A new species of Saussurea (Asteraceae) from Tibet and its systematic position based on ITS sequence analysis

A new species of Saussurea, S. erecta S. W Liu, J. T Pan A J. Q. Liu sp. nov., is described from Tibet. It resembles S. kingii but may be distinguished by having distinct stems and glabrous achenes. Saussurea kingii was placed in sect. Pseudoeriocoryne of subgen. Eriocoryne; this section was circumscribed by acaulescence and an inflorescence with congested capitula surrounded by a rosette of leaves. The discovery of S. erecta with distinct stems, cauline leaves and corymbose capitula blurred the delimitation of sect. Pseudoeriocoryne and suggested that the section may be polyphyletic. Both the close relationship and the significant difference between S. erecta and S. kingii were confirmed by analyses of nrDNA ITS sequences. The resulting phylogenies based on ITS data further suggest that Saussurea sect. Pseudoeriocoryne, as traditionally defined, does not constitute a monophyletic group. The rapid radiation and speciation of Saussurea in the Qinghai-Tibetan Plateau, as inferred from ITS phylogeny, are discussed. (c) 2005 The Linnean Society of London.

大洋有孔虫微量元素研究

The most novel aspect of this thesis is the combination analysis of the boron isotopes and trace elements. What’s more, it also provides a reliable analytical technique, which is suitable for both boron isotopes and trace elements. Al/Ca values can be used to monitor the clay removal during the sample preparation. It is found that when Al/Ca>100 mol/mol, the measured boron isotopic compositions are always several permil lower than those properly cleaned. B/Ca ratios can be used to calculate the exact boron loaded for each sample. Otherwise, too much loading will lead to too long time for the whole analytical sequence, and too less loading might incur serious blank problem. One other benefit besides those discussed above is that the combination analysis of boron isotopes and trace elements on the same sample allows reconstruction of the marine carbonate system and atmospheric pCO2 without assumption of the other parameter. In the marine carbonate system, with the seawater pH from the foraminiferal 11B, one has to make an assumption on the other variable to obtain the rest four variables. A series studies found that U/Ca and B/Ca are potential proxies for seawater [CO32-]and [HCO3-], respectively. Since they are measured on the same sample with boron isotopes, hence, there is no spatial or temporal ambiguity in the incorporation of the two controlling parameters. With 11B and U/Ca, the reconstructed atmospheric pCO2 variations match the atmospheric pCO2 record from the Vostok ice core within ±20 ppm. The incorporations of U and B into foraminiferal carbonates are controlled by the overall growth rate of individual foraminifers and other possible factors. The reliable application of these proxies still require further calibrations. In a similar fashion, the combination analysis of boron isotopes and Mg/Ca also has great advantages. Mg/Ca has been proved to be a reliable proxy for the surface seawater temperature. With the combination analysis, one can determine the phase between changes in atmospheric pCO2 and surface seawater temperature, thus explore the cause and mechanism of the changes in atmospheric pCO2. .

保重心脉冲压缩滤波及其在速度自动拾取中的应用

To pick velocity automatically is not only helpful to improve the efficiency of seismic data process, but also to provide quickly the initial velocity for prestack depth migration. In this thesis, we use the Viterbi algorithm to do automatic picking, but the velocity picked usually is immoderate. By thorough study and analysis, we think that the Viterbi algorithm has the function to do quickly and effectually automatic picking, but the data provided for picking maybe not continuous on derivative of its curved surface, viz., the curved face on velocity spectrum is not slick. Therefore, the velocity picked may include irrational velocity information. To solve the problem above, we develop a new method to filter signal by performing nonlinear transformation of coordinate and filter of function. Here, we call it as Gravity Center Preserved Pulse Compressed Filter (GCPPCF). The main idea to perform the GCPPCF as follows: separating a curve, such as a pulse, to several subsection, calculating the gravity center (coordinate displacement), and then assign the value (density) on the subsection to gravity center. When gravity center departure away from center of its subsection, the value assigned to gravity center is smaller than the actual one, but non other than gravity center anastomoses fully with its subsection center, the assigned value equal to the actual one. By doing so, the curve shape under new coordinate breadthwise narrows down compare to its original one. It is a process of nonlinear transformation of coordinate, due to gravity center changing with the shape of subsection. Furthermore, the gravity function is filter one, because it is a cause of filtering that the value assigned from subsection center to gravity center is obtained by calculating its weight mean of subsetion function. In addition, the filter has the properties of the adaptive time delay changed filter, owing to the weight coefficient used for weight mean also changes with the shape of subsection. In this thesis, the Viterbi algorithm inducted, being applied to auto pick the stack velocity, makes the rule to integral the max velocity spectrum ("energy group") forward and to get the optimal solution in recursion backward. It is a convenient tool to pick automatically velocity. The GCPPCF above not only can be used to preserve the position of peak value and compress the velocity spectrum, but also can be used as adaptive time delay changed filter to smooth object curved line or curved face. We apply it to smooth variable of sequence observed to get a favourable source data ta provide for achieving the final exact resolution. If there is no the adaptive time delay-changed filter to perform optimization, we can't get a finer source data and also can't valid velocity information, moreover, if there is no the Viterbi algorithm to do shortcut searching, we can't pick velocity automatically. Accordingly, combination of both of algorithm is to make an effective method to do automatic picking. We apply the method of automatic picking velocity to do velocity analysis of the wavefield extrapolated. The results calculated show that the imaging effect of deep layer with the wavefield extrapolated was improved dominantly. The GCPPCF above has achieved a good effect in application. It not only can be used to optimize and smooth velocity spectrum, but also can be used to perform a correlated process for other type of signal. The method of automatic picking velocity developed in this thesis has obtained favorable result by applying it to calculate single model, complicated model (Marmousi model) and also the practical data. The results show that it not only has feasibility, but also practicability.

Comonomer sequence distribution in metallocene-based ethylene/1-butene (S-34) and ethylene/1-hexene (S-43) copolymers

Metallocene based polyethylenes were prepared by SMOPEC's "metallocene adduct" technology in a gas phase fluidized bed model reactor. The C-13-NMR spectra of ethylene/1-butene (S-34) and ethylene/1-hexene(S-43) copolymers were studied in a manner analogous to that established by Hsieh and Cheng. The comonomer sequence distributions of copolymer samples were obtained. The results show that these metallocene based copolymers contain a small amount of butene and hexene, and the EE and EEE sequences are dominant.

Sequence-Seeking and Counter Streams: A Model for Information Processing in the Cortex

This paper presents a model for the general flow in the neocortex. The basic process, called "sequence-seeking," is a search for a sequence of mappings or transformations, linking source and target representations. The search is bi-directional, "bottom-up" as well as "top-down," and it explores in parallel a large numbe rof alternative sequences. This operation is implemented in a structure termed "counter streams," in which multiple sequences are explored along two separate, complementary pathways which seeking to meet. The first part of the paper discusses the general sequence-seeking scheme and a number of related processes, such as the learning of successful sequences, context effects, and the use of "express lines" and partial matches. The second part discusses biological implications of the model in terms of connections within and between cortical areas. The model is compared with existing data, and a number of new predictions are proposed.

A Note of Zipf's Law, Natural Languages, and Noncoding DNA Regions

In Phys. Rev. Letters (73:2), Mantegna et al. conclude on the basis of Zipf rank frequency data that noncoding DNA sequence regions are more like natural languages than coding regions. We argue on the contrary that an empirical fit to Zipf"s "law" cannot be used as a criterion for similarity to natural languages. Although DNA is a presumably "organized system of signs" in Mandelbrot"s (1961) sense, and observation of statistical featurs of the sort presented in the Mantegna et al. paper does not shed light on the similarity between DNA's "gramar" and natural language grammars, just as the observation of exact Zipf-like behavior cannot distinguish between the underlying processes of tossing an M-sided die or a finite-state branching process.

Homology Induction: the use of machine learning to improve sequence similarity searches

Karwath, A. King, R. Homology induction: the use of machine learning to improve sequence similarity searches. BMC Bioinformatics. 23rd April 2002. 3:11 Additional File Describes the title organims species declaration in one string [http://www.biomedcentral.com/content/supplementary/1471- 2105-3-11-S1.doc] Sponsorship: Andreas Karwath and Ross D. King were supported by the EPSRC grant GR/L62849.

The EXACT description of biomedical protocols

Soldatova, L. N., Aubrey, W., King, R. D., Clare, A. J. (2008). The EXACT description of biomedical protocols. Bioinformatics, 24 (13), i295-i303 Sponsorship: BBSRC / RAEng / EPSRC specialissue: ISMB

Learning styles and performance in the introductory programming sequence

Thomas, L., Ratcliffe, M., Woodbury, J., and Jarman, E. 2002. Learning styles and performance in the introductory programming sequence. SIGCSE Bull. 34, 1 (Mar. 2002), 33-37.

Analysis of Sequence Periodicity in E. coli Proteins: Empirical Investigation of the ?Duplication and Divergence? Theory of Protein Evolution

Gatherer, D., and McEwan, N.R. (2003). Analysis of sequence periodicity in E. coli proteins: empirical investigation of the 'duplication and divergence' theory of protein evolution. Journal of Molecular Evolution 57, 149-158. RAE2008

A Phylogenetic Mixture Model for Detecting Pattern-Heterogeneity in Gene Sequence or Character-State Data

Mark Pagel, Andrew Meade (2004). A phylogenetic mixture model for detecting pattern-heterogeneity in gene sequence or character-state data. Systematic Biology, 53(4), 571-581. RAE2008

From Parallel Sequence Representations to Calligraphic Control: A Conspiracy of Neural Circuits

Calligraphic writing presents a rich set of challenges to the human movement control system. These challenges include: initial learning, and recall from memory, of prescribed stroke sequences; critical timing of stroke onsets and durations; fine control of grip and contact forces; and letter-form invariance under voluntary size scaling, which entails fine control of stroke direction and amplitude during recruitment and derecruitment of musculoskeletal degrees of freedom. Experimental and computational studies in behavioral neuroscience have made rapid progress toward explaining the learning, planning and contTOl exercised in tasks that share features with calligraphic writing and drawing. This article summarizes computational neuroscience models and related neurobiological data that reveal critical operations spanning from parallel sequence representations to fine force control. Part one addresses stroke sequencing. It treats competitive queuing (CQ) models of sequence representation, performance, learning, and recall. Part two addresses letter size scaling and motor equivalence. It treats cursive handwriting models together with models in which sensory-motor tmnsformations are performed by circuits that learn inverse differential kinematic mappings. Part three addresses fine-grained control of timing and transient forces, by treating circuit models that learn to solve inverse dynamics problems.

SOVEREIGN: An Autonomous Neural System for Incrementally Learning Planned Action Sequence to Navigate Towards a Rewarded Goal

How do reactive and planned behaviors interact in real time? How are sequences of such behaviors released at appropriate times during autonomous navigation to realize valued goals? Controllers for both animals and mobile robots, or animats, need reactive mechanisms for exploration, and learned plans to reach goal objects once an environment becomes familiar. The SOVEREIGN (Self-Organizing, Vision, Expectation, Recognition, Emotion, Intelligent, Goaloriented Navigation) animat model embodies these capabilities, and is tested in a 3D virtual reality environment. SOVEREIGN includes several interacting subsystems which model complementary properties of cortical What and Where processing streams and which clarify similarities between mechanisms for navigation and arm movement control. As the animat explores an environment, visual inputs are processed by networks that are sensitive to visual form and motion in the What and Where streams, respectively. Position-invariant and sizeinvariant recognition categories are learned by real-time incremental learning in the What stream. Estimates of target position relative to the animat are computed in the Where stream, and can activate approach movements toward the target. Motion cues from animat locomotion can elicit head-orienting movements to bring a new target into view. Approach and orienting movements are alternately performed during animat navigation. Cumulative estimates of each movement are derived from interacting proprioceptive and visual cues. Movement sequences are stored within a motor working memory. Sequences of visual categories are stored in a sensory working memory. These working memories trigger learning of sensory and motor sequence categories, or plans, which together control planned movements. Predictively effective chunk combinations are selectively enhanced via reinforcement learning when the animat is rewarded. Selected planning chunks effect a gradual transition from variable reactive exploratory movements to efficient goal-oriented planned movement sequences. Volitional signals gate interactions between model subsystems and the release of overt behaviors. The model can control different motor sequences under different motivational states and learns more efficient sequences to rewarded goals as exploration proceeds.

Exact Geosedics and Shortest Paths on Polyhedral Surface

We present two algorithms for computing distances along a non-convex polyhedral surface. The first algorithm computes exact minimal-geodesic distances and the second algorithm combines these distances to compute exact shortest-path distances along the surface. Both algorithms have been extended to compute the exact minimalgeodesic paths and shortest paths. These algorithms have been implemented and validated on surfaces for which the correct solutions are known, in order to verify the accuracy and to measure the run-time performance, which is cubic or less for each algorithm. The exact-distance computations carried out by these algorithms are feasible for large-scale surfaces containing tens of thousands of vertices, and are a necessary component of near-isometric surface flattening methods that accurately transform curved manifolds into flat representations.

Laminar Cortical Dynamics of Cognitive and Motor Working Memory, Sequence Learning and Performance: Toward a Unified Theory of How the Cerebral Cortex Works

How do the layered circuits of prefrontal and motor cortex carry out working memory storage, sequence learning, and voluntary sequential item selection and performance? A neural model called LIST PARSE is presented to explain and quantitatively simulate cognitive data about both immediate serial recall and free recall, including bowing of the serial position performance curves, error-type distributions, temporal limitations upon recall, and list length effects. The model also qualitatively explains cognitive effects related to attentional modulation, temporal grouping, variable presentation rates, phonemic similarity, presentation of non-words, word frequency/item familiarity and list strength, distracters and modality effects. In addition, the model quantitatively simulates neurophysiological data from the macaque prefrontal cortex obtained during sequential sensory-motor imitation and planned performance. The article further develops a theory concerning how the cerebral cortex works by showing how variations of the laminar circuits that have previously clarified how the visual cortex sees can also support cognitive processing of sequentially organized behaviors.