-theoretic approach to the H∞filtering, a new optimization-based estimation scheme for uncertain linear systems is proposed, namely the H∞-full information estimator, H∞-FIE in short. In this formulation, the set of processed data grows with time as more measurements are received preventing recursive formulations as in Kalman filtering. To overcome the latter problem, a moving horizon approximation to the H∞-FIE is also presented, the H∞-MHE in short. This moving horizon approximation is achieved since the arrival cost is suitably defined for the proposed scheme. Sufficient conditions for the stability of the H∞-MHE are derived. Simulation results show the benefits of the proposed scheme when compared with two H∞filters and the well-known Kalman filter.展开更多
The prediction performance of traditional forecasting methods is low due to the high level of complexity in a series of energy prices.The present study attempts to compare the traditional regression,machine learning t...The prediction performance of traditional forecasting methods is low due to the high level of complexity in a series of energy prices.The present study attempts to compare the traditional regression,machine learning tools and hybrid models to conclude the outperforming model.The first step is to propose the effective denoising technique for Tadawul energy index,which has confirmed the superiority of CSD based denoising.However,we use the CSD-ARIMA,CSD-ANN,and CSD-RNN as hybrid models.As a result,CSD-RNN outperforms both other models in terms of MSE,MAPE,RMSE and Dstat.The findings are useful for policy makers,investors and portfolio managers to forecast the energy trends,and hedge the portfolio risk accordingly.展开更多
The outcome of patents on environmental(POET)technologies on the EF in the USA has not been com-prehensively explored.Therefore,to close this breach in the literature,the present study discovers how patents on ecologi...The outcome of patents on environmental(POET)technologies on the EF in the USA has not been com-prehensively explored.Therefore,to close this breach in the literature,the present study discovers how patents on ecological technologies affect ecological footprint(EF)in the USA while regulatory for GDP and EC using the Fourier-based approaches.The conclusions of the present study reveal that POET are an important predictor of EF in the USA and cause a reduction in ecological deprivation in the long run;as expected,economic growth negatively affects environmental sustainability.The outcomes suggest that it is possible to resolve conflicts between the economy and the environment by using technological inno-vation.The USA government must reconsider its policy focus,particularly on coal energy sourcing and industrial energy,while continuing with heavy investments in its ambitious renewable energy technol-ogy development plan.Moreover,the government should continue to promote investments in environ-mental technologies.展开更多
文摘Bioethanol is an attractive renewable energy resource that can be produced from agricultural feed stocks such as sugarcane, corn, sugar beet, wheat, barley and many types of waste biomass materials. It can be used as a transport fuel, mainly as a biofuel additive for gasoline called ＂gasohol＂. In this study the possibility of using ethanol as a gasoline additive from economic, environmental and agricultural point of view in Iran is investigated. Daily gasoline consumption of Iran is about 66 million liters and 340 of this amount is imported. We consider the production of sugarcane-derived ethanol to displace 15% of gasoline use in lran. With existing technology, 450,000 hectares of land, 21 standard distillery and US $3,600 million investment will be required to produce this amount of ethanol. This is just about 60% of the money that currently Iran expends annually for importing about 5.8 million tones of gasoline.
文摘Globally,economies have become complex and new technologies have transformed and facilitated the modernization of economies.In the previous literature,economic complexity approach has become one of the popular tools in the development and innovation studies of economic geography.Researchers have found that green technology and eco-innovation approaches should be used to decisively reduce the effects of carbon emissions on the environment.However,debates about the impact of economic complexity on environment remain unsettled since some emerging production technologies have far-reaching pollution effects.This study explored the impacts of economic complexity on environmental sustainability in Turkey using the novel Fourier-based approaches,namely:Fourier Augmented Dickey-Fuller(FADF)and Fourier Autoregressive-Distributed Lag(FARDL)models.The Fourier-based approaches indicated that all variables(economic complexity index(ECI),GDP,energy consumption,and CO_(2)emission(CO_(2)E))are cointegrated in the long run.Additionally,the FARDL model implied that(i)in the long run,the effect of ECI(as a proxy for economic complexity),GDP(as a proxy for economic growth),and energy consumption on CO_(2)E(as a proxy for environmental quality)are important;(ii)economic complexity decreases environmental degradation in Turkey;and(iii)economic growth and energy consumption negatively affect environmental quality.The results also showed that economic complexity could be used as a policy tool to tackle environmental degradation.The findings also revealed that the fossil fuelbased economy will continue to expand and undermine Turkey’s efforts to meet its net zero emission target by 2053.Therefore,policy-makers should take actions and establish diversified economic,environmental,and energy strategies.For policy insights,the Turkish governments can use the combination of tax exemptions and technical support systems to support knowledge creation and the diffusion of environmentally friendly technologies The governments can also impose strict environmental regulations on the knowledge development phases.
文摘This research sheds light on the causal link between commodity price indexes,i.e.,the Agricultural Raw Materials Price Index,Industry Input Price Index,Metal Price Index,and Energy Price Index,in the global market,using wavelet coherence,Toda–Yamamoto causality,and gradual shift causality tests over the period 1992M1 to 2019M12.Findings from the wavelet power spectrum and partial wavelet coherence reveal that:(1)there was significant volatility in the Agricultural Raw Materials Price Index,Industry Input Price Index,Metal Price Index,and Energy Price Index between 2004 and 2014 at different frequencies;and(2)commodity price indexes significantly caused the energy price index at different time periods and frequencies.It is noteworthy that the outcomes of the Toda–Yamamoto causality and gradual-shift causality tests are in line with the results of wavelet coherence.
文摘This paper, using multiple-Hubbert model, forecasts oil production trend of Iran with special focus on Iran＇s insufficient investment for developing recently discovered oilfields and overproduction from mature oilfields. This is mostly due to Iran＇s political and technical limitations to carry out oil and gas projects. The trend of Iran＇s oil production has been forecasted based on a multi-cycle modified Hubbert. Three different scenarios have been assumed. In the first scenario, it is assumed that Iran does not have any limitations to carry out oil and gas projects and develop its oilfields. International sanctions and lack of foreign investment have been taken into account in the second scenario. Overproduction from currently producing mature oilfields and its effect on production trend is investigated in the third scenario. The most important parameter to forecast oil production trend is URR （ultimate recoverable resource）. URR of Iran has been estimated by parabolic fractal curve. Here, based on the plotted parabolic fractal curve for the oil fields, amount of URR of Iran has been calculated that is around 200 Gb. First scenario has two peaks while the second and third scenarios have three peaks. All of the scenarios have forecasted Iran＇s first peak in 1975 at annual production rate of 2 Gb/Year. Based on first scenario, Iran＇s second peak will occur in 2029 at 2.334 Gb/Year. Second scenario has forecasted Iran＇s second and third peaks in 2011 at 1.575 Gb/Year and in 2064 at 2.205 Gb/Year respectively, and third scenario＇s peaks have been estimated to occur in 2011 at 1.573 Gb/Year and in 2061 at 2.030 Gb/Year.
文摘Offshore support operations must balance safety and sustainability under highly variable sea conditions.Deterministic motion analyses can underestimate extreme vessel responses,leading to insufficient operational limits and increased environmental impact.We develop a fuzzy‐enhanced multi‐body dynamics framework in which key inputs significant wave height,peak period,added mass,and radiation damping are represented as fuzzy numbers.Anα-cut decomposition yields interval bounds at each confidence level,and a fourth-order Runge-Kutta scheme integrates the six-degree-of-freedom equations of motion for both lower and upper“vertex”systems.A case study off the Karnataka coast applies both full 6-DoF and single-DOF heave approximations to demonstrate methodology.The heave response envelopes under calm(nominalα=1:0.73 m;full range atα=0:0.64–1.64 m)and severe(nominal 1.58 m;range 1.32–2.36 m)sea states reveal potential underestimations of 124%and 49%,respectively,when using only nominal values.By selecting an operationalα-level(e.g.,α^(*)=0.35 to cap heave≤1.8 m),decision-makers can balance risk tolerance and conservatism.Sensitivity analysis identifies significant wave height as the dominant uncertainty driver.Computational trade-offs and adaptiveα-sampling strategies are discussed.This work provides a self-contained,uncertainty-aware tool for deriving operational envelopes that improve risk-informed planning and enable fuel-efficiency optimization.By embedding fuzzy uncertainty quantification into vessel dynamics,the methodology supports safer,more sustainable marine operations and can be extended to real-time sensor fusion,multi-vessel interactions,and frequency-dependent hydrodynamics.
文摘This study addresses the critical need for decarbonization in offshore marine logistics by developing an integrated modeling framework to support low-emission operations across complex,multi-echelon vessel networks.It focuses on port-to-platform supply chains serving offshore wind farms,oil rigs,and floating logistics hubs.A hybrid analytical approach was adopted,combining Mixed-Integer Linear Programming(MILP)for optimizing emission-minimizing routing,Discrete-Event Simulation(DES)to evaluate offshore scheduling performance under variability,and a Multi-Criteria Decision Analysis(MCDA)model using AHP-TOPSIS to rank alternative marine fuel types.Monte Carlo simulation was also employed to assess cost and delivery fluctuations across uncertain operational scenarios.Data inputs were compiled from real-world offshore fleet specifications,port emissions records,and marine fuel technology benchmarks.MILP-based network flow optimization reduced CO₂emissions by 22%while maintaining service reliability across all demand points.DES simulations revealed congestion-driven scheduling delays during peak vessel utilization.MCDA analysis ranked bio-LNG and hydrogen propulsion systems as optimal choices based on emission,cost,and availability trade-offs.Hypothesis testing confirmed significant relationships between fuel type,network structure,and emission performance.The study demonstrates how multi-echelon logistics planning,integrated with emissions-based modeling,can facilitate environmentally responsible marine supply chain design.The framework offers practical guidance for offshore fleet managers,port authorities,and policy regulators aiming to align operational efficiency with decarbonization objectives under IMO and EU directives.
文摘Vessel motions in offshore operations are heavily influenced by uncertain wave loads and hydrodynamic parameters.Yet,traditional deterministic or probabilistic models often fail to capture epistemic ambiguity when data are scarce.We introduce a fuzzy–set framework usingα-cut interval analysis to represent imprecise wave heights,periods,added mass,damping,and stiffness as fuzzy numbers.These are incorporated into the multi-body equations of motion and solved via a fuzzy Runge–Kutta scheme across nestedα-levels.A simulation architecture iterates overα-cuts and time-steps to produce interval bounds on heavy responses.A case study off the Karnataka coast,with realistic sea-state data for moderate and severe scenarios,yields heave-amplitude envelopes whose widths quantify response uncertainty.At mid-confidence(α=0.5),moderate seas produce amplitudes of 8.30–9.65 m(±15%),while severe seas yield 7.15–8.90 m(±22%).Envelope narrowing asα→1 confirms that increased parameter confidence reduces prediction spread,and bias analysis against crisp baselines highlights the impact of imprecision on mean responses.This non-probabilistic approach provides interpretable,worst-and best-case motion bounds without requiring large datasets,offering marine engineers robust safety margins and guidance for targeted data collection and real-time uncertainty updating.
文摘As offshore wind infrastructure becomes more important to global efforts to reduce carbon emissions,it is becoming more important to connect lifecycle cost management with circular economy(CE)principles.When looking at the long-term costs of infrastructure,traditional lifecycle cost models often fail to account for residual value recovery,material circularity,or environmental externalities.This study creates a unified analytical framework that adds CE strategies to lifecycle cost modelling for offshore wind systems,such as turbines,substructures,moorings,and floating platforms.The method uses multi-objective optimization and system dynamics simulation along with net present value(NPV)modelling,material flow analysis,and carbonadjusted cost accounting.We modelled project-level datasets over 25 years to look at the trade-offs between economic and environmental factors in both linear and circular lifecycle scenarios.We use Python,MATLAB,and OpenLCA to look at key metrics like the Material Circularity Indicator(MCI),estimates of residual value,and internalized carbon costs.The results show that circular infrastructure strategies greatly lower lifecycle costs while also increasing material recovery and carbon efficiency.Scenario simulations showed that CE-based configurations could cut costs by up to 18%and emissions over the life of the product by 22%.Regression and sensitivity analyses showed that MCI,CAPEX,and circular design strategies are good at predicting residual value and long-term economic performance.This study adds a new,evidence-based model for making decisions about infrastructure that takes into account financial,environmental,and material circularity.
文摘AIM:To determine the relationship of pulmonary abnormalities and bowel disease activity in inflammatory bowel disease(IBD).METHODS:Thirty ulcerative colitis(UC)and nine Crohn's disease patients,and 20 control subjects were enrolled in this prospective study.Detailed clinical information was obtained.Extent and activity of the bowel disease were established endoscopically.Each patient underwent pulmonary function tests and high-resolution computed tomography(HRCT).Blood samples for measurement of C-reactive protein(CRP),erythrocyte sedimentation rate(ESR),angiotensin converting enzyme and total IgE were delivered by the patients.RESULTS:Ten(25.6%)patients had respiratory symptoms.A pulmonary function abnormality was present in 22 of 39 patients.Among all patients,the most prevalent abnormalities in lung functions were a decrease in forced expiratory volume in 1 s(FEV1),FEV1/forced vital capacity(FVC),forced expiratory flow(FEF)25%-75%,transfer coefficient for carbon monoxide(DLCO),DLCO/alveolar volume.Increased respiratory symptoms score was associated with high endoscopic activity index in UC patients.Endoscopic and clinical activities in UC patients were correlated with FEV1,FEV1/FVC,and FEF 25%-75%.Smoking status,duration of disease and medication were not correlated with pulmonary physiological test results,HRCT abnormalities,clinical/endoscopic disease activity,CRP,ESR or total IgE level or body mass index.CONCLUSION:It is important that respiratory manifestations are recognized and treated early in IBD.Otherwise,they can lead to destructive and irreversible changes in the airway wall.
基金supported by the European Community s Seventh Framework Programme FP7/2007-2013(No.223854)COLCIENCIAS-Departamento Administrativo de Ciencia,Tecnologíae Innovacin de Colombia
文摘This paper addresses the state estimation problem for linear systems with additive uncertainties in both the state and output equations using a moving horizon approach. Based on the full information estimation setting and the game-theoretic approach to the H∞filtering, a new optimization-based estimation scheme for uncertain linear systems is proposed, namely the H∞-full information estimator, H∞-FIE in short. In this formulation, the set of processed data grows with time as more measurements are received preventing recursive formulations as in Kalman filtering. To overcome the latter problem, a moving horizon approximation to the H∞-FIE is also presented, the H∞-MHE in short. This moving horizon approximation is achieved since the arrival cost is suitably defined for the proposed scheme. Sufficient conditions for the stability of the H∞-MHE are derived. Simulation results show the benefits of the proposed scheme when compared with two H∞filters and the well-known Kalman filter.
基金the Deputyship for Research&Innovation,Ministry of Education in Saudi Arabia for funding this research work through the project number MoF-IFUJ-22-20745-X.
文摘The prediction performance of traditional forecasting methods is low due to the high level of complexity in a series of energy prices.The present study attempts to compare the traditional regression,machine learning tools and hybrid models to conclude the outperforming model.The first step is to propose the effective denoising technique for Tadawul energy index,which has confirmed the superiority of CSD based denoising.However,we use the CSD-ARIMA,CSD-ANN,and CSD-RNN as hybrid models.As a result,CSD-RNN outperforms both other models in terms of MSE,MAPE,RMSE and Dstat.The findings are useful for policy makers,investors and portfolio managers to forecast the energy trends,and hedge the portfolio risk accordingly.
文摘The outcome of patents on environmental(POET)technologies on the EF in the USA has not been com-prehensively explored.Therefore,to close this breach in the literature,the present study discovers how patents on ecological technologies affect ecological footprint(EF)in the USA while regulatory for GDP and EC using the Fourier-based approaches.The conclusions of the present study reveal that POET are an important predictor of EF in the USA and cause a reduction in ecological deprivation in the long run;as expected,economic growth negatively affects environmental sustainability.The outcomes suggest that it is possible to resolve conflicts between the economy and the environment by using technological inno-vation.The USA government must reconsider its policy focus,particularly on coal energy sourcing and industrial energy,while continuing with heavy investments in its ambitious renewable energy technol-ogy development plan.Moreover,the government should continue to promote investments in environ-mental technologies.
