Population ageing, longevity and migration: an overlapping generations approach

The silent demographic revolution characterizing the main industrialized countries is an unavoidable factor which has major economic, social, cultural and psychological implications. This thesis studies the main consequences of population ageing and the connections with the phenomenon of migration, The theoretical analysis is developed using Overlapping Generations Models (OLG). The thesis is divided in the following four chapters: 1) “A Model for Determining Consumption and Social Assistance Demand in Uncertainty Conditions”, focuses on the relation between demographic impact and social insurance and proposes the institution of a non selfsufficiency fund for the elderly. 2) "Population Ageing, Longevity and Health", analyzes the effects of health investment on intertemporal individual behaviour and capital accumulation. 3) "Population Ageing and the Nursing Flow", studies the consequences of migration in the nursing sector. 4) "Quality of Multiculturalism and Minorities' Assimilation", focuses on the problem of assimilation and integration of minorities.

Genetic characterization, population history and evolutionary medicine perspective in two native south american populations: Yanesha and Wichi

Two Amerindian populations from the Peruvian Amazon (Yanesha) and from rural lowlands of the Argentinean Gran Chaco (Wichi) were analyzed. They represent two case study of the South American genetic variability. The Yanesha represent a model of population isolated for long-time in the Amazon rainforest, characterized by environmental and altitudinal stratifications. The Wichi represent a model of population living in an area recently colonized by European populations (the Criollos are the population of the admixed descendents), whose aim is to depict the native ancestral gene pool and the degree of admixture, in relation to the very high prevalence of Chagas disease. The methods used for the genotyping are common, concerning the Y chromosome markers (male lineage) and the mitochondrial markers (maternal lineage). The determination of the phylogeographic diagnostic polymorphisms was carried out by the classical techniques of PCR, restriction enzymes, sequencing and specific mini-sequencing. New method for the detection of the protozoa Trypanosoma cruzi was developed by means of the nested PCR. The main results show patterns of genetic stratification in Yanesha forest communities, referable to different migrations at different times, estimated by Bayesian analyses. In particular Yanesha were considered as a population of transition between the Amazon basin and the Andean Cordillera, evaluating the potential migration routes and the separation of clusters of community in relation to different genetic bio-ancestry. As the Wichi, the gene pool analyzed appears clearly differentiated by the admixed sympatric Criollos, due to strict social practices (deeply analyzed with the support of cultural anthropological tools) that have preserved the native identity at a diachronic level. A pattern of distribution of the seropositivity in relation to the different phylogenetic lineages (the adaptation in evolutionary terms) does not appear, neither Amerindian nor European, but in relation to environmental and living conditions of the two distinct subpopulations.

Work and Family: a complex interplay. An Italian application of the DISC Model on health care workers

The present thesis investigates the issue of work-family conflict and facilitation in a sanitarian contest, using the DISC Model (De Jonge and Dormann, 2003, 2006). The general aim has been declined in two empirical studies reported in this dissertation chapters. Chapter 1 reporting the psychometric properties of the Demand-Induced Strain Compensation Questionnaire. Although the empirical evidence on the DISC Model has received a fair amount of attention in literature both for the theoretical principles and for the instrument developed to display them (DISQ; De Jonge, Dormann, Van Vegchel, Von Nordheim, Dollard, Cotton and Van den Tooren, 2007) there are no studies based solely on psychometric investigation of the instrument. In addition, no previous studies have ever used the DISC as a model or measurement instrument in an Italian context. Thus the first chapter of the present dissertation was based on psychometric investigation of the DISQ. Chapter 2 reporting a longitudinal study contribution. The purpose was to examine, using the DISC model, the relationship between emotional job characteristics, work-family interface and emotional exhaustion among a health care population. We started testing the Triple Match Principle of the DISC Model using solely the emotional dimension of the strain-stress process (i.e. emotional demands, emotional resources and emotional exhaustion). Then we investigated the mediator role played by w-f conflict and w-f facilitation in relation to emotional job characteristics and emotional exhaustion. Finally we compared the mediator model across workers involved in chronic illness home demands and workers who are not involved. Finally, a general conclusion, integrated and discussed the main findings of the studies reported in this dissertation.

The role of EBI-3 in a murine model of lung metastases of melanoma

In dieser Arbeit wurde die Rolle des Epstein-Barr Virus induzierten Gens 3 in einem Mausmodel des durch B16-F10 Zellen hervorgerufenen metastasierenden Melanoms untersucht. Das von aktivierten antigenpräsentierenden Zellen exprimierte EBI-3 gehört zur Familie der löslichen Typ 1 Zytokinrezeptoren, weist eine hohe Homologie zur p40 Untereinheit des IL-12 auf und bildet zusammen mit p28 das IL-27. Die intravenöse Injektion der B16-F10 Zelllinie führte zu einer signifikanten Erniedrigung der Tumormetastasen in den EBI-3 defizienten Lungen sowie zu einer höheren Lebenserwartung dieser Mäuse im Vergleich zu den B6 Wildtypen. Darüber hinaus habe ich in den EBI-3 defizienten Mäusen eine verminderte VCAM-1 Expression auf den Endothelzellen der Lunge gefunden während Änderungen in der VEGF Expression nicht detektiert wurden. Der immunologische Hintergrund, der diesen therapeutischen Effekt hervorrief, konnte durch die T-Zellaktivierung durch die kürzlich neu beschriebene DC Population, welche Interferon-produzierende Killer Dendritische Zellen genannt werden (IK-DC), die zusätzlich von aktivierten und maturierten klassischen DCs unterstützt wurden, erklärt werden. IK-DCs von EBI-3 defizienten Mäusen produzierten höhere Mengen an IFN-g während die klassischen DCs MHC und co-stimulatorische Moleküle exprimierten, welche die Sekretion von IL-12 initiierten. Das Zusammenspiel der genannten Faktoren induzierte eine verstärkte CD4 und CD8 T-Zellantwort in den Lungen dieser Mäuse. Dies wiederum resultierte im TNF- und TRAIL abhängigen programmierten Zelltod der B16-F10 Melanomzellen in den Lungen der EBI-3 defizienten Mäuse, wohingegen sowohl weitere anti-apoptotische Mechanismen als auch T regulatorische Zellen keinen Einfluss auf die in den EBI-3 defizienten Mäusen beobachtete Tumorabwehr zu spielen scheint. Schlussendlich konnten EBI-3 defiziente CD8+ T-Zellen, welche zuvor mit Tumorantigen geprimed wurden, adoptiv in B6 Wildtypmäuse transferiert werden, was zeigte, dass diese Zellen in der Lage sind, die Tumormasse in den Empfängermäusen signifikant zu verringern. Zusammengefasst, demonstrieren diese Daten, dass das Blockieren von EBI-3 im metastasierenden Melanom ein vielversprechender Angriffspunkt in der Tumortherapie darstellt.

Urban water demand model: the case study of Emilia Romagna (Italy)

Water is the driving force in nature. We use water for washing cars, doing laundry, cooking, taking a shower, but also to generate energy and electricity. Therefore water is a necessary product in our daily lives (USGS. Howard Perlman, 2013). The model that we created is based on the urban water demand computer model from the Pacific Institute (California). With this model we will forecast the future urban water use of Emilia Romagna up to the year of 2030. We will analyze the urban water demand in Emilia Romagna that includes the 9 provinces: Bologna, Ferrara, Forli-Cesena, Modena, Parma, Piacenza, Ravenna, Reggio Emilia and Rimini. The term urban water refers to the water used in cities and suburbs and in homes in the rural areas. This will include the residential, commercial, institutional and the industrial use. In this research, we will cover the water saving technologies that can help to save water for daily use. We will project what influence these technologies have to the urban water demand, and what it can mean for future urban water demands. The ongoing climate change can reduce the snowpack, and extreme floods or droughts in Italy. The changing climate and development patterns are expected to have a significant impact on water demand in the future. We will do this by conducting different scenario analyses, by combining different population projections, climate influence and water saving technologies. In addition, we will also conduct a sensitivity analyses. The several analyses will show us how future urban water demand is likely respond to changes in water conservation technologies, population, climate, water price and consumption. I hope the research can contribute to the insight of the reader’s thoughts and opinion.

Maternal Smoking Impact on the Delivery Cost: a population-based study in the Emilia-Romagna region

This doctoral thesis is devoted to the study of the causal effects of the maternal smoking on the delivery cost. The interest of economic consequences of smoking in pregnancy have been studied fairly extensively in the USA, and very little is known in European context. To identify the causal relation between different maternal smoking status and the delivery cost in the Emilia-Romagna region two distinct methods were used. The first - geometric multidimensional - is mainly based on the multivariate approach and involves computing and testing the global imbalance, classifying cases in order to generate well-matched comparison groups, and then computing treatment effects. The second - structural modelling - refers to a general methodological account of model-building and model-testing. The main idea of this approach is to decompose the global mechanism into sub-mechanisms though a recursive decomposition of a multivariate distribution.

Validation of statistical shape model based reconstruction of the proximal femur - A morphology study

Seventeen bones (sixteen cadaveric bones and one plastic bone) were used to validate a method for reconstructing a surface model of the proximal femur from 2D X-ray radiographs and a statistical shape model that was constructed from thirty training surface models. Unlike previously introduced validation studies, where surface-based distance errors were used to evaluate the reconstruction accuracy, here we propose to use errors measured based on clinically relevant morphometric parameters. For this purpose, a program was developed to robustly extract those morphometric parameters from the thirty training surface models (training population), from the seventeen surface models reconstructed from X-ray radiographs, and from the seventeen ground truth surface models obtained either by a CT-scan reconstruction method or by a laser-scan reconstruction method. A statistical analysis was then performed to classify the seventeen test bones into two categories: normal cases and outliers. This classification step depends on the measured parameters of the particular test bone. In case all parameters of a test bone were covered by the training population's parameter ranges, this bone is classified as normal bone, otherwise as outlier bone. Our experimental results showed that statistically there was no significant difference between the morphometric parameters extracted from the reconstructed surface models of the normal cases and those extracted from the reconstructed surface models of the outliers. Therefore, our statistical shape model based reconstruction technique can be used to reconstruct not only the surface model of a normal bone but also that of an outlier bone.

Learning Spike-Based Population Codes by Reward and Population Feedback

We investigate a recently proposed model for decision learning in a population of spiking neurons where synaptic plasticity is modulated by a population signal in addition to reward feedback. For the basic model, binary population decision making based on spike/no-spike coding, a detailed computational analysis is given about how learning performance depends on population size and task complexity. Next, we extend the basic model to n-ary decision making and show that it can also be used in conjunction with other population codes such as rate or even latency coding.

Spatio-temporal credit assignment in population learning

Learning by reinforcement is important in shaping animal behavior, and in particular in behavioral decision making. Such decision making is likely to involve the integration of many synaptic events in space and time. However, using a single reinforcement signal to modulate synaptic plasticity, as suggested in classical reinforcement learning algorithms, a twofold problem arises. Different synapses will have contributed differently to the behavioral decision, and even for one and the same synapse, releases at different times may have had different effects. Here we present a plasticity rule which solves this spatio-temporal credit assignment problem in a population of spiking neurons. The learning rule is spike-time dependent and maximizes the expected reward by following its stochastic gradient. Synaptic plasticity is modulated not only by the reward, but also by a population feedback signal. While this additional signal solves the spatial component of the problem, the temporal one is solved by means of synaptic eligibility traces. In contrast to temporal difference (TD) based approaches to reinforcement learning, our rule is explicit with regard to the assumed biophysical mechanisms. Neurotransmitter concentrations determine plasticity and learning occurs fully online. Further, it works even if the task to be learned is non-Markovian, i.e. when reinforcement is not determined by the current state of the system but may also depend on past events. The performance of the model is assessed by studying three non-Markovian tasks. In the first task, the reward is delayed beyond the last action with non-related stimuli and actions appearing in between. The second task involves an action sequence which is itself extended in time and reward is only delivered at the last action, as it is the case in any type of board-game. The third task is the inspection game that has been studied in neuroeconomics, where an inspector tries to prevent a worker from shirking. Applying our algorithm to this game yields a learning behavior which is consistent with behavioral data from humans and monkeys, revealing themselves properties of a mixed Nash equilibrium. The examples show that our neuronal implementation of reward based learning copes with delayed and stochastic reward delivery, and also with the learning of mixed strategies in two-opponent games.

Spatio-temporal credit assignment in population learning

Learning by reinforcement is important in shaping animal behavior. But behavioral decision making is likely to involve the integration of many synaptic events in space and time. So in using a single reinforcement signal to modulate synaptic plasticity a twofold problem arises. Different synapses will have contributed differently to the behavioral decision and, even for one and the same synapse, releases at different times may have had different effects. Here we present a plasticity rule which solves this spatio-temporal credit assignment problem in a population of spiking neurons. The learning rule is spike time dependent and maximizes the expected reward by following its stochastic gradient. Synaptic plasticity is modulated not only by the reward but by a population feedback signal as well. While this additional signal solves the spatial component of the problem, the temporal one is solved by means of synaptic eligibility traces. In contrast to temporal difference based approaches to reinforcement learning, our rule is explicit with regard to the assumed biophysical mechanisms. Neurotransmitter concentrations determine plasticity and learning occurs fully online. Further, it works even if the task to be learned is non-Markovian, i.e. when reinforcement is not determined by the current state of the system but may also depend on past events. The performance of the model is assessed by studying three non-Markovian tasks. In the first task the reward is delayed beyond the last action with non-related stimuli and actions appearing in between. The second one involves an action sequence which is itself extended in time and reward is only delivered at the last action, as is the case in any type of board-game. The third is the inspection game that has been studied in neuroeconomics. It only has a mixed Nash equilibrium and exemplifies that the model also copes with stochastic reward delivery and the learning of mixed strategies.

Spatio-temporal credit assignment in population learning

We present a model for plasticity induction in reinforcement learning which is based on a cascade of synaptic memory traces. In the cascade of these so called eligibility traces presynaptic input is first corre lated with postsynaptic events, next with the behavioral decisions and finally with the external reinforcement. A population of leaky integrate and fire neurons endowed with this plasticity scheme is studied by simulation on different tasks. For operant co nditioning with delayed reinforcement, learning succeeds even when the delay is so large that the delivered reward reflects the appropriateness, not of the immediately preceeding response, but of a decision made earlier on in the stimulus - decision sequence . So the proposed model does not rely on the temporal contiguity between decision and pertinent reward and thus provides a viable means of addressing the temporal credit assignment problem. In the same task, learning speeds up with increasing population si ze, showing that the plasticity cascade simultaneously addresses the spatial problem of assigning credit to the different population neurons. Simulations on other task such as sequential decision making serve to highlight the robustness of the proposed sch eme and, further, contrast its performance to that of temporal difference based approaches to reinforcement learning.

Minimization of Intra-Operative Shaping of Orthopaedic Fixation Plates: A Population-Based Design

In this paper we present a new population-based method for the design of bone fixation plates. Standard pre-contoured plates are designed based on the mean shape of a certain population. We propose a computational process to design implants while reducing the amount of required intra-operative shaping, thus reducing the mechanical stresses applied to the plate. A bending and torsion model was used to measure and minimize the necessary intra-operative deformation. The method was applied and validated on a population of 200 femurs that was further augmented with a statistical shape model. The obtained results showed substantial reduction in the bending and torsion needed to shape the new design into any bone in the population when compared to the standard mean-based plates.

Irradiated disks and planet population synthesis

Recent planet population synthesis models (Alibert et al. 2010, submitted) have emphasized the key role played by the proto-planetary disk properties in determining the overall planet population characteristics. We present a disk model that takes into account viscous heating and irradiation by a central star. We consider the case of an equilibrium flaring angle. We illustrate the consequences of the resulting changes in the disk structure on the planet population by the synthetic populations corresponding to each of the different structures.

Habitat-specific demography and source-sink dynamics in a population of Siberian jays

P>1. There are a number of models describing population structure, many of which have the capacity to incorporate spatial habitat effects. One such model is the source-sink model, that describes a system where some habitats have a natality that is higher than mortality (source) and others have a mortality that exceeds natality (sink). A source can be maintained in the absence of migration, whereas a sink will go extinct. 2. However, the interaction between population dynamics and habitat quality is complex, and concerns have been raised about the validity of published empirical studies addressing source-sink dynamics. In particular, some of these studies fail to provide data on survival, a significant component in disentangling a sink from a low quality source. Moreover, failing to account for a density-dependent increase in mortality, or decrease in fecundity, can result in a territory being falsely assigned as a sink, when in fact, this density-dependent suppression only decreases the population size to a lower level, hence indicating a 'pseudo-sink'. 3. In this study, we investigate a long-term data set for key components of territory-specific demography (mortality and reproduction) and their relationship to habitat characteristics in the territorial, group-living Siberian jay (Perisoreus infaustus). We also assess territory-specific population growth rates (r), to test whether spatial population dynamics are consistent with the ideas of source-sink dynamics. 4. Although average mortality did not differ between sexes, habitat-specific mortality did. Female mortality was higher in older forests, a pattern not observed in males. Male mortality only increased with an increasing amount of open areas. Moreover, reproductive success was higher further away from human settlement, indicating a strong effect of human-associated nest predators. 5. Averaged over all years, 76% of the territories were sources. These territories generally consisted of less open areas, and were located further away from human settlement. 6. The source-sink model provides a tool for modelling demography in distinct habitat patches of different quality, which can aid in identifying key habitats within the landscape, and thus, reduce the risk of implementing unsound management decisions.

A Method for Detecting Population Genetic Structure in Diverse, High Gene-Flow Species

Detecting small amounts of genetic subdivision across geographic space remains a persistent challenge. Often a failure to detect genetic structure is mistaken for evidence of panmixia, when more powerful statistical tests may uncover evidence for subtle geographic differentiation. Such slight subdivision can be demographically and evolutionarily important as well as being critical for management decisions. We introduce here a method, called spatial analysis of shared alleles (SAShA), that detects geographically restricted alleles by comparing the spatial arrangement of allelic co-occurrences with the expectation under panmixia. The approach is allele-based and spatially explicit, eliminating the loss of statistical power that can occur with user-defined populations and statistical averaging within populations. Using simulated data sets generated under a stepping-stone model of gene flow, we show that this method outperforms spatial autocorrelation (SA) and UST under common real-world conditions: at relatively high migration rates when diversity is moderate or high, especially when sampling is poor. We then use this method to show clear differences in the genetic patterns of 2 nearshore Pacific mollusks, Tegula funebralis (5 Chlorostoma funebralis) and Katharina tunicata, whose overall patterns of within-species differentiation are similar according to traditional population genetics analyses. SAShA meaningfully complements UST/FST, SA, and other existing geographic genetic analyses and is especially appropriate for evaluating species with high gene flow and subtle genetic differentiation.