Estimation of cosmological parameters using adaptive importance sampling

We present a Bayesian sampling algorithm called adaptive importance sampling or population Monte Carlo (PMC), whose computational workload is easily parallelizable and thus has the potential to considerably reduce the wall-clock time required for sampling, along with providing other benefits. To assess the performance of the approach for cosmological problems, we use simulated and actual data consisting of CMB anisotropies, supernovae of type Ia, and weak cosmological lensing, and provide a comparison of results to those obtained using state-of-the-art Markov chain Monte Carlo (MCMC). For both types of data sets, we find comparable parameter estimates for PMC and MCMC, with the advantage of a significantly lower wall-clock time for PMC. In the case of WMAP5 data, for example, the wall-clock time scale reduces from days for MCMC to hours using PMC on a cluster of processors. Other benefits of the PMC approach, along with potential difficulties in using the approach, are analyzed and discussed.

Networks of stored grain diseases and pests: Strategies for sampling and mitigation

Pathogens and pests of stored grains move through complex dynamic networks linking fields, farms, and bulk storage facilities. Human transport and other forms of dispersal link the components of this network. A network model for pathogen and pest movement through stored grain systems is a first step toward new sampling and mitigation strategies that utilize information about the network structure. An understanding of network structure can be applied to identifying the key network components for pathogen or pest movement through the system. For example, it may be useful to identify a network node, such as a local grain storage facility, through which grain from a large number of fields will be accumulated and move through the network. This node may be particularly important for sampling and mitigation. In some cases more detailed information about network structure can identify key nodes that link two large sections of the network, such that management at the key nodes will greatly reduce the risk of spread between the two sections. In addition to the spread of particular species of pathogens and pests, we also evaluate the spread of problematic subpopulations, such as subpopulations with pesticide resistance. We present an analysis of stored grain pathogen and pest networks for Australia and the United States.

The need for speed: Timely prevention of the dispersal of noxious weeds in relief fodder using efficient sampling procedures

Invasive and noxious weeds are well known as a pervasive problem, imposing significant economic burdens on all areas of agriculture. Whilst there are multiple possible pathways of weed dispersal in this industry, of particular interest to this discussion is the unintended dispersal of weed seeds within fodder. During periods of drought or following natural disasters such as wild fire or flood, there arises the urgent need for 'relief' fodder to ensure survival and recovery of livestock. In emergency situations, relief fodder may be sourced from widely dispersed geographic regions, and some of these regions may be invaded by an extensive variety of weeds that are both exotic and detrimental to the intended destination for the fodder. Pasture hay is a common source of relief fodder and it typically consists of a mixture of grassy and broadleaf species that may include noxious weeds. When required urgently, pasture hay for relief fodder can be cut, baled, and transported over long distances in a short period of time, with little opportunity for prebaling inspection. It appears that, at the present time, there has been little effort towards rapid testing of bales, post-baling, for the presence of noxious weeds, as a measure to prevent dispersal of seeds. Published studies have relied on the analysis of relatively small numbers of bales, tested to destruction, in order to reveal seed species for identification and enumeration. The development of faster, more reliable, and non-destructive sampling methods is essential to increase the fodder industry's capacity to prevent the dispersal of noxious weeds to previously unaffected locales.

A note on sampling chironomids for RNA-based studies of natural populations that retains critical morphological vouchers

The rapid uptake of transcriptomic approaches in freshwater ecology has seen a wealth of data produced concerning the ways in which organisms interact with their environment on a molecular level. Typically, such studies focus either at the community level and so don’t require species identifications, or on laboratory strains of known species identity or natural populations of large, easily identifiable taxa. For chironomids, impediments still exist for applying these technologies to natural populations because they are small-bodied and often require time-consuming secondary sorting of stream material and morphological voucher preparation to confirm species diagnosis. These procedures limit the ability to maintain RNA quantity and quality in such organisms because RNA degrades rapidly and gene expression can be altered rapidly in organisms; thereby limiting the inclusion of such taxa in transcriptomic studies. Here, we demonstrate that these limitations can be overcome and outline an optimised protocol for collecting, sorting and preserving chironomid larvae that enables retention of both morphological vouchers and RNA for subsequent transcriptomics purposes. By ensuring that sorting and voucher preparation are completed within <4 hours after collection and that samples are kept cold at all times, we successfully retained both RNA and morphological vouchers from all specimens. Although not prescriptive in specific methodology, we anticipate that this paper will assist in promoting transcriptomic investigations of the sublethal impact on chironomid gene expression of changes to aquatic environments.

Effect of human chorionic gonadotropin on serum levels of progesterone and estrogens in the pregnant bonnet monkev (Macaca radiata)

Administration of human chorionic gonadotropin to pregnant bonnet monkeys (Macaca radiata) at 55-60 days and 130-140 days of pregnancy resulted in a significant increase in serum progesterone levels. This effect could be observed even in lutectomized monkeys.However, no significant change in the serum estrogen level was noticed. These results suggest that although no chorionic gonadotropin is detectable in the serum after 35 days of pregnancy, the foetoplacental steroidogenic system is still responsive to exogenous gonadotropic stimulation.

Optimal adaptive sequential spatial sampling of soil using pair-copulas

A spatial sampling design that uses pair-copulas is presented that aims to reduce prediction uncertainty by selecting additional sampling locations based on both the spatial configuration of existing locations and the values of the observations at those locations. The novelty of the approach arises in the use of pair-copulas to estimate uncertainty at unsampled locations. Spatial pair-copulas are able to more accurately capture spatial dependence compared to other types of spatial copula models. Additionally, unlike traditional kriging variance, uncertainty estimates from the pair-copula account for influence from measurement values and not just the configuration of observations. This feature is beneficial, for example, for more accurate identification of soil contamination zones where high contamination measurements are located near measurements of varying contamination. The proposed design methodology is applied to a soil contamination example from the Swiss Jura region. A partial redesign of the original sampling configuration demonstrates the potential of the proposed methodology.

Effect Of Human Chorionic Gonadotrophin And Ovine Luteinizing Hormone On Rat Ovarian Macromolecular Metabolism

Administration of human chorionic gonadotrophin (HCG) or ovine LH to immature rats primed with pregnant mare serum gonadotrophin (PMSG) stimulated the rate of synthesis of polyadenylic acid (poly A)-rich RNA in the ovaries. The rate of total RNA synthesis was not affected significantly by hormone treatment, whereas protein synthesis was enhanced. The increase in the rate of synthesis of poly(A)-rich RNA in the ovaries could be inferred as induction of messenger RNA synthesis after the hormone treatment. The poly(A)-rich nature of the isolated RNA was established by oligo(dT)–cellulose chromatography, binding to Millipore filter disks and hydridization with [3H]polyuridylic acid. The level of cyclic AMP in the ovaries of such rats was also raised after administration of LH, the increase coincided with the increase in the rate of synthesis of poly(A)-rich RNA. The implications of these results are discussed in the light of the biochemical basis of luteinization and the action of LH.

Mapping of assembled epitopic regions of human chorionic gonadotropin reveals proximity of CTP alpha to the determinant loop beta 93-100

Three overlapping assembled epitopes of beta hCG have been mapped using MAb probes and a single step solid phase radioimmunoassay. These epitopes have been shown to be at receptor binding region comprising of the loop region beta Cys93-Cys100. Importance of disulphide bonds in maintaining integrity of these epitopes is assessed. Two MAbs (INN 58 and INN 22) interact with the beta region as well as the alpha C-terminal peptide, while the other MAb INN 24 interacts with only the beta region. Cross-reactivity pattern with beta hCG and hLH as web as the reported crystal structure of hCG substantiates the epitope identification. The results demonstrate utility of MAbs as probes in investigations on three-dimensional structure of gonadatropins.

Sampling frequency affects estimates of annual nitrous oxide fluxes

Quantifying nitrous oxide (N(2)O) fluxes, a potent greenhouse gas, from soils is necessary to improve our knowledge of terrestrial N(2)O losses. Developing universal sampling frequencies for calculating annual N(2)O fluxes is difficult, as fluxes are renowned for their high temporal variability. We demonstrate daily sampling was largely required to achieve annual N(2)O fluxes within 10% of the best estimate for 28 annual datasets collected from three continents, Australia, Europe and Asia. Decreasing the regularity of measurements either under- or overestimated annual N(2)O fluxes, with a maximum overestimation of 935%. Measurement frequency was lowered using a sampling strategy based on environmental factors known to affect temporal variability, but still required sampling more than once a week. Consequently, uncertainty in current global terrestrial N(2)O budgets associated with the upscaling of field-based datasets can be decreased significantly using adequate sampling frequencies.

Analysis of human chorionic gonadotropin-monoclonal antibody interaction in BIAcore

Kinetic studies of macromolecular ligand-ligate interaction have generated ample interest since the advent of plasmon resonance based instruments like BIAcore. Most of the studies reported in literature assume a simple 1 : 1 Langmuir binding and complete reversibility of the system. However we observed that in a high affinity antigen-antibody system [human chorionic gonadotropin-monoclonal antibody (hCG-mAb)] dissociation is insignificant and the sensogram data cannot be used to measure the equilibrium and kinetic parameters. At low concentrations of mAb the complete sensogram could be fitted to a single exponential. Interestingly we found that at higher mAb concentrations, the binding data did not conform to a simple bimolecular model. Instead, the data fitted a two-step model, which may be because of surface heterogeneity of affinity sites. In this paper, we report on the global fit of the sensograms. We have developed a method by which a single two-minute sensogram can be used in high affinity systems to measure the association rate constant of the reaction and the functional capacity of the ligand (hCG) immobilized on the chip. We provide a rational explanation for the discrepancies generally observed in most of the BIAcore sensograms

Stability of assembled epitopes on human chorionic gonadotropin to covalent modifications

A measure of stability of a given epitope is an important parameter in the exploration of the utility of a desired MAb. It defines the conditions necessary for using MAbs as an investigative tool in several research methodologies and therapeutic protocols. Despite these obvious interests the lack of simple and rapid assay systems for quantitating MAb-Ag interactions has largely hampered these studies. A single step MAb-Solid Phase Radioimmunoassay (SS-SPRIA), is described which eliminates errors that may arise with multistep sandwich assays. SS-SPRIA has been used to demonstrate the differential stability of the assembled epitopes on gonadotropins. Differential stability towards specific reagents can be exploited to identify aminoacid residues at the epitopic site. Inactivation of an epitopic region is indicative of the presence of the group modified, provided conformational relaxations are not induced due to modifications at distant sites. Here we provide evidence to validate these conclusions.

Autonomous greenhouse gas sampling using multiple robotic boats

Accurately quantifying total greenhouse gas emissions (e.g. methane) from natural systems such as lakes, reservoirs and wetlands requires the spatial-temporal measurement of both diffusive and ebullitive (bubbling) emissions. Traditional, manual, measurement techniques provide only limited localised assessment of methane flux, often introducing significant errors when extrapolated to the whole-of-system. In this paper, we directly address these current sampling limitations and present a novel multiple robotic boat system configured to measure the spatiotemporal release of methane to atmosphere across inland waterways. The system, consisting of multiple networked Autonomous Surface Vehicles (ASVs) and capable of persistent operation, enables scientists to remotely evaluate the performance of sampling and modelling algorithms for real-world process quantification over extended periods of time. This paper provides an overview of the multi-robot sampling system including the vehicle and gas sampling unit design. Experimental results are shown demonstrating the system’s ability to autonomously navigate and implement an exploratory sampling algorithm to measure methane emissions on two inland reservoirs.