An automated microreactor for semi-continuous biosensor measurements.

Living bacteria or yeast cells are frequently used as bioreporters for the detection of specific chemical analytes or conditions of sample toxicity. In particular, bacteria or yeast equipped with synthetic gene circuitry that allows the production of a reliable non-cognate signal (e.g., fluorescent protein or bioluminescence) in response to a defined target make robust and flexible analytical platforms. We report here how bacterial cells expressing a fluorescence reporter ("bactosensors"), which are mostly used for batch sample analysis, can be deployed for automated semi-continuous target analysis in a single concise biochip. Escherichia coli-based bactosensor cells were continuously grown in a 13 or 50 nanoliter-volume reactor on a two-layered polydimethylsiloxane-on-glass microfluidic chip. Physiologically active cells were directed from the nl-reactor to a dedicated sample exposure area, where they were concentrated and reacted in 40 minutes with the target chemical by localized emission of the fluorescent reporter signal. We demonstrate the functioning of the bactosensor-chip by the automated detection of 50 μgarsenite-As l(-1) in water on consecutive days and after a one-week constant operation. Best induction of the bactosensors of 6-9-fold to 50 μg l(-1) was found at an apparent dilution rate of 0.12 h(-1) in the 50 nl microreactor. The bactosensor chip principle could be widely applicable to construct automated monitoring devices for a variety of targets in different environments.

Determination of etoricoxib in human plasma using automated on-line solid-phase extraction coupled with LC-APCI/MS/MS

A liquid chromatography-tandem mass spectrometry method with atmospheric pressure chemical ionization (LC-APCI/MS/MS) was validated for the determination of etoricoxib in human plasma using antipyrin as internal standard, followed by on-line solid-phase extraction. The method was performed on a Luna C18 column and the mobile phase consisted of acetonitrile:water (95:5, v/v)/ammonium acetate (pH 4.0; 10 mM), run at a flow rate of 0.6 mL/min. The method was linear in the range of 1-5000 ng/mL (r²>0.99). The lower limit of quantitation was 1 ng/mL. The recoveries were within 93.72-96.18%. Moreover, method validation demonstrated acceptable results for the precision, accuracy and stability studies.

Ligandless cloud point extraction of trace amounts of palladium and rhodium in road dust samples using Span 80 prior to their determination by flame atomic absorption spectrometry

In this study, a procedure is developed for cloud point extraction of Pd(II) and Rh(III) ions in aqueous solution using Span 80 (non-ionic surfactant) prior to their determination by flame atomic absorption spectroscopy. This method is based on the extraction of Pd(II) and Rh(III) ions at a pH of 10 using Span 80 with no chelating agent. We investigated the effect of various parameters on the recovery of the analyte ions, including pH, equilibration temperature and time, concentration of Span 80, and ionic strength. Under the best experimental conditions, the limits of detection based on 3Sb for Pd(II) and Rh(III) ions were 1.3 and 1.2 ng mL-1, respectively. Seven replicate determinations of a mixture of 0.5 µg mL-1 palladium and rhodium ions gave a mean absorbance of 0.058 and 0.053 with relative standard deviations of 1.8 and 1.6%, respectively. The developed method was successfully applied to the extraction and determination of the palladium and rhodium ions in road dust and standard samples and satisfactory results were obtained.

Extraction of tidal channel networks from aerial photographs alone and combined with laser altimetry

Tidal channel networks play an important role in the intertidal zone, exerting substantial control over the hydrodynamics and sediment transport of the region and hence over the evolution of the salt marshes and tidal flats. The study of the morphodynamics of tidal channels is currently an active area of research, and a number of theories have been proposed which require for their validation measurement of channels over extensive areas. Remotely sensed data provide a suitable means for such channel mapping. The paper describes a technique that may be adapted to extract tidal channels from either aerial photographs or LiDAR data separately, or from both types of data used together in a fusion approach. Application of the technique to channel extraction from LiDAR data has been described previously. However, aerial photographs of intertidal zones are much more commonly available than LiDAR data, and most LiDAR flights now involve acquisition of multispectral images to complement the LiDAR data. In view of this, the paper investigates the use of multispectral data for semiautomatic identification of tidal channels, firstly from only aerial photographs or linescanner data, and secondly from fused linescanner and LiDAR data sets. A multi-level, knowledge-based approach is employed. The algorithm based on aerial photography can achieve a useful channel extraction, though may fail to detect some of the smaller channels, partly because the spectral response of parts of the non-channel areas may be similar to that of the channels. The algorithm for channel extraction from fused LiDAR and spectral data gives an increased accuracy, though only slightly higher than that obtained using LiDAR data alone. The results illustrate the difficulty of developing a fully automated method, and justify the semi-automatic approach adopted.

Semi-automatic segmentation of fetal cardiac cavities: progress towards an automated fetal echocardiogram

OBJECTIVE: To develop a novel application of a tool for semi-automatic volume segmentation and adapt it for analysis of fetal cardiac cavities and vessels from heart volume datasets. METHODS: We studied retrospectively virtual cardiac volume cycles obtained with spatiotemporal image correlation (STIC) from six fetuses with postnatally confirmed diagnoses: four with normal hearts between 19 and 29 completed gestational weeks, one with d-transposition of the great arteries and one with hypoplastic left heart syndrome. The volumes were analyzed offline using a commercially available segmentation algorithm designed for ovarian folliculometry. Using this software, individual 'cavities' in a static volume are selected and assigned individual colors in cross-sections and in 3D-rendered views, and their dimensions (diameters and volumes) can be calculated. RESULTS: Individual segments of fetal cardiac cavities could be separated, adjacent segments merged and the resulting electronic casts studied in their spatial context. Volume measurements could also be performed. Exemplary images and interactive videoclips showing the segmented digital casts were generated. CONCLUSION: The approach presented here is an important step towards an automated fetal volume echocardiogram. It has the potential both to help in obtaining a correct structural diagnosis, and to generate exemplary visual displays of cardiac anatomy in normal and structurally abnormal cases for consultation and teaching.

Lake ice phenology from AVHRR data for European lakes: An automated two-step extraction method

Several lake ice phenology studies from satellite data have been undertaken. However, the availability of long-term lake freeze-thaw-cycles, required to understand this proxy for climate variability and change, is scarce for European lakes. Long time series from space observations are limited to few satellite sensors. Data of the Advanced Very High Resolution Radiometer (AVHRR) are used in account of their unique potential as they offer each day global coverage from the early 1980s expectedly until 2022. An automatic two-step extraction was developed, which makes use of near-infrared reflectance values and thermal infrared derived lake surface water temperatures to extract lake ice phenology dates. In contrast to other studies utilizing thermal infrared, the thresholds are derived from the data itself, making it unnecessary to define arbitrary or lake specific thresholds. Two lakes in the Baltic region and a steppe lake on the Austrian–Hungarian border were selected. The later one was used to test the applicability of the approach to another climatic region for the time period 1990 to 2012. A comparison of the extracted event dates with in situ data provided good agreements of about 10 d mean absolute error. The two-step extraction was found to be applicable for European lakes in different climate regions and could fill existing data gaps in future applications. The extension of the time series to the full AVHRR record length (early 1980 until today) with adequate length for trend estimations would be of interest to assess climate variability and change. Furthermore, the two-step extraction itself is not sensor-specific and could be applied to other sensors with equivalent near- and thermal infrared spectral bands.

Real-time 3D semi-local surface patch extraction using GPGPU

Feature vectors can be anything from simple surface normals to more complex feature descriptors. Feature extraction is important to solve various computer vision problems: e.g. registration, object recognition and scene understanding. Most of these techniques cannot be computed online due to their complexity and the context where they are applied. Therefore, computing these features in real-time for many points in the scene is impossible. In this work, a hardware-based implementation of 3D feature extraction and 3D object recognition is proposed to accelerate these methods and therefore the entire pipeline of RGBD based computer vision systems where such features are typically used. The use of a GPU as a general purpose processor can achieve considerable speed-ups compared with a CPU implementation. In this work, advantageous results are obtained using the GPU to accelerate the computation of a 3D descriptor based on the calculation of 3D semi-local surface patches of partial views. This allows descriptor computation at several points of a scene in real-time. Benefits of the accelerated descriptor have been demonstrated in object recognition tasks. Source code will be made publicly available as contribution to the Open Source Point Cloud Library.

Towards rope shovel automation operation information system

The road to electric rope shovel automation is marked with technological innovations that include an increase in operational information available to mining operations. The CRCMining Shovel Operator Information System not only collects machine operational data but also provides the operator with knowledge-of-performance and influences his/her performance to achieve higher productivity with reduced machine duty. The operator’s behaviour is one of the most important aspects of the man-machine interaction to be considered before semi- or fully-automated shovel systems can be realised. This paper presents the results of the rope shovel studies conducted by CRCMining between 2002 and 2004, provides information on current research to improve shovel performance and briefly discusses the implications of human-system interactions on future designs of autonomous machines.

Advancing Bag-of-visual-words Representations For Lesion Classification In Retinal Images.

Diabetic Retinopathy (DR) is a complication of diabetes that can lead to blindness if not readily discovered. Automated screening algorithms have the potential to improve identification of patients who need further medical attention. However, the identification of lesions must be accurate to be useful for clinical application. The bag-of-visual-words (BoVW) algorithm employs a maximum-margin classifier in a flexible framework that is able to detect the most common DR-related lesions such as microaneurysms, cotton-wool spots and hard exudates. BoVW allows to bypass the need for pre- and post-processing of the retinographic images, as well as the need of specific ad hoc techniques for identification of each type of lesion. An extensive evaluation of the BoVW model, using three large retinograph datasets (DR1, DR2 and Messidor) with different resolution and collected by different healthcare personnel, was performed. The results demonstrate that the BoVW classification approach can identify different lesions within an image without having to utilize different algorithms for each lesion reducing processing time and providing a more flexible diagnostic system. Our BoVW scheme is based on sparse low-level feature detection with a Speeded-Up Robust Features (SURF) local descriptor, and mid-level features based on semi-soft coding with max pooling. The best BoVW representation for retinal image classification was an area under the receiver operating characteristic curve (AUC-ROC) of 97.8% (exudates) and 93.5% (red lesions), applying a cross-dataset validation protocol. To assess the accuracy for detecting cases that require referral within one year, the sparse extraction technique associated with semi-soft coding and max pooling obtained an AUC of 94.2 ± 2.0%, outperforming current methods. Those results indicate that, for retinal image classification tasks in clinical practice, BoVW is equal and, in some instances, surpasses results obtained using dense detection (widely believed to be the best choice in many vision problems) for the low-level descriptors.

Rapid detection of bovine coronavirus by a semi-nested RT-PCR

Bovine coronavirus (BCoV) is a member of the group 2 of the Coronavirus (Nidovirales: Coronaviridae) and the causative agent of enteritis in both calves and adult bovine, as well as respiratory disease in calves. The present study aimed to develop a semi-nested RT-PCR for the detection of BCoV based on representative up-to-date sequences of the nucleocapsid gene, a conserved region of coronavirus genome. Three primers were designed, the first round with a 463bp and the second (semi-nested) with a 306bp predicted fragment. The analytical sensitivity was determined by 10-fold serial dilutions of the BCoV Kakegawa strain (HA titre: 256) in DEPC treated ultra-pure water, in fetal bovine serum (FBS) and in a BCoV-free fecal suspension, when positive results were found up to the 10-2, 10-3 and 10-7 dilutions, respectively, which suggests that the total amount of RNA in the sample influence the precipitation of pellets by the method of extraction used. When fecal samples was used, a large quantity of total RNA serves as carrier of BCoV RNA, demonstrating a high analytical sensitivity and lack of possible substances inhibiting the PCR. The final semi-nested RT-PCR protocol was applied to 25 fecal samples from adult cows, previously tested by a nested RT-PCR RdRp used as a reference test, resulting in 20 and 17 positives for the first and second tests, respectively, and a substantial agreement was found by kappa statistics (0.694). The high sensitivity and specificity of the new proposed method and the fact that primers were designed based on current BCoV sequences give basis to a more accurate diagnosis of BCoV-caused diseases, as well as to further insights on protocols for the detection of other Coronavirus representatives of both Animal and Public Health importance.

Tree-ring formation, radial increment periodicity, and phenology of tree species from a seasonal semi-deciduous forest in southeast Brazil

Many tropical tree species produce growth rings in response to seasonal environmental factors that influence the activity of the vascular cambium. We applied the following methods to analyze the annual nature of treering formation of 24 tree species from a seasonal semi-deciduous forest of southeast Brazil: describing wood anatomy and phenology, counting tree rings after cambium markings, and using permanent dendrometer bands. After 7 years of systematic observations and measurements, we found the following: the trees lost their leaves during the dry season and grew new leaves at the end of the same season; trunk increment dynamics corresponded to seasonal changes in precipitation, with higher increment (active period) during the rainy season (October-April) and lower increment (dormant period) during the dry season (May-September); the number of tree rings formed after injuries to the cambium coincided with the number of years since the extraction of the wood samples. As a result of these observations, it was concluded that most study trees formed one growth ring per year. This suggests that tree species from the seasonal semi-deciduous forests of Brazil have an annual cycle of wood formation. Therefore, these trees have potential for use in future studies of tree age and radial growth rates, as well as to infer ecological and regional climatic conditions. These future studies can provide important information for the management and conservation of these endangered forests.

Improving wheat simulation capabilities in Australia from a cropping systems perspective: water and nitrogen effects on spring wheat in a semi-arid environment

Systems approaches can help to evaluate and improve the agronomic and economic viability of nitrogen application in the frequently water-limited environments. This requires a sound understanding of crop physiological processes and well tested simulation models. Thus, this experiment on spring wheat aimed to better quantify water x nitrogen effects on wheat by deriving some key crop physiological parameters that have proven useful in simulating crop growth. For spring wheat grown in Northern Australia under four levels of nitrogen (0 to 360 kg N ha(-1)) and either entirely on stored soil moisture or under full irrigation, kernel yields ranged from 343 to 719 g m(-2). Yield increases were strongly associated with increases in kernel number (9150-19950 kernels m(-2)), indicating the sensitivity of this parameter to water and N availability. Total water extraction under a rain shelter was 240 mm with a maximum extraction depth of 1.5 m. A substantial amount of mineral nitrogen available deep in the profile (below 0.9 m) was taken up by the crop. This was the source of nitrogen uptake observed after anthesis. Under dry conditions this late uptake accounted for approximately 50% of total nitrogen uptake and resulted in high (>2%) kernel nitrogen percentages even when no nitrogen was applied,Anthesis LAI values under sub-optimal water supply were reduced by 63% and under sub-optimal nitrogen supply by 50%. Radiation use efficiency (RUE) based on total incident short-wave radiation was 1.34 g MJ(-1) and did not differ among treatments. The conservative nature of RUE was the result of the crop reducing leaf area rather than leaf nitrogen content (which would have affected photosynthetic activity) under these moderate levels of nitrogen limitation. The transpiration efficiency coefficient was also conservative and averaged 4.7 Pa in the dry treatments. Kernel nitrogen percentage varied from 2.08 to 2.42%. The study provides a data set and a basis to consider ways to improve simulation capabilities of water and nitrogen effects on spring wheat. (C) 1997 Elsevier Science B.V.

Data mining framework for fatty liver disease classification in ultrasound: a hybrid feature extraction paradigm

PURPOSE: Fatty liver disease (FLD) is an increasing prevalent disease that can be reversed if detected early. Ultrasound is the safest and ubiquitous method for identifying FLD. Since expert sonographers are required to accurately interpret the liver ultrasound images, lack of the same will result in interobserver variability. For more objective interpretation, high accuracy, and quick second opinions, computer aided diagnostic (CAD) techniques may be exploited. The purpose of this work is to develop one such CAD technique for accurate classification of normal livers and abnormal livers affected by FLD. METHODS: In this paper, the authors present a CAD technique (called Symtosis) that uses a novel combination of significant features based on the texture, wavelet transform, and higher order spectra of the liver ultrasound images in various supervised learning-based classifiers in order to determine parameters that classify normal and FLD-affected abnormal livers. RESULTS: On evaluating the proposed technique on a database of 58 abnormal and 42 normal liver ultrasound images, the authors were able to achieve a high classification accuracy of 93.3% using the decision tree classifier. CONCLUSIONS: This high accuracy added to the completely automated classification procedure makes the authors' proposed technique highly suitable for clinical deployment and usage.

Use of solvent extraction to remediate soils contaminated with hydrocarbons

The main objective of this research is to exploit the possibility of using an ex situ solvent extraction technique for the remediation of soils contaminated with semi-volatile petroleum hydrocarbons. The composition of the organic phase was chosen in order to form a single phase mixture with an aqueous phase and simultaneously not being disturbed (forming stable emulsions) by the soil particles hauling the contaminants. It should also permit a regeneration of the organic solvent phase. As first, we studied the miscibility domain of the chosen ternary systems constituted by ethyl acetate–acetone–water. This system proved to satisfy the previous requirements allowing for the formation of a single liquid phase mixture within a large spectrum of compositions, and also allowing for an intimate contact with the soil. Contaminants in the diesel range within different functional groups were selected: xylene, naphthalene and hexadecane. The analytical control was done by gas chromatography with FID detector. The kinetics of the extractions proved to be fast, leading to equilibrium after 10 min. The effect of the solid–liquid ratio on the extraction efficiency was studied. Lower S/L ratios (1:8, w/v) proved to be more efficient, reaching recoveries in the order of 95%. The option of extraction in multiple contacts did not improve the recovery in relation to a single contact. The solvent can be regenerated by distillation with a loss around 10%. The contaminants are not evaporated and they remain in the non-volatile phase. The global results show that the ex situ solvent extraction is technically a feasible option for the remediation of semi-volatile aromatic, polyaromatic and linear hydrocarbons.

Declarative approach to data extraction of web pages

Thesis submitted to Faculdade de Ciências e Tecnologia of the Universidade Nova de Lisboa, in partial fulfilment of the requirements for the degree of Master in Computer Science