Comparison of heat-treated rapeseed expeller and solvent-extracted soya-bean meal as protein supplements for dairy cows given grass silage-based diets

Sixteen early to mid lactation Finnish Ayrshire dairy cows were used in a cyclic change-over experiment with four 21-day experimental periods and a 4 5 2 factorial arrangement of treatments to evaluate the effects of heat-treated rapeseed expeller and solvent-extracted soya-bean meal protein supplements on animal performance. Dietary treatments consisted of grass silage offered ad libitum supplemented with a fixed amount of a cereal based concentrate (10 kg/day on a fresh weight basis) containing 120, 150, 180 or 210 g crude protein (CP) per kg dry matter (DM). Concentrate CP content was manipulated by replacement of basal ingredients (g/kg) with either rapeseed expeller (R; 120, 240 and 360) or soya-bean meal (S; 80, 160 and 240). Increases in concentrate CP stimulated linear increases (P < 0.05) in silage intake (mean 22.5 and 23.8 g DM per g/kg increase in dietary CP content, for R and S, respectively) and milk production. Concentrate inclusion of rapeseed expeller elicited higher (P < 0.01) milk yield and milk protein output responses (mean 108 and 3.71 g/day per g/kg DM increase in dietary CP content) than soya-bean meal (corresponding values 62 and 2.57). Improvements in the apparent utilization of dietary nitrogen for milk protein synthesis (mean 0.282 and 0.274, for R and S, respectively) were associated with higher (P < 0.05) plasma concentrations of histidine, branched-chain, essential and total amino acids (35, 482, 902 and 2240 and 26, 410, 800 and 2119 mu mol/l, respectively) and lower (P < 0.01) concentrations of urea (corresponding values 4.11 and 4.52 mmol/l). Heat-treated rapeseed expeller proved to be a more effective protein supplement than solvent-extracted soya-bean meal for cows offered grass silage-based diets.

Mind the gap: improving the dissemination of CBT

Empirically supported psychological treatments have been developed for a range of psychiatric disorders but there is evidence that patients are not receiving them in routine clinical care. Furthermore, even when patients do receive these treatments there is evidence that they are often not well delivered. The aim of this paper is to identify the barriers to the dissemination of evidence-based psychological treatments and then propose ways of overcoming them, hence potentially bridging the gap between research findings and clinical practice. (C) 2009 Elsevier Ltd. All rights reserved.

Assessing the environmental performance of English arable and livestock holdings using data from the Farm Accountancy Data Network (FADN)

Agri-environment schemes (AESs) have been implemented across EU member states in an attempt to reconcile agricultural production methods with protection of the environment and maintenance of the countryside. To determine the extent to which such policy objectives are being fulfilled, participating countries are obliged to monitor and evaluate the environmental, agricultural and socio-economic impacts of their AESs. However, few evaluations measure precise environmental outcomes and critically, there are no agreed methodologies to evaluate the benefits of particular agri-environmental measures, or to track the environmental consequences of changing agricultural practices. In response to these issues, the Agri-Environmental Footprint project developed a common methodology for assessing the environmental impact of European AES. The Agri-Environmental Footprint Index (AFI) is a farm-level, adaptable methodology that aggregates measurements of agri-environmental indicators based on Multi-Criteria Analysis (MCA) techniques. The method was developed specifically to allow assessment of differences in the environmental performance of farms according to participation in agri-environment schemes. The AFI methodology is constructed so that high values represent good environmental performance. This paper explores the use of the AFI methodology in combination with Farm Business Survey data collected in England for the Farm Accountancy Data Network (FADN), to test whether its use could be extended for the routine surveillance of environmental performance of farming systems using established data sources. Overall, the aim was to measure the environmental impact of three different types of agriculture (arable, lowland livestock and upland livestock) in England and to identify differences in AFI due to participation in agri-environment schemes. However, because farm size, farmer age, level of education and region are also likely to influence the environmental performance of a holding, these factors were also considered. Application of the methodology revealed that only arable holdings participating in agri-environment schemes had a greater environmental performance, although responses differed between regions. Of the other explanatory variables explored, the key factors determining the environmental performance for lowland livestock holdings were farm size, farmer age and level of education. In contrast, the AFI value of upland livestock holdings differed only between regions. The paper demonstrates that the AFI methodology can be used readily with English FADN data and therefore has the potential to be applied more widely to similar data sources routinely collected across the EU-27 in a standardised manner.

Generalized neurofuzzy network modeling algorithms using Bezier-Bernstein polynomial functions and additive decomposition

This paper introduces a new neurofuzzy model construction algorithm for nonlinear dynamic systems based upon basis functions that are Bezier-Bernstein polynomial functions. This paper is generalized in that it copes with n-dimensional inputs by utilising an additive decomposition construction to overcome the curse of dimensionality associated with high n. This new construction algorithm also introduces univariate Bezier-Bernstein polynomial functions for the completeness of the generalized procedure. Like the B-spline expansion based neurofuzzy systems, Bezier-Bernstein polynomial function based neurofuzzy networks hold desirable properties such as nonnegativity of the basis functions, unity of support, and interpretability of basis function as fuzzy membership functions, moreover with the additional advantages of structural parsimony and Delaunay input space partition, essentially overcoming the curse of dimensionality associated with conventional fuzzy and RBF networks. This new modeling network is based on additive decomposition approach together with two separate basis function formation approaches for both univariate and bivariate Bezier-Bernstein polynomial functions used in model construction. The overall network weights are then learnt using conventional least squares methods. Numerical examples are included to demonstrate the effectiveness of this new data based modeling approach.

The North Atlantic jet stream under climate change and its relation to the NAO and EA patterns

This paper describes recent variations of the North Atlantic eddy-driven jet stream and analyzes the mean response of the jet to anthropogenic forcing in climate models. Jet stream changes are analyzed both using a direct measure of the near-surface westerly wind maximum and using an EOF-based approach. This allows jet stream changes to be related to the widely used leading patterns of variability: the North Atlantic Oscillation (NAO) and East Atlantic (EA) pattern. Viewed in NAO–EA state space, isolines of jet latitude and speed resemble a distorted polar coordinate system, highlighting the dependence of the jet stream quantities on both spatial patterns. Some differences in the results of the two methods are discussed, but both approaches agree on the general characteristics of the climate models. While there is some agreement between models on a poleward shift of the jet stream in response to anthropogenic forcing, there is still considerable spread between different model projections, especially in winter. Furthermore, the model responses to forcing are often weaker than their biases when compared to a reanalysis. Diagnoses of jet stream changes can be sensitive to the methodologies used, and several aspects of this are also discussed.

Where, when and why brain activation differs for bilinguals and monolinguals during picture naming and reading aloud

Using functional magnetic resonance imaging, we found that when bilinguals named pictures or read words aloud, in their native or nonnative language, activation was higher relative to monolinguals in 5 left hemisphere regions: dorsal precentral gyrus, pars triangularis, pars opercularis, superior temporal gyrus, and planum temporale. We further demonstrate that these areas are sensitive to increasing demands on speech production in monolinguals. This suggests that the advantage of being bilingual comes at the expense of increased work in brain areas that support monolingual word processing. By comparing the effect of bilingualism across a range of tasks, we argue that activation is higher in bilinguals compared with monolinguals because word retrieval is more demanding; articulation of each word is less rehearsed; and speech output needs careful monitoring to avoid errors when competition for word selection occurs between, as well as within,language.

Physicochemical changes occuring in oil when atmospheric frying is combined with post-frying vacuum application

The aim of this study was to investigate the effect of atmospheric frying followed by drainage under vacuum on the stability of oil, compared to similar frying with drainage at atmospheric pressure. Changes in the oil were assessed by the free fatty acid (FFA) content, p-anisidine value (AnV), colour, viscosity, fatty acid profile and concentration of tocols. The rate of FFA formation in the case of vacuum drainage was found to be about half that of atmospheric drainage. Oil deterioration by oxidation and polymerisation was also reduced by the use of vacuum drainage. The AnV of the oil after vacuum drainage was lower by about 12%, the total colour difference was improved by 14% and viscosity was slightly reduced after 5 days of frying, compared to the values for oil that had been drained at atmospheric pressure. There was a reduction in the loss of polyunsaturated fatty acids in the case of vacuum drainage after 5 days of frying but differences in retention of tocols were only evident in the first two days of frying.

Studying the impact of ubiquitous monitoring technology on office worker behaviours: the value of sharing research data

Pervasive computing is a continually, and rapidly, growing field, although still remains in relative infancy. The possible applications for the technology are numerous, and stand to fundamentally change the way users interact with technology. However, alongside these are equally numerous potential undesirable effects and risks. The lack of empirical naturalistic data in the real world makes studying the true impacts of this technology difficult. This paper describes how two independent research projects shared such valuable empirical data on the relationship between pervasive technologies and users. Each project had different aims and adopted different methods, but successfully used the same data and arrived at the same conclusions. This paper demonstrates the benefit of sharing research data in multidisciplinary pervasive computing research where real world implementations are not widely available.

Climate change modelling and its roles to chinese crops yield

Climate has been changing in the last fifty years in China and will continue to change regardless any efforts for mitigation. Agriculture is a climate-dependent activity and highly sensitive to climate changes and climate variability. Understanding the interactions between climate change and agricultural production is essential for society stable development of China. The first mission is to fully understand how to predict future climate and link it with agriculture production system. In this paper, recent studies both domestic and international are reviewed in order to provide an overall image of the progress in climate change researches. The methods for climate change scenarios construction are introduced. The pivotal techniques linking crop model and climate models are systematically assessed and climate change impacts on Chinese crops yield among model results are summarized. The study found that simulated productions of grain crop inherit uncertainty from using different climate models, emission scenarios and the crops simulation models. Moreover, studies have different spatial resolutions, and methods for general circulation model (GCM) downscaling which increase the uncertainty for regional impacts assessment. However, the magnitude of change in crop production due to climate change (at 700 ppm CO2 eq correct) appears within ±10% for China in these assessments. In most literatures, the three cereal crop yields showed decline under climate change scenarios and only wheat in some region showed increase. Finally, the paper points out several gaps in current researches which need more studies to shorten the distance for objective recognizing the impacts of climate change on crops. The uncertainty for crop yield projection is associated with climate change scenarios, CO2 fertilization effects and adaptation options. Therefore, more studies on the fields such as free air CO2 enrichment experiment and practical adaptations implemented need to be carried out