Seasonality of delta C-13 and C/N ratios in modern and mid-holocene sediments in the Severn Estuary levels, SW Britain

Bulk organic VC and C/N ratios from mid-Holocene salt-marsh deposits with sedimentary banding reveal subtle but significant differences between coarse- and fine-grained deposits. These are consistent with findings from seasonally sampled modern silts, and with the interpretation, on physical and palynological grounds, of the fine-grained and coarse-grained components as warm-season and cold-season deposits, respectively. The control is considered to be seasonal variations in the character of the organic matter supplied.

Change in the effect of constant photoperiods on the rate of sexual maturation in modern genotypes of domestic pullet

1. Data for modern egg-type hybrids reared on constant daylengths show that, as expected, they mature more quickly than earlier genotypes. However, the constant photoperiod which gives earliest sexual maturity has not changed as a result of selection and is 10 h for both early and modern genotypes. 2. Further analysis showed that the rate of delay in sexual maturity for constant photoperiods above 10 h is similar for modern and for early hybrids ( +0.29 d for each incremental one hour of photoperiod), the response of modern hybrids below 10 h ( +4.22 d for each one-hour reduction in photoperiod) is more than double that of early hybrids ( +1.71 d/h).

Science in modern poetry: new directions

An edited collection of essays by the leading scholars in the field on science in poetry from 1900 to the present. This is a collection of research essays, not a companion. The introduction (pp. 1-15) and one of the 12 main chapters, 'From Bergson to Darwin: Evolutionary Biology in the Poetry of Judith Wright' (pp. 194-209), are by the editor.

Inverse problems in neural field theory

We study inverse problems in neural field theory, i.e., the construction of synaptic weight kernels yielding a prescribed neural field dynamics. We address the issues of existence, uniqueness, and stability of solutions to the inverse problem for the Amari neural field equation as a special case, and prove that these problems are generally ill-posed. In order to construct solutions to the inverse problem, we first recast the Amari equation into a linear perceptron equation in an infinite-dimensional Banach or Hilbert space. In a second step, we construct sets of biorthogonal function systems allowing the approximation of synaptic weight kernels by a generalized Hebbian learning rule. Numerically, this construction is implemented by the Moore–Penrose pseudoinverse method. We demonstrate the instability of these solutions and use the Tikhonov regularization method for stabilization and to prevent numerical overfitting. We illustrate the stable construction of kernels by means of three instructive examples.

Plant–pathogen interactions: disease resistance in modern agriculture

The growing human population will require a significant increase in agricultural production. This challenge is made more difficult by the fact that changes in the climatic and environmental conditions under which crops are grown have resulted in the appearance of new diseases, whereas genetic changes within the pathogen have resulted in the loss of previously effective sources of resistance. To help meet this challenge, advanced genetic and statistical methods of analysis have been used to identify new resistance genes through global screens, and studies of plant-pathogen interactions have been undertaken to uncover the mechanisms by which disease resistance is achieved. The informed deployment of major, race-specific and partial, race-nonspecific resistance, either by conventional breeding or transgenic approaches, will enable the production of crop varieties with effective resistance without impacting on other agronomically important crop traits. Here, we review these recent advances and progress towards the ultimate goal of developing disease-resistant crops.

Self-organized 40Hz synchronization in a physiological theory of EEG

We present evidence that large-scale spatial coherence of 40 Hz oscillations can emerge dynamically in a cortical mean field theory. The simulated synchronization time scale is about 150 ms, which compares well with experimental data on large-scale integration during cognitive tasks. The same model has previously provided consistent descriptions of the human EEG at rest, with tranquilizers, under anesthesia, and during anesthetic-induced epileptic seizures. The emergence of coherent gamma band activity is brought about by changing just one physiological parameter until cortex becomes marginally unstable for a small range of wavelengths. This suggests for future study a model of dynamic computation at the edge of cortical stability.