Isolation, characterization and electron microscopic single particle analysis of the NADH : ubiquinone oxidoreductase (complex I) from the hyperthermophilic eubacterium Aquifex aeolicus

The proton-translocating NADH:ubiquinone oxidoreductase (complex I) has been purified from Aquifex aeolicus, a hyperthermophilic eubacterium of known genome sequence. The purified detergent solubilized enzyme is highly active above 50 degreesC. The specific activity for electron transfer from NADH to decylubiquinone is 29 U/mg at 80 degreesC. The A. aeolicus complex I is completely sensitive to rotenone and 2-n-decyl-quinazoline-4-yl-amine. SDS polyacrylamide gel electrophoresis shows that it may contain up to 14 subunits. N-terminal amino acid sequencing of the bands indicates the presence of a stable subcomplex, which is composed of subunits E, F, and G. The isolated complex is highly stable and active in a temperature range from 50 to 90 degreesC, with a half-life of about 10 h at 80 degreesC. The activity shows a linear Arrhenius plot at 50-85 degreesC with an activation energy at 31.92 J/mol K. Single particle electron microscopy shows that the A. aeolicus complex I has the typical L-shape. However, visual inspection of averaged images reveals many more details in the external arm of the complex than has been observed for complex I from other sources. In addition, the angle (90degrees) between the cytoplasmic peripheral arm and the membrane intrinsic arm of the complex appears to be invariant.

基于ARM的可编程控制系统实现

采用ARM设计小型可编程控制器,提供基于以太网和OPC标准的组态监控接口。用户采用符合IEC61131-3标准的梯形图方式对控制器自由编程,并通过计算机网络对其进行程序调试、下载和数据通信,从而实现了一套经济实用的小型可编程控制系统。

ARM处理器在AFM纳米操作系统中的应用

文章介绍了在原子力显微镜(AFM)纳米操作系统中ARM处理器的应用及开发,在此基础上搭建了具有3D力反馈的纳米操作系统。结合AFM纳米操作系统的实时性问题,进行了ARM开发板的系统软件架构和PSD(四象限光电检测器)信号的PID控制结果的分析,使纳米操作系统在实时性和成像的质量等方面都得到相应改进。

Recognition of Surface Reflectance Properties from a Single Image under Unknown Real-World Illumination

This paper describes a machine vision system that classifies reflectance properties of surfaces such as metal, plastic, or paper, under unknown real-world illumination. We demonstrate performance of our algorithm for surfaces of arbitrary geometry. Reflectance estimation under arbitrary omnidirectional illumination proves highly underconstrained. Our reflectance estimation algorithm succeeds by learning relationships between surface reflectance and certain statistics computed from an observed image, which depend on statistical regularities in the spatial structure of real-world illumination. Although the algorithm assumes known geometry, its statistical nature makes it robust to inaccurate geometry estimates.

Virtual Visual Hulls: Example-Based 3D Shape Estimation from a Single Silhouette

Recovering a volumetric model of a person, car, or other object of interest from a single snapshot would be useful for many computer graphics applications. 3D model estimation in general is hard, and currently requires active sensors, multiple views, or integration over time. For a known object class, however, 3D shape can be successfully inferred from a single snapshot. We present a method for generating a ``virtual visual hull''-- an estimate of the 3D shape of an object from a known class, given a single silhouette observed from an unknown viewpoint. For a given class, a large database of multi-view silhouette examples from calibrated, though possibly varied, camera rigs are collected. To infer a novel single view input silhouette's virtual visual hull, we search for 3D shapes in the database which are most consistent with the observed contour. The input is matched to component single views of the multi-view training examples. A set of viewpoint-aligned virtual views are generated from the visual hulls corresponding to these examples. The 3D shape estimate for the input is then found by interpolating between the contours of these aligned views. When the underlying shape is ambiguous given a single view silhouette, we produce multiple visual hull hypotheses; if a sequence of input images is available, a dynamic programming approach is applied to find the maximum likelihood path through the feasible hypotheses over time. We show results of our algorithm on real and synthetic images of people.

A Coupled Multi-ALU Processing Node for a Highly Parallel Computer

This report describes Processor Coupling, a mechanism for controlling multiple ALUs on a single integrated circuit to exploit both instruction-level and inter-thread parallelism. A compiler statically schedules individual threads to discover available intra-thread instruction-level parallelism. The runtime scheduling mechanism interleaves threads, exploiting inter-thread parallelism to maintain high ALU utilization. ALUs are assigned to threads on a cycle byscycle basis, and several threads can be active concurrently. Simulation results show that Processor Coupling performs well both on single threaded and multi-threaded applications. The experiments address the effects of memory latencies, function unit latencies, and communication bandwidth between function units.

The Definition and Implementation of a Computer Programming Language Based on Constraints

The constraint paradigm is a model of computation in which values are deduced whenever possible, under the limitation that deductions be local in a certain sense. One may visualize a constraint 'program' as a network of devices connected by wires. Data values may flow along the wires, and computation is performed by the devices. A device computes using only locally available information (with a few exceptions), and places newly derived values on other, locally attached wires. In this way computed values are propagated. An advantage of the constraint paradigm (not unique to it) is that a single relationship can be used in more than one direction. The connections to a device are not labelled as inputs and outputs; a device will compute with whatever values are available, and produce as many new values as it can. General theorem provers are capable of such behavior, but tend to suffer from combinatorial explosion; it is not usually useful to derive all the possible consequences of a set of hypotheses. The constraint paradigm places a certain kind of limitation on the deduction process. The limitations imposed by the constraint paradigm are not the only one possible. It is argued, however, that they are restrictive enough to forestall combinatorial explosion in many interesting computational situations, yet permissive enough to allow useful computations in practical situations. Moreover, the paradigm is intuitive: It is easy to visualize the computational effects of these particular limitations, and the paradigm is a natural way of expressing programs for certain applications, in particular relationships arising in computer-aided design. A number of implementations of constraint-based programming languages are presented. A progression of ever more powerful languages is described, complete implementations are presented and design difficulties and alternatives are discussed. The goal approached, though not quite reached, is a complete programming system which will implicitly support the constraint paradigm to the same extent that LISP, say, supports automatic storage management.

Single Mueller matrix description of the propagation of degree of polarisation in a uniformly anisotropic single-mode optical fibre

R. Zwiggelaar and M.G.F. Wilson, 'Single Mueller matrix description of the propagation of degree of polarisation in a uniformly anisotropic single-mode optical fibre', IEE Proceedings Optoelectronics 141 (6), 367-372 (1994)

Estimating Human Body Pose from a Single Image via the Specialized Mappings Architecture

A non-linear supervised learning architecture, the Specialized Mapping Architecture (SMA) and its application to articulated body pose reconstruction from single monocular images is described. The architecture is formed by a number of specialized mapping functions, each of them with the purpose of mapping certain portions (connected or not) of the input space, and a feedback matching process. A probabilistic model for the architecture is described along with a mechanism for learning its parameters. The learning problem is approached using a maximum likelihood estimation framework; we present Expectation Maximization (EM) algorithms for two different instances of the likelihood probability. Performance is characterized by estimating human body postures from low level visual features, showing promising results.

A Self-Organizing Neural Model of Motor Equivalent Reaching and Tool Use by a Multijoint Arm

This paper describes a self-organizing neural model for eye-hand coordination. Called the DIRECT model, it embodies a solution of the classical motor equivalence problem. Motor equivalence computations allow humans and other animals to flexibly employ an arm with more degrees of freedom than the space in which it moves to carry out spatially defined tasks under conditions that may require novel joint configurations. During a motor babbling phase, the model endogenously generates movement commands that activate the correlated visual, spatial, and motor information that are used to learn its internal coordinate transformations. After learning occurs, the model is capable of controlling reaching movements of the arm to prescribed spatial targets using many different combinations of joints. When allowed visual feedback, the model can automatically perform, without additional learning, reaches with tools of variable lengths, with clamped joints, with distortions of visual input by a prism, and with unexpected perturbations. These compensatory computations occur within a single accurate reaching movement. No corrective movements are needed. Blind reaches using internal feedback have also been simulated. The model achieves its competence by transforming visual information about target position and end effector position in 3-D space into a body-centered spatial representation of the direction in 3-D space that the end effector must move to contact the target. The spatial direction vector is adaptively transformed into a motor direction vector, which represents the joint rotations that move the end effector in the desired spatial direction from the present arm configuration. Properties of the model are compared with psychophysical data on human reaching movements, neurophysiological data on the tuning curves of neurons in the monkey motor cortex, and alternative models of movement control.

Paclitaxel versus doxorubicin as first-line single-agent chemotherapy for metastatic breast cancer: a European Organization for Research and Treatment of Cancer Randomized Study with cross-over.

PURPOSE: To compare the efficacy of paclitaxel versus doxorubicin given as single agents in first-line therapy of advanced breast cancer (primary end point, progression-free survival ¿PFS) and to explore the degree of cross-resistance between the two agents. PATIENTS AND METHODS: Three hundred thirty-one patients were randomized to receive either paclitaxel 200 mg/m(2), 3-hour infusion every 3 weeks, or doxorubicin 75 mg/m(2), intravenous bolus every 3 weeks. Seven courses were planned unless progression or unacceptable toxicity occurred before the seven courses were finished. Patients who progressed within the seven courses underwent early cross-over to the alternative drug, while a delayed cross-over was optional for the remainder of patients at the time of disease progression. RESULTS: Objective response in first-line therapy was significantly better (P =.003) for doxorubicin (response rate ¿RR, 41%) than for paclitaxel (RR, 25%), with doxorubicin achieving a longer median PFS (7.5 months for doxorubicin v 3.9 months for paclitaxel, P <.001). In second-line therapy, cross-over to doxorubicin (91 patients) and to paclitaxel (77 patients) gave response rates of 30% and 16%, respectively. The median survival durations of 18.3 months for doxorubicin and 15.6 months for paclitaxel were not significantly different (P =.38). The doxorubicin arm had greater toxicity, but this was counterbalanced by better symptom control. CONCLUSION: At the dosages and schedules used in the present study, doxorubicin achieves better disease and symptom control than paclitaxel in first-line treatment. Doxorubicin and paclitaxel are not totally cross-resistant, which supports further investigation of these drugs in combination or in sequence, both in advanced disease and in the adjuvant setting.

Stream segregation on a single electrode as a function of pulse rate in cochlear implant listeners.

While cochlear implants (CIs) usually provide high levels of speech recognition in quiet, speech recognition in noise remains challenging. To overcome these difficulties, it is important to understand how implanted listeners separate a target signal from interferers. Stream segregation has been studied extensively in both normal and electric hearing, as a function of place of stimulation. However, the effects of pulse rate, independent of place, on the perceptual grouping of sequential sounds in electric hearing have not yet been investigated. A rhythm detection task was used to measure stream segregation. The results of this study suggest that while CI listeners can segregate streams based on differences in pulse rate alone, the amount of stream segregation observed decreases as the base pulse rate increases. Further investigation of the perceptual dimensions encoded by the pulse rate and the effect of sequential presentation of different stimulation rates on perception could be beneficial for the future development of speech processing strategies for CIs.

Of Mice and Men: An Ergonomic and Market Assessment of Current Computer Mice

Gemstone Team MICE (Modifying and Improving Computer Ergonomics)

Magnetophoretic circuits for digital control of single particles and cells.

The ability to manipulate small fluid droplets, colloidal particles and single cells with the precision and parallelization of modern-day computer hardware has profound applications for biochemical detection, gene sequencing, chemical synthesis and highly parallel analysis of single cells. Drawing inspiration from general circuit theory and magnetic bubble technology, here we demonstrate a class of integrated circuits for executing sequential and parallel, timed operations on an ensemble of single particles and cells. The integrated circuits are constructed from lithographically defined, overlaid patterns of magnetic film and current lines. The magnetic patterns passively control particles similar to electrical conductors, diodes and capacitors. The current lines actively switch particles between different tracks similar to gated electrical transistors. When combined into arrays and driven by a rotating magnetic field clock, these integrated circuits have general multiplexing properties and enable the precise control of magnetizable objects.

Comparative analyses of seven algorithms for copy number variant identification from single nucleotide polymorphism arrays.

Determination of copy number variants (CNVs) inferred in genome wide single nucleotide polymorphism arrays has shown increasing utility in genetic variant disease associations. Several CNV detection methods are available, but differences in CNV call thresholds and characteristics exist. We evaluated the relative performance of seven methods: circular binary segmentation, CNVFinder, cnvPartition, gain and loss of DNA, Nexus algorithms, PennCNV and QuantiSNP. Tested data included real and simulated Illumina HumHap 550 data from the Singapore cohort study of the risk factors for Myopia (SCORM) and simulated data from Affymetrix 6.0 and platform-independent distributions. The normalized singleton ratio (NSR) is proposed as a metric for parameter optimization before enacting full analysis. We used 10 SCORM samples for optimizing parameter settings for each method and then evaluated method performance at optimal parameters using 100 SCORM samples. The statistical power, false positive rates, and receiver operating characteristic (ROC) curve residuals were evaluated by simulation studies. Optimal parameters, as determined by NSR and ROC curve residuals, were consistent across datasets. QuantiSNP outperformed other methods based on ROC curve residuals over most datasets. Nexus Rank and SNPRank have low specificity and high power. Nexus Rank calls oversized CNVs. PennCNV detects one of the fewest numbers of CNVs.