Vapour-liquid equilibrium studies at atmospheric to moderate pressures

A study of vapour-liquid equilibria is presented together with current developments. The theory of vapour-liquid equilibria is discussed. Both experimental and prediction methods for obtaining vapour-liquid equilibria data are critically reviewed. The development of a new family of equilibrium stills to measure experimental VLE data from sub-atmosphere to 35 bar pressure is described. Existing experimental techniques are reviewed, to highlight the needs for these new apparati and their major attributes. Details are provided of how apparatus may be further improved and how computer control may be implemented. To provide a rigorous test of the apparatus the stills have been commissioned using acetic acid-water mixture at one atmosphere pressure. A Barker-type consistency test computer program, which allows for association in both phases has been applied to the data generated and clearly shows that the stills produce data of a very high quality. Two high quality data sets, for the mixture acetone-chloroform, have been generated at one atmosphere and 64.3oC. These data are used to investigate the ability of the new novel technique, based on molecular parameters, to predict VLE data for highly polar mixtures. Eight, vapour-liquid equilibrium data sets have been produced for the cyclohexane-ethanol mixture at one atmosphere, 2, 4, 6, 8 and 11 bar, 90.9oC and 132.8oC. These data sets have been tested for thermodynamic consistency using a Barker-type fitting package and shown to be of high quality. The data have been used to investigate the dependence of UNIQUAC parameters with temperature. The data have in addition been used to compare directly the performance of the predictive methods - Original UNIFAC, a modified version of UNIFAC, and the new novel technique, based on molecular parameters developed from generalised London's potential (GLP) theory.

Predictive gene lists for breast cancer prognosis: a topographic visualisation study

Background: The controversy surrounding the non-uniqueness of predictive gene lists (PGL) of small selected subsets of genes from very large potential candidates as available in DNA microarray experiments is now widely acknowledged 1. Many of these studies have focused on constructing discriminative semi-parametric models and as such are also subject to the issue of random correlations of sparse model selection in high dimensional spaces. In this work we outline a different approach based around an unsupervised patient-specific nonlinear topographic projection in predictive gene lists. Methods: We construct nonlinear topographic projection maps based on inter-patient gene-list relative dissimilarities. The Neuroscale, the Stochastic Neighbor Embedding(SNE) and the Locally Linear Embedding(LLE) techniques have been used to construct two-dimensional projective visualisation plots of 70 dimensional PGLs per patient, classifiers are also constructed to identify the prognosis indicator of each patient using the resulting projections from those visualisation techniques and investigate whether a-posteriori two prognosis groups are separable on the evidence of the gene lists. A literature-proposed predictive gene list for breast cancer is benchmarked against a separate gene list using the above methods. Generalisation ability is investigated by using the mapping capability of Neuroscale to visualise the follow-up study, but based on the projections derived from the original dataset. Results: The results indicate that small subsets of patient-specific PGLs have insufficient prognostic dissimilarity to permit a distinction between two prognosis patients. Uncertainty and diversity across multiple gene expressions prevents unambiguous or even confident patient grouping. Comparative projections across different PGLs provide similar results. Conclusion: The random correlation effect to an arbitrary outcome induced by small subset selection from very high dimensional interrelated gene expression profiles leads to an outcome with associated uncertainty. This continuum and uncertainty precludes any attempts at constructing discriminative classifiers. However a patient's gene expression profile could possibly be used in treatment planning, based on knowledge of other patients' responses. We conclude that many of the patients involved in such medical studies are intrinsically unclassifiable on the basis of provided PGL evidence. This additional category of 'unclassifiable' should be accommodated within medical decision support systems if serious errors and unnecessary adjuvant therapy are to be avoided.

Selectivity and timing performance of UK investment trusts

This study examines the selectivity and timing performance of 218 UK investment trusts over the period July 1981 to June 2009. We estimate the Treynor and Mazuy (1966) and Henriksson and Merton (1981) models augmented with the size, value, and momentum factors, either under the OLS method adjusted with the Newey-West procedure or under the GARCH(1,1)-in-mean method following the specification of Glosten et al. (1993; hereafter GJR-GARCH-M). We find that the OLS method provides little evidence in favour of the selectivity and timing ability, consistent with previous studies. Interestingly, the GJR-GARCH-M method reverses this result, showing some relatively strong evidence on favourable selectivity ability, particularly for international funds, as well as favourable timing ability, particularly for domestic funds. We conclude that the GJR-GARCH-M method performs better in evaluating fund performance compared with the OLS method and the non-parametric approach, as it essentially accounts for the time-varying characteristics of factor loadings and hence obtains more reliable results, in particular, when the high frequency data, such as the daily returns, are used in the analysis. Our results are robust to various in-sample and out-of-sample tests and have valuable implications for practitioners in making their asset allocation decisions across different fund styles. © 2012 Elsevier B.V.

Neural network DEA for measuring the efficiency of mutual funds

Efficiency in the mutual fund (MF), is one of the issues that has attracted many investors in countries with advanced financial market for many years. Due to the need for frequent study of MF's efficiency in short-term periods, investors need a method that not only has high accuracy, but also high speed. Data envelopment analysis (DEA) is proven to be one of the most widely used methods in the measurement of the efficiency and productivity of decision making units (DMUs). DEA for a large dataset with many inputs/outputs would require huge computer resources in terms of memory and CPU time. This paper uses neural network back-ropagation DEA in measurement of mutual funds efficiency and shows the requirements, in the proposed method, for computer memory and CPU time are far less than that needed by conventional DEA methods and can therefore be a useful tool in measuring the efficiency of a large set of MFs. Copyright © 2014 Inderscience Enterprises Ltd.

Quantifying the complexity of chaos in multibasin multidimensional dynamics of molecular systems

The simulated classical dynamics of a small molecule exhibiting self-organizing behavior via a fast transition between two states is analyzed by calculation of the statistical complexity of the system. It is shown that the complexity of molecular descriptors such as atom coordinates and dihedral angles have different values before and after the transition. This provides a new tool to identify metastable states during molecular self-organization. The highly concerted collective motion of the molecule is revealed. Low-dimensional subspaces dynamics is found sensitive to the processes in the whole, high-dimensional phase space of the system. © 2004 Wiley Periodicals, Inc.

Estimation of transportation battery second life for use in electricity grid systems

This paper presents research from part of a larger project focusing on the potential development of commercial opportunities for the reuse of batteries on the electricity grid system, subsequent to their primary use in low and ultra-low carbon vehicles, and investigating the life cycle issues surrounding the batteries. The work has three main areas; examination of electric vehicle fleet data in detail to investigate usage in first life. Batteries that have passed through a battery recycler at the end of their first life have been tested within the laboratory to confirm the general assumption that remaining capacity of 80% after use in transportation is a reasonable assumption as a basis for second-life applications. The third aspect of the paper is an investigation of the equivalent usage for three different second-life applications based on connection to the electricity grid. Additionally, the paper estimates the time to cell failure of the batteries within their second-life application to estimate lifespan for use within commercial investigations. © 2014 IEEE.

All-analogue real-time broadband filter bank multicarrier optical communications system

This paper studies the key aspects of an optical link which transmits a broadband microwave filter bank multicarrier (FBMC) signal. The study is presented in the context of creating an all-analogue real-time multigigabit orthogonal frequency division multiplexing electro-optical transceiver for short range and high-capacity data center networks. Passive microwave filters are used to perform the pulse shaping of the bit streams, allowing an orthogonal transmission without the necessity of digital signal processing (DSP). Accordingly, a cyclic prefix that would cause a reduction in the net data rate is not required. An experiment consisting of three orthogonally spaced 2.7 Gbaud quadrature phase shift keyed subchannels demonstrates that the spectral efficiency of traditional DSP-less subcarrier multiplexed links can be potentially doubled. A sensitivity of -29.5 dBm is achieved in a 1-km link.

Handwritten and machine-printed text discrimination using a template matching approach

We propose a novel template matching approach for the discrimination of handwritten and machine-printed text. We first pre-process the scanned document images by performing denoising, circles/lines exclusion and word-block level segmentation. We then align and match characters in a flexible sized gallery with the segmented regions, using parallelised normalised cross-correlation. The experimental results over the Pattern Recognition & Image Analysis Research Lab-Natural History Museum (PRImA-NHM) dataset show remarkably high robustness of the algorithm in classifying cluttered, occluded and noisy samples, in addition to those with significant high missing data. The algorithm, which gives 84.0% classification rate with false positive rate 0.16 over the dataset, does not require training samples and generates compelling results as opposed to the training-based approaches, which have used the same benchmark.

Issues for Managing Tourism Information

The need for a high quality tourism database is well known. For example, planners and managers need high quality data for budgeting, forecasting, planning marketing and advertising strategies, and staffing. Thus the concepts of quality and need are intertwined to pose a problem to the tourism professional, be they private sector or public sector employees. One could argue that collaboration by public and private sector tourism professionals could provide the best sources and uses of high quality tourism data. This discussion proposes just such a collaboration and a detailed methodology for operationalizing this arrangement.

Assessment of the occurrence and potential risks of antibiotics and their metabolites in South Florida waters using liquid chromatography tandem mass spectrometry

An automated on-line SPE-LC-MS/MS method was developed for the quantitation of multiple classes of antibiotics in environmental waters. High sensitivity in the low ng/L range was accomplished by using large volume injections with 10-mL of sample. Positive confirmation of analytes was achieved using two selected reaction monitoring (SRM) transitions per antibiotic and quantitation was performed using an internal standard approach. Samples were extracted using online solid phase extraction, then using column switching technique; extracted samples were immediately passed through liquid chromatography and analyzed by tandem mass spectrometry. The total run time per each sample was 20 min. The statistically calculated method detection limits for various environmental samples were between 1.2 and 63 ng/L. Furthermore, the method was validated in terms of precision, accuracy and linearity. ^ The developed analytical methodology was used to measure the occurrence of antibiotics in reclaimed waters (n=56), surface waters (n=53), ground waters (n=8) and drinking waters (n=54) collected from different parts of South Florida. In reclaimed waters, the most frequently detected antibiotics were nalidixic acid, erythromycin, clarithromycin, azithromycin trimethoprim, sulfamethoxazole and ofloxacin (19.3-604.9 ng/L). Detection of antibiotics in reclaimed waters indicates that they can't be completely removed by conventional wastewater treatment process. Furthermore, the average mass loads of antibiotics released into the local environment through reclaimed water were estimated as 0.248 Kg/day. Among the surface waters samples, Miami River (reaching up to 580 ng/L) and Black Creek canal (up to 124 ng/L) showed highest concentrations of antibiotics. No traces of antibiotics were found in ground waters. On the other hand, erythromycin (monitored as anhydro erythromycin) was detected in 82% of the drinking water samples (n.d-66 ng/L). The developed approach is suitable for both research and monitoring applications.^ Major metabolites of antibiotics in reclaimed wates were identified and quantified using high resolution benchtop Q-Exactive orbitrap mass spectrometer. A phase I metabolite of erythromycin was tentatively identified in full scan based on accurate mass measurement. Using extracted ion chromatogram (XIC), high resolution data-dependent MS/MS spectra and metabolic profiling software the metabolite was identified as desmethyl anhydro erythromycin with molecular formula C36H63NO12 and m/z 702.4423. The molar concentration of the metabolite to erythromycin was in the order of 13 %. To my knowledge, this is the first known report on this metabolite in reclaimed water. Another compound acetyl-sulfamethoxazole, a phase II metabolite of sulfamethoxazole was also identified in reclaimed water and mole fraction of the metabolite represent 36 %, of the cumulative sulfamethoxazole concentration. The results were illustrating the importance to include metabolites also in the routine analysis to obtain a mass balance for better understanding of the occurrence, fate and distribution of antibiotics in the environment. ^ Finally, all the antibiotics detected in reclaimed and surface waters were investigated to assess the potential risk to the aquatic organisms. The surface water antibiotic concentrations that represented the real time exposure conditions revealed that the macrolide antibiotics, erythromycin, clarithromycin and tylosin along with quinolone antibiotic, ciprofloxacin were suspected to induce high toxicity to aquatic biota. Preliminary results showing that, among the antibiotic groups tested, macrolides posed the highest ecological threat, and therefore, they may need to be further evaluated with, long-term exposure studies considering bioaccumulation factors and more number of species selected. Overall, the occurrence of antibiotics in aquatic environment is posing an ecological health concern.^

WiFi and LTE Coexistence in the Unlicensed Spectrum

Today, smart-phones have revolutionized wireless communication industry towards an era of mobile data. To cater for the ever increasing data traffic demand, it is of utmost importance to have more spectrum resources whereby sharing under-utilized spectrum bands is an effective solution. In particular, the 4G broadband Long Term Evolution (LTE) technology and its foreseen 5G successor will benefit immensely if their operation can be extended to the under-utilized unlicensed spectrum. In this thesis, first we analyze WiFi 802.11n and LTE coexistence performance in the unlicensed spectrum considering multi-layer cell layouts through system level simulations. We consider a time division duplexing (TDD)-LTE system with an FTP traffic model for performance evaluation. Simulation results show that WiFi performance is more vulnerable to LTE interference, while LTE performance is degraded only slightly. Based on the initial findings, we propose a Q-Learning based dynamic duty cycle selection technique for configuring LTE transmission gaps, so that a satisfactory throughput is maintained both for LTE and WiFi systems. Simulation results show that the proposed approach can enhance the overall capacity performance by 19% and WiFi capacity performance by 77%, hence enabling effective coexistence of LTE and WiFi systems in the unlicensed band.

The role of group activity participation in depression among institutionalized elderly

The role of group activity participation in depression among a group of residents (N=65), age 80 and older, in a nursing home was examined using the framework of Roy's Adaptation Theory and Nolen-Hoeksema's Response Style Theory of Depression. Roy views depression as a maladaptation. Nolen-Hoeksema views group activity participation as a therapeutic distraction to break depressed moods and thus allow for positive adaptation. This study utilized data from medical records, group activity attendance, and self-report questionnaires. Demographic distributions were computed and correlational statistics were performed between subjects' participation and their degree of depression, pain experience, functional status, presence of social support, and perception of benefits. Results show a negative correlation between frequency of participation and Geriatric Depression Scale score (GDS). The wide range of measured frequencies among low GDS-scored subjects suggests that less depressed individuals exercise more freedom of choice to participate than those who are more depressed. Significant finding show a positive correlation of group activity participation with functional status in terms of ambulation. Data shows that the experience of pain was not a significant deterrent to participation. The presence of social support from the staff and family did not increase participation. However there is a lesser GDS score among subjects who had recent family/friends visit suggesting a positive role of family in decreasing depression. These results are significant not only for optimizing group therapeutic effects but also for understanding basic human and environmental correlates of depression. Study limitations are pointed out and recommendations are presented.

Modelagem da degradação de fenol em efluentes aquosos através do processo de foto-fenton

Advanced Oxidation Processes (AOP) are techniques involving the formation of hydroxyl radical (HO•) with high organic matter oxidation rate. These processes application in industry have been increasing due to their capacity of degrading recalcitrant substances that cannot be completely removed by traditional processes of effluent treatment. In the present work, phenol degrading by photo-Fenton process based on addition of H2O2, Fe2+ and luminous radiation was studied. An experimental design was developed to analyze the effect of phenol, H2O2 and Fe2+ concentration on the fraction of total organic carbon (TOC) degraded. The experiments were performed in a batch photochemical parabolic reactor with 1.5 L of capacity. Samples of the reactional medium were collected at different reaction times and analyzed in a TOC measurement instrument from Shimadzu (TOC-VWP). The results showed a negative effect of phenol concentration and a positive effect of the two other variables in the TOC degraded fraction. A statistical analysis of the experimental design showed that the hydrogen peroxide concentration was the most influent variable in the TOC degraded fraction at 45 minutes and generated a model with R² = 0.82, which predicted the experimental data with low precision. The Visual Basic for Application (VBA) tool was used to generate a neural networks model and a photochemical database. The aforementioned model presented R² = 0.96 and precisely predicted the response data used for testing. The results found indicate the possible application of the developed tool for industry, mainly for its simplicity, low cost and easy access to the program.

Modelagem da degradação de fenol em efluentes aquosos através do processo de foto-fenton

Advanced Oxidation Processes (AOP) are techniques involving the formation of hydroxyl radical (HO•) with high organic matter oxidation rate. These processes application in industry have been increasing due to their capacity of degrading recalcitrant substances that cannot be completely removed by traditional processes of effluent treatment. In the present work, phenol degrading by photo-Fenton process based on addition of H2O2, Fe2+ and luminous radiation was studied. An experimental design was developed to analyze the effect of phenol, H2O2 and Fe2+ concentration on the fraction of total organic carbon (TOC) degraded. The experiments were performed in a batch photochemical parabolic reactor with 1.5 L of capacity. Samples of the reactional medium were collected at different reaction times and analyzed in a TOC measurement instrument from Shimadzu (TOC-VWP). The results showed a negative effect of phenol concentration and a positive effect of the two other variables in the TOC degraded fraction. A statistical analysis of the experimental design showed that the hydrogen peroxide concentration was the most influent variable in the TOC degraded fraction at 45 minutes and generated a model with R² = 0.82, which predicted the experimental data with low precision. The Visual Basic for Application (VBA) tool was used to generate a neural networks model and a photochemical database. The aforementioned model presented R² = 0.96 and precisely predicted the response data used for testing. The results found indicate the possible application of the developed tool for industry, mainly for its simplicity, low cost and easy access to the program.

IRAS 00183-7111: ALMA and X-ray view of an ultra luminous infrared galaxy

The aim of this Thesis work is to study the multi-frequency properties of the Ultra Luminous Infrared Galaxy (ULIRG) IRAS 00183-7111 (I00183) at z = 0.327, connecting ALMA sub-mm/mm observations with those at high energies in order to place constraints on the properties of its central power source and verify whether the gas traced by the CO may be responsible for the obscuration observed in X-rays. I00183 was selected from the so-called Spoon diagnostic diagram (Spoon et al. 2007) for mid-infrared spectra of infrared galaxies based on the equivalent width of the 6.2 μm Polycyclic Aromatic Hydrocarbon (PAH) emission feature versus the 9.7 μm silicate strength. Such features are a powerful tool to investigate the contribution of star formation and AGN activity in this class of objects. I00183 was selected from the top-left region of the plot where the most obscured sources, characterized by a strong Si absorption feature, are located. To link the sub-mm/mm to the X-ray properties of I00183, ALMA archival Cycle 0 data in Band 3 (87 GHz) and Band 6 (270 GHz) have been calibrated and analyzed, using CASA software. ALMA Cycle 0 was the Early Science program for which data reprocessing is strongly suggested. The main work of this Thesis consisted in reprocessing raw data to provide an improvement with respect to the available archival products and results, which were obtained using standard procedures. The high-energy data consists of Chandra, XMM-Newton and NuSTAR observations which provide a broad coverage of the spectrum in the energy range 0.5 − 30 keV. Chandra and XMM archival data were used, with an exposure time of 22 and 22.2 ks, respectively; their reduction was carried out using CIAO and SAS software. The 100 ks NuSTAR are still private and the spectra were obtained by courtesy of the PI (K. Iwasawa). A detailed spectral analysis was done using XSPEC software; the spectral shape was reproduced starting from simple phenomenological models, and then more physical models were introduced to account for the complex mechanisms that involve this source. In Chapter 1, an overview of the scientific background is discussed, with a focus on the target, I00183, and the Spoon diagnostic diagram, from which it was originally selected. In Chapter 2, the basic principles of interferometry are briefly introduced, with a description of the calibration theory applied to interferometric observations. In Chapter 3, ALMA and its capabilities, both current and future, are shown, explaining also the complex structure of the ALMA archive. In Chapter 4, the calibration of ALMA data is presented and discussed, showing also the obtained imaging products. In Chapter 5, the analysis and discussion of the main results obtained from ALMA data is presented. In Chapter 6, the X-ray observations, data reduction and spectral analysis are reported, with a brief introduction to the basic principle of X-ray astronomy and the instruments from which the observations were carried out. Finally, the overall work is summarized, with particular emphasis on the main obtained results and the possible future perspectives.