A well-posedness theory in measures for some kinetic models of collective motion

We present existence, uniqueness and continuous dependence results for some kinetic equations motivated by models for the collective behavior of large groups of individuals. Models of this kind have been recently proposed to study the behavior of large groups of animals, such as flocks of birds, swarms, or schools of fish. Our aim is to give a well-posedness theory for general models which possibly include a variety of effects: an interaction through a potential, such as a short-range repulsion and long-range attraction; a velocity-averaging effect where individuals try to adapt their own velocity to that of other individuals in their surroundings; and self-propulsion effects, which take into account effects on one individual that are independent of the others. We develop our theory in a space of measures, using mass transportation distances. As consequences of our theory we show also the convergence of particle systems to their corresponding kinetic equations, and the local-in-time convergence to the hydrodynamic limit for one of the models.

Theoretical aspects of graph models for MANETs

We survey the main theoretical aspects of models for Mobile Ad Hoc Networks (MANETs). We present theoretical characterizations of mobile network structural properties, different dynamic graph models of MANETs, and finally we give detailed summaries of a few selected articles. In particular, we focus on articles dealing with connectivity of mobile networks, and on articles which show that mobility can be used to propagate information between nodes of the network while at the same time maintaining small transmission distances, and thus saving energy.

State-dependent threshold STAR models

In this paper we consider extensions of smooth transition autoregressive (STAR) models to situations where the threshold is a time-varying function of variables that affect the separation of regimes of the time series under consideration. Our specification is motivated by the observation that unusually high/low values for an economic variable may sometimes be best thought of in relative terms. State-dependent logistic STAR and contemporaneous-threshold STAR models are introduced and discussed. These models are also used to investigate the dynamics of U.S. short-term interest rates, where the threshold is allowed to be a function of past output growth and inflation.

Mixture of bivariate Poisson regression models with an application to insurance

In a recent paper Bermúdez [2009] used bivariate Poisson regression models for ratemaking in car insurance, and included zero-inflated models to account for the excess of zeros and the overdispersion in the data set. In the present paper, we revisit this model in order to consider alternatives. We propose a 2-finite mixture of bivariate Poisson regression models to demonstrate that the overdispersion in the data requires more structure if it is to be taken into account, and that a simple zero-inflated bivariate Poisson model does not suffice. At the same time, we show that a finite mixture of bivariate Poisson regression models embraces zero-inflated bivariate Poisson regression models as a special case. Additionally, we describe a model in which the mixing proportions are dependent on covariates when modelling the way in which each individual belongs to a separate cluster. Finally, an EM algorithm is provided in order to ensure the models’ ease-of-fit. These models are applied to the same automobile insurance claims data set as used in Bermúdez [2009] and it is shown that the modelling of the data set can be improved considerably.

Tethyan margins in space and time

Rifting processes, leading to sea-floor spreading, are characterized by a sequence of events: transtensive phase of extension with syn-rift volcanism; simple shear extension accompanied by lithospheric thinning and asthenospheric up-welling and thermal uplift of the rift shoulder and asymmetric volcanism. The simple shear model of extension leads to an asymmetric model of passive margin: a lower plate tilted block margin and an upper plate flexural, ramp-like margin- Both will be affected by thermal contraction and subsidence, starting soon after sea-floor spreading. Based on these actualistic models Tethyan margins are classified as one type or the other. Their evolution from the first transtensional phase of extension to the passive margin stage are analyzed. Four main rifting events are recognized in the Tethyan realm: an episode of lower Paleozoic events leading to the formation of the Paleotethys; a Late Paleozoic event leading to the opening of the Permotethys and East Mediterranean basin: an early Mesozoic event leading to the opening of the Pindos Neotethys and a Jurassic event related to the opening of the Alpine/Atlantic Neotethys. Type margins are given as example of each rifting event: -Northern Iran (Alborz) as a type area for the Late Ordovician to Silurian rifting of Paleotethys. -Northern India and Oman for the Late Carboniferous to early Permian rifting of Permotethys. -The East Mediterranean (Levant, Tunisia) as a Late Carboniferous rifting event. -The Neotethyan rifting phases are separated in two types: an eastern Pindos system found in Turkey and Greece is genetically linked to the Permotethys with a sea-floor spreading delayed until middle Triassic: a western Alpine system directly linked to the opening of the central Atlantic is characterized by a Late Triassic transtensive phase, an early to Middle Liassic break-away phase and. following sea-floor spreading, a thermal subsidence phase starting in Dogger. Problems related to the closure of the Paleozoic oceanic domains are reviewed. A Late Permian, early Triassic phase of `'docking'' between an European accretionary prism (Chios) and a Paleotethyan margin is supported by recent findings in the Mediterranean area. Back-arc rifting within the European active margin led to the formation of marginal seas during Permian and Triassic times and will contribute to the closure of the Paleozoic oceans.

Documenting a time-bound, circular view of hierarchies: a microanalysis of parent-infant dyadic interaction.

This article presents a new theory that separates the levels of communication and relates them circularly, namely, by separating time from space/meaning variables. Documenting this proposition requires sequential microdescriptions--a far-out project in the field of family therapy. In an extensive study of clinical and nonclinical families, starting with available microanalytic data on nonverbal parent-infant dialogue, distinct time organizations have been found to modify the degree of circularity between the levels of interaction according to the observed types of engagement, that is, consensual, conflictual, and paradoxical. The double description of the dyad as a totality versus the dyad as a framing/developing organization imparts crucial information on how development proceeds in dyadic, co-evolutive systems, and presumably in larger ones too. In this perspective, a model is elaborated and then applied to a case description in our therapeutic consultation.

Niche dynamics in space and time.

Niche conservatism, the tendency of a species niche to remain unchanged over time, is often assumed when discussing, explaining or predicting biogeographical patterns. Unfortunately, there has been no basis for predicting niche dynamics over relevant timescales, from tens to a few hundreds of years. The recent application of species distribution models (SDMs) and phylogenetic methods to analysis of niche characteristics has provided insight to niche dynamics. Niche shifts and conservatism have both occurred within the last 100 years, with recent speciation events, and deep within clades of species. There is increasing evidence that coordinated application of these methods can help to identify species which likely fulfill one key assumption in the predictive application of SDMs: an unchanging niche. This will improve confidence in SDM-based predictions of the impacts of climate change and species invasions on species distributions and biodiversity.

Multivariate ARIMA Compositional Time Series Analysis

A compositional time series is obtained when a compositional data vector is observed atdifferent points in time. Inherently, then, a compositional time series is a multivariatetime series with important constraints on the variables observed at any instance in time.Although this type of data frequently occurs in situations of real practical interest, atrawl through the statistical literature reveals that research in the field is very much in itsinfancy and that many theoretical and empirical issues still remain to be addressed. Anyappropriate statistical methodology for the analysis of compositional time series musttake into account the constraints which are not allowed for by the usual statisticaltechniques available for analysing multivariate time series. One general approach toanalyzing compositional time series consists in the application of an initial transform tobreak the positive and unit sum constraints, followed by the analysis of the transformedtime series using multivariate ARIMA models. In this paper we discuss the use of theadditive log-ratio, centred log-ratio and isometric log-ratio transforms. We also presentresults from an empirical study designed to explore how the selection of the initialtransform affects subsequent multivariate ARIMA modelling as well as the quality ofthe forecasts

Compositional Time Series: An Application

The composition of the labour force is an important economic factor for a country.Often the changes in proportions of different groups are of interest.I this paper we study a monthly compositional time series from the Swedish LabourForce Survey from 1994 to 2005. Three models are studied: the ILR-transformed series,the ILR-transformation of the compositional differenced series of order 1, and the ILRtransformationof the compositional differenced series of order 12. For each of thethree models a VAR-model is fitted based on the data 1994-2003. We predict the timeseries 15 steps ahead and calculate 95 % prediction regions. The predictions of thethree models are compared with actual values using MAD and MSE and the predictionregions are compared graphically in a ternary time series plot.We conclude that the first, and simplest, model possesses the best predictive power ofthe three models

Gut Microbiota Composition in Male Rat Models under Different Nutritional Status and Physical Activity and Its Association with Serum Leptin and Ghrelin Levels.

BACKGROUND Several evidences indicate that gut microbiota is involved in the control of host energy metabolism. OBJECTIVE To evaluate the differences in the composition of gut microbiota in rat models under different nutritional status and physical activity and to identify their associations with serum leptin and ghrelin levels. METHODS IN A CASE CONTROL STUDY, FORTY MALE RATS WERE RANDOMLY ASSIGNED TO ONE OF THESE FOUR EXPERIMENTAL GROUPS: ABA group with food restriction and free access to exercise; control ABA group with food restriction and no access to exercise; exercise group with free access to exercise and feed ad libitum and ad libitum group without access to exercise and feed ad libitum. The fecal bacteria composition was investigated by PCR-denaturing gradient gel electrophoresis and real-time qPCR. RESULTS In restricted eaters, we have found a significant increase in the number of Proteobacteria, Bacteroides, Clostridium, Enterococcus, Prevotella and M. smithii and a significant decrease in the quantities of Actinobacteria, Firmicutes, Bacteroidetes, B. coccoides-E. rectale group, Lactobacillus and Bifidobacterium with respect to unrestricted eaters. Moreover, a significant increase in the number of Lactobacillus, Bifidobacterium and B. coccoides-E. rectale group was observed in exercise group with respect to the rest of groups. We also found a significant positive correlation between the quantity of Bifidobacterium and Lactobacillus and serum leptin levels, and a significant and negative correlation among the number of Clostridium, Bacteroides and Prevotella and serum leptin levels in all experimental groups. Furthermore, serum ghrelin levels were negatively correlated with the quantity of Bifidobacterium, Lactobacillus and B. coccoides-Eubacterium rectale group and positively correlated with the number of Bacteroides and Prevotella. CONCLUSIONS Nutritional status and physical activity alter gut microbiota composition affecting the diversity and similarity. This study highlights the associations between gut microbiota and appetite-regulating hormones that may be important in terms of satiety and host metabolism.

Adolescent survivors of childhood cancer: are they vulnerable for psychological distress?

OBJECTIVES: We aimed to (i) evaluate psychological distress in adolescent survivors of childhood cancer and compare them to siblings and a norm population; (ii) compare the severity of distress of distressed survivors and siblings with that of psychotherapy patients; and (iii) determine risk factors for psychological distress in survivors. METHODS: We sent a questionnaire to all childhood cancer survivors aged <16 years when diagnosed, who had survived ≥ 5 years and were aged 16-19 years at the time of study. Our control groups were same-aged siblings, a norm population, and psychotherapy patients. Psychological distress was measured with the Brief Symptom Inventory-18 (BSI-18) assessing somatization, depression, anxiety, and a global severity index (GSI). Participants with a T-score ≥ 57 were defined as distressed. We used logistic regression to determine risk factors. RESULTS: We evaluated the BSI-18 in 407 survivors and 102 siblings. Fifty-two survivors (13%) and 11 siblings (11%) had scores above the distress threshold (T ≥ 57). Distressed survivors scored significantly higher in somatization (p=0.027) and GSI (p=0.016) than distressed siblings, and also scored higher in somatization (p ≤ 0.001) and anxiety (p=0.002) than psychotherapy patients. In the multivariable regression, psychological distress was associated with female sex, self-reported late effects, and low perceived parental support. CONCLUSIONS: The majority of survivors did not report psychological distress. However, the severity of distress of distressed survivors exceeded that of distressed siblings and psychotherapy patients. Systematic psychological follow-up can help to identify survivors at risk and support them during the challenging period of adolescence.

Study and implementation of some quantitative trading models

Quantitative or algorithmic trading is the automatization of investments decisions obeying a fixed or dynamic sets of rules to determine trading orders. It has increasingly made its way up to 70% of the trading volume of one of the biggest financial markets such as the New York Stock Exchange (NYSE). However, there is not a signi cant amount of academic literature devoted to it due to the private nature of investment banks and hedge funds. This projects aims to review the literature and discuss the models available in a subject that publications are scarce and infrequently. We review the basic and fundamental mathematical concepts needed for modeling financial markets such as: stochastic processes, stochastic integration and basic models for prices and spreads dynamics necessary for building quantitative strategies. We also contrast these models with real market data with minutely sampling frequency from the Dow Jones Industrial Average (DJIA). Quantitative strategies try to exploit two types of behavior: trend following or mean reversion. The former is grouped in the so-called technical models and the later in the so-called pairs trading. Technical models have been discarded by financial theoreticians but we show that they can be properly cast into a well defined scientific predictor if the signal generated by them pass the test of being a Markov time. That is, we can tell if the signal has occurred or not by examining the information up to the current time; or more technically, if the event is F_t-measurable. On the other hand the concept of pairs trading or market neutral strategy is fairly simple. However it can be cast in a variety of mathematical models ranging from a method based on a simple euclidean distance, in a co-integration framework or involving stochastic differential equations such as the well-known Ornstein-Uhlenbeck mean reversal ODE and its variations. A model for forecasting any economic or financial magnitude could be properly defined with scientific rigor but it could also lack of any economical value and be considered useless from a practical point of view. This is why this project could not be complete without a backtesting of the mentioned strategies. Conducting a useful and realistic backtesting is by no means a trivial exercise since the \laws" that govern financial markets are constantly evolving in time. This is the reason because we make emphasis in the calibration process of the strategies' parameters to adapt the given market conditions. We find out that the parameters from technical models are more volatile than their counterpart form market neutral strategies and calibration must be done in a high-frequency sampling manner to constantly track the currently market situation. As a whole, the goal of this project is to provide an overview of a quantitative approach to investment reviewing basic strategies and illustrating them by means of a back-testing with real financial market data. The sources of the data used in this project are Bloomberg for intraday time series and Yahoo! for daily prices. All numeric computations and graphics used and shown in this project were implemented in MATLAB^R scratch from scratch as a part of this thesis. No other mathematical or statistical software was used.

The Limits of Discrete Time Repeated Games:Some Notes and Comments

This paper studies the limits of discrete time repeated games with public monitoring. We solve and characterize the Abreu, Milgrom and Pearce (1991) problem. We found that for the "bad" ("good") news model the lower (higher) magnitude events suggest cooperation, i.e., zero punishment probability, while the highrt (lower) magnitude events suggest defection, i.e., punishment with probability one. Public correlation is used to connect these two sets of signals and to make the enforceability to bind. The dynamic and limit behavior of the punishment probabilities for variations in ... (the discount rate) and ... (the time interval) are characterized, as well as the limit payo¤s for all these scenarios (We also introduce uncertainty in the time domain). The obtained ... limits are to the best of my knowledge, new. The obtained ... limits coincide with Fudenberg and Levine (2007) and Fudenberg and Olszewski (2011), with the exception that we clearly state the precise informational conditions that cause the limit to converge from above, to converge from below or to degenerate. JEL: C73, D82, D86. KEYWORDS: Repeated Games, Frequent Monitoring, Random Pub- lic Monitoring, Moral Hazard, Stochastic Processes.

The administration of atomoxetine during alcohol deprivation induces a time-limited increase in alcohol consumption after relapse.

The administration of selective serotonin reuptake inhibitors (SSRIs) typically used as antidepressants increases alcohol consumption after an alcohol deprivation period in rats. However, the appearance of this effect after the treatment with selective noradrenaline reuptake inhibitors (SNRIs) has not been studied. In the present work we examined the effects of a 15-d treatment with the SNRI atomoxetine (1, 3 and 10 mg/kg, i.p.) in male rats trained to drink alcohol solutions in a 4-bottle choice test. The treatment with atomoxetine (10 mg/kg, i.p.) during an alcohol deprivation period increased alcohol consumption after relapse. This effect only lasted one week, disappearing thereafter. Treatment with atomoxetine did not cause a behavioral sensitized response to a challenge dose of amphetamine (1.5 mg/kg, i.p.), indicating the absence of a supersensitive dopaminergic transmission. This effect is markedly different from that of SSRI antidepressants that produced both long-lasting increases in alcohol consumption and behavioral sensitization. Clinical implications are discussed.

Space-time relatedness and Hamilton's rule for long-lasting behaviors in viscous populations.

Genes affect not only the behavior and fitness of their carriers but also that of other individuals. According to Hamilton's rule, whether a mutant gene will spread in the gene pool depends on the effects of its carrier on the fitness of all individuals in the population, each weighted by its relatedness to the carrier. However, social behaviors may affect not only recipients living in the generation of the actor but also individuals living in subsequent generations. In this note, I evaluate space-time relatedness coefficients for localized dispersal. These relatedness coefficients weight the selection pressures on long-lasting behaviors, which stem from a multigenerational gap between phenotypic expression by actors and the resulting environmental feedback on the fitness of recipients. Explicit values of space-time relatedness coefficients reveal that they can be surprisingly large for typical dispersal rates, even for hundreds of generations in the future.