Curvature Induced by Amyloplast Magnetophoresis in Protonemata of the Moss Ceratodon purpureus1

After gravistimulation of Ceratodon purpureus (Hedw.) Brid. protonemata in the dark, amyloplast sedimentation was followed by upward curvature in the wild-type (WT) and downward curvature in the wwr mutant (wrong way response). We used ponderomotive forces induced by high-gradient magnetic fields (HGMF) to simulate the effect of gravity and displace the presumptive statoliths. The field was applied by placing protonemata either between two permanent magnets at the edge of the gap, close to the edge of a magnetized ferromagnetic wedge, or close to a small (<1 mm) permanent magnet. Continuous application of an HGMF in all three configurations resulted in plastid displacement and induced curvature in tip cells of WT and wwr protonemata. WT cells curved toward the HGMF, and wwr cells curved away from the HGMF, comparable to gravitropism. Plastids isolated from protonemal cultures had densities ranging from 1.24 to 1.38 g cm−3. Plastid density was similar for both genotypes, but the mutant contained larger plastids than the WT. The size difference might explain the stronger response of the wwr protonemata to the HGMF. Our data support the plastid-based theory of gravitropic sensing and suggest that HGMF-induced ponderomotive forces can substitute for gravity.

Autonomic Straightening after Gravitropic Curvature of Cress Roots1

Few studies have documented the response of gravitropically curved organs to a withdrawal of a constant gravitational stimulus. The effects of stimulus withdrawal on gravitropic curvature were studied by following individual roots of cress (Lepidium sativum L.) through reorientation and clinostat rotation. Roots turned to the horizontal curved down 62° and 88° after 1 and 5 h, respectively. Subsequent rotation on a clinostat for 6 h resulted in root straightening through a loss of gravitropic curvature in older regions and through new growth becoming aligned closer to the prestimulus vertical. However, these roots did not return completely to the prestimulus vertical, indicating the retention of some gravitropic response. Clinostat rotation shifted the mean root angle −36° closer to the prestimulus vertical, regardless of the duration of prior horizontal stimulation. Control roots (no horizontal stimulation) were slanted at various angles after clinostat rotation. These findings indicate that gravitropic curvature is not necessarily permanent, and that the root retains some commitment to its equilibrium orientation prior to gravitropic stimulation.

The effects of sequence context on DNA curvature.

Recent experiments have exposed significant discrepancies between experimental data and predictive models for DNA structure. These results strongly suggest that DNA structural parameters incorporated in the models are not always sufficient to account for the influence of sequence context and of specific ion effects. In an attempt to evaluate these two effects, we have investigated repetitive DNA sequences with the sequence motif GAGAG.CTCTC located in different helical phasing arrangements with respect to poly(A) tracts and GGGCCC.GGGCCC sequence motifs. Methods used are ligase-mediated cyclization and gel mobility experiments along with DNase I cutting and chemical probe studies. The results provide new evidence for curvature in poly(A) tracts. They also show that the sequence context in which bending and flexible sequence elements are found is an important aspect of sequence-dependent DNA conformation. Although dinucleotide models generally have good predictive power, this work demonstrates that in some instances sequence elements larger than the dinucleotide must be taken into account, and hence it provides a starting point for the appropriate modification and refinement of existing structural models for DNA.

Image processing via level set curvature flow.

We present a controlled image smoothing and enhancement method based on a curvature flow interpretation of the geometric heat equation. Compared to existing techniques, the model has several distinct advantages. (i) It contains just one enhancement parameter. (ii) The scheme naturally inherits a stopping criterion from the image; continued application of the scheme produces no further change. (iii) The method is one of the fastest possible schemes based on a curvature-controlled approach.

A constant radius of curvature model for the organization of DNA in toroidal condensates.

Toroidal DNA condensates have received considerable attention for their possible relationship to the packaging of DNA in viruses and in general as a model of ordered DNA condensation. A spool-like model has primarily been supported for DNA organization within toroids. However, our observations suggest that the actual organization may be considerably different. We present an alternate model in which DNA for a given toroid is organized within a series of equally sized contiguous loops that precess about the toroid axis. A related model for the toroid formation process is also presented. This kinetic model predicts a distribution of toroid sizes for DNA condensed from solution that is in good agreement with experimental data.

The elements of the differential calculus, comprehending the general theory of curve surfaces, and of curves of double curvature. Intended for the use of mathematical students in schools and universities.

Available on demand as hard copy or computer file from Cornell University Library.

A treatise on analytical geometry of three dimensions : containing the theory of curve surfaces and of curves of double curvature /

Mode of access: Internet.

Pore size characterization of mesoporous materials by a thermodynamic approach: A curvature-dependent solid-fluid potential

A thermodynamic analysis of nitrogen adsorption in cylindrical pores of MCM-41 and SBA-15 samples at 77 K is presented within the framework of the Broekhoff and de Boer (BdB) theory. We accounted for the effect of the solid surface curvature on the potential exerted by the pore walls. The developed model is in quantitative agreement with the non-local density functional theory (NLDFT) for pores larger than 2 tun. This modified BdB theory accounting for the Curvature Dependent Potential (CDP-BdB) was applied to determine the pore size distribution (PSD) of a number of MCM-41 and SBA-15 samples on the basis of matching the equilibrium theoretical isotherm against the adsorption branch of the experimental isotherm. In all cases investigated the PSDs determined with the new approach are very similar to those determined with the non-local density functional theory also using the same basis of matching of theoretical isotherm against the experimental adsorption branch. The developed continuum theory is very simple in its utilization, suggesting that CDP-BdB could be used as an alternative tool to obtain PSD for mesoporous solids from the analysis of adsorption branch of adsorption isotherms of any sub-critical fluids.

A Bayesian approach to imposing curvature on distance functions

The estimated parameters of output distance functions frequently violate the monotonicity, quasi-convexity and convexity constraints implied by economic theory, leading to estimated elasticities and shadow prices that are incorrectly signed, and ultimately to perverse conclusions concerning the effects of input and output changes on productivity growth and relative efficiency levels. We show how a Bayesian approach can be used to impose these constraints on the parameters of a translog output distance function. Implementing the approach involves the use of a Gibbs sampler with data augmentation. A Metropolis-Hastings algorithm is also used within the Gibbs to simulate observations from truncated pdfs. Our methods are developed for the case where panel data is available and technical inefficiency effects are assumed to be time-invariant. Two models-a fixed effects model and a random effects model-are developed and applied to panel data on 17 European railways. We observe significant changes in estimated elasticities and shadow price ratios when regularity restrictions are imposed. (c) 2004 Elsevier B.V. All rights reserved.

Curvature-driven smoothing: a learning algorithm for feed-forward networks

The performance of feed-forward neural networks in real applications can be often be improved significantly if use is made of a-priori information. For interpolation problems this prior knowledge frequently includes smoothness requirements on the network mapping, and can be imposed by the addition to the error function of suitable regularization terms. The new error function, however, now depends on the derivatives of the network mapping, and so the standard back-propagation algorithm cannot be applied. In this paper, we derive a computationally efficient learning algorithm, for a feed-forward network of arbitrary topology, which can be used to minimize the new error function. Networks having a single hidden layer, for which the learning algorithm simplifies, are treated as a special case.

Incorporating curvature information into on-line learning

We analyse the dynamics of a number of second order on-line learning algorithms training multi-layer neural networks, using the methods of statistical mechanics. We first consider on-line Newton's method, which is known to provide optimal asymptotic performance. We determine the asymptotic generalization error decay for a soft committee machine, which is shown to compare favourably with the result for standard gradient descent. Matrix momentum provides a practical approximation to this method by allowing an efficient inversion of the Hessian. We consider an idealized matrix momentum algorithm which requires access to the Hessian and find close correspondence with the dynamics of on-line Newton's method. In practice, the Hessian will not be known on-line and we therefore consider matrix momentum using a single example approximation to the Hessian. In this case good asymptotic performance may still be achieved, but the algorithm is now sensitive to parameter choice because of noise in the Hessian estimate. On-line Newton's method is not appropriate during the transient learning phase, since a suboptimal unstable fixed point of the gradient descent dynamics becomes stable for this algorithm. A principled alternative is to use Amari's natural gradient learning algorithm and we show how this method provides a significant reduction in learning time when compared to gradient descent, while retaining the asymptotic performance of on-line Newton's method.

Phakometric measurement of ocular surface radii of curvature, axial separations and alignment in relaxed and accommodated human eyes

Measurements (autokeratometry, A-scan ultrasonography and video ophthalmophakometry) of ocular surface radii, axial separations and alignment were made in the horizontal meridian of nine emmetropes (aged 20-38 years) with relaxed (cycloplegia) and active accommodation (mean ± 95% confidence interval: 3.7 ± 1.1 D). The anterior chamber depth (-1.5 ± 0.3 D) and both crystalline lens surfaces (front 3.1 ± 0.8 D; rear 2.1 ± 0.6 D) contributed to dioptric vergence changes that accompany accommodation. Accommodation did not alter ocular surface alignment. Ocular misalignment in relaxed eyes is mainly because of eye rotation (5.7 ± 1.6° temporally) with small amounts of lens tilt (0.2 ± 0.8° temporally) and decentration (0.1 ± 0.1 mm nasally) but these results must be viewed with caution as we did not account for corneal asymmetry. Comparison of calculated and empirically derived coefficients (upon which ocular surface alignment calculations depend) revealed that negligible inherent errors arose from neglect of ocular surface asphericity, lens gradient refractive index properties, surface astigmatism, effects of pupil size and centration, assumed eye rotation axis position and use of linear equations for analysing Purkinje image shifts. © 2004 The College of Optometrists.

Phakometric measurement of ocular surface radius of curvature and alignment: evaluation of method with physical model eyes

Ophthalmophakometric measurements of ocular surface radius of curvature and alignment were evaluated on physical model eyes encompassing a wide range of human ocular dimensions. The results indicated that defocus errors arising from imperfections in the ophthalmophakometer camera telecentricity and light source collimation were smaller than experimental errors. Reasonable estimates emerged for anterior lens surface radius of curvature (accuracy: 0.02–0.10 mm; precision 0.05–0.09 mm), posterior lens surface radius of curvature (accuracy: 0.10–0.55 mm; precision 0.06–0.20 mm), eye rotation (accuracy: 0.00–0.32°; precision 0.06–0.25°), lens tilt (accuracy: 0.00–0.33°; precision 0.05–0.98°) and lens decentration (accuracy: 0.00–0.07 mm; precision 0.00–0.07 mm).