Mechanical behavior of carbon/flax hybrid composites for structural applications

In this work, the influence of an unidirectional carbon fabric layer on the mechanical performances of bidirectional flax fabric/epoxy composites used for structural applications was studied. Two different bidirectional flax fabrics were used to produce flax fabric reinforced plastic (FFRP) laminates by a vacuum bagging process: one is normally used to make curtains; the other, heavier and more expensive than the previous one, is usually used as reinforcement in composite structures. In order to realize hybrid structures starting from FFRP, an unidirectional UHM carbon fabric was used to replace a bidirectional flax fabric. Tensile and three-point bending tests were performed to evaluate the mechanical properties of the laminates investigated (both FFRP and hybrids). Furthermore, the mechanical behavior of the different bidirectional flax fabrics was analyzed by carrying out tensile tests. The experimental tests showed that the structures reinforced with flax fabrics, normally used to make curtains, present better flexural properties than that of others while, in tensile configuration, these last show higher modulus and strength. Moreover, both FFRP laminates show low mechanical properties, which do not allow their use in structural applications while the presence of one external layer of unidirectional carbon involves remarkable increase in their properties. According to this study, the hybrid composites realized could be used in several structural applications (i.e., nautical and automotive)

Under the Spell of Multiple Realizability - A defence of reductionism in mind studies

Hilary Putnam’s ‘Psychological Predicates’ (1967) represents the first formalization of the argument for the multiple realizability theory (MRT) of mental states. Few years later, Jerry Fodor (1974) conceived the generalised version of the MRT over times which supported the irreducibility of ‘special sciences’ as the necessary consequence of Putnam’s theory. Every science grounded on the study of the mind became autonomous from any fixed ‘bridge law’ that could bind it to physics. Recently, some philosophers have challenged the likelihood of the argument (Zangwill 1992, Shapiro 2000) whilst others have stressed the failures of the predictions implied by the generalised theory (Bechtel and Mundale, 1999). My contribution to the controversy consists in a connectionist perspective that helps in showing two weak points in the standard approach to the MRT. Firstly, philosophers usually forget that Turing machines cannot compute (or simulate) every possible mathematical function and it is still to demonstrate if they are able to perform the mathematical functions computed by neural systems. Such a result may be only achieved using a mathematical approach to the processes implemented by parallel systems and there are good reasons to believe that the unique features showed by these systems cannot be simulated in any serial devices. Secondly, the possibility to isolate single parts of a complex system identifying their functions, should be rejected for several reason, the most important being that such functions lead to partial descriptions of the system itself. These descriptions may be useful in some contexts (i.e. if we do not have access to complete descriptions), but they fail to give us exhaustive explanations and should be considered weak as the ground for an explanatory model. In conclusion, I claim that a complete description of an information processing system relies on the formalization of the ‘mathematical functions’ it realizes (i.e. the mathematical description of the processes implemented by the system). This formalization can only be achieved studying the physical matter that generates the mathematical functions

Addiction beyond pharmacological effects: The role of environment complexity and bounded rationality

Several decision-making vulnerabilities have been identified as underlying causes for addictive behaviours, or the repeated execution of stereotyped actions despite their adverse consequences. These vulnerabilities are mostly associated with brain alterations caused by the consumption of substances of abuse. However, addiction can also happen in the absence of a pharmacological component, such as seen in pathological gambling and videogaming. We use a new reinforcement learning model to highlight a previously neglected vulnerability that we suggest interacts with those already identified, whilst playing a prominent role in non-pharmacological forms of addiction. Specifically, we show that a dual-learning system (i.e. combining model-based and model-free) can be vulnerable to highly rewarding, but suboptimal actions, that are followed by a complex ramification of stochastic adverse effects. This phenomenon is caused by the overload of the capabilities of an agent, as time and cognitive resources required for exploration, deliberation, situation recognition, and habit formation, all increase as a function of the depth and richness of detail of an environment. Furthermore, the cognitive overload can be aggravated due to alterations (e.g. caused by stress) in the bounded rationality, i.e. the limited amount of resources available for the model-based component, in turn increasing the agent’s chances to develop or maintain addictive behaviours. Our study demonstrates that, independent of drug consumption, addictive behaviours can arise in the interaction between the environmental complexity and the biologically finite resources available to explore and represent it

A Multilevel Computational Characterization of Endophenotypes in Addiction

Addiction is characterized by a profound intersubject (phenotypic) variability in the expression of addictive symptomatology and propensity to relapse following treatment. However, laboratory investigations have primarily focused on common neural substrates in addiction and have not yet been able to identify mechanisms that can account for the multifaceted phenotypic behaviors reported in the literature. To fill this knowledge gap theoretically, here we simulated phenotypic variations in addiction symptomology and responses to putative treatments, using both a neural model, based on cortico-striatal circuit dynamics, and an algorithmic model of reinforcement learning (RL). These simulations rely on the widely accepted assumption that both the ventral, model-based, goal-directed system and the dorsal, model-free, habitual system are vulnerable to extra-physiologic dopamine reinforcements triggered by addictive rewards. We found that endophenotypic differences in the balance between the two circuit or control systems resulted in an inverted-U shape in optimal choice behavior. Specifically, greater unbalance led to a higher likelihood of developing addiction and more severe drug-taking behaviors. Furthermore, endophenotypes with opposite asymmetrical biases among cortico-striatal circuits expressed similar addiction behaviors, but responded differently to simulated treatments, suggesting personalized treatment development could rely on endophenotypic rather than phenotypic differentiations. We propose our simulated results, confirmed across neural and algorithmic levels of analysis, inform on a fundamental and, to date, neglected quantitative method to characterize clinical heterogeneity in addiction

Corticolimbic catecholamines in stress: A computational model of the appraisal of controllability

Appraisal of a stressful situation and the possibility to control or avoid it is thought to involve frontal-cortical mechanisms. The precise mechanism underlying this appraisal and its translation into effective stress coping (the regulation of physiological and behavioural responses) are poorly understood. Here, we propose a computational model which involves tuning motivational arousal to the appraised stressing condition. The model provides a causal explanation of the shift from active to passive coping strategies, i.e. from a condition characterised by high motivational arousal, required to deal with a situation appraised as stressful, to a condition characterised by emotional and motivational withdrawal, required when the stressful situation is appraised as uncontrollable/unavoidable. The model is motivated by results acquired via microdialysis recordings in rats and highlights the presence of two competing circuits dominated by different areas of the ventromedial prefrontal cortex: these are shown having opposite effects on several subcortical areas, affecting dopamine outflow in the striatum, and therefore controlling motivation. We start by reviewing published data supporting structure and functioning of the neural model and present the computational model itself with its essential neural mechanisms. Finally, we show the results of a new experiment, involving the condition of repeated inescapable stress, which validate most of the model's prediction

A computational model of stress coping in rats

No abstract availabl

Charged particle's flux measurement from PMMA irradiated by 80 MeV/u carbon ion beam

Hadrontherapy is an emerging technique in cancer therapy that uses beams of charged particles. To meet the improved capability of hadrontherapy in matching the dose release with the cancer position, new dose monitoring techniques need to be developed and introduced into clinical use. The measurement of the fluxes of the secondary particles produced by the hadron beam is of fundamental importance in the design of any dose monitoring device and is eagerly needed to tune Monte Carlo simulations. We report the measurements done with charged secondary particles produced from the interaction of a 80 MeV/u fully stripped carbon ion beam at the INFN Laboratori Nazionali del Sud, Catania, with a Poly-methyl methacrylate target. Charged secondary particles, produced at 90$\degree$ with respect to the beam axis, have been tracked with a drift chamber, while their energy and time of flight has been measured by means of a LYSO scintillator. Secondary protons have been identified exploiting the energy and time of flight information, and their emission region has been reconstructed backtracking from the drift chamber to the target. Moreover a position scan of the target indicates that the reconstructed emission region follows the movement of the expected Bragg peak position. Exploting the reconstruction of the emission region, an accuracy on the Bragg peak determination in the submillimeter range has been obtained. The measured differential production rate for protons produced with $E^{\rm Prod}_{\rm kin} >$ 83 MeV and emitted at 90$\degree$ with respect to the beam line is: $dN_{\rm P}/(dN_{\rm C}d\Omega)(E^{\rm Prod}_{\rm kin} > 83 {\rm ~MeV}, \theta=90\degree)= (2.69\pm 0.08_{\rm stat} \pm 0.12_{\rm sys})\times 10^{-4} sr^{-1}$.Comment: 13 pages, 9 figure

Surgical site infection after caesarean section. Space for post-discharge surveillance improvements and reliable comparisons

Surgical site infections (SSI) after caesarean section (CS) represent a substantial health system concern. Surveying SSI has been associated with a reduction in SSI incidence. We report the findings of three (2008, 2011 and 2013) regional active SSI surveillances after CS in community hospital of the Latium region determining the incidence of SSI. Each CS was surveyed for SSI occurrence by trained staff up to 30 post-operative days, and association of SSI with relevant characteristics was assessed using binomial logistic regression. A total of 3,685 CS were included in the study. A complete 30 day post-operation follow-up was achieved in over 94% of procedures. Overall 145 SSI were observed (3.9% cumulative incidence) of which 131 (90.3%) were superficial and 14 (9.7%) complex (deep or organ/space) SSI; overall 129 SSI (of which 89.9% superficial) were diagnosed post-discharge. Only higher NNIS score was significantly associated with SSI occurrence in the regression analysis. Our work provides the first regional data on CS-associated SSI incidence, highlighting the need for a post-discharge surveillance which should assure 30 days post-operation to not miss data on complex SSI, as well as being less labour intensive

Measurement of {\eta} meson production in {\gamma}{\gamma} interactions and {\Gamma}({\eta}-->{\gamma}{\gamma}) with the KLOE detector

We present a measurement of {\eta} meson production in photon-photon interactions produced by electron-positron beams colliding with \sqrt{s}=1 GeV. The measurement is done with the KLOE detector at the \phi-factory DA{\Phi}NE with an integrated luminosity of 0.24 fb^{-1}. The e^+e^- --> e^+e^-{\eta} cross section is measured without detecting the outgoing electron and positron, selecting the decays {\eta}-->{\pi}^+{\pi}^-{\pi}^0 and {\eta}-->{\pi}^0{\pi}^0{\pi}^0. The most relevant background is due to e^+e^- --> {\eta}{\gamma} when the monochromatic photon escapes detection. The cross section for this process is measured as {\sigma}(e^+e^- -->{\eta}{\gamma}) = (856 \pm 8_{stat} \pm 16_{syst}) pb. The combined result for the e^+e^- -->e^+e^-{\eta} cross section is {\sigma}(e^+e^- -->e^+e^-{\eta}) = (32.72 \pm 1.27_{stat} \pm 0.70_{syst}) pb. From this we derive the partial width {\Gamma}({\eta}-->{\gamma}{\gamma}) = (520 \pm 20_{stat} \pm 13_{syst}) eV. This is in agreement with the world average and is the most precise measurement to date.Comment: Version accepted by JHE