Determination of an appropriate quadrat size and shape for detecting association between plant species

The outcome of association analysis between species can be influenced by the size and shape of sampling quadrats. To eliminate this problem, a new method is proposed for determining an appropriate size for sampling quadrat. This method is based on measurement of the density of the plant species concerned. The use of this method is illustrated for the detection of association between species in a hypothetical community.     

仇山膨润土矿不同酸度活化后蒙脱石形态及其变化

浙江仇山膨润土经不同酸度活化,蒙脱石在酸度为17.5～20％时其颗粒大小、厚度趋于一致;酸度分别为12.5％,20％时集合体由絮状,团块状向厚片状,片状变化;酸度为12.5～17.5％时其颗粒边缘变为光滑,而酸度为25％时则变为锯齿状;酸度20％时,表面更加光滑,平整。蒙脱石形态直接反映它的表面积的变化,决定了活性白土脱色性能的优劣。本文讨论了蒙脱石表面积与活性白土脱色力的变化关系。     

铁磁形状记忆合金研究进展与展望(Ⅲ):应用研究

阐述了铁磁形状记忆合金(Ferromagnetic Shape Memory Alloy,简写为FSMA)在智能材料及其应用领域的优越性.重点介绍了FSMA装置研发和基于FSMA装置的体系分析理论的发展历程和研究现状.仔细分析了各种FSMA装置频率、输出力和最大位移等关键技术指标,讨论了基于电磁学、热力学和力学原理的包...     

大孔径冲孔翻边一次成型的设计

此文主要根据冲压件“前顶梁”冲孔翻边一次成型模设计的实践经验,提出大孔径冲孔翻边一次成型的工艺分析和计算及典型结构的设计,突破了冲孔与翻边同时进行只能在Φ8以下圆孔翻边的局限,并成功地一次试模合格,为类似的圆孔翻边在Φ8以上提供了宝贵的经验。     

基于MARC系统的V型砧角度优化

针对目前塑性加工参数优化研究中,有限元分析方法效率低,可靠性差,通用性不强等现状,将国际上著名的大型通用非线性有限元软件MARC与先进的非线性约束优化问题的解法——改进的约束变尺度算法相结合,开发了一个可用于塑性加工参数优化的软件,并应用于轴类大锻件拔长工艺的V型砧形状角度优化.优化结果与实验结果吻合较好,证明了该系统的可靠性.它还表明改进的约束变尺度算法具有较高的计算效率,可以搜索到工程全局最优解.文中所提出的曲线V型砧对圆形坯料具有较好的孔洞闭合效果.本系统的开发为塑性加工参数优化的研究开辟了一个新思路.     

铁磁形状记忆合金研究进展与展望(Ⅰ):材料、力学特性

综述了铁磁形状记忆合金(Ferromagnetic Shape Memory Alloy,简写为FSMA)在材料研制和热磁力学特性方面的研究现状,对其存在的问题进行了分析并指出其发展方向.在材料研发方面,介绍了新型合金、Ni-Mn-Ga-X系列合金、复合材料和Ni2MnGa系列合金;在热磁力学特性方面,介绍了形状记忆效...     

环保型型煤的研制

介绍以工业固体废弃物为主添加物，经科学的研究选择，按一定比例将工业固体废弃物掺入原煤中制成新型型煤，打破传统下燃式，采用上点火向上热伸展明火反应烧的方式。     

Indicators of perceived naturalness as drivers of landscape preference

The concept of naturalness is one of the more studied concepts in landscape preference research and describes how close a landscape is to a perceived natural state. In this study we explored the relationship between landscape preference and three landscape indicators of naturalness (level of succession, number of woodland patches and shape index of edges). We used computer-generated visualisations of a hypothetical landscape containing pasture and broadleaved woodland. In the landscape simulations we altered the values of the naturalness indicators between the levels of low, medium and high, creating 27 different visualisations. The survey was distributed as an on-line survey in seven different languages and obtained 703 respondents. The study showed a strong relationship with preference for both the level of succession and number of woodland patches, and a weaker relationship with shape index of edges. The two demographic factors which were shown to contribute most to the formation of preference were gender and having a landscape related profession. The results suggest that the selected indicators are more important drivers of preference than demographic factors.     

CuZnAl形状记忆合金在井下火灾防预系统上的应用初探

应用ＣｕＺｎＡｌ形状记忆合金的感温——驱动原理,制作井下火灾防预系统装置,具有较大的实用性。探讨该系统的设计原理及方法,研究复合细化、热处理工艺对形状记忆合金的影响     

Quantifying ecological thresholds from response surfaces

Ecological thresholds are abrupt changes of ecological state. While an ecological threshold is a widely accepted concept, most empirical methods detect them in time or across geographic space. Although useful, these approaches do not quantify the direct drivers of threshold response. Causal understanding of thresholds detected empirically requires their investigation in a multi-factor domain containing the direct drivers (often referred to as state space). Here, we present an approach to quantify thresholds from response surfaces modeled empirically in state space. We present two indices of shape attributes measured from response surfaces. The response surfaces are built using a regression method in state space. The indices are threshold strength (T) and diagonality (D). We use 48 simulated response surfaces of different shapes to test the efficacy of the indices in 3D. Our results show that T is sensitive to the steepness of the transition from one state to the next, with various forms of abrupt, centralized thresholds yielding the highest values among the simulated surfaces. D represents the orientation of the response surface or the simultaneous influence of more than one predictor in eliciting the response gradient. Strongly diagonal surfaces have the most diagonal surface area demonstrated by sharply undulating diagonal surfaces. Given that the success of T and D requires a regression method to accurately capture any shape of complex data structure, we also test the accuracy of empirical regression methods known to be tractable with complex data. We test classification and regression trees (CART), Random Forest, and non-parametric multiplicative regression (NPMR) for binary and continuous responses. We use the 48 simulated response surfaces to test the methods, and we find that prediction accuracy depends on both the T and D of the simulated data for each method. We choose the most accurate method among those we test for capturing any shape of response surface from real data, NPMR. Finally, we use NPMR to build response surfaces and quantify T and D from real ecological data sets. We demonstrate how measuring threshold strength and diagonality from multi-factor response surfaces can advance ecology.