Nitrogen-15 signals of leaf-litter-soil continuum as a possible indicator of ecosystem nitrogen saturation by forest succession and N loads

National Key Research and Development Program [2010CB833502]; National Natural Science Foundation of China [30600071, 40601097, 30590381]; Chinese Academy of Sciences [KZCX2-YW-432, O7V70080SZ, LENOM07LS-01]; GUCAS [O85101PM03]

Optimal specificity and function for flexible biomolecular recognition

Biomolecular associations often accompanied by large conformational changes, sometimes folding and unfolding. By exploring an exactly solvable model, we constructed the free energy landscape and established a general framework for studying the biomolecular flexible binding process. We derived an optimal criterion for the specificity and function for flexible biomolecular binding where the binding and conformational folding are coupled.

Optimal specificity and function for flexible biomolecular recognition

Biomolecular associations often accompanied by large conformational changes, sometimes folding and unfolding. By exploring an exactly solvable model, we constructed the free energy landscape and established a general framework for studying the biomolecular flexible binding process. We derived an optimal criterion for the specificity and function for flexible biomolecular binding where the binding and conformational folding are coupled.

Energy landscape theory, funnels, specificity, and optimal criterion of biomolecular binding

We study the nature of biomolecular binding. We found that in general there exists several thermodynamic phases: a native binding phase, a non-native phase, and a glass or local trapping phase. The quantitative optimal criterion for the binding specificity is found to be the maximization of the ratio of the binding transition temperature versus the trapping transition temperature, or equivalently the ratio of the energy gap of binding between the native state and the average non-native states versus the dispersion or variance of the non-native states. This leads to a funneled binding energy landscape.

Comparison of photobioreactors and optimal light regime for rapid vegetative propagation of transgenic Undaria pinnatifida gametophytes

BACKGROUND: Previously, tachyplesin gene (tac) has been successfully transferred into Undaria pinnatifida gametophytes using the method of microprojectile bombardment transformation. The objectives of this study were to compare and evaluate the performance of bubble-column and airlift bioreactors to determine a preferred configuration of bioreactor for vegetative propagation of transgenic U. pinnatifida gametophytes, and to then investigate the influence of light on vegetative propagation of these gametophytes, including incident light intensity, photoperiod and light quality to resolve the problems of rapid vegetative propagation within the selected bioreactor. RESULTS: Experimental results showed that final dry cell density in the airlift bioreactor was 12.7% higher than that in the bubble-column bioreactor under the optimal aeration rate of 1.2 L air min(-1) L-1 culture. And a maximum final dry cell density of 2830 mg L-1 was obtained within the airlift bioreactor using blue light at 40 mu mol m(-2) s(-1) with a light/dark cycle of 14/10 (h). Polymerase chain reaction (PCR) analysis indicated that genes (bar and tac) were not lost during rapid vegetative propagation within the airlift bioreactor. CONCLUSION: The airlift bioreactor was shown to be much more suitable for rapid vegetative propagation of transgenic U. pinnatifida gametophytes than the bubble-column bioreactor in the laboratory. The use of blue light allows improvement of vegetative propagation of transgenic U. pinnatifida gametophytes. (C) 2009 Society of Chemical Industry

Optimal light regime for the cultivation of transgenic Laminaria japonica gametophytes in a bubble-column bioreactor

Fluctuating light intensity had a more significant impact on growth of gametophytes of transgenic Laminaria japonica in a 2500 ml bubble-column bioreactor than constant light intensity. A fluctuating light intensity between 10 and 110 mu E m(-2) s(-1), with a photoperiod of 14 h:10 h light:dark, was the best regime for growth giving 1430 mg biomass l(-1).

Algorithm Studies on How to Obtain a Conditional Nonlinear Optimal Perturbation (CNOP)

The conditional nonlinear optimal perturbation (CNOP), which is a nonlinear generalization of the linear singular vector (LSV), is applied in important problems of atmospheric and oceanic sciences, including ENSO predictability, targeted observations, and ensemble forecast. In this study, we investigate the computational cost of obtaining the CNOP by several methods. Differences and similarities, in terms of the computational error and cost in obtaining the CNOP, are compared among the sequential quadratic programming (SQP) algorithm, the limited memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) algorithm, and the spectral projected gradients (SPG2) algorithm. A theoretical grassland ecosystem model and the classical Lorenz model are used as examples. Numerical results demonstrate that the computational error is acceptable with all three algorithms. The computational cost to obtain the CNOP is reduced by using the SQP algorithm. The experimental results also reveal that the L-BFGS algorithm is the most effective algorithm among the three optimization algorithms for obtaining the CNOP. The numerical results suggest a new approach and algorithm for obtaining the CNOP for a large-scale optimization problem.

Diel vertical migration of zooplankton following optimal food intake under predation

A model is developed to investigate the trade-offs between benefits and costs involved in zooplanktonic diel vertical migration (DVM) strategies. The 'venturous revenue' (VR) is used as the criterion for optimal trade-offs. It is a function of environmental factors and the age of zooplankter. During vertical migration, animals are assumed to check instantaneously the variations of environmental parameters and thereby select the optimal behavioral strategy to maximize the value of VR, i.e. taking up as much food as possible with a certain risk of mortality. The model is run on a diel time scale (24 h) in four possible scenarios during the animal's life history. The results show that zooplankton can perform normal DVM balancing optimal food intake against predation risk, with the profile of DVM largely modified by the age of zooplankter.

Size dependence of biomass spectra and abundance spectra: the optimal distributions

Based on the hypothesis of self-optimization, we derive four models of biomass spectra and abundance spectra in communities with size-dependent metabolic rates. In Models 1 and 2, the maximum diversity of population abundance in different size classes subject to the constraints of constant mean body mass and constant mean respiration rate is assumed to be the strategy for ecosystems to organize their size structure. In Models 3 and 4, the organizing strategy is defined as the maximum diversity of biomass in different size classes without constraints on mean body mass and subject to the constant mean specific respiration rate of all individuals, i.e. the average specific respiration rate over all individuals of a community or group, which characterizes the mean rate of energy consumption in a community. Models 1 and 2 generate peaked distributions of biomass spectral density whereas Model 3 generates a fiat distribution. In Model 4, the distributions of biomass spectral density and of abundance spectral density depend on the Lagrangian multipler (lambda (2)). When lambda (2) tends to zero or equals zero, the distributions of biomass spectral density and of abundance spectral density correspond to those from Model 3. When lambda (2) has a large negative value, the biomass spectrum is similar to the empirical fiat biomass spectrum organized in logarithmic size intervals. When lambda (2) > 0, the biomass spectral density increases with body mass and the distribution of abundance spectral density is an unimodal curve. (C) 2001 Elsevier Science B.V. All rights reserved.

Effect of graded levels of rapeseed oil in isonitrogenous diets on the development of the gastrointestinal tract, and utilisation of protein, fat and energy in broiler chickens

The effect of feeding 0, 4, 8 and 16% rapeseed oil from 12-42 days of age was studied in broiler chickens on performance, digestibility of nutrients, and development of gastrointestinal tract, protein and energy metabolism. Thirty six female chickens (Ross 208) with initial body weight average 246 g were allocated to the four groups and kept pair-wise in metabolism cages. The chickens were fed similar amounts of metabolisable energy (ME) per day and similar amounts of essential amino acids relative to ME by adjusting with crystalline amino acids. The chickens were subjected to four balance periods each of five days with two 24 h measurements of gas exchange in two open-air-circuit respiration chambers inserted on the second and third day of each period. The addition of rapeseed oil increased the amount of gutfill indicating a reduced rate of passage and causing a hypertrophy of the gastrointestinal tract. There was a positive effect on feed utilisation as well as on digestibility especially of dietary fat together with higher utilisation of protein with addition of rapeseed oil. The partial fat digestibility of rapeseed oil estimated by regression was 91.1% and the partial metabolisability (ME/GE) of the rapeseed oil was estimated to 85% yielding an apparent metabolisable energy value of 34.30 MJ/kg.

Theoretical and experimental research on time-optimal trajectory planning and control of industrial robots

提出了一种用于工业机器人时间最优轨迹规划及轨迹控制的新方法，它可以确保在关节位移、速度、加速度以及二阶加速度边界值的约束下，机器人手部沿笛卡尔空间中规定路径运动的时间阳短。在这种方法中，所规划的关节轨迹都采用二次多项式加余弦函数的形式，不仅可以保证各关节运动的位移、速度 、加速度连续而且还可以保证各关节运动的二阶加速度连续。采用这种方法，既可以提高机器人的工作效率又可以延长机器人的工作寿命以PUMA560机器人为对象进行了计算机仿真和机器人实验，结果表明这种方法是正确的有效的。它为工业机器人在非线性运动学约束条件下的时间最优轨迹规划及控制问题提供了一种较好的解决方案。

Optimal Fuzzy PID Controller with Incomplete Derivation and Its Simulation Research on Application of Intelligent Artificial Legs

提出了一种新的最优模糊PID控制器，它由两部分组成，即在线模糊推理机构和带有不完全微分的常规PID控制器，在模糊推理机构中，引入了三个可调节因子xp,xi和xd，其作用是进一步修改和优化模糊推理的结果，以使控制器对一个给定对象具有最优的控制效果，可调节因子的最优值采用ITAE准则及Nelder和Mead提出的柔性多面体最优搜索算法加以确定，这种PID控制器被用来控制由作者设计的智能人工腿中的一个直流电机，仿真结果表明该控制器的设计是非常有效的，它可被用于控制各种不同的对象和过程。

An Optimal Scale for Edge Detection

Many problems in early vision are ill posed. Edge detection is a typical example. This paper applies regularization techniques to the problem of edge detection. We derive an optimal filter for edge detection with a size controlled by the regularization parameter $\\ lambda $ and compare it to the Gaussian filter. A formula relating the signal-to-noise ratio to the parameter $\\lambda $ is derived from regularization analysis for the case of small values of $\\lambda$. We also discuss the method of Generalized Cross Validation for obtaining the optimal filter scale. Finally, we use our framework to explain two perceptual phenomena: coarsely quantized images becoming recognizable by either blurring or adding noise.

Neural Network Exploration Using Optimal Experiment Design

We consider the question "How should one act when the only goal is to learn as much as possible?" Building on the theoretical results of Fedorov [1972] and MacKay [1992], we apply techniques from Optimal Experiment Design (OED) to guide the query/action selection of a neural network learner. We demonstrate that these techniques allow the learner to minimize its generalization error by exploring its domain efficiently and completely. We conclude that, while not a panacea, OED-based query/action has much to offer, especially in domains where its high computational costs can be tolerated.