Online solid phase extraction liquid chromatography tandem mass spectrometry (SPE-LC-MS/MS) method for the determination of sucralose in reclaimed and drinking waters and its photo degradation in natural waters from South Florida

Background Sucralose has gained popularity as a low calorie artificial sweetener worldwide. Due to its high stability and persistence, sucralose has shown widespread occurrence in environmental waters, at concentrations that could reach up to several μg/L. Previous studies have used time consuming sample preparation methods (offline solid phase extraction/derivatization) or methods with rather high detection limits (direct injection) for sucralose analysis. This study described a faster and sensitive analytical method for the determination of sucralose in environmental samples. Results An online SPE-LC–MS/MS method was developed, being capable to quantify sucralose in 12 minutes using only 10 mL of sample, with method detection limits (MDLs) of 4.5 ng/L, 8.5 ng/L and 45 ng/L for deionized water, drinking and reclaimed waters (1:10 diluted with deionized water), respectively. Sucralose was detected in 82% of the reclaimed water samples at concentrations reaching up to 18 μg/L. The monthly average for a period of one year was 9.1 ± 2.9 μg/L. The calculated mass loads per capita of sucralose discharged through WWTP effluents based on the concentrations detected in wastewaters in the U. S. is 5.0 mg/day/person. As expected, the concentrations observed in drinking water were much lower but still relevant reaching as high as 465 ng/L. In order to evaluate the stability of sucralose, photodegradation experiments were performed in natural waters. Significant photodegradation of sucralose was observed only in freshwater at 254 nm. Minimal degradation (<20%) was observed for all matrices under more natural conditions (350 nm or solar simulator). The only photolysis product of sucralose identified by high resolution mass spectrometry was a de-chlorinated molecule at m/z 362.0535, with molecular formula C12H20Cl2O8. Conclusions Online SPE LC-APCI/MS/MS developed in the study was applied to more than 100 environmental samples. Sucralose was frequently detected (>80%) indicating that the conventional treatment process employed in the sewage treatment plants is not efficient for its removal. Detection of sucralose in drinking waters suggests potential contamination of surface and ground waters sources with anthropogenic wastewater streams. Its high resistance to photodegradation, minimal sorption and high solubility indicate that sucralose could be a good tracer of anthropogenic wastewater intrusion into the environment.

The use of quantitative polymerase chain reaction amplification method to determine sex ratio of human spermatozoa in semen and to determine maternal contamination of amniotic fluid samples

We have modified a technique which uses a single pair of primer sets directed against homologous but distinct genes on the X and Y chromosomes, all of which are coamplified in the same reaction tube with trace amounts of radioactivity. The resulting bands are equal in length, yet distinguishable by restriction enzyme sites generating two independent bands, a 364 bp X-specific band and a 280 bp Y-specific band. A standard curve was generated to show the linear relationship between X/Y ratio average vs. %Y or %X chromosomal content. Of the 51 purified amniocyte DNA samples analyzed, 16 samples showed evidence of high % X contamination while 2 samples demonstrated higher % Y than the expected 50% X and 50% Y chromosomal content. With regards to the 25 processed sperm samples analyzed, X-sperm enrichment was evident when compared to the primary sex ratio whereas Y-sperm was enriched when we compared before and after selection samples.

Estimation and Prediction of Average Vehicle Occupancies using Traffic Accident Records

As congestion management strategies begin to put more emphasis on person trips than vehicle trips, the need for vehicle occupancy data has become more critical. The traditional methods of collecting these data include the roadside windshield method and the carousel method. These methods are labor-intensive and expensive. An alternative to these traditional methods is to make use of the vehicle occupancy information in traffic accident records. This method is cost effective and may provide better spatial and temporal coverage than the traditional methods. However, this method is subject to potential biases resulting from under- and over-involvement of certain population sectors and certain types of accidents in traffic accident records. In this dissertation, three such potential biases, i.e., accident severity, driver¡¯s age, and driver¡¯s gender, were investigated and the corresponding bias factors were developed as needed. The results show that although multi-occupant vehicles are involved in higher percentages of severe accidents than are single-occupant vehicles, multi-occupant vehicles in the whole accident vehicle population were not overrepresented in the accident database. On the other hand, a significant difference was found between the distributions of the ages and genders of drivers involved in accidents and those of the general driving population. An information system that incorporates adjustments for the potential biases was developed to estimate the average vehicle occupancies (AVOs) for different types of roadways on the Florida state roadway system. A reasonableness check of the results from the system shows AVO estimates that are highly consistent with expectations. In addition, comparisons of AVOs from accident data with the field estimates show that the two data sources produce relatively consistent results. While accident records can be used to obtain the historical AVO trends and field data can be used to estimate the current AVOs, no known methods have been developed to project future AVOs. Four regression models for the purpose of predicting weekday AVOs on different levels of geographic areas and roadway types were developed as part of this dissertation. The models show that such socioeconomic factors as income, vehicle ownership, and employment have a significant impact on AVOs.

Development of a surface-enhanced raman spectroscopy method for the detection of benzodiazepines in urine

Benzodiazepines are among the most prescribed compounds for anti-anxiety and are present in many toxicological screens. These drugs are also prominent in the commission of drug facilitated sexual assaults due their effects on the central nervous system. Due to their potency, a low dose of these compounds is often administered to victims; therefore, the target detection limit for these compounds in biological samples is 10 ng/mL. Currently these compounds are predominantly analyzed using immunoassay techniques; however more specific screening methods are needed. ^ The goal of this dissertation was to develop a rapid, specific screening technique for benzodiazepines in urine samples utilizing surface-enhanced Raman spectroscopy (SERS), which has previously been shown be capable of to detect trace quantities of pharmaceutical compounds in aqueous solutions. Surface enhanced Raman spectroscopy has the advantage of overcoming the low sensitivity and fluorescence effects seen with conventional Raman spectroscopy. The spectra are obtained by applying an analyte onto a SERS-active metal substrate such as colloidal metal particles. SERS signals can be further increased with the addition of aggregate solutions. These agents cause the nanoparticles to amass and form hot-spots which increase the signal intensity. ^ In this work, the colloidal particles are spherical gold nanoparticles in aqueous solution with an average size of approximately 30 nm. The optimum aggregating agent for the detection of benzodiazepines was determined to be 16.7 mM MgCl2, providing the highest signal intensities at the lowest drug concentrations with limits of detection between 0.5 and 127 ng/mL. A supported liquid extraction technique was utilized as a rapid clean extraction for benzodiazepines from urine at a pH of 5.0, allowing for clean extraction with limits of detection between 6 and 640 ng/mL. It was shown that at this pH other drugs that are prevalent in urine samples can be removed providing the selective detection of the benzodiazepine of interest. ^ This technique has been shown to provide rapid (less than twenty minutes), sensitive, and specific detection of benzodiazepines at low concentrations in urine. It provides the forensic community with a sensitive and specific screening technique for the detection of benzodiazepines in drug facilitated assault cases.^

Development of a Surface-Enhanced Raman Spectroscopy Method for the Detection of Benzodiazepines in Urine

Benzodiazepines are among the most prescribed compounds for anti-anxiety and are present in many toxicological screens. These drugs are also prominent in the commission of drug facilitated sexual assaults due their effects on the central nervous system. Due to their potency, a low dose of these compounds is often administered to victims; therefore, the target detection limit for these compounds in biological samples is 10 ng/mL. Currently these compounds are predominantly analyzed using immunoassay techniques; however more specific screening methods are needed. The goal of this dissertation was to develop a rapid, specific screening technique for benzodiazepines in urine samples utilizing surface-enhanced Raman spectroscopy (SERS), which has previously been shown be capable of to detect trace quantities of pharmaceutical compounds in aqueous solutions. Surface enhanced Raman spectroscopy has the advantage of overcoming the low sensitivity and fluorescence effects seen with conventional Raman spectroscopy. The spectra are obtained by applying an analyte onto a SERS-active metal substrate such as colloidal metal particles. SERS signals can be further increased with the addition of aggregate solutions. These agents cause the nanoparticles to amass and form hot-spots which increase the signal intensity. In this work, the colloidal particles are spherical gold nanoparticles in aqueous solution with an average size of approximately 30 nm. The optimum aggregating agent for the detection of benzodiazepines was determined to be 16.7 mM MgCl2, providing the highest signal intensities at the lowest drug concentrations with limits of detection between 0.5 and 127 ng/mL. A supported liquid extraction technique was utilized as a rapid clean extraction for benzodiazepines from urine at a pH of 5.0, allowing for clean extraction with limits of detection between 6 and 640 ng/mL. It was shown that at this pH other drugs that are prevalent in urine samples can be removed providing the selective detection of the benzodiazepine of interest. This technique has been shown to provide rapid (less than twenty minutes), sensitive, and specific detection of benzodiazepines at low concentrations in urine. It provides the forensic community with a sensitive and specific screening technique for the detection of benzodiazepines in drug facilitated assault cases.

New Method for the Estimation of Viscosity of Pure and Mixtures of Ionic Liquids Based on the UNIFAC–VISCO Model

A modified UNIFAC–VISCO group contribution method was developed for the correlation and prediction of viscosity of ionic liquids as a function of temperature at 0.1 MPa. In this original approach, cations and anions were regarded as peculiar molecular groups. The significance of this approach comes from the ability to calculate the viscosity of mixtures of ionic liquids as well as pure ionic liquids. Binary interaction parameters for selected cations and anions were determined by fitting the experimental viscosity data available in literature for selected ionic liquids. The temperature dependence on the viscosity of the cations and anions were fitted to a Vogel–Fulcher–Tamman behavior. Binary interaction parameters and VFT type fitting parameters were then used to determine the viscosity of pure and mixtures of ionic liquids with different combinations of cations and anions to ensure the validity of the prediction method. Consequently, the viscosities of binary ionic liquid mixtures were then calculated by using this prediction method. In this work, the viscosity data of pure ionic liquids and of binary mixtures of ionic liquids are successfully calculated from 293.15 K to 363.15 K at 0.1 MPa. All calculated viscosity data showed excellent agreement with experimental data with a relative absolute average deviation lower than 1.7%.

New Method Based on the UNIFAC–VISCO Model for the Estimation of Ionic Liquids Viscosity Using the Experimental Data Recommended by Mathematical Gnostics

The viscosity of ionic liquids (ILs) has been modeled as a function of temperature and at atmospheric pressure using a new method based on the UNIFAC–VISCO method. This model extends the calculations previously reported by our group (see Zhao et al. J. Chem. Eng. Data 2016, 61, 2160–2169) which used 154 experimental viscosity data points of 25 ionic liquids for regression of a set of binary interaction parameters and ion Vogel–Fulcher–Tammann (VFT) parameters. Discrepancies in the experimental data of the same IL affect the quality of the correlation and thus the development of the predictive method. In this work, mathematical gnostics was used to analyze the experimental data from different sources and recommend one set of reliable data for each IL. These recommended data (totally 819 data points) for 70 ILs were correlated using this model to obtain an extended set of binary interaction parameters and ion VFT parameters, with a regression accuracy of 1.4%. In addition, 966 experimental viscosity data points for 11 binary mixtures of ILs were collected from literature to establish this model. All the binary data consist of 128 training data points used for the optimization of binary interaction parameters and 838 test data points used for the comparison of the pure evaluated values. The relative average absolute deviation (RAAD) for training and test is 2.9% and 3.9%, respectively.

Modelling and Verification of a Correction Factor to Evaluate the Efficiency of Solar Thermal Collectors with the Rapid Test Method

A new method for the evaluation of the efficiency of parabolic trough collectors, called Rapid Test Method, is investigated at the Solar Institut Jülich. The basic concept is to carry out measurements under stagnation conditions. This allows a fast and inexpensive process due to the fact that no working fluid is required. With this approach, the temperature reached by the inner wall of the receiver is assumed to be the stagnation temperature and hence the average temperature inside the collector. This leads to a systematic error which can be rectified through the introduction of a correction factor. A model of the collector is simulated with COMSOL Multipyisics to study the size of the correction factor depending on collector geometry and working conditions. The resulting values are compared with experimental data obtained at a test rig at the Solar Institut Jülich. These results do not match with the simulated ones. Consequentially, it was not pos-sible to verify the model. The reliability of both the model with COMSOL Multiphysics and of the measurements are analysed. The influence of the correction factor on the rapid test method is also studied, as well as the possibility of neglecting it by measuring the receiver’s inner wall temperature where it receives the least amount of solar rays. The last two chapters analyse the specific heat capacity as a function of pressure and tem-perature and present some considerations about the uncertainties on the efficiency curve obtained with the Rapid Test Method.

Average-case analysis of power consumption in embedded systems

Power efficiency is one of the most important constraints in the design of embedded systems since such systems are generally driven by batteries with limited energy budget or restricted power supply. In every embedded system, there are one or more processor cores to run the software and interact with the other hardware components of the system. The power consumption of the processor core(s) has an important impact on the total power dissipated in the system. Hence, the processor power optimization is crucial in satisfying the power consumption constraints, and developing low-power embedded systems. A key aspect of research in processor power optimization and management is “power estimation”. Having a fast and accurate method for processor power estimation at design time helps the designer to explore a large space of design possibilities, to make the optimal choices for developing a power efficient processor. Likewise, understanding the processor power dissipation behaviour of a specific software/application is the key for choosing appropriate algorithms in order to write power efficient software. Simulation-based methods for measuring the processor power achieve very high accuracy, but are available only late in the design process, and are often quite slow. Therefore, the need has arisen for faster, higher-level power prediction methods that allow the system designer to explore many alternatives for developing powerefficient hardware and software. The aim of this thesis is to present fast and high-level power models for the prediction of processor power consumption. Power predictability in this work is achieved in two ways: first, using a design method to develop power predictable circuits; second, analysing the power of the functions in the code which repeat during execution, then building the power model based on average number of repetitions. In the first case, a design method called Asynchronous Charge Sharing Logic (ACSL) is used to implement the Arithmetic Logic Unit (ALU) for the 8051 microcontroller. The ACSL circuits are power predictable due to the independency of their power consumption to the input data. Based on this property, a fast prediction method is presented to estimate the power of ALU by analysing the software program, and extracting the number of ALU-related instructions. This method achieves less than 1% error in power estimation and more than 100 times speedup in comparison to conventional simulation-based methods. In the second case, an average-case processor energy model is developed for the Insertion sort algorithm based on the number of comparisons that take place in the execution of the algorithm. The average number of comparisons is calculated using a high level methodology called MOdular Quantitative Analysis (MOQA). The parameters of the energy model are measured for the LEON3 processor core, but the model is general and can be used for any processor. The model has been validated through the power measurement experiments, and offers high accuracy and orders of magnitude speedup over the simulation-based method.

An approximate method for the solution of an influence function foil rolling model

Fleck and Johnson (Int. J. Mech. Sci. 29 (1987) 507) and Fleck et al. (Proc. Inst. Mech. Eng. 206 (1992) 119) have developed foil rolling models which allow for large deformations in the roll profile, including the possibility that the rolls flatten completely. However, these models require computationally expensive iterative solution techniques. A new approach to the approximate solution of the Fleck et al. (1992) Influence Function Model has been developed using both analytic and approximation techniques. The numerical difficulties arising from solving an integral equation in the flattened region have been reduced by applying an Inverse Hilbert Transform to get an analytic expression for the pressure. The method described in this paper is applicable to cases where there is or there is not a flat region.

Reducing the global burden of depression : population level analysis of intervention cost-effectiveness in 14 world regions

International evidence on the cost and effects of interventions for reducing the global burden of depression remain scarce. Aims: To estimate the population-level cost-effectiveness of evidence-based depression interventions and their contribution towards reducing current burden. Method: Primary-care-based depression interventions were modelled at the level of whole populations in 14 epidemiological subregions of the world. Total population-level costs (in international dollars or I$) and effectiveness (disability adjusted life years (DALYs) averted) were combined to form average and incremental cost-effectiveness ratios. Results: Evaluated interventions have the potential to reduce the current burden of depression by 10–30%. Pharmacotherapy with older antidepressant drugs, with or without proactive collaborative care, are currently more cost-effective strategies than those using newer antidepressants, particularly in lower-income subregions. Conclusions: Even in resource-poor regions, each DALYaverted by efficient depression treatments in primary care costs less than 1 year of average per capita income, making such interventions a cost-effective use of health resources. However, current levels of burden can only be reduced significantlyif there is a substantialincrease substantial increase intreatment coverage.