Quanto options allow the buyer to exchange the foreign currency payoff into the domestic currency at a fixed exchange rate. We investigate quanto options with multiple underlying assets valued in different foreign cur...Quanto options allow the buyer to exchange the foreign currency payoff into the domestic currency at a fixed exchange rate. We investigate quanto options with multiple underlying assets valued in different foreign currencies each with a different strike price in the payoff function. We carry out a comparative performance analysis of different stochastic volatility (SV), stochastic correlation (SC), and stochastic exchange rate (SER) models to determine the best combination of these models for Monte Carlo (MC) simulation pricing. In addition, we test the performance of all model variants with constant correlation as a benchmark. We find that a combination of GARCH-Jump SV, Weibull SC, and Ornstein Uhlenbeck (OU) SER performs best. In addition, we analyze different discretization schemes and their results. In our simulations, the Milstein scheme yields the best balance between execution times and lower standard deviations of price estimates. Furthermore, we find that incorporating mean reversion into stochastic correlation and stochastic FX rate modeling is beneficial for MC simulation pricing. We improve the accuracy of our simulations by implementing antithetic variates variance reduction. Finally, we derive the correlation risk parameters Cora and Gora in our framework so that correlation hedging of quanto options can be performed.展开更多
In this paper,we incorporate Markov regime-switching into a two-factor stochastic volatility jump-diffusion model to enhance the pricing of power options.Furthermore,we assume that the interest rates and the jump inte...In this paper,we incorporate Markov regime-switching into a two-factor stochastic volatility jump-diffusion model to enhance the pricing of power options.Furthermore,we assume that the interest rates and the jump intensities of the assets are stochastic.Under the proposed framework,first,we derive the analytical pricing formula for power options by using Fourier transform technique,Esscher transform and characteristic function.Then we provide the efficient approximation to calculate the analytical pricing formula of power options by using the FFT approach and examine the accuracy of the approximation by Monte Carlo simulation.Finally,we provide some sensitivity analysis of the model parameters to power options.Numerical examples show this model is suitable for empirical work in practice.展开更多
This paper employs the PPO(Proximal Policy Optimization) algorithm to study the risk hedging problem of the Shanghai Stock Exchange(SSE) 50ETF options. First, the action and state spaces were designed based on the cha...This paper employs the PPO(Proximal Policy Optimization) algorithm to study the risk hedging problem of the Shanghai Stock Exchange(SSE) 50ETF options. First, the action and state spaces were designed based on the characteristics of the hedging task, and a reward function was developed according to the cost function of the options. Second, combining the concept of curriculum learning, the agent was guided to adopt a simulated-to-real learning approach for dynamic hedging tasks, reducing the learning difficulty and addressing the issue of insufficient option data. A dynamic hedging strategy for 50ETF options was constructed. Finally, numerical experiments demonstrate the superiority of the designed algorithm over traditional hedging strategies in terms of hedging effectiveness.展开更多
From AR-enhanced picture books to eco-friendly smart toys,the items now filling children’s shopping carts are more than just products-they epitomize the transformation of consumption in the new era.
In this paper,we consider the price of catastrophe options with credit risk in a regime-switching model.We assume that the macroeconomic states are described by a continuous-time Markov chain with a finite state space...In this paper,we consider the price of catastrophe options with credit risk in a regime-switching model.We assume that the macroeconomic states are described by a continuous-time Markov chain with a finite state space.By using the measure change technique,we derive the price expressions of catastrophe put options.Moreover,we conduct some numerical analysis to demonstrate how the parameters of the model affect the price of the catastrophe put option.展开更多
Spatio-temporal variability and dynamics in Sahelian agro-pastoral zones make each local situation a special case. These specificities must be considered to guide the dissemination of agricultural options with a view ...Spatio-temporal variability and dynamics in Sahelian agro-pastoral zones make each local situation a special case. These specificities must be considered to guide the dissemination of agricultural options with a view to sustainable development. The territorial scale of municipalities is not sufficient for this necessary contextualization;the scale of the “village terroir” seems to be a better option. This is the hypothesis we put forward in the framework of the Global Collaboration for Resilient Food Systems program (CRFS), i.e. local context is spatially defined by village terroir. The study is based on data collected through participatory mapping and surveys in “village terroirs” in three regions of Niger (Maradi, Dosso and Tillabéri). Then the links between farm managers and their cultivated land, as well as the spatio-temporal dynamics of local context are analyzed. This study provides evidence of the existence and functional usefulness of the village terroir for farmers, their land management and their activities. It demonstrates the usefulness of contextualizing agricultural options at this scale. Their analysis elucidates the links between “terroirs village” and the specific functioning of the agrosocio-ecosystems acting on each of them, thus laying the systemic and geographical foundations for a model of the spatio- temporal dynamics of “village terroirs”. This initial work has opened up new perspectives in modeling and sustainable development.展开更多
Venture capital investments are characterized by high input,high yield,and high risk.Due to the complexity of the market environment,stage-by-stage investment is becoming increasingly important.Traditional evaluation ...Venture capital investments are characterized by high input,high yield,and high risk.Due to the complexity of the market environment,stage-by-stage investment is becoming increasingly important.Traditional evaluation methods like comparison,proportion,maturity,internal rate of return,scenario analysis,decision trees,and net present value cannot fully consider the uncertainty and stage characteristics of the project.The fuzzy real options method addresses this by combining real option theory,fuzzy number theory,and composite option theory to provide a more accurate and objective evaluation of Public-Private Partnership(PPP)projects.It effectively considers the interaction of options and the ambiguity of project parameters,making it a valuable tool for project evaluation in the context of venture capital investment.展开更多
In the FinTech era,we contribute to the literature by studying the pricing of Bitcoin options,which is timely and important given that both Nasdaq and the CME Group have started to launch a variety of Bitcoin derivati...In the FinTech era,we contribute to the literature by studying the pricing of Bitcoin options,which is timely and important given that both Nasdaq and the CME Group have started to launch a variety of Bitcoin derivatives.We find pricing errors in the presence of market smiles in Bitcoin options,especially for short-maturity ones.Long-maturity options display more of a“smirk”than a smile.Additionally,the ARJI-EGARCH model provides a better overall fit for the pricing of Bitcoin options than the other ARJI-GARCH type models.We also demonstrate that the ARJI-GARCH model can provide more precise pricing of Bitcoin and its options than the SVCJ model in term of the goodness-of-fit in forecasting.Allowing for jumps is crucial for modeling Bitcoin options as we find evidence of time-varying jumps.Our empirical results demonstrate that the realized jump variation can describe the volatility behavior and capture the jump risk dynamics in Bitcoin and its options.展开更多
We derive methods for risk-neutral pricing of multi-asset options,when log-returns jointly follow a multivariate tempered stable distribution.These lead to processes that are more realistic than the better known Brown...We derive methods for risk-neutral pricing of multi-asset options,when log-returns jointly follow a multivariate tempered stable distribution.These lead to processes that are more realistic than the better known Brownian motion and stable processes.Further,we introduce the diagonal tempered stable model,which is parsimonious but allows for rich dependence between assets.Here,the number of parameters only grows linearly as the dimension increases,which makes it tractable in higher dimensions and avoids the so-called“curse of dimensionality.”As an illustration,we apply the model to price multi-asset options in two,three,and four dimensions.Detailed goodness-of-fit methods show that our model fits the data very well.展开更多
Modeling implied volatility(IV)is important for option pricing,hedging,and risk management.Previous studies of deterministic implied volatility functions(DIVFs)propose two parameters,moneyness and time to maturity,to ...Modeling implied volatility(IV)is important for option pricing,hedging,and risk management.Previous studies of deterministic implied volatility functions(DIVFs)propose two parameters,moneyness and time to maturity,to estimate implied volatility.Recent DIVF models have included factors such as a moving average ratio and relative bid-ask spread but fail to enhance modeling accuracy.The current study offers a generalized DIVF model by including a momentum indicator for the underlying asset using a relative strength index(RSI)covering multiple time resolutions as a factor,as momentum is often used by investors and speculators in their trading decisions,and in contrast to volatility,RSI can distinguish between bull and bear markets.To the best of our knowledge,prior studies have not included RSI as a predictive factor in modeling IV.Instead of using a simple linear regression as in previous studies,we use a machine learning regression algorithm,namely random forest,to model a nonlinear IV.Previous studies apply DVIF modeling to options on traditional financial assets,such as stock and foreign exchange markets.Here,we study options on the largest cryptocurrency,Bitcoin,which poses greater modeling challenges due to its extreme volatility and the fact that it is not as well studied as traditional financial assets.Recent Bitcoin option chain data were collected from a leading cryptocurrency option exchange over a four-month period for model development and validation.Our dataset includes short-maturity options with expiry in less than six days,as well as a full range of moneyness,both of which are often excluded in existing studies as prices for options with these characteristics are often highly volatile and pose challenges to model building.Our in-sample and out-sample results indicate that including our proposed momentum indicator significantly enhances the model’s accuracy in pricing options.The nonlinear machine learning random forest algorithm also performed better than a simple linear regression.Compared to prevailing option pricing models that employ stochastic variables,our DIVF model does not include stochastic factors but exhibits reasonably good performance.It is also easy to compute due to the availability of real-time RSIs.Our findings indicate our enhanced DIVF model offers significant improvements and may be an excellent alternative to existing option pricing models that are primarily stochastic in nature.展开更多
The aim of this paper is to price power option with its underlying asset price following exponential normal inverse gaussian(NIG)process.We first find the risk neutral equivalent martingale measure Q by Esscher transf...The aim of this paper is to price power option with its underlying asset price following exponential normal inverse gaussian(NIG)process.We first find the risk neutral equivalent martingale measure Q by Esscher transform.Then,using the Fourier transform and its inverse,we derive the analytical pricing formulas of power options which are expressed in the form of Fourier integral.In addition,the fast Fourier transform(FFT)algorithm is applied to calculate these pricing formulas.Finally,Shangzheng 50ETF options are chosen to test our results.Estimating the parameters in NIG process by maximum likelihood method,we show that the NIG prices are much closer to market prices than the Black-Scholes-Merton(BSM)ones.展开更多
Alcoholic liver disease(ALD)and non-alcoholic fatty liver disease(NAFLD)are serious health problems worldwide.These two diseases have similar pathological spectra,ranging from simple steatosis to hepatitis to cirrhosi...Alcoholic liver disease(ALD)and non-alcoholic fatty liver disease(NAFLD)are serious health problems worldwide.These two diseases have similar pathological spectra,ranging from simple steatosis to hepatitis to cirrhosis and hepatocellular carcinoma.Although most people with excessive alcohol or calorie intake display abnormal fat accumulation in the liver(simple steatosis),a small percentage develops progressive liver disease.Despite extensive research on understanding the pathophysiology of both these diseases there are still no targeted therapies available.The treatment for ALD remains as it was 50 years ago:abstinence,nutritional support and corticosteroids(or pentoxifylline as an alternative if steroids are contraindicated).As for NAFLD,the treatment modality is mainly directed toward weight loss and co-morbidity management.Therefore,new pathophysiology directed therapies are urgently needed.However,the involvement of several inter-related pathways in the pathogenesis of these diseases suggests that a single therapeutic agent is unlikely to be an effective treatment strategy.Hence,a combination therapy towards multiple targets would eventually be required.In this review,we delineate the treatment options in ALD and NAFLD,including various new targeted therapies that are currently under investigation.We hope that soon we will be having an effective multi-therapeutic regimen for each disease.展开更多
An experimental study on mitigation of greenhouse gas (CH4, N2O and NO) emission has been conducted in a typical cropping system of Southeast China for 4 years. By simultaneous measurement, the CH4, N2O and NO emissio...An experimental study on mitigation of greenhouse gas (CH4, N2O and NO) emission has been conducted in a typical cropping system of Southeast China for 4 years. By simultaneous measurement, the CH4, N2O and NO emission fluxes from rice-wheat rotation fields, effects of fertilization, water management, temperature and soil moisture were investigated. Temperature, fertilization and water status were found to be the key factors to regulate CH4, N2O and NO emis-sions. Based on the experimental results, some agricultural measures were recommended as techni-cal options to mitigate greenhouse gas emissions from rice-wheat rotation ecosystems. These miti-gation measures are reducing mineral N input, coupling organic manure with chemical fertilizers, applying fertilizers which release available N slowly during periods with intensive plant activity, and applying dry fermented organic manure and well management of water and fertilizer. Key words Mitigation options - Emission - Greenhouse gases - Ecosystems This study was supported by projects “ Experimental and Modeling Study on N2O Emission from the Rice-Wheat Rotation Fields of Southeast China” and “ Experimental and Modeling Study on NO Emission from Croplands” , which were granted by the National Natural Science Foundation of China, the State Key Fundamental Research Project “ Predicting the Future (20–50 years) Trend of Environmental Change in China”, and the project of Chinese Academy of Sciences “ Theory and Methodology on Air Pollution Prediction”.Thanks are due to Professor Zhang Wen, Dr. Bai Jianhui, Mr. Gong Yanbang, Mrs. Luo Dongmei and Mr. Liu Guangren from the Institute of Atmospheric Physics, Chinese Academy of Sciences for their help in experiments.展开更多
It is believed that the global CO2 emissions have to begin dropping in the near fu- ture to limit the temperature increase within 2 degrees by 2100. So it is of great concern to environmentalists and national decision...It is believed that the global CO2 emissions have to begin dropping in the near fu- ture to limit the temperature increase within 2 degrees by 2100. So it is of great concern to environmentalists and national decision-makers to know how the global or national CO2 emissions would trend. This paper presented an approach to project the future CO2 emissions from the perspective of optimal economic growth, and applied this model to the cases of China and the United States, whose CO2 emissions together contributed to more than 40% of the global emissions. The projection results under the balanced and optimal economic growth path reveal that the CO2 emissions will peak in 2029 for China and 2024 for the USA owing to their empirically implied pace of energy efficiency improvement. Moreover, some abatement options are analyzed for China, which indicate that 1） putting up the energy price will de- crease the emissions at a high cost; 2） enhancing the decline rate of energy intensity can significantly mitigate the emissions with a modest cost; and 3） the energy substitution policy of replacing carbon intensive energies with clean ones has considerable potential to alleviate emissions without compromising the economic development.展开更多
Ameliorating waste treatment by technological improvements affects the economic and the ecological-environment benefits of intensive pig production. The objective of the research was to develop and test a method to de...Ameliorating waste treatment by technological improvements affects the economic and the ecological-environment benefits of intensive pig production. The objective of the research was to develop and test a method to determine the technical optimization to ameliorate waste treatment methods and gain insight into the relationship between technological options and the economic and ecological effects. We developed an integrated bio-economic model which incorporates the farming production and waste disposal systems to simulate the impact of technological improvements in pig manure treatment on economic and environmental benefits for the case of a pilot farm in Beijing, China. Based on different waste treatment technology options, three scenarios are applied for the simulation analysis of the model. The simulation results reveal that the economic-environmental benefits of the livestock farm could be improved by reducing the cropland manure application and increasing the composting production with the current technologies. Nevertheless, the technical efficiency, the waste treatment capacity and the economic benefits could be further improved by the introduction of new technologies. It implies that technological and economic support policies should be implemented comprehensively on waste disposal and resource utilization to promote sustainable development in intensive livestock production in China.展开更多
文摘Quanto options allow the buyer to exchange the foreign currency payoff into the domestic currency at a fixed exchange rate. We investigate quanto options with multiple underlying assets valued in different foreign currencies each with a different strike price in the payoff function. We carry out a comparative performance analysis of different stochastic volatility (SV), stochastic correlation (SC), and stochastic exchange rate (SER) models to determine the best combination of these models for Monte Carlo (MC) simulation pricing. In addition, we test the performance of all model variants with constant correlation as a benchmark. We find that a combination of GARCH-Jump SV, Weibull SC, and Ornstein Uhlenbeck (OU) SER performs best. In addition, we analyze different discretization schemes and their results. In our simulations, the Milstein scheme yields the best balance between execution times and lower standard deviations of price estimates. Furthermore, we find that incorporating mean reversion into stochastic correlation and stochastic FX rate modeling is beneficial for MC simulation pricing. We improve the accuracy of our simulations by implementing antithetic variates variance reduction. Finally, we derive the correlation risk parameters Cora and Gora in our framework so that correlation hedging of quanto options can be performed.
文摘In this paper,we incorporate Markov regime-switching into a two-factor stochastic volatility jump-diffusion model to enhance the pricing of power options.Furthermore,we assume that the interest rates and the jump intensities of the assets are stochastic.Under the proposed framework,first,we derive the analytical pricing formula for power options by using Fourier transform technique,Esscher transform and characteristic function.Then we provide the efficient approximation to calculate the analytical pricing formula of power options by using the FFT approach and examine the accuracy of the approximation by Monte Carlo simulation.Finally,we provide some sensitivity analysis of the model parameters to power options.Numerical examples show this model is suitable for empirical work in practice.
基金supported by the Foundation of Key Laboratory of System Control and Information Processing,Ministry of Education,China,Scip20240111Aeronautical Science Foundation of China,Grant 2024Z071108001the Foundation of Key Laboratory of Traffic Information and Safety of Anhui Higher Education Institutes,Anhui Sanlian University,KLAHEI18018.
文摘This paper employs the PPO(Proximal Policy Optimization) algorithm to study the risk hedging problem of the Shanghai Stock Exchange(SSE) 50ETF options. First, the action and state spaces were designed based on the characteristics of the hedging task, and a reward function was developed according to the cost function of the options. Second, combining the concept of curriculum learning, the agent was guided to adopt a simulated-to-real learning approach for dynamic hedging tasks, reducing the learning difficulty and addressing the issue of insufficient option data. A dynamic hedging strategy for 50ETF options was constructed. Finally, numerical experiments demonstrate the superiority of the designed algorithm over traditional hedging strategies in terms of hedging effectiveness.
文摘From AR-enhanced picture books to eco-friendly smart toys,the items now filling children’s shopping carts are more than just products-they epitomize the transformation of consumption in the new era.
基金supported by the Jiangsu University Philosophy and Social Science Research Project(Grant No.2019SJA1326).
文摘In this paper,we consider the price of catastrophe options with credit risk in a regime-switching model.We assume that the macroeconomic states are described by a continuous-time Markov chain with a finite state space.By using the measure change technique,we derive the price expressions of catastrophe put options.Moreover,we conduct some numerical analysis to demonstrate how the parameters of the model affect the price of the catastrophe put option.
文摘Spatio-temporal variability and dynamics in Sahelian agro-pastoral zones make each local situation a special case. These specificities must be considered to guide the dissemination of agricultural options with a view to sustainable development. The territorial scale of municipalities is not sufficient for this necessary contextualization;the scale of the “village terroir” seems to be a better option. This is the hypothesis we put forward in the framework of the Global Collaboration for Resilient Food Systems program (CRFS), i.e. local context is spatially defined by village terroir. The study is based on data collected through participatory mapping and surveys in “village terroirs” in three regions of Niger (Maradi, Dosso and Tillabéri). Then the links between farm managers and their cultivated land, as well as the spatio-temporal dynamics of local context are analyzed. This study provides evidence of the existence and functional usefulness of the village terroir for farmers, their land management and their activities. It demonstrates the usefulness of contextualizing agricultural options at this scale. Their analysis elucidates the links between “terroirs village” and the specific functioning of the agrosocio-ecosystems acting on each of them, thus laying the systemic and geographical foundations for a model of the spatio- temporal dynamics of “village terroirs”. This initial work has opened up new perspectives in modeling and sustainable development.
基金The research was funded by VSB-Technical University of Ostrava,the SGS Projects SP2022/58,SP2023/008.Huanyu Li,Ing.,Economic Faculty,VSB-TUO,Ostrava,Czech Republic。
文摘Venture capital investments are characterized by high input,high yield,and high risk.Due to the complexity of the market environment,stage-by-stage investment is becoming increasingly important.Traditional evaluation methods like comparison,proportion,maturity,internal rate of return,scenario analysis,decision trees,and net present value cannot fully consider the uncertainty and stage characteristics of the project.The fuzzy real options method addresses this by combining real option theory,fuzzy number theory,and composite option theory to provide a more accurate and objective evaluation of Public-Private Partnership(PPP)projects.It effectively considers the interaction of options and the ambiguity of project parameters,making it a valuable tool for project evaluation in the context of venture capital investment.
文摘In the FinTech era,we contribute to the literature by studying the pricing of Bitcoin options,which is timely and important given that both Nasdaq and the CME Group have started to launch a variety of Bitcoin derivatives.We find pricing errors in the presence of market smiles in Bitcoin options,especially for short-maturity ones.Long-maturity options display more of a“smirk”than a smile.Additionally,the ARJI-EGARCH model provides a better overall fit for the pricing of Bitcoin options than the other ARJI-GARCH type models.We also demonstrate that the ARJI-GARCH model can provide more precise pricing of Bitcoin and its options than the SVCJ model in term of the goodness-of-fit in forecasting.Allowing for jumps is crucial for modeling Bitcoin options as we find evidence of time-varying jumps.Our empirical results demonstrate that the realized jump variation can describe the volatility behavior and capture the jump risk dynamics in Bitcoin and its options.
文摘We derive methods for risk-neutral pricing of multi-asset options,when log-returns jointly follow a multivariate tempered stable distribution.These lead to processes that are more realistic than the better known Brownian motion and stable processes.Further,we introduce the diagonal tempered stable model,which is parsimonious but allows for rich dependence between assets.Here,the number of parameters only grows linearly as the dimension increases,which makes it tractable in higher dimensions and avoids the so-called“curse of dimensionality.”As an illustration,we apply the model to price multi-asset options in two,three,and four dimensions.Detailed goodness-of-fit methods show that our model fits the data very well.
文摘Modeling implied volatility(IV)is important for option pricing,hedging,and risk management.Previous studies of deterministic implied volatility functions(DIVFs)propose two parameters,moneyness and time to maturity,to estimate implied volatility.Recent DIVF models have included factors such as a moving average ratio and relative bid-ask spread but fail to enhance modeling accuracy.The current study offers a generalized DIVF model by including a momentum indicator for the underlying asset using a relative strength index(RSI)covering multiple time resolutions as a factor,as momentum is often used by investors and speculators in their trading decisions,and in contrast to volatility,RSI can distinguish between bull and bear markets.To the best of our knowledge,prior studies have not included RSI as a predictive factor in modeling IV.Instead of using a simple linear regression as in previous studies,we use a machine learning regression algorithm,namely random forest,to model a nonlinear IV.Previous studies apply DVIF modeling to options on traditional financial assets,such as stock and foreign exchange markets.Here,we study options on the largest cryptocurrency,Bitcoin,which poses greater modeling challenges due to its extreme volatility and the fact that it is not as well studied as traditional financial assets.Recent Bitcoin option chain data were collected from a leading cryptocurrency option exchange over a four-month period for model development and validation.Our dataset includes short-maturity options with expiry in less than six days,as well as a full range of moneyness,both of which are often excluded in existing studies as prices for options with these characteristics are often highly volatile and pose challenges to model building.Our in-sample and out-sample results indicate that including our proposed momentum indicator significantly enhances the model’s accuracy in pricing options.The nonlinear machine learning random forest algorithm also performed better than a simple linear regression.Compared to prevailing option pricing models that employ stochastic variables,our DIVF model does not include stochastic factors but exhibits reasonably good performance.It is also easy to compute due to the availability of real-time RSIs.Our findings indicate our enhanced DIVF model offers significant improvements and may be an excellent alternative to existing option pricing models that are primarily stochastic in nature.
基金Supported by National Natural Science Foundation of China(11571089,11501164)Natural Science Founda-tion of Hebei Province(A2019205299)+1 种基金the Foundation of Hebei Education Department(ZD2018065,ZD2019053)Hebei Normal University(L2019Z01).
文摘The aim of this paper is to price power option with its underlying asset price following exponential normal inverse gaussian(NIG)process.We first find the risk neutral equivalent martingale measure Q by Esscher transform.Then,using the Fourier transform and its inverse,we derive the analytical pricing formulas of power options which are expressed in the form of Fourier integral.In addition,the fast Fourier transform(FFT)algorithm is applied to calculate these pricing formulas.Finally,Shangzheng 50ETF options are chosen to test our results.Estimating the parameters in NIG process by maximum likelihood method,we show that the NIG prices are much closer to market prices than the Black-Scholes-Merton(BSM)ones.
基金Supported by Merit Review grants BX001155 from the Department of Veterans Affairs,Office of Research and Development(Biomedical Laboratory Research and Development)to Kharbanda KK
文摘Alcoholic liver disease(ALD)and non-alcoholic fatty liver disease(NAFLD)are serious health problems worldwide.These two diseases have similar pathological spectra,ranging from simple steatosis to hepatitis to cirrhosis and hepatocellular carcinoma.Although most people with excessive alcohol or calorie intake display abnormal fat accumulation in the liver(simple steatosis),a small percentage develops progressive liver disease.Despite extensive research on understanding the pathophysiology of both these diseases there are still no targeted therapies available.The treatment for ALD remains as it was 50 years ago:abstinence,nutritional support and corticosteroids(or pentoxifylline as an alternative if steroids are contraindicated).As for NAFLD,the treatment modality is mainly directed toward weight loss and co-morbidity management.Therefore,new pathophysiology directed therapies are urgently needed.However,the involvement of several inter-related pathways in the pathogenesis of these diseases suggests that a single therapeutic agent is unlikely to be an effective treatment strategy.Hence,a combination therapy towards multiple targets would eventually be required.In this review,we delineate the treatment options in ALD and NAFLD,including various new targeted therapies that are currently under investigation.We hope that soon we will be having an effective multi-therapeutic regimen for each disease.
文摘An experimental study on mitigation of greenhouse gas (CH4, N2O and NO) emission has been conducted in a typical cropping system of Southeast China for 4 years. By simultaneous measurement, the CH4, N2O and NO emission fluxes from rice-wheat rotation fields, effects of fertilization, water management, temperature and soil moisture were investigated. Temperature, fertilization and water status were found to be the key factors to regulate CH4, N2O and NO emis-sions. Based on the experimental results, some agricultural measures were recommended as techni-cal options to mitigate greenhouse gas emissions from rice-wheat rotation ecosystems. These miti-gation measures are reducing mineral N input, coupling organic manure with chemical fertilizers, applying fertilizers which release available N slowly during periods with intensive plant activity, and applying dry fermented organic manure and well management of water and fertilizer. Key words Mitigation options - Emission - Greenhouse gases - Ecosystems This study was supported by projects “ Experimental and Modeling Study on N2O Emission from the Rice-Wheat Rotation Fields of Southeast China” and “ Experimental and Modeling Study on NO Emission from Croplands” , which were granted by the National Natural Science Foundation of China, the State Key Fundamental Research Project “ Predicting the Future (20–50 years) Trend of Environmental Change in China”, and the project of Chinese Academy of Sciences “ Theory and Methodology on Air Pollution Prediction”.Thanks are due to Professor Zhang Wen, Dr. Bai Jianhui, Mr. Gong Yanbang, Mrs. Luo Dongmei and Mr. Liu Guangren from the Institute of Atmospheric Physics, Chinese Academy of Sciences for their help in experiments.
基金National Basic Research Program of China （973 Program）, No.2012CB955804 National Science Foundation of China, No.41201594 CAS Strategic Priority Research Program, No.XDA05150502
文摘It is believed that the global CO2 emissions have to begin dropping in the near fu- ture to limit the temperature increase within 2 degrees by 2100. So it is of great concern to environmentalists and national decision-makers to know how the global or national CO2 emissions would trend. This paper presented an approach to project the future CO2 emissions from the perspective of optimal economic growth, and applied this model to the cases of China and the United States, whose CO2 emissions together contributed to more than 40% of the global emissions. The projection results under the balanced and optimal economic growth path reveal that the CO2 emissions will peak in 2029 for China and 2024 for the USA owing to their empirically implied pace of energy efficiency improvement. Moreover, some abatement options are analyzed for China, which indicate that 1） putting up the energy price will de- crease the emissions at a high cost; 2） enhancing the decline rate of energy intensity can significantly mitigate the emissions with a modest cost; and 3） the energy substitution policy of replacing carbon intensive energies with clean ones has considerable potential to alleviate emissions without compromising the economic development.
基金supported by the International Cooperation Project of Ministry of Science and Technology of China(MOST:2009DFA32710,BMBF(FKZ):0330847F)the Natural Science Foundation of Zhejiang Province,China(Y13G030168)
文摘Ameliorating waste treatment by technological improvements affects the economic and the ecological-environment benefits of intensive pig production. The objective of the research was to develop and test a method to determine the technical optimization to ameliorate waste treatment methods and gain insight into the relationship between technological options and the economic and ecological effects. We developed an integrated bio-economic model which incorporates the farming production and waste disposal systems to simulate the impact of technological improvements in pig manure treatment on economic and environmental benefits for the case of a pilot farm in Beijing, China. Based on different waste treatment technology options, three scenarios are applied for the simulation analysis of the model. The simulation results reveal that the economic-environmental benefits of the livestock farm could be improved by reducing the cropland manure application and increasing the composting production with the current technologies. Nevertheless, the technical efficiency, the waste treatment capacity and the economic benefits could be further improved by the introduction of new technologies. It implies that technological and economic support policies should be implemented comprehensively on waste disposal and resource utilization to promote sustainable development in intensive livestock production in China.
