The use of earth observation techniques to improve catchment-scale pollution predictions

Remote sensing can potentially provide information useful in improving pollution transport modelling in agricultural catchments. Realisation of this potential will depend on the availability of the raw data, development of information extraction techniques, and the impact of the assimilation of the derived information into models. High spatial resolution hyperspectral imagery of a farm near Hereford, UK is analysed. A technique is described to automatically identify the soil and vegetation endmembers within a field, enabling vegetation fractional cover estimation. The aerially-acquired laser altimetry is used to produce digital elevation models of the site. At the subfield scale the hypothesis that higher resolution topography will make a substantial difference to contaminant transport is tested using the AGricultural Non-Point Source (AGNPS) model. Slope aspect and direction information are extracted from the topography at different resolutions to study the effects on soil erosion, deposition, runoff and nutrient losses. Field-scale models are often used to model drainage water, nitrate and runoff/sediment loss, but the demanding input data requirements make scaling up to catchment level difficult. By determining the input range of spatial variables gathered from EO data, and comparing the response of models to the range of variation measured, the critical model inputs can be identified. Response surfaces to variation in these inputs constrain uncertainty in model predictions and are presented. Although optical earth observation analysis can provide fractional vegetation cover, cloud cover and semi-random weather patterns can hinder data acquisition in Northern Europe. A Spring and Autumn cloud cover analysis is carried out over seven UK sites close to agricultural districts, using historic satellite image metadata, climate modelling and historic ground weather observations. Results are assessed in terms of probability of acquisition probability and implications for future earth observation missions. (C) 2003 Elsevier Ltd. All rights reserved.

Effectiveness of high-throughput miniaturized sorbent- and solid phase microextraction techniques combined with gas chromatography–mass spectrometry analysis for a rapid screening of volatile and semi-volatile composition of wines: a comparative study

In this study the feasibility of different extraction procedures was evaluated in order to test their potential for the extraction of the volatile (VOCs) and semi-volatile constituents (SVOCs) from wines. In this sense, and before they could be analysed by gas chromatography–quadrupole first stage masss spectrometry (GC–qMS), three different high-throughput miniaturized (ad)sorptive extraction techniques, based on solid phase extraction (SPE), microextraction by packed sorbents (MEPS) and solid phase microextraction (SPME), were studied for the first time together, for the extraction step. To achieve the most complete volatile and semi-volatile signature, distinct SPE (LiChrolut EN, Poropak Q, Styrene-Divinylbenzene and Amberlite XAD-2) and MEPS (C2, C8, C18, Silica and M1 (mixed C8-SCX)) sorbent materials, and different SPME fibre coatings (PA, PDMS, PEG, DVB/CAR/PDMS, PDMS/DVB, and CAR/PDMS), were tested and compared. All the extraction techniques were followed by GC–qMS analysis, which allowed the identification of up to 103 VOCs and SVOCs, distributed by distinct chemical families: higher alcohols, esters, fatty acids, carbonyl compounds and furan compounds. Mass spectra, standard compounds and retention index were used for identification purposes. SPE technique, using LiChrolut EN as sorbent (SPELiChrolut EN), was the most efficient method allowing for the identification of 78 VOCs and SVOCs, 63 and 19 more than MEPS and SPME techniques, respectively. In MEPS technique the best results in terms of number of extractable/identified compounds and total peak areas of volatile and semi-volatile fraction, were obtained by using C8 resin whereas DVB/CAR/PDMS was revealed the most efficient SPME coating to extract VOCs and SVOCs from Bual wine. Diethyl malate (18.8 ± 3.2%) was the main component found in wine SPELiChrolut EN extracts followed by ethyl succinate (13.5 ± 5.3%), 3-methyl-1-butanol (13.2 ± 1.7%), and 2-phenylethanol (11.2 ± 9.9%), while in SPMEDVB/CAR/PDMS technique 3-methyl-1-butanol (43.3 ± 0.6%) followed by diethyl succinate (18.9 ± 1.6%), and 2-furfural (10.4 ± 0.4%), are the major compounds. The major VOCs and SVOCs isolated by MEPSC8 were 3-methyl-1-butanol (26.8 ± 0.6%, from wine total volatile fraction), diethyl succinate (24.9 ± 0.8%), and diethyl malate (16.3 ± 0.9%). Regardless of the extraction technique, the highest extraction efficiency corresponds to esters and higher alcohols and the lowest to fatty acids. Despite some drawbacks associated with the SPE procedure such as the use of organic solvents, the time-consuming and tedious sampling procedure, it was observed that SPELiChrolut EN, revealed to be the most effective technique allowing the extraction of a higher number of compounds (78) rather than the other extraction techniques studied.

Assessment of the quality of dna extracted by two techniques from Mycobacterium tuberculosis for fast molecular identification and genotyping

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Optimisation of conditions for the extraction of casearins from Casearia sylvestris using response surface methodology

Optimal conditions for the extraction of casearins from Casearia sylvestris were determined using response surface methodology. The maceration and sonication extraction techniques were performed using a 3 x 3 x 3 full factorial design including three acidity conditions, three solvents of different polarities and three extraction times. The yields and selectivities of the extraction of casearins were significantly influenced by acidity conditions. Taking into account all variables tested, the optimal conditions for maceration extraction were estimated to involve treatment with dichloromethane saturated with ammonium hydroxide for 26 h. Similar yields and selectivities for casearins were determined for sonication extraction using the same solvent but for the much shorter time of I h. The best results for stabilisation of the fresh plant material were obtained using leaves that had been oven dried at 40 degrees C for 48 h. Copyright (c) 2006 John Wiley & Sons, Ltd.

Automatic microstructural characterization and classification using artificial intelligence techniques on ultrasound signals

Secondary phases such as Laves and carbides are formed during the final solidification stages of nickel based superalloy coatings deposited during the gas tungsten arc welding cold wire process. However, when aged at high temperatures, other phases can precipitate in the microstructure, like the γ″ and δ phases. This work presents a new application and evaluation of artificial intelligent techniques to classify (the background echo and backscattered) ultrasound signals in order to characterize the microstructure of a Ni-based alloy thermally aged at 650 and 950 °C for 10, 100 and 200 h. The background echo and backscattered ultrasound signals were acquired using transducers with frequencies of 4 and 5 MHz. Thus with the use of features extraction techniques, i.e.; detrended fluctuation analysis and the Hurst method, the accuracy and speed in the classification of the secondary phases from ultrasound signals could be studied. The classifiers under study were the recent optimum-path forest (OPF) and the more traditional support vector machines and Bayesian. The experimental results revealed that the OPF classifier was the fastest and most reliable. In addition, the OPF classifier revealed to be a valid and adequate tool for microstructure characterization through ultrasound signals classification due to its speed, sensitivity, accuracy and reliability. © 2013 Elsevier B.V. All rights reserved.

Matrix Porewater In Crystalline Rocks: Extraction and Analysis

The chemical and isotopic characterization of porewater residing in the inter- and intragranular pore space of the low-permeability rock matrix is an important component with respect to the site characterization and safety assessment of potential host rocks for a radioactive waste disposal. The chemical and isotopic composition of porewater in such low permeability rocks has to be derived by indirect extraction techniques applied to naturally saturated rock material. In most of such indirect extraction techniques – especially in case of rocks of a porosity below about 2 vol.% – the original porewater concentrations are diluted and need to be back-calculated to in-situ concentrations. This requires a well-defined value for the connected porosity – accessible to different solutes under in-situ conditions. The derivation of such porosity values, as well as solute concentrations, is subject to various perturbations during drilling, core sampling, storage and experiments in the laboratory. The present study aims to demonstrate the feasibility of a variety of these techniques to charac-terize porewater and solute transport in crystalline rocks. The methods, which have been de-veloped during multiple porewater studies in crystalline environments, were applied on four core samples from the deep borehole DH-GAP04, drilled in the Kangerlussuaq area, Southwest Greenland, as part of the joint NWMO–Posiva–SKB Greenland Analogue Project (GAP). Potential artefacts that can influence the estimation of in situ porewater chemistry and isotopes, as well as their controls, are described in detail in this report, using specific examples from borehole DH-GAP04

Analysis of pattern recognition and dimensionality reduction techniques for odor biometrics

In this paper, we analyze the performance of several well-known pattern recognition and dimensionality reduction techniques when applied to mass-spectrometry data for odor biometric identification. Motivated by the successful results of previous works capturing the odor from other parts of the body, this work attempts to evaluate the feasibility of identifying people by the odor emanated from the hands. By formulating this task according to a machine learning scheme, the problem is identified with a small-sample-size supervised classification problem in which the input data is formed by mass spectrograms from the hand odor of 13 subjects captured in different sessions. The high dimensionality of the data makes it necessary to apply feature selection and extraction techniques together with a simple classifier in order to improve the generalization capabilities of the model. Our experimental results achieve recognition rates over 85% which reveals that there exists discriminatory information in the hand odor and points at body odor as a promising biometric identifier.

A comprehensive solution to procedural knowledge acquisition using information extraction

Procedural knowledge is the knowledge required to perform certain tasks. It forms an important part of expertise, and is crucial for learning new tasks. This paper summarises existing work on procedural knowledge acquisition, and identifies two major challenges that remain to be solved in this field; namely, automating the acquisition process to tackle bottleneck in the formalization of procedural knowledge, and enabling machine understanding and manipulation of procedural knowledge. It is believed that recent advances in information extraction techniques can be applied compose a comprehensive solution to address these challenges. We identify specific tasks required to achieve the goal, and present detailed analyses of new research challenges and opportunities. It is expected that these analyses will interest researchers of various knowledge management tasks, particularly knowledge acquisition and capture.

Microplastics in sediments: A review of techniques, occurrence and effects

Microplastics are omnipresent in the marine environment and sediments are hypothesized to be major sinks of these plastics. Here, over 100 articles spanning the last 50 year are reviewed with following objectives: (i) to evaluate current microplastic extraction techniques, (ii) to discuss the occurrence and worldwide distribution of microplastics in sediments, and (iii) to make a comprehensive assessment of the possible adverse effects of this type of pollution to marine organisms. Based on this review we propose future research needs and conclude that there is a clear need for a standardized techniques, unified reporting units and more realistic effect assessments.

Optimization of ultrasound-assisted extraction to obtain mycosterols from Agaricus bisporus L. by response surface methodology and comparison with conventional Soxhlet extraction

Ergosterol, a molecule with high commercial value, is the most abundant mycosterol in Agaricus bisporus L. To replace common conventional extraction techniques (e.g. Soxhlet), the present study reports the optimal ultrasound-assisted extraction conditions for ergosterol. After preliminary tests, the results showed that solvents, time and ultrasound power altered the extraction efficiency. Using response surface methodology, models were developed to investigate the favourable experimental conditions that maximize the extraction efficiency. All statistical criteria demonstrated the validity of the proposed models. Overall, ultrasound-assisted extraction with ethanol at 375 W during 15 min proved to be as efficient as the Soxhlet extraction, yielding 671.5 ± 0.5mg ergosterol/100 g dw. However, with n-hexane extracts with higher purity (mg ergosterol/g extract) were obtained. Finally, it was proposed for the removal of the saponification step, which simplifies the extraction process and makes it more feasible for its industrial transference.

Técnicas de extrações e procedimentos de clean-up para a determinação de hidrocarbonetos policílicos aromáticos (HPA) em sedimentos da costa do Ceará

Extraction and clean-up are essential points in polycyclic aromatic hydrocarbon (PAHs) analysis in a solid matrix. This work compares extraction techniques and clean-up procedures for PAH analysis. PAH levels, their toxicological significance and source were also evaluated in the waters of the Cocó and Ceará rivers. The efficiency of PAH recovery was higher for the soxhlet and ultrasonic techniques. PAH recovery varied from 69.3 to 99.3%. Total PAH concentration (ΣHPA) varied from 720.73 to 2234.76 µg kg-1 (Cocó river) and 96.4 to 1859.21 µg kg-1 (Ceará river). The main PAH sources are pyrolytic processes and the levels were classified as medium so that adverse effects are possible.

Time-frequency and time-scale analysis of Barkhausen noise signals

Carrying out information about the microstructure and stress behaviour of ferromagnetic steels, magnetic Barkhausen noise (MBN) has been used as a basis for effective non-destructive testing methods, opening new areas in industrial applications. One of the factors that determines the quality and reliability of the MBN analysis is the way information is extracted from the signal. Commonly, simple scalar parameters are used to characterize the information content, such as amplitude maxima and signal root mean square. This paper presents a new approach based on the time-frequency analysis. The experimental test case relates the use of MBN signals to characterize hardness gradients in a AISI4140 steel. To that purpose different time-frequency (TFR) and time-scale (TSR) representations such as the spectrogram, the Wigner-Ville distribution, the Capongram, the ARgram obtained from an AutoRegressive model, the scalogram, and the Mellingram obtained from a Mellin transform are assessed. It is shown that, due to nonstationary characteristics of the MBN, TFRs can provide a rich and new panorama of these signals. Extraction techniques of some time-frequency parameters are used to allow a diagnostic process. Comparison with results obtained by the classical method highlights the improvement on the diagnosis provided by the method proposed.

Reconhecimento de língua gestual

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Informática e Computadores

Phenolic compounds from olive mill wastes: Health effects, analytical approach and application as food antioxidants

Background Over the years, food industry wastes have been the focus of a growing interest due to their content in high added-value compounds. A good example are the olive oil by-products (OOBP), which retain a great amount of phenolic compounds during olive oil production. Their structure and biological properties justify their potential use as antioxidants in other food products. The efficient recovery of phenolic compounds has been extensively studied and optimized in order to maximize their reintroduction in the food chain and contribute to a higher valorization and better management of wastes from olive oil industry. Scope and approach This paper reviews the most representative phenolic compounds described in OOBP and their biological properties. New extraction procedures to efficiently recover these compounds and the most advanced chromatographic techniques that have been used for a better understanding of the phenolic profile of these complex matrices are also referred. Finally, this paper reports the main applications of OOBP, with emphasis on their phenolic content as natural antioxidants for food applications. Key findings and conclusions Besides their antioxidant activity, phenolic compounds from OOBP have also shown antimicrobial and antitumoral properties. Their application as food antioxidants requires new extraction techniques, including the use of non-toxic solvents and, in a pilot scale, the use of filters and adsorbent resins. The inclusion of phenolic compounds from OOBP in some food matrices have improved not only their antioxidant capacity but also their sensory attributes.

Polymerase chain reaction and nested-PCR approaches for detecting Cryptosporidium in water catchments of water treatment plants in Curitiba, State of Paraná, Brazil

Introduction Cryptosporidium is an important protozoan cause of waterborne disease worldwide of concern to public health authorities. To prevent outbreaks of cryptosporidiosis, the monitoring of this parasite in drinking water is necessary. In the present work, the polymerase chain reaction (PCR) and nested-PCR techniques were used to detect Cryptosporidium in raw water from catchment points of four water treatment plants (WTP) in Curitiba, Paraná, Brazil. Methods First, DNA extraction techniques were tested in samples containing decreasing amount of oocysts in reagent water, and PCR and nested-PCR with specific primers for 18SSU rDNA of Cryptosporidium were conducted to determine their sensitivity. In reagent water, a commercial extraction kit provided the best analytical sensitivity, and PCR and nested-PCR allowed the detection of five and two oocysts, respectively, with the primers XIAOR/XIAOF and XIAO1F/XIAO2R. Results In the spiking experiments, only the PCR with the primers AWA995F/AWA1206R was successful at detecting concentrations of 0.1 oocysts/mL. Two catchments samples of raw water and/or water sludge from four WTPs were contaminated with Cryptosporidium. Conclusions The application of the techniques to monitor Cryptosporidium in water and detect contamination in water catchments of WTPs in Curitiba are discussed in the present work.