LCM （life cycle management） is a systematic approach, mindset and culture that considers economic, social, and environmental factors among other factors in the decision making process throughout various business or ...LCM （life cycle management） is a systematic approach, mindset and culture that considers economic, social, and environmental factors among other factors in the decision making process throughout various business or organizational decisions that affect both inputs and outputs of a product or service life cycle. It is a product, process, or activity management system aimed at minimizing environmental and socio-economic burdens associated with an organization＇s product or process during its entire life cycle and value chain. LCM＇s application is gaining wider acceptance both in the corporate and governmental organizations as an approach to reduce ecological footprints and to improve the sustainability of human activities. But where and how can it be used in agricultural engineering applications？ This study highlights the potential areas of LCM application in agricultural and allied sectors and how it can be utilized. The study revealed that LCM tools such as design for environment and life cycle analysis can be used to evaluate the environmental impacts of-and to improve the products, equipment, and structures produced by biosystems engineers as well as the processes used to generate them.展开更多
Efficient numerical solver for the SchrSdinger equation is very important in physics and chemistry. The finite element discrete variable representation （FE-DVR） was first proposed by Rescigno and Mc-Curdy [Phys. Rev...Efficient numerical solver for the SchrSdinger equation is very important in physics and chemistry. The finite element discrete variable representation （FE-DVR） was first proposed by Rescigno and Mc-Curdy [Phys. Rev. A 62, 032706 （2000）] for solving quantum-mechanical scattering problems. In this work, an FE-DVR method in a mapped coordinate was proposed to improve the efficiency of the original FE-DVR method. For numerical demonstration, the proposed approach is applied for solving the electronic eigenfunctions and eigenvalues of the hydrogen atom and vibrational states of the electronic state 3E＋ of the Cs2 molecule which has long-range interaction potential. The numerical results indicate that the numerical efficiency of the original FE-DVR has been improved much using our proposed mapped coordinate scheme.展开更多
We develop an influenza pandemic model with quarantine and treatment, and analyze the dynamics of the model. Analytical results of the model show that, if basic repro- duction number R0 〈 1, the disease-free equilibr...We develop an influenza pandemic model with quarantine and treatment, and analyze the dynamics of the model. Analytical results of the model show that, if basic repro- duction number R0 〈 1, the disease-free equilibrium （DFE） is globally asymptotically stable, if R0〉 1, the disease is uniformly persistent. The model is then extended to assess the impact of three anti-influenza control measures, precaution, quarantine and treat- ment, by re-formulating the model as an optimal control problem. We focus primarily on controlling disease with a possible minimal the systemic cost. Pontryagin＇s maximum principle is used to characterize the optimal levels of the three controls. Numerical sim- ulations of the optimality system, using a set of reasonable parameter values, indicate that the precaution measure is more effective in reducing disease transmission than the other two control measures. The precaution measure should be emphasized.展开更多
文摘LCM （life cycle management） is a systematic approach, mindset and culture that considers economic, social, and environmental factors among other factors in the decision making process throughout various business or organizational decisions that affect both inputs and outputs of a product or service life cycle. It is a product, process, or activity management system aimed at minimizing environmental and socio-economic burdens associated with an organization＇s product or process during its entire life cycle and value chain. LCM＇s application is gaining wider acceptance both in the corporate and governmental organizations as an approach to reduce ecological footprints and to improve the sustainability of human activities. But where and how can it be used in agricultural engineering applications？ This study highlights the potential areas of LCM application in agricultural and allied sectors and how it can be utilized. The study revealed that LCM tools such as design for environment and life cycle analysis can be used to evaluate the environmental impacts of-and to improve the products, equipment, and structures produced by biosystems engineers as well as the processes used to generate them.
文摘Efficient numerical solver for the SchrSdinger equation is very important in physics and chemistry. The finite element discrete variable representation （FE-DVR） was first proposed by Rescigno and Mc-Curdy [Phys. Rev. A 62, 032706 （2000）] for solving quantum-mechanical scattering problems. In this work, an FE-DVR method in a mapped coordinate was proposed to improve the efficiency of the original FE-DVR method. For numerical demonstration, the proposed approach is applied for solving the electronic eigenfunctions and eigenvalues of the hydrogen atom and vibrational states of the electronic state 3E＋ of the Cs2 molecule which has long-range interaction potential. The numerical results indicate that the numerical efficiency of the original FE-DVR has been improved much using our proposed mapped coordinate scheme.
文摘We develop an influenza pandemic model with quarantine and treatment, and analyze the dynamics of the model. Analytical results of the model show that, if basic repro- duction number R0 〈 1, the disease-free equilibrium （DFE） is globally asymptotically stable, if R0〉 1, the disease is uniformly persistent. The model is then extended to assess the impact of three anti-influenza control measures, precaution, quarantine and treat- ment, by re-formulating the model as an optimal control problem. We focus primarily on controlling disease with a possible minimal the systemic cost. Pontryagin＇s maximum principle is used to characterize the optimal levels of the three controls. Numerical sim- ulations of the optimality system, using a set of reasonable parameter values, indicate that the precaution measure is more effective in reducing disease transmission than the other two control measures. The precaution measure should be emphasized.
