A spatially explicit Markovian individual-based model for terrestrial plant dynamics

An individual-based model (IBM) of a spatiotemporal terrestrial ecological population is proposed. This model is spatially explicit and features the position of each individual together with another characteristic, such as the size of the individual, which evolves according to a given stochastic model. The population is locally regulated through an explicit competition kernel. The IBM is represented as a measure-valued branching/diffusing stochastic process. The approach allows (i) to describe the associated Monte Carlo simulation and (ii) to analyze the limit process under large initial population size asymptotic. The limit macroscopic model is a deterministic integro-differential equation.Comment: 31 pages, 1 figur

Stochastic models of the chemostat

We consider the modeling of the dynamics of the chemostat at its very source. The chemostat is classically represented as a system of ordinary differential equations. Our goal is to establish a stochastic model that is valid at the scale immediately preceding the one corresponding to the deterministic model. At a microscopic scale we present a pure jump stochastic model that gives rise, at the macroscopic scale, to the ordinary differential equation model. At an intermediate scale, an approximation diffusion allows us to propose a model in the form of a system of stochastic differential equations. We expound the mechanism to switch from one model to another, together with the associated simulation procedures. We also describe the domain of validity of the different models

Estimation of the parameters of a stochastic logistic growth model

We consider a stochastic logistic growth model involving both birth and death rates in the drift and diffusion coefficients for which extinction eventually occurs almost surely. The associated complete Fokker-Planck equation describing the law of the process is established and studied. We then use its solution to build a likelihood function for the unknown model parameters, when discretely sampled data is available. The existing estimation methods need adaptation in order to deal with the extinction problem. We propose such adaptations, based on the particular form of the Fokker-Planck equation, and we evaluate their performances with numerical simulations. In the same time, we explore the identifiability of the parameters which is a crucial problem for the corresponding deterministic (noise free) model

Expertise or Experience: What Raises Pay?

An equilibrium job search model with on-the-job-search is presented and solved, in which we allow firms to implement optimal wage posting strategies in the sense that they leave no rent to their employees and counter the offers received by their employees from competing firms. Cross-firm productivity dispersion arises endogenously in equilibrium. The model delivers a hump-shaped aggregate earnings distribution that reflects both firm- and worker-heterogeneity. The model also generates plausible individual career paths on the basis of which it is estimated, using a French panel of wages over the period 1994-96.

The Challenge of Believability in Video Games: Definitions, Agents Models and Imitation Learning

In this paper, we address the problem of creating believable agents (virtual characters) in video games. We consider only one meaning of believability, ``giving the feeling of being controlled by a player'', and outline the problem of its evaluation. We present several models for agents in games which can produce believable behaviours, both from industry and research. For high level of believability, learning and especially imitation learning seems to be the way to go. We make a quick overview of different approaches to make video games' agents learn from players. To conclude we propose a two-step method to develop new models for believable agents. First we must find the criteria for believability for our application and define an evaluation method. Then the model and the learning algorithm can be designed

Learning a Representation of a Believable Virtual Character's Environment with an Imitation Algorithm

In video games, virtual characters' decision systems often use a simplified representation of the world. To increase both their autonomy and believability we want those characters to be able to learn this representation from human players. We propose to use a model called growing neural gas to learn by imitation the topology of the environment. The implementation of the model, the modifications and the parameters we used are detailed. Then, the quality of the learned representations and their evolution during the learning are studied using different measures. Improvements for the growing neural gas to give more information to the character's model are given in the conclusion

Biological effects of phytocannabinoids and endocannabinoids on oestrogen receptor-positive (ER+) breast cancer cells

Tese de mestrado, Ciências Biofarmacêuticas, Universidade de Lisboa, Faculdade de Farmácia, 2018Breast cancer is one of the most common forms of cancer worldwide and the second leading cause of cancer-related death. Oestrogen receptor positive (ER+) breast cancer makes up the majority of breast cancer cases, where oestrogens play a key role in promoting cancer cell growth and tumour progression. Besides the therapeutic success of the endocrine therapies and their clinical effectiveness in the treatment of this type of tumours, the side effects associated with these therapies, along with the development of endocrine resistance, emphasise the importance and the need to find new and improved therapies. In recent years, several studies on different cancer cell models, including breast cancer, have demonstrated and enhanced the anticancer properties of cannabinoids. Considering this, in this study, the in vitro effects of the phytocannabinoids, cannabidiol (CBD) and Δ9-tetrahydrocannabinol (THC), as well as of the endocannabinoid anandamide (AEA), were investigated on an ER+ breast cancer cell line that overexpresses the enzyme aromatase (MCF-7aro) and on a resistant ER+ breast cancer cell line (LTEDaro), which mimics the late-stage of resistance to endocrine therapy. A non-tumour fibroblastic cell line (HFF-1) was also used to explore whether these compounds are toxic towards non-cancerous cells. Our results demonstrate that AEA, CBD and THC are non-toxic towards the non-cancerous cells, and have the ability to reduce MCF-7aro cell viability and inhibit and decrease the levels of aromatase, as well as ERα, in these cells. Moreover, in MCF-7aro cells, these compounds also caused cell cycle arrest and induced apoptotic cell death in, through the mitochondrial pathway. Curiously, AEA and CBD also caused an up-regulation of ERβ levels in these cells, which along with aromatase inhibition may be a therapeutic advantage for this type of tumour. Contrary to CBD, the effects induced by THC on these cells were dependent on cannabinoid receptors CB1 and CB2, while for AEA were only CB2-dependent. In addition, it was also shown that CBD induced autophagy in MCF-7aro cells as a promoter mechanism of apoptosis. Interestingly, the resistant LTEDaro cells were sensitive to cannabinoid treatment. In conclusion, these cannabinoids show promising anti-tumour properties regarding ER+ breast cancer treatment, and even in cases of late-stage resistance. Thus, the results from this study will provide relevant information for future research involving cannabinoids and cancer, which may lead to their potential use in the clinic for the treatment of this disease.O cancro de mama é uma das formas mais comuns de cancro em todo o mundo e a segunda principal causa de morte relacionada com cancro. A maioria dos casos de cancro de mama são recetor de estrogénio positivo (ER+), onde os estrogénios desempenham um papel fundamental na promoção do crescimento e progressão do tumor. No entanto, apesar do sucesso terapêutico e da eficácia clínica das terapias endócrinas utilizadas neste tipo de tumores, os efeitos adversos associados a estas terapias, juntamente com o desenvolvimento de resistência endócrina, realçam a importância e a necessidade da procura de novas terapias mais eficazes. Nos últimos anos, vários estudos em diferentes modelos celulares, incluindo cancro de mama, demonstraram a possível relevância das propriedades anticancerígenas dos canabinóides. Tendo isto em consideração, neste trabalho foram estudados os efeitos in vitro dos fitocanabinóides, canabidiol (CBD) e Δ9-tetrahidrocanabinol (THC), assim como do endocanabinóide anandamida (AEA), numa linha celular de cancro de mama ER+ que sobreexpressa a enzima aromatase (MCF-7aro) e numa linha celular resistente de cancro de mama ER+ (LTEDaro), que mimetiza a fase tardia da resistência à terapia endócrina. Uma linha celular de fibroblastos não-tumoral (HFF-1) foi também utilizada, de forma a explorar se estes compostos são tóxicos para células não-cancerígenas. Os nossos resultados demonstram que AEA, CBD e THC não são tóxicos para as células não-cancerígenas, contudo têm a capacidade de reduzir a viabilidade das células MCF-7aro e inibir e diminuir os níveis da aromatase, bem como do ERα. Além disso, em células MCF-7aro, estes compostos causaram uma paragem do ciclo celular e induziram a morte celular por apoptose, através da via mitocondrial. Curiosamente, AEA e CBD também causaram um aumento dos níveis do ERβ nessas células, o que, juntamente com a inibição da aromatase, poderá ser uma vantagem terapêutica para esse tipo de tumores. Ao contrário do CBD, os efeitos induzidos pelo THC nestas células foram dependentes dos recetores canabinóides CB1 e CB2, enquanto que para a AEA foram apenas dependentes do CB2. Para além disso, foi demonstrado também que o CBD induziu autofagia nas células MCF-7aro como um mecanismo promotor da apoptose. Curiosamente, as células resistentes LTEDaro foram sensíveis ao tratamento com os canabinóides. Em conclusão, estes canabinóides apresentaram propriedades anti-tumorais promissoras para o tratamento do cancro de mama ER+, até mesmo em casos de uma resistência tardia. Assim, os resultados deste estudo poderão fornecer informações relevantes para pesquisas futuras envolvendo canabinóides e cancro, o que poderá conduzir ao seu potencial uso na clínica para o tratamento desta doença.This project had the financial support from Fundação para a Ciência e Tecnologia (FCT), through the attribution of the Post-Doc grant to Cristina Amaral (SFRH/BPD/98304/2013) and by the project FCT/MEC (UID/MULTI/04378/2013 – POCI/01/0145/FEDER/007728), co-financed by FEDER and by national funds, under the Partnership Agreement PT2020

A novel experimental method for the measurement of the caloric curves of clusters

A novel experimental scheme has been developed in order to measure the heat capacity of mass selected clusters. It is based on controlled sticking of atoms on clusters. This allows one to construct the caloric curve, thus determining the melting temperature and the latent heat of fusion in the case of first-order phase transitions. This method is model-free. It is transferable to many systems since the energy is brought to clusters through sticking collisions. As an example, it has been applied to Na\_90\^+ and Na\_140\^+. Our results are in good agreement with previous measurements

Synthesis of variable dancing styles based on a compact spatiotemporal representation of dance

Dance as a complex expressive form of motion is able to convey emotion, meaning and social idiosyncrasies that opens channels for non-verbal communication, and promotes rich cross-modal interactions with music and the environment. As such, realistic dancing characters may incorporate crossmodal information and variability of the dance forms through compact representations that may describe the movement structure in terms of its spatial and temporal organization. In this paper, we propose a novel method for synthesizing beatsynchronous dancing motions based on a compact topological model of dance styles, previously captured with a motion capture system. The model was based on the Topological Gesture Analysis (TGA) which conveys a discrete three-dimensional point-cloud representation of the dance, by describing the spatiotemporal variability of its gestural trajectories into uniform spherical distributions, according to classes of the musical meter. The methodology for synthesizing the modeled dance traces back the topological representations, constrained with definable metrical and spatial parameters, into complete dance instances whose variability is controlled by stochastic processes that considers both TGA distributions and the kinematic constraints of the body morphology. In order to assess the relevance and flexibility of each parameter into feasibly reproducing the style of the captured dance, we correlated both captured and synthesized trajectories of samba dancing sequences in relation to the level of compression of the used model, and report on a subjective evaluation over a set of six tests. The achieved results validated our approach, suggesting that a periodic dancing style, and its musical synchrony, can be feasibly reproduced from a suitably parametrized discrete spatiotemporal representation of the gestural motion trajectories, with a notable degree of compression