935 resultados para Extraction and Processing Industry
Resumo:
Lithium is used in the cathode and electrolyte of rechargeable batteries in many portable electronics and electric vehicles, and is thus seen as a critical component of modern technology (Gruber et al., 2011). Electric vehicles are promoted as a way to reduce carbon emissions associated with the transportation sector, which accounts for 14.3% of anthropogenic greenhouse gas emissions (OECD International Transport Forum, 2010). However, the sustainability of lithium procurement will influence the overall environmental impact of this proposed “green” solution. It is estimated that 66% of the world’s lithium resource is contained in natural brines, 24% in pegmatites, and 8% in sedimentary rocks such as hectorite clays (Gruber et al., 2011). It has been shown that “[r]ecycling of lithium from Li-ion batteries may be a critical factor in balancing the supply of lithium with future demand” (Gruber et al., 2011). In an attempt to quantify energy and materials consumption associated with production of a unit of useful lithium compounds, industry reports and peer-reviewed scientific literature concerning lithium mining and lithium recycling were reviewed and compared. Other aspects of sustainability, such as waste or by-products produced in the production of a unit of useful lithium, were also explored. Thus, this paper will serve to further the evaluation of the comparative environmental consequences associated with lithium production via extraction versus recycling. Efficiencies must be made in both processes to maximize productivity while minimizing ecological harm.
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Automatic video segmentation plays a vital role in sports videos annotation. This paper presents a fully automatic and computationally efficient algorithm for analysis of sports videos. Various methods of automatic shot boundary detection have been proposed to perform automatic video segmentation. These investigations mainly concentrate on detecting fades and dissolves for fast processing of the entire video scene without providing any additional feedback on object relativity within the shots. The goal of the proposed method is to identify regions that perform certain activities in a scene. The model uses some low-level feature video processing algorithms to extract the shot boundaries from a video scene and to identify dominant colours within these boundaries. An object classification method is used for clustering the seed distributions of the dominant colours to homogeneous regions. Using a simple tracking method a classification of these regions to active or static is performed. The efficiency of the proposed framework is demonstrated over a standard video benchmark with numerous types of sport events and the experimental results show that our algorithm can be used with high accuracy for automatic annotation of active regions for sport videos.
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Companies operating in the wood processing industry need to increase their productivity by implementing automation technologies in their production systems. An increasing global competition and rising raw material prizes challenge their competitiveness. Yet, too extensive automation brings risks such as a deterioration in situation awareness and operator deskilling. The concept of Levels of Automation is generally seen as means to achieve a balanced task allocation between the operators’ skills and competences and the need for automation technology relieving the humans from repetitive or hazardous work activities. The aim of this thesis was to examine to what extent existing methods for assessing Levels of Automation in production processes are applicable in the wood processing industry when focusing on an improved competitiveness of production systems. This was done by answering the following research questions (RQ): RQ1: What method is most appropriate to be applied with measuring Levels of Automation in the wood processing industry? RQ2: How can the measurement of Levels of Automation contribute to an improved competitiveness of the wood processing industry’s production processes? Literature reviews were used to identify the main characteristics of the wood processing industry affecting its automation potential and appropriate assessment methods for Levels of Automation in order to answer RQ1. When selecting the most suitable method, factors like the relevance to the target industry, application complexity or operational level the method is penetrating were important. The DYNAMO++ method, which covers both a rather quantitative technical-physical and a more qualitative social-cognitive dimension, was seen as most appropriate when taking into account these factors. To answer RQ 2, a case study was undertaken at a major Swedish manufacturer of interior wood products to point out paths how the measurement of Levels of Automation contributes to an improved competitiveness of the wood processing industry. The focus was on the task level on shop floor and concrete improvement suggestions were elaborated after applying the measurement method for Levels of Automation. Main aspects considered for generalization were enhancements regarding ergonomics in process design and cognitive support tools for shop-floor personnel through task standardization. Furthermore, difficulties regarding the automation of grading and sorting processes due to the heterogeneous material properties of wood argue for a suitable arrangement of human intervention options in terms of work task allocation. The application of a modified version of DYNAMO++ reveals its pros and cons during a case study which covers a high operator involvement in the improvement process and the distinct predisposition of DYNAMO++ to be applied in an assembly system.
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The objective of this study was to extract and concentrate calcium oxalate (CaOx) crystals from plant leaves that form the above mentioned crystals. The chemical and physical studies of CaOx from plant to be performed depend on an adequate amount of the crystals. The plant used in this study was croton (Codiaeum variegatum). The leaves were ground in a heavy duty blender and sieved through a 0.20 mm sieve. The suspension obtained was suspended in distilled water. The crystals were concentrated at the bottom of a test tube. The supernatant must be washed until it is free of plant pigments and other organic substances. Biogenic CaOx crystals have well-defined and sharp peaks, indicating very high crystallinity. Moreover, the CaOx crystals were not damaged during the extraction procedure, as can be seen on the scanning electron microscope images. The porposed method can be considered efficient to extract and concentrate biogenic calcium oxalate.
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Introduction. This protocol aims at preparing total RNA for gene expression analysis by Northern blots, RT-PCR and real-time quantitative PCR; cDNA isolation by RTPCR; and cDNA library construction. The principle, key advantages, starting plant material, time required for obtaining total RNA and expected results are presented. Materials and methods. This part describes the required materials and the 27 steps necessary for preparing RNA from peel and pulp fruit tissue: preparation of plant tissue powder, preparation of the complete RNA extraction buffer and isolation of RNA from ground banana fruit tissue. Results. Extraction of total RNA by the method described makes it possible to achieve electrophoresis under denatured conditions and in vitro reverse transcription. An example for Northern blot analysis is illustrated.
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An improved procedure is proposed for determination of the pesticide carbaryl in natural waters based on double cloud point extraction. The clean up step was carried out only with Triton X-114 in alkaline medium in order to avoid the use of toxic organic solvents as well as to minimise waste generation. Cloud point preconcentration of the product of the reaction of the analyte with p-aminophenol and cetyltrimethylammonium bromide was explored to increase sensitivity and improve the detection limit. Linear response was achieved within 10 and 500 mu g L-1 and the apparent molar absorptivity was estimated as 4.6 x 105 L mol-1 cm-1. The detection limit was estimated as 7 mu g L-1 at the 99.7% confidence level and the coefficient of variation was 3.4% (n = 8). Recoveries within 91 and 99% were estimated for carbaryl spiked water samples. The results obtained for natural water samples were in agreement with those achieved by the batch of spectrophotometric procedure at the 95% confidence level. The proposed procedure is then a simple, fast, inexpensive and greener alternative for carbaryl determination.
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A flow injection (FI) micelle-mediated separation/preconcentration procedure for the determination of lead and cadmium by flame atomic absorption spectrometry (FAAS) has been proposed. The analytes reacted with 1-(2-thiazolylazo)-2-naphthol (TAN) to form hydrophobic chelates, which were extracted into the micelles of 0.05% (w/v) Triton X-114 in a solution buffered at pH 8.4. In the preconcentration stage, the micellar solution was continuously injected into a flow system with four mini-columns packed with cotton, glass wool. or TNT compresses for phase separation. The analytes-containing micelles were eluted from the mini-columns by a stream of 3 mol L(-1) HCl solution and the analytes were determined by FAAS. Chemical and flow variables affecting the preconcentration of the analytes were studied. For 15 mL. of preconcentrated solution, the enhancement factors varied between 15.1 and 20.3, the limits of detection were approximately 4.5 and 0.75 mu g L(-1) for lead and cadmium, respectively. For a solution containing 100 and 10 mu g L(-1) of lead and cadmium, respectively, the R.S.D. values varied from 1.6 to 3.2% (n = 7). The accuracy of the preconcentration system was evaluated by recovery measurements on spiked water samples. The method was susceptible to matrix effects, but these interferences were minimized by adding barium ions as masking agent in the sample solutions, and recoveries from spiked sample varied in the range of 95.1-107.3%. (C) 2008 Elsevier B.V. All rights reserved.
Resumo:
This paper proposes a novel computer vision approach that processes video sequences of people walking and then recognises those people by their gait. Human motion carries different information that can be analysed in various ways. The skeleton carries motion information about human joints, and the silhouette carries information about boundary motion of the human body. Moreover, binary and gray-level images contain different information about human movements. This work proposes to recover these different kinds of information to interpret the global motion of the human body based on four different segmented image models, using a fusion model to improve classification. Our proposed method considers the set of the segmented frames of each individual as a distinct class and each frame as an object of this class. The methodology applies background extraction using the Gaussian Mixture Model (GMM), a scale reduction based on the Wavelet Transform (WT) and feature extraction by Principal Component Analysis (PCA). We propose four new schemas for motion information capture: the Silhouette-Gray-Wavelet model (SGW) captures motion based on grey level variations; the Silhouette-Binary-Wavelet model (SBW) captures motion based on binary information; the Silhouette-Edge-Binary model (SEW) captures motion based on edge information and the Silhouette Skeleton Wavelet model (SSW) captures motion based on skeleton movement. The classification rates obtained separately from these four different models are then merged using a new proposed fusion technique. The results suggest excellent performance in terms of recognising people by their gait.
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A three-phase LPME (liquid-phase microextraction) method for the enantioselective analysis of venlafaxine (VF) metabolites (O-desmethylvenlafaxine (ODV) and N-desmethylvenlafaxine (NDV) in microsomal preparations is described for the first time. The assay involves the chiral HPLC separation of drug and metabolites using a Chiralpak AD column under normal-phase mode of elution and detection at 230 nm. The LPME procedure was optimized using multifactorial experiments and the following optimal condition was established: sample agitation at 1,750 rpm, 20 min of extraction, acetic acid 0.1 mol/L as acceptor phase, 1-octanol as organic phase and donor phase pH adjustment to 10.0. Under these conditions, the mean recoveries were 41% and 42% for (-)-(R)-ODV and (+)-(S)-ODV, respectively, and 47% and 48% for (-)-( R)-NDV and (+)-( S)-NDV, respectively. The method presented quantification limits of 200 ng/mL and it was linear over the concentration range of 200-5,000 ng/mL for all analytes. The validated method was employed to study the in vitro biotransformation of VF using rat liver microsomal fraction. The results demonstrated the enantioselective biotransformation of VF.
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A simple method for the measurement of pindolol enantiomers by HPLC is presented. Alkalinized serum or urine is extracted with ethyl acetate and the residue remaining after evaporation of the organic layer is then derivatised with (S)-(-)-alpha-methylbenzyl isocyanate. The diastereoisomers of derivatised pindolol and metoprolol (internal standard) are separated by high-performance liquid chromatography (HPLC) using a C-18 silica column and detected using fluorescence (excitation lambda: 215 nm, emission lambda: 320 nm). The assay displays reproducible linearity for pindolol enantiomers with a correlation coefficient of r(2) greater than or equal to 0.998 over the concentration range 8-100 ng ml(-1) for plasma and 0.1-2.5 mu g ml(-1) for urine. The coefficient of variation for accuracy and precision of the quality control samples for both plasma and urine are consistently
Resumo:
A sensitive and reproducible stir bar-sorptive extraction and high-performance liquid chromatography-UV detection (SBSE/HPLC-UV) method for therapeutic drug monitoring of carbamazepine, carbamazepine-10,11-epoxide, phenytoin and phenobarbital in plasma samples is described and compared with a liquid:liquid extraction (LLE/HPLC-UV) method. Important factors in the optimization of SBSE efficiency such as pH, extraction time and desorption conditions (solvents, mode magnetic stir, mode ultrasonic stir, time and number of steps) assured recoveries ranging from 72 to 86%, except for phenytoin (62%). Separation was obtained using a reverse phase C-18 column with UV detection (210 nm). The mobile phase consisted of water: acetonitrile (78:22, v/v). The SBSE/HPLC-UV method was linear over a working range of 0.08-40.0 mu g mL(-1) for carbamazepine, carbamazepine-10,11-epoxide and phenobarbital and 0.125-40.0 mu g mL(-1) for phenytoin, The intra-assay and inter-assay precision and accuracy were studied at three concentrations (1.0, 4.0 and 20.0 mu g mL(-1)). The intra-assay coefficients of variation (CVs) for all compounds were less than 8.8% and all inter-CVs were less than 10%. Limits of quantification were 0.08 mu g mL(-1) for carbamazepine, carbamazepine-10,11-epoxide and phenobarbital and 0.125 mu g mL(-1) for phenytoin. No interference of the drugs normally associated with antiepileptic drugs was observed. Based on figures of merit results, the SBSE/HPLC-UV proved adequate for antiepileptic drugs analyses from therapeutic levels. This method was successfully applied to the analysis of real samples and was as effective as the LLE/HPLC-UV method. (c) 2008 Elsevier B.V. All rights reserved.
Resumo:
A sensitive and precise stir bar sorptive extraction (SBSE) combined with LC (SBSE/LC) analysis is described for simultaneous determination of methyl, ethyl, propyl, and butyl parabens in commercial cosmetic products in agreement with the European Union Cosmetics Directive 76/768/EEC. Important factors in the optimization of SB SE efficiency are discussed, such as time and temperature of extraction, pH, and ionic strength of the sample, matrix effects, and liquid desorption conditions by different modes (magnetic stirring, ultrasonic). The LOQs of the SBSE/LC method ranged from 30 to 200 ng/mg, with linear response over a dynamic range, from the LOQ to 2.5 mu g/mg, with a coefficient of determination higher than 0.993. The interday precision of the SBSE/LC method presented a coefficient of variation lower than 5%. The effectiveness of the proposed method was proven for analysis of commercial cosmetic products such as body creams, antiperspirant creams, and sunscreens.
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A sensitive and reproducible stir bar-sorptive extraction and high performance liquid chromatography-UV detection (SBSE/HPLC-UV) method for therapeutic drug monitoring of rifampicin in plasma samples is described and compared with a liquid:liquid extraction (LLE/HPLC-UV) method. This miniaturized method can result in faster analysis, higher sample throughput, lower solvent consumption and less workload per sample while maintaining or even improving sensitivity. Important factors in the optimization of SBSE efficiency such as pH, temperature, extraction time and desorption conditions (solvents, mode magnetic stir, mode ultrasonic stir, time and number of steps) were optimized recoveries ranging from 75 to 80%. Separation was obtained using a reverse phase C(8) column with UV detection (254 nm). The mobile phase consisted of methanol:0.25 N sodium acetate buffer, pH 5.0 (58:42, v/v). The SBSE/HPLC-UV method was linear over a working range of 0.125-50.0 mu g mL(-1). The intra-assay and inter-assay precision and accuracy were studied at three concentrations (1.25, 6.25 and 25.0 mu g mL(-1)). The intra-assay coefficients of variation (CVs) for all compounds were less than 10% and all inter-CVs were less than 10%. Limits of quantification were 0.125 mu g mL(-1). Stability studies showed rifampicin was stable in plasma for 12 h after thawing; the samples were also stable for 24 h after preparation. Based on the figures of merit results, the SBSE/HPLC-UV proved to be adequate to the rifampicin analyses from therapeutic to toxic levels. This method was successfully applied to the analysis of real samples and was as effective as the LLE/HPLC-UV method. (C) 2009 Elsevier B.V. All rights reserved.