Survey-gap analysis in expeditionary research: where do we go from here?

Research expeditions into remote areas to collect biological specimens provide vital information for understanding biodiversity. However, major expeditions to little-known areas are expensive and time consuming, time is short, and well-trained people are difficult to find. In addition, processing the collections and obtaining accurate identifications takes time and money. In order to get the maximum return for the investment, we need to determine the location of the collecting expeditions carefully. In this study we used environmental variables and information on existing collecting localities to help determine the sites of future expeditions. Results from other studies were used to aid in the selection of the environmental variables, including variables relating to temperature, rainfall, lithology and distance between sites. A survey gap analysis tool based on 'ED complementarity' was employed to select the sites that would most likely contribute the most new taxa. The tool does not evaluate how well collected a previously visited site survey site might be; however, collecting effort was estimated based on species accumulation curves. We used the number of collections and/or number of species at each collecting site to eliminate those we deemed poorly collected. Plants, birds, and insects from Guyana were examined using the survey gap analysis tool, and sites for future collecting expeditions were determined. The south-east section of Guyana had virtually no collecting information available. It has been inaccessible for many years for political reasons and as a result, eight of the first ten sites selected were in that area. In order to evaluate the remainder of the country, and because there are no immediate plans by the Government of Guyana to open that area to exploration, that section of the country was not included in the remainder of the study. The range of the ED complementarity values dropped sharply after the first ten sites were selected. For plants, the group for which we had the most records, areas selected included several localities in the Pakaraima Mountains, the border with the south-east, and one site in the north-west. For birds, a moderately collected group, the strongest need was in the north-west followed by the east. Insects had the smallest data set and the largest range of ED complementarity values; the results gave strong emphasis to the southern parts of the country, but most of the locations appeared to be equidistant from one another, most likely because of insufficient data. Results demonstrate that the use of a survey gap analysis tool designed to solve a locational problem using continuous environmental data can help maximize our resources for gathering new information on biodiversity. (c) 2005 The Linnean Society of London.

Data-driven fuzzy analysis in quantitative mineral resource assessment

The integration of geo-information from multiple sources and of diverse nature in developing mineral favourability indexes (MFIs) is a well-known problem in mineral exploration and mineral resource assessment. Fuzzy set theory provides a convenient framework to combine and analyse qualitative and quantitative data independently of their source or characteristics. A novel, data-driven formulation for calculating MFIs based on fuzzy analysis is developed in this paper. Different geo-variables are considered fuzzy sets and their appropriate membership functions are defined and modelled. A new weighted average-type aggregation operator is then introduced to generate a new fuzzy set representing mineral favourability. The membership grades of the new fuzzy set are considered as the MFI. The weights for the aggregation operation combine the individual membership functions of the geo-variables, and are derived using information from training areas and L, regression. The technique is demonstrated in a case study of skarn tin deposits and is used to integrate geological, geochemical and magnetic data. The study area covers a total of 22.5 km(2) and is divided into 349 cells, which include nine control cells. Nine geo-variables are considered in this study. Depending on the nature of the various geo-variables, four different types of membership functions are used to model the fuzzy membership of the geo-variables involved. (C) 2002 Elsevier Science Ltd. All rights reserved.

Designs for generalized linear models with several variables and model uncertainty

Standard factorial designs sometimes may be inadequate for experiments that aim to estimate a generalized linear model, for example, for describing a binary response in terms of several variables. A method is proposed for finding exact designs for such experiments that uses a criterion allowing for uncertainty in the link function, the linear predictor, or the model parameters, together with a design search. Designs are assessed and compared by simulation of the distribution of efficiencies relative to locally optimal designs over a space of possible models. Exact designs are investigated for two applications, and their advantages over factorial and central composite designs are demonstrated.

Clustering Process Analysis in a Large-Size Dropshaft and in a Hydraulic Jump

Recent efforts in the characterization of air-water flows properties have included some clustering process analysis. A cluster of bubbles is defined as a group of two or more bubbles, with a distinct separation from other bubbles before and after the cluster. The present paper compares the results of clustering processes two hydraulic structures. That is, a large-size dropshaft and a hydraulic jump in a rectangular horizontal channel. The comparison highlighted some significant differences in clustering production and structures. Both dropshaft and hydraulic jump flows are complex turbulent shear flows, and some clustering index may provide some measure of the bubble-turbulence interactions and associated energy dissipation.

Data analysis in multiple-frequency bioelectrical impedance analysis

The performance of three analytical methods for multiple-frequency bioelectrical impedance analysis (MFBIA) data was assessed. The methods were the established method of Cole and Cole, the newly proposed method of Siconolfi and co-workers and a modification of this procedure. Method performance was assessed from the adequacy of the curve fitting techniques, as judged by the correlation coefficient and standard error of the estimate, and the accuracy of the different methods in determining the theoretical values of impedance parameters describing a set of model electrical circuits. The experimental data were well fitted by all curve-fitting procedures (r = 0.9 with SEE 0.3 to 3.5% or better for most circuit-procedure combinations). Cole-Cole modelling provided the most accurate estimates of circuit impedance values, generally within 1-2% of the theoretical values, followed by the Siconolfi procedure using a sixth-order polynomial regression (1-6% variation). None of the methods, however, accurately estimated circuit parameters when the measured impedances were low (<20 Omega) reflecting the electronic limits of the impedance meter used. These data suggest that Cole-Cole modelling remains the preferred method for the analysis of MFBIA data.

Parallel processing and image analysis in the eyes of mantis shrimps

The compound eyes of mantis shrimps, a group of tropical marine crustaceans, incorporate principles of serial and parallel processing of visual information that may be applicable to artificial imaging systems. Their eyes include numerous specializations for analysis of the spectral and polarizational properties of light, and include more photoreceptor classes for analysis of ultraviolet light, color, and polarization than occur in any other known visual system. This is possible because receptors in different regions of the eye are anatomically diverse and incorporate unusual structural features, such as spectral filters, not seen in other compound eyes. Unlike eyes of most other animals, eyes of mantis shrimps must move to acquire some types of visual information and to integrate color and polarization with spatial vision. Information leaving the retina appears to be processed into numerous parallel data streams leading into the central nervous system, greatly reducing the analytical requirements at higher levels. Many of these unusual features of mantis shrimp vision may inspire new sensor designs for machine vision

A comparison of low-storage strategies for spectral analysis in dissipative systems: filter diagonalisation in the Lanczos representation and harmonic inversion of the Chebychev-order-domain autocorrelation function

We compare the performance of two different low-storage filter diagonalisation (LSFD) strategies in the calculation of complex resonance energies of the HO2, radical. The first is carried out within a complex-symmetric Lanczos subspace representation [H. Zhang, S.C. Smith, Phys. Chem. Chem. Phys. 3 (2001) 2281]. The second involves harmonic inversion of a real autocorrelation function obtained via a damped Chebychev recursion [V.A. Mandelshtam, H.S. Taylor, J. Chem. Phys. 107 (1997) 6756]. We find that while the Chebychev approach has the advantage of utilizing real algebra in the time-consuming process of generating the vector recursion, the Lanczos, method (using complex vectors) requires fewer iterations, especially for low-energy part of the spectrum. The overall efficiency in calculating resonances for these two methods is comparable for this challenging system. (C) 2001 Elsevier Science B.V. All rights reserved.

Host plant specificity in several species of generalist mite predators

1. Species in the genus Neoseiulus are considered to be generalist predators. with some species used in biological control programmes against phytophagous mites and insects. 2. A general survey of Neoseiulus species in inland Australia indicated that different species are associated with particular tree species. This pattern of host plant use was investigated for four Neoseiulus species (N. buxeus, N. cappari, N. brigarinus, N. eremitus) by means of a sampling programme through time and across space. 3. Each species of Neoseiulus was collected entirely or mostly from one species of tree: little or no overlap was detected despite the tree species growing in well-mixed stands. Host plant specificity thus appears to be strong in this genus. 4. Species in two other genera (Pholaseius and Australiseiulus), also considered to be predatory, showed a similar association with particular tree species. 5. The implications for the use of these predators in biological control are considerable. In particular, phytoseiid species with specific needs in terms of host plants may not be suitable for use as general purpose predators. Meeting the needs of phytoseiids through the modification of host plant attributes may be a step towards enhancing their efficacy as biological control agents.

Estimation of total body water from bioelectrical impedance analysis in patients with pancreatic cancer - agreement between three methods of prediction

Introduction Bioelectrical impedance analysis (BIA) is a useful field measure to estimate total body water (TBW). No prediction formulae have been developed or validated against a reference method in patients with pancreatic cancer. The aim of this study was to assess the agreement between three prediction equations for the estimation of TBW in cachectic patients with pancreatic cancer. Methods Resistance was measured at frequencies of 50 and 200 kHz in 18 outpatients (10 males and eight females, age 70.2 +/- 11.8 years) with pancreatic cancer from two tertiary Australian hospitals. Three published prediction formulae were used to calculate TBW - TBWs developed in surgical patients, TBWca-uw and TBWca-nw developed in underweight and normal weight patients with end-stage cancer. Results There was no significant difference in the TBW estimated by the three prediction equations - TBWs 32.9 +/- 8.3 L, TBWca-nw 36.3 +/- 7.4 L, TBWca-uw 34.6 +/- 7.6 L. At a population level, there is agreement between prediction of TBW in patients with pancreatic cancer estimated from the three equations. The best combination of low bias and narrow limits of agreement was observed when TBW was estimated from the equation developed in the underweight cancer patients relative to the normal weight cancer patients. When no established BIA prediction equation exists, practitioners should utilize an equation developed in a population with similar critical characteristics such as diagnosis, weight loss, body mass index and/or age. Conclusions Further research is required to determine the accuracy of the BIA prediction technique against a reference method in patients with pancreatic cancer.

Application of ICP-MS trace element analysis in study of ancient Chinese ceramics

Thirty-nine trace elements of the Song-Yuan period (960-1368 AD) porcelain bodies from Cizhou, Jizhou and Longquanwu kilns were analyzed with ICP-MS, a technique rarely used in Chinese archaeometry, to investigate its potential application in such studies. Trace element compositions clearly reflect the distinctive raw materials and their mineralogy at the three kilns and allow their products to be distinguished. Significant chemical variations are also observed between Yuan and Song-Jing dynasties samples from Cizhou as well as fine and coarse porcelain bodies from Longquanwu. In Cizhou, porcelains of better quality which imitate the famous Ding kiln have trace element features distinctive from ordinary Cizhou products, that indicates geochemically distinctive raw materials were used and which possibly also underwent extra refining prior to use. The distinct trace element features of different kilns and the various types of porcelains from an individual kiln can be interpreted from a geochemical perspective. ICP-MS can provide a large amount of valuable information about ancient Chinese ceramics as it is capable of analyzing >40 elements with a typical of precision < 2%.