A model of cellular dosimetry for macroscopic tumors in radiopharmaceutical therapy.

PURPOSE: In the radiopharmaceutical therapy approach to the fight against cancer, in particular when it comes to translating laboratory results to the clinical setting, modeling has served as an invaluable tool for guidance and for understanding the processes operating at the cellular level and how these relate to macroscopic observables. Tumor control probability (TCP) is the dosimetric end point quantity of choice which relates to experimental and clinical data: it requires knowledge of individual cellular absorbed doses since it depends on the assessment of the treatment's ability to kill each and every cell. Macroscopic tumors, seen in both clinical and experimental studies, contain too many cells to be modeled individually in Monte Carlo simulation; yet, in particular for low ratios of decays to cells, a cell-based model that does not smooth away statistical considerations associated with low activity is a necessity. The authors present here an adaptation of the simple sphere-based model from which cellular level dosimetry for macroscopic tumors and their end point quantities, such as TCP, may be extrapolated more reliably. METHODS: Ten homogenous spheres representing tumors of different sizes were constructed in GEANT4. The radionuclide 131I was randomly allowed to decay for each model size and for seven different ratios of number of decays to number of cells, N(r): 1000, 500, 200, 100, 50, 20, and 10 decays per cell. The deposited energy was collected in radial bins and divided by the bin mass to obtain the average bin absorbed dose. To simulate a cellular model, the number of cells present in each bin was calculated and an absorbed dose attributed to each cell equal to the bin average absorbed dose with a randomly determined adjustment based on a Gaussian probability distribution with a width equal to the statistical uncertainty consistent with the ratio of decays to cells, i.e., equal to Nr-1/2. From dose volume histograms the surviving fraction of cells, equivalent uniform dose (EUD), and TCP for the different scenarios were calculated. Comparably sized spherical models containing individual spherical cells (15 microm diameter) in hexagonal lattices were constructed, and Monte Carlo simulations were executed for all the same previous scenarios. The dosimetric quantities were calculated and compared to the adjusted simple sphere model results. The model was then applied to the Bortezomib-induced enzyme-targeted radiotherapy (BETR) strategy of targeting Epstein-Barr virus (EBV)-expressing cancers. RESULTS: The TCP values were comparable to within 2% between the adjusted simple sphere and full cellular models. Additionally, models were generated for a nonuniform distribution of activity, and results were compared between the adjusted spherical and cellular models with similar comparability. The TCP values from the experimental macroscopic tumor results were consistent with the experimental observations for BETR-treated 1 g EBV-expressing lymphoma tumors in mice. CONCLUSIONS: The adjusted spherical model presented here provides more accurate TCP values than simple spheres, on par with full cellular Monte Carlo simulations while maintaining the simplicity of the simple sphere model. This model provides a basis for complementing and understanding laboratory and clinical results pertaining to radiopharmaceutical therapy.

An Experimental Validation of a Statistical-Based Damage Detection Approach, January 2011

In this work, a previously-developed, statistical-based, damage-detection approach was validated for its ability to autonomously detect damage in bridges. The damage-detection approach uses statistical differences in the actual and predicted behavior of the bridge caused under a subset of ambient trucks. The predicted behavior is derived from a statistics-based model trained with field data from the undamaged bridge (not a finite element model). The differences between actual and predicted responses, called residuals, are then used to construct control charts, which compare undamaged and damaged structure data. Validation of the damage-detection approach was achieved by using sacrificial specimens that were mounted to the bridge and exposed to ambient traffic loads and which simulated actual damage-sensitive locations. Different damage types and levels were introduced to the sacrificial specimens to study the sensitivity and applicability. The damage-detection algorithm was able to identify damage, but it also had a high false-positive rate. An evaluation of the sub-components of the damage-detection methodology and methods was completed for the purpose of improving the approach. Several of the underlying assumptions within the algorithm were being violated, which was the source of the false-positives. Furthermore, the lack of an automatic evaluation process was thought to potentially be an impediment to widespread use. Recommendations for the improvement of the methodology were developed and preliminarily evaluated. These recommendations are believed to improve the efficacy of the damage-detection approach.

Spatial behavior in groups: an agent-based approach

We present an agent-based model with the aim of studying how macro-level dynamics of spatial distances among interacting individuals in a closed space emerge from micro-level dyadic and local interactions. Our agents moved on a lattice (referred to as a room) using a model implemented in a computer program called P-Space in order to minimize their dissatisfaction, defined as a function of the discrepancy between the real distance and the ideal, or desired, distance between agents. Ideal distances evolved in accordance with the agent's personal and social space, which changed throughout the dynamics of the interactions among the agents. In the first set of simulations we studied the effects of the parameters of the function that generated ideal distances, and in a second set we explored how group macrolevel behavior depended on model parameters and other variables. We learned that certain parameter values yielded consistent patterns in the agents' personal and social spaces, which in turn led to avoidance and approaching behaviors in the agents. We also found that the spatial behavior of the group of agents as a whole was influenced by the values of the model parameters, as well as by other variables such as the number of agents. Our work demonstrates that the bottom-up approach is a useful way of explaining macro-level spatial behavior. The proposed model is also shown to be a powerful tool for simulating the spatial behavior of groups of interacting individuals.

Development of a Subgrade Drainage Model for Unpaved Roads, TR-654, 2015

With over 68 thousand miles of gravel roads in Iowa and the importance of these roads within the farm-to-market transportation system, proper water management becomes critical for maintaining the integrity of the roadway materials. However, the build-up of water within the aggregate subbase can lead to frost boils and ultimately potholes forming at the road surface. The aggregate subbase and subgrade soils under these gravel roads are produced with material opportunistically chosen from local sources near the site and, many times, the compositions of these sublayers are far from ideal in terms of proper water drainage with the full effects of this shortcut not being fully understood. The primary objective of this project was to provide a physically-based model for evaluating the drainability of potential subbase and subgrade materials for gravel roads in Iowa. The Richards equation provided the appropriate framework to study the transient unsaturated flow that usually occurs through the subbase and subgrade of a gravel road. From which, we identified that the saturated hydraulic conductivity, Ks, was a key parameter driving the time to drain of subgrade soils found in Iowa, thus being a good proxy variable for accessing roadway drainability. Using Ks, derived from soil texture, we were able to identify potential problem areas in terms of roadway drainage . It was found that there is a threshold for Ks of 15 cm/day that determines if the roadway will drain efficiently, based on the requirement that the time to drain, Td, the surface roadway layer does not exceed a 2-hr limit. Two of the three highest abundant textures (loam and silty clay loam), which cover nearly 60% of the state of Iowa, were found to have average Td values greater than the 2-hr limit. With such a large percentage of the state at risk for the formation of boils due to the soil with relatively low saturated hydraulic conductivity values, it seems pertinent that we propose alternative design and/or maintenance practices to limit the expensive repair work in Iowa. The addition of drain tiles or French mattresses my help address drainage problems. However, before pursuing this recommendation, a comprehensive cost-benefit analysis is needed.

A statistical shape model of the human second cervical vertebra.

PURPOSE: Statistical shape and appearance models play an important role in reducing the segmentation processing time of a vertebra and in improving results for 3D model development. Here, we describe the different steps in generating a statistical shape model (SSM) of the second cervical vertebra (C2) and provide the shape model for general use by the scientific community. The main difficulties in its construction are the morphological complexity of the C2 and its variability in the population. METHODS: The input dataset is composed of manually segmented anonymized patient computerized tomography (CT) scans. The alignment of the different datasets is done with the procrustes alignment on surface models, and then, the registration is cast as a model-fitting problem using a Gaussian process. A principal component analysis (PCA)-based model is generated which includes the variability of the C2. RESULTS: The SSM was generated using 92 CT scans. The resulting SSM was evaluated for specificity, compactness and generalization ability. The SSM of the C2 is freely available to the scientific community in Slicer (an open source software for image analysis and scientific visualization) with a module created to visualize the SSM using Statismo, a framework for statistical shape modeling. CONCLUSION: The SSM of the vertebra allows the shape variability of the C2 to be represented. Moreover, the SSM will enable semi-automatic segmentation and 3D model generation of the vertebra, which would greatly benefit surgery planning.

Flocking behaviour: Agent-based simulation and hierarchical leadership.

We have studied how leaders emerge in a group as a consequence of interactions among its members. We propose that leaders can emerge as a consequence of a self-organized process based on local rules of dyadic interactions among individuals. Flocks are an example of self-organized behaviour in a group and properties similar to those observed in flocks might also explain some of the dynamics and organization of human groups. We developed an agent-based model that generated flocks in a virtual world and implemented it in a multi-agent simulation computer program that computed indices at each time step of the simulation to quantify the degree to which a group moved in a coordinated way (index of flocking behaviour) and the degree to which specific individuals led the group (index of hierarchical leadership). We ran several series of simulations in order to test our model and determine how these indices behaved under specific agent and world conditions. We identified the agent, world property, and model parameters that made stable, compact flocks emerge, and explored possible environmental properties that predicted the probability of becoming a leader.

Reward networks in the brain as captured by connectivity measures

An assortment of human behaviors is thought to be driven by rewards including reinforcement learning, novelty processing, learning, decision making, economic choice, incentive motivation, and addiction. In each case the ventral tegmental area/ventral striatum (nucleus accumbens) (VTAVS) system has been implicated as a key structure by functional imaging studies, mostly on the basis of standard, univariate analyses. Here we propose that standard functional magnetic resonance imaging analysis needs to be complemented by methods that take into account the differential connectivity of the VTAVS system in the different behavioral contexts in order to describe reward based processes more appropriately. We fi rst consider the wider network for reward processing as it emerged from animal experimentation. Subsequently, an example for a method to assess functional connectivity is given. Finally, we illustrate the usefulness of such analyses by examples regarding reward valuation, reward expectation and the role of reward in addiction.

Reflexive Space. A Constructionist Model of the Russian Reflexive Marker

This study examines the structure of the Russian Reflexive Marker ( ся/-сь) and offers a usage-based model building on Construction Grammar and a probabilistic view of linguistic structure. Traditionally, reflexive verbs are accounted for relative to non-reflexive verbs. These accounts assume that linguistic structures emerge as pairs. Furthermore, these accounts assume directionality where the semantics and structure of a reflexive verb can be derived from the non-reflexive verb. However, this directionality does not necessarily hold diachronically. Additionally, the semantics and the patterns associated with a particular reflexive verb are not always shared with the non-reflexive verb. Thus, a model is proposed that can accommodate the traditional pairs as well as for the possible deviations without postulating different systems. A random sample of 2000 instances marked with the Reflexive Marker was extracted from the Russian National Corpus and the sample used in this study contains 819 unique reflexive verbs. This study moves away from the traditional pair account and introduces the concept of Neighbor Verb. A neighbor verb exists for a reflexive verb if they share the same phonological form excluding the Reflexive Marker. It is claimed here that the Reflexive Marker constitutes a system in Russian and the relation between the reflexive and neighbor verbs constitutes a cross-paradigmatic relation. Furthermore, the relation between the reflexive and the neighbor verb is argued to be of symbolic connectivity rather than directionality. Effectively, the relation holding between particular instantiations can vary. The theoretical basis of the present study builds on this assumption. Several new variables are examined in order to systematically model variability of this symbolic connectivity, specifically the degree and strength of connectivity between items. In usage-based models, the lexicon does not constitute an unstructured list of items. Instead, items are assumed to be interconnected in a network. This interconnectedness is defined as Neighborhood in this study. Additionally, each verb carves its own niche within the Neighborhood and this interconnectedness is modeled through rhyme verbs constituting the degree of connectivity of a particular verb in the lexicon. The second component of the degree of connectivity concerns the status of a particular verb relative to its rhyme verbs. The connectivity within the neighborhood of a particular verb varies and this variability is quantified by using the Levenshtein distance. The second property of the lexical network is the strength of connectivity between items. Frequency of use has been one of the primary variables in functional linguistics used to probe this. In addition, a new variable called Constructional Entropy is introduced in this study building on information theory. It is a quantification of the amount of information carried by a particular reflexive verb in one or more argument constructions. The results of the lexical connectivity indicate that the reflexive verbs have statistically greater neighborhood distances than the neighbor verbs. This distributional property can be used to motivate the traditional observation that the reflexive verbs tend to have idiosyncratic properties. A set of argument constructions, generalizations over usage patterns, are proposed for the reflexive verbs in this study. In addition to the variables associated with the lexical connectivity, a number of variables proposed in the literature are explored and used as predictors in the model. The second part of this study introduces the use of a machine learning algorithm called Random Forests. The performance of the model indicates that it is capable, up to a degree, of disambiguating the proposed argument construction types of the Russian Reflexive Marker. Additionally, a global ranking of the predictors used in the model is offered. Finally, most construction grammars assume that argument construction form a network structure. A new method is proposed that establishes generalization over the argument constructions referred to as Linking Construction. In sum, this study explores the structural properties of the Russian Reflexive Marker and a new model is set forth that can accommodate both the traditional pairs and potential deviations from it in a principled manner.

Cell Model Systems in Characterizing Alpha2-Adrenoceptors as Drug Targets.

The three alpha2-adrenoceptor (alpha2-AR) subtypes belong to the G protein-coupled receptor superfamily and represent potential drug targets. These receptors have many vital physiological functions, but their actions are complex and often oppose each other. Current research is therefore driven towards discovering drugs that selectively interact with a specific subtype. Cell model systems can be used to evaluate a chemical compound's activity in complex biological systems. The aim of this thesis was to optimize and validate cell-based model systems and assays to investigate alpha2-ARs as drug targets. The use of immortalized cell lines as model systems is firmly established but poses several problems, since the protein of interest is expressed in a foreign environment, and thus essential components of receptor regulation or signaling cascades might be missing. Careful cell model validation is thus required; this was exemplified by three different approaches. In cells heterologously expressing alpha2A-ARs, it was noted that the transfection technique affected the test outcome; false negative adenylyl cyclase test results were produced unless a cell population expressing receptors in a homogenous fashion was used. Recombinant alpha2C-ARs in non-neuronal cells were retained inside the cells, and not expressed in the cell membrane, complicating investigation of this receptor subtype. Receptor expression enhancing proteins (REEPs) were found to be neuronalspecific adapter proteins that regulate the processing of the alpha2C-AR, resulting in an increased level of total receptor expression. Current trends call for the use of primary cells endogenously expressing the receptor of interest; therefore, primary human vascular smooth muscle cells (SMC) expressing alpha2-ARs were tested in a functional assay monitoring contractility with a myosin light chain phosphorylation assay. However, these cells were not compatible with this assay due to the loss of differentiation. A rat aortic SMC cell line transfected to express the human alpha2B-AR was adapted for the assay, and it was found that the alpha2-AR agonist, dexmedetomidine, evoked myosin light chain phosphorylation in this model.

Production unit’s overhead cost allocation with activity-based costing in food industry enterprise

The main objective of this Master’s thesis is to develop a cost allocation model for a leading food industry company in Finland. The goal is to develop an allocation method for fixed overhead expenses produced in a specific production unit and create a plausible tracking system for product costs. The second objective is to construct an allocation model and modify the created model to be suited for other units as well. Costs, activities, drivers and appropriate allocation methods are studied. This thesis is started with literature review of existing theory of ABC, inspecting cost information and then conducting interviews with officials to get a general view of the requirements for the model to be constructed. The familiarization of the company started with becoming acquainted with the existing cost accounting methods. The main proposals for a new allocation model were revealed through interviews, which were utilized in setting targets for developing the new allocation method. As a result of this thesis, an Excel-based model is created based on the theoretical and empiric data. The new system is able to handle overhead costs in more detail improving the cost awareness, transparency in cost allocations and enhancing products’ cost structure. The improved cost awareness is received by selecting the best possible cost drivers for this situation. Also the capacity changes are taken into consideration, such as usage of practical or normal capacity instead of theoretical is suggested to apply. Also some recommendations for further development are made about capacity handling and cost collection.

Les déterminants de l'épuisement professionnel et des troubles musculosquelettiques et leur cooccurrence chez les policiers

Ce mémoire est rédigé dans le cadre d’une recherche multidisciplinaire visant à développer de meilleurs outils d’intervention et politiques en santé mentale au travail. L’objectif principal de cette étude était de cibler les déterminants de l’épuisement professionnel et des troubles musculosquelettiques et leur cooccurrence chez une population policière. Un échantillon de 410 policiers du Service de Police de Montréal (SPVM) a été sondé à l’aide d’un questionnaire basé sur des outils standardisés en santé mentale au travail. Les conditions organisationnelles, variables indépendantes de cette étude, ont été identifiées à partir de modèles théoriques validés. L’analyse segmentée de chacun des grands concepts (latitude décisionnelle, soutien social au travail, demandes, justice distributive et sur engagement) révèle que l’effet des conditions organisationnelles ne se manifeste pas également sur chacune des trois dimensions de l’épuisement professionnel (l’épuisement émotionnel, le cynisme et l’efficacité professionnelle). De plus, on observe que les trois formes de récompenses de justice distributive tirées du modèle « Déséquilibre-Efforts-Récompenses » (Siegrist, 1996) ne sont pas distribuées également selon les dimensions de l’épuisement professionnel. Selon nos données, la justice distributive d’estime de soi et le sur engagement s’avèrent significatifs dans tous les cas en regard des dimensions de l’épuisement professionnel et de son indice global. Finalement, nos résultats révèlent que la justice distributive d’estime de soi a un lien significatif sur la cooccurrence de l’épuisement professionnel et des troubles musculosquelettiques. Par contre, on note que des outils de recherche plus spécifiques permettraient une analyse approfondie de l’effet des conditions organisationnelles sur les troubles musculosquelettiques et sur l’effet de cooccurrence entre les deux problèmes à l’étude.

Hessian-based occlusion-aware radiance caching

Simuler efficacement l'éclairage global est l'un des problèmes ouverts les plus importants en infographie. Calculer avec précision les effets de l'éclairage indirect, causés par des rebonds secondaires de la lumière sur des surfaces d'une scène 3D, est généralement un processus coûteux et souvent résolu en utilisant des algorithmes tels que le path tracing ou photon mapping. Ces techniquesrésolvent numériquement l'équation du rendu en utilisant un lancer de rayons Monte Carlo. Ward et al. ont proposé une technique nommée irradiance caching afin d'accélérer les techniques précédentes lors du calcul de la composante indirecte de l'éclairage global sur les surfaces diffuses. Krivanek a étendu l'approche de Ward et Heckbert pour traiter le cas plus complexe des surfaces spéculaires, en introduisant une approche nommée radiance caching. Jarosz et al. et Schwarzhaupt et al. ont proposé un modèle utilisant le hessien et l'information de visibilité pour raffiner le positionnement des points de la cache dans la scène, raffiner de manière significative la qualité et la performance des approches précédentes. Dans ce mémoire, nous avons étendu les approches introduites dans les travaux précédents au problème du radiance caching pour améliorer le positionnement des éléments de la cache. Nous avons aussi découvert un problème important négligé dans les travaux précédents en raison du choix des scènes de test. Nous avons fait une étude préliminaire sur ce problème et nous avons trouvé deux solutions potentielles qui méritent une recherche plus approfondie.

Example Based Learning for View-Based Human Face Detection

We present an example-based learning approach for locating vertical frontal views of human faces in complex scenes. The technique models the distribution of human face patterns by means of a few view-based "face'' and "non-face'' prototype clusters. At each image location, the local pattern is matched against the distribution-based model, and a trained classifier determines, based on the local difference measurements, whether or not a human face exists at the current image location. We provide an analysis that helps identify the critical components of our system.

Visual Segmentation without Classification in a Model of the Primary Visual Cortex

Stimuli outside classical receptive fields significantly influence the neurons' activities in primary visual cortex. We propose that such contextual influences are used to segment regions by detecting the breakdown of homogeneity or translation invariance in the input, thus computing global region boundaries using local interactions. This is implemented in a biologically based model of V1, and demonstrated in examples of texture segmentation and figure-ground segregation. By contrast with traditional approaches, segmentation occurs without classification or comparison of features within or between regions and is performed by exactly the same neural circuit responsible for the dual problem of the grouping and enhancement of contours.

Application of agent-based modeling to the study of gender stereotypes

Gender stereotypes are sets of characteristics that people believe to be typically true of a man or woman. We report an agent-based model (ABM) that simulates how stereotypes disseminate in a group through associative mechanisms. The model consists of agents that carry one of several different versions of a stereotype, which share part of their conceptual content. When an agent acts according to his/her stereotype, and that stereotype is shared by an observer, then the latter’s stereotype strengthens. Contrarily, if the agent does not act according to his/ her stereotype, then the observer’s stereotype weakens. In successive interactions, agents develop preferences, such that there will be a higher probability of interaction with agents that confirm their stereotypes. Depending on the proportion of shared conceptual content in the stereotype’s different versions, three dynamics emerge: all stereotypes in the population strengthen, all weaken, or a bifurcation occurs, i.e., some strengthen and some weaken. Additionally, we discuss the use of agent-based modeling to study social phenomena and the practical consequences that the model’s results might have on stereotype research and their effects on a community