Movement of newly assimilated 13C carbon in the grass Lolium perenne and its incorporation into rhizosphere microbial DNA

One of the key processes that drives rhizosphere microbial activity is the exudation of soluble organic carbon (C) by plant roots. We describe an experiment designed to determine the impact of defoliation on the partitioning and movement of C in grass (Lolium perenne L.), soil and grass-sterile sand microcosms, using a (13)CO(2) pulse-labelling method. The pulse-derived (13)C in the shoots declined over time, but that of the roots remained stable throughout the experiment. There were peaks in the atom% (13)C of rhizosphere CO(2) in the first few hours after labelling probably due to root respiration, and again at around 100 h. The second peak was only seen in the soil microcosms and not in those with sterilised sand as the growth medium, indicating possible microbial activity. Incorporation of the (13)C label into the microbial biomass increased at 100 h when incorporation into replicating cells, as indicated by the amounts of the label in the microbial DNA, started to increase. These results indicate that the rhizosphere environment is conducive to bacterial growth and replication. The results also show that defoliation had no impact on the pattern of movement of (13)C from plant roots into the microbial population in the rhizosphere.

Evidence for a climate signal in trends of global crop yield variability over the past 50 years

Low variability of crop production from year to year is desirable for many reasons, including reduced income risk and stability of supplies. Therefore, it is important to understand the nature of yield variability, whether it is changing through time, and how it varies between crops and regions. Previous studies have shown that national crop yield variability has changed in the past, with the direction and magnitude dependent on crop type and location. Whilst such studies acknowledge the importance of climate variability in determining yield variability, it has been assumed that its magnitude and its effect on crop production have not changed through time and, hence, that changes to yield variability have been due to non-climatic factors. We address this assumption by jointly examining yield and climate variability for three major crops (rice, wheat and maize) over the past 50 years. National yield time series and growing season temperature and precipitation were de-trended and related using multiple linear regression. Yield variability changed significantly in half of the crop–country combinations examined. For several crop–country combinations, changes in yield variability were related to changes in climate variability.

Femto-chemometrics: the signal processing of fast pulse transients

Traditional chemometrics techniques are augmented with algorithms tailored specifically for the de-noising and analysis of femtosecond duration pulse datasets. The new algorithms provide additional insights on sample responses to broadband excitation and multi-moded propagation phenomena.

Towards a lawn without grass: the journey of the imperfect lawn and its analogues

In much of the English-speaking world the lawn is the most common of all garden features. For arguably a millennium it has played a significant role in the landscape and during that period it has been inextricably linked with grasses. Nevertheless other plant species have accompanied the grasses and also been used in creating lawns. From medieval wildflowers to Victorian weeds, the plants that challenge the formal concept of the perfect lawn have journeyed with it but have until recently remained only small players within the dominion of grass. By the beginning of the 21st century, with a new environmental ethos permeating the garden, the long journey of the grassy lawn and its plant companions has led to the grass monoculture being heretically rethought: by removing both the monoculture and the grass.

Theory and generalization of Monte Carlo models of the BOLD signal source

The dependency of the blood oxygenation level dependent (BOLD) signal on underlying hemodynamics is not well understood. Building a forward biophysical model of this relationship is important for the quantitative estimation of the hemodynamic changes and neural activity underlying functional magnetic resonance imaging (fMRI) signals. We have developed a general model of the BOLD signal which can model both intra- and extravascular signals for an arbitrary tissue model across a wide range of imaging parameters. The model of the BOLD signal was instantiated as a look-up-table (LuT), and was verified against concurrent fMRI and optical imaging measurements of activation induced hemodynamics. Magn Reson Med, 2008. © 2008 Wiley-Liss, Inc.

The grass-free lawn: management and species choice for optimum ground cover and plant diversity

In Britain, managed grass lawns provide the most traditional and widespread of garden and landscape practices in use today. Grass lawns are coming under increasing challenge as they tend to support a low level of biodiversity and can require substantial additional inputs to maintain. Here we apply a novel approach to the traditional monocultural lawnscape by replacing grasses entirely with clonal perennial forbs. We monitored changes in plant coverage and species composition over a two year period and here we report the results of a study comparing plant origin native, non-native and mixed) and mowing regime. This allows us to assess the viability of this construct as an alternative to traditional grass lawns. Grass-free lawns provided a similar level of plant cover to grass lawns. Both the mowing regime and the combination of species used affected this outcome, with native plant species seen to have the highest survival rates, and mowing at 4cm to produce the greatest amount of ground coverage and plant species diversity within grass-free lawns. Grass-free lawns required over 50% less mowing than a traditionally managed grass lawn. Observations suggest that plant forms that exhibited: a) a relatively fast growth rate, b) a relatively large individual leaf area, and c) an average leaf height substantially above the cut to be applied, were unsuitable for use in grass-free lawns. With an equivalent level of ground coverage to grass lawns, increased plant diversity and a reduced need for mowing, the grass-free lawn can be seen as a species diverse, lower input and potentially highly ornamental alternative to the traditional lawn format.

An enhanced model for small-signal analysis of the phase-shifted full-bridge converter

This paper presents an in-depth critical discussion and derivation of a detailed small-signal analysis of the Phase-Shifted Full-Bridge (PSFB) converter. Circuit parasitics, resonant inductance and transformer turns ratio have all been taken into account in the evaluation of this topology’s open-loop control-to-output, line-to-output and load-to-output transfer functions. Accordingly, the significant impact of losses and resonant inductance on the converter’s transfer functions is highlighted. The enhanced dynamic model proposed in this paper enables the correct design of the converter compensator, including the effect of parasitics on the dynamic behavior of the PSFB converter. Detailed experimental results for a real-life 36V-to-14V/10A PSFB industrial application show excellent agreement with the predictions from the model proposed herein.1

The influence of plant species number on productivity, ground coverage and floral performance in grass-free lawns

The grass-free lawn is a novel development in modern ornamental horticulture where the traditional monoculture of grass is replaced by a variety of mowing-tolerant clonal forbs. It brings floral aesthetics and a diverse species approach to the use of lawn space. How the number of constituent forb species affects the aesthetic and structural performance of grass-free lawns was investigated using grass-free lawns composed of four, six and twelve British native clonal perennial forb species. Lawn productivity was seen to increase with increasing species number but the relationship was not linear. Plant cover was dynamic in all lawn types, varied between years and was not representative of individual species' floral performance. The behaviour of component species common to all lawns suggested that lawns with 12 species show greater structural stability than the lawns with a lower species number. Visual performance in lawns with the greatest species number was lower than in lawns with fewer species, with increasing variety in floral size and individual species floral productivity leading to a trade-off between diversity and floral performance. Individual species were seen to have different aesthetic functions in grass-free lawns either by providing flowers, ground coverage or both.

Adding value to the urban lawnscape: insect abundance and diversity in grass-free lawns

Insect diversity may be declining even more rapidly than in plants and vertebrates, particularly in areas where indigenous habitats are replaced by an anthropogenic one. The most common component of anthropogenic greenspace is the ornamental lawn. Intensively managed and offering limited habitat opportunities for both plants and insects, lawns are biodiversity poor and ecologically insensitive. An alternative lawn format that positively influences biodiversity and reduces management requirements would be a useful tool in eco-friendly urban greenspace management. In investigating the potential for a forb-only alternative to the grass lawn we sampled both trial grass-free lawn formats and turf lawns to identify any influence that lawn composition and grass-free lawn specific mowing regimes might have on the abundance and diversity of insect families. In addition to the mowing regimes, both the composition and origin of lawn flora were found to significantly influence insect abundance and diversity and these factors rarely interacted. Native-only and mixed origin grass-free lawns hosted greater numbers of adult insects than found in turf and an equivalent diversity of insect families, however the mowing regime applied was distinct from traditional turf lawn management by being substantially less intensive and our results suggest that there is the potential for even greater abundance and diversity via the grass-free format that may offer additional resources to insectivorous garden species such as birds. When the composition of grass-free lawns included native forbs the diversity of insect families was found be sufficiently different from turf lawns to form distinct assemblages and in so doing contribute to beta diversity within urban greenspace. In sum, grass-free lawns may be a useful and aesthetically appropriate tool for adding value to the generally biodiversity poor urban lawnscape.

On the application of optimal wavelet filter banks for ECG signal classification

This paper discusses ECG signal classification after parametrizing the ECG waveforms in the wavelet domain. Signal decomposition using perfect reconstruction quadrature mirror filter banks can provide a very parsimonious representation of ECG signals. In the current work, the filter parameters are adjusted by a numerical optimization algorithm in order to minimize a cost function associated to the filter cut-off sharpness. The goal consists of achieving a better compromise between frequency selectivity and time resolution at each decomposition level than standard orthogonal filter banks such as those of the Daubechies and Coiflet families. Our aim is to optimally decompose the signals in the wavelet domain so that they can be subsequently used as inputs for training to a neural network classifier.

Evidence of a topographic signal in surface soil moisture derived from ENVISAT ASAR wide swath data

The susceptibility of a catchment to flooding is affected by its soil moisture prior to an extreme rainfall event. While soil moisture is routinely observed by satellite instruments, results from previous work on the assimilation of remotely sensed soil moisture into hydrologic models have been mixed. This may have been due in part to the low spatial resolution of the observations used. In this study, the remote sensing aspects of a project attempting to improve flow predictions from a distributed hydrologic model by assimilating soil moisture measurements are described. Advanced Synthetic Aperture Radar (ASAR) Wide Swath data were used to measure soil moisture as, unlike low resolution microwave data, they have sufficient resolution to allow soil moisture variations due to local topography to be detected, which may help to take into account the spatial heterogeneity of hydrological processes. Surface soil moisture content (SSMC) was measured over the catchments of the Severn and Avon rivers in the South West UK. To reduce the influence of vegetation, measurements were made only over homogeneous pixels of improved grassland determined from a land cover map. Radar backscatter was corrected for terrain variations and normalized to a common incidence angle. SSMC was calculated using change detection. To search for evidence of a topographic signal, the mean SSMC from improved grassland pixels on low slopes near rivers was compared to that on higher slopes. When the mean SSMC on low slopes was 30–90%, the higher slopes were slightly drier than the low slopes. The effect was reversed for lower SSMC values. It was also more pronounced during a drying event. These findings contribute to the scant information in the literature on the use of high resolution SAR soil moisture measurement to improve hydrologic models.

Decomposition of surface electromyographic signal using Hidden Markov Model

The detection of physiological signals from the motor system (electromyographic signals) is being utilized in the practice clinic to guide the therapist in a more precise and accurate diagnosis of motor disorders. In this context, the process of decomposition of EMG (electromyographic) signals that includes the identification and classification of MUAP (Motor Unit Action Potential) of a EMG signal, is very important to help the therapist in the evaluation of motor disorders. The EMG decomposition is a complex task due to EMG features depend on the electrode type (needle or surface), its placement related to the muscle, the contraction level and the health of the Neuromuscular System. To date, the majority of researches on EMG decomposition utilize EMG signals acquired by needle electrodes, due to their advantages in processing this type of signal. However, relatively few researches have been conducted using surface EMG signals. Thus, this article aims to contribute to the clinical practice by presenting a technique that permit the decomposition of surface EMG signal via the use of Hidden Markov Models. This process is supported by the use of differential evolution and spectral clustering techniques. The developed system presented coherent results in: (1) identification of the number of Motor Units actives in the EMG signal; (2) presentation of the morphological patterns of MUAPs in the EMG signal; (3) identification of the firing sequence of the Motor Units. The model proposed in this work is an advance in the research area of decomposition of surface EMG signals.

Long-latency reductions in gamma power predict hemodynamic changes that underlie the negative BOLD signal

Studiesthat use prolonged periods of sensory stimulation report associations between regional reductions in neural activity and negative blood oxygenation level-dependent (BOLD) signaling. However, the neural generators of the negative BOLD response remain to be characterized. Here, we use single-impulse electrical stimulation of the whisker pad in the anesthetized rat to identify components of the neural response that are related to “negative” hemodynamic changes in the brain. Laminar multiunit activity and local field potential recordings of neural activity were performed concurrently withtwo-dimensional optical imaging spectroscopy measuring hemodynamic changes. Repeated measurements over multiple stimulation trials revealed significant variations in neural responses across session and animal datasets. Within this variation, we found robust long-latency decreases (300 and 2000 ms after stimulus presentation) in gammaband power (30 – 80 Hz) in the middle-superficial cortical layers in regions surrounding the activated whisker barrel cortex. This reduction in gamma frequency activity was associated with corresponding decreases in the hemodynamic responses that drive the negative BOLD signal. These findings suggest a close relationship between BOLD responses and neural events that operate over time scales that outlast the initiating sensory stimulus, and provide important insights into the neurophysiological basis of negative neuroimaging signals.

Prediction of metabolisable energy concentrations of fresh cut grass using digestibility data measured with non-pregnant non-lactating cows

Pasture-based ruminant production systems are common in certain areas of the world, but energy evaluation in grazing cattle is performed with equations developed, in their majority, with sheep or cattle fed total mixed rations. The aim of the current study was to develop predictions of metabolisable energy (ME) concentrations in fresh-cut grass offered to non-pregnant non-lactating cows at maintenance energy level, which may be more suitable for grazing cattle. Data were collected from three digestibility trials performed over consecutive grazing seasons. In order to cover a range of commercial conditions and data availability in pasture-based systems, thirty-eight equations for the prediction of energy concentrations and ratios were developed. An internal validation was performed for all equations and also for existing predictions of grass ME. Prediction error for ME using nutrient digestibility was lowest when gross energy (GE) or organic matter digestibilities were used as sole predictors, while the addition of grass nutrient contents reduced the difference between predicted and actual values, and explained more variation. Addition of N, GE and diethyl ether extract (EE) contents improved accuracy when digestible organic matter in DM was the primary predictor. When digestible energy was the primary explanatory variable, prediction error was relatively low, but addition of water-soluble carbohydrates, EE and acid-detergent fibre contents of grass decreased prediction error. Equations developed in the current study showed lower prediction errors when compared with those of existing equations, and may thus allow for an improved prediction of ME in practice, which is critical for the sustainability of pasture-based systems.

Prediction of nutrient digestibility and energy concentrations in fresh grass using nutrient composition

Improved nutrient utilization efficiency is strongly related to enhanced economic performance and reduced environmental footprint of dairy farms. Pasture-based systems are widely used for dairy production in certain areas of the world, but prediction equations of fresh grass nutritive value (nutrient digestibility and energy concentrations) are limited. Equations to predict digestible energy (DE) and metabolizable energy (ME) used for grazing cattle have been either developed with cattle fed conserved forage and concentrate diets or sheep fed previously frozen grass, and the majority of them require measurements less commonly available to producers, such as nutrient digestibility. The aim of the present study was therefore to develop prediction equations more suitable to grazing cattle for nutrient digestibility and energy concentrations, which are routinely available at farm level by using grass nutrient contents as predictors. A study with 33 nonpregnant, nonlactating cows fed solely fresh-cut grass at maintenance energy level for 50 wk was carried out over 3 consecutive grazing seasons. Freshly harvested grass of 3 cuts (primary growth and first and second regrowth), 9 fertilizer input levels, and contrasting stage of maturity (3 to 9 wk after harvest) was used, thus ensuring a wide representation of nutritional quality. As a result, a large variation existed in digestibility of dry matter (0.642-0.900) and digestible organic matter in dry matter (0.636-0.851) and in concentrations of DE (11.8-16.7 MJ/kg of dry matter) and ME (9.0-14.1 MJ/kg of dry matter). Nutrient digestibilities and DE and ME concentrations were negatively related to grass neutral detergent fiber (NDF) and acid detergent fiber (ADF) contents but positively related to nitrogen (N), gross energy, and ether extract (EE) contents. For each predicted variable (nutrient digestibilities or energy concentrations), different combinations of predictors (grass chemical composition) were found to be significant and increase the explained variation. For example, relatively higher R(2) values were found for prediction of N digestibility using N and EE as predictors; gross-energy digestibility using EE, NDF, ADF, and ash; NDF, ADF, and organic matter digestibilities using N, water-soluble carbohydrates, EE, and NDF; digestible organic matter in dry matter using water-soluble carbohydrates, EE, NDF, and ADF; DE concentration using gross energy, EE, NDF, ADF, and ash; and ME concentration using N, EE, ADF, and ash. Equations presented may allow a relatively quick and easy prediction of grass quality and, hence, better grazing utilization on commercial and research farms, where nutrient composition falls within the range assessed in the current study.