Optimisation of in-cell accelerated solvent extraction technique for the determination of organochlorine pesticides in river sediments

Organochlorine pesticides (OCPs) are ubiquitous environmental contaminants with adverse impacts on aquatic biota, wildlife and human health even at low concentrations. However, conventional methods for their determination in river sediments are resource intensive. This paper presents an approach that is rapid and also reliable for the detection of OCPs. Accelerated Solvent Extraction (ASE) with in-cell silica gel clean-up followed by Triple Quadrupole Gas Chromatograph Mass Spectrometry (GCMS/MS) was used to recover OCPs from sediment samples. Variables such as temperature, solvent ratio, adsorbent mass and extraction cycle were evaluated and optimised for the extraction. With the exception of Aldrin, which was unaffected by any of the variables evaluated, the recovery of OCPs from sediment samples was largely influenced by solvent ratio and adsorbent mass and, to some extent, the number of cycles and temperature. The optimised conditions for OCPs extraction in sediment with good recoveries were determined to be 4 cycles, 4.5 g of silica gel, 105 ᴼC, and 4:3 v/v DCM: hexane mixture. With the exception of two compounds (α-BHC and Aldrin) whose recoveries were low (59.73 and 47.66 % respectively), the recovery of the other pesticides were in the range 85.35 – 117.97% with precision < 10 % RSD. The method developed significantly reduces sample preparation time, the amount of solvent used, matrix interference, and is highly sensitive and selective.

Data mining approaches to software fault diagnosis

Automatic identification of software faults has enormous practical significance. This requires characterizing program execution behavior and the use of appropriate data mining techniques on the chosen representation. In this paper, we use the sequence of system calls to characterize program execution. The data mining tasks addressed are learning to map system call streams to fault labels and automatic identification of fault causes. Spectrum kernels and SVM are used for the former while latent semantic analysis is used for the latter The techniques are demonstrated for the intrusion dataset containing system call traces. The results show that kernel techniques are as accurate as the best available results but are faster by orders of magnitude. We also show that latent semantic indexing is capable of revealing fault-specific features.

Mapping Road Infrastructure in Developing Countries Applying Remote Sensing and GIS - The Case of the Taita Hills, Kenya

Road transport and infrastructure has a fundamental meaning for the developing world. Poor quality and inadequate coverage of roads, lack of maintenance operations and outdated road maps continue to hinder economic and social development in the developing countries. This thesis focuses on studying the present state of road infrastructure and its mapping in the Taita Hills, south-east Kenya. The study is included as a part of the TAITA-project by the Department of Geography, University of Helsinki. The road infrastructure of the study area is studied by remote sensing and GIS based methodology. As the principal dataset, true colour airborne digital camera data from 2004, was used to generate an aerial image mosaic of the study area. Auxiliary data includes SPOT satellite imagery from 2003, field spectrometry data of road surfaces and relevant literature. Road infrastructure characteristics are interpreted from three test sites using pixel-based supervised classification, object-oriented supervised classifications and visual interpretation. Road infrastructure of the test sites is interpreted visually from a SPOT image. Road centrelines are then extracted from the object-oriented classification results with an automatic vectorisation process. The road infrastructure of the entire image mosaic is mapped by applying the most appropriate assessed data and techniques. The spectral characteristics and reflectance of various road surfaces are considered with the acquired field spectra and relevant literature. The results are compared with the experimented road mapping methods. This study concludes that classification and extraction of roads remains a difficult task, and that the accuracy of the results is inadequate regardless of the high spatial resolution of the image mosaic used in this thesis. Visual interpretation, out of all the experimented methods in this thesis is the most straightforward, accurate and valid technique for road mapping. Certain road surfaces have similar spectral characteristics and reflectance values with other land cover and land use. This has a great influence for digital analysis techniques in particular. Road mapping is made even more complicated by rich vegetation and tree canopy, clouds, shadows, low contrast between roads and surroundings and the width of narrow roads in relation to the spatial resolution of the imagery used. The results of this thesis may be applied to road infrastructure mapping in developing countries on a more general context, although with certain limits. In particular, unclassified rural roads require updated road mapping schemas to intensify road transport possibilities and to assist in the development of the developing world.

Thermodynamics of oxygen in liquid copper, lead and copper lead alloys

Solid oxide galvanic cells of the type Pt, Ni-NiO I Solid electrolyte ( Ometa,, Cermet. Pt were used to measure the activity coefficient of oxygen in liquid copper at 11 00 and 1 300eC, and in lead at 11 00'C. Similar cells were used to study the activity coefficient of oxygen in the whole range of Cu + Pb alloys at 1100'C and in lead-rich alloys at 900 and 750'C.The results obtained are discussed in terms of proposed solution models. An equation based on the formation of 'species' of the form M,O in solutions of oxygen in binary alloys is shown to fit the experimental data.

Gibbs free energies of formation of indium (III) oxide and sulphate

Emf measurements on the galvanic cell Pt, Ta, In + In,O, / Tho,-Y,03 / Cu + C+O, Pt were used to obtain the standard free energy of formation of 1%03fr om 600 to 900°C. Differential thermal analysis was used to detect the decomposition of In2(S0,), under controlled SO2 + O2 + Ar mixtures in thqtemperature range 640-8wC. X-ray diffraction analysis indicated that the decomposition product was 1%03 without an oxywlphate intermediate. The following equations were obtained for the variation of the standard free-energy change(Jlmole) with temperature:

An improved X-ray structural analysis for determining cation distribution in ZnFe2O4 and ZnFe2O4- Fe3O4 solid solutions

The distribution of zinc cation between crystallographically nonequivalent positions in ZnFe204 has been determined by anomalous X-ray scattering near the Zn K absorption edge. Measured intensity ratio with two energies close to the edge can be quantitatively explained only by assigning all zinc cations to the tetrahedral position in the approximately cubic close packed array of oxygen ions. A similar conclusion has also been reached for ZnxFe3-x04 solid solutions with x = 0.73, 0.54 and 0.35 employing the improved X-ray method. This is consistent with the EXAFS results which indicate an almost unchanged environmental structure around zinc cation in these solid solutions.

Thermodynamic properties of Ln-O (Ln = La, Pr, Nd) solid solutions and their deoxidation by molten salt electrolysis

The lanthanide metals lanthanum, praseodymium and neodymium containing 2,200, 2,600, 1,850 mass ppm oxygen, respectively, were deoxidized to 20-30 ppm level at 1,073 K by an electrochemical method. The metal to be deoxidized was used as the cathode in an electrolysis cell which consisted of a graphite anode and molten CaCl2 electrolyte. The calcium metal produced at the cathode by electrolysis effectively deoxidized the lanthanide metal. Calcium oxide produced by deoxidation, dissolved in the melt. The liberation of carbon monoxide/dioxide at the anode was found to prevent accumulation of oxygen in the melt. For a quantitative discussion of the limits of deoxidation achievable by this technique, a thermodynamic investigation of the lanthanide-oxygen (Ln-O ; Ln = La, Pr, Nd) solid solutions was conducted. The lanthanide metal, yttrium and titanium samples were immersed in calcium-saturated CaCl2 melt, containing a small quantity of dissolved CaO, at 1,093 K. The oxygen potential of the melt and the Ln-O solid solutions were obtained from the oxygen content of yttrium samples at equilibrium, and the known thermodynamic properties of yttrium-oxygen solid solution. The results were confirmed by using Y/Y2O3 equilibrium to control the oxygen potential of the molten salt reservoir. The oxygen affinity of the metals was found to decrease in the order : Y > Ti > Nd > Pr > La. The deoxidation results are consistent with the thermodynamic properties of the RE-O solid solutions.

Automatic extraction of free-form surface features (FFSFs)

This paper presents a new algorithm for extracting Free-Form Surface Features (FFSFs) from a surface model. The extraction algorithm is based on a modified taxonomy of FFSFs from that proposed in the literature. A new classification scheme has been proposed for FFSFs to enable their representation and extraction. The paper proposes a separating curve as a signature of FFSFs in a surface model. FFSFs are classified based on the characteristics of the separating curve (number and type) and the influence region (the region enclosed by the separating curve). A method to extract these entities is presented. The algorithm has been implemented and tested for various free-form surface features on different types of free-form surfaces (base surfaces) and is found to correctly identify and represent the features irrespective of the type of underlying surface. The representation and extraction algorithm are both based on topology and geometry. The algorithm is data-driven and does not use any pre-defined templates. The definition presented for a feature is unambiguous and application independent. The proposed classification of FFSFs can be used to develop an ontology to determine semantic equivalences for the feature to be exchanged, mapped and used across PLM applications. (C) 2011 Elsevier Ltd. All rights reserved.

An experimental set-up for carbon isotopic analysis of atmospheric CO2 and an example of ecosystem response during solar eclipse 2010

We present here, an experimental set-up developed for the first time in India for the determination of mixing ratio and carbon isotopic ratio of air-CO2. The set-up includes traps for collection and extraction of CO2 from air samples using cryogenic procedures, followed by the measurement of CO2 mixing ratio using an MKS Baratron gauge and analysis of isotopic ratios using the dual inlet peripheral of a high sensitivity isotope ratio mass spectrometer (IRMS) MAT 253. The internal reproducibility (precision) for the PC measurement is established based on repeat analyses of CO2 +/- 0.03 parts per thousand. The set-up is calibrated with international carbonate and air-CO2 standards. An in-house air-CO2 mixture, `OASIS AIRMIX' is prepared mixing CO2 from a high purity cylinder with O-2 and N-2 and an aliquot of this mixture is routinely analyzed together with the air samples. The external reproducibility for the measurement of the CO2 mixing ratio and carbon isotopic ratios are +/- 7 (n = 169) mu mol.mol(-1) and +/- 0.05 (n = 169) parts per thousand based on the mean of the difference between two aliquots of reference air mixture analyzed during daily operation carried out during November 2009-December 2011. The correction due to the isobaric interference of N2O on air-CO2 samples is determined separately by analyzing mixture of CO2 (of known isotopic composition) and N2O in varying proportions. A +0.2 parts per thousand correction in the delta C-13 value for a N2O concentration of 329 ppb is determined. As an application, we present results from an experiment conducted during solar eclipse of 2010. The isotopic ratio in CO2 and the carbon dioxide mixing ratio in the air samples collected during the event are different from neighbouring samples, suggesting the role of atmospheric inversion in trapping the emitted CO2 from the urban atmosphere during the eclipse.

Learning from positive and unlabelled examples using maximum margin clustering

Learning from Positive and Unlabelled examples (LPU) has emerged as an important problem in data mining and information retrieval applications. Existing techniques are not ideally suited for real world scenarios where the datasets are linearly inseparable, as they either build linear classifiers or the non-linear classifiers fail to achieve the desired performance. In this work, we propose to extend maximum margin clustering ideas and present an iterative procedure to design a non-linear classifier for LPU. In particular, we build a least squares support vector classifier, suitable for handling this problem due to symmetry of its loss function. Further, we present techniques for appropriately initializing the labels of unlabelled examples and for enforcing the ratio of positive to negative examples while obtaining these labels. Experiments on real-world datasets demonstrate that the non-linear classifier designed using the proposed approach gives significantly better generalization performance than the existing relevant approaches for LPU.

PIB: Profiling Influential Blogger in Online Social Networks, A Knowledge Driven Data Mining Approach

Online Social Networks (OSNs) facilitate to create and spread information easily and rapidly, influencing others to participate and propagandize. This work proposes a novel method of profiling Influential Blogger (IB) based on the activities performed on one's blog documents who influences various other bloggers in Social Blog Network (SBN). After constructing a social blogging site, a SBN is analyzed with appropriate parameters to get the Influential Blog Power (IBP) of each blogger in the network and demonstrate that profiling IB is adequate and accurate. The proposed Profiling Influential Blogger (PIB) Algorithm survival rate of IB is high and stable. (C) 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Modified Simplified Rate Equation Model of Flowing Chemical Oxygen-Iodine Laser and its Application

A modified simplified rate equation (RE) model of flowing chemical oxygen-iodine laser (COIL), which is adapted to both the condition of homogeneous broadening and inhomogeneous broadening being of importance and the condition of inhomogeneous broadening being predominant, is presented for performance analyses of a COIL. By using the Voigt profile function and the gain-equal-loss approximation, a gain expression has been deduced from the rate equations of upper and lower level laser species. This gain expression is adapted to the conditions of very low gas pressure up to quite high pressure and can deal with the condition of lasing frequency being not equal to the central one of spectral profile. The expressions of output power and extraction efficiency in a flowing COIL can be obtained by solving the coupling equations of the deduced gain expression and the energy equation which expresses the complete transformation of the energy stored in singlet delta state oxygen into laser energy. By using these expressions, the RotoCOIL experiment is simulated, and obtained results agree well with experiment data. Effects of various adjustable parameters on the performances of COIL are also presented.

Modified Simplified Rate Equation Model of Flowing Chemical Oxygen-Iodine Laser and its Application

A modified simplified rate equation (RE) model of flowing chemical oxygen-iodine laser (COIL), which is adapted to both the condition of homogeneous broadening and inhomogeneous broadening being of importance and the condition of inhomogeneous broadening being predominant, is presented for performance analyses of a COIL. By using the Voigt profile function and the gain-equal-loss approximation, a gain expression has been deduced from the rate equations of upper and lower level laser species. This gain expression is adapted to the conditions of very low gas pressure up to quite high pressure and can deal with the condition of lasing frequency being not equal to the central one of spectral profile. The expressions of output power and extraction efficiency in a flowing COIL can be obtained by solving the coupling equations of the deduced gain expression and the energy equation which expresses the complete transformation of the energy stored in singlet delta state oxygen into laser energy. By using these expressions, the RotoCOIL experiment is simulated, and obtained results agree well with experiment data. Effects of various adjustable parameters on the performances of COIL are also presented.

Temperature and composition profile during double-track laser cladding of H13 tool steel

Multi-track laser cladding is now applied commercially in a range of industries such as automotive, mining and aerospace due to its diversified potential for material processing. The knowledge of temperature, velocity and composition distribution history is essential for a better understanding of the process and subsequent microstructure evolution and properties. Numerical simulation not only helps to understand the complex physical phenomena and underlying principles involved in this process, but it can also be used in the process prediction and system control. The double-track coaxial laser cladding with H13 tool steel powder injection is simulated using a comprehensive three-dimensional model, based on the mass, momentum, energy conservation and solute transport equation. Some important physical phenomena, such as heat transfer, phase changes, mass addition and fluid flow, are taken into account in the calculation. The physical properties for a mixture of solid and liquid phase are defined by treating it as a continuum media. The velocity of the laser beam during the transition between two tracks is considered. The evolution of temperature and composition of different monitoring locations is simulated.

Digits speech recognition based on geometrical learning

We investigate the use of independent component analysis (ICA) for speech feature extraction in digits speech recognition systems.We observe that this may be true for a recognition tasks based on geometrical learning with little training data. In contrast to image processing, phase information is not essential for digits speech recognition. We therefore propose a new scheme that shows how the phase sensitivity can be removed by using an analytical description of the ICA-adapted basis functions via the Hilbert transform. Furthermore, since the basis functions are not shift invariant, we extend the method to include a frequency-based ICA stage that removes redundant time shift information. The digits speech recognition results show promising accuracy, Experiments show method based on ICA and geometrical learning outperforms HMM in different number of train samples.