A Spiking Neural Network Model of the Medial Superior Olive using Spike Timing Dependent Plasticity for Sound Localisation

Sound localization can be defined as the ability to identify the position of an input sound source and is considered a powerful aspect of mammalian perception. For low frequency sounds, i.e., in the range 270 Hz-1.5 KHz, the mammalian auditory pathway achieves this by extracting the Interaural Time Difference between sound signals being received by the left and right ear. This processing is performed in a region of the brain known as the Medial Superior Olive (MSO). This paper presents a Spiking Neural Network (SNN) based model of the MSO. The network model is trained using the Spike Timing Dependent Plasticity learning rule using experimentally observed Head Related Transfer Function data in an adult domestic cat. The results presented demonstrate how the proposed SNN model is able to perform sound localization with an accuracy of 91.82% when an error tolerance of +/-10 degrees is used. For angular resolutions down to 2.5 degrees , it will be demonstrated how software based simulations of the model incur significant computation times. The paper thus also addresses preliminary implementation on a Field Programmable Gate Array based hardware platform to accelerate system performance.

Spiking neural network model of sound localisation using the interaural intensity difference

In this paper, a spiking neural network (SNN) architecture to simulate the sound localization ability of the mammalian auditory pathways using the interaural intensity difference cue is presented. The lateral superior olive was the inspiration for the architecture, which required the integration of an auditory periphery (cochlea) model and a model of the medial nucleus of the trapezoid body. The SNN uses leaky integrateand-fire excitatory and inhibitory spiking neurons, facilitating synapses and receptive fields. Experimentally derived headrelated transfer function (HRTF) acoustical data from adult domestic cats were employed to train and validate the localization ability of the architecture, training used the supervised learning algorithm called the remote supervision method to determine the azimuthal angles. The experimental results demonstrate that the architecture performs best when it is localizing high-frequency sound data in agreement with the biology, and also shows a high degree of robustness when the HRTF acoustical data is corrupted by noise.

Population model of the recent subtidal invasion of Sargassum muticum in southern Portugal

Dissertação de Mestrado, Biologia Marinha, Especialização em Ecologia e Conservação, Faculdade de Ciências do Mar e do Ambiente, Universidade do Algarve, 2007

Towards a hydrodynamic operational model of the Algarve coast and St. Vincent Cape

This study attempts to implement a hydrodynamic operational model which can ultimately be used for projecting oil spill dispersal patterns and also sewage, pollution and can also be used in wave forecasting. A two layer nested model was created using MOHID Water, which is powerful ocean modelling software. The first layer (father) is used to impose the boundary conditions for the second layer (son). This was repeated for two different wind dominant regimes, Easterly and Westerly winds respectively. A qualitative comparison was done between measured tidal data and the tidal output. Sea surface temperature was also qualitatively compared with the model’s results. The results from both simulations were analysed and compared to historical literature. The comparison was done at the surface layer, 100 metre depth and at 800m depth. In the surface layer the first simulation generated an upwelling event near Cape St. Vincent and within the Algarve. The second simulation generated a non-upwelling event within which the surface was flow reversed and the warm water mass was along the Algarve coastline and evening turning clockwise around Cape St. Vincent. At the 100 metre depth for both simulations, velocity vortexes were observed near Cape St. Vincent travelling northerly and southerly at various instances. At 800metre depth a strong oceanic flow was observed moving north westerly along the continental shelf.

Going beyond the identification of change facilitators to effectively implement a new model of services: lessons learned from a case example in paediatric rehabilitation

Purpose: To identify facilitators and barriers to service reorganization, how they evolved and interacted to influence change during the implementation of a new service delivery model of paediatric rehabilitation. Methods: Over 3 years, different stakeholders responded to SWOT questionnaires (n = 139) and participated in focus groups (n = 19) and telephone interviews (n = 13). A framework based on socio constructivist theories made sense of the data. Results: Facilitators related to the programme's structure (e.g. funding), the actors (e.g. willingness to test the new service model) and the change management process (e.g. participative approach). Some initial facilitators became barriers (e.g. leadership lacked at the end), while other barriers emerged (e.g. lack of tools). Understanding factor interactions requires examining the multiple actors’ intentions, actions and consequences and their relations with structural elements. Conclusions: Analysing facilitators and barriers helped better understand the change processes, but this must be followed by concrete actions to successfully implement new paediatric rehabilitation models.

Development, implementation, and evaluation of the Apollo model of pediatric rehabilitation service delivery

This article presents the experience of a rehabilitation program that un- dertook the challenge to reorganize its services to address accessibility issues and im- prove service quality. The context in which the reorganization process occurred, along with the relevant literature justifying the need for a new service delivery model, and an historical perspective on the planning; implementation; and evaluation phases of the process are described. In the planning phase, the constitution of the working committee, the data collected, and the information found in the literature are presented. Apollo, the new service delivery model, is then described along with each of its components (e.g., community, group, and individual interventions). Actions and lessons learnt during the implementation of each component are presented. We hope by sharing our experiences that we can help others make informed decisions about service reorganization to im- prove the quality of services provided to children with disabilities, their families, and their communities.

BIMP: A real-time biological model of multi-scale keypoint detection in V1

We present an improved, biologically inspired and multiscale keypoint operator. Models of single- and double-stopped hypercomplex cells in area V1 of the mammalian visual cortex are used to detect stable points of high complexity at multiple scales. Keypoints represent line and edge crossings, junctions and terminations at fine scales, and blobs at coarse scales. They are detected by applying first and second derivatives to responses of complex cells in combination with two inhibition schemes to suppress responses along lines and edges. A number of optimisations make our new algorithm much faster than previous biologically inspired models, achieving real-time performance on modern GPUs and competitive speeds on CPUs. In this paper we show that the keypoints exhibit state-of-the-art repeatability in standardised benchmarks, often yielding best-in-class performance. This makes them interesting both in biological models and as a useful detector in practice. We also show that keypoints can be used as a data selection step, significantly reducing the complexity in state-of-the-art object categorisation. (C) 2014 Elsevier B.V. All rights reserved.

Ecologic zonation model of the benthic foraminifera and thecamoebians of Guadiana river estuary and application in paleoenvironmental reconstruction

Tese de doutoramento, Ciências do Mar ( Processos de Ecossistemas Marinhos), Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2012

A multi-agent-based evolution model of innovation networks in dynamic environments

An innovation network can be considered as a complex adaptive system with evolution affected by dynamic environments. This paper establishes a multi-agent-based evolution model of innovation networks under dynamic settings through computational and logical modeling, and a multi-agent system paradigm. This evolution model is composed of several sub-models of agents' knowledge production by independent innovations in dynamic situations, knowledge learning by cooperative innovations covering agents' heterogeneities, decision-making for innovation selections, and knowledge update considering decay factors. On the basis of above-mentioned sub-models, an evolution rule for multi-agent based innovation network system is given. The proposed evolution model can be utilized to simulate and analyze different scenarios of innovation networks in various dynamic environments and support decision-making for innovation network optimization.

You Can't Always Get What You Want: A Gewirthian Model of Rational Autonomy in Abortion

The law regulating the availability of abortion is problematic both legally and morally. It is dogmatic in its requirements of women and doctors and ignorant of would-be fathers. Practically, its usage is liberal - with s1(1)(a) Abortion Act 1967 treated as a ‘catch all’ ground - it allows abortion on demand. Yet this is not reflected in the ‘law’. Against this outdated legislation I propose a model of autonomy which seeks to tether our moral concerns with a new legal approach to abortion. I do so by maintaining that a legal conception of autonomy is derivable from the categorical imperative resulting from Gewirth’s argument to the Principle of Generic Consistency: Act in accordance with the generic rights of your recipients as well as of yourself. This model of Gewirthian Rational Autonomy, I suggest, provides a guide for both public and private notions of autonomy and how our autonomous interests can be balanced across social structures in order to legitimately empower choice. I claim, ultimately, that relevant rights in the context of abortion are derivable from this model.

Towards an Application-Specific Thermal Energy Model of Current Processors

Recent developments of high-end processors recognize temperature monitoring and tuning as one of the main challenges towards achieving higher performance given the growing power and temperature constraints. To address this challenge, one needs both suitable thermal energy abstraction and corresponding instrumentation. Our model is based on application-specific parameters such as power consumption, execution time, and asymptotic temperature as well as hardware-specific parameters such as half time for thermal rise or fall. As observed with our out-of-band instrumentation and monitoring infrastructure, the temperature changes follow a relatively slow capacitor-style charge-discharge process. Therefore, we use the lumped thermal model that initiates an exponential process whenever there is a change in processor’s power consumption. Initial experiments with two codes – Firestarter and Nekbone – validate our thermal energy model and demonstrate its use for analyzing and potentially improving the application-specific balance between temperature, power, and performance.

Deep-Sea ecosystem model of the Condor seamount

Dissertação de Mestrado, Estudos Integrados dos Oceanos, 25 de Julho 2013, Universidade dos Açores.

Iron Overload in a Murine Model of Hereditary Hemochromatosis Is Associated with Accelerated Progression of Osteoarthritis Under Mechanical Stress

OBJECTIVE: Hereditary hemochromatosis (HH) is a disease caused by mutations in the Hfe gene characterised by systemic iron overload and associated with an increased prevalence of osteoarthritis (OA) but the role of iron overload in the development of OA is still undefined. To further understand the molecular mechanisms involved we have used a murine model of HH and studied the progression of experimental OA under mechanical stress. DESIGN: OA was surgically induced in the knee joints of 10-week-old C57BL6 (wild-type) mice and Hfe-KO mice. OA progression was assessed using histology, micro CT, gene expression and immunohistochemistry at 8 weeks after surgery. RESULTS: Hfe-KO mice showed a systemic iron overload and an increased iron accumulation in the knee synovial membrane following surgery. The histological OA score was significantly higher in the Hfe-KO mice at 8 weeks after surgery. Micro CT study of the proximal tibia revealed increased subchondral bone volume and increased trabecular thickness. Gene expression and immunohistochemical analysis showed a significant increase in the expression of matrix metallopeptidase 3 (MMP-3) in the joints of Hfe-KO mice compared with control mice at 8 weeks after surgery. CONCLUSIONS: HH was associated with an accelerated development of OA in mice. Our findings suggest that synovial iron overload has a definite role in the progression of HH-related OA

How to potentiate the business model of Mobitto for B2B?

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics