Functional petit-suisse cheese: measure of the prebiotic effect

Prebiotics and probiotics are increasingly being used to produce potentially synbiotic foods, particularly through dairy products as vehicles. It is well known that both ingredients may offer benefits to improve the host health. This research aimed to evaluate the prebiotic potential of novel petit-suisse cheeses using an in vitro fermentation model. Five petit-suisse cheese formulations combining candidate prebiotics (inulin. oligofructose. hone) and probiotics (Lactobacillus acidophilus, Bifidobacterium lactis) were tested in vitro using, sterile. stirred, batch culture fermentations with human faecal slurry. Measurement of prebiotic effect (MPE) values were generated comparing bacterial changes through determination of maximum growth rates of groups, rate of substrate assimilation and production of lactate and short chain fatty acids. Fastest fermentation and high lactic acid production, promoting increased growth rates of bifidobacteria and lactobacilli. were achieved with addition of prebiotics to a probiotic cheese (made using starter + probiotics). Addition of probiotic strains to control cheese (made using just a starter culture) also resulted in high lactic acid production. Highest MPE values were obtained with addition of prebiotics to a probiotic cheese, followed by addition of prebiotics and/or probiotics to a control cheese. Under the in vitro conditions used, cheese made with the combination of different prebiotics and probiotics resulted in the most promising functional petit-suisse cheese. The study allowed comparison of potentially functional petit-suisse cheeses and screening of preferred synbiotic potential for future market use. (c) 2007 Elsevier Ltd. All rights reserved.

Family interventions in psychosis: a scale to measure therapist adherence

The efficacy of family interventions in psychosis is well documented. UK and USA schizophrenia treatment guidelines advocate the practice of family interventions within routine clinical services. However, less attention has been paid to the study of treatment fidelity and the tools used in its assessment. This study reports the inter-rater reliability of a new scale: Family Intervention in Psychosis-Adherence Scale (FIPAS). This measure is designed to assess therapist adherence to the Kuipers et al. (2002) family intervention in psychosis treatment manual. Reliability ratings were based on a sample of thirteen audiotapes drawn from a randomized controlled trial of family intervention. The results indicated that the majority of items of the FIPAS had acceptable levels of inter-rater reliability. The findings are discussed in terms of their implications for the training and monitoring of the effectiveness of practitioners for family interventions in psychosis.

A review of instruments developed to measure outcomes for carers of people with mental health problems

Objective: Community-based care for mental disorders places considerable burden on families and carers. Measuring their experiences has become a priority, but there is no consensus on appropriate instruments. We aimed to review instruments carers consider relevant to their needs and assess evidence for their use. Method: A literature search was conducted for outcome measures used with mental health carers. Identified instruments were assessed for their relevance to the outcomes identified by carers and their psychometric properties. Results: Three hundred and ninety two published articles referring to 241 outcome measures were identified, 64 of which were eligible for review (used in three or more studies). Twenty-six instruments had good psychometric properties; they measured (i) carers' well-being, (ii) the experience of caregiving and (iii) carers' needs for professional support. Conclusion: Measures exist which have been used to assess the most salient aspects of carer outcome in mental health. All require further work to establish their psychometric properties fully.

Kernel classifier construction using orthogonal forward selection and boosting with Fisher ratio class separability measure

A greedy technique is proposed to construct parsimonious kernel classifiers using the orthogonal forward selection method and boosting based on Fisher ratio for class separability measure. Unlike most kernel classification methods, which restrict kernel means to the training input data and use a fixed common variance for all the kernel terms, the proposed technique can tune both the mean vector and diagonal covariance matrix of individual kernel by incrementally maximizing Fisher ratio for class separability measure. An efficient weighted optimization method is developed based on boosting to append kernels one by one in an orthogonal forward selection procedure. Experimental results obtained using this construction technique demonstrate that it offers a viable alternative to the existing state-of-the-art kernel modeling methods for constructing sparse Gaussian radial basis function network classifiers. that generalize well.

Cereal-based wholecrop silages: a potential conservation measure for farmland birds in pastoral landscapes

Declines of farmland birds have been pronounced in landscapes dominated by lowland livestock production and densities of seed-eating birds are particularly low in such areas. Modern livestock production often entails a simple cropping system dominated by ley grassland and maize grown for animal feed. These crops often lack invertebrate and seed resources for foraging birds and can be hostile nesting environments. Cereal-based wholecrop silages (CBWCS) offer potential benefits for farmland birds because they can be grown with minimal herbicide applications and can be spring-sown with following winter stubbles. We compared the biodiversity benefits and agronomic yields of winter-sown wheat and spring-sown barley as alternatives to grass and maize silage in intensive dairy livestock systems. Seed-eating birds foraged mainly in CBWCS fields during summer, and mainly on barley stubbles during winter and this reflected the higher densities of seed-bearing plants therein. Maize and grass fields lacked seed-bearing vegetation and were strongly avoided by most seed-eating birds. Production costs of CBWCS are similar to those of maize and lower than those of grass silage. Selective (rather than broad-spectrum) herbicide application on spring barley crops increased forb cover, reduced yields (by 11%) but caused only a small (<4%) increase in production costs. CBWCS grown with selective herbicide and with following winter stubbles offer a practical conservation measure for seed-eating farmland birds in landscapes dominated by intensively-managed grassland and maize. However, the relatively early harvesting of CBWCS could destroy a significant proportion of breeding attempts of late-nesting species like corn bunting (Emberiza calandra) or yellow wagtail (Motocilla flava). Where late-breeding species are likely to nest in CBWCS fields, harvesting should be delayed until most nesting attempts have been completed (e.g. until after 1st August in southern Britain). (C) 2010 Elsevier Ltd. All rights reserved.

Developing a brand performance measure for financial services brands

With no universal approach for measuring brand performance, we show how a consumer-based brand measure was developed for corporate financial services brands. Churchill's paradigm was adopted. A literature review and 20 depth interviews with experts suggested that brand loyalty, consumer satisfaction and reputation constitute the brand performance measure. Ten financial services organisations provided access to their consumers. Following a postal survey, 600 questionnaires were analysed through principal components analysis to identify the consumer-based measure. Further testing revealed this to be a valid and reliable brand performance measure.

The Huntington's Disease health-related Quality of Life questionnaire (HDQoL): a disease-specific measure of health-related quality of life

Hocaoglu MB, Gaffan EA, Ho AK. The Huntington's disease health-related quality of life questionnaire: a disease-specific measure of health-related quality of life. Huntington's disease (HD) is a genetic neurodegenerative disorder characterized by motor, cognitive and psychiatric disturbances, and yet there is no disease-specific patient-reported health-related quality of life outcome measure for patients. Our aim was to develop and validate such an instrument, i.e. the Huntington's Disease health-related Quality of Life questionnaire (HDQoL), to capture the true impact of living with this disease. Semi-structured interviews were conducted with the full spectrum of people living with HD, to form a pool of items, which were then examined in a larger sample prior to data-driven item reduction. We provide the statistical basis for the extraction of three different sets of scales from the HDQoL, and present validation and psychometric data on these scales using a sample of 152 participants living with HD. These new patient-derived scales provide promising patient-reported outcome measures for HD.

Can we measure terrestrial photosynthesis from space directly, using spectral reflectance and fluorescence?

Attempts to estimate photosynthetic rate or gross primary productivity from remotely sensed absorbed solar radiation depend on knowledge of the light use efficiency (LUE). Early models assumed LUE to be constant, but now most researchers try to adjust it for variations in temperature and moisture stress. However, more exact methods are now required. Hyperspectral remote sensing offers the possibility of sensing the changes in the xanthophyll cycle, which is closely coupled to photosynthesis. Several studies have shown that an index (the photochemical reflectance index) based on the reflectance at 531 nm is strongly correlated with the LUE over hours, days and months. A second hyperspectral approach relies on the remote detection of fluorescence, which is a directly related to the efficiency of photosynthesis. We discuss the state of the art of the two approaches. Both have been demonstrated to be effective, but we specify seven conditions required before the methods can become operational.

Validation of three new measure-correlate-predict models for the long-term prospection of the wind resource

The estimation of the long-term wind resource at a prospective site based on a relatively short on-site measurement campaign is an indispensable task in the development of a commercial wind farm. The typical industry approach is based on the measure-correlate-predict �MCP� method where a relational model between the site wind velocity data and the data obtained from a suitable reference site is built from concurrent records. In a subsequent step, a long-term prediction for the prospective site is obtained from a combination of the relational model and the historic reference data. In the present paper, a systematic study is presented where three new MCP models, together with two published reference models �a simple linear regression and the variance ratio method�, have been evaluated based on concurrent synthetic wind speed time series for two sites, simulating the prospective and the reference site. The synthetic method has the advantage of generating time series with the desired statistical properties, including Weibull scale and shape factors, required to evaluate the five methods under all plausible conditions. In this work, first a systematic discussion of the statistical fundamentals behind MCP methods is provided and three new models, one based on a nonlinear regression and two �termed kernel methods� derived from the use of conditional probability density functions, are proposed. All models are evaluated by using five metrics under a wide range of values of the correlation coefficient, the Weibull scale, and the Weibull shape factor. Only one of all models, a kernel method based on bivariate Weibull probability functions, is capable of accurately predicting all performance metrics studied.