The impact of Solanum elaeagnifolium, an invasive plant in the Mediterranean, on the flower visitation and seed set of the native co-flowering species Glaucium flavum

We examined the effect of the invasive Solanum elaeagnifolium (Solanaceae) on flower visitation patterns and seed set of the co-flowering native Glaucium flavum (Papaveraceae). We observed flowering G. flavum plants in invaded and uninvaded sites and found that G. flavum flowers in uninvaded sites received significantly more total visits. In addition, we hand-pollinated flowers on plants of G. flavum with (i) pure conspecific pollen, (ii) pure S. elaeagnifolium pollen and (iii) three different mixtures of the two types of pollen (containing 25, 50 and 75% invasive pollen). As a control, flowers were left unmanipulated or were permanently bagged. Seed set did not differ significantly between flowers receiving pollen mixtures and pure conspecific pollen. However, in the open pollination treatment, seed set was significantly lower than in the 100% conspecific pollen treatment, which suggests pollen limitation. Bagged flowers had very low seed set. G. flavum was generally resilient against the deposition of S. elaeagnifolium pollen.

Purpose built teaching equipment for a laboratory based course in three phase machines and drives

The hazards associated with high voltage three phase inverters ond the rotating sha@s of large electrical machines have resulted in most of the engineering courses covering these topics to be predominantly theoretical. This paper describes a set of purpose built, low voltage and low cost teaching equipment which allows the “hands on I’ instruction of three phase inverters and rotating machines. By using low voltages, the student can experiment freely with the motors and inverter and can access all of the current and voltage waveforms, which until now could only be studied in text books or observed as part of laboratory demonstrations. Both the motor and the inverter designs are optimized for teaching purposes, cost around $25 and can be made with minimal effort.

Three-phase machines and drives - Equipment for a laboratory-based course

The hazards associated with high-voltage three-phase inverters and high-powered large electrical machines have resulted in most of the engineering courses covering three-phase machines and drives theoretically. This paper describes a set of purpose-built, low-voltage, and low-cost teaching equipment that allows the hands-on instruction of three-phase inverters and rotating machines. The motivation for moving towards a system running at low voltages is that the students can safely experiment freely with the motors and inverter. The students can also access all of the current and voltage waveforms, which until now could only be studied in textbooks or observed as part of laboratory demonstrations. Both the motor and the inverter designs are for teaching purposes and require minimal effort and cost.

Complex formation of bovine serum albumin with a poly(ethylene glycol) lipid conjugate

In this work, we report the formation of complexes by self-assembly of bovine serum albumin (BSA) with a poly(ethylene glycol) lipid conjugate (PEG(2000)-PE) in phosphate saline buffer solution (pH 7.4). Three different sets of samples have been studied. The BSA concentration remained fixed (1, 0.01, or 0.001 wt % BSA) within each set of samples, while the PEG(2000)-PE concentration was varied. Dynamic light scattering (DLS), rheology, and small-angle X-ray scattering (SAXS) were used to study samples with 1 wt % BSA. DLS showed that BSA/PEG(2000)-PE aggregates have a size intermediate between a BSA monomer and a PEG(2000)-PE micelle. Rheology suggested that BSA/PEG(2000)-PE complexes might be surrounded by a relatively compact PEG-lipid shell, while SAXS results showed that depletion forces do not take an important role in the stabilization of the complexes. Samples containing 0.01 wt % BSA were studied by circular dichroism (CD) and ultraviolet fluorescence spectroscopy (UV). UV results showed that at low concentrations of PEG-lipid, PEG(2000)-PE binds to tryptophan (Trp) groups in BSA, while at high concentrations of PEG-lipid the Trp groups are exposed to water. CD results showed that changes in Trp environment take place with a minimal variation of the BSA secondary structure elements. Finally, samples containing 0.001 wt % BSA were studied by zeta-potential experiments. Results showed that steric interactions might play an important role in the stabilization of the BSA/PEG(2000)-PE complexes.

Revised QUICKI provides a strong surrogate estimate of insulin sensitivity when compared with the minimal model

OBJECTIVE: To compare insulin sensitivity (Si) from a frequently sampled intravenous glucose tolerance test (FSIGT) and subsequent minimal model analyses with surrogate measures of insulin sensitivity and resistance and to compare features of the metabolic syndrome between Caucasians and Indian Asians living in the UK. SUBJECTS: In all, 27 healthy male volunteers (14 UK Caucasians and 13 UK Indian Asians), with a mean age of 51.2 +/- 1.5 y, BMI of 25.8 +/- 0.6 kg/m(2) and Si of 2.85 +/- 0.37. MEASUREMENTS: Si was determined from an FSIGT with subsequent minimal model analysis. The concentrations of insulin, glucose and nonesterified fatty acids (NEFA) were analysed in fasting plasma and used to calculate surrogate measure of insulin sensitivity (quantitative insulin sensitivity check index (QUICKI), revised QUICKI) and resistance (homeostasis for insulin resistance (HOMA IR), fasting insulin resistance index (FIRI), Bennetts index, fasting insulin, insulin-to-glucose ratio). Plasma concentrations of triacylglycerol (TAG), total cholesterol, high density cholesterol, (HDL-C) and low density cholesterol, (LDL-C) were also measured in the fasted state. Anthropometric measurements were conducted to determine body-fat distribution. RESULTS: Correlation analysis identified the strongest relationship between Si and the revised QUICKI (r = 0.67; P = 0.000). Significant associations were also observed between Si and QUICKI (r = 0.51; P = 0.007), HOMA IR (r = -0.50; P = 0.009), FIRI and fasting insulin. The Indian Asian group had lower HDL-C (P = 0.001), a higher waist-hip ratio (P = 0.01) and were significantly less insulin sensitive (Si) than the Caucasian group (P = 0.02). CONCLUSION: The revised QUICKI demonstrated a statistically strong relationship with the minimal model. However, it was unable to differentiate between insulin-sensitive and -resistant groups in this study. Future larger studies in population groups with varying degrees of insulin sensitivity are recommended to investigate the general applicability of the revised QUICKI surrogate technique.

Comprehension of wh-questions and declarative sentences in agrammatic aphasia: the set partition hypothesis

Problematic trace-antecedent relations between deep and surface structure have been a dominant theme in sentence comprehension in agrammatism. We challenge this view and propose that the comprehension in agrammatism in declarative sentences and wh-questions stems from impaired processing in logical form. We present new data from wh-questions and declarative sentences and advance a new hypothesis which we call the set partition hypothesis. We argue that elements that signal set partition operations influence sentence comprehension while trace-antecedent relations remain intact. (C) 2007 Elsevier Ltd. All rights reserved.

Simulating global properties of electroencephalograms with minimal random neural networks

The human electroencephalogram (EEG) is globally characterized by a 1/f power spectrum superimposed with certain peaks, whereby the "alpha peak" in a frequency range of 8-14 Hz is the most prominent one for relaxed states of wakefulness. We present simulations of a minimal dynamical network model of leaky integrator neurons attached to the nodes of an evolving directed and weighted random graph (an Erdos-Renyi graph). We derive a model of the dendritic field potential (DFP) for the neurons leading to a simulated EEG that describes the global activity of the network. Depending on the network size, we find an oscillatory transition of the simulated EEG when the network reaches a critical connectivity. This transition, indicated by a suitably defined order parameter, is reflected by a sudden change of the network's topology when super-cycles are formed from merging isolated loops. After the oscillatory transition, the power spectra of simulated EEG time series exhibit a 1/f continuum superimposed with certain peaks. (c) 2007 Elsevier B.V. All rights reserved.

A kernel-based two-class classifier for imbalanced data sets

Many kernel classifier construction algorithms adopt classification accuracy as performance metrics in model evaluation. Moreover, equal weighting is often applied to each data sample in parameter estimation. These modeling practices often become problematic if the data sets are imbalanced. We present a kernel classifier construction algorithm using orthogonal forward selection (OFS) in order to optimize the model generalization for imbalanced two-class data sets. This kernel classifier identification algorithm is based on a new regularized orthogonal weighted least squares (ROWLS) estimator and the model selection criterion of maximal leave-one-out area under curve (LOO-AUC) of the receiver operating characteristics (ROCs). It is shown that, owing to the orthogonalization procedure, the LOO-AUC can be calculated via an analytic formula based on the new regularized orthogonal weighted least squares parameter estimator, without actually splitting the estimation data set. The proposed algorithm can achieve minimal computational expense via a set of forward recursive updating formula in searching model terms with maximal incremental LOO-AUC value. Numerical examples are used to demonstrate the efficacy of the algorithm.

Backward elimination model construction for regression and classification using leave-one-out criteria

A fundamental principle in practical nonlinear data modeling is the parsimonious principle of constructing the minimal model that explains the training data well. Leave-one-out (LOO) cross validation is often used to estimate generalization errors by choosing amongst different network architectures (M. Stone, "Cross validatory choice and assessment of statistical predictions", J. R. Stast. Soc., Ser. B, 36, pp. 117-147, 1974). Based upon the minimization of LOO criteria of either the mean squares of LOO errors or the LOO misclassification rate respectively, we present two backward elimination algorithms as model post-processing procedures for regression and classification problems. The proposed backward elimination procedures exploit an orthogonalization procedure to enable the orthogonality between the subspace as spanned by the pruned model and the deleted regressor. Subsequently, it is shown that the LOO criteria used in both algorithms can be calculated via some analytic recursive formula, as derived in this contribution, without actually splitting the estimation data set so as to reduce computational expense. Compared to most other model construction methods, the proposed algorithms are advantageous in several aspects; (i) There are no tuning parameters to be optimized through an extra validation data set; (ii) The procedure is fully automatic without an additional stopping criteria; and (iii) The model structure selection is directly based on model generalization performance. The illustrative examples on regression and classification are used to demonstrate that the proposed algorithms are viable post-processing methods to prune a model to gain extra sparsity and improved generalization.

Fault tolerance of Mobius cubes under two forbidden fault set models

An n-dimensional Mobius cube, 0MQ(n) or 1MQ(n), is a variation of n-dimensional cube Q(n) which possesses many attractive properties such as significantly smaller communication delay and stronger graph-embedding capabilities. In some practical situations, the fault tolerance of a distributed memory multiprocessor system can be measured more precisely by the connectivity of the underlying graph under forbidden fault set models. This article addresses the connectivity of 0MQ(n)/1MQ(n), under two typical forbidden fault set models. We first prove that the connectivity of 0MQ(n)/1MQ(n) is 2n - 2 when the fault set does not contain the neighborhood of any vertex as a subset. We then prove that the connectivity of 0MQ(n)/1MQ(n) is 3n - 5 provided that the neighborhood of any vertex as well as that of any edge cannot fail simultaneously These results demonstrate that 0MQ(n)/1MQ(n) has the same connectivity as Q(n) under either of the previous assumptions.

Modelling sediment supply and transport in the River Lugg: strategies for controlling sediment loads

The River Lugg has particular problems with high sediment loads that have resulted in detrimental impacts on ecology and fisheries. A new dynamic, process-based model of hydrology and sediments (INCA- SED) has been developed and applied to the River Lugg system using an extensive data set from 1995–2008. The model simulates sediment sources and sinks throughout the catchment and gives a good representation of the sediment response at 22 reaches along the River Lugg. A key question considered in using the model is the management of sediment sources so that concentrations and bed loads can be reduced in the river system. Altogether, five sediment management scenarios were selected for testing on the River Lugg, including land use change, contour tillage, hedging and buffer strips. Running the model with parameters altered to simulate these five scenarios produced some interesting results. All scenarios achieved some reduction in sediment levels, with the 40% land use change achieving the best result with a 19% reduction. The other scenarios also achieved significant reductions of between 7% and 9%. Buffer strips produce the best result at close to 9%. The results suggest that if hedge introduction, contour tillage and buffer strips were all applied, sediment reductions would total 24%, considerably improving the current sediment situation. We present a novel cost-effectiveness analysis of our results where we use percentage of land removed from production as our cost function. Given the minimal loss of land associated with contour tillage, hedges and buffer strips, we suggest that these management practices are the most cost-effective combination to reduce sediment loads.