Targeting B-alanyl aminopeptidase in pseudomonas aeruginosa

The aim of this study was to perform homology modeling of the β-alanyl aminopeptidase sequence of Pseudomonas aeruginosa, and to use the model obtained in the design, synthesis and testing of inhibitors in order to evaluate the cellular role of this enzyme. A 3D model of β-alanyl aminopeptidase was derived and evaluated using Maestro (version 9.3, Schrödinger). Virtual database screening was then conducted in order to discover inhibitors which would be predicted to bind to the active site of the enzyme. Twenty-seven hit compounds with the highest docking scores were synthesized, purified and the in vitro antimicrobial activities for these synthesized agents, against both Gram-negative and Gram-positive strains were evaluated using both disc diffusion and micro-dilution assays. Under disc diffusion assay, N-(2-aminoethyl)benzenesulfonamide trifluoroacetate salt 1a, N-(2-aminoethyl)-4-methylbenzenesulfonamide trifluoroacetate salt 1b, N-(2-aminoethyl)-4-chlorophenylsulfonamide trifluoroacetate 1c, N-(2-aminoethyl)-4-nitrophenylsulfonamide trifluoroacetate 1d, N-(2-aminoethyl)-2-nitrophenylsulfonamide trifluoroacetate 1e, and 3-amino-N-{2-(2-nitrophenylsulfonamido)ethyl}propanamide trifluoroacetate 8e showed the greatest anti-pseudomonal activity. Based on disc diffusion assay, against Gram positive and Gram negative strains, 3-Amino-N-{2-(2-nitrophenylsulfonamido)ethyl}propanamide trifluoroacetate 8e had the greatest selectivity, followed by N-(2-aminoethyl)-4-chlorophenylsulfonamide trifluoroacetate 1c and N-(2-aminoethyl)-4-methylbenzenesulfonamide trifluoroacetate salt 1b. Additionally, compound N-(2-aminoethyl)-4-nitrophenylsulfonamide trifluoroacetate 1d showed the greatest anti-pseudomonal effeact, with an MIC of 78.125 µg/ml. This effect was not specific as it also had the greatest effect against B. subtilis and P. vulgaris, with an MIC of 156.25 µg/ml for both species. These sulfonamides (and their β-alanyl derivatives) represent new leads in the search for antimicrobial agents for the treatment of P. aeruginosa. Although compounds 8e, 1c, and 1b have selective effects upon PAO1, their anti-pseudomonal activities are not sufficient for the development of potent anti-pseudomonal agents, suggesting that β-alanyl aminopeptidase has no physiological role in the growth of Pseudomonas aeruginosa. The results obtained in this work do, however, support further work to enhance the activity of these non-classical sulphonamides, as well as proteomics and protein purification in order to isolate and study β-alanyl aminopeptidase crystallographicall

The characterisation of international stock markets using signal processing techniques.

Investors are constantly asking whether beating the market on a consistent basis is possible. There is probably no definitive answer to the question of how to make a guaranteed profit (or return) because index prices can fluctuate at any time. The aim of most investors, therefore, is to predict the stock market return and the volatility, (a measure of investment nsk) and this requires an understanding of stock market behaviour. In this research, diierent techniques, both previously existing and newly developed here (and associated specifically with the discrete wavelet transform (DWT)), are applied to study the behav~our of global stock market indices We consider type of memory, mterrelationships between stock markets, market reaction to crashes and events, and the best indicators of market types (short-term, long-term or mixed). The unifylng aim is to provide a baseline set of characteristic features which typify behaviors of given market type Principal remarks include the fact that the DWT, alone or with other methods, can succeed in providing an in-depth view of these data, in particular when confronted with non-stationary, non-normal and noisy characteristics. The approach provides an important method for the aualysis and interpretation of financial market time series. Our principal findings on volatility measures, moreover, show strong evidence of long-term memory effects, which are not evident in the returns themselves. Emerging and Mature markets are found to deal differently with crashes and events with the latter taking a shorter time to recover from crises on average, compared to the former. Furthermore, we conclude that this binary classification is too simple and stock markets can now be demonstrated to fall into more than two groups, with the designation L'emerging" ("developing") and "mature" ("developed") proving imprecise. Additionally, and in the context of the global market, from Chapter 5, we note that international co-movements and volatility (or nsk) have increased markedly since the middle of the 20th century and that cloclnuzse transmtssion between global stock markets is observed, i.e from Asaa to h o p e to Amerzca back to Asia). The combination of ~nternadl ependencies and external influences provide the impacts for stock market volatility. The ultimate goal, of course, would be to anticipate these Impacts to be able to make the rlght investment decision

Apples and oranges: the difference between the reaction of the emerging and mature markets to crashes

We study here the behavior of the eigenvalues of the covariance matrices of returns for emerging and mature markets at times of crises. Our results appear to indicate that mature markets respond to crashes differently to emerging ones and that emerging markets take longer to recover than mature markets. In addition, the results appear to indicate that the second largest eigenvalue gives additional information on market movement and that a study of the behavior of the other eigenvalues may provide insight on crash dynamics

Interrelationships among international stock market indices: Europe, Asia and the Americas

In this paper, we investigate the price interdependence between seven international stock markets, namely Irish, UK, Portuguese, US, Brazilian, Japanese and Hong Kong, using a new testing method, based on the wavelet transform to reconstruct the data series, as suggested by Lee (2002). We find evidence of intra-European (Irish, UK and Portuguese) market co-movements with the US market also weakly influencing the Irish market. We also find co-movement between the US and Brazilian markets and similar intra-Asian co-movements (Japanese and Hong Kong). Finally, we conclude that the circle of impact is that of the European markets (Irish, UK and Portuguese) on both American markets (US and Brazilian), with these in turn impacting on the Asian markets (Japanese and Hong Kong) which in turn influence the European markets. In summary, we find evidence for intra-continental relationships and an increase in importance of international spillover effects since the mid 1990’s, while the importance of historical transmissions has decreased since the beginning of this century

Interdependence between emerging and major markets

In this paper, we investigate the price spillover effects among two developed markets, (the US and the UK ), and two developing markets, (Irish and Portuguese), using a new testing method suggested by Lee (2002). We find that there are interrelationships between any two of the Irish, the UK and Portuguese markets and that the co-movements between the emerging markets and the US are statistically significant but weak. We also found that the US market is slightly influenced by the UK but not vice versa

The Impact of Investment in Accounting Information Systems on Business Performance: The Case of the Libyan Commercial Banks

This study aimed to explore investment in accounting information system (AIS) in the commercial banks in Libya. It focuses on the extent and nature of AIS investment in the Libyan commercial banks, resultant changes in business processes and the significance of training and up-skilling of the workforce in delivering systems benefits. Following an initial literature review, the research reviewed AIS investment in all Libyan commercial banks and established top line profiles of nine of the thirteen existing banks (the other four being close to merger with, or acquisition by, other banks). Three banks were selected for detailed case study analysis, representing a cross-section in terms of size, staff, age profile, and ownership of the banks. Three methods were adopted to collect data - individual questionnaires with key bank personnel, semi-structured interviews and review and analysis of pertinent bank documents. The study researched and analysed the recent investment in advanced IT in the case study banks, where AIS packaged software and communications infrastructure had been implemented. The banks that use developed global systems have more efficient and effective systems than the banks that use local systems, and in general there are no adequate policies or plans in place for training and up-skilling of staff using these new systems. The study also found that investment in AIS and associated technological infrastructure had impacted on all main business processes, bringing about significant process improvement in some cases. Contributions to knowledge include a qualitative assessment of AIS in Libyan banks, which has not been done before, and the identification of some of the benefits and problems that result from major systems deployment. The study has also shown that models formulated for application in the developed world can be adapted and applied to assess information systems in a developing world commercial environment

Cooperative spectrum sensing: performance analysis and algorithms

The employment of cognitive (intelligent) radios presents an opportunity to efficiently use the scarce spectrum with the condition that it causes a minimal disturbance to the primary user. So the cognitive or secondary users use spectrum sensing to detect the presence of primary user. In this thesis, different aspects related to spectrum sensing and cognitive radio performance are theoretically studied for the discussion and in most cases, closedform expressions are derived. Simulations results are also provided to verify the derivations. Firstly, robust spectrum sensing techniques are proposed considering some realistic conditions, such as carrier frequency offset (CFO) and phase noise (PN). These techniques are called the block-coherent detector (N2 -BLCD), the secondorder matched filter-I (SOMF-I) and the second-order matched filter-II (SOMF-II). The effect of CFO on N2 -BLCD and SOMF-I is evaluated theoretically and by simulation for SOMF-II. However, the effect of PN is only evaluated by simulation for all proposed techniques. Secondly, the detection performance of an energy detector (ED) is analytically investigated over a Nakagami-m frequency-selective (NFS) channel. Thirdly, the energy efficiency aspect of cooperative spectrum sensing is addressed, whereby the energy expenditure is reduced when secondary users report their test statistics to the fusion center (FC). To alleviate the energy consumption overhead, a censored selection combining based power censoring (CSCPC) is proposed. The accomplishment of energy saving is conducted by not sending the test statistic that does not contain robust information or it requires a lot of transmit power. The detection performance of the CSCPC is analytically derived using stochastic geometry tools and verified by simulation. Simulation results show that that the CSCPC technique can reduce the energy consumption compared with the conventional techniques while a detection performance distortion remains negligible. Finally, an analytical evaluation for the cognitive radio performance is presented while taking into consideration realistic issues, such as noise uncertainty (NU) and NFS channel. In the evaluation, sensing-throughput tradeoff is used as an examination metric. The results illustrate the NU badly affects the performance, but the performance may improve when the number of multipath increases

Wavelet multiscale analysis for hedge funds: scaling and strategies

The wide acceptance of Hedge Funds by Institutional Investors and Pension Funds has led to an explosive growth in assets under management. These investors are drawn to Hedge Funds due to the seemingly low correlation with traditional investments and the attractive returns. The correlations and market risk (the Beta in the Capital Asset Pricing Model) of Hedge Funds are generally calculated using monthly returns data, which may produce misleading results as Hedge Funds often hold illiquid exchange-traded securities or difficult to price over-the- counter securities. In this paper, the Maximum Overlap Discrete Wavelet Transform (MODWT) is applied to measure the scaling properties of Hedge Fund correlation and market risk with respect to the S&P 500. It is found that the level of correlation and market risk varies greatly according to the strategy studied and the time scale examined. Finally, the effects of scaling properties on the risk profile of a portfolio made up of Hedge Funds is studied using correlation matrices calculated over different time horizons

The Acceleration of Digital Maturity during the COVID-19 Pandemic in the Retail Industry in Sri Lanka

The recent saying is that COVID-19 pandemic had the most exerted influence in the world after the Second World War. Developing countries, such as Sri Lanka, are no exception. The pandemic brought various digital initiatives to cope with limitations that lead to a much-accelerated digital transformation. The retail sector continued to undergo digital transformation in Sri Lanka with a particular focus on advancing the customer experience by digitally creating, delivering, and capturing value. We interviewed top management in various areas in the retail industry in Sri Lanka and followed a hybrid research methodology for analysis combining the grounded theory and the framework-based approach. We described the gap between the focus of the literature’s digital maturity models in the past 10 years and the top management’s needs throughout the accelerated digital transformation during the pandemic as follows: the difference in the percentage of the expression of common dimensions in digital transformation and maturity models and the percentage of the expression of dimensions in the managers’ interviews. Our findings call for the attention of academic research to dedicate more attention to further integrate more dimensions related to technology, cloud and data, digital marketing, and products into the digital transformation and maturity models