The implications of improved communications for participatory forest management in Tanzania

Following the 1998 National Forest Policy and Forest Act of 2002, participatory forest management (PFM) is being introduced in Tanzania. PFM has two key objectives: to reduce forest degradation thereby increasing ecosystem services, and to improve the livelihoods of local villagers. A unique data set collected in 2006 suggests that significant challenges remain with respect to communicating the new forest policies if the objectives of PFM are to be achieved. First, villagers as a group are much less well informed than other stakeholders, and their knowledge is often inaccurate. Second, women are less likely than men to have heard of the changes. Third, how PFM will contribute to poverty reduction (a key objective of PFM) is not always clear. Fourth, environmental degradation may not be reduced as much as anticipated – without alternatives sources, villagers often continue to cut trees for charcoal and firewood in the protected forests. Finally, several mismatches in perceptions are identified that could lead to difficulties in implementing PFM.

Breast, colorectal, and prostate cancer risk in the European Prospective Investigation into Cancer and Nutrition–Norfolk in relation to phytoestrogen intake derived from an improved database

Background: The characterization of phytoestrogen intake and cancer risk has been hindered by the absence of accurate dietary phytoestrogen values. Objective: We examined the risk of breast, colorectal, and prostate cancers relative to phytoestrogen intake on the basis of a comprehensive database. Design: Demographic and anthropometric characteristics, a medical history, and 7-d records of diet were collected prospectively from participants (aged 40–79 y) in the European Prospective Investigation into Cancer and Nutrition–Norfolk (EPIC-Norfolk). Five hundred nine food items were analyzed by liquid chromatography–mass spectrometry/mass spectrometry, and 13C3-labeled internal standards were analyzed for isoflavones (genistein, daidzein, glycitein, biochanin A, and formononetin), lignans (secoisolariciresinol and matairesinol), and enterolignans from gut microbial metabolism in animal food sources (equol and enterolactone). From the direct analysis, values for 10,708 foods were calculated. Odds ratios (ORs) for breast (244 cases, 941 controls), colorectal (221 cases, 886 controls), and prostate (204 cases, 812 controls) cancers were calculated relative to phytoestrogen intake. Results: Phytoestrogen intake was not associated with breast cancer among women or colorectal cancer among men. Among women, colorectal cancer risk was inversely associated with enterolactone (OR: 0.33; 95% CI: 0.14, 0.74) and total enterolignans (OR: 0.32; 95% CI: 0.13, 0.79), with a positive trend detected for secoisolariciresinol (OR: 1.60; 95% CI: 0.96, 2.69). A positive trend between enterolignan intake and prostate cancer risk (OR: 1.27; 95% CI: 0.97, 1.66) was attenuated after adjustment for dairy intake (OR: 1.19; 95% CI: 0.77, 1.82). Conclusion: Dietary phytoestrogens may contribute to the risk of colorectal cancer among women and prostate cancer among men.

Influencing energy efficient occupant behavior through improved building and control design

There is growing pressure on the construction industry to deliver energy efficient, sustainable buildings but there is evidence to suggest that, in practice, designs regularly fail to achieve the anticipated levels of in-use energy consumption. One of the key factors behind this discrepancy is the behavior of the building occupants. This paper explores how insights from experimental psychology could potentially be used to reduce the gap between the predicted and actual energy performance of buildings. It demonstrates why traditional methods to engage with the occupants are not always successful and proposes a model for a more holistic approach to this issue. The paper concludes that achieving energy efficiency in buildings is not solely a technological issue and that the construction industry needs to adopt a more user-centred approach.

Incorporating technology buying behaviour into UK-based long term domestic stock energy models to provide improved policy analysis

The UK has a target for an 80% reduction in CO2 emissions by 2050 from a 1990 base. Domestic energy use accounts for around 30% of total emissions. This paper presents a comprehensive review of existing models and modelling techniques and indicates how they might be improved by considering individual buying behaviour. Macro (top-down) and micro (bottom-up) models have been reviewed and analysed. It is found that bottom-up models can project technology diffusion due to their higher resolution. The weakness of existing bottom-up models at capturing individual green technology buying behaviour has been identified. Consequently, Markov chains, neural networks and agent-based modelling are proposed as possible methods to incorporate buying behaviour within a domestic energy forecast model. Among the three methods, agent-based models are found to be the most promising, although a successful agent approach requires large amounts of input data. A prototype agent-based model has been developed and tested, which demonstrates the feasibility of an agent approach. This model shows that an agent-based approach is promising as a means to predict the effectiveness of various policy measures.

Layer-by-layer coating of alginate matrices with chitosan–alginate for the improved survival and targeted delivery of probiotic bacteria after oral administration

The oral administration of probiotic bacteria has shown potential in clinical trials for the alleviation of specific disorders of the gastrointestinal tract. However, cells must be alive in order to exert these benefits. The low pH of the stomach can greatly reduce the number of viable microorganisms that reach the intestine, thereby reducing the efficacy of the administration. Herein, a model probiotic, Bifidobacterium breve, has been encapsulated into an alginate matrix before coating in multilayers of alternating alginate and chitosan. The intention of this formulation was to improve the survival of B. breve during exposure to low pH and to target the delivery of the cells to the intestine. The material properties were first characterized before in vitro testing. Biacore™ experiments allowed for the polymer interactions to be confirmed; additionally, the stability of these multilayers to buffers simulating the pH of the gastrointestinal tract was demonstrated. Texture analysis was used to monitor changes in the gel strength during preparation, showing a weakening of the matrices during coating as a result of calcium ion sequestration. The build-up of multilayers was confirmed by confocal laser-scanning microscopy, which also showed the increase in the thickness of coat over time. During exposure to in vitro gastric conditions, an increase in viability from <3 log(CFU) per mL, seen in free cells, up to a maximum of 8.84 ± 0.17 log(CFU) per mL was noted in a 3-layer coated matrix. Multilayer-coated alginate matrices also showed a targeting of delivery to the intestine, with a gradual release of their loads over 240 min.

Factors influencing adoption of improved grassland management by small-scale dairy farmers in central Mexico and the implications for future research on smallholder adoption in developing countries

There have been limited recent advances in understanding of what influences uptake of innovations despite the current international focus on smallholder agriculture as a means of achieving food security and rural development. This paper provides a rigorous study of factors influencing adoption by smallholders in central Mexico and builds on findings to identify a broad approach to significantly improve research on and understanding of factors influencing adoption by smallholders in developing countries. Small-scale dairy systems play an important role in providing income, employment and nutrition in the highlands of central Mexico. A wide variety of practices and technologies have been promoted by the government public services to increase milk production and economic efficiency, but there have been very low levels of uptake of most innovations, with the exception of improving grassland through introduction of grass varieties together with management practices. A detailed study was conducted with 80 farmers who are already engaged with the use of this innovation to better understand the process of adoption and identify socioeconomic and farm variables, cognitive (beliefs), and social–psychological (social norms) factors associated with farmers' use of improved grassland. The Theory of Reasoned Action (TRA) was used as a theoretical framework and Spearman Rank Order correlation was conducted to analyse the data. Most farmers (92.5%) revealed strong intention to continue to use improved grassland (which requires active management and investment of resources) for the next 12 months; whereas 7.5% of farmers were undecided and showed weak intention, which was associated with farmers whose main income was from non-farm activities as well as with farmers who had only recently started using improved grassland. Despite farmers' experience of using improved grassland (mean of 18 years) farmers' intentions to continue to adopt it was influenced almost as much by salient referents (mainly male relatives) as by their own attitudes. The hitherto unnoticed longevity of the role social referents play in adoption decisions is an important finding and has implications for further research and for the design of extension approaches. The study demonstrates the value and importance of using TRA or TPB approaches to understand social cognitive (beliefs) and social–psychological (social norms) factors in the study of adoption. However, other factors influencing adoption processes need to be included to provide fuller understanding. An approach that would enable this, and the development of more generalisable findings than from location specific case studies, and contribute to broader conceptualisation, is proposed.

High yield production of a soluble bifidobacterial β-galactosidase (BbgIV) inE. coliDH5α with improved catalytic efficiency for the synthesis of prebiotic galactooligosaccharides

The bifidobacterial β-galactosidase (BbgIV) was produced in E. coli DH5α at 37 and 30 °C in a 5 L bioreactor under varied conditions of dissolved oxygen (dO2) and pH. The yield of soluble BbgIV was significantly (P < 0.05) increased once the dO2 dropped to 0–2% and remained at such low values during the exponential phase. Limited dO2 significantly (P < 0.05) increased the plasmid copy number and decreased the cells growth rate. Consequently, the BbgIV yield increased to its maximum (71–75 mg per g dry cell weight), which represented 20–25% of the total soluble proteins in the cells. In addition, the specific activity and catalytic efficiency of BbgIV were significantly (P < 0.05) enhanced under limited dO2 conditions. This was concomitant with a change in the enzyme secondary structure, suggesting a link between the enzyme structure and function. The knowledge generated from this work is very important for producing BbgIV as a biocatalyst for the development of a cost-effective process for the synthesis of prebiotic galactooligosaccharides from lactose.

Modeling electrocortical activity through improved local approximations of integral neural field equations

Neural field models of firing rate activity typically take the form of integral equations with space-dependent axonal delays. Under natural assumptions on the synaptic connectivity we show how one can derive an equivalent partial differential equation (PDE) model that properly treats the axonal delay terms of the integral formulation. Our analysis avoids the so-called long-wavelength approximation that has previously been used to formulate PDE models for neural activity in two spatial dimensions. Direct numerical simulations of this PDE model show instabilities of the homogeneous steady state that are in full agreement with a Turing instability analysis of the original integral model. We discuss the benefits of such a local model and its usefulness in modeling electrocortical activity. In particular, we are able to treat “patchy” connections, whereby a homogeneous and isotropic system is modulated in a spatially periodic fashion. In this case the emergence of a “lattice-directed” traveling wave predicted by a linear instability analysis is confirmed by the numerical simulation of an appropriate set of coupled PDEs.

An improved methodology for the recovery of Zea mays and other large crop pollen, with implications for environmental archaeology in the Neotropics

We present a simple sieving methodology to aid the recovery of large cultigen pollen grains, such as maize (Zea mays L.), manioc (Manihot esculenta Crantz), and sweet potato (Ipomoea batatas L.), among others, for the detection of food production using fossil pollen analysis of lake sediments in the tropical Americas. The new methodology was tested on three large study lakes located next to known and/or excavated pre-Columbian archaeological sites in South and Central America. Five paired samples, one treated by sieving, the other prepared using standard methodology, were compared for each of the three sites. Using the new methodology, chemically digested sediment samples were passed through a 53 µm sieve, and the residue was retained, mounted in silicone oil, and counted for large cultigen pollen grains. The filtrate was mounted and analysed for pollen according to standard palynological procedures. Zea mays (L.) was recovered from the sediments of all three study lakes using the sieving technique, where no cultigen pollen had been previously recorded using the standard methodology. Confidence intervals demonstrate there is no significant difference in pollen assemblages between the sieved versus unsieved samples. Equal numbers of exotic Lycopodium spores added to both the filtrate and residue of the sieved samples allow for direct comparison of cultigen pollen abundance with the standard terrestrial pollen count. Our technique enables the isolation and rapid scanning for maize and other cultigen pollen in lake sediments, which, in conjunction with charcoal and pollen records, is key to determining land-use patterns and the environmental impact of pre-Columbian societies.

An improved sum-product estimate for general finite fields

An improved sum-product estimate for subsets of a finite field whose order is not prime is provided. It is shown, under certain conditions, that max{∣∣∣A+A∣∣∣,∣∣∣A⋅A∣∣∣}≫∣∣A∣∣12/11(log2∣∣A∣∣)5/11. This new estimate matches, up to a logarithmic factor, the current best known bound obtained over prime fields by Rudnev

Estimation of sea surface temperature from the Spinning Enhanced Visible and Infra Red Imager, improved using numerical weather prediction

Most of the operational Sea Surface Temperature (SST) products derived from satellite infrared radiometry use multi-spectral algorithms. They show, in general, reasonable performances with root mean square (RMS) residuals around 0.5 K when validated against buoy measurements, but have limitations, particularly a component of the retrieval error that relates to such algorithms' limited ability to cope with the full variability of atmospheric absorption and emission. We propose to use forecast atmospheric profiles and a radiative transfer model to simulate the algorithmic errors of multi-spectral algorithms. In the practical case of SST derived from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard Meteosat Second Generation (MSG), we demonstrate that simulated algorithmic errors do explain a significant component of the actual errors observed for the non linear (NL) split window algorithm in operational use at the Centre de Météorologie Spatiale (CMS). The simulated errors, used as correction terms, reduce significantly the regional biases of the NL algorithm as well as the standard deviation of the differences with drifting buoy measurements. The availability of atmospheric profiles associated with observed satellite-buoy differences allows us to analyze the origins of the main algorithmic errors observed in the SEVIRI field of view: a negative bias in the inter-tropical zone, and a mid-latitude positive bias. We demonstrate how these errors are explained by the sensitivity of observed brightness temperatures to the vertical distribution of water vapour, propagated through the SST retrieval algorithm.