Simulating the effects of grassland management and grass ensiling on methane emission from lactating cows

A dynamic, mechanistic model of enteric fermentation was used to investigate the effect of type and quality of grass forage, dry matter intake (DMI) and proportion of concentrates in dietary dry matter (DM) on variation in methane (CH(4)) emission from enteric fermentation in dairy cows. The model represents substrate degradation and microbial fermentation processes in rumen and hindgut and, in particular, the effects of type of substrate fermented and of pH oil the production of individual volatile fatty acids and CH, as end-products of fermentation. Effects of type and quality of fresh and ensiled grass were evaluated by distinguishing two N fertilization rates of grassland and two stages of grass maturity. Simulation results indicated a strong impact of the amount and type of grass consumed oil CH(4) emission, with a maximum difference (across all forage types and all levels of DM 1) of 49 and 77% in g CH(4)/kg fat and protein corrected milk (FCM) for diets with a proportion of concentrates in dietary DM of 0.1 and 0.4, respectively (values ranging from 10.2 to 19.5 g CH(4)/kg FCM). The lowest emission was established for early Cut, high fertilized grass silage (GS) and high fertilized grass herbage (GH). The highest emission was found for late cut, low-fertilized GS. The N fertilization rate had the largest impact, followed by stage of grass maturity at harvesting and by the distinction between GH and GS. Emission expressed in g CH(4)/kg FCM declined oil average 14% with an increase of DMI from 14 to 18 kg/day for grass forage diets with a proportion of concentrates of 0.1, and on average 29% with an increase of DMI from 14 to 23 kg/day for diets with a proportion of concentrates of 0.4. Simulation results indicated that a high proportion of concentrates in dietary DM may lead to a further reduction of CH, emission per kg FCM mainly as a result of a higher DM I and milk yield, in comparison to low concentrate diets. Simulation results were evaluated against independent data obtained at three different laboratories in indirect calorimetry trials with COWS consuming GH mainly. The model predicted the average of observed values reasonably, but systematic deviations remained between individual laboratories and root mean squared prediction error was a proportion of 0.12 of the observed mean. Both observed and predicted emission expressed in g CH(4)/kg DM intake decreased upon an increase in dietary N:organic matter (OM) ratio. The model reproduced reasonably well the variation in measured CH, emission in cattle sheds oil Dutch dairy farms and indicated that oil average a fraction of 0.28 of the total emissions must have originated from manure under these circumstances.

Do designers show categorical perception of typefaces?

Readers need to easily discriminate between different letters, so typefaces are designed to make these differences distinctive. But there is also a uniformity of style within a typeface. These styles are recognised by typographic designers and may be categorised to enable more efficient discrimination among typefaces. The manner in which designers perceive typefaces is explored using the paradigm of Categorical Perception (CP). A continuum of fonts is created by interpolating between two typefaces and two tasks (identification and discrimination) are used to test for CP. As the application of CP to typefaces is a new approach, various methodological issues are pursued. The experiments reveal that the conditions required to demonstrate CP are quite specific and CP was only evident in Times and Helvetica and not Garamond and Bodoni. Possible reasons for this difference are the characteristics of the two typefaces and their context of use. Speculation as to the purpose of CP in non-designers raises the under-researched question of how we identify letters in different typefaces when reading.

Rethinking 'Inside the Visible'

This essay appears in the first book to examine feminist curatorship in the last 40 years. It undertakes an extended reading of Cathy de Zegher's influential exhibition, Inside the Visible, An Elliptical Traverse of 20th Century Art. In, of and From the Feminine (1995) which proposed that modern art should be understood through cyclical shifts involving the constant reinvention of artistic method and identified four key moments in 20th century history to structure its project. The essay analyses Inside the Visible's concept of an elliptical traverse to raise questions about repetitions and recurrences in feminist exhibitions of the early 1980s, the mid 1990s and 2007 asking whether and in what ways questions of feminist curating have been continuously repeated and reinvented. The essay argues that Inside the Visible was a key project in second wave feminism and exemplified debates about women's time, first theorised by Julia Kristeva. It concludes, however, that 'women's time' has had its moment, and new conceptions of feminism and its history are needed if feminist curating is not endlessly to recycle its past. The essay informs a wider collaborative project on the sexual politics of violence, feminism and contemporary art, in collaboration with Edinburgh and one of the editors of this collection.

Binaural prediction of speech intelligibility in reverberant rooms with multiple noise sources

When speech is in competition with interfering sources in rooms, monaural indicators of intelligibility fail to take account of the listener’s abilities to separate target speech from interfering sounds using the binaural system. In order to incorporate these segregation abilities and their susceptibility to reverberation, Lavandier and Culling [J. Acoust. Soc. Am. 127, 387–399 (2010)] proposed a model which combines effects of better-ear listening and binaural unmasking. A computationally efficient version of this model is evaluated here under more realistic conditions that include head shadow, multiple stationary noise sources, and real-room acoustics. Three experiments are presented in which speech reception thresholds were measured in the presence of one to three interferers using real-room listening over headphones, simulated by convolving anechoic stimuli with binaural room impulse-responses measured with dummy-head transducers in five rooms. Without fitting any parameter of the model, there was close correspondence between measured and predicted differences in threshold across all tested conditions. The model’s components of better-ear listening and binaural unmasking were validated both in isolation and in combination. The computational efficiency of this prediction method allows the generation of complex “intelligibility maps” from room designs. © 2012 Acoustical Society of America

TIGGE: comparison of the prediction of Southern Hemisphere extratropical cyclones by different ensemble prediction systems.

The prediction of Northern Hemisphere (NH) extratropical cyclones by nine different ensemble prediction systems(EPSs), archived as part of The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE), has recently been explored using a cyclone tracking approach. This paper provides a continuation of this work, extending the analysis to the Southern Hemisphere (SH). While the EPSs have larger error in all cyclone properties in the SH, the relative performance of the different EPSs remains broadly consistent between the two hemispheres. Some interesting differences are also shown. The Chinese Meteorological Administration (CMA) EPS has a significantly lower level of performance in the SH compared to the NH. Previous NH results showed that the Centro de Previsao de Tempo e Estudos Climaticos (CPTEC) EPS underpredicts cyclone intensity. The results of this current study show that this bias is significantly larger in the SH. The CPTEC EPS also has very little spread in both hemispheres. As with the NH results, cyclone propagation speed is underpredicted by all the EPSs in the SH. To investigate this further, the bias was also computed for theECMWFhigh-resolution deterministic forecast. The bias was significantly smaller than the lower resolution ECMWF EPS.

Collision prediction of a moving object within a virtual world

This paper provides a solution for predicting moving/moving and moving/static collisions of objects within a virtual environment. Feasible prediction in real-time virtual worlds can be obtained by encompassing moving objects within a sphere and static objects within a convex polygon. Fast solutions are then attainable by describing the movement of objects parametrically in time as a polynomial.

Prediction of novel and analogous folds using fragment assembly and fold recognition

A number of new and newly improved methods for predicting protein structure developed by the Jones–University College London group were used to make predictions for the CASP6 experiment. Structures were predicted with a combination of fold recognition methods (mGenTHREADER, nFOLD, and THREADER) and a substantially enhanced version of FRAGFOLD, our fragment assembly method. Attempts at automatic domain parsing were made using DomPred and DomSSEA, which are based on a secondary structure parsing algorithm and additionally for DomPred, a simple local sequence alignment scoring function. Disorder prediction was carried out using a new SVM-based version of DISOPRED. Attempts were also made at domain docking and “microdomain” folding in order to build complete chain models for some targets.

Protein structure prediction servers at University College London

A number of state-of-the-art protein structure prediction servers have been developed by researchers working in the Bioinformatics Unit at University College London. The popular PSIPRED server allows users to perform secondary structure prediction, transmembrane topology prediction and protein fold recognition. More recent servers include DISOPRED for the prediction of protein dynamic disorder and DomPred for domain boundary prediction.

The DISOPRED server for the prediction of protein disorder

Dynamically disordered regions appear to be relatively abundant in eukaryotic proteomes. The DISOPRED server allows users to submit a protein sequence, and returns a probability estimate of each residue in the sequence being disordered. The results are sent in both plain text and graphical formats, and the server can also supply predictions of secondary structure to provide further structural information.

Prediction and functional analysis of native disorder in proteins from the Three Kingdoms of Life

An automatic method for recognizing natively disordered regions from amino acid sequence is described and benchmarked against predictors that were assessed at the latest critical assessment of techniques for protein structure prediction (CASP) experiment. The method attains a Wilcoxon score of 90.0, which represents a statistically significant improvement on the methods evaluated on the same targets at CASP. The classifier, DISOPRED2, was used to estimate the frequency of native disorder in several representative genomes from the three kingdoms of life. Putative, long (>30 residue) disordered segments are found to occur in 2.0% of archaean, 4.2% of eubacterial and 33.0% of eukaryotic proteins. The function of proteins with long predicted regions of disorder was investigated using the gene ontology annotations supplied with the Saccharomyces genome database. The analysis of the yeast proteome suggests that proteins containing disorder are often located in the cell nucleus and are involved in the regulation of transcription and cell signalling. The results also indicate that native disorder is associated with the molecular functions of kinase activity and nucleic acid binding.

Automatic prediction of functional site regions in low-resolution protein structures

World-wide structural genomics initiatives are rapidly accumulating structures for which limited functional information is available. Additionally, state-of-the art structural prediction programs are now capable of generating at least low resolution structural models of target proteins. Accurate detection and classification of functional sites within both solved and modelled protein structures therefore represents an important challenge. We present a fully automatic site detection method, FuncSite, that uses neural network classifiers to predict the location and type of functionally important sites in protein structures. The method is designed primarily to require only backbone residue positions without the need for specific side-chain atoms to be present. In order to highlight effective site detection in low resolution structural models FuncSite was used to screen model proteins generated using mGenTHREADER on a set of newly released structures. We found effective metal site detection even for moderate quality protein models illustrating the robustness of the method.