Melt processing and properties of linear low density polyethylene-graphene nanoplatelet composites

Composites of Linear Low Density Polyethylene (LLDPE) and Graphene Nanoplatelets (GNPs) were processed using a twin screw extruder under different extrusion conditions. The effects of screw speed, feeder speed and GNP content on the electrical, thermal and mechanical properties of composites were investigated. The inclusion of GNPs in the matrix improved the thermal stability and conductivity by 2.7% and 43%, respectively. The electrical conductivity improved from 10−11 to 10−5 S/m at 150 rpm due to the high thermal stability of the GNPs and the formation of phonon and charge carrier networks in the polymer matrix. Higher extruder speeds result in a better distribution of the GNPs in the matrix and a significant increase in thermal stability and thermal conductivity. However, this effect is not significant for the electrical conductivity and tensile strength. The addition of GNPs increased the viscosity of the polymer, which will lead to higher processing power requirements. Increasing the extruder speed led to a reduction in viscosity, which is due to thermal degradation and/or chain scission. Thus, while high speeds result in better dispersions, the speed needs to be optimized to prevent detrimental impacts on the properties.

Spiking neural network connectivity and its potential for temporal sensory processing and variable binding

The most biologically-inspired artificial neurons are those of the third generation, and are termed spiking neurons, as individual pulses or spikes are the means by which stimuli are communicated. In essence, a spike is a short-term change in electrical potential and is the basis of communication between biological neurons. Unlike previous generations of artificial neurons, spiking neurons operate in the temporal domain, and exploit time as a resource in their computation. In 1952, Alan Lloyd Hodgkin and Andrew Huxley produced the first model of a spiking neuron; their model describes the complex electro-chemical process that enables spikes to propagate through, and hence be communicated by, spiking neurons. Since this time, improvements in experimental procedures in neurobiology, particularly with in vivo experiments, have provided an increasingly more complex understanding of biological neurons. For example, it is now well-understood that the propagation of spikes between neurons requires neurotransmitter, which is typically of limited supply. When the supply is exhausted neurons become unresponsive. The morphology of neurons, number of receptor sites, amongst many other factors, means that neurons consume the supply of neurotransmitter at different rates. This in turn produces variations over time in the responsiveness of neurons, yielding various computational capabilities. Such improvements in the understanding of the biological neuron have culminated in a wide range of different neuron models, ranging from the computationally efficient to the biologically realistic. These models enable the modeling of neural circuits found in the brain.

Spiking Neural Network Connectivity and its Potential for Temporal Sensory Processing and Variable Binding

The most biologically-inspired artificial neurons are those of the third generation, and are termed spiking neurons, as individual pulses or spikes are the means by which stimuli are communicated. In essence, a spike is a short-term change in electrical potential and is the basis of communication between biological neurons. Unlike previous generations of artificial neurons, spiking neurons operate in the temporal domain, and exploit time as a resource in their computation. In 1952, Alan Lloyd Hodgkin and Andrew Huxley produced the first model of a spiking neuron; their model describes the complex electro-chemical process that enables spikes to propagate through, and hence be communicated by, spiking neurons. Since this time, improvements in experimental procedures in neurobiology, particularly with in vivo experiments, have provided an increasingly more complex understanding of biological neurons. For example, it is now well understood that the propagation of spikes between neurons requires neurotransmitter, which is typically of limited supply. When the supply is exhausted neurons become unresponsive. The morphology of neurons, number of receptor sites, amongst many other factors, means that neurons consume the supply of neurotransmitter at different rates. This in turn produces variations over time in the responsiveness of neurons, yielding various computational capabilities. Such improvements in the understanding of the biological neuron have culminated in a wide range of different neuron models, ranging from the computationally efficient to the biologically realistic. These models enable the modelling of neural circuits found in the brain. In recent years, much of the focus in neuron modelling has moved to the study of the connectivity of spiking neural networks. Spiking neural networks provide a vehicle to understand from a computational perspective, aspects of the brain’s neural circuitry. This understanding can then be used to tackle some of the historically intractable issues with artificial neurons, such as scalability and lack of variable binding. Current knowledge of feed-forward, lateral, and recurrent connectivity of spiking neurons, and the interplay between excitatory and inhibitory neurons is beginning to shed light on these issues, by improved understanding of the temporal processing capabilities and synchronous behaviour of biological neurons. This research topic aims to amalgamate current research aimed at tackling these phenomena.

Alexithymia, emotional processing and psychotherapy : a mixed methods research

Tese de doutoramento, Psicologia (Psicologia Clínica), Universidade de Lisboa, Faculdade de Psicologia, 2014

Some reflections on acquisition, processing and analysis of statistical data in forest soils

Beyond the classical statistical approaches (determination of basic statistics, regression analysis, ANOVA, etc.) a new set of applications of different statistical techniques has increasingly gained relevance in the analysis, processing and interpretation of data concerning the characteristics of forest soils. This is possible to be seen in some of the recent publications in the context of Multivariate Statistics. These new methods require additional care that is not always included or refered in some approaches. In the particular case of geostatistical data applications it is necessary, besides to geo-reference all the data acquisition, to collect the samples in regular grids and in sufficient quantity so that the variograms can reflect the spatial distribution of soil properties in a representative manner. In the case of the great majority of Multivariate Statistics techniques (Principal Component Analysis, Correspondence Analysis, Cluster Analysis, etc.) despite the fact they do not require in most cases the assumption of normal distribution, they however need a proper and rigorous strategy for its utilization. In this work, some reflections about these methodologies and, in particular, about the main constraints that often occur during the information collecting process and about the various linking possibilities of these different techniques will be presented. At the end, illustrations of some particular cases of the applications of these statistical methods will also be presented.

Effect of mindfulness meditation on the neural substrates of emotion processing and resting state in experienced and beginner meditators

La méditation par le ‘mindfulness’ favorise la stabilité émotionelle, mais les mécanismes neuroneux qui sous-tendent ces effets sont peu connus. Ce projet investiga l’effet du ‘mindfulness’ sur les réponses cérébrales et subjectives à des images négatives, positives et neutres chez des méditants expérimentés et des débutants au moyen de l’imagerie par résonance magnétique fonctionnelle (IRMf). Le ‘mindfulness’ atténua l’intensité émotionelle via différents mécanismes cérébraux pour chaque groupe. Comparés aux méditants, les débutants manifestèrent une déactivation de l’amygdale en réponse aux stimuli émotifs durant le ‘mindfulness’. Comparés aux débutants, les méditants exhibèrent une déactivation de régions du réseau du mode par défaut (RMD) pendant le ‘mindfulness’ pour tous stimuli (cortex médian préfrontal [CMP], cortex cingulaire postérieur [CCP]). Le RMD est constitué de régions fonctionnellement connectées, activées au repos et déactivées lors de tâches explicites. Cependant, nous ne connaissons pas les impacts de l’entraînement par la méditation sur la connectivité entre régions du RMD et si ces effets persistent au-delà d’un état méditatif. La connectivité fonctionnelle entre régions du RMD chez les méditants et débutants au repos fut investiguée au moyen de l’IRMf. Comparés aux débutants, les méditants montrèrent une connectivité affaiblie entre subdivisions du CMP, et une connectivité accrue entre le lobule pariétal inférieur et trois regions du RMD. Ces résultats reflètent que les bienfaits immédiats du ‘mindfulness’ sur la psychopathologie pourraient être dûs à une déactivation de régions limbiques impliquées dans la réactivité émotionelle. De plus, les bienfaits à long-terme de la méditation sur la stabilité émotionelle pourrait être dûs à une déactivation de régions corticales et cingulaires impliquées dans l’évaluation de la signification émotive et une connectivité altérée entre régions du RMD à l’état de repos.

A Psychophysical Assessment of Multisensory Processing and Multiple Object Tracking in Autism Spectrum Disorders

Les troubles du spectre autistique (TSA) sont actuellement caractérisés par une triade d'altérations, incluant un dysfonctionnement social, des déficits de communication et des comportements répétitifs. L'intégration simultanée de multiples sens est cruciale dans la vie quotidienne puisqu'elle permet la création d'un percept unifié. De façon similaire, l'allocation d'attention à de multiples stimuli simultanés est critique pour le traitement de l'information environnementale dynamique. Dans l'interaction quotidienne avec l'environnement, le traitement sensoriel et les fonctions attentionnelles sont des composantes de base dans le développement typique (DT). Bien qu'ils ne fassent pas partie des critères diagnostiques actuels, les difficultés dans les fonctions attentionnelles et le traitement sensoriel sont très courants parmi les personnes autistes. Pour cela, la présente thèse évalue ces fonctions dans deux études séparées. La première étude est fondée sur la prémisse que des altérations dans le traitement sensoriel de base pourraient être à l'origine des comportements sensoriels atypiques chez les TSA, tel que proposé par des théories actuelles des TSA. Nous avons conçu une tâche de discrimination de taille intermodale, afin d'investiguer l'intégrité et la trajectoire développementale de l'information visuo-tactile chez les enfants avec un TSA (N = 21, âgés de 6 à18 ans), en comparaison à des enfants à DT, appariés sur l’âge et le QI de performance. Dans une tâche à choix forcé à deux alternatives simultanées, les participants devaient émettre un jugement sur la taille de deux stimuli, basé sur des inputs unisensoriels (visuels ou tactiles) ou multisensoriels (visuo-tactiles). Des seuils différentiels ont évalué la plus petite différence à laquelle les participants ont été capables de faire la discrimination de taille. Les enfants avec un TSA ont montré une performance diminuée et pas d'effet de maturation aussi bien dans les conditions unisensorielles que multisensorielles, comparativement aux participants à DT. Notre première étude étend donc des résultats précédents d'altérations dans le traitement multisensoriel chez les TSA au domaine visuo-tactile. Dans notre deuxième étude, nous avions évalué les capacités de poursuite multiple d’objets dans l’espace (3D-Multiple Object Tracking (3D-MOT)) chez des adultes autistes (N = 15, âgés de 18 à 33 ans), comparés à des participants contrôles appariés sur l'âge et le QI, qui devaient suivre une ou trois cibles en mouvement parmi des distracteurs dans un environnement de réalité virtuelle. Les performances ont été mesurées par des seuils de vitesse, qui évaluent la plus grande vitesse à laquelle des observateurs sont capables de suivre des objets en mouvement. Les individus autistes ont montré des seuils de vitesse réduits dans l'ensemble, peu importe le nombre d'objets à suivre. Ces résultats étendent des résultats antérieurs d'altérations au niveau des mécanismes d'attention en autisme quant à l'allocation simultanée de l'attention envers des endroits multiples. Pris ensemble, les résultats de nos deux études révèlent donc des altérations chez les TSA quant au traitement simultané d'événements multiples, que ce soit dans une modalité ou à travers des modalités, ce qui peut avoir des implications importantes au niveau de la présentation clinique de cette condition.

Effect of curing temperature , fibre loading and bonding agent on the equilibrium swelling of isora-natural rubbercomposites

Isora fibre-reinforced natural rubber (NR) composites were cured at 80, 100, 120 and 150°C using a low temperature curing accelerator system. Composites were also prepared using a conventional accelerator system and cured at 150°C. The swelling behavior of these composites at varying fibre loadings was studied in toluene and hexane. Results show that the uptake of solvent and volume fraction of rubber due to swelling was lower for the low temperature cured vulcanizates which is an indication of the better fibre/rubber adhesion. The uptake of aromatic solvent was higher than that of aliphatic solvent, for all the composites. As the fibre content increased, the solvent uptake decreased, due to the superior solvent resistance of the fibre and good fibre-rubber interactions. The bonding agent improved the swelling resistance of the composites due to the strong interfacial adhesion. Due to the improved adhesion between the fibre and rubber, the ratio of the change in volume fraction of rubber due to swelling to the volume fraction of rubber in the dry sample (V,) was found to decrease in the presence of bonding agent. At a fixed fibre loading, the alkali treated fibre composite showed a lower percentage swelling than untreated one for both systems showing superior rubber-fibre interactions.

Processing And Frozen Storage Characteristics Of Ray Fillets

Rays, belonging to the class Elasmobranchii, constitute a major fishery in many states in India like Tamil Nadu, Gujarat, Andhra Pradesh, Kerala and Maharashtra. The estimated landings are 21,700 tonnes per annum. Even though the meat of rays is nutritious and free from bones and spines, there is little demand for fresh meat due to the presence of a high urea content. The landings are mainly used for salt curing which fetches only very low prices for the producers. Urea nitrogen constituted the major component (50.8%) of the non-protein nitrogen of the meat. An attempt has been made to standat-dize the processing steps to reduce the urea levels in the meat before freezing by using different simple techniques like dipping the fillets in stagnant chilled water, dipping in chilled running water and dipping in stirred chilled running water. It was found that meat dipped in stirred running water for two hours reduced the urea level of the meat by 62%. The yield of the lateral fin fillets and caudal fin fillets vary with the size of the ray. The drip loss during frozen storage is found to be more in the case of samples frozen stored after the treatment for urea removal by the method of stirring in running water. The samples treated in stagnant chilled water had the lowest drip loss. The total nitrogen was higher in samples treated in stagnant chilled water and lowest in the samples treated in stirred running water. The overall acceptability was high in the case of samples treated with stirred running water and frozen stored

Natural Rubber Latex Filler Masterbatch by Soap Sensitised Coagulation-Preparation, Processing and Evaluation

Sensitisation of natural rubber latex by addition of a small quantity of an anionic surfactant prior to the addition of a coacervant results in quick coagulation. The natural rubber prepared by the novel coagulation method shows improved raw rubber characteristics, better cure characteristics in gum and carbon black filled compounds and improved mechanical properties as compared to the conventionally coagulated natural rubber. Compounds based on dried masterbatches prepared by the incorporation of fluffy carbon black in different forms of soap sensitised natural rubber latices such as fresh latex, preserved field latex, centrifuged latex and a blend of preserved field latex and skim latex show improved cure characteristics and vucanizate properties as compared to an equivalent conventional dry rubber-fluffy carbon black based compound. The latex masterbatch based vulcanizates show higher level of crosslinking and better dispersion of filler. Vulcanizates based on fresh natural rubber latex- dual filler masterbatches containing a blend of carbon black and silica prepared by the modified coagulation process shows very good mechanical and dynamic properties that could be correlated to a low rolling resistance. The carbon black/silica/nanoclay tri-filler - fresh natural rubber latex masterbatch based vulcanizates show improved mechanical properties as the proportion of nanoclay increased up to 5 phr. The fresh natural rubber latex based carbon black-silica masterbatch/ polybutadiene blend vulcanizates show superior mechanical and dynamic properties as compared to the equivalent compound vulcanizates prepared from the dry natural rubber-filler (conventional dry mix)/polybutadiene blends