Artificial societies and information theory: modelling of sub system formation based on Luhmann's autopoietic theory

This thesis develops a theoretical framework for the generation of artificial societies. In particular it shows how sub-systems emerge when the agents are able to learn and have the ability to communicate. This novel theoretical framework integrates the autopoietic hypothesis of human societies, formulated originally by the German sociologist Luhmann, with concepts of Shannon's information theory applied to adaptive learning agents. Simulations were executed using Multi-Agent-Based Modelling (ABM), a relatively new computational modelling paradigm involving the modelling of phenomena as dynamical systems of interacting agents. The thesis in particular, investigates the functions and properties necessary to reproduce the paradigm of society by using the mentioned ABM approach. Luhmann has proposed that in society subsystems are formed to reduce uncertainty. Subsystems can then be composed by agents with a reduced behavioural complexity. For example in society there are people who produce goods and other who distribute them. Both the behaviour and communication is learned by the agent and not imposed. The simulated task is to collect food, keep it and eat it until sated. Every agent communicates its energy state to the neighbouring agents. This results in two subsystems whereas agents in the first collect food and in the latter steal food from others. The ratio between the number of agents that belongs to the first system and to the second system, depends on the number of food resources. Simulations are in accordance with Luhmann, who suggested that adaptive agents self-organise by reducing the amount of sensory information or, equivalently, reducing the complexity of the perceived environment from the agent's perspective. Shannon's information theorem is used to assess the performance of the simulated learning agents. A practical measure, based on the concept of Shannon's information ow, is developed and applied to adaptive controllers which use Hebbian learning, input correlation learning (ICO/ISO) and temporal difference learning. The behavioural complexity is measured with a novel information measure, called Predictive Performance, which is able to measure at a subjective level how good an agent is performing a task. This is then used to quantify the social division of tasks in a social group of honest, cooperative food foraging, communicating agents

Numerical scattering simulations for interpreting simultaneous observations of clouds by a W-band spaceborne and a C-band ground radar

The spaceborne W-band (94 GHz) Cloud Profiling Radar (CPR) onboard the CloudSat (CS) satellite, which was launched in 2006, is providing valuable information about global cloud properties. This work aims at interpreting collocated time/space observations from CPR on CS and a ground C-band (5.6 GHz) Radar (GR), with the help of numerical simulations of electromagnetic scattering returns from populations of monodisperse spheres of ice and liquid water. Two cloud systems over Apulia region are investigated. CPR and GR images have been geo-referenced, then combined and displayed for analysis. The numerical simulations of the two radar reflectivities are used as a tool in the inversion procedure, aiming at identifying the hydrometeors, in their phase and size distribution, in the cloud volume simultaneously observed by the two radars. The possible vertical profiles of hydrometeors are presented

Principles of wide bandwidth acoustic detectors and the single-mass DUAL detector

We apply the standard theory of the elastic body to obtain a set of equations describing the behavior of an acoustic Gravitational Wave detector, fully taking into account the 3-dimensional properties of the mass, the readout and the signal. We show that the advantages given by a Dual detector made by two nested oscillators can also be obtained by monitoring two different acoustic modes of the same oscillator, thus easing the detector realization. We apply these concepts and by means of an optimization process we derive the main figures of such a single-mass Dual detector designed specifically for the frequency interval 2-5kHz. Finally we calculate the SQL sensitivity of this detector.Comment: 29 pages, 10 figure

Dc superconducting quantum interference device amplifier for gravitational wave detectors with a true noise temperature of 16 μK

We report on the noise characterization of a two-stage dc superconducting quantum interference device (SQUID) amplifier developed for resonant gravitational wave detectors. The back action noise is estimated by coupling the SQUID to an electrical resonator at 1.6 kHz with Q=1.1×106. From measurements of back action and additive SQUID noise, performed in the temperature range 1.5–4.2 K, an upper limit is set on the noise temperature Tn of the device at the resonator frequency. The best value obtained at 1.5 K is Tn⩽16 μK and corresponds to 200 resonator quanta. The thermal component of the noise temperature is found in reasonable agreement with the predicted value

Changes in attitude towards LAI antipsychotic maintenance treatment: A two-year follow-up study.

AbstractBackground:To present real-world evidence on the effects of switching from oral to long-acting injectable (LAI) antipsychotic maintenance treatment (AMT) in a sample of clinically stable patients with schizophrenia, with regard to subjective experience of treatment, attitude towards drug and quality of life.Methods:50 clinically stable adult schizophrenic outpatients were recruited. At the time of enrolment (T0), all patients were under a stabilized therapy with a single oral second-generation antipsychotic (SGA) and were switched to the equivalent maintenance regimen with the long-acting formulation of the same antipsychotic. 43 patients completed the 24-month prospective, longitudinal, open-label, observational study. Participants were assessed at baseline (T0), after 12 (T1) and 24 months (T2), using psychometric scales (PANSS, YMRS and MDRS) and patient-reported outcome measures (SWN-K, DAI-10 and SF-36).Results:The switch to LAI-AMT was associated with a significant clinical improvement at T1 and T2 compared to baseline (T0). All of the psychometric indexes, as well as patients' subjective experience of treatment (SWN-K), and quality of life (SF-36) showed a significant improvement after one year of LAI-AMT, with stable results after two years. Patients' attitude towards drug (DAI-10) increased throughout the follow-up period, with a further improvement during the second year.Conclusions:The switch to LAI-AMT may help to address the subjective core of an optimal recovery in stabilized schizophrenic patients. A sustained improvement in patients' attitude towards drug may help to achieve patient's compliance. The size of this study needs to be expanded to produce more solid and generalizable results

How feedback inhibition shapes spike-timing-dependent plasticity and its implications for recent Schizophrenia models

It has been shown that plasticity is not a fixed property but, in fact, changes depending on the location of the synapse on the neuron and/or changes of biophysical parameters. Here we investigate how plasticity is shaped by feedback inhibition in a cortical microcircuit. We use a differential Hebbian learning rule to model spike-timing dependent plasticity and show analytically that the feedback inhibition shortens the time window for LTD during spike-timing dependent plasticity but not for LTP. We then use a realistic GENESIS model to test two hypothesis about interneuron hypofunction and conclude that a reduction in GAD67 is the most likely candidate as the cause for hypofrontality as observed in Schizophrenia

A modular phage vector platform for targeted photodynamic therapy of Gram-negative bacterial pathogens

: Growing antibiotic resistance has encouraged the revival of phage-inspired antimicrobial approaches. On the other hand, photodynamic therapy (PDT) is considered a very promising research domain for the protection against infectious diseases. Yet, very few efforts have been made to combine the advantages of both approaches in a modular, retargetable platform. Here, we foster the M13 bacteriophage as a multifunctional scaffold, enabling the selective photodynamic killing of bacteria. We took advantage of the well-defined molecular biology of M13 to functionalize its capsid with hundreds of photo-activable Rose Bengal sensitizers and contemporarily target this light-triggerable nanobot to specific bacterial species by phage display of peptide targeting moieties fused to the minor coat protein pIII of the phage. Upon light irradiation of the specimen, the targeted killing of diverse Gram(-) pathogens occurred at subnanomolar concentrations of the phage vector. Our findings contribute to the development of antimicrobials based on targeted and triggerable phage-based nanobiotherapeutics