Sustainable Energy Crop Production: A Case Study for Sugarcane and Cassava Production in Yunnan, China

The possibility of using biomass as a source of energy in reducing the greenhouse-effect imposed by carbon dioxide emission and relieving energy crisis is a matter of great interest, such as bioethanol production. Nevertheless, the cultivation of dedicated energy crops dose meet with some criticisms (conflict with food security and environmental degradation, for example). Nowadays sugarcane and cassava are regarded as the potential energy crops for bioethanol production. Endowed with natural resources and favorable weather condition, Yunnan province, China, is the major sugarcane and cassava production area in China. This paper presents production structures of these two crops in Yunnan and compares the sustainable production between the usages of sugarcane and cassava as bioethanol feedstock. Firstly, we estimated the technical efficiency for sugarcane and cassava production by adopting the production function and stochastic frontier production function. Field surveys from 61 sugarcane farmers and 50 cassava farmers were collected in June and September, 2008. Secondly, the sustainability of each crop production was evaluated. Since there is no generally accepted definition of sustainable production, a set of criteria was defined including 2 concerns (employment and food supply) from socio-economic area and 3 concerns (conversion rate to ethanol, water requirement, and fertilizer pollution) from environmental area. Empirical results demonstrated that the average production function was located below the frontier production function, 5% for sugarcane production and 7% for cassava production. These findings reflect the existence of technical inefficiency not only in the sugarcane production but also in the cassava production as well. But after considering sustainable production, cassava, which requires low agro-chemical, should be recommended as a prior energy crop in Yunnan with higher rates in ethanol conversion and dry matter.International Development, Production Economics, Energy crop, stochastic frontier production, Sustainable production, Yunnan province, Bioethanol,

The transition from incoherent to coherent random laser in defect waveguide based on organic/inorganic hybrid laser dye

This paper systematically demonstrated a variety of experimental phenomena of random lasers (RLs) of N,N′-di-(3-(isobutyl polyhedral oligomeric silsesquioxanes)propyl) perylene diimide (DPP) organic/inorganic hybrid laser dye, which is composed of perylene diimide (PDI) as gain media and polyhedral oligomeric silsesquioxanes (POSS) as scattering media at a mole ratio of 1:2. In this work, we observe the transition from incoherent RL in the DPP-doped solutions and polymer membrane systems using dip-coating method to coherent RL in the polymer membrane system with defect waveguide using semi-polymerization (SP) coating method. Meanwhile, we found that the hybrid dye-DPP has a long lasing lifetime compared with the traditional laser dyes, which indicates that the POSS group can suppress the photo-bleaching effect to extend the working life of laser dyes

Sustainable Energy Crop Production: A Case Study for Sugarcane and Cassava Production in Yunnan, China

The possibility of using biomass as a source of energy in reducing the greenhouse-effect imposed by carbon dioxide emission and relieving energy crisis is a matter of great interest, such as bioethanol production. Nevertheless, the cultivation of dedicated energy crops dose meet with some criticisms (conflict with food security and environmental degradation, for example). Nowadays sugarcane and cassava are regarded as the potential energy crops for bioethanol production. Endowed with natural resources and favorable weather condition, Yunnan province, China, is the major sugarcane and cassava production area in China. This paper presents production structures of these two crops in Yunnan and compares the sustainable production between the usages of sugarcane and cassava as bioethanol feedstock. Firstly, we estimated the technical efficiency for sugarcane and cassava production by adopting the production function and stochastic frontier production function. Field surveys from 61 sugarcane farmers and 50 cassava farmers were collected in June and September, 2008. Secondly, the sustainability of each crop production was evaluated. Since there is no generally accepted definition of sustainable production, a set of criteria was defined including 2 concerns (employment and food supply) from socio-economic area and 3 concerns (conversion rate to ethanol, water requirement, and fertilizer pollution) from environmental area. Empirical results demonstrated that the average production function was located below the frontier production function, 5% for sugarcane production and 7% for cassava production. These findings reflect the existence of technical inefficiency not only in the sugarcane production but also in the cassava production as well. But after considering sustainable production, cassava, which requires low agro-chemical, should be recommended as a prior energy crop in Yunnan with higher rates in ethanol conversion and dry matter

Path-Following and Obstacle Avoidance Control of Nonholonomic Wheeled Mobile Robot Based on Deep Reinforcement Learning

In this paper, a novel path-following and obstacle avoidance control method is given for nonholonomic wheeled mobile robots (NWMRs), based on deep reinforcement learning. The model for path-following is investigated first, and then applied to the proposed reinforcement learning control strategy. The proposed control method can achieve path-following control through interacting with the environment of the set path. The path-following control method is mainly based on the design of the state and reward function in the training of the reinforcement learning. For extra obstacle avoidance problems in following, the state and reward function is redesigned by utilizing both distance and directional perspective aspects, and a minimum representative value is proposed to deal with the occurrence of multiple obstacles in the path-following environment. Through the reinforcement learning algorithm deep deterministic policy gradient (DDPG), the NWMR can gradually achieve the path it is required to follow and avoid the obstacles in simulation experiments, and the effectiveness of the proposed algorithm is verified

Early changes of bone metabolites and lymphocyte subsets may participate in osteoporosis onset: a preliminary study of a postmenopausal osteoporosis mouse model

PurposeMetabolic and immune changes in the early stages of osteoporosis are not well understood. This study aimed to explore the changes in bone metabolites and bone marrow lymphocyte subsets and their relationship during the osteoporosis onset.MethodsWe established OVX and Sham mouse models. After 5, 15, and 40 days, five mice in each group were sacrificed. Humeri were analyzed by microCT. The bone marrow cells of the left femur and tibia were collected for flow cytometry analysis. The right femur and tibia were analyzed by LC-MS/MS for metabolomics analysis.ResultsBone microarchitecture was significantly deteriorated 15 days after OVX surgery. Analysis of bone metabolomics showed that obvious metabolite changes had happened since 5 days after surgery. Lipid metabolism was significant at the early stage of the osteoporosis. The proportion of immature B cells was increased, whereas the proportion of mature B cells was decreased in the OVX group. Metabolites were significantly correlated with the proportion of lymphocyte subsets at the early stage of the osteoporosis.ConclusionLipid metabolism was significant at the early stage of the osteoporosis. Bone metabolites may influence bone formation by interfering with bone marrow lymphocyte subsets

Path-Following and Obstacle Avoidance Control of Nonholonomic Wheeled Mobile Robot Based on Deep Reinforcement Learning

In this paper, a novel path-following and obstacle avoidance control method is given for nonholonomic wheeled mobile robots (NWMRs), based on deep reinforcement learning. The model for path-following is investigated first, and then applied to the proposed reinforcement learning control strategy. The proposed control method can achieve path-following control through interacting with the environment of the set path. The path-following control method is mainly based on the design of the state and reward function in the training of the reinforcement learning. For extra obstacle avoidance problems in following, the state and reward function is redesigned by utilizing both distance and directional perspective aspects, and a minimum representative value is proposed to deal with the occurrence of multiple obstacles in the path-following environment. Through the reinforcement learning algorithm deep deterministic policy gradient (DDPG), the NWMR can gradually achieve the path it is required to follow and avoid the obstacles in simulation experiments, and the effectiveness of the proposed algorithm is verified

Enhancing Crystallinity and Orientation by Hot-Stretching to Improve the Mechanical Properties of Electrospun Partially Aligned Polyacrylonitrile (PAN) Nanocomposites

Partially aligned polyacrylonitrile (PAN)-based nanofibers were electrospun from PAN and PAN/single-walled carbon nanotubes (SWNTs) in a solution of dimethylformamide (DMF) to make the nanofiber composites. The as-spun nanofibers were then hot-stretched in the oven to enhance its orientation and crystallinity. With the introduction of SWNTs and by the hot-stretched process, the mechanical properties will be enhanced correspondingly. Scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray scattering (XRD), differential scanning calorimetry (DSC), and the tensile test were used to characterize the microstructure and performances of the nanofibers. The orientation and crystallinity of the as-spun and hot-stretched nanofibers confirmed by X-ray have increased. Differential scanning calorimetry showed that the glass transition temperature of PAN increased about 3 °C by an addition of 0.75 wt% SWNTs indicating a strong interfacial interaction between PAN and SWNTs. The tensile strength and the modulus of the nanofibers increased revealing significant load transfer across the nanotube-matrix interface. For PAN nanofibers, the improved fiber alignment, orientation and crystallinity resulted in enhanced mechanical properties, such as the tensile strength and modulus of the nanofibers. It was concluded that the hot-stretched nanofiber and the PAN/SWNTs nanofibers can be used as a potential precursor to produce high-performance nanocomposites