Designing business models of cloud platforms

Cloud computing and its three facets (Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS)) are terms that denote new developments in the software industry. In particular, PaaS solutions, also referred to as cloud platforms, are changing the way software is being produced, distributed, consumed, and priced. Software vendors have started considering cloud platforms as a strategic option but are battling to redefine their offerings to embrace PaaS. In contrast to SaaS and IaaS, PaaS allows for value co-creation with partners to develop complementary components and applications. It thus requires multisided business models that bring together two or more distinct customer segments. Understanding how to design PaaS business models to establish a flourishing ecosystem is crucial for software vendors. This doctoral thesis aims to address this issue in three interrelated research parts. First, based on case study research, the thesis provides a deeper understanding of current PaaS business models and their evolution. Second, it analyses and simulates consumers' preferences regarding PaaS business models, using a conjoint approach to find out what determines the choice of cloud platforms. Finally, building on the previous research outcomes, the third part introduces a design theory for the emerging class of PaaS business models, which is grounded on an extensive action design research study with a large European software vendor. Understanding PaaS business models from a market as well as a consumer perspective will, together with the design theory, inform and guide decision makers in their business model innovation plans. It also closes gaps in the research related to PaaS business model design and more generally related to platform business models.

Additive functions in boolean models of gene regulatory network modules.

Gene-on-gene regulations are key components of every living organism. Dynamical abstract models of genetic regulatory networks help explain the genome's evolvability and robustness. These properties can be attributed to the structural topology of the graph formed by genes, as vertices, and regulatory interactions, as edges. Moreover, the actual gene interaction of each gene is believed to play a key role in the stability of the structure. With advances in biology, some effort was deployed to develop update functions in Boolean models that include recent knowledge. We combine real-life gene interaction networks with novel update functions in a Boolean model. We use two sub-networks of biological organisms, the yeast cell-cycle and the mouse embryonic stem cell, as topological support for our system. On these structures, we substitute the original random update functions by a novel threshold-based dynamic function in which the promoting and repressing effect of each interaction is considered. We use a third real-life regulatory network, along with its inferred Boolean update functions to validate the proposed update function. Results of this validation hint to increased biological plausibility of the threshold-based function. To investigate the dynamical behavior of this new model, we visualized the phase transition between order and chaos into the critical regime using Derrida plots. We complement the qualitative nature of Derrida plots with an alternative measure, the criticality distance, that also allows to discriminate between regimes in a quantitative way. Simulation on both real-life genetic regulatory networks show that there exists a set of parameters that allows the systems to operate in the critical region. This new model includes experimentally derived biological information and recent discoveries, which makes it potentially useful to guide experimental research. The update function confers additional realism to the model, while reducing the complexity and solution space, thus making it easier to investigate.

Stability of cascade networks via fluid models

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Study and implementation of some quantitative trading models

Quantitative or algorithmic trading is the automatization of investments decisions obeying a fixed or dynamic sets of rules to determine trading orders. It has increasingly made its way up to 70% of the trading volume of one of the biggest financial markets such as the New York Stock Exchange (NYSE). However, there is not a signi cant amount of academic literature devoted to it due to the private nature of investment banks and hedge funds. This projects aims to review the literature and discuss the models available in a subject that publications are scarce and infrequently. We review the basic and fundamental mathematical concepts needed for modeling financial markets such as: stochastic processes, stochastic integration and basic models for prices and spreads dynamics necessary for building quantitative strategies. We also contrast these models with real market data with minutely sampling frequency from the Dow Jones Industrial Average (DJIA). Quantitative strategies try to exploit two types of behavior: trend following or mean reversion. The former is grouped in the so-called technical models and the later in the so-called pairs trading. Technical models have been discarded by financial theoreticians but we show that they can be properly cast into a well defined scientific predictor if the signal generated by them pass the test of being a Markov time. That is, we can tell if the signal has occurred or not by examining the information up to the current time; or more technically, if the event is F_t-measurable. On the other hand the concept of pairs trading or market neutral strategy is fairly simple. However it can be cast in a variety of mathematical models ranging from a method based on a simple euclidean distance, in a co-integration framework or involving stochastic differential equations such as the well-known Ornstein-Uhlenbeck mean reversal ODE and its variations. A model for forecasting any economic or financial magnitude could be properly defined with scientific rigor but it could also lack of any economical value and be considered useless from a practical point of view. This is why this project could not be complete without a backtesting of the mentioned strategies. Conducting a useful and realistic backtesting is by no means a trivial exercise since the \laws" that govern financial markets are constantly evolving in time. This is the reason because we make emphasis in the calibration process of the strategies' parameters to adapt the given market conditions. We find out that the parameters from technical models are more volatile than their counterpart form market neutral strategies and calibration must be done in a high-frequency sampling manner to constantly track the currently market situation. As a whole, the goal of this project is to provide an overview of a quantitative approach to investment reviewing basic strategies and illustrating them by means of a back-testing with real financial market data. The sources of the data used in this project are Bloomberg for intraday time series and Yahoo! for daily prices. All numeric computations and graphics used and shown in this project were implemented in MATLAB^R scratch from scratch as a part of this thesis. No other mathematical or statistical software was used.

Modelling world investment markets using threshold conditional correlation models

In this paper we propose a parsimonious regime-switching approach to model the correlations between assets, the threshold conditional correlation (TCC) model. This method allows the dynamics of the correlations to change from one state (or regime) to another as a function of observable transition variables. Our model is similar in spirit to Silvennoinen and Teräsvirta (2009) and Pelletier (2006) but with the appealing feature that it does not suffer from the course of dimensionality. In particular, estimation of the parameters of the TCC involves a simple grid search procedure. In addition, it is easy to guarantee a positive definite correlation matrix because the TCC estimator is given by the sample correlation matrix, which is positive definite by construction. The methodology is illustrated by evaluating the behaviour of international equities, govenrment bonds and major exchange rates, first separately and then jointly. We also test and allow for different parts in the correlation matrix to be governed by different transition variables. For this, we estimate a multi-threshold TCC specification. Further, we evaluate the economic performance of the TCC model against a constant conditional correlation (CCC) estimator using a Diebold-Mariano type test. We conclude that threshold correlation modelling gives rise to a significant reduction in portfolio´s variance.

Estratègies de teràpia gènica per a neuropatia diabètica

L'objectiu del projecte consisteix en desenvolupar estratègies de teràpia gènica per al tractament de la neuropatia diabètica. Per a la teràpia gènica és necessària la utilització de vectors per tal d'introduir el material genètic exogen en les cèl•lules diana. En aquest projecte s'utilitzen vectors derivats de virus adenoassociats i es fan estudis de tropisme de diferents serotips de vectors administrant-los per diferents vies. D’aquesta manera es pot escollir quin és el millor vector i la millor via d'administració per a cada cas, i en el cas d'aquest projecte, per a tractar les cèl•lules afectades en la neuropatia diabètica. La neuropatia diabètica és una complicació de la diabetis per a la qual no hi ha cap tractament. Afecta les cèl•lules del sistema nerviós perifèric (neurones sensorials, neurones motores i cèl•lules de Schwann) i és la causa la major part de les amputacions d'extremitats inferiors. En aquest projecte es pretén estudiar quines són les possibles causes del desenvolupament de la neuropatia diabètica analitzant canvis a nivell de l'expressió gènica en models de ratolins diabètics i també en els models in vitro dissenyats per al projecte. Posteriorment es vol proposar un tractament de teràpia gènica mitjançant els resultats dels estudis de tropisme dels vectors virals i dels estudis d'expressió gènica dels models de diabetis.

Preinfarction angina prior to first myocardial infarction does not influence long-term prognosis: a retrospective study with subgroup analysis in elderly and diabetic patients.

BACKGROUND AND HYPOTHESIS Although prodromal angina occurring shortly before an acute myocardial infarction (MI) has protective effects against in-hospital complications, this effect has not been well documented after initial hospitalization, especially in older or diabetic patients. We examined whether angina 1 week before a first MI provides protection in these patients. METHODS A total of 290 consecutive patients, 143 elderly (>64 years of age) and 147 adults (<65 years of age), 68 of whom were diabetic (23.4%) and 222 nondiabetic (76.6%), were examined to assess the effect of preceding angina on long-term prognosis (56 months) after initial hospitalization for a first MI. RESULTS No significant differences were found in long-term complications after initial hospitalization in these adult and elderly patients according to whether or not they had prodromal angina (44.4% with angina vs 45.4% without in adults; 45.5% vs 58% in elderly, P < 0.2). Nor were differences found according to their diabetic status (61.5% with angina vs 72.7% without in diabetics; 37.3% vs 38.3% in nondiabetics; P = 0.4). CONCLUSION The occurrence of angina 1 week before a first MI does not confer long-term protection against cardiovascular complications after initial hospitalization in adult or elderly patients, whether or not they have diabetes.

Identification of factors associated with diagnostic error in primary care.

BACKGROUND Missed, delayed or incorrect diagnoses are considered to be diagnostic errors. The aim of this paper is to describe the methodology of a study to analyse cognitive aspects of the process by which primary care (PC) physicians diagnose dyspnoea. It examines the possible links between the use of heuristics, suboptimal cognitive acts and diagnostic errors, using Reason's taxonomy of human error (slips, lapses, mistakes and violations). The influence of situational factors (professional experience, perceived overwork and fatigue) is also analysed. METHODS Cohort study of new episodes of dyspnoea in patients receiving care from family physicians and residents at PC centres in Granada (Spain). With an initial expected diagnostic error rate of 20%, and a sampling error of 3%, 384 episodes of dyspnoea are calculated to be required. In addition to filling out the electronic medical record of the patients attended, each physician fills out 2 specially designed questionnaires about the diagnostic process performed in each case of dyspnoea. The first questionnaire includes questions on the physician's initial diagnostic impression, the 3 most likely diagnoses (in order of likelihood), and the diagnosis reached after the initial medical history and physical examination. It also includes items on the physicians' perceived overwork and fatigue during patient care. The second questionnaire records the confirmed diagnosis once it is reached. The complete diagnostic process is peer-reviewed to identify and classify the diagnostic errors. The possible use of heuristics of representativeness, availability, and anchoring and adjustment in each diagnostic process is also analysed. Each audit is reviewed with the physician responsible for the diagnostic process. Finally, logistic regression models are used to determine if there are differences in the diagnostic error variables based on the heuristics identified. DISCUSSION This work sets out a new approach to studying the diagnostic decision-making process in PC, taking advantage of new technologies which allow immediate recording of the decision-making process.

Construcción y validación del cuestionario G_Clinic para medir la satisfacción laboral en profesionales de enfermería de las unidades de gestión clínica.

BACKGROUND Job satisfaction of nurses is a determinant factor in the quality and organizational adaptation of clinical management models in the current socio-economic context. The aim of this study was to construct and validate a questionnaire to measure job satisfaction of nurses in the Clinical Management Units in the Andalusian Public Health System. METHODS Clinimetric and cross-sectional study with a sample of 314 nurses of two university hospitals from Seville. Nurses were surveyed in 2011, from March to June. We used the Font Roja questionnaire adapted to our study variables. We performed analyses of correlations, reliability and construct validity, using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) to test the a priori model. RESULTS The end questionnaire consists of 10 items, whose internal consistency was 0.75, with a percentage of variance explaining of 63.67%. CFA confirmed 4 dimensions (work environment, work relationships, motivation, and recognition): significant χ2 (p < .001); χ2/gl = 2.013; GFI= 0.958, RMR = 0.055 y RMSEA = 0.057; AGFI = 0.927, NFI = 0.878, TLI = 0.902, CFI =0.933 e IFI = 0.935; AIC = 132.486 y ECVI = 0.423. CONCLUSION This new questionnaire (G_Clinic) improves clinimetric values of the Font Roja questionnaire, because it reduces the number of items, improves the reliability of the dimensions, increases the value of variance explained, and allows knowing job satisfaction of nurses in clinical managementt.

Large-scale analysis of orthologs and paralogs under covarion-like and constant-but-different models of amino acid evolution.

Functional divergence between homologous proteins is expected to affect amino acid sequences in two main ways, which can be considered as proxies of biochemical divergence: a "covarion-like" pattern of correlated changes in evolutionary rates, and switches in conserved residues ("conserved but different"). Although these patterns have been used in case studies, a large-scale analysis is needed to estimate their frequency and distribution. We use a phylogenomic framework of animal genes to answer three questions: 1) What is the prevalence of such patterns? 2) Can we link such patterns at the amino acid level with selection inferred at the codon level? 3) Are patterns different between paralogs and orthologs? We find that covarion-like patterns are more frequently detected than "constant but different," but that only the latter are correlated with signal for positive selection. Finally, there is no obvious difference in patterns between orthologs and paralogs.

Reaching for the Holy Grail: insights from infection/cure models on the prospects for vaccines for Trypanosoma cruziinfection

Prevention of Trypanosoma cruzi infection in mammals likely depends on either prevention of the invading trypomastigotes from infecting host cells or the rapid recognition and killing of the newly infected cells byT. cruzi-specific T cells. We show here that multiple rounds of infection and cure (by drug therapy) fails to protect mice from reinfection, despite the generation of potent T cell responses. This disappointing result is similar to that obtained with many other vaccine protocols used in attempts to protect animals from T. cruziinfection. We have previously shown that immune recognition ofT. cruziinfection is significantly delayed both at the systemic level and at the level of the infected host cell. The systemic delay appears to be the result of a stealth infection process that fails to trigger substantial innate recognition mechanisms while the delay at the cellular level is related to the immunodominance of highly variable gene family proteins, in particular those of the trans-sialidase family. Here we discuss how these previous studies and the new findings herein impact our thoughts on the potential of prophylactic vaccination to serve a productive role in the prevention of T. cruziinfection and Chagas disease.

The role of nonhematopoietic MHC class II expression in immune responses and tolerance

Si les rôles fonctionnels de diverses cellules immunitaires infiltrant des tissus enflammés sont assez bien compris, par contre, étonnamment, on connaît bien moins la capacité des cellules non hématopoïétiques résidant dans des tissus, à moduler l'activité biologique des cellules immunitaires immigrantes, et donc le résultat de la réponse immunitaire. La présentation des antigènes, dans le contexte des molécules du CMH de classe II (CMHII) à la surface des cellules présentatrices d'antigènes (CPA) professionnelles à une sous- population de lymphocytes T, est cruciale pour le développement des réponses immunitaires protectives spécifiques de l'antigène. En général, l'expression de CMHII est réservée aux CPAs. Toutefois, au cours des pathologies inflammatoires spécifiques d'organe, telles que l'auto-immunité ou la maladie inflammatoire de l'intestin, l'expression de CMHII est également induite par la cytokine interféron (IFN)-y sur des cellules non hématopoïétiques qui résident dans des tissus enflammés. Les conséquences de ce phénomène sont encore peu comprises. Dans cette étude, nous avons utilisé une souche de souris génétiquement modifiées, qui n'a pas la capacité d'induire l'expression de CMHII sur les cellules non hématopoïétiques, mais a maintenu la régulation normale d'expression de CMHII sur les cellules hématopoïétiques. Nous avons appliqué ces souris à différents modèles d'inflammation intestinale et à un modèle de maladie qui imite la maladie auto-immune de l'inflammation du muscle cardiaque (myocardite) chez l'homme. Nous avons pu montrer que, au cours de l'inflammation intestinale, l'expression du CMHII nonhématopoïétique, ou encore l'expression du CMHII par les cellules épithéliales de l'intestin, confère une protection contre la maladie, en réduisant les cellules immunitaires inflammatoires et en augmentant les cellules Τ régulatrices anti-inflammatoires. Ces résultats pourraient expliquer l'échec des traitements d'anti-IFN-γ dans les maladies intestinales inflammatoires chez l'homme. En revanche, dans la myocardite auto-immune, nos résultats indiquent que la présentation d'antigènes par les cellules non hématopoïétiques du coeur est nécessaire pour l'apparition de la pathologie cardiaque, comme nos souris sont résistantes à la maladie. Toutefois, cela n'est pas dû à un défaut d'activation des lymphocytes T, car les lymphocytes Τ des souris mutantes sont parfaitement capables de promouvoir la maladie après le transfert adoptif dans des animaux de type naturel. Nos résultats suggèrent que, durant les maladies inflammatoires spécifiques d'organe, la présentation d'antigène par des cellules non hématopoïétiques module et contribue au résultat de la réponse immunitaire d'une manière opposée, conférant soit la protection contre la maladie ou sa promotion. Nos résultats pourraient ouvrir la voie à des thérapies qui prennent en compte la contribution de la présentation d'antigènes par les cellules non hématopoïétiques, au cours des maladies inflammatoires spécifiques d'organe. - Les molécules du CMH de classe II (CMHII) sont fondamentales pour la présentation des antigènes aux lymphocytes Τ CD4+, car elles permettent le développement des réponses immunitaires spécifiques de l'antigène. Il est largement admis que l'expression de CMHII est réservée aux cellules présentatrices d'antigènes (CPA). Cependant, dans des conditions inflammatoires, l'expression de CMHII est en principe également induite par l'interféron (IFN)-y sur les cellules non hématopoïétiques, telles que les cellules épithéliales et les cardiomyocytes. Une controverse existe jusqu'à présent au sujet de la fonction de cette présentation d'antigènes non professionnelle, pour savoir si elle favorise la tolérance ou l'immunité dépendante des lymphocytes Τ in vivo. Pour répondre à cette question, nous avons testé des souris qui ne sont pas capables d'induire l'expression du CMHII sur les cellules non hématopoïétiques (souris PIV-/- K14 CIITA Tg) parmi différents modèles murins de pathologies inflammatoires, à savoir les modèles de vaccination pour induire des réponses spécifiques d'antigènes des lymphocytes B, plusieurs modèles de colite et un modèle de myocardite auto-immune expérimental (EAM). Pour cela, nous avons administré à ces souris un modèle de colite atténuée, induite par une infection chronique à Helicobacter hepaticus et par l'administration d'anticorps monoclonaux bloquant le récepteur de l'interleukine (IL)-10 (anti-IL-10R). Dans ce système, nous avons pu observer que l'expression abrogée de CMHII a aggravé la colite bactérienne, soit par les cellules non hématopoïétiques, soit exclusivement par les cellules épithéliales intestinales (CEI) dans un autre modèle murin (souris plV_fl/fl vil-Cre Tg). Ce phénotype du côlon a été associé à une augmentation des fréquences de cellules immunitaires innées, de lymphocytes Th1 CD4+, et d'expression des cytokines et de chimiokines pro-inflammatoires, y compris l'IFN-γ. Notamment, l'expression défectueuse de CMHII non hématopoïétique a également réduit les cellules Τ régulatrices (Treg) Forkhead box P3 (FoxP3)+, sans influencer les fréquences des cellules innées lymphoïdes et des cellules Th17. Ces résultats suggèrent un rôle tolérogène de CEIs CMHII+ qui contribue à l'homéostasie immunitaire intestinale. En revanche, dans le modèle d'EAM, les souris ayant subi une ablation de CMHII non hématopoïétique étaient résistantes à l'induction de la maladie, alors que la progression de la pathologie cardiaque, dans les souris de type naturel ou hétérozygotes, a été accompagnée par une régulation positive de l'expression de CMHII du myocarde. Cependant, l'inflammation cardiaque pourrait être transférée de manière adoptive depuis des souris amorcées PIV-/- K14 CIITA Tg vers des souris de type naturel, indiquant l'absence de défaut intrinsèque d'amorçage des cellules T CD4+ dans notre modèle de souris. Ces observations impliquent un rôle à jouer pour des cellules CMHII+ non hématopoïétiques résidentes du coeur, dans la promotion active de ΙΈΑΜ. En conclusion, nos résultats, provenant de diverses pathologies inflammatoires spécifiques d'organes, suggèrent un rôle complexe et divergent, soit tolérogène, soit immunogène/ pathologique, pour l'expression de CMHII non hématopoïétique au cours des pathologies inflammatoires. L'expression non professionnelle de CMHII semble influencer le résultat des réponses immunitaires en fonction de différents facteurs, tels que le tissu cible, le(s) type(s) de cellule(s) non hématopoïétique(s) participante(s) et l'origine de l'inflammation. Nos résultats pourraient potentiellement ouvrir la voie à des applications thérapeutiques, qui tiennent compte de la contribution de la présentation d'antigènes par des CPAs non professionnelles, au cours de l'inflammation spécifique d'organe. - MHC class II (MHCII) molecules are fundamental for the presentation of antigens to CD4+ Τ cells, allowing the development of antigen-specific immune responses. It is widely accepted that MHCII expression is restricted to antigen-presenting cells (APC). However, under inflammatory conditions, MHCII expression is typically also induced by interferon (IFN)-y on nonhematopoietic cells such as epithelial cells and cardiomyocytes. So far, it remains controversial whether this nonprofessional antigen-presentation function promotes CD4+ Τ cell-dependent tolerance or immunity in vivo. To address this issue, we utilised mice which lack inducible MHCII expression on nonhematopoietic cells (pIV-/- K14 CIITA Tg mice) in different mouse models of inflammatory pathologies, namely immunisation models to induce antigen-specific Β cell responses, various colitis models and a model of experimental autoimmune myocarditis (EAM). In an attenuated model of colitis induced by chronic Helicobacter hepaticus infection and treatment with anti-interleukin (IL)-10 receptor (anti-IL-10R) monoclonal blocking antibody, we observed that abrogated MHCII expression by nonhematopoietic cells or, in an alternative tamoxifen-inducible mouse model (plV_fl/fl vil-Cre Tg mice), exclusively by intestinal epithelial cells (IEC), exacerbated bacterial-driven colitis, which was associated with increased colonic frequencies of innate immune cells, CD4+ Th1 cells and expression of proinflammatory cytokines and chemokines, including IFN-γ. Notably, defective nonhematopoietic MHCII expression also resulted in reduced Forkhead box P3 (FoxP3)+ regulatory Τ (Treg) cells without influencing innate lymphoid cell (ILC) and Th17 cell frequencies. These findings suggest a tolerogenic role of MHClT lECs to contribute to intestinal immune homeostasis. In contrast, in the EAM model, mice ablated of nonhematopoietic MHCII were resistant to disease induction, whereas progression of cardiac pathology in WT and heterozygous control mice was accompanied by upregulation of myocardial MHCII expression. However, cardiac inflammation could be adoptively transferred from primed pIV-/- K14 CIITA Tg mice into WT mice, indicating no intrinsic defect of CD4+ Τ activation in our mouse model. These observations imply a role for MHCIT heart-resident nonhematopoietic cells in actively promoting EAM. In conclusion, our findings from different organ-specific inflammatory pathologies suggest a complex and diverging role - either tolerogenic or immunogenic/ pathologic - for nonhematopoietic MHCII expression during inflammatory pathologies: Nonprofessional MHCII expression appears to influence the outcome of immune responses depending on 7 factors such as the target tissue, participating non hematopoietic cell type(s) and the origin of inflammation. Our findings may potentially open the way to therapeutic applications taking into account the contribution of antigen presentation by nonprofessional, tissue-resident APCs during organ-specific inflammation.

The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models.

Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, >30,000 models were built using many combinations of analytical methods. The teams generated predictive models without knowing the biological meaning of some of the endpoints and, to mimic clinical reality, tested the models on data that had not been used for training. We found that model performance depended largely on the endpoint and team proficiency and that different approaches generated models of similar performance. The conclusions and recommendations from MAQC-II should be useful for regulatory agencies, study committees and independent investigators that evaluate methods for global gene expression analysis.