Finance investor versus corporate management :who defines technology strategy?

D.B.A. ThesisBackground : The contours of today’s corporate landscape are strongly shaped by finance investors who own businesses, either in part or fully. This thesis analyses the processes of cooperation and interaction between businesses and finance investors regarding technology strategy. In addition to the question of the direct influence finance investors might have on technology strategy, indirect influences are also investigated. An evaluation of the finance investors’ capabilities and responsibilities is carried out in parallel to understand what “real potential” investors have to influence the technology strategy of companies in their portfolio. This work addresses a gap in current existing literature and research in this area as the elements of direct involvement of investors in technology strategy of firms they own are not yet studied in depth. Methodology : A purely qualitative approach of case study research was chosen as the method most suitable for obtaining the desired insights. A pilot project involving two cases, confirmed the efficacy of the semi-structured questionnaire for conducting in-depth interviews. A further 12 case studies were carried out with companies that were selected following defined criteria to ensure the reproducibility of results. The final work has a fundament of 14 cases, consisting of 43 interviews with finance investors and portfolio company representatives. Conclusion : Finance investors consider the technology strategy of their portfolio companies to be vital as it impacts the market value of the company and financial results. Besides the financial impact of technology strategy, finance investors show no specific interest in technology strategy nor are they likely to have major expertise in this area. Responsibility for driving technology strategy is clearly in the hands of the corporate managers. But finance investors do exert strong indirect influence by controlling and steering budgets, investments, etc. and also through their consultancy role in the organisational development process

Hardware-aware block size tailoring on adaptive spacetree grids for shallow water waves.

Spacetrees are a popular formalism to describe dynamically adaptive Cartesian grids. Though they directly yield an adaptive spatial discretisation, i.e. a mesh, it is often more efficient to augment them by regular Cartesian blocks embedded into the spacetree leaves. This facilitates stencil kernels working efficiently on homogeneous data chunks. The choice of a proper block size, however, is delicate. While large block sizes foster simple loop parallelism, vectorisation, and lead to branch-free compute kernels, they bring along disadvantages. Large blocks restrict the granularity of adaptivity and hence increase the memory footprint and lower the numerical-accuracy-per-byte efficiency. Large block sizes also reduce the block-level concurrency that can be used for dynamic load balancing. In the present paper, we therefore propose a spacetree-block coupling that can dynamically tailor the block size to the compute characteristics. For that purpose, we allow different block sizes per spacetree node. Groups of blocks of the same size are identied automatically throughout the simulation iterations, and a predictor function triggers the replacement of these blocks by one huge, regularly rened block. This predictor can pick up hardware characteristics while the dynamic adaptivity of the fine grid mesh is not constrained. We study such characteristics with a state-of-the-art shallow water solver and examine proper block size choices on AMD Bulldozer and Intel Sandy Bridge processors

Block Fusion on Dynamically Adaptive Spacetree Grids for Shallow Water Waves

Spacetrees are a popular formalism to describe dynamically adaptive Cartesian grids. Even though they directly yield a mesh, it is often computationally reasonable to embed regular Cartesian blocks into their leaves. This promotes stencils working on homogeneous data chunks. The choice of a proper block size is sensitive. While large block sizes foster loop parallelism and vectorisation, they restrict the adaptivity's granularity and hence increase the memory footprint and lower the numerical accuracy per byte. In the present paper, we therefore use a multiscale spacetree-block coupling admitting blocks on all spacetree nodes. We propose to find sets of blocks on the finest scale throughout the simulation and to replace them by fused big blocks. Such a replacement strategy can pick up hardware characteristics, i.e. which block size yields the highest throughput, while the dynamic adaptivity of the fine grid mesh is not constrained—applications can work with fine granular blocks. We study the fusion with a state-of-the-art shallow water solver at hands of an Intel Sandy Bridge and a Xeon Phi processor where we anticipate their reaction to selected block optimisation and vectorisation

Hardware-aware block size tailoring on adaptive spacetree grids for shallow water waves

Spacetrees are a popular formalism to describe dynamically adaptive Cartesian grids. Though they directly yield an adaptive spatial discretisation, i.e. a mesh, it is often more efficient to augment them by regular Cartesian blocks embedded into the spacetree leaves. This facilitates stencil kernels working efficiently on homogeneous data chunks. The choice of a proper block size, however, is delicate. While large block sizes foster simple loop parallelism, vectorisation, and lead to branch-free compute kernels, they bring along disadvantages. Large blocks restrict the granularity of adaptivity and hence increase the memory footprint and lower the numerical-accuracy-per-byte efficiency. Large block sizes also reduce the block-level concurrency that can be used for dynamic load balancing. In the present paper, we therefore propose a spacetree-block coupling that can dynamically tailor the block size to the compute characteristics. For that purpose, we allow different block sizes per spacetree node. Groups of blocks of the same size are identied automatically throughout the simulation iterations, and a predictor function triggers the replacement of these blocks by one huge, regularly rened block. This predictor can pick up hardware characteristics while the dynamic adaptivity of the fine grid mesh is not constrained. We study such characteristics with a state-of-the-art shallow water solver and examine proper block size choices on AMD Bulldozer and Intel Sandy Bridge processors

The Simrad EK60 echosounder dataset from the Malaspina circumnavigation

The Malaspina Expedition was funded by the Spanish Ministry of Economy and Competitiveness through the Malaspina 2010 expedition project (Consolider-Ingenio 2010, CSD2008-00077), the Fundación BBVA, CSIC, the Spanish Institute of Oceanography, AZTI Foundation, the universities of Granada, Cadiz, Basque Country and Barcelona and the King Abdullah University of Science and Technology. Data have been made available through the EU funded project SUMMER (H2020-BG-2018-2, proposal number: 817806-2).We provide the raw acoustic data collected from the R/V Hesperides during the global Malaspina 2010 Spanish Circumnavigation Expedition (14th December 2010, Cádiz-14th July 2011, Cartagena) using a Simrad EK60 scientific echosounder operating at 38 and 120 kHz. The cruise was divided into seven legs: leg 1 (14th December 2010, Cádiz-13th January 2011, Rio de Janeiro), leg 2 (17th January 2011, Rio de Janeiro-6th February 2011, Cape Town), leg 3 (11th February 2011, Cape Town-13th March 2011, Perth), leg 4 (17th March 2011, Perth-30th March 2011, Sydney), leg 5 (16th April 2011, Auckland-8th May 2011, Honolulu), leg 6 (13th May 2011, Honolulu-10th June 2011, Cartagena de Indias) and leg 7 (19th June 2011, Cartagena de Indias-14th July 2011, Cartagena). The echosounder was calibrated at the start of the expedition and calibration parameters were updated in the data acquisition software (ER60) i.e., the logged raw data are calibrated. We also provide a data summary of the acoustic data in the form of post-processed products.Publisher PDFPeer reviewe

Literatur-Rundschau

Hans-Rüdiger Schwab (Hg.): Eigensinn und Bindung. Katholische deutsche Intellektuelle im 20. Jahrhundert (Walter Hömberg)Joachim Westerbarkey (Hg.): EndZeitKommunikation. Diskurse der Temporalität (Ramin J. Mohammadzadeh-Nowzad)Jim McDonnell: Managing Your Reputation. A Guide to Crisis Management for Church Communicators (Ferdinand Oertel)Walter Hömberg: Lektor im Buchverlag. Repräsentative Studie über einen unbekannten Kommunikationsberuf (Reinhard Wittmann)Marie Luise Kiefer: Journalismus und Medien als Institutionen (Alexander Godulla)Markus Will: Wertorientiertes Kommunikationsmanagement (Roland Burkart)Jürgen Kniep: „Keine Jugendfreigabe!“ Filmzensur in Westdeutschland 1949–1990 (Peter Hasenberg)Walter Hömberg / Daniela Hahn / Timon B. Schaffer (Hg.): Kommunikation und Verständigung. Theorie – Empirie – Praxis. Festschrift für Roland Burkart; Tobias Eberwein / Daniel Müller (Hg.): Journalismus und Öffentlichkeitsarbeit. Eine Profession und ihr gesellschaftlicher Auftrag. Festschrift für Horst Pöttker (Romy Fröhlich)

Limited life cycle and cost assessment for the bioconversion of lignin-derived aromatics into adipic acid

Lignin is an abundant and heterogeneous waste byproduct of the cellulosic industry, which has the potential of being transformed into valuable biochemicals via microbial fermentation. In this study, we applied a fast-pyrolysis process using softwood lignin resulting in a two-phase bio-oil containing monomeric and oligomeric aromatics without syringol. We demonstrated that an additional hydrodeoxygenation step within the process leads to an enhanced thermochemical conversion of guaiacol into catechol and phenol. After steam bath distillation, Pseudomonas putida KT2440-BN6 achieved a percent yield of cis, cis-muconic acid of up to 95 mol% from catechol derived from the aqueous phase. We next established a downstream process for purifying cis, cis-muconic acid (39.9 g/L) produced in a 42.5 L fermenter using glucose and benzoate as carbon substrates. On the basis of the obtained values for each unit operation of the empirical processes, we next performed a limited life cycle and cost analysis of an integrated biotechnological and chemical process for producing adipic acid and then compared it with the conventional petrochemical route. The simulated scenarios estimate that by attaining a mixture of catechol, phenol, cresol, and guaiacol (1:0.34:0.18:0, mol ratio), a titer of 62.5 (g/L) cis, cis-muconic acid in the bioreactor, and a controlled cooling of pyrolysis gases to concentrate monomeric aromatics in the aqueous phase, the bio-based route results in a reduction of CO2 -eq emission by 58% and energy demand by 23% with a contribution margin for the aqueous phase of up to 88.05 euro/ton. We conclude that the bio-based production of adipic acid from softwood lignins brings environmental benefits over the petrochemical procedure and is cost-effective at an industrial scale. Further research is essential to achieve the proposed cis, cis-muconic acid yield from true lignin-derived aromatics using whole-cell biocatalysts

Effects of diabetes and hypertension on macrophage infiltration and matrix expansion in the rat kidney

BACKGROUND: In experimental models of diabetes mellitus, aggravation of renal injury by concomitant hypertension has been described. Inflammatory mechanisms contribute to renal damage in both diseases. We investigated whether hypertension and diabetes mellitus act synergistically to induce macrophage infiltration and matrix expansion in the kidney. METHODS: Insulin-dependent diabetes mellitus was induced by streptozotocin injections to hypertensive mRen2-transgenic rats (TGR) and normotensive Sprague-Dawley control rats. Quantitative immunohistochemical examination of kidney tissue sections was used to measure macrophage infiltration and matrix expansion. The expression of MCP-1, Osteopontin, RANTES, ICAM-1 and VCAM-1 was evaluated by real-time RT-PCR. The localization of MCP-1 was studied by immunohistochemistry. RESULTS: Macrophage infiltration was present in the kidney of normotensive diabetic rats. Hypertensive rats exhibited a more marked infiltration of macrophages, regardless of whether diabetes was present or not. Gene expression of ICAM-1, VCAM-1 and RANTES was unaltered whereas Osteopontin and MCP-1 were induced by hypertension. Immunoreactive MCP-1 was slightly increased in diabetic rat kidney podocytes, and more markedly increased in hypertensive animals. Glomerular matrix accumulation was induced by diabetes and hypertension to a similar degree, and was highest in hypertensive, diabetic animals. CONCLUSION: Diabetes mellitus caused a mild, and angiotensin-dependent hypertension a more marked infiltration of macrophages in the kidney. Combination of both diseases led to additive effects on matrix expansion but not on inflammation. Hypertension appears to be a much stronger stimulus for inflammation of the kidney than STZ diabetes, at least in mRen2-transgenic rats