小麦条锈病流行程度趋势预测专家系统雏型

本文运用知识工程语言 M·1构造了一个用于小麦条锈病流行程度趋势预测的专家系统雏型。专家的知识用产生式规则来表示。知识库中的知识规则可相对独立,便于知识库的扩充和完善。     

GI PiCO2: Tissue Specific Monitoring For Improving Patient Outcomes

Improvements in human patient monitoring despite their development in animals, do not always find their way into veterinary clinical use due to financial constraints. Gastrointestinal intraluminal CO₂ partial pressure (Gip₁CO₂) monitoring, however, is not only proving very beneficial in human trauma and critical patient care but is also very likely to become relatively inexpensive. By providing information on the perfusion adequacy of a high risk, critically important tissue, the GI mucosa, GI P₁CO₂ monitoring offers an easily accesible indicator of the efficacy and adequacy of resuscitative interventions. The potential for decreasing morbidity and mortality is enormous. Therefore, the practicing veterinarian should become familiar with GI P₁CO₂ monitoring theory and technology so he or she can be better prepared to incorporate it into practice when in becomes available.     

应用积分GM(1,1)模型进行杉木炭疽病预测预报的研究

以积分生成代替传统的累加生成方法 ,并用双向差分建立积分GM (1,1)灰色预测模型进行杉木炭疽病预测预报的研究 ,结果表明积分GM (1,1)模型能较好地预测杉木炭疽病在三明市的发生     

不同海拔下甲醇替代率和主喷正时对RCCI发动机性能的影响

为探究不同海拔条件下甲醇/柴油反应活性控制压燃（reactivity controlled compression ignition, RCCI）发动机的运行特性,该研究基于甲醇/柴油双燃料发动机试验台架,试验研究1 800r/min、100%负荷和3 200r/min、100%负荷下不同甲醇替代率、柴油喷射正时对发动机燃烧与排放性能的影响规律。结果表明：不同海拔条件下随着甲醇替代率的增加,缸压和瞬时放热率峰值逐渐升高,燃烧始点和燃烧中心前移,当量有效燃油消耗率（equivalent brake specific fuel consumption, ESFC）降低,有效热效率升高,NO_x和碳烟排放大幅降低,THC（total hydrocarbons）和CO排放增加。1 800 r/min、100%负荷工况下,甲醇替代率由0增至20%,0、1 000、2 000m海拔下最大缸压平均增加1.72MPa,瞬时放热率峰值平均升高25.08J/(°),ESFC平均降低4.67%,有效热效率平均升高4.90%,NO_x和碳烟排放分别平均降低16.63%和50%,THC和CO排放量分别平均增加142.03、388.18 mg/kg。3 200 r/min下甲醇替代率由0增至7%,不同海拔高度下ESFC平均降低1.76%,有效热效率平均升高1.79%,NO_x和碳烟排放量分别平均降低8.17%和20.70%。海拔高度由0升至2 000m,1 800r/min、20%甲醇替代率与3 200r/min、7%甲醇替代率下,瞬时放热率峰值分别降低4.80和8.08J/(°),燃烧中心分别推迟1.44°和1.43°,有效热效率分别降低0.82%和0.68%,ESFC分别升高2.10%和1.99%,NO_x排放量分别减少10.61%和7.35%,碳烟排放分别增加26.54%和32.12%,THC排放分别升高29.88%和15.45%,CO排放量分别增加22.42%和18.15%。固定甲醇替代率后,随着柴油主喷正时提前,不同海拔条件下缸压和放热率峰值逐渐升高,燃烧中心向上止点靠近,ESFC逐渐降低,有效热效率升高,碳烟排放减少,NO_x、THC和CO排放增加。1 800 r/min、15%甲醇替代率下,主喷正时从-1.5°提前至-7.5°,不同海拔高度下ESFC平均降低8.27%,有效热效率平均升高9.08%,碳烟排放平均减少90.94%。为提升高海拔条件下甲醇/柴油RCCI发动机的热效率和燃油经济性,可以适当增大柴油主喷正时。研究结果可为不同海拔环境下甲醇/柴油RCCI发动机燃烧与污染物排放控制优化提供参考。     

Predicting the spatial distribution of ground flora on large domains using a hierarchical Bayesian model

Accomodation of important sources of uncertainty in ecological models is essential to realistically predicting ecological processes. The purpose of this project is to develop a robust methodology for modeling natural processes on a landscape while accounting for the variability in a process by utilizing environmental and spatial random effects. A hierarchical Bayesian framework has allowed the simultaneous integration of these effects. This framework naturally assumes variables to be random and the posterior distribution of the model provides probabilistic information about the process. Two species in the genus Desmodium were used as examples to illustrate the utility of the model in Southeast Missouri, USA. In addition, two validation techniques were applied to evaluate the qualitative and quantitative characteristics of the predictions.This revised version was published online in May 2005 with corrections to the Cover Date.     

新亚欧大陆桥新疆段受损区段的灰色预测

在对新亚欧大陆桥新疆段受损区段、受损长度及受损频率和受损密度详尽分析的基础上，揭示了陆桥新疆段受损区段的时空分布规律。并依据灾害的时序分布特征，运用灰色原理和方法，根据受损区段数确立阈值和相应的年份序列，分别建立GM（1，1）模型，求出年份序列的序号响应式，并对实际值和理论预测结果进行了拟合检验，模型群的原点误差范围为0.198-1.314之间，平均误差为0.823-1.917，并同时预测了陆桥新疆段2001－2005年间可能的受损区段数。     

闭锁群体BLUP选择下遗传方差和近交系数的变化

采用计算机随机模拟方法模拟了在一个闭锁群体内连续对单个性状进行 1 5个世代选择的情况。选择过程中世代不重叠 ,每个世代的种畜根据动物模型最佳线性无偏预测 (BLUP)法估计的育种值进行选留 ,并在此基础上系统地比较了不同群体规模、公母比例和性状遗传力对群体遗传方差和近交系数变化的影响。结果表明 ,扩大育种群规模、增加公畜比例以及对低遗传力性状进行选择时 ,群体遗传方差降低的速度和近交系数上升的速度会更慢 ,在长期选择时可望获得更大的持续进展和适宜的近交增量     

ANN在森林资源预测中的应用研究

人工神经网络(ANN)方法是基于实例的方法,不需要考虑数学模型的内部结构,不需要假设前提条件,不需要人为地确定因子权重,作为一个黑箱综合地映射研究对象的整体性。应用人工神经网络多步预测方法对甘肃连城林场吐鲁沟营林区有林地面积进行预测,网络模型的最大相对误差为0 080 8％,最小相对误差达到0 0089％,平均为0.038 6％,表明预测值与实际值吻合程度很好,因此模型的精度较高,并且建模简单经预测,林场2000-2004年有林地面积稍有下降趋势,分别为2 873.2 hm2,2 618 7 hm2,2 484.5 hm2,2 346 hm2,2 171 6hm2。     

Including an additional systematic environmental effect within a generation in an evaluation model improves accuracy of prediction of breeding values in a closed herd of pigs

The present study evaluated the advantage of mixed‐model techniques over a selection index under different magnitudes of an additional systematic environmental effect (ASEE) in terms of accuracy of prediction and expected genetic gain. The data attempted to simulate a closed herd in a pig breeding program. The base population (G₀) consisted of 10 males and 50 females. Six generations (G₀ to G₅) were selected by using a selection index of three traits without overlapping. Additional systematic environmental constants with four levels in a generation were assigned from a uniform distribution at different ranges. Breeding values of animals in the last generation (G₅) were estimated on the basis of an index of individual phenotype (SI‐U), SI‐U adjusted for ASEE using a least‐squares mean (SI‐A), best linear unbiased prediction using an animal model excluding ASEE (AM‐E), and an animal model including ASEE (AM‐I). Accuracy of prediction and expected genetic gain were larger by the animal model than by the selection index, even if heritability of the traits selected was high and ASEE was set to zero. When ASEE was zero, the accuracy of prediction and expected genetic gain given by SI‐U and AM‐I were similar to those given by SI‐A and AM‐E, respectively. However, the differences in accuracy and expected gain between SI‐U and AI‐A and between AM‐I and AM‐E increased as the range of ASEE increased. It was concluded that selection based on an animal model was more effective than index selection, even if the herd environment was uniform and traits with high heritability were selected, and that it should be always included in an evaluation model, however slight any systematic environmental effect may be in a closed herd.