Evolutionarily stable learning schedules and cumulative culture in discrete generation models.

Individual learning (e.g., trial-and-error) and social learning (e.g., imitation) are alternative ways of acquiring and expressing the appropriate phenotype in an environment. The optimal choice between using individual learning and/or social learning may be dictated by the life-stage or age of an organism. Of special interest is a learning schedule in which social learning precedes individual learning, because such a schedule is apparently a necessary condition for cumulative culture. Assuming two obligatory learning stages per discrete generation, we obtain the evolutionarily stable learning schedules for the three situations where the environment is constant, fluctuates between generations, or fluctuates within generations. During each learning stage, we assume that an organism may target the optimal phenotype in the current environment by individual learning, and/or the mature phenotype of the previous generation by oblique social learning. In the absence of exogenous costs to learning, the evolutionarily stable learning schedules are predicted to be either pure social learning followed by pure individual learning ("bang-bang" control) or pure individual learning at both stages ("flat" control). Moreover, we find for each situation that the evolutionarily stable learning schedule is also the one that optimizes the learned phenotype at equilibrium.

Investigation of discrete imaging models and iterative image reconstruction in differential X-ray phase-contrast tomography.

Differential X-ray phase-contrast tomography (DPCT) refers to a class of promising methods for reconstructing the X-ray refractive index distribution of materials that present weak X-ray absorption contrast. The tomographic projection data in DPCT, from which an estimate of the refractive index distribution is reconstructed, correspond to one-dimensional (1D) derivatives of the two-dimensional (2D) Radon transform of the refractive index distribution. There is an important need for the development of iterative image reconstruction methods for DPCT that can yield useful images from few-view projection data, thereby mitigating the long data-acquisition times and large radiation doses associated with use of analytic reconstruction methods. In this work, we analyze the numerical and statistical properties of two classes of discrete imaging models that form the basis for iterative image reconstruction in DPCT. We also investigate the use of one of the models with a modern image reconstruction algorithm for performing few-view image reconstruction of a tissue specimen.

Length of hospital stay and postdischarge mortality in patients with pulmonary embolism: a statewide perspective

BACKGROUND: The optimal length of stay (LOS) for patients with pulmonary embolism (PE) is unknown. Although reducing LOS is likely to save costs, the effects on patient safety are unclear. We sought to identify patient and hospital factors associated with LOS and assess whether LOS was associated with postdischarge mortality. METHODS: We evaluated patients discharged with a primary diagnosis of PE from 186 acute care hospitals in Pennsylvania (January 2000 through November 2002). We used discrete survival models to examine the association between (1) patient and hospital factors and the time to discharge and (2) LOS and postdischarge mortality within 30 days of presentation, adjusting for patient and hospital factors. RESULTS: Among 15 531 patient discharges with PE, the median LOS was 6 days, and postdischarge mortality rate was 3.3%. In multivariate analysis, patients from Philadelphia were less likely to be discharged on a given day (odds ratio [OR], 0.82; 95% confidence interval [CI], 0.73-0.93), as were black patients (OR, 0.88; 95% CI, 0.82-0.94).The odds of discharge decreased notably with greater patient severity of illness and in patients without private health insurance. Adjusted postdischarge mortality was significantly higher for patients with an LOS of 4 days or less (OR, 1.55; 95% CI, 1.21-2.00) relative to those with an LOS of 5 to 6 days. CONCLUSIONS: Several hospital and patient factors were independently associated with LOS. Patients with a very short LOS had greater postdischarge mortality relative to patients with a typical LOS, suggesting that physicians may inappropriately select patients with PE for early discharge who are at increased risk of complications

Weekend versus weekday admission and mortality after acute pulmonary embolism.

BACKGROUND: Optimal management of acute pulmonary embolism (PE) requires medical expertise, diagnostic testing, and therapies that may not be available consistently throughout the entire week. We sought to assess whether associations exist between weekday or weekend admission and mortality and length of hospital stay for patients hospitalized with PE. METHODS AND RESULTS: We evaluated patients discharged with a primary diagnosis of PE from 186 acute care hospitals in Pennsylvania (January 2000 to November 2002). We used random-effect logistic models to study the association between weekend admission and 30-day mortality and used discrete survival models to study the association between weekend admission and time to hospital discharge, adjusting for hospital (region, size, and teaching status) and patient factors (race, insurance, severity of illness, and use of thrombolytic therapy). Among 15 531 patient discharges with PE, 3286 patients (21.2%) had been admitted on a weekend. Patients admitted on weekends had a higher unadjusted 30-day mortality rate (11.1% versus 8.8%) than patients admitted on weekdays, with no difference in length of stay. Patients admitted on weekends had significantly greater adjusted odds of dying (odds ratio 1.17, 95% confidence interval 1.03 to 1.34) than patients admitted on weekdays. The higher mortality among patients hospitalized on weekends was driven by the increased mortality rate among the most severely ill patients. CONCLUSIONS: Patients with PE who are admitted on weekends have a significantly higher short-term mortality than patients admitted on weekdays. Quality-improvement efforts should aim to ensure a consistent approach to the management of PE 7 days a week.

Hospital volume and patient outcomes in pulmonary embolism.

BACKGROUND: In numerous high-risk medical and surgical conditions, a greater volume of patients undergoing treatment in a given setting or facility is associated with better survival. For patients with pulmonary embolism, the relation between the number of patients treated in a hospital (volume) and patient outcome is unknown. METHODS: We studied discharge records from 186 acute care hospitals in Pennsylvania for a total of 15 531 patients for whom the primary diagnosis was pulmonary embolism. The study outcomes were all-cause mortality in hospital and within 30 days after presentation for pulmonary embolism and the length of hospital stay. We used logistic models to study the association between hospital volume and 30-day mortality and discrete survival models to study the association between in-hospital mortality and time to hospital discharge. RESULTS: The median annual hospital volume for pulmonary embolism was 20 patients (interquartile range 10-42). Overall in-hospital mortality was 6.0%, whereas 30-day mortality was 9.3%. In multivariable analysis, very-high-volume hospitals (> or = 42 cases per year) had a significantly lower odds of in-hospital death (odds ratio [OR] 0.71, 95% confidence interval [CI] 0.51-0.99) and of 30-day death (OR 0.71, 95% CI 0.54-0.92) than very-low-volume hospitals (< 10 cases per year). Although patients in the very-high-volume hospitals had a slightly longer length of stay than those in the very-low-volume hospitals (mean difference 0.7 days), there was no association between volume and length of stay. INTERPRETATION: In hospitals with a high volume of cases, pulmonary embolism was associated with lower short-term mortality. Further research is required to determine the causes of the relation between volume and outcome for patients with pulmonary embolism.

Evidence for an overestimated vulnerability of adolescent rats to develop signs of drug addiction

Drug addiction is a multi-etiological disorder to which some individuals are more vulnerable an others. Whereas converging clinical and epidemiological studies report a peak of drug use ring adolescence, many behavioral traits characterizing teenagers have been proposed to contribute to this vulnerability, including a heightened sensation-seeking, an enhanced impulsivity d a larger influence exerted by peers. By many aspects, juvenile rodents display behavioral traits at resemble those of teenagers. However, the concept of increased vulnerability to drug addiction juvenile rats remains in debate. Indeed, only a few studies directly compared juvenile and adult fdents regarding behavioral predictors of drug abuse. Moreover, some key features of drug diction have never been investigated in juvenile rats yet. For this very reason, we conducted a arge-scale behavioral comparison of adult and adolescent rats with the aim of dissecting their espective behavioral traits and vulnerabilities to drug addiction. We first have shown that juvenile rats exhibited an enhanced motor impulsivity, and a loss of control over reward seeking assessed by a persistent reward taking despite adverse consequences mild electric footshocks]. We also report that juvenile rats displayed a higher anxiety profile, ind we discuss why these behaviors might represent key underpinning mechanisms leading to an enhanced vulnerability to drug abuse. Meanwhile, we collected clear cut observations that do not support such an interpretation. In Articular, juvenile and adult rats displayed identical novelty-induced habituation and preference at are considered to represent two potent predictors of cocaine initiation and compulsive intake, "pre strikingly, juvenile rats were less attracted by cues predicting reward in a Pavlovian utoshaping task, suggesting a lower propensity for cues or context to trigger the reinstatement of a^previously extinguished reward seeking behavior. Finally, using a paradigm assessing schedule- ciuced polydipsia, juvenile and adult rats exhibited similar compulsive drinking, under control conditions and following a chronic cocaine treatment as well. Hence, these observations call for a cautious interpretation of adolescent vulnerability to drug use. In particular, we underlined that even the most compulsive young rats did not consume ärger amounts of cocaine than adults, nor exhibited larger efforts in a cue-induced relapse aradigm, despite a transient increased motivation for lever-pressing. And further, despite a higher ensitivity to the behavioral effects of cocaine, juvenile rats did not differ from adults in their ropensity to constantly prefer saccharin over cocaine in a discrete-choice procedure, even after a ?'Id chronic stress procedure. Altogether, our results shape an objective overview of the juvenile rats' behavior in relation to oth drug and non-drug rewards, suggesting a heterogeneous and task-specific profile. Despite elements potentially underlying a real risk for substance use, adolescent rats do not exhibit a ehavioral repertoire suggesting increased vulnerability for compulsive drug abuse. Our conclusions strongly encourage deeper neurobiological investigations of the developing brain, and also open a debate on a possible overestimation of juvenile rats' and teenager's risk to develop aladaptive behaviors and drug addiction. - L'addiction aux drogues est une pathologie d'origine multifactorielle, à laquelle certains individus sont plus vulnérables que d'autres. De nombreuses études cliniques et épidémiologiques suggèrent une consommation excessive de drogues pendant l'adolescence, et plusieurs explications ont été avancées pour justifier cette tendance, parmi lesquelles on note une augmentation de la recherche de sensation, une impulsivité plus marquée et une plus forte influence de l'entourage. Le rat juvénile présente de nombreuses caractéristiques développementales similaires à l'adolescence humaine. En revanche, la vulnérabilité des rats juvéniles à l'abus de drogue est encore sujette à caution. En effet, peu d'études ont directement comparé des traits de comportements pouvant refléter un accroissement du risque d'abus chez les rats juvéniles par comparaison aux rats adultes. En outre, certaines caractéristiques fondamentales de l'addiction chez l'homme n'ont pas encore été étudiées chez le rat adolescent. Ce travail de thèse s'est donc donné pour objectif de comparer le comportement de rats adultes vis-à-vis de celui de rats adolescents, afin d'évaluer dans quelle mesure ces derniers seraient plus vulnérables à l'abus de drogues. Nos résultats indiquent que les rats juvéniles présentent une augmentation des comportements impulsifs, ainsi qu'une plus grande persistance à rechercher de manière compulsive une récompense en dépit de légers chocs électriques. Les rats juvéniles présentent également un profil anxieux plus élevé, ce qui peut constituer une autre source de vulnérabilité. Cependant, certaines caractéristiques comportementales ne suggèrent pas de vulnérabilité chez les rats juvéniles. Aucune différence entre rats adultes et adolescents n'a été trouvée pour l'habituation et la préférence pour la nouveauté, deux traits prédisant l'initiation et la prise compulsive de drogue. De plus, nous avons montré que les rats adolescents attribuent moins d'intérêt à des stimuli prédisant la disponibilité d'une récompense, suggérant une vulnérabilité plus faible à la rechute induite par les stimuli associés à la prise de drogue. Une étude complémentaire des comportements compulsifs indique une absence de différence entre rats adultes et adolescents, à la fois en condition basale ou après un traitement chronique à la cocaïne. L'étude des comportements de prise de drogue ne va pas non plus dans le sens d'une vulnérabilité des rats adolescents. Bien que les rats compulsifs sélectionnés pendant la période juvénile présentent une plus grande motivation à prendre de la cocaïne, ils ne diffèrent ni dans la quantité de cocaïne consommée, ni dans la rechute induite par les stimuli environnementaux. En dépit d'une sensibilisation comportementale plus importante, les rats adolescents présentent la même préférence que les adultes face à un choix entre une drogue et une récompense alternative, suggérant une résilience à la cocaïne comparable à celle des adultes. Enfin, cette résilience pour la cocaïne n'est pas affectée par un stress chronique lors de l'adolescence. En résumé, cette étude dresse un regard objectif sur les comportements en lien avec une vulnérabilité à l'abus de drogues chez le rat juvénile, suggérant que celle-ci est hétérogène et spécifique au protocole utilisé. En dépit de certains éléments de vulnérabilité, les rats adolescents ne présentent pas d'attirance excessive pour la cocaïne, ni de prédisposition à la consommation compulsive de cette drogue. L'ensemble de ces éléments pourra constituer une base solide pour l'investigation neurobiologique du cerveau en développement, et ouvre un débat sur une possible surestimation de la vulnérabilité des rats juvéniles et de leurs homologues humains aux pathologies psychiatriques telles que l'addiction aux drogues.

A qualitative continuous model of cellular auxin and brassinosteroid signaling and their crosstalk.

Motivation: Hormone pathway interactions are crucial in shaping plant development, such as synergism between the auxin and brassinosteroid pathways in cell elongation. Both hormone pathways have been characterized in detail, revealing several feedback loops. The complexity of this network, combined with a shortage of kinetic data, renders its quantitative analysis virtually impossible at present.Results: As a first step towards overcoming these obstacles, we analyzed the network using a Boolean logic approach to build models of auxin and brassinosteroid signaling, and their interaction. To compare these discrete dynamic models across conditions, we transformed them into qualitative continuous systems, which predict network component states more accurately and can accommodate kinetic data as they become available. To this end, we developed an extension for the SQUAD software, allowing semi-quantitative analysis of network states. Contrasting the developmental output depending on cell type-specific modulators enabled us to identify a most parsimonious model, which explains initially paradoxical mutant phenotypes and revealed a novel physiological feature.

Geometric stopping of a random walk and its applications to valuing equity-linked death benefits

We study discrete-time models in which death benefits can depend on a stock price index, the logarithm of which is modeled as a random walk. Examples of such benefit payments include put and call options, barrier options, and lookback options. Because the distribution of the curtate-future-lifetime can be approximated by a linear combination of geometric distributions, it suffices to consider curtate-future-lifetimes with a geometric distribution. In binomial and trinomial tree models, closed-form expressions for the expectations of the discounted benefit payment are obtained for a series of options. They are based on results concerning geometric stopping of a random walk, in particular also on a version of the Wiener-Hopf factorization.

Sensitivity of predictive species distribution models to change in grain size

Predictive species distribution modelling (SDM) has become an essential tool in biodiversity conservation and management. The choice of grain size (resolution) of environmental layers used in modelling is one important factor that may affect predictions. We applied 10 distinct modelling techniques to presence-only data for 50 species in five different regions, to test whether: (1) a 10-fold coarsening of resolution affects predictive performance of SDMs, and (2) any observed effects are dependent on the type of region, modelling technique, or species considered. Results show that a 10 times change in grain size does not severely affect predictions from species distribution models. The overall trend is towards degradation of model performance, but improvement can also be observed. Changing grain size does not equally affect models across regions, techniques, and species types. The strongest effect is on regions and species types, with tree species in the data sets (regions) with highest locational accuracy being most affected. Changing grain size had little influence on the ranking of techniques: boosted regression trees remain best at both resolutions. The number of occurrences used for model training had an important effect, with larger sample sizes resulting in better models, which tended to be more sensitive to grain. Effect of grain change was only noticeable for models reaching sufficient performance and/or with initial data that have an intrinsic error smaller than the coarser grain size.

Using 3D surface datasets to understand landslide evolution: From analogue models to real case study

Early detection of landslide surface deformation with 3D remote sensing techniques, as TLS, has become a great challenge during last decade. To improve our understanding of landslide deformation, a series of analogue simulation have been carried out on non-rigid bodies coupled with 3D digitizer. All these experiments have been carried out under controlled conditions, as water level and slope angle inclination. We were able to follow 3D surface deformation suffered by complex landslide bodies from precursory deformation still larger failures. These experiments were the basis for the development of a new algorithm for the quantification of surface deformation using automatic tracking method on discrete points of the slope surface. To validate the algorithm, comparisons were made between manually obtained results and algorithm surface displacement results. Outputs will help in understanding 3D deformation during pre-failure stages and failure mechanisms, which are fundamental aspects for future implementation of 3D remote sensing techniques in early warning systems.

Do pseudo-absence selection strategies influence species distribution models and their predictions? An information-theoretic approach based on simulated data

Background Multiple logistic regression is precluded from many practical applications in ecology that aim to predict the geographic distributions of species because it requires absence data, which are rarely available or are unreliable. In order to use multiple logistic regression, many studies have simulated "pseudo-absences" through a number of strategies, but it is unknown how the choice of strategy influences models and their geographic predictions of species. In this paper we evaluate the effect of several prevailing pseudo-absence strategies on the predictions of the geographic distribution of a virtual species whose "true" distribution and relationship to three environmental predictors was predefined. We evaluated the effect of using a) real absences b) pseudo-absences selected randomly from the background and c) two-step approaches: pseudo-absences selected from low suitability areas predicted by either Ecological Niche Factor Analysis: (ENFA) or BIOCLIM. We compared how the choice of pseudo-absence strategy affected model fit, predictive power, and information-theoretic model selection results. Results Models built with true absences had the best predictive power, best discriminatory power, and the "true" model (the one that contained the correct predictors) was supported by the data according to AIC, as expected. Models based on random pseudo-absences had among the lowest fit, but yielded the second highest AUC value (0.97), and the "true" model was also supported by the data. Models based on two-step approaches had intermediate fit, the lowest predictive power, and the "true" model was not supported by the data. Conclusion If ecologists wish to build parsimonious GLM models that will allow them to make robust predictions, a reasonable approach is to use a large number of randomly selected pseudo-absences, and perform model selection based on an information theoretic approach. However, the resulting models can be expected to have limited fit.

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.

Mate choice evolution, dominance effects, and the maintenance of genetic variation.

Female mate choice influences the maintenance of genetic variation by altering the mating success of males with different genotypes. The evolution of preferences themselves, on the other hand, depends on genetic variation present in the population. Few models have tracked this feedback between a choice gene and its effects on genetic variation, in particular when genes that determine offspring viability and attractiveness have dominance effects. Here we build a population genetic model that allows comparing the evolution of various choice rules in a single framework. We first consider preferences for good genes and show that focused preferences for homozygotes evolve more easily than broad preferences, which allow heterozygous males high mating success too. This occurs despite better maintenance of genetic diversity in the latter scenario, and we discuss why empirical findings of superior mating success of heterozygous males consequently do not immediately lead to a better understanding of the lek paradox. Our results thus suggest that the mechanisms that help maintain genetic diversity also have a flipside of making female choice an inaccurate means of producing the desired kind of offspring. We then consider preferences for heterozygosity per se, and show that these evolve only under very special conditions. Choice for compatible genotypes can evolve but its selective advantage diminishes quickly due to frequency-dependent selection. Finally, we show that our model reproduces earlier results on selfing, when the female choice strategy produces assortative mating. Overall, our model indicates that various forms of heterozygote-favouring (or variable) female choice pose a problem for the theory of sexual ornamentation based on indirect benefits, rather than a solution.