人为干扰对黄土高原子午岭油松人工林土壤物理性质的影响

研究了放牧、收集枯落物及清灌等人为干扰活动对黄土高原于午岭油松林土壤结构及抗蚀性的影响。结果表明,随人为干扰强度的增加,0～50cm土壤中砂粒含量比无干扰时分别增加了11.83％、37．80％和51．60％;粉粒下降了8．16％、11．83％和15．55％;粘粒下降了8．10％、20．84％和30．72％,土壤表现出粗骨化趋势;〉0.25mm水稳性团聚体含量比无干扰林地分别下降了16．59％、43.12％和61．13％。〉1．0mm的团聚体含量仅为无干扰林地土壤的27．78％和24．34％,1．0—0．25mmm的团聚体下降幅度较小;〉0．05mm微团聚体的比例分别下降了19．39％、32．62％和33．47％。而〈0．05mm微团聚体所占比例随干扰程度的增加而大幅度上升。土壤容重增加了0．11-0．41g／cm^3。土壤总孔隙度分别降低了13．64％、25．47％和39．14％,毛管孔隙下降了7．79％、11．54％和29．32％,非毛管孔隙下降了28．47％、60．79％和64．08％。说明表层土壤非毛管孔隙对人为干扰更为敏感。最大持水量分别下降23．42％、37．15％和52．92％;毛管持水量下降33．79％、43．01％和52．22％;自然含水量下降31．03％、39．34％和46．28％。饱和持水量下降16．14％、28．80％和49．68％;田间持水量下降了12．39％、33．92％和47．47％;土壤有效水含量下降了9．55％、20．55％和58．91％。土壤前3min初渗率下降了38．74％、51．45％和63．23％;稳渗速率下降了54．06％、71．63％和84．10％,相应地受人为干扰林地前30min累计人渗量也较未受人为干扰林地土壤分别低48．15％、65．93％和73．35％。饱和导水率较对照下降了8．73％、33．33％和51．00％。土壤的结构系数。由79．12％下降到27．32％。团聚度由59．48％下降到11．11％,分散率上升了l倍多,分散系数上升了4倍多。土壤枯落物层及有机质的减少是引起土壤物理性质恶化的主要原因,其次是放牧和踏实等活动。     

铁线莲属研究随记(Ⅱ)

(1)对铁线链属以下诸种Clematis potaninii Maxim., C．heynei Rau,C．trichotoma Nakai,C．apiculata Hook．f.&; Thoms., C．theobromina Dunn,C．hedysarifolia DC．和C．dissecta Baker的系统位置进行了讨论,提出了新见解;(2)过去一些作者或不承认C．trifida Hook．,C．pimpinellifolia Hook.,C．oligophylla Hook．,和Clematopsis lineariloba Hutch诸种,或进行降级,作为种下分类群处理。本文作者在研究了有关标本之后认为上述4种有明显区别特征,均应成立;(3)对裂叶铁线莲Clematis parviloba Gardn．&; Champ．的5个变种,短毛铁线莲C．puberula Hook．f.&; Thoms．的4个变种和丝铁线莲组sect．Naraveliopsis Hand.-Mazz．的20个种做出新的分类安排;(4)归并了subsect．Potanimianae W．T．Wang,C．heynei M．Johnson,C．petelotii Gagnep．以及其他几个学名;(5)描述了2新亚组,4新系,3新种和3新变种;(6)做出了3个新等级,4个新组合。     

彩云兜兰及其近缘种的研究

简要讨论了彩云兜兰及其近亲种的亲缘关系;描述了两个新种：缅甸兜兰Paphiopedilum burmanicum J．Y．Zhang et Z．J．Liu和短唇兜兰Paphiopedilum brevilabium Z．J．Liu et J．Y．Zhang;并提供了一个图版和有关5个种的分种检索表。     

中国冬青属苦丁茶名实辨证

通过对冬青科饮料植物苦丁茶的考证,将苦丁茶ＩｌｅｘｋｕｄｉｎｇｃｈａＣ．Ｊ．Ｔｓｅｎｇ并入扣树Ｉ．ｋａｕｓｈｕｅＳ．Ｙ．Ｈｕ中,对新种五棱苦丁茶Ｉ．ｐｅｎｔａｇｏｎａＳ．Ｋ．Ｃｈｅｎ,Ｙ．Ｘ．ＦｅｎｇｅｔＣ．Ｆ．Ｌｉａｎｇ作了描述,并提供了４个相近种的检索表     

玲珑兜兰, 中国云南兰科一新种

对中国云南产的兰科新种玲珑兜兰Paphiopedilum microchilum Z．J．Liu et S．C．Chen作了描述和绘图,并简要地讨论了它与彩云兜兰Paph．wardii Summerh．的亲缘关系。     

地黄连作对根际微生物区系及土壤酶活性的影响

以地黄连作2年和1年的土壤为研究对象,分别测定了根际微生物区系变化及根际土壤酶活性．结果表明：地黄连作对其根际微生物区系及土壤酶活性产生了较大的影响．随种植年限的增加,根际细菌和真菌减少,但差异均不显著;放线菌增多,连作2年的土壤约为1年的4倍．土壤中氨化细菌、好气性固氮菌、硫化细菌、反硝化细菌和嫌气性纤维素分解菌分别增加了25．99、45．39、11．43、1．36和1．43倍,而好气性纤维素分解菌减少了86．74％．连作地黄根系的分泌物对脲酶、多酚氧化酶、蔗糖酶、蛋白酶和纤维素酶活性具有促进作用,分别增加了62．87％、9．43％、47．91％、139．62％和31．33％,而对过氧化氢酶则呈抑制作用．说明地黄连作会破坏根际微生物种群平衡．     

香港润楠属植物的分类研究

本文记载了香港润楠属植物共１１种,其中包括２个香港新记录（Ｍ．ｌｅｐｔｏｐｈｙｌａＨａｎｄ．－Ｍａｚ．,Ｍ．ｒｏｂｕｓｔａＷ．Ｗ．Ｓｍ．）,改正了４个过去被误定的植物种名。     

REVISION OF THE GENUS CALIROA O.COSTA(HYMENOPTERA:HETERARTHRIDAE)FROM CHINA

本文系统厘定了中国粘叶蜂属种类,报道了分布于中国的粘叶蜂属１０种,其中包括６新种：陷齿粘叶蜂Ｃ．ｃａｖｉｓｅｒｒｕｌａｓｐ．ｎｏｖ．,波粘叶蜂Ｃ．ｃｕｒｖａｔａｓｐ．ｎｏｖ．,大粘叶蜂Ｃ．ｍｅｇａｓｏｍａｓｐ．ｎｏｖ．,大眼粘叶蜂Ｃ．ｍｅｇｏｍｍａｓｐ．ｎｏｖ．,小粘叶蜂Ｃ．ｐａｒｖｕｌａｓｐ．ｎｏｖ．,塞氏粘叶蜂Ｃ．ｓａｉｎｉｓｐ．ｎｏｖ．．光额粘叶蜂Ｃ．ｇｌａｂｒｉｆｒｏｎｓＭａｌａｉｓｅ和榉粘叶蜂Ｃ．ｚｅｌｋｏｖａＯｋｕｔａｎｉ为中国新记录种。编制了粘叶蜂属中国和中南半岛已知种检索表。     

铁线莲属研究随记(Ⅴ)

(1)描述了9新种,4新变种;做出了2新等级,1新组合和1新名称。(2)归并了以下拉丁学名： Clematis dioica L．ssp．virginiana(L．)Kuntze var．bahamica Kuntze,C．bahamica (Kuntze) Britton,C．orbic- ulata Correll,C．brasiliana DC．var．laxa St．Hilaire,C．perulata Kuntze,C．barranacae Jones,C．discolor Gardn., C．laxiflora Baker,C．bathiei Lévl．和C．mauritiana Lam．var．sulfurea Viguier &; Perrier。(3)对威灵仙C．chinensis Osbeck的5个变种进行了分类;特产日本的C．fujisanensis Hisauti &; Hara与C.chinensis 极为相近,主要区别在于具较大的花,但有时花与C.chinensis的花同样大,由于区别不大,在本文中被 降级作变种处理;与其近缘、具强烈退化花序、特产华东的C．anhweiensis M．C．Chang也随之被处理为 变种。(4)瑞典学者Johnson在最近出版的铁线莲属专著中将特产西印度群岛东部的C．Flukenetii DC． 归并于特产美国东南部的C．catesbyana Pursh;本文不同意他做出的归并,并列出了这两个种的明显区 别特征,确认后者是一个应该得到承认的独立的种。(5)根据墨西哥标本描述的C．acapulcensis Hook． &; Arn．原知分布于中美一带,而其在南美的居群和一小叶多毛的新变种(var．puberula)过去长期间被误 定为其近缘种C．affinis St．Hilaire;这个混乱在本文中得到澄清,同时,本文给出了这二近缘种的区别 特征。(6)Viguier和Perrier两位学者在上世纪四十年代末研究马达加斯加一带的黄花铁线莲组-怀特铁 线莲亚组(sect．Meclatis subsect．Wightianae)植物时做出了不少错误鉴定：(a)将特产马达加斯加的具三 出复叶的C．mauritiana Lam. var．mauritiana,var．coriacea和C．microcuspis Baker,以及具单叶的C．ac- tinostemmatifolia W．T．Wang均鉴定为分布于非洲大陆的C．simensis Fresen., 并将后者作为分布于亚洲和欧洲的C．orientalis L．的亚种处理;(b)将特产马达加斯加具三出复叶的C．laxiflora Baker和具一回羽状复叶的C．ibarensis Baker鉴定为特产印度南部的C．wightiana Wall.,也将后者作为C．orientalis的亚种处理;(c)将特产科摩罗(Comoros)具二回羽状复叶的C．comoresensis W．T. Wang鉴定为C．brachiata Thunb.,也将后者作为C．orientalis L．的亚种处理;(d)将C．ibarensis Baker(具一回羽状复叶和两性花)这一拉丁学名用在了另一特产马达加斯加具2～3回羽状复叶和单性花、应属于单性铁线莲组sect． Aspidanthera的种(C．rutoides W．T．Wang)之上;(e)将另一特产马达加斯加具一回羽状复叶和单性花、 也属于单性铁线莲组的C．edentata Baker(＝C．insidiosa Baill．)降级作为这两位学者曲解的C．ibarensis Baker的亚种处理;(f)将特产马达加斯加的C．dissecta Baker归并到属于茴芹叶铁线莲组(sect． Pseudanemone)的C．pimpindllifolia Hook．中。此次本文第五部分继去年第一、二部分之后对上述混乱情况做出了完全澄清,并给出了分布于马达加斯加及其邻近岛屿的怀特铁线莲亚组8种植物的检索表;由于C．ibarensis Baker的定义被上述两位学者严重误解,本文根据较多具花、果的标本写出了此种完整、正确的形态描述。     

青岩油杉的核型分析

本文报道了青岩油杉（Ｋｅｔｅｌｅｒｉａｄａｖｉｄｉａｎａｖａｒ．ｃｈｉｅｎ－ｐｅｉ（Ｆｌｏｕｓ）ＣｈｅｎｇｅｔＬ．Ｋ．Ｆｕ）的染色体数目及核型,并与铁坚杉（Ｋ．ｄａｖｉｄｉａｎａ）和台湾油杉（Ｋ．ｄａｖｉｄｉａｎａｖａｒ．ｆｏｒｍｏｓａｎａ．）的核型进行了比较,讨论了三种油杉核型进化趋势,提出了铁坚杉种群的变异及进化趋势为南面的类型比北面的类型进化。     

Dynamics of a minimal neural model consisting of an astrocyte,a neuron,and an interneuron

In this paper, a biophysical neural network model consisting of a pyramidal neuron, an interneuron, and the astrocyte is studied. The corresponding dynamical properties are mainly investigated by using numerical simulations. The results show that the presence of the adenosine triphosphate and of the interneuron impacts the overall neural activity. It is shown that the fluxes of calcium through the cellular membrane strongly affect the modulation of the neural activity arising from the astrocyte.     

Influence of noise on the function of a “physiological” neural network

A model neural network with stochastic elements in its millisecond dynamics is investigated. The network consists of neuronal units which are modelled in close analogy to physiological neurons. Dynamical variables of the network are the cellular potentials, axonic currents and synaptic efficacies. The dynamics of the synapses obeys a modified Hebbian rule and, as proposed by v. d. Malsburg (1981, 1985), develop on a time scale of a tenth of a second. In a previous publication (Buhmann and Schulten 1986) we have confirmed that the resulting noiseless autoassociative network is capable of the well-known computational tasks of formal associative networks (Cooper 1973; Kohonen et al. 1984, 1981; Hopfield 1982). In the present paper we demonstrate that random fluctuations of the membrane potential improve the performance of the network. In comparison to a deterministic network a noisy neural network can learn at lower input frequencies and with lower average neural firing rates. The electrical activity of a noisy network is very reminiscent of that observed by physiological recordings. We demonstrate furthermore that associative storage reduces the effective dimension of the phase space in which the electrical activity of the network develops.     

Cytoskeletal involvement in neuronal learning: a review

This paper introduces the ideas of neural networks in the context of currently recognized cellular structures within neurons. Neural network models and paradigms require adaptation of synapses for learning to occur in the network. Some models of learning paradigms require information to move from axon to dendrite. This motivated us to examine the possibility of intracellular signaling to mediate such signals. The cytoskeleton forms a substrate for intracellular signaling via material transport and other putative mechanisms. Furthermore, many experimental results suggest a link between the cytoskeleton and cognitive processing. In this paper we review research on intracellular signaling in the context of neural network learning.Abbreviations MT microtubule - MTs microtubules - ART adaptive resonance theory - RCE restricted coulomb energy - MAP microtubule associated protein - NO nitric oxide Correspondence to: J. Dayhoff     

A simulation method for the firing sequences of motor units.

The firing sequences of motoneurons contain important information with regard to the underlying neural processes. Several methods have been proposed in the literature to simulate these sequences, however, one of the limitations is that they are not capable of simulating the complex neural dynamics of motor neurons, especially those of concurrently active ones, such as motor unit synchrony and motor unit common drive. In this paper, a novel model based on the Hodgkin-Huxley (HH) system is proposed, which has the ability to simulate the complex neurodynamics of the firing sequences of motor neurons. The model is presented at the cellular level and network level, and some simulation results from a simple 3-neuron network are presented to demonstrate its applications.     

Realization of couplings in a polynomial type mixed-mode cellular neural network

In this paper realization of couplings between cells in a polynomial type mixed-mode cellular neural network (CNN) is analyzed. The choice of the multiplier is discussed and two multiplier types are analyzed. Also, two circuits for generating the second and third order polynomial terms of cell output are described. The accuracy of the multipliers and polynomial circuits at the presence of device mismatch is analyzed.     

Neural network modeling in optimisation of continuous fermentation processes

The capability of self-recurrent neural networks in dynamic modeling of continuous fermentation is investigated in this simulation study. In the past, feedforward neural networks have been successfully used as one-step-ahead predictors. However, in steady-state optimisation of continuous fermentations the neural network model has to be iterated to predict many time steps ahead into the future in order to get steady-state values of the variables involved in objective cost function, and this iteration may result in increasing errors. Therefore, as an alternative to classical feedforward neural network trained by using backpropagation method, self-recurrent multilayer neural net trained by backpropagation through time method was chosen in order to improve accuracy of long-term predictions. Prediction capabilities of the resulting neural network model is tested by implementing this into the Integrated System Optimisation and Parameter Estimation (ISOPE) optimisation algorithm. Maximisation of cellular productivity of the baker's yeast continuous fermentation was used as the goal of the proposed optimising control problem. The training and prediction results of proposed neural network and performances of resulting optimisation structure are demonstrated.     

Macroscopic coherent structures in a stochastic neural network: from interface dynamics to coarse-grained bifurcation analysis

Journal of Mathematical Biology - We study coarse pattern formation in a cellular automaton modelling a spatially-extended stochastic neural network. The model, originally proposed by Gong and...     

CMOS realization of a 2-layer CNN universal machine chip

Some features of the biological retina can be modelled by a 2-layer cellular neural network (CNN) composed of locally connected elementary nonlinear processors. In order to explore these complex spatiotemporal dynamics for image processing, a prototype chip has been designed and fabricated in a 0.5 microm CMOS technology. Design challenges, trade-offs, the building blocks and the tests results for this system with 0.5 x 10(6) transistors, most of them operating in analog mode, are presented in this paper.     

An improved genetic algorithm based fuzzy-tuned neural network

This paper presents a fuzzy-tuned neural network, which is trained by an improved genetic algorithm (GA). The fuzzy-tuned neural network consists of a neural-fuzzy network and a modified neural network. In the modified neural network, a neuron model with two activation functions is used so that the degree of freedom of the network function can be increased. The neural-fuzzy network governs some of the parameters of the neuron model. It will be shown that the performance of the proposed fuzzy-tuned neural network is better than that of the traditional neural network with a similar number of parameters. An improved GA is proposed to train the parameters of the proposed network. Sets of improved genetic operations are presented. The performance of the improved GA will be shown to be better than that of the traditional GA. Some application examples are given to illustrate the merits of the proposed neural network and the improved GA.     

Attractability and location of equilibrium point of cellular neural networks with time-varying delays

This paper presents new theoretical results on global exponential stability of cellular neural networks with time-varying delays. The stability conditions depend on external inputs, connection weights and delays of cellular neural networks. Using these results, global exponential stability of cellular neural networks can be derived, and the estimate for location of equilibrium point can also be obtained. Finally, the simulating results demonstrate the validity and feasibility of our proposed approach.