Stoneley wave modeling in heterogeneous porous media with viscous pore fluids

We implemented Biot-type porous wave equations in a pseudo-spectral numerical modeling algorithm for the simulation of Stoneley waves in porous media. Fourier and Chebyshev methods are used to compute the spatial derivatives along the horizontal and vertical directions, respectively. To prevent from overly short time steps due to the small grid spacing at the top and bottom of the model as a consequence of the Chebyshev operator, the mesh is stretched in the vertical direction. As a large benefit, the Chebyshev operator allows for an explicit treatment of interfaces. Boundary conditions can be implemented with a characteristics approach. The characteristic variables are evaluated at zero viscosity. We use this approach to model seismic wave propagation at the interface between a fluid and a porous medium. Each medium is represented by a different mesh and the two meshes are connected through the above described characteristics domain-decomposition method. We show an experiment for sealed pore boundary conditions, where we first compare the numerical solution to an analytical solution. We then show the influence of heterogeneity and viscosity of the pore fluid on the propagation of the Stoneley wave and surface waves in general.

Benchmarking therapeutic drug monitoring software: A review of available computer tools

Therapeutic drug monitoring (TDM) aims to optimize treatments by individualizing dosage regimens based on the measurement of blood concentrations. Dosage individualization to maintain concentrations within a target range requires pharmacokinetic and clinical capabilities. Bayesian calculations currently represent the gold standard TDM approach but require computation assistance. In recent decades computer programs have been developed to assist clinicians in this assignment. The aim of this survey was to assess and compare computer tools designed to support TDM clinical activities. The literature and the Internet were searched to identify software. All programs were tested on personal computers. Each program was scored against a standardized grid covering pharmacokinetic relevance, user friendliness, computing aspects, interfacing and storage. A weighting factor was applied to each criterion of the grid to account for its relative importance. To assess the robustness of the software, six representative clinical vignettes were processed through each of them. Altogether, 12 software tools were identified, tested and ranked, representing a comprehensive review of the available software. Numbers of drugs handled by the software vary widely (from two to 180), and eight programs offer users the possibility of adding new drug models based on population pharmacokinetic analyses. Bayesian computation to predict dosage adaptation from blood concentration (a posteriori adjustment) is performed by ten tools, while nine are also able to propose a priori dosage regimens, based only on individual patient covariates such as age, sex and bodyweight. Among those applying Bayesian calculation, MM-USC*PACK© uses the non-parametric approach. The top two programs emerging from this benchmark were MwPharm© and TCIWorks. Most other programs evaluated had good potential while being less sophisticated or less user friendly. Programs vary in complexity and might not fit all healthcare settings. Each software tool must therefore be regarded with respect to the individual needs of hospitals or clinicians. Programs should be easy and fast for routine activities, including for non-experienced users. Computer-assisted TDM is gaining growing interest and should further improve, especially in terms of information system interfacing, user friendliness, data storage capability and report generation.

Phylogenetic Code in the Cloud - Can it Meet the Expectations?

Cloud computing has recently become very popular, and several bioinformatics applications exist already in that domain. The aim of this article is to analyse a current cloud system with respect to usability, benchmark its performance and compare its user friendliness with a conventional cluster job submission system. Given the current hype on the theme, user expectations are rather high, but current results show that neither the price/performance ratio nor the usage model is very satisfactory for large-scale embarrassingly parallel applications. However, for small to medium scale applications that require CPU time at certain peak times the cloud is a suitable alternative.

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.

A Confluence of Risks: Control and Compliance in the World of Unstructured Data, Big Data and the Cloud

The emergence of powerful new technologies, the existence of large quantities of data, and increasing demands for the extraction of added value from these technologies and data have created a number of significant challenges for those charged with both corporate and information technology management. The possibilities are great, the expectations high, and the risks significant. Organisations seeking to employ cloud technologies and exploit the value of the data to which they have access, be this in the form of "Big Data" available from different external sources or data held within the organisation, in structured or unstructured formats, need to understand the risks involved in such activities. Data owners have responsibilities towards the subjects of the data and must also, frequently, demonstrate that they are in compliance with current standards, laws and regulations. This thesis sets out to explore the nature of the technologies that organisations might utilise, identify the most pertinent constraints and risks, and propose a framework for the management of data from discovery to external hosting that will allow the most significant risks to be managed through the definition, implementation, and performance of appropriate internal control activities.

Skeletal muscle mitochondrial and lipid droplet content assessed with standardized grid sizes for stereology.

Skeletal muscle mitochondrial (Mito) and lipid droplet (Lipid) content are often measured in human translational studies. Stereological point counting allows computing Mito and Lipid volume density (Vd) from micrographs taken with transmission electron microscopes. Former studies are not specific as to the size of individual squares that make up the grids, making reproducibility difficult, particularly when different magnifications are used. Our objective was to determine which size grid would be best at predicting fractional volume efficiently without sacrificing reliability and to test a novel method to reduce sampling bias. Methods: ten subjects underwent vastus lateralis biopsies. Samples were fixed, embedded, and cut longitudinally in ultrathin sections of 60 nm. Twenty micrographs from the intramyofibrillar region were taken per subject at Ã-33,000 magnification. Different grid sizes were superimposed on each micrograph: 1,000 Ã- 1,000 nm, 500 Ã- 500 nm, and 250 Ã- 250 nm. Results: mean Mito and Lipid Vd were not statistically different across grids. Variability was greater when going from 1,000 Ã- 1,000 to 500 Ã- 500 nm grid than from 500 Ã- 500 to 250 Ã- 250 nm grid. Discussion: this study is the first to attempt to standardize grid size while keeping with the conventional stereology principles. This is all in hopes of producing replicable assessments that can be obtained universally across different studies looking at human skeletal muscle mitochondrial and lipid droplet content.

Benchmarking therapeutic drug monitoring software: A systematic evaluation of available computer tools

Introduction: Therapeutic drug monitoring (TDM) aims at optimizing treatment by individualizing dosage regimen based on measurement of blood concentrations. Maintaining concentrations within a target range requires pharmacokinetic and clinical capabilities. Bayesian calculation represents a gold standard in TDM approach but requires computing assistance. In the last decades computer programs have been developed to assist clinicians in this assignment. The aim of this benchmarking was to assess and compare computer tools designed to support TDM clinical activities.¦Method: Literature and Internet search was performed to identify software. All programs were tested on common personal computer. Each program was scored against a standardized grid covering pharmacokinetic relevance, user-friendliness, computing aspects, interfacing, and storage. A weighting factor was applied to each criterion of the grid to consider its relative importance. To assess the robustness of the software, six representative clinical vignettes were also processed through all of them.¦Results: 12 software tools were identified, tested and ranked. It represents a comprehensive review of the available software's characteristics. Numbers of drugs handled vary widely and 8 programs offer the ability to the user to add its own drug model. 10 computer programs are able to compute Bayesian dosage adaptation based on a blood concentration (a posteriori adjustment) while 9 are also able to suggest a priori dosage regimen (prior to any blood concentration measurement), based on individual patient covariates, such as age, gender, weight. Among those applying Bayesian analysis, one uses the non-parametric approach. The top 2 software emerging from this benchmark are MwPharm and TCIWorks. Other programs evaluated have also a good potential but are less sophisticated (e.g. in terms of storage or report generation) or less user-friendly.¦Conclusion: Whereas 2 integrated programs are at the top of the ranked listed, such complex tools would possibly not fit all institutions, and each software tool must be regarded with respect to individual needs of hospitals or clinicians. Interest in computing tool to support therapeutic monitoring is still growing. Although developers put efforts into it the last years, there is still room for improvement, especially in terms of institutional information system interfacing, user-friendliness, capacity of data storage and report generation.

Benchmarking therapeutic drug monitoring software: A systematic evaluation of available computer tools

Objectives: Therapeutic drug monitoring (TDM) aims at optimizing treatment by individualizing dosage regimen based on blood concentrations measurement. Maintaining concentrations within a target range requires pharmacokinetic (PK) and clinical capabilities. Bayesian calculation represents a gold standard in TDM approach but requires computing assistance. The aim of this benchmarking was to assess and compare computer tools designed to support TDM clinical activities.¦Methods: Literature and Internet were searched to identify software. Each program was scored against a standardized grid covering pharmacokinetic relevance, user-friendliness, computing aspects, interfacing, and storage. A weighting factor was applied to each criterion of the grid to consider its relative importance. To assess the robustness of the software, six representative clinical vignettes were also processed through all of them.¦Results: 12 software tools were identified, tested and ranked. It represents a comprehensive review of the available software characteristics. Numbers of drugs handled vary from 2 to more than 180, and integration of different population types is available for some programs. Nevertheless, 8 programs offer the ability to add new drug models based on population PK data. 10 computer tools incorporate Bayesian computation to predict dosage regimen (individual parameters are calculated based on population PK models). All of them are able to compute Bayesian a posteriori dosage adaptation based on a blood concentration while 9 are also able to suggest a priori dosage regimen, only based on individual patient covariates. Among those applying Bayesian analysis, MM-USC*PACK uses a non-parametric approach. The top 2 programs emerging from this benchmark are MwPharm and TCIWorks. Others programs evaluated have also a good potential but are less sophisticated or less user-friendly.¦Conclusions: Whereas 2 software packages are ranked at the top of the list, such complex tools would possibly not fit all institutions, and each program must be regarded with respect to individual needs of hospitals or clinicians. Programs should be easy and fast for routine activities, including for non-experienced users. Although interest in TDM tools is growing and efforts were put into it in the last years, there is still room for improvement, especially in terms of institutional information system interfacing, user-friendliness, capability of data storage and automated report generation.

Modelling hydrodynamics in the Rio Parana, Argentina : an evaluation and inter-comparison of reduced-complexity and physics based models applied to a large sand-bed river

Depth-averaged velocities and unit discharges within a 30 km reach of one of the world's largest rivers, the Rio Parana, Argentina, were simulated using three hydrodynamic models with different process representations: a reduced complexity (RC) model that neglects most of the physics governing fluid flow, a two-dimensional model based on the shallow water equations, and a three-dimensional model based on the Reynolds-averaged Navier-Stokes equations. Row characteristics simulated using all three models were compared with data obtained by acoustic Doppler current profiler surveys at four cross sections within the study reach. This analysis demonstrates that, surprisingly, the performance of the RC model is generally equal to, and in some instances better than, that of the physics based models in terms of the statistical agreement between simulated and measured flow properties. In addition, in contrast to previous applications of RC models, the present study demonstrates that the RC model can successfully predict measured flow velocities. The strong performance of the RC model reflects, in part, the simplicity of the depth-averaged mean flow patterns within the study reach and the dominant role of channel-scale topographic features in controlling the flow dynamics. Moreover, the very low water surface slopes that typify large sand-bed rivers enable flow depths to be estimated reliably in the RC model using a simple fixed-lid planar water surface approximation. This approach overcomes a major problem encountered in the application of RC models in environments characterised by shallow flows and steep bed gradients. The RC model is four orders of magnitude faster than the physics based models when performing steady-state hydrodynamic calculations. However, the iterative nature of the RC model calculations implies a reduction in computational efficiency relative to some other RC models. A further implication of this is that, if used to simulate channel morphodynamics, the present RC model may offer only a marginal advantage in terms of computational efficiency over approaches based on the shallow water equations. These observations illustrate the trade off between model realism and efficiency that is a key consideration in RC modelling. Moreover, this outcome highlights a need to rethink the use of RC morphodynamic models in fluvial geomorphology and to move away from existing grid-based approaches, such as the popular cellular automata (CA) models, that remain essentially reductionist in nature. In the case of the world's largest sand-bed rivers, this might be achieved by implementing the RC model outlined here as one element within a hierarchical modelling framework that would enable computationally efficient simulation of the morphodynamics of large rivers over millennial time scales. (C) 2012 Elsevier B.V. All rights reserved.

Memory-based scheduling of scientific computing clusters

This study looks at how increased memory utilisation affects throughput and energy consumption in scientific computing, especially in high-energy physics. Our aim is to minimise energy consumed by a set of jobs without increasing the processing time. The earlier tests indicated that, especially in data analysis, throughput can increase over 100% and energy consumption decrease 50% by processing multiple jobs in parallel per CPU core. Since jobs are heterogeneous, it is not possible to find an optimum value for the number of parallel jobs. A better solution is based on memory utilisation, but finding an optimum memory threshold is not straightforward. Therefore, a fuzzy logic-based algorithm was developed that can dynamically adapt the memory threshold based on the overall load. In this way, it is possible to keep memory consumption stable with different workloads while achieving significantly higher throughput and energy-efficiency than using a traditional fixed number of jobs or fixed memory threshold approaches.

Des cheminements sur la voie royale : une analyse sociologique des parcours de vie des normaliens-ne-s de Saint-Cloud, Fontenay-aux-Roses et Lyon (1981-1987)

Cette thèse est consacrée à l'analyse des parcours de vie d'un groupe d'anciens et anciennes élèves d'un établissement scolaire d'élite français (les Ecoles normales supérieures de Fontenay-aux-roses, Saint-Cloud et Lyon - promotions 1981-1987). A partir d'une approche longitudinale, son but est de montrer comment l'articulation entre la socialisation familiale, scolaire, professionnelle et conjugale participe à l'orientation progressive des parcours de vie des normalien-ne-s. Elle vise ainsi à remettre en question l'idée, largement répandue, selon laquelle l'intégration d'un cursus scolaire aussi sélectif et prestigieux que celui des ENS garantirait à Lou.te.s les élèves les mêmes chances d'accès aux positions dominantes de l'espace social. Alliant l'analyse de trois types de données (archives, questionnaires, entretiens), cette thèse met en évidence la manière dont inégalités relatives à l'origine sociale et au sexe se recomposent, une fois les portes de l'institution franchies. Elle montre que, dans un contexte socio-historique marqué par une forte expansion scolaire, il est plus que jamais nécessaire d'opérer une articulation systématique entre l'analyse des conditions sociales de réussite scolaire et l'analyse des conditions sociales d'exploitation des titres scolaires, afin de rendre compte des processus complexes de reproduction des inégalités et d'esquisser certaines de leur conditions de dépassement. Abstract: This thesis is dedicated to the life course analysis of alumni from one of the most prestigious French Grandes écoles (the Ecoles Normales Supérieures of Fontenay-aux- roses, Saint-Cloud and Lyon - classes of 1981.-1987). Through a longitudinal perspective, it aims to analyze how family, educational, professional and conjugal socialization processes combine to shape the life course of this particular group of graduates. The main goal of this research is to question the widespread belief that the French Grandes Ecoles guarantee automatic access to the very top of the professional and social hierarchy for all of their graduates. Based on a mixed methods research design (archive data, a questionnaire survey and semi-structured interviews), this thesis shows that, according to social origin and gender, ENS graduates actually adopt a diverse range of professional careers. It show how, in a socio-historical context characterized by a general increase in educational levels, any analysis of social inequalities should combine two levels of analysis: the social conditions of access to educational credentials, on the one hand, and the labor market value of formal qualifications, on the other hand. Our results suggest that the combined analysis of these two processes provide useful insight into the increasingly complex processes of social reproduction - and suggest fruitful perspectives for reducing some sources of inequality.