Synthesis of opiate derivatives : investigations into a key step from the manufacturing of buprenorphine and definitive preparation of degradation impurities related to naloxone

The subject of this thesis is the synthesis and impurity profiling of semi-synthetic opiates, namely buprenorphine and naloxone. Opiates are a class of naturally occurring narcotic analgesic drugs produced from the opium poppy Papaver somniferum, including morphine, codeine and thebaine. Semi-synthetic opiates are a class of drugs chemically derived from naturally occurring opiates; typically these are narcotic analgesics such as diacetylmorphine and buprenorphine. A final related class of drug, the opioids, are fully synthetic drugs such as fentanyl, designed to be structurally similar to opiates and elicit similar pharmacological effects. Whilst these drugs and a number of their analogues can be used as analgesics in a medical setting, a number of serious side effects such as addiction and respiratory depression limit their application and can lead to long term dependency for the patient. The narcotic effects of opium, morphine and diacetylmorphine (heroin) makes them attractive to recreational drug users, who often become addicted to and dependent upon them. These drugs are controlled through various legislations worldwide as potential drugs of abuse

Evaluating leadership's approach to implementing organizational change across the Naval Aviation Enterprise with a focus on the development of Fleet Readiness Centers

MBA Professional ReportNAVAIR is currently realigning its Aviation Maintenance infrastructure to fall under the overarching umbrella of the newly minted Naval Aviation Enterprise (NAE). This realignment will call for a new enterprise-wide strategy and structure. Hierarchies and relationships are being redefined throughout the enterprise resulting in entirely new organizational structures functionally equivalent to industryb2ss small business units. This realignment will result in the elimination of Intermediate level maintenance as it exists today and presents a myriad of challenges to the Fleet in the terms of achieving business efficiencies and employee relationship management. This MBA Project evaluates, by survey, how effectively the U. S. Navy and Marine Corps have managed the change effort as they continue to realign their Intermediate and Depot level units under the new FRC construct.http://archive.org/details/evaluatingleader1094510097US Navy (USN) authorApproved for public release; distribution is unlimited

Recalibrating the cosmic star formation history

The calibrations linking observed luminosities to the star formation rate depend on the assumed stellar population synthesis model, initial mass function, star formation and metal enrichment history, and whether reprocessing by dust and gas is included. Consequently the shape and normalisation of the inferred cosmic star formation history is sensitive to these assumptions. Using v2.2.1 of the Binary Population and Spectral Synthesis (\bpass) model we determine a new set of calibration coefficients for the ultraviolet, thermal-infrared, and, hydrogen recombination lines. These ultraviolet and thermal infrared coefficients are 0.15-0.2 dex higher than those widely utilised in the literature while the H$\alpha$ coefficient is $\sim 0.35$ dex larger. These differences arise in part due to the inclusion binary evolution pathways but predominantly reflect an extension in the IMF to 300 $M_{\odot}$ and a change in the choice of reference metallicity. We use these new coefficients to recalibrate the cosmic star formation history, and find improved agreement between the integrated cosmic star formation history and the in-situ measured stellar mass density as a function of redshift. However, these coefficients produce new tension between star formation rate densities inferred from the ultraviolet and thermal-infrared and those from H$\alpha$.Comment: 7 pages, 8 figures, accepted for publication in MNRA

Exploring the history of star formation in galaxies and its environmental dependence at high redshift

The first stars formed in the early universe and shortly after assembled into the first galaxies. Since then, galaxies have been subject to a variety of processes, both internal and external, that affect their ability to form stars. At low redshift, environment plays a large role in inhibiting star formation, however it is less clear what effect it has at high redshift. This is predominantly due to the difficulty of determining the nature of the high redshift environment from uncertain redshift measurements, and the small coverage of high redshift surveys leading to poor sampling of the cosmic variance. In this thesis I use a variety of numerical approaches to various aspects of this problem. In the first section I use a semi-analytic model to study the relationship between observed galaxy surface overdensity and the probability of coinciding with a protocluster, the pre-collapse progenitors of galaxy clusters, and make recommendations for optimum measurement apertures for their identification. In the second section I use a suite of hydrodynamic simulations of galaxy clusters, across a range of descendant halo masses, to study the galaxy evolution in their protocluster progenitors in detail. I characterise the star-forming sequence, studying it’s difference in protocluster and field environments, as well as within dense groups in the collapsing protocluster. In the final section I use a novel approach to estimate the star formation history of galaxies. Rather than studying the high redshift environment directly, I estimate when the stars in a low redshift galaxy were formed using population synthesis techniques. In this work I couple this with hydrodynamical simulations in order to provide more informative priors on the shape of the star formation history, which typically imposes strong biases on inferred properties, such as the total stellar mass, in more traditional approaches

Mapping Circumgalactic Medium Observations to Theory Using Machine Learning

We present a random forest framework for predicting circumgalactic medium (CGM) physical conditions from quasar absorption line observables, trained on a sample of Voigt profile-fit synthetic absorbers from the Simba cosmological simulation. Traditionally, extracting physical conditions from CGM absorber observations involves simplifying assumptions such as uniform single-phase clouds, but by using a cosmological simulation we bypass such assumptions to better capture the complex relationship between CGM observables and underlying gas conditions. We train random forest models on synthetic spectra for HI and selected metal lines around galaxies across a range of star formation rates, stellar masses, and impact parameters, to predict absorber overdensities, temperatures, and metallicities. The models reproduce the true values from Simba well, with normalised transverse standard deviations of $0.50-0.54$ dex in overdensity, $0.32-0.54$ dex in temperature, and $0.49-0.53$ dex in metallicity predicted from metal lines (not HI), across all ions. Examining the feature importance, the random forest indicates that the overdensity is most informed by the absorber column density, the temperature is driven by the line width, and the metallicity is most sensitive to the specific star formation rate. Alternatively examining feature importance by removing one observable at a time, the overdensity and metallicity appear to be more driven by the impact parameter. We introduce a normalising flow approach in order to ensure the scatter in the true physical conditions is accurately spanned by the network. The trained models are available online.Comment: 16 pages, 14 figures. Accepted for publication in MNRA