Combining GIS and Expert Opinion to Model Landscapes for a Smallholder Forest Extension Program in Leyte, the Philippines

A Geographic Information System (GIS) was used to model datasets of Leyte Island, the Philippines, to identify land which was suitable for a forest extension program on the island. The datasets were modelled to provide maps of the distance of land from cities and towns, land which was a suitable elevation and slope for smallholder forestry and land of various soil types. An expert group was used to assign numeric site suitabilities to the soil types and maps of site suitability were used to assist the selection of municipalities for the provision of extension assistance to smallholders. Modelling of the datasets was facilitated by recent developments of the ArcGIS® suite of computer programs and derivation of elevation and slope was assisted by the availability of digital elevation models (DEM) produced by the Shuttle Radar Topography (SRTM) mission. The usefulness of GIS software as a decision support tool for small-scale forestry extension programs is discussed.

Structure optimization combining soft-core interaction functions, the diffusion equation method, and molecular dynamics

Smoothing the potential energy surface for structure optimization is a general and commonly applied strategy. We propose a combination of soft-core potential energy functions and a variation of the diffusion equation method to smooth potential energy surfaces, which is applicable to complex systems such as protein structures; The performance of the method was demonstrated by comparison with simulated annealing using the refinement of the undecapeptide Cyclosporin A as a test case. Simulations were repeated many times using different initial conditions and structures since the methods are heuristic and results are only meaningful in a statistical sense.

Supervisory control of wastewater treatment plants by combining principal component analysis and fuzzy c-means clustering

In this paper a methodology for integrated multivariate monitoring and control of biological wastewater treatment plants during extreme events is presented. To monitor the process, on-line dynamic principal component analysis (PCA) is performed on the process data to extract the principal components that represent the underlying mechanisms of the process. Fuzzy c-means (FCM) clustering is used to classify the operational state. Performing clustering on scores from PCA solves computational problems as well as increases robustness due to noise attenuation. The class-membership information from FCM is used to derive adequate control set points for the local control loops. The methodology is illustrated by a simulation study of a biological wastewater treatment plant, on which disturbances of various types are imposed. The results show that the methodology can be used to determine and co-ordinate control actions in order to shift the control objective and improve the effluent quality.

Investigations into a power-combining structure using a reflect array of dual-feed aperture-coupled microstrip patch antennas

This paper details an investigation of a power combiner that uses a reflect array of dual-feed aperture-coupled microstrip patch antennas and a corporate-fed dual-polarized array as a signal distributing/combining device. In this configuration, elements of the reflect array receive a linearly polarized wave and retransmit it with an orthogonal polarization using variable-length sections of microstrip lines connecting receive and transmit ports. By applying appropriate lengths of these delay lines, the array focuses the transmitted wave onto the feed array. The operation of the combiner is investigated for a small-size circular reflect array for the cases of -3 dB, -6 dB and -10 dB edge illumination by the 2 x 2-element dual-polarized array.

Combining the analyses of introgressive hybridisation and linkage mapping to investigate the genetic architecture of population divergence in the lake whitefish (Coregonus clupeaformis, Mitchill)

Adaptation and reproductive isolation, the engines of biological diversity, are still elusive when discussing the genetic bases of speciation. Namely, the number of genes and magnitude of selection acting positively or negatively on genomic traits implicated in speciation is contentious. Here, we describe the first steps of an ongoing research program aimed at understanding the genetic bases of population divergence and reproductive isolation in the lake whitefish (Coregonus clupeaformis). A preliminary linkage map originating from a hybrid cross between dwarf and normal ecotypes is presented, whereby some of the segregating AFLP markers were found to be conserved among natural populations. Maximum-likelihood was used to estimate hybrid indices from non-diagnostic markers at 998 AFLP loci. This allowed identification of the most likely candidate loci that have been under the influence of selection during the natural hybridisation of whitefish originating from different glacial races. As some of these loci could be identified on the linkage map, the possibility that selection of traits in natural populations may eventually be correlated to specific chromosomal regions was demonstrated. The future prospects and potential of these approaches to elucidate the genetic bases of adaptation and reproductive isolation among sympatric ecotypes of lake whitefish is discussed.

Modelling the activated sludge flocculation process combining laser light diffraction particle sizing and population balance modelling (PBM)

A technique based on laser light diffraction is shown to be successful in collecting on-line experimental data. Time series of floc size distributions (FSD) under different shear rates (G) and calcium additions were collected. The steady state mass mean diameter decreased with increasing shear rate G and increased when calcium additions exceeded 8 mg/l. A so-called population balance model (PBM) was used to describe the experimental data, This kind of model describes both aggregation and breakage through birth and death terms. A discretised PBM was used since analytical solutions of the integro-partial differential equations are non-existing. Despite the complexity of the model, only 2 parameters need to be estimated: the aggregation rate and the breakage rate. The model seems, however, to lack flexibility. Also, the description of the floc size distribution (FSD) in time is not accurate.

Combining nonthermal technologies to control foodborne microorganisms

Novel nonthermal processes, such as high hydrostatic pressure (HHP), pulsed electric fields (PEFs), ionizing radiation and ultrasonication, are able to inactivate microorganisms at ambient or sublethal temperatures. Many of these processes require very high treatment intensities, however, to achieve adequate microbial destruction in low-acid foods. Combining nonthermal processes with conventional preservation methods enhances their antimicrobial effect so that lower process intensities can be used. Combining two or more nonthermal processes can also enhance microbial inactivation and allow the use of lower individual treatment intensities. For conventional preservation treatments, optimal microbial control is achieved through the hurdle concept, with synergistic effects resulting from different components of the microbial cell being targeted simultaneously. The mechanisms of inactivation by nonthermal processes are still unclear; thus, the bases of synergistic combinations remain speculative. This paper reviews literature on the antimicrobial efficiencies of nonthermal processes combined with conventional and novel nonthermal technologies. Where possible, the proposed mechanisms of synergy is mentioned. (C) 2003 Elsevier Science B.V. All rights reserved.

Joining forces - Combining cognition-targeted motor control training with group or individual pain physiology education: A successful treatment for chronic low back pain

Chronic unremittent low back pain (LBP) is characterised by cognitive barriers to treatment. Combining a motor control training approach with individualised education about pain physiology is effective in this group of patients. This randomized comparative trial (i) evaluates an approach to motor control acquisition and training that considers the complexities of the relationship between pain and motor output, and (ii) compares the efficacy and cost of individualized and group pain physiology education. After an "ongoing usual treatment" period, patients participated in a 4-week motor control and pain physiology education program. Patients received four one-hour individualized education sessions (IE) or one 4-hour group lecture (GE). Both groups reduced pain (numerical rating scale) and disability (Roland Morris Disability Questionnaire). IE showed bigger decreases, which were maintained at 12 months (P < 0.05 for all). The combined motor control and education approach is effective. Although group education imparts a lesser effect, it may be more cost-efficient. [ABSTRACT FROM AUTHOR]

Remotely sensed data for ecosystem analyses: Combining hierarchy and scene models

Remotely sensed data have been used extensively for environmental monitoring and modeling at a number of spatial scales; however, a limited range of satellite imaging systems often. constrained the scales of these analyses. A wider variety of data sets is now available, allowing image data to be selected to match the scale of environmental structure(s) or process(es) being examined. A framework is presented for use by environmental scientists and managers, enabling their spatial data collection needs to be linked to a suitable form of remotely sensed data. A six-step approach is used, combining image spatial analysis and scaling tools, within the context of hierarchy theory. The main steps involved are: (1) identification of information requirements for the monitoring or management problem; (2) development of ideal image dimensions (scene model), (3) exploratory analysis of existing remotely sensed data using scaling techniques, (4) selection and evaluation of suitable remotely sensed data based on the scene model, (5) selection of suitable spatial analytic techniques to meet information requirements, and (6) cost-benefit analysis. Results from a case study show that the framework provided an objective mechanism to identify relevant aspects of the monitoring problem and environmental characteristics for selecting remotely sensed data and analysis techniques.

Predictive vaccinology: Optimisation of predictions using support vector machine classifiers

Promiscuous human leukocyte antigen (HLA) binding peptides are ideal targets for vaccine development. Existing computational models for prediction of promiscuous peptides used hidden Markov models and artificial neural networks as prediction algorithms. We report a system based on support vector machines that outperforms previously published methods. Preliminary testing showed that it can predict peptides binding to HLA-A2 and -A3 super-type molecules with excellent accuracy, even for molecules where no binding data are currently available.

Combining Sr and Na additions in hypoeutectic Al-Si foundry alloys

From recent published data, it is still unclear whether combining additions of Na and Sr have synergistic effects or deleterious interactions, This paper clarifies the interactions between these two modifiers and investigates the effects of such interactions on alloy solidification and castability. It was found that combined additions of Sr and Na do not appear to cause improvement of the modification of the eutectic microstructure even after only a short period after addition. Na addition may promote Sr vaporization and/or oxidation kinetically. leading to a quicker loss of both modifiers, which is blamed for the rapid loss of the modification effect during melt holding. Quenching trials during the eutectic arrest indicate that addition of Sr into Na-modified melts does not alter the eutectic solidification behaviour The effect of Na on eutectic solidification dominates, and the eutectic is observed to evolve with a significant dependency on the thermal gradient, Combining Sr and Na additions produced no beneficial effects on porosity and casting defects. (c) 2005 Elsevier B.V. All rights reserved.

The performance of the maximum ratio combining method in correlated Rician-fading channels for antenna-diversity signal combining

The performance of the maximum ratio combining method for the combining of antenna-diversity signals in correlated Rician-fading channels is rigorously studied. The distribution function of the normalized signal-to-noise ratio (SNR) is expanded in terms of a power series and calculated numerically. This power series can easily take into account the signal correlations and antenna gains and can be applied to any number of receiving antennas. An application of the method to dual-antenna diversity systems produces useful distribution curves for the normalized SNR which can be used to find the diversity gain. It is revealed that signal correlation in Rician-fading channels helps to increase the diversity gain rather than to decrease it as in the Rayleigh fading channels. It is also shown that with a relative strong direct signal component, the diversity gain can be much higher than that without a direct signal component.