179 research outputs found
sj-doc-3-jhs-10.1177_1753193416638812 – Supplemental material for Comparison of activities of daily living after proximal row carpectomy or wrist four-corner fusion
No full textSupplemental material, sj-doc-3-jhs-10.1177_1753193416638812 for Comparison of activities of daily living after proximal row carpectomy or wrist four-corner fusion by M.E. Brinkhorst, H.P. Singh, J.J. Dias, R. Feitz and S.E.R. Hovius in Journal of Hand Surgery (European Volume)</p
sj-doc-2-jhs-10.1177_1753193416638812 – Supplemental material for Comparison of activities of daily living after proximal row carpectomy or wrist four-corner fusion
No full textSupplemental material, sj-doc-2-jhs-10.1177_1753193416638812 for Comparison of activities of daily living after proximal row carpectomy or wrist four-corner fusion by M.E. Brinkhorst, H.P. Singh, J.J. Dias, R. Feitz and S.E.R. Hovius in Journal of Hand Surgery (European Volume)</p
sj-doc-1-jhs-10.1177_1753193416638812 – Supplemental material for Comparison of activities of daily living after proximal row carpectomy or wrist four-corner fusion
No full textSupplemental material, sj-doc-1-jhs-10.1177_1753193416638812 for Comparison of activities of daily living after proximal row carpectomy or wrist four-corner fusion by M.E. Brinkhorst, H.P. Singh, J.J. Dias, R. Feitz and S.E.R. Hovius in Journal of Hand Surgery (European Volume)</p
Ginninderra I and Ginniderra II: introduction to the CO(2) controlled release experiments
No full textPaper 30aTwo shallow sub-surface CO2 controlled release experiments were conducted at the Ginninderra test site during 2012. The theme of the first experiment was CO2 detection in the soil and surface emissions quantification. The theme for the second experiment was investigating sub-surface migration and broad scale detection technologies. Our objective overall is to design cheaper monitoring technologies to evaluate leakage and environmental impact in the shallow sub-surface. Over 10 different monitoring techniques were evaluated at the site against a known CO2 release. These included soil gas, soil CO2 flux, soil analysis, eddy covariance, atmospheric tomography, noble gas tracers, ground penetrating radar, electromagnetic surveys, airborne hyperspectral, in-field phenotyping (thermal, hyperspectral and 3D imaging), and microbial soil genomics. Technique highlights and an assessment of the implications for large scale storage are presented in the following corresponding talks.A. Feitz, H. Berko, C. Kemp, C. Jenkins, U. Schacht, R. Noble, S. Zegelin, T Kuske, A. McGrath, R. Pevzner, I. Schroder, X. Sirault and J. Jimenez-Bern
Great Artesian Basin - Cadna-owie Hooray Aquifer - pH
No full textMaintenance and Update Frequency: notPlannedStatement: SOURCE DATA:
Data was obtained from a variety of sources, as listed below:
1. Water quality data from the Queensland groundwater database, Department of Environment and Resource Management
2. Geological Society of Queensland water chemistry database (1970s to 1980s). Muller, PJ, Dale, NM (1985) Storage System for Groundwater Data Held by the Geological Survey of Queensland. GSQ Record 1985/47. Queensland.
3. Geoscience Australia GAB hydrochemistry dataset 1973-1997. Published in Radke BM, Ferguson J, Cresswell RG, Ransley TR and Habermehl MA (2000) Hydrochemistry and implied hydrodynamics of the Cadna-owie - Hooray Aquifer, Great Artesian Basin, Australia. Canberra, Bureau of Rural Sciences: xiv, 229p.
4. Feitz, A.J., Ransley, T.R., Dunsmore, R., Kuske, T.J., Hodgkinson, J., Preda, M., Spulak, R., Dixon, O. & Draper, J., 2014. Geoscience Australia and Geological Survey of Queensland Surat and Bowen Basins Groundwater Surveys Hydrochemistry Dataset (2009-2011). Geoscience Australia, Canberra Australia
5. Water quality data from the Office of Groundwater Impact Assessment, Department of Natural Resources and Mines, Queensland Government
6. Geoscience Australia (2010) Hydrogeochemical collection. A compilation of quality controlled groundwater data taken from well completion reports from QLD and NSW.
7. Water quality data from the Office of Groundwater Impact Assessment, Department of Natural Resources and Mines, Queensland Government
BOUNDARIES:
Data covers the extent of the Cadna-owie-Hooray Aquifer and Equivalents as defined in Great Artesian Basin - Cadna-owie-Hooray Aquifer and Equivalents - Thickness and Extent dataset (Available from www.ga.gov.au using catalogue number 81678)
METHOD:
Groundwater chemistry data was compiled from the data sources listed above. Data was imported into ESRI ArcGIS (ArcMap 10) as data point sets and used to create a predicted values surface using an ordinary kriging method within the Geostatistical Analyst extension. A log transform was applied to the Alkalinity, TDS, Na, SO4, Mg, Ca, K, F, Cl, Cl36 data prior to kriging. No transform was applied to the 13C, 18O, 2H, pH data prior to kriging. The geostatistical model was optimized using cross validation. The search neighbourhood was extended to a 1 degree radius, comprising of 4 sectors (N, S, E and W) with a minimum and maximum of 3 and 8 neighbours, respectively, per sector. The predicted values surface was exported to a vector format (Shapefile) and clipped to the aquifer boundaries.Data used to produce the predicted pH map for the Cadna-owie - Hooray Aquifer in the Hydrogeological Atlas of the Great Artesian Basin (Ransley et.al., 2015).<br/><br/>There are four layers in the Cadna-owie - Hooray Aquifer pH map data<br/><br/>A. Location of hydrochemistry samples (Point data, Shapefile)<br/>B. Predicted Concentration (Filled contours , Shapefile)<br/>C. Predicted Concentration Contours (Contours, Shapefile)<br/>D. Prediction Standard Error (Filled contours , Shapefile)<br/><br/>The predicted values provide a regional based estimate and may be associated with considerable error. It is recommended that the predicted values are read together with the predicted error map, which provides an estimate of the absolute standard error associated with the predicted values at any point within the map.<br/><br/>The predicted standard error map provides an absolute standard error associated with the predicted values at any point within the map. Please note this is not a relative error map and the concentration of a parameter needs to be considered when interpreting the map. Predicted standard error values are low where the concentration is low and there is a high density of samples. Predicted standard errors values can be high where the concentration is high and there is moderate variability between nearby samples or where there is a paucity of data.<br/><br/>Coordinate system is Lambert conformal conic GDA 1994, with central meridian 134 degrees longitude, standard parallels at -18 and -36 degrees latitude.<br/><br/>The Cadna-owie - Hooray Aquifer pH map is one of 14 hydrochemistry maps for the Cadna-owie - Hooray Aquifer and 24 hydrochemistry maps in the Hydrogeological Atlas of the Great Artesian Basin (Ransley et.al., 2014). <br/><br/>This dataset and associated metadata can be obtained from www.ga.gov.au, using catalogue number 81696<br/> <br/>References:<br/>Hitchon, B. and Brulotte, M. (1994): Culling criteria for 'standard' formation water analyses; Applied Geochemistry, v. 9, p. 637-645<br/><br/>Ransley, T., Radke, B., Feitz, A., Kellett, J., Owens, R., Bell, J. and Stewart, G., 2015. Hydrogeological Atlas of the Great Artesian Basin. Geoscience Australia. Canberra. [available from www.ga.gov.au using catalogue number 79790
Great Artesian Basin - Coreena Wallumbilla Aquifer - Alkalinity
No full textMaintenance and Update Frequency: notPlannedStatement: SOURCE DATA:
Data was obtained from a variety of sources, as listed below:
1. Water quality data from the Queensland groundwater database, Department of Environment and Resource Management
2. Geological Society of Queensland water chemistry database (1970s to 1980s). Muller, PJ, Dale, NM (1985) Storage System for Groundwater Data Held by the Geological Survey of Queensland. GSQ Record 1985/47. Queensland.
3. Geoscience Australia GAB hydrochemistry dataset 1973-1997. Published in Radke BM, Ferguson J, Cresswell RG, Ransley TR and Habermehl MA (2000) Hydrochemistry and implied hydrodynamics of the Cadna-owie - Hooray Aquifer, Great Artesian Basin, Australia. Canberra, Bureau of Rural Sciences: xiv, 229p.
4. Feitz, A.J., Ransley, T.R., Dunsmore, R., Kuske, T.J., Hodgkinson, J., Preda, M., Spulak, R., Dixon, O. & Draper, J., 2014. Geoscience Australia and Geological Survey of Queensland Surat and Bowen Basins Groundwater Surveys Hydrochemistry Dataset (2009-2011). Geoscience Australia, Canberra Australia
5. Water quality data from the Office of Groundwater Impact Assessment, Department of Natural Resources and Mines, Queensland Government
6. Geoscience Australia (2010) Hydrogeochemical collection. A compilation of quality controlled groundwater data taken from well completion reports from QLD and NSW.
7. Water quality data from the Office of Groundwater Impact Assessment, Department of Natural Resources and Mines, Queensland Government
BOUNDARIES:
Data covers the extent of the Rolling Downs Aquitard as defined in Great Artesian Basin - Rolling Downs Aquitard - Thickness and Extent dataset (Available from www.ga.gov.au using catalogue number 81677).
METHOD:
Groundwater chemistry data was compiled from the data sources listed above. Data was imported into ESRI ArcGIS (ArcMap 10) as data point sets and used to create a predicted values surface using an ordinary kriging method within the Geostatistical Analyst extension. A log transform was applied to the Alkalinity, TDS, Na, SO4, Mg, Ca, K, F, Cl, Cl36 data prior to kriging. No transform was applied to the 13C, 18O, 2H, pH data prior to kriging. The geostatistical model was optimized using cross validation. The search neighbourhood was extended to a 1 degree radius, comprising of 4 sectors (N, S, E and W) with a minimum and maximum of 3 and 8 neighbours, respectively, per sector. The predicted values surface was exported to a vector format (Shapefile) and clipped to the aquifer boundaries.Data used to produce the predicted Alkalinity map for the Wallumbilla - Rolling Downs Group aquifers in the Hydrogeological Atlas of the Great Artesian Basin (Ransley et.al., 2015).<br/><br/>There are four layers in the Wallumbilla - Rolling Downs Group aquifers Alkalinity map data<br/><br/>A. Location of hydrochemistry samples (Point data, Shapefile)<br/>B. Predicted Concentration (Filled contours , Shapefile)<br/>C. Predicted Concentration Contours (Contours, Shapefile)<br/>D. Prediction Standard Error (Filled contours , Shapefile)<br/><br/>The predicted values provide a regional based estimate and may be associated with considerable error. It is recommended that the predicted values are read together with the predicted error map, which provides an estimate of the absolute standard error associated with the predicted values at any point within the map.<br/><br/>The predicted standard error map provides an absolute standard error associated with the predicted values at any point within the map. Please note this is not a relative error map and the concentration of a parameter needs to be considered when interpreting the map. Predicted standard error values are low where the concentration is low and there is a high density of samples. Predicted standard errors values can be high where the concentration is high and there is moderate variability between nearby samples or where there is a paucity of data.<br/><br/>Concentrations are Alkalinity as CaCO3 mg/L.<br/><br/>Coordinate system is Lambert conformal conic GDA 1994, with central meridian 134 degrees longitude, standard parallels at -18 and -36 degrees latitude.<br/><br/>The Wallumbilla - Rolling Downs Group aquifers Alkalinity map is one of two hydrochemistry maps for the Wallumbilla - Rolling Downs Group aquifers and 24 hydrochemistry maps in the Hydrogeological Atlas of the Great Artesian Basin (Ransley et. al, 2014). <br/><br/>This dataset and associated metadata can be obtained from www.ga.gov.au, using catalogue number 81690<br/> <br/>References: <br/>Hitchon, B. and Brulotte, M. (1994): Culling criteria for 'standard' formation water analyses; Applied Geochemistry, v. 9, p. 637-645<br/><br/>Ransley, T., Radke, B., Feitz, A., Kellett, J., Owens, R., Bell, J. and Stewart, G., 2015. Hydrogeological Atlas of the Great Artesian Basin. Geoscience Australia. Canberra. [available from www.ga.gov.au using catalogue number 79790
TANGOS / Alfred HAUSE et son Ensemble
No full textComprend : DONNA VATRA / KOPPING - CE N'EST QUE VOTRE MAIN MADAME / R. ERWIN - VIOLETTA / O. KLOSE - R. LUKESCH - GUITARE DE LA NUIT / RIXNER - ROSES ROUGES / RITTER - ORCHIDEES NOIRES / W. RICHARTZ - VIENS REVER / B. DE WEILLE - H. WOEZEL - JE N'AI QUE TOI AU MONDE / SCHMITZ - K. FELTZ - NUITS FLORENTINES / N. DOSTAL - E. MEDER - EIN MUSIKUS / H. GAZE - K. FEITZ - LEON / H. GAZE - SCHWENN - LE TANGO DES JOURS HEUREUX / M. HARDEN - A. HOFFBnF-Partenariats, Collection sonore - BelieveContient une table des matière
Great Artesian Basin - Cadna-owie Hooray Aquifer - 18O
No full textMaintenance and Update Frequency: notPlannedStatement: SOURCE DATA:
Data was obtained from a variety of sources, as listed below:
1. Geoscience Australia GAB hydrochemistry dataset 1973-1997. Published in Radke BM, Ferguson J, Cresswell RG, Ransley TR and Habermehl MA (2000) Hydrochemistry and implied hydrodynamics of the Cadna-owie - Hooray Aquifer, Great Artesian Basin, Australia. Canberra, Bureau of Rural Sciences: xiv, 229p.
2. Feitz, A.J., Ransley, T.R., Dunsmore, R., Kuske, T.J., Hodgkinson, J., Preda, M., Spulak, R., Dixon, O. & Draper, J., 2014. Geoscience Australia and Geological Survey of Queensland Surat and Bowen Basins Groundwater Surveys Hydrochemistry Dataset (2009-2011). Geoscience Australia, Canberra Australia
BOUNDARIES:
Data covers the extent of the Cadna-owie-Hooray Aquifer and Equivalents as defined in Great Artesian Basin - Cadna-owie-Hooray Aquifer and Equivalents - Thickness and Extent dataset (Available from www.ga.gov.au using catalogue number 81678)
METHOD:
Groundwater chemistry data was compiled from the data sources listed above. Data was imported into ESRI ArcGIS (ArcMap 10) as data point sets and used to create a predicted values surface using an ordinary kriging method within the Geostatistical Analyst extension. A log transform was applied to the Alkalinity, TDS, Na, SO4, Mg, Ca, K, F, Cl, Cl36 data prior to kriging. No transform was applied to the 13C, 18O, 2H, pH data prior to kriging. The geostatistical model was optimized using cross validation. The search neighbourhood was extended to a 1 degree radius, comprising of 4 sectors (N, S, E and W) with a minimum and maximum of 3 and 8 neighbours, respectively, per sector. The predicted values surface was exported to a vector format (Shapefile) and clipped to the aquifer boundaries.Data used to produce the predicted Oxygen-18 map for the Cadna-owie - Hooray Aquifer in the Hydrogeological Atlas of the Great Artesian Basin (Ransley et.al., 2015).<br/><br/>There are four layers in the Cadna-owie - Hooray Aquifer Oxygen-18 map data<br/><br/>A. Location of hydrochemistry samples (Point data, Shapefile)<br/>B. Predicted Concentration (Filled contours , Shapefile)<br/>C. Predicted Concentration Contours (Contours, Shapefile)<br/>D. Prediction Standard Error (Filled contours , Shapefile)<br/><br/>The predicted values provide a regional based estimate and may be associated with considerable error. It is recommended that the predicted values are read together with the predicted error map, which provides an estimate of the absolute standard error associated with the predicted values at any point within the map.<br/><br/>The predicted standard error map provides an absolute standard error associated with the predicted values at any point within the map. Please note this is not a relative error map and the concentration of a parameter needs to be considered when interpreting the map. Predicted standard error values are low where the concentration is low and there is a high density of samples. Predicted standard errors values can be high where the concentration is high and there is moderate variability between nearby samples or where there is a paucity of data.<br/><br/>Oxygen-18 units are 18O SMOW. <br/><br/>Coordinate system is Lambert conformal conic GDA 1994, with central meridian 134 degrees longitude, standard parallels at -18 and -36 degrees latitude.<br/><br/>The Cadna-owie - Hooray Aquifer Oxygen-18 map is one of 14 hydrochemistry maps for the Cadna-owie - Hooray Aquifer and 24 hydrochemistry maps in the Hydrogeological Atlas of the Great Artesian Basin (Ransley et.al., 2014). <br/><br/>This dataset and associated metadata can be obtained from www.ga.gov.au, using catalogue number 81705<br/> <br/>References:<br/>Hitchon, B. and Brulotte, M. (1994): Culling criteria for 'standard' formation water analyses; Applied Geochemistry, v. 9, p. 637-645<br/><br/>Ransley, T., Radke, B., Feitz, A., Kellett, J., Owens, R., Bell, J. and Stewart, G., 2015. Hydrogeological Atlas of the Great Artesian Basin. Geoscience Australia. Canberra. [available from www.ga.gov.au using catalogue number 79790
Liquid-core microcapsules: A mechanism for the recovery and purification of selected molecules in different environments
No full textLiquid-core microcapsules can be described as miniature sized particles ( 1.2 l/hr of microspheres and > 2 l/hr of liquid-core microcapsules, and this can be easily and naturally elevated to higher volumes by increasing the number of nozzles on the encapsulator.
Firstly the microcapsules were used as an innovative technique (known as capsular perstraction) to recover the commonly found pharmaceutically active compounds; sulfamethoxazole, metoprolol, furosemide, carbamazepine, clofibric acid, warfarin and diclofenac from water. The approach of preparing capsules with different solvents within their cores and combining them in water, contaminated with pharmaceuticals, enabled a rapid recovery of the drugs from this sphere. In addition the uptake of warfarin was examined to assess the conditions affecting mass transfer of the molecules into the capsules. It was subsequently determined that the stagnant organic layer was the main limiting factor. This part of the study emphasized how the characteristics (size and membrane thickness) of capsules can affect the removal rate of compounds into the liquid-core and also how the rate of extraction can be simply controlled by varying these parameters during the capsule manufacturing process. In a second application, the capsular extraction technology was further developed by adopting it as an aide for the recovery and purification of the antibiotic geldanamycin from Bennett’s medium. From this work it was shown how a small quantity of capsules was capable of rapidly extracting the molecule from the culture medium. Again the limitations to mass transfer were accessed, and it was discovered that the main rate limiting step was the external resistance outside of the capsules, which can be governed by controlling the outer turbulence. In a further development the capsules showed their potential to be used as a mechanism for concentrating, purifying and enabling crystallization of the extractant, using a very simplistic and straightforward procedure, which was not destructive to the microcapsules, hence enabling their continuous re-use.
Finally the capsules were applied to a real-time situation, in order to examine the feasibility of using the simple, non-toxic and sterile technology as a novel in-situ product recovery technique, to improve the production and recovery yield of geldanamycin in cultures containing the bacterium Streptomyces hygroscopicus.
Implementation of this approach resulted in the rapid removal of the metabolite from an environment which was causing its break-down and seriously affecting recovery yields.
Extraction enabled the molecule to be transferred into a stable and secure domain, where it was protected from external influences. This removal improved overall net production by 30% compared to fermentations containing no capsules. Most importantly however, the capsule-facilitated recovery process acted as a methodology, which enabled high recoveries (> 53%) of the fermented geldanamycin to be obtained as highly purified crystals (> 97%) using a facile, inexpensive and reproducible process, which should be easily implemented at a lab-scale or industrial-level
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