Enhancing spatial resolution of remotely sensed data for mapping freshwater environments

Freshwater environments are important for ecosystem services and biodiversity. These environments are subject to many natural and anthropogenic changes, which influence their quality; therefore, regular monitoring is required for their effective management. High biotic heterogeneity, elongated land/water interaction zones, and logistic difficulties with access make field based monitoring on a large scale expensive, inconsistent and often impractical. Remote sensing (RS) is an established mapping tool that overcomes these barriers. However, complex and heterogeneous vegetation and spectral variability due to water make freshwater environments challenging to map using remote sensing technology. Satellite images available for New Zealand were reviewed, in terms of cost, and spectral and spatial resolution. Particularly promising image data sets for freshwater mapping include the QuickBird and SPOT-5. However, for mapping freshwater environments a combination of images is required to obtain high spatial, spectral, radiometric, and temporal resolution. Data fusion (DF) is a framework of data processing tools and algorithms that combines images to improve spectral and spatial qualities. A range of DF techniques were reviewed and tested for performance using panchromatic and multispectral QB images of a semi-aquatic environment, on the southern shores of Lake Taupo, New Zealand. In order to discuss the mechanics of different DF techniques a classification consisting of three groups was used - (i) spatially-centric (ii) spectrally-centric and (iii) hybrid. Subtract resolution merge (SRM) is a hybrid technique and this research demonstrated that for a semi aquatic QuickBird image it out performed Brovey transformation (BT), principal component substitution (PCS), local mean and variance matching (LMVM), and optimised high pass filter addition (OHPFA). However some limitations were identified with SRM, which included the requirement for predetermined band weights, and the over-representation of the spatial edges in the NIR bands due to their high spectral variance. This research developed three modifications to the SRM technique that addressed these limitations. These were tested on QuickBird (QB), SPOT-5, and Vexcel aerial digital images, as well as a scanned coloured aerial photograph. A visual qualitative assessment and a range of spectral and spatial quantitative metrics were used to evaluate these modifications. These included spectral correlation and root mean squared error (RMSE), Sobel filter based spatial edges RMSE, and unsupervised classification. The first modification addressed the issue of predetermined spectral weights and explored two alternative regression methods (Least Absolute Deviation, and Ordinary Least Squares) to derive image-specific band weights for use in SRM. Both methods were found equally effective; however, OLS was preferred as it was more efficient in processing band weights compared to LAD. The second modification used a pixel block averaging function on high resolution panchromatic images to derive spatial edges for data fusion. This eliminated the need for spectral band weights, minimised spectral infidelity, and enabled the fusion of multi-platform data. The third modification addressed the issue of over-represented spatial edges by introducing a sophisticated contrast and luminance index to develop a new normalising function. This improved the spatial representation of the NIR band, which is particularly important for mapping vegetation. A combination of the second and third modification of SRM was effective in simultaneously minimising the overall spectral infidelity and undesired spatial errors for the NIR band of the fused image. This new method has been labelled Contrast and Luminance Normalised (CLN) data fusion, and has been demonstrated to make a significant contribution in fusing multi-platform, multi-sensor, multi-resolution, and multi-temporal data. This contributes to improvements in the classification and monitoring of fresh water environments using remote sensing

An Undergraduate forensic biochemistry laboratory experiment to detect doping in animal hair using LCMS

Doping using performance enhancing banned substances is a serious problem in almost every sport competition. Not surprisingly, the detection of these contra banned drugs is an area of active and continuous improvement and innovation by bioanalytical chemists. Additionally, most students working out in the gym and taking part in various sports need to be made aware of the doping and the health problems associated with it. Science or STEM students, in particular chemistry students, must not only be made aware of these issues, but also be taught that chemistry (and science) can provide solutions to such real-life issues. To this end, a newly developed forensic laboratory experiment is described that guides students to learn liquid chromatography mass spectrometry instrumentation (LC-MS) to detect four common doping drugs cortisol, dexamethasone, methyl prednisolone and flumethasone in camel hair samples. In addition, the project is also designed to reinforce the importance of hair analysis as an additional sample matrix, complementary to saliva, blood and urine tests, in doping applications. In addition to learning various aspects of sample preparation, extraction, and LC-MS principles, students will also learn how to validate this method according to Food and Drugs Administration guidelines for intra and inter day precision and accuracy, recovery, stability and linearity. This “applied forensic science” experiment was successfully implemented in a biochemistry undergraduate research course to enhance students\u27 learning of doping issues as well as important bio-analytical and forensic biochemistry concepts. Student survey confirmed that this laboratory experiment was successful in achieving the objectives of raising awareness of doping control in students and illustrating the usefulness of chemistry in solving real-life problems. This experiment can be easily adopted in an advanced biochemistry laboratory course and taught as an inquiry-guided exercise. Such hands-on and engaging experiments should be part of undergraduate curriculum to foster deeper interest and innovation in STEM subjects to better prepare the next-generation workforce in science and technology

Thermophilic bioremediation of emerging pollutants using a recombinant thermophilic fungal peroxidase

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An Empirical Evidence of Human Capital Constraint towards Economic Growth

Human capital plays a crucial role in enhancing sustainable economic growth. The aim of this study is to investigate the long run linkage between economic growth and human capital and explore the problems facing by education and health sectors in Pakistan, how to remove these problems in order to increase Human Capital, eminence of Human Capital and Economic Growth also. For this purpose, this study has been taken annual time series data from 1977 to 2014 and employed co-integration technique to find out the results. This study has been used the data from WDI, SBP, and Economic Survey of Pakistan (various issues). The results of this study revealed strong positive and significant long run association between human capital and economic growth in Pakistan. It is also found by the study that current status of health and education sectors in Pakistan is very poor. This study may be useful for health and educational policy making and human capital formation to boost up economic growth in Pakistan. Keywords: Human capital, Economic Growth, Johansen Co-integration, Skilled Worker

A Prioritized Uplink Call Admission Control Algorithm for 3G WCDMA Cellular Systems with Multi-Services

The 3G cellular mobile systems which are based on WCDMA technology are expected to be interference limited. Soft capacity is one of the main characteristics of 3G (i.e, UMTS) and it requires new radio resource management strategies to serve diverse quality of service requirements. In this paper, a WCDMA prioritized uplink call admission control (CAC) algorithm for UMTS, which combines QoS negotiation and service differentiation by priority, is studied. This CAC scheme gives preferential treatment to high priority calls, such as soft handoff calls, by reserving some bandwidth margin (soft guard channel) to reduce handoff failures. In addition, queuing is also used to enhance the handoff success probability. The algorithm uses the effective load as an admission criterion and applies different thresholds for new and handoff calls. Finally, the study considers two types of services: voice and data calls. Results indicate that this algorithm reduces the drop handoff calls and increases the total system capacity; hence the GoS and the system performance can significantly be improved especially in case of high mobility environments

A Prioritized Uplink Call Admission Control Algorithm for 3G WCDMA Cellular Systems with Multi-Services

The 3G cellular mobile systems which are based on WCDMA technology are expected to be interference limited. Soft capacity is one of the main characteristics of 3G (i.e, UMTS) and it requires new radio resource management strategies to serve diverse quality of service requirements. In this paper, a WCDMA prioritized uplink call admission control (CAC) algorithm for UMTS, which combines QoS negotiation and service differentiation by priority, is studied. This CAC scheme gives preferential treatment to high priority calls, such as soft handoff calls, by reserving some bandwidth margin (soft guard channel) to reduce handoff failures. In addition, queuing is also used to enhance the handoff success probability. The algorithm uses the effective load as an admission criterion and applies different thresholds for new and handoff calls. Finally, the study considers two types of services: voice and data calls. Results indicate that this algorithm reduces the drop handoff calls and increases the total system capacity; hence the GoS and the system performance can significantly be improved especially in case of high mobility environments

HPLC estimation of iothalamate to measure glomerular filtration rate in humans

Glomerular filtration rate (GFR) is usually determined by estimation of iothalamate (IOT) clearance. We have developed and validated an accurate and robust method for the analysis of IOT in human plasma and urine. The mobile phase consisted of methanol and 50 mM sodium phosphate (10:90; v/v). Flow rate was 1.2 mL/min on a C18 reverse phase column, Synergi-hydro (250 × 4.6 mm) 4 µm 80 Å, with an ultraviolet detector set to 254 nm. Acetonitrile was used for the deproteination and extraction of IOT from human plasma and urine. Precision and accuracy were within 15% for IOT in both plasma and urine. The recoveries of IOT in urine and plasma ranged between 93.14% and 114.74 and 96.04–118.38%, respectively. The linear range for urine and plasma assays were 25–1500 and 1–150 µg/mL respectively. The lower limits of detection were 0.5 µg/mL for both urine and plasma, with no interference from plasma and urine matices. This method has been fully validated according to FDA guidelines and the new HPLC assay has been applied to a new formulation of IOT (Conray™ 43), to calculate GFR in healthy volunteers. The new method is simple, less expensive and it would be instrumental in future clinical and pharmacokinetic studies of iothalamate in kidney patients

Maximising access to timely trauma care across population of Karachi and its districts: A geospatial approach to develop a trauma care network

Objectives: To develop and propose a cost-effective trauma care network for Karachi, Pakistan, by calculating maximum timely trauma care (TTC) coverage achieved with the addition of potential designated private and public level 1 and level 2 trauma centres (TCs). Setting: A lower middle-income country metropolis, Karachi is Pakistan\u27s largest city with a population of 16 million and a total of 56 hospitals as per government registry data. Participants: 41 potential TCs selected using a two-level, contextually-relevant TC designation criteria adapted from various international guidelines. Primary and secondary outcome measures: Maximum TTC coverage achievable with the addition of potential TCs. Proposed trauma care network composition to achieve maximum TTC coverage. Results: Coverage with five public level 1 hospitals alone is 74.4%. Marginal benefit with stepwise addition of five potential private level 1 TCs, four public level 2 TCs and two private level 2 TCs is 12.2%, 7.1% and 3.1%, respectively. Maximum possible TTC coverage is 96.7%. Poorest coverage with the proposed 16 hospital network is noted in Malir district while 100% coverage is achieved in the centrally located South, Central and East districts. Conclusion: Addition of private level 1 and private and public level 2 hospitals to the trauma care network is necessary. Implementation of the proposed trauma care network requires strong stewardship from the government and coordinated effort of multiple stakeholders is needed to ensure standard TC designation. The study exhibits an effective method to scientifically plan and develop a cost-effective trauma system which can be applied in other resource-limited geographical area

Determination of diclofenac concentrations in human plasma using a sensitive gas chromatography mass spectrometry method

Background A gas chromatography mass spectrometry (GCMS) method for the determination of diclofenac in human plasma has been developed and validated. Results This method utilizes hexane which is a relatively less toxic extraction solvent compared to heptane and benzene. In addition, phosphoric acid and acetone were added to the samples as deproteination agents, which increased the recovery of diclofenac. These revised processes allow clean extraction and near-quantitative recovery of analyte (approx. 89–95 %). Separation was achieved on a BP-1 column with helium as carrier gas. The molecular ion peaks of the indolinone derivatives of diclofenac ion (m/z 277) and the internal standard, 4-hydroxydiclofenac ion (m/z 439) were monitored by a mass-selective detector using selected ion monitoring (SIM) mode. The linear range for the newly developed and highly sensitive assay was between 0.25–50 ng/mL. The detection and lower quantifiable limits were 0.125 and 0.25 ng/mL, respectively. The inter-day and intra-day coefficients of variation for high, medium and low quality control concentrations were less than 9 %. The robustness and efficacy of this sensitive GCMS method was further demonstrated by using it for a pharmacokinetic study of an oral dosage form of diclofenac, 100 mg of modified-release capsules (Rhumalgan XL), in human plasma. Conclusions This method is rapid, sensitive, specific, reproducible and robust, and offers improved sensitivity over previous methods. This method has considerable potential to be used for detailed pharmacokinetics, pharmacodynamics and bioequivalence studies of diclofenac in humans