50 publications from this institution
Light is often considered the primary factor leading to the regeneration failure of Korean pines (Pinus koraiensis) under the forest canopy. However, studies on the effect of light on Korean pines mainly focus on the use of an artificial sunshade net to control shade; field studies on the canopy are extremely scarce, and the current experimental results are contradictory. For a deeper understanding of the relationship between light conditions and understory Korean pine trees, the conditions of low, middle, high and full light (control) under the forest were tested at 18 years of age. The photosynthetic pigments, chlorophyll fluorescence, non-structural carbohydrate metabolism, antioxidant enzyme activity, and nutrient concentrations of current-year needles from Korean pine trees were measured. From June to September, light intensity and quality decreased under full light, but following leaf fall, understory light conditions improved slightly. As the light conditions improved, the photosynthetic pigments in the needles decreased, but Car/Chl were highest in the needles under full light. All light conditions had a positive correlation with glucose concentrations and Rubisco activity. Full-light needles had the highest APX activity, DPPH scavenging capacity, and proline concentration, as well as higher NPQ and lower Fv/Fm readings. This indicated that full-light Korean pine trees were stressed and inhibited photosynthesis to some extent, while the understory light environment may alleviate stress. The conservative strategy of storing more starch and using less glucose in understory Korean pine trees may be one of the reasons for the observed differences in growth rates among Korean pine trees under varying light conditions. Overall, this study implies that understory light during the growing season is not always unfavorable to 18-year-old Korean pine trees; this means that 18-year-old Korean pine trees still have shade tolerance to some extent and are capable of living under a canopy of deciduous trees.
In this paper,from the construction of double-slot miller especially applied in widespread european type of wooden windows,the problems of the construction of double-slot miller was analyed and the construction of double-slot miller was improved,the main factor impacting bearing life of principal axis of double-slot miller was discussed.
Abstract For the first 660MW ultra-supercritical circulating fluidized bed boiler in China, the original NO X emission concentration would be controlled and maintained below 50mg/Nm 3 , by improving the uniformity of bed temperature and bed pressure, strengthening the secondary air fractional combustion, optimizing the combustion temperature and operating oxygen and so on. Meanwhile, selective non-catalytic reduction (SNCR) technology with urea as reducing agent is selected as the auxiliary method to ensure the boiler achieves ultra-low NO X emission under full load conditions.
With the rapid development of urban economy and the increase of motor vehicles, the city traffic brings several negative impacts and environment pollution is more and more serious increasingly. Thus, it has become very important to reduce the vehicle emission. This paper addresses this context by introducing the research background about the driving condition and constructing the energy consumption model. On that basis, this paper presents the concept of the energy utilization rate and calculation model, and moreover, applies it under the European driving condition and brings out the energy utilization rate of vehicle, which provides the recommendations for the vehicle safety and environmental protection.
The adaptability and stable yield capacity of Andan 3 were evaluated by using the conventional analysis method,and high and stable coefficient method based on the data of Guizhou regional tests during 2001-2006 to provide a reference for guiding its large acreage production and maize breeding.The results showed that there was no significant difference in its yield between different regions and between different years,the variance coefficient,standard deviation and environment parameter of its yield were lower than those of other varieties and its stable coefficient was the highest in the same group,which indicates that Andan 3 is of the better adaptability and stable yield capacity in different ecological and production environments of Guizhou province.
Although photosynthesis (carbohydrate production) decreases under wind load, it is unclear how carbohydrate categories allocation changes. We determined the leaf morphology (specific leaf area (SLA), needle thickness), anatomy (cuticle thickness, epidermal thickness), photosynthesis (effective quantum yield of Photosystem II (Y(II)), carbohydrate (structure carbohydrate (SC) and non-structure carbohydrate (NSC)), and environmental variables in Pinus thunbergii plantations from coast to inland, with wind speed decreasing. As expected, wind, accounting for 19–69% of the total variation, was the most dominant environmental variable determining the leaf traits. Y(II) and NSC increased, while SC and SC/NSC decreased along the coast-inland gradients (p < 0.01). These results confirmed that, although carbohydrate production decreased, SC allocation increased with increasing wind load. SLA and needle thickness decreased, while cuticle thickness and epidermal thickness increased from coast to inland. Needle thickness and cuticle thickness showed strong correlations to SC/NSC. These variations indicated that carbohydrate categories allocation related to variations of needle morphology and anatomy for P. thunbergii under wind, because of more SC allocation in leaf to support tensile strength and hardness of the cell wall under wind. Therefore, allocation between SC and NSC may be helpful for understanding the long-term adaptation of plants to wind load.
A Hopfield neural network dynamic model with an improved energy function was presented for edge detection of log digital images in this paper. Different from the traditional methods, the edge detection problem in this paper was formulated as an optimization process that sought the edge points to minimize an energy function. The dynamics of Hopfield neural networks were applied to solve the optimization problem. An initial edge was first estimated by the method of traditional edge algorithm. The gray value of image pixel was described as the neuron state of Hopfield neural network. The state updated till the energy function touch the minimum value. The final states of neurons were the result image of edge detection. The novel energy function ensured that the network converged and reached a near-optimal solution. Taking advantage of the collective computational ability and energy convergence capability of the Hopfield network, the noises will be effectively removed. The experimental results showed that our method can obtain more vivid and more accurate edge than the traditional methods of edge detection.
