Development of model observers applied to 3D breast tomosynthesis microcalcifications and masses

The development of model observers for mimicking human detection strategies has followed from symmetric signals in simple noise to increasingly complex backgrounds. In this study we implement different model observers for the complex task of detecting a signal in a 3D image stack. The backgrounds come from real breast tomosynthesis acquisitions and the signals were simulated and reconstructed within the volume. Two different tasks relevant to the early detection of breast cancer were considered: detecting an 8 mm mass and detecting a cluster of microcalcifications. The model observers were calculated using a channelized Hotelling observer (CHO) with dense difference-of-Gaussian channels, and a modified (Partial prewhitening [PPW]) observer which was adapted to realistic signals which are not circularly symmetric. The sustained temporal sensitivity function was used to filter the images before applying the spatial templates. For a frame rate of five frames per second, the only CHO that we calculated performed worse than the humans in a 4-AFC experiment. The other observers were variations of PPW and outperformed human observers in every single case. This initial frame rate was a rather low speed and the temporal filtering did not affect the results compared to a data set with no human temporal effects taken into account. We subsequently investigated two higher speeds at 5, 15 and 30 frames per second. We observed that for large masses, the two types of model observers investigated outperformed the human observers and would be suitable with the appropriate addition of internal noise. However, for microcalcifications both only the PPW observer consistently outperformed the humans. The study demonstrated the possibility of using a model observer which takes into account the temporal effects of scrolling through an image stack while being able to effectively detect a range of mass sizes and distributions.

Intraocular penetration of penciclovir after oral administration of famciclovir: a population pharmacokinetic model.

OBJECTIVES: We developed a population model that describes the ocular penetration and pharmacokinetics of penciclovir in human aqueous humour and plasma after oral administration of famciclovir. METHODS: Fifty-three patients undergoing cataract surgery received a single oral dose of 500 mg of famciclovir prior to surgery. Concentrations of penciclovir in both plasma and aqueous humour were measured by HPLC with fluorescence detection. Concentrations in plasma and aqueous humour were fitted using a two-compartment model (NONMEM software). Inter-individual and intra-individual variabilities were quantified and the influence of demographics and physiopathological and environmental variables on penciclovir pharmacokinetics was explored. RESULTS: Drug concentrations were fitted using a two-compartment, open model with first-order transfer rates between plasma and aqueous humour compartments. Among tested covariates, creatinine clearance, co-intake of angiotensin-converting enzyme inhibitors and body weight significantly influenced penciclovir pharmacokinetics. Plasma clearance was 22.8 ± 9.1 L/h and clearance from the aqueous humour was 8.2 × 10(-5) L/h. AUCs were 25.4 ± 10.2 and 6.6 ± 1.8 μg · h/mL in plasma and aqueous humour, respectively, yielding a penetration ratio of 0.28 ± 0.06. Simulated concentrations in the aqueous humour after administration of 500 mg of famciclovir three times daily were in the range of values required for 50% growth inhibition of non-resistant strains of the herpes zoster virus family. CONCLUSIONS: Plasma and aqueous penciclovir concentrations showed significant variability that could only be partially explained by renal function, body weight and comedication. Concentrations in the aqueous humour were much lower than in plasma, suggesting that factors in the blood-aqueous humour barrier might prevent its ocular penetration or that redistribution occurs in other ocular compartments.

The effects of uncertainty avoidance on brand performance: Marketing creativity, product innovation and the brand duration

This paper investigates the link between brand performance and cultural primes in high-risk,innovation-based sectors. In theory section, we propose that the level of cultural uncertaintyavoidance embedded in a firm determine its marketing creativity by increasing the complexityand the broadness of a brand. It determines also the rate of firm product innovations.Marketing creativity and product innovation influence finally the firm marketingperformance. Empirically, we study trademarked promotion in the Software Security Industry(SSI). Our sample consists of 87 firms that are active in SSI from 11 countries in the period1993-2000. We use the data coming from SSI-related trademarks registered by these firms,ending up with 2,911 SSI-related trademarks and a panel of 18,213 observations. We estimatea two stage model in which first we predict the complexity and the broadness of a trademarkas a measure of marketing creativity and the rate of product innovations. Among severalcontrol variables, our variable of theoretical interest is the Hofstede s uncertainty avoidancecultural index. Then, we estimate the trademark duration with a hazard model using thepredicted complexity and broadness as well as the rate of product innovations, along with thesame control variables. Our evidence confirms that the cultural avoidance affects the durationof the trademarks through the firm marketing creativity and product innovation.

Secret information acquisition in Cournot markets

Two-stage game models of information acquisition in stochastic oligopoliesrequire the unrealistic assumption that firms observe the precision ofinformation chosen by their competitors before determining quantities. Thispaper analyzes secret information acquisition as a one-stage game. Relativeto the two-stage game firms are shown to acquire less information. Policyimplications based on the two-stage game yield, therefore, too high taxes ortoo low subsidies for research activities. For the case of heterogeneousduopoly it is shown that comparative statics results partly depend on theobservability assumption.

Strategic ambiguity in electoral competition

Many have observed that political candidates running for election areoften purposefully expressing themselves in vague and ambiguous terms. In thispaper we provide a simple formal model of this phenomenon. We model theelectoral competition between two candidates as a two--stage game. In thefirst stage of the game two candidates simultaneously choose their ideologies,and in the second stage they simultaneously choose their level of ambiguity.Our results show that ambiguity, although disliked by voters, may be sustainedin equilibrium. The introduction of ambiguity as a strategic choice variablefor the candidates can also serve to explain why candidates with the sameelectoral objectives end up ``separating'', that is, assuming different ideological positions.

Social value orientation as a moral intuition: Decision-making in the dictator game

We studied the decision making process in the Dictator Game and showed that decisions are the result of a two-step process. In a first step, decision makers generate an automatic, intuitive proposal. Given sufficient motivation and cognitive resources, they adjust this in a second, more deliberated phase. In line with the social intuitionist model, we show that one s Social Value Orientation determines intuitive choice tendencies in the first step, and that this effect is mediated by the dictator s perceived interpersonal closeness with the receiver. Self-interested concerns subsequently leadto a reduction of donation size in step 2. Finally, we show that increasing interpersonal closeness can promote pro-social decision-making.

Numerical simulation of ambient seismic wavefield modification caused by pore-fluid effects in an oil reservoir

We have modeled numerically the seismic response of a poroelastic inclusion with properties applicable to an oil reservoir that interacts with an ambient wavefield. The model includes wave-induced fluid flow caused by pressure differences between mesoscopic-scale (i.e., in the order of centimeters to meters) heterogeneities. We used a viscoelastic approximation on the macroscopic scale to implement the attenuation and dispersion resulting from this mesoscopic-scale theory in numerical simulations of wave propagation on the kilometer scale. This upscaling method includes finite-element modeling of wave-induced fluid flow to determine effective seismic properties of the poroelastic media, such as attenuation of P- and S-waves. The fitted, equivalent, viscoelastic behavior is implemented in finite-difference wave propagation simulations. With this two-stage process, we model numerically the quasi-poroelastic wave-propagation on the kilometer scale and study the impact of fluid properties and fluid saturation on the modeled seismic amplitudes. In particular, we addressed the question of whether poroelastic effects within an oil reservoir may be a plausible explanation for low-frequency ambient wavefield modifications observed at oil fields in recent years. Our results indicate that ambient wavefield modification is expected to occur for oil reservoirs exhibiting high attenuation. Whether or not such modifications can be detected in surface recordings, however, will depend on acquisition design and noise mitigation processing as well as site-specific conditions, such as the geologic complexity of the subsurface, the nature of the ambient wavefield, and the amount of surface noise.

The Mont-Mort metapelites: Variscan metamorphism and geodynamic context (Brianconnais basement, Western Alps, Switzerland)

The Mont-Mort metapelites are one of the best preserved relies of the Variscan unit in the Brianconnais basement. These micaschists crystallized during a poly-phase metamorphic cycle, under amphibolite facies conditions. Mineral parageneses and geothermobarometric calculations indicate a two-stage evolution. Stage (1) (550-600 degrees C and 5-8 kbar) is documented by assemblages of zoned garnet, staurolite, kyanite(?), biotite, muscovite, quartz and pla gioclase. Stage (2) (550-600 degrees C and 2 kbar) is illustrated by assemblages of andalusite, sillimanite, muscovite, biotite. This metamorphic evolution is characterized by a nearly isothermal decompression path, terminating with the formation of andalusite-bearing veins. U-Pb monazite dates at 330 Ma and Ar-40/Ar-39 muscovite dates at 290-310 Ma (without substantial evidence of argon resetting) point to Variscan metamorphism and yield an estimate of the time interval between the thermal peak and the retrogression stage within this part of the Brianconnais basement. Restoring the Brianconnais and other Alpine basement units within an existing geodynamic model of Cordillera construction and destruction, it is possible to understand better the transition from a medium pressure/high temperature regime (collision with a peak metamorphism around 330 Ma) to low-P/high-T conditions (decompression in an extensional regime) with high geothermal gradient, as recorded by the successive Variscan parageneses within the Mont-Mort metapelites.

A framework to understand the variations of PSD-95 expression in brain aging and in Alzheimer's disease.

The postsynaptic density protein PSD-95 is a major element of synapses. PSD-95 is involved in aging, Alzheimer's disease (AD) and numerous psychiatric disorders. However, contradictory data about PSD-95 expression in aging and AD have been reported. Indeed in AD versus control brains PSD-95 varies according to regions, increasing in the frontal cortex, at least in a primary stage, and decreasing in the temporal cortex. In contrast, in transgenic mouse models of aging and AD PSD-95 expression is decreased, in behaviorally aged impaired versus unimpaired rodents it can decrease or increase and finally, it is increased in rodents grown in enriched environments. Different factors explain these contradictory results in both animals and humans, among others concomitant psychiatric endophenotypes, such as depression. The possible involvement of PSD-95 in reactive and/or compensatory mechanisms during AD progression is underscored, at least before the occurrence of important synaptic elimination. Thus, in AD but not in AD transgenic mice, enhanced expression might precede the diminution commonly observed in advanced aging. A two-compartments cell model, separating events taking place in cell bodies and synapses, is presented. Overall these data suggest that AD research will progress by untangling pathological from protective events, a prerequisite for effective therapeutic strategies.

On making causal claims: A review and recommendations

Social scientists often estimate models from correlational data, where the independent variable has not been exogenously manipulated; they also make implicit or explicit causal claims based on these models. When can these claims be made? We answer this question by first discussing design and estimation conditions under which model estimates can be interpreted, using the randomized experiment as the gold standard. We show how endogeneity--which includes omitted variables, omitted selection, simultaneity, common methods bias, and measurement error--renders estimates causally uninterpretable. Second, we present methods that allow researchers to test causal claims in situations where randomization is not possible or when causal interpretation is confounded, including fixed-effects panel, sample selection, instrumental variable, regression discontinuity, and difference-in-differences models. Third, we take stock of the methodological rigor with which causal claims are being made in a social sciences discipline by reviewing a representative sample of 110 articles on leadership published in the previous 10 years in top-tier journals. Our key finding is that researchers fail to address at least 66 % and up to 90 % of design and estimation conditions that make causal claims invalid. We conclude by offering 10 suggestions on how to improve non-experimental research.

Diet and the risk of head and neck cancer: a pooled analysis in the INHANCE consortium.

We investigated the association between diet and head and neck cancer (HNC) risk using data from the International Head and Neck Cancer Epidemiology (INHANCE) consortium. The INHANCE pooled data included 22 case-control studies with 14,520 cases and 22,737 controls. Center-specific quartiles among the controls were used for food groups, and frequencies per week were used for single food items. A dietary pattern score combining high fruit and vegetable intake and low red meat intake was created. Odds ratios (OR) and 95% confidence intervals (CI) for the dietary items on the risk of HNC were estimated with a two-stage random-effects logistic regression model. An inverse association was observed for higher-frequency intake of fruit (4th vs. 1st quartile OR = 0.52, 95% CI = 0.43-0.62, p (trend) < 0.01) and vegetables (OR = 0.66, 95% CI = 0.49-0.90, p (trend) = 0.01). Intake of red meat (OR = 1.40, 95% CI = 1.13-1.74, p p (trend) < 0.01) was positively associated with HNC risk. Higher dietary pattern scores, reflecting high fruit/vegetable and low red meat intake, were associated with reduced HNC risk (per score increment OR = 0.90, 95% CI = 0.84-0.97).

Essays on the measurement of school efficiency

Measuring school efficiency is a challenging task. First, a performance measurement technique has to be selected. Within Data Envelopment Analysis (DEA), one such technique, alternative models have been developed in order to deal with environmental variables. The majority of these models lead to diverging results. Second, the choice of input and output variables to be included in the efficiency analysis is often dictated by data availability. The choice of the variables remains an issue even when data is available. As a result, the choice of technique, model and variables is probably, and ultimately, a political judgement. Multi-criteria decision analysis methods can help the decision makers to select the most suitable model. The number of selection criteria should remain parsimonious and not be oriented towards the results of the models in order to avoid opportunistic behaviour. The selection criteria should also be backed by the literature or by an expert group. Once the most suitable model is identified, the principle of permanence of methods should be applied in order to avoid a change of practices over time. Within DEA, the two-stage model developed by Ray (1991) is the most convincing model which allows for an environmental adjustment. In this model, an efficiency analysis is conducted with DEA followed by an econometric analysis to explain the efficiency scores. An environmental variable of particular interest, tested in this thesis, consists of the fact that operations are held, for certain schools, on multiple sites. Results show that the fact of being located on more than one site has a negative influence on efficiency. A likely way to solve this negative influence would consist of improving the use of ICT in school management and teaching. Planning new schools should also consider the advantages of being located on a unique site, which allows reaching a critical size in terms of pupils and teachers. The fact that underprivileged pupils perform worse than privileged pupils has been public knowledge since Coleman et al. (1966). As a result, underprivileged pupils have a negative influence on school efficiency. This is confirmed by this thesis for the first time in Switzerland. Several countries have developed priority education policies in order to compensate for the negative impact of disadvantaged socioeconomic status on school performance. These policies have failed. As a result, other actions need to be taken. In order to define these actions, one has to identify the social-class differences which explain why disadvantaged children underperform. Childrearing and literary practices, health characteristics, housing stability and economic security influence pupil achievement. Rather than allocating more resources to schools, policymakers should therefore focus on related social policies. For instance, they could define pre-school, family, health, housing and benefits policies in order to improve the conditions for disadvantaged children.

Coarsening of solid-liquid mixtures in a random acceleration field

The effects of flow induced by a random acceleration field (g-jitter) are considered in two related situations that are of interest for microgravity fluid experiments: the random motion of isolated buoyant particles, and diffusion driven coarsening of a solid-liquid mixture. We start by analyzing in detail actual accelerometer data gathered during a recent microgravity mission, and obtain the values of the parameters defining a previously introduced stochastic model of this acceleration field. The diffusive motion of a single solid particle suspended in an incompressible fluid that is subjected to such random accelerations is considered, and mean squared velocities and effective diffusion coefficients are explicitly given. We next study the flow induced by an ensemble of such particles, and show the existence of a hydrodynamically induced attraction between pairs of particles at distances large compared with their radii, and repulsion at short distances. Finally, a mean field analysis is used to estimate the effect of g-jitter on diffusion controlled coarsening of a solid-liquid mixture. Corrections to classical coarsening rates due to the induced fluid motion are calculated, and estimates are given for coarsening of Sn-rich particles in a Sn-Pb eutectic fluid, an experiment to be conducted in microgravity in the near future.

Estimation of the correlation structure of crustal velocity heterogeneity from seismic reflection data

Numerous sources of evidence point to the fact that heterogeneity within the Earth's deep crystalline crust is complex and hence may be best described through stochastic rather than deterministic approaches. As seismic reflection imaging arguably offers the best means of sampling deep crustal rocks in situ, much interest has been expressed in using such data to characterize the stochastic nature of crustal heterogeneity. Previous work on this problem has shown that the spatial statistics of seismic reflection data are indeed related to those of the underlying heterogeneous seismic velocity distribution. As of yet, however, the nature of this relationship has remained elusive due to the fact that most of the work was either strictly empirical or based on incorrect methodological approaches. Here, we introduce a conceptual model, based on the assumption of weak scattering, that allows us to quantitatively link the second-order statistics of a 2-D seismic velocity distribution with those of the corresponding processed and depth-migrated seismic reflection image. We then perform a sensitivity study in order to investigate what information regarding the stochastic model parameters describing crustal velocity heterogeneity might potentially be recovered from the statistics of a seismic reflection image using this model. Finally, we present a Monte Carlo inversion strategy to estimate these parameters and we show examples of its application at two different source frequencies and using two different sets of prior information. Our results indicate that the inverse problem is inherently non-unique and that many different combinations of the vertical and lateral correlation lengths describing the velocity heterogeneity can yield seismic images with the same 2-D autocorrelation structure. The ratio of all of these possible combinations of vertical and lateral correlation lengths, however, remains roughly constant which indicates that, without additional prior information, the aspect ratio is the only parameter describing the stochastic seismic velocity structure that can be reliably recovered.

Large-scale clustering through functional embedding

We present a new framework for large-scale data clustering. The main idea is to modify functional dimensionality reduction techniques to directly optimize over discrete labels using stochastic gradient descent. Compared to methods like spectral clustering our approach solves a single optimization problem, rather than an ad-hoc two-stage optimization approach, does not require a matrix inversion, can easily encode prior knowledge in the set of implementable functions, and does not have an ?out-of-sample? problem. Experimental results on both artificial and real-world datasets show the usefulness of our approach.