新型木材产销模式下的安全生产管理探讨

安全生产是构建和谐社会的基础和前提,是可持续发展的基本保障。随着市场经济的不断发展,国有林场的进一步深化改革,三明市国有林场探索总结出了“定产定销”的新型木材产销模式,林业生产经营和生产用工状况发生了很大的变化。探讨了在新型木材生产销售模式下如何进行安全生产管理的问题。     

北京市危险化学品安全生产监管监控现状与技术选择

分析了北京市危险化学品的安全生产现状以及监管监控现状,预测了北京市危险化学品的监管监控趋势,为了提高危险化学品监管监控的能力,给出了监管监控危险化学品的优化技术。     

Organic matter and concentrated nitrogen removal by shortcut nitrification and denitrification from mature municipal landfill leachate

An UASB＋Anoxic/Oxic （A/O） system was introduced to treat a mature landfill leachate with low carbon-to-nitrogen ratio and high ammonia concentration. To make the best use of the biodegradable COD in the leaehate, the denitrifieation of NOx^--N in the reeireulation effluent from the elarifier was carried out in the UASB. The results showed that most biodegradable organic matters were removed by the denitrifieation in the UASB. The NH4^＋-N loading rate （ALR） of A/O reactor and operational temperature was 0.28- 0.60 kg NH4^＋-N/（m^3-d） and 17-29℃ during experimental period, respectively. The short-cut nitrification with nitrite accumulation efficiency of 90%-99% was stabilized during the whole experiment. The NH4^＋-N removal efficiency varied between 90% and 100%. When ALR was less than 0.45 kg NH4^＋-N/（m^3.d）, the NH4^＋-N removal efficiency was more than 98%. With the influent NH4^＋-N of 1200-1800 mg/L, the effluent NH4^＋-N was less than 15 mg/L. The shortcut nitrification and denitrifieation can save 40% carbon source, with a highly efficient denitrifieation taking place in the UASB. When the ratio of the feed COD to feed NH4^＋-N was only 2-3, the total inorganic nitrogen （TIN） removal efficiency attained 67%-80%. Besides, the sludge samples from A/O reactor were analyzed using FISH. The FISH analysis revealed that ammonia oxidation bacteria （AOB） accounted for 4% of the total eubaeterial population, whereas nitrite oxidation bacteria （NOB） accounted only for 0.2% of the total eubaeterial population.     

Effect of sulfate on the methanogenic activity of a bacterial culture from a brewery wastewater during glucose degradation

The maximum specific methanogenic activity （SMA） of a sludge originating from a brewery wastewater treatment plant on the degradation of glucose was investigated at various levels of sulfate on a specific loading basis. Batch experiments were conducted in serum bottles at pH 7 and 35℃. A comparison of the values indicates that the SMA of this mixed culture was increased and reached its highest level of 0.128 g CH4 gas COD/（g VSS.d） when biomass was in contact with sulfate at a ratio of 1：0.114 by weight.     

Anaerobic tapered fluidized bed reactor for starch wastewater treatment and modeling using multilayer perceptron neural network

Anaerobic treatability of synthetic sago wastewater was investigated in a laboratory anaerobic tapered fluidized bed reactor(ATFBR) with a mesoporous granular activated carbon(GAC)as a support material.The experimental protocol was defined to examine the effect of the maximum organic loading rate(OLR),hydraulic retention time(HRT),the efficiency of the reactor and to report on its steady- state performance.The reactor was subjected to a steady-state operation over a range of OLR up to 85.44 kg COD/(m~3.d).The COD removal efficiency was found to be 92% in the reactor while the biogas produced in the digester reached 25.38 m~3/(m~3·d) of the reactor. With the increase of OLR from 83.7 kg COD/(m~3.d),the COD removal efficiency decreased.Also an artificial neural network(ANN) model using multilayer perceptron(MLP)has been developed for a system of two input variable and five output dependent variables. For the training of the input-output data,the experimental values obtained have been used.The output parameters predicted have been found to be much closer to the corresponding experimental ones and the model was validated for 30% of the untrained data.The mean square error(MSE)was found to be only 0.0146.     

Management of an Agroecosystem

Agroecosystems (AESs) are autotrophic ecosystems managed by man. The goal of the management is to obtain the maximum possible amount of high-quality agricultural products while preserving agricultural resources, primarily the soils and biodiversity. The main components of the management of AES structures and functions, including primary and secondary biological production, the ratio between the energy flows in the plant–man and plant–livestock–man food chains, the efficiency of energy transfer in the plant–livestock link, and conservation of agricultural resources, are considered.     

A panel study on the relationship between biofuels production and sustainable development

Biomass is one of the renewable energy sources on which policy makers are greatly dependent on since it is a flexible feedstock capable of conversion into electricity, transport liquid fuels and heat by chemical and biological processes on demand. Though numerous publications have examined the relationship of economic growth with renewable energy and other parameters, biomass energy has never been included in these studies. Then, this study examines the causal relationship within a multivariate panel cointegration/error correction framework which combines the cross-section and time series data while allowing for heterogeneity across different provinces. After employing panel data regression model ranging from 2003 through 2012 to examine the relationships of biofuels production with sustainable development in China, the paper concludes that the development of biofuel energy production integrated with the consideration of the improvement of income per capita, and the attraction of more capital investment, does make a significant contribution to economic growth. However, some negative side effects including the increase of greenhouse emissions and the decrease of marginal land still coexist with the economic development. Of course, the importance of these findings lies on their implications and their adoption on strategic policies.     

Optimizing mixture properties of biodiesel production using genetic algorithm-based evolutionary support vector machine

Nowadays, biodiesel is used as one of the alternative renewable energy due to the increasing energy demand. However, optimum production of biodiesel still requires a huge number of expensive and time-consuming laboratory tests. To address the problem, this research develops a novel Genetic Algorithm-based Evolutionary Support Vector Machine (GA-ESIM). The GA-ESIM is an Artificial Intelligence (AI)-based tool that combines K-means Chaotic Genetic Algorithm (KCGA) and Evolutionary Support Vector Machine Inference Model (ESIM). The ESIM is utilized as a supervised learning technique to establish a highly accurate prediction model between the input--output of biodiesel mixture properties; and the KCGA is used to perform the simulation to obtain the optimum mixture properties based on the prediction model. A real biodiesel experimental data is provided to validate the GA-ESIM performance. Our simulation results demonstrate that the GA-ESIM establishes a prediction model with better accuracy than other AI-based tool and thus obtains the mixture properties with the biodiesel yield of 99.9%, higher than the best experimental data record, 97.4%.     

Economic and environmental value stream map (E2VSM) simulation for multi-product manufacturing systems

Value stream mapping (VSM) is a well-accepted tool within lean manufacturing concept which is often used for analysing and designing the flow of materials and information required to manufacture a product. However, the analysis is static and single product oriented, which fails to cope with either the variation of production plan or a multi-product environment. In addition, the environmental impact of a manufacturing system is highly associated with the dynamic consumption of energy and resources. Despite the recent integration of VSM with simulation or environmental studies (in the domain of energy efficiency), still neglected is the dynamic assessment of all the resources involved in a multi-product production environment. This paper presents a methodology for modelling multi-product manufacturing systems with dynamic material, energy and information flows with the aim to generate economic and environmental value stream maps (E²VSM). The proposed methodology is validated with an industrial case.     

中国经济发展方式的转变动力及其作用途径

以全要素生产率增长动力作为经济发展方式的转变动力,本文采用1989-2013年4组省际面板数据经由可行广义最小二乘法实证估计了10个动力因素对全要素生产率增长率的贡献水平与作用途径。研究发现:技术创新水平、市场化水平、人力资本存量水平、异质性企业集聚水平和对外开放度的综合指数对中国全要素生产率增长率的回归估计系数分别为0.575 7,0.212 5,0.136 8,0.064 4和0.018,表明技术创新、市场化改革、人力资本积累、异质性企业集聚和对外开放是促进中国经济发展方式转变的直接动力因素。进一步的研究结果显示:技术创新和异质性企业集聚通过提高前沿技术进步率和生产效率变化率以及规模报酬收益率途径,市场化改革通过提高前沿技术进步率途径,人力资本积累与对外开放通过提高前沿技术进步率和规模报酬收益率途径,促进了中国全要素生产率增长。虽然产业结构变迁、城市化、基础设施建设、区域经济政策实施和金融发展对中国全要素生产率的增长表现为负向或拖累作用,但是,产业结构变迁与城市化能够提高前沿技术进步率,基础设施建设和区域经济政策能够提高规模报酬收益率,金融发展能够提高生产效率增长率和规模报酬收益率,这5项动力因素对促进中国全要素生产率增长的正向贡献有待提高。依据上述研究结论,本文提出尽快攻克制约生产率增长的核心技术,统筹考虑产业结构升级、城市化、基础设施建设和区域经济政策实施以及加快金融领域改革等政策建议,以期加快我国经济发展方式转变进程。