Assessment of intercalibration methods for satellite microwave humidity sounders

Three methods for intercalibrating humidity sounding channels are compared to assess their merits and demerits. The methods use the following: (1) natural targets (Antarctica and tropical oceans), (2) zonal average brightness temperatures, and (3) simultaneous nadir overpasses (SNOs). Advanced Microwave Sounding Unit-B instruments onboard the polar-orbiting NOAA 15 and NOAA 16 satellites are used as examples. Antarctica is shown to be useful for identifying some of the instrument problems but less promising for intercalibrating humidity sounders due to the large diurnal variations there. Owing to smaller diurnal cycles over tropical oceans, these are found to be a good target for estimating intersatellite biases. Estimated biases are more resistant to diurnal differences when data from ascending and descending passes are combined. Biases estimated from zonal-averaged brightness temperatures show large seasonal and latitude dependence which could have resulted from diurnal cycle aliasing and scene-radiance dependence of the biases. This method may not be the best for channels with significant surface contributions. We have also tested the impact of clouds on the estimated biases and found that it is not significant, at least for tropical ocean estimates. Biases estimated from SNOs are the least influenced by diurnal cycle aliasing and cloud impacts. However, SNOs cover only relatively small part of the dynamic range of observed brightness temperatures.

Cloud clearing techniques over land for land surface temperature retrieval from the Advanced Along Track Scanning Radiometer

We present five new cloud detection algorithms over land based on dynamic threshold or Bayesian techniques, applicable to the Advanced Along Track Scanning Radiometer (AATSR) instrument and compare these with the standard threshold based SADIST cloud detection scheme. We use a manually classified dataset as a reference to assess algorithm performance and quantify the impact of each cloud detection scheme on land surface temperature (LST) retrieval. The use of probabilistic Bayesian cloud detection methods improves algorithm true skill scores by 8-9 % over SADIST (maximum score of 77.93 % compared to 69.27 %). We present an assessment of the impact of imperfect cloud masking, in relation to the reference cloud mask, on the retrieved AATSR LST imposing a 2 K tolerance over a 3x3 pixel domain. We find an increase of 5-7 % in the observations falling within this tolerance when using Bayesian methods (maximum of 92.02 % compared to 85.69 %). We also demonstrate that the use of dynamic thresholds in the tests employed by SADIST can significantly improve performance, applicable to cloud-test data to provided by the Sea and Land Surface Temperature Radiometer (SLSTR) due to be launched on the Sentinel 3 mission (estimated 2014).

Polymer protected gold nanoparticles: synthesis, characterization and application in catalysis

This review discusses the stabilization of gold nanoparticles (AuNPs) by nonionic, anionic, cationic and amphoteric polymers. The protocols used for synthesis of AuNPs in aqueous and organic solvents are described. Size, shape and morphology of AuNPs are characterized by various physicochemical methods. Application aspects of polymer-protected AuNPs in catalysis are outlined.

Advanced multivariate analysis to assess remediation of hydrocarbons in soils

Accurate monitoring of degradation levels in soils is essential in order to understand and achieve complete degradation of petroleum hydrocarbons in contaminated soils. We aimed to develop the use of multivariate methods for the monitoring of biodegradation of diesel in soils and to determine if diesel contaminated soils could be remediated to a chemical composition similar to that of an uncontaminated soil. An incubation experiment was set up with three contrasting soil types. Each soil was exposed to diesel at varying stages of degradation and then analysed for key hydrocarbons throughout 161 days of incubation. Hydrocarbon distributions were analysed by Principal Coordinate Analysis and similar samples grouped by cluster analysis. Variation and differences between samples were determined using permutational multivariate analysis of variance. It was found that all soils followed trajectories approaching the chemical composition of the unpolluted soil. Some contaminated soils were no longer significantly different to that of uncontaminated soil after 161 days of incubation. The use of cluster analysis allows the assignment of a percentage chemical similarity of a diesel contaminated soil to an uncontaminated soil sample. This will aid in the monitoring of hydrocarbon contaminated sites and the establishment of potential endpoints for successful remediation.

Evaluation of simulated sea-ice concentrations from sea-ice/ocean models using satellite data and polynya classification methods

Sea-ice concentrations in the Laptev Sea simulated by the coupled North Atlantic-Arctic Ocean-Sea-Ice Model and Finite Element Sea-Ice Ocean Model are evaluated using sea-ice concentrations from Advanced Microwave Scanning Radiometer-Earth Observing System satellite data and a polynya classification method for winter 2007/08. While developed to simulate largescale sea-ice conditions, both models are analysed here in terms of polynya simulation. The main modification of both models in this study is the implementation of a landfast-ice mask. Simulated sea-ice fields from different model runs are compared with emphasis placed on the impact of this prescribed landfast-ice mask. We demonstrate that sea-ice models are not able to simulate flaw polynyas realistically when used without fast-ice description. Our investigations indicate that without landfast ice and with coarse horizontal resolution the models overestimate the fraction of open water in the polynya. This is not because a realistic polynya appears but due to a larger-scale reduction of ice concentrations and smoothed ice-concentration fields. After implementation of a landfast-ice mask, the polynya location is realistically simulated but the total open-water area is still overestimated in most cases. The study shows that the fast-ice parameterization is essential for model improvements. However, further improvements are necessary in order to progress from the simulation of large-scale features in the Arctic towards a more detailed simulation of smaller-scaled features (here polynyas) in an Arctic shelf sea.

Sampling uncertainty in gridded sea surface temperature products and Advanced Very High Resolution Radiometer (AVHRR) Global Area Coverage (GAC) data

Sea surface temperature (SST) data are often provided as gridded products, typically at resolutions of order 0.05 degrees from satellite observations to reduce data volume at the request of data users and facilitate comparison against other products or models. Sampling uncertainty is introduced in gridded products where the full surface area of the ocean within a grid cell cannot be fully observed because of cloud cover. In this paper we parameterise uncertainties in SST as a function of the percentage of clear-sky pixels available and the SST variability in that subsample. This parameterisation is developed from Advanced Along Track Scanning Radiometer (AATSR) data, but is applicable to all gridded L3U SST products at resolutions of 0.05-0.1 degrees, irrespective of instrument and retrieval algorithm, provided that instrument noise propagated into the SST is accounted for. We also calculate the sampling uncertainty of ~0.04 K in Global Area Coverage (GAC) Advanced Very High Resolution Radiometer (AVHRR) products, using related methods.

In silico identification and characterization of protein-ligand binding sites

Protein–ligand binding site prediction methods aim to predict, from amino acid sequence, protein–ligand interactions, putative ligands, and ligand binding site residues using either sequence information, structural information, or a combination of both. In silico characterization of protein–ligand interactions has become extremely important to help determine a protein’s functionality, as in vivo-based functional elucidation is unable to keep pace with the current growth of sequence databases. Additionally, in vitro biochemical functional elucidation is time-consuming, costly, and may not be feasible for large-scale analysis, such as drug discovery. Thus, in silico prediction of protein–ligand interactions must be utilized to aid in functional elucidation. Here, we briefly discuss protein function prediction, prediction of protein–ligand interactions, the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and the Continuous Automated EvaluatiOn (CAMEO) competitions, along with their role in shaping the field. We also discuss, in detail, our cutting-edge web-server method, FunFOLD for the structurally informed prediction of protein–ligand interactions. Furthermore, we provide a step-by-step guide on using the FunFOLD web server and FunFOLD3 downloadable application, along with some real world examples, where the FunFOLD methods have been used to aid functional elucidation.

Immunohistochemical Characterization of Canine Prostatic Intraepithelial Neoplasia

The development of prostate cancer is believed to be a multistep process, progressing sequentially from normal epithelium, to prostatic intraepithelial neoplasia (PIN) and, finally, to invasive neoplasia. Malignant stem cells within the basal cell layer of the prostatic epithelium are believed to play an important role in the failure of androgen-ablation therapy that occurs in the most advanced form of prostate cancer. The aim of the present study was to immunohistochemically characterize the lesions of canine PIN. Prostatic tissue from five dogs with PIN was compared with normal prostate tissue from nine further dogs. There was an increase in the number of basal epithelial cells in lesions consistent with PIN as defined by expression of the nuclear protein p63. These lesions had elevated expression of proliferating cell nuclear antigen (PCNA) and heterogeneous labelling for the nuclear androgen receptor (AR). These findings suggest that the basal cells present in PIN may play a role in canine prostate carcinogenesis and that the proliferation of these cells occurs despite the heterogeneous expression of the AR. (C) 2009 Elsevier Ltd. All rights reserved.

Geophysical investigation using resistivity and GPR methods: a case study of a lubricant oil waste disposal area in the city of Ribeiro Preto, So Paulo, Brazil

Geophysics has been shown to be effective in identifying areas contaminated by waste disposal, contributing to the greater efficiency of soundings programs and the installation of monitoring wells. In the study area, four trenches were constructed with a total volume of about 25,000 m(3). They were almost totally filled with re-refined lubricating oil waste for approximately 25 years. No protection liners were used in the bottoms and laterals of the disposal trenches. The purpose of this work is to evaluate the potential of the resistivity and ground penetrating radar (GPR) methods in characterizing the contamination of this lubricant oil waste disposal area in Ribeiro Preto, SP, situated on the geological domain of the basalt spills of the Serra Geral Formation and the sandstones of the Botucatu Formation. Geophysical results were shown in 2D profiles. The geophysical methods used enabled the identification of geophysical anomalies, which characterized the contamination produced by the trenches filled with lubricant oil waste. Conductive anomalies (smaller than 185 Omega m) immediately below the trenches suggest the action of bacteria in the hydrocarbons, as has been observed in several sites contaminated by hydrocarbons in previously reported cases in the literature. It was also possible to define the geometry of the trenches, as evidenced by the GPR method. Direct sampling (chemical analysis of the soil and the water in the monitoring well) confirmed the contamination. In the soil analysis, low concentrations of several polycyclic aromatic hydrocarbons (PAHs) were found, mainly naphthalene and phenanthrene. In the water samples, an analysis verified contamination of the groundwater by lead (Pb). The geophysical methods used in the investigation provided an excellent tool for environmental characterization in this study of a lubricant oil waste disposal area, and could be applied in the study of similar areas.

Molecular characterization and fumonisin production by Fusarium verticillioides isolated from corn grains of different geographic origins in Brazil

Gibberella moniliformis is most commonly associated with maize worldwide and produces high levels of fumonisins, some of the most agriculturally important mycotoxins. Studies demonstrate that molecular methods can be helpful for a rapid identification of Fusarium species and their levels of toxin production. The purpose of this research was to apply molecular methods (AFLP, TEF-1 alpha partial gene sequencing and PCR based on MAT alleles) for the identification of Fusarium species isolated from Brazilian corn and to verify if real time RT-PCR technique based on FUM1 and FUM19 genes is appropriated to estimate fumonisins B(1) and B(2) production levels. Among the isolated strains, 96 were identified as Fusarium verricillioides, and four as other Fusarium species. Concordant phylogenies were obtained by AFLP and TEF-1 alpha sequencing, permitting the classification of the different species into distinct clades. Concerning MAT alleles, 70% of the F. verricillioides isolates carried the MAT-1 and 30% MAT-2. A significant correlation was observed between the expression of the genes and toxin production r=0.95 and r=0.79 (correlation of FUM1 with FB(1) and FB(2), respectively, P < 0.0001): r=0.93 and r =0.78 (correlation of FUM19 with FB(1) and FB(2). respectively, P < 0.0001). Molecular methods used in this study were found to be useful for the rapid identification of Fusarium species. The high and significant correlation between FUM1 and FUM19 expression and fumonisins production suggests that real time RT-PCR is suitable for studies considering the influence of abiotic and biotic factors on expression of these genes. This is the first report concerning the expression of fumonisin biosynthetic genes in Fusarium strains isolated from Brazilian agricultural commodity. (c) 2010 Elsevier B.V. All rights reserved.

Cathepsin L-like genes of Trypanosoma vivax from Africa and South America - characterization, relationships and diagnostic implications

We characterized sequences from genes encoding cathepsin L-like (CatL-like) cysteine proteases from African and South American isolates of Trypanosoma vivax and T. vivax-like organisms, and evaluated their suitability as genetic markers for population structure analysis and diagnosis. Phylogenetic analysis of sequences corresponding to CatL-like catalytic domains revealed substantial polymorphism, and clades of sequences (TviCatL1-9) were separated by large genetic distances. TviCatL1-4 sequences were from cattle isolates from West Africa (Nigeria and Burkina Faso) and South America (Brazil and Venezuela), which belonged to the same T. vivax genotype. T. vivax-like genotypes from East Africa showed divergent sequences, including TviCatL5-7 for isolates from Mozambique and TviCatL8-9 for an isolate from Kenya. Phylogenetic analysis of CatL-like gene data supported the relationships among trypanosome species reflected in the phylogenies based on the analysis of small subunit (SSU) of ribosomal RNA gene sequence data. The discovery of different CatL-like sequences for each genotype, defined previously by ribosomal DNA data, indicate that these sequences provide useful targets for epidemiological and population genetic studies. Regions in CatL-like sequences shared by all T. vivax genotypes but not by other trypanosomes allowed the establishment of a specific and sensitive diagnostic PCR for epidemiological studies in South America and Africa. (C) 2008 Elsevier Ltd. All rights reserved.

Diruthenium(II, III) complexes of ibuprofen, aspirin, naproxen and indomethacin non-steroidal anti-inflammatory drugs: Synthesis, characterization and their effects on tumor-cell proliferation

[Ru-2(dNSAID)(4)Cl] and novel [Ru-2(dNSAID)(4)(H2O)(2)]PF6 complexes, where dNSAID = deprotonated carboxylate from the non-steroidal anti-inflammatory drugs (NSIDs), respectively: ibuprofen, Hibp (1) and aspirin, Hasp (2); naproxen, Hnpx (3) and indomethacin, Hind (4), have been prepared and characterized by optical spectroscopic methods. All of the compounds exhibit mixed valent Ru-2(II, III) cores where metal-metal bonds are stabilized by four drug-carboxylate bridging ligands in paddlewheel type structures. The diruthenium complexes and their parent NSAIDs showed no significant effects for Hep2 human larynx or T24/83 human bladder tumor. In contrast, the coordination of Ru-2(II,III) core led to synergistic effects that increased significantly the inhibition of C6 rat glioma proliferation in relation to the organic NSAIDs naproxen and ibuprofen, The possibility that the complexes Ru-2-ibp and Ru-2-npx may exert effects (anti-angiogenic and anti-matrix metalloprotease) that are similar to those exhibited by NAMI-A opens new horizons for in vivo C6 glioma model studies. (C) 2007 Elsevier Ltd. All rights reserved.

Topological triangle characterization with application to object detection from images

A novel mathematical framework inspired on Morse Theory for topological triangle characterization in 2D meshes is introduced that is useful for applications involving the creation of mesh models of objects whose geometry is not known a priori. The framework guarantees a precise control of topological changes introduced as a result of triangle insertion/removal operations and enables the definition of intuitive high-level operators for managing the mesh while keeping its topological integrity. An application is described in the implementation of an innovative approach for the detection of 2D objects from images that integrates the topological control enabled by geometric modeling with traditional image processing techniques. (C) 2008 Published by Elsevier B.V.

Advanced functionality for radio analysis in the Offline software framework of the Pierre Auger Observatory

The advent of the Auger Engineering Radio Array (AERA) necessitates the development of a powerful framework for the analysis of radio measurements of cosmic ray air showers. As AERA performs ""radio-hybrid"" measurements of air shower radio emission in coincidence with the surface particle detectors and fluorescence telescopes of the Pierre Auger Observatory, the radio analysis functionality had to be incorporated in the existing hybrid analysis solutions for fluorescence and surface detector data. This goal has been achieved in a natural way by extending the existing Auger Offline software framework with radio functionality. In this article, we lay out the design, highlights and features of the radio extension implemented in the Auger Offline framework. Its functionality has achieved a high degree of sophistication and offers advanced features such as vectorial reconstruction of the electric field, advanced signal processing algorithms, a transparent and efficient handling of FFTs, a very detailed simulation of detector effects, and the read-in of multiple data formats including data from various radio simulation codes. The source code of this radio functionality can be made available to interested parties on request. (C) 2011 Elsevier B.V. All rights reserved.