Planning for Digital Transformation: Implications for Institutional Enterprise Architecture

Enterprise Architecture (EA) and its management have received considerable attention from the academic and practical audience. Despite a very wide treatment on EA, research on EA in the academic sector has not received similar attention till date. There is also a growing interest on digital transformation with evidences suggesting that academic institutions have increased their investment into digital technology which prompts a need to reflect on how this technology affects these institutions and the educational processes. In the dissertation, we propose to link these concerns based on three research issues, through which we explore the objectives an academic institute wants to achieve in planning for digital transformation and the necessary institutional readiness factors of a digital enterprise architecture, and then propose a design framework to support the endeavour. The dissertation employs both qualitative and quantitative research methodologies. Implications for research and practice are also delineated at the end

Dynamics of Implementation of Mitigating Measures to Reduce CO2 Emissions from Commercial Aviation

Increasing demand for air transportation and growing environmental concerns motivate the need to implement measures to reduce CO2 emissions from aviation. Case studies of historical changes in the aviation industry have shown that the implementation of changes generally followed S-curves with relatively long time–constants. This research analyzed the diffusion characteristics of a portfolio of CO2 emission mitigating measures and their relative contribution to cumulative system wide improvements. A literature review identified 41 unique measures, including (1) technological improvements, (2) operational improvements, and (3) the use of alternative fuels. It was found that several operational changes can be implemented in the short term but are unlikely to significantly reduce CO2 emissions. Technology retrofits and some operational changes can be implemented in the medium term. 2nd and 3rd generation biofuels can significantly reduce carbon emissions but are likely to have long diffusion times and may not be available in sufficient quantities to the aviation industry. Technology measures in the form of next generation aircraft have the highest CO2 reduction potential, but only in the long term due to slow fleet turnover. An Aircraft Diffusion Dynamic Model (ADDM) was developed using System Dynamics modeling techniques to understand how the fleet efficiency will be influenced by the entry of various generations of aircraft with different levels of emissions performance. The model was used to evaluate effects of several future potential scenarios on the US narrow body jet fleet as well as their sensitivity to S-curve parameters. Results from the model showed that strategies that emphasize the early entry into service of available technology, as opposed to waiting and delaying entry for more fuel- efficient technology, have greater potential to improve fleet fuel-burn performance. Also, strategies that incentivize early retirement of older aircraft have marginal potential for reducing fuel burn. Future demand scenarios showed that the infusion of fuel-efficient aircraft alone is unlikely to reduce emissions below 2006 levels. Instead, a portfolio of measures that also include demand reduction mechanisms, operational improvements, and adoption of alternative fuels will be required in order to limit the growth of CO2 emissions from aviation.This work was supported by the MIT/Masdar Institute of Science and Technology under grant number Mubadala Development Co. Agreement 12/1/06

Dynamics of implementation of mitigating measures to reduce CO₂ emissions from commercial aviation

Thesis (S.M. in Technology and Policy)--Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2010.Cataloged from PDF version of thesis.Includes bibliographical references.Increasing demand for air transportation and growing environmental concerns motivate the need to implement measures to reduce CO₂ emissions from aviation. Case studies of historical changes in the aviation industry have shown that the implementation of changes generally followed S-curves with relatively long time-constants. This research analyzed the diffusion characteristics of a portfolio of CO₂ emission mitigating measures and their relative contribution to cumulative system wide improvements. A literature review identified 41 unique measures, including (1) technological improvements, (2) operational improvements, and (3) the use of alternative fuels. It was found that several operational changes can be implemented in the short term but are unlikely to significantly reduce CO₂ emissions. Technology retrofits and some operational changes can be implemented in the medium term. 2 nd and 3rd generation biofuels can significantly reduce carbon emissions but are likely to have long diffusion times and may not be available in sufficient quantities to the aviation industry. Technology measures in the form of next generation aircraft have the highest CO₂ reduction potential, but only in the long term due to slow fleet turnover. An Aircraft Diffusion Dynamic Model (ADDM) was developed using System Dynamics modeling techniques to understand how the fleet efficiency will be influenced by the entry of various generations of aircraft with different levels of emissions performance. The model was used to evaluate effects of several future potential scenarios on the US narrow body jet fleet as well as their sensitivity to S-curve parameters. Results from the model showed that strategies that emphasize the early entry into service of available technology, as opposed to waiting and delaying entry for more fuel efficient technology, have greater potential to improve fleet fuel-burn performance. Also, strategies that incentivize early retirement of older aircraft have marginal potential for reducing fuel burn. Future demand scenarios showed that the infusion of fuel-efficient aircraft alone is unlikely to reduce emissions below 2006 levels. Instead, a portfolio of measures that also include demand reduction mechanisms, operational improvements, and adoption of alternative fuels will be required in order to limit the growth of CO₂ emissions from aviation.by Rahul Kar.S.M.in Technology and Polic

Morpho-kinematic and photoionization models of the multipolar structures in planetary nebula NGC 6572

We have studied the planetary nebula (PN) NGC 6572 through 3D morpho-kinematic and photoionization modelling. The 3D morphology is reconstructed from the Hubble Space Telescope images in different narrow band filters and position-velocity spectra. The PN have a multipolar morphology consisting of highly collimated outflows. The nebular image show signatures of multiple lobes within a spiral-ring-like structure. The multipolar structure is modelled with two bipolar shells (axes ratios 5.5:1 and 3:1), having closed and opened lobes, respectively. A toroidal structure (radius:height = 1:3) surrounds the shells at the waist. The toroidal axis aligns with the major axes of the bipolar shells. Our study reveals the nebula to have a history of collimated polar outflow perpendicular to a higher density equatorial wind with the outflow seemingly have episodes of changing direction of ejection. We construct a photoionization model of NGC 6572 using the deep optical spectra obtained at the 2 m Himalayan Chandra Telescope. For the photoionization model, we configure the input shell geometry in form of a highly bipolar nebular shell with reference to the 3D morphology. Our photoionization model satisfactorily reproduces the observables. We estimate the nebular elemental abundances, and important characteristic parameters of the central star (e.g., effective temperature, luminosity, gravity, mass, etc.) and the nebula (e.g., hydrogen density profiles, radii, etc.). We compare the resolved H$\beta$, [O III], and [N II] profiles in the 4.2 m William Herschel Telescope with that from the photoionization model and find a good characteristic match.Comment: 14 pages, 10 figures, 6 table

On the Origin of Metallicity and Stability of the Metastable Phase in Chemically Exfoliated MoS2_2

Chemical exfoliation of MoS$_2$ via Li-intercalation route has led to many desirable properties and spectacular applications due to the presence of a metastable state in addition to the stable H phase. However, the nature of the specific metastable phase formed, and its basic charge conduction properties have remained controversial. Using spatially resolved Raman spectroscopy (~1 micrometer resolution) and photoelectron spectroscopy (~120 nm resolution), we probe such chemically exfoliated MoS$_2$ samples in comparison to a mechanically exfoliated H phase sample and confirm that the dominant metastable state formed by this approach is a distorted T' state with a small semiconducting gap. Investigating two such samples with different extents of Li residues present, we establish that Li+ ions, not only help to exfoliate MoS$_2$ into few layer samples, but also contribute to enhancing the relative stability of the metastable state as well as dope the system with electrons, giving rise to a lightly doped small bandgap system with the T' structure, responsible for its spectacular properties.Comment: 34 pages, Main manuscript + Supplementary Materia

Predicting the effect of statins on cancer risk using genetic variants from a Mendelian randomization study in the UK Biobank

Funder: National Institute for Health Research; FundRef: http://dx.doi.org/10.13039/501100000272Laboratory studies have suggested oncogenic roles of lipids, as well as anticarcinogenic effects of statins. Here we assess the potential effect of statin therapy on cancer risk using evidence from human genetics. We obtained associations of lipid-related genetic variants with the risk of overall and 22 site-specific cancers for 367,703 individuals in the UK Biobank. In total, 75,037 individuals had a cancer event. Variants in the HMGCR gene region, which represent proxies for statin treatment, were associated with overall cancer risk (odds ratio [OR] per one standard deviation decrease in low-density lipoprotein [LDL] cholesterol 0.76, 95% confidence interval [CI] 0.65–0.88, p=0.0003) but variants in gene regions representing alternative lipid-lowering treatment targets (PCSK9, LDLR, NPC1L1, APOC3, LPL) were not. Genetically predicted LDL-cholesterol was not associated with overall cancer risk (OR per standard deviation increase 1.01, 95% CI 0.98–1.05, p=0.50). Our results predict that statins reduce cancer risk but other lipid-lowering treatments do not. This suggests that statins reduce cancer risk through a cholesterol independent pathway