Objective Structured Clinical Examinations (OSCE) improved communication skills of student of Pharmacology in Medicine and Podiatry degree.

Objective Structured Clinical Examinations (OSCE) improved communication skills of student of Pharmacology in Medicine and Podiatry degree. Bellido I, Blanco E, Gomez-Luque A. D. Pharmacology and Clinical Therapeutic. Medicine School. University of Malaga. IBIMA. Malaga, Spain. Objective Structured Clinical Examinations (OSCEs) are versatile multipurpose evaluative tools that can be utilized to assess health care professionals in a clinical setting including communication skills and ability to handle unpredictable patient behavior, which usually are not included in the traditional clinical exam. To designee and perform OSCEs by student is a novelty that really like to the students and may improve their arguing and planning capacities and their communication skills. Aim: To evaluate the impact of designing, developing and presenting Objective Structured Clinical Examinations (OSCE) by student in the communication skills development and in the learning of medicines in Medicine and Podiatry undergraduate students. Methods: A one-year study in which students were invited to voluntarily form groups (4 students maximum). Each group has to design and perform an OSCE (10 min maximum) showing a clinical situation/problem in which medicines’ use was needed. A clinical history, camera, a mobile-phone's video editor, photos, actors, dolls, simulators or whatever they may use was allowed. The job of each group was supervised and helped by a teacher. The students were invited to present their work to the rest of the class. After each OSCE performance the students were encouraged to ask questions if they wanted to do it. After all the OSCEs performances the students voluntarily answered a satisfaction survey. Results: Students of Pharmacology of Medicine degree and Podiatry degree, N=80, 53.75% female, 21±2.3 years old were enrolled. 26 OSCEs showing a clinical situation or clinical problem were made. The average time spent by students in making the OSCE was 21.5±9 h. The percentage of students which were satisfied with this way of presentation of the OSCE was 89.7%. Conclusion: Objective Structured Clinical Examinations (OSCE) designed and performed by student of Pharmacology of the Medicine and Podiatry Degree improved their communication skills.

Triangular mesh parameterization with trimmed surfaces

Given a 2manifold triangular mesh \(M \subset {\mathbb {R}}^3\), with border, a parameterization of \(M\) is a FACE or trimmed surface \(F=\{S,L_0,\ldots, L_m\}\) -- \(F\) is a connected subset or region of a parametric surface \(S\), bounded by a set of LOOPs \(L_0,\ldots ,L_m\) such that each \(L_i \subset S\) is a closed 1manifold having no intersection with the other \(L_j\) LOOPs -- The parametric surface \(S\) is a statistical fit of the mesh \(M\) -- \(L_0\) is the outermost LOOP bounding \(F\) and \(L_i\) is the LOOP of the ith hole in \(F\) (if any) -- The problem of parameterizing triangular meshes is relevant for reverse engineering, tool path planning, feature detection, redesign, etc -- Stateofart mesh procedures parameterize a rectangular mesh \(M\) -- To improve such procedures, we report here the implementation of an algorithm which parameterizes meshes \(M\) presenting holes and concavities -- We synthesize a parametric surface \(S \subset {\mathbb {R}}^3\) which approximates a superset of the mesh \(M\) -- Then, we compute a set of LOOPs trimming \(S\), and therefore completing the FACE \(F=\ {S,L_0,\ldots ,L_m\}\) -- Our algorithm gives satisfactory results for \(M\) having low Gaussian curvature (i.e., \(M\) being quasi-developable or developable) -- This assumption is a reasonable one, since \(M\) is the product of manifold segmentation preprocessing -- Our algorithm computes: (1) a manifold learning mapping \(\phi : M \rightarrow U \subset {\mathbb {R}}^2\), (2) an inverse mapping \(S: W \subset {\mathbb {R}}^2 \rightarrow {\mathbb {R}}^3\), with \ (W\) being a rectangular grid containing and surpassing \(U\) -- To compute \(\phi\) we test IsoMap, Laplacian Eigenmaps and Hessian local linear embedding (best results with HLLE) -- For the back mapping (NURBS) \(S\) the crucial step is to find a control polyhedron \(P\), which is an extrapolation of \(M\) -- We calculate \(P\) by extrapolating radial basis functions that interpolate points inside \(\phi (M)\) -- We successfully test our implementation with several datasets presenting concavities, holes, and are extremely nondevelopable -- Ongoing work is being devoted to manifold segmentation which facilitates mesh parameterization

Pseudospectral methods and numerical continuation for the analysis os structured population models.

191 p.

Surface structured platinum electrodes for the electrochemical reduction of carbon dioxide in imidazolium based ionic liquids

The direct CO2 electrochemical reduction on model platinum single crystal electrodes Pt(hkl) is studied in [C2mim+][NTf2−], a suitable room temperature ionic liquid (RTIL) medium due to its moderate viscosity, high CO2 solubility and conductivity. Single crystal electrodes represent the most convenient type of surface structured electrodes for studying the impact of RTIL ion adsorption on relevant electrocatalytic reactions, such as surface sensitive electrochemical CO2 reduction. We propose here based on cyclic voltammetry and in situ electrolysis measurements, for the first time, the formation of a stable adduct [C2mimH–CO2−] by a radical–radical coupling after the simultaneous reduction of CO2 and [C2mim+]. It means between the CO2 radical anion and the radical formed from the reduction of the cation [C2mim+] before forming the corresponding electrogenerated carbene. This is confirmed by the voltammetric study of a model imidazolium-2-carboxylate compound formed following the carbene pathway. The formation of that stable adduct [C2mimH–CO2−] blocks CO2 reduction after a single electron transfer and inhibits CO2 and imidazolium dimerization reactions. However, the electrochemical reduction of CO2 under those conditions provokes the electrochemical cathodic degradation of the imidazolium based RTIL. This important limitation in CO2 recycling by direct electrochemical reduction is overcome by adding a strong acid, [H+][NTf2−], into solution. Then, protons become preferentially adsorbed on the electrode surface by displacing the imidazolium cations and inhibiting their electrochemical reduction. This fact allows the surface sensitive electro-synthesis of HCOOH from CO2 reduction in [C2mim+][NTf2−], with Pt(110) being the most active electrode studied.

Development of an innovative non rule-based energy management strategy for a Hybrid Electric Vehicle, structured for predictive driving controls based on external information knowledge

Recently, the interest of the automotive market for hybrid vehicles has increased due to the more restrictive pollutants emissions legislation and to the necessity of decreasing the fossil fuel consumption, since such solution allows a consistent improvement of the vehicle global efficiency. The term hybridization regards the energy flow in the powertrain of a vehicle: a standard vehicle has, usually, only one energy source and one energy tank; instead, a hybrid vehicle has at least two energy sources. In most cases, the prime mover is an internal combustion engine (ICE) while the auxiliary energy source can be mechanical, electrical, pneumatic or hydraulic. It is expected from the control unit of a hybrid vehicle the use of the ICE in high efficiency working zones and to shut it down when it is more convenient, while using the EMG at partial loads and as a fast torque response during transients. However, the battery state of charge may represent a limitation for such a strategy. That’s the reason why, in most cases, energy management strategies are based on the State Of Charge, or SOC, control. Several studies have been conducted on this topic and many different approaches have been illustrated. The purpose of this dissertation is to develop an online (usable on-board) control strategy in which the operating modes are defined using an instantaneous optimization method that minimizes the equivalent fuel consumption of a hybrid electric vehicle. The equivalent fuel consumption is calculated by taking into account the total energy used by the hybrid powertrain during the propulsion phases. The first section presents the hybrid vehicles characteristics. The second chapter describes the global model, with a particular focus on the energy management strategies usable for the supervisory control of such a powertrain. The third chapter shows the performance of the implemented controller on a NEDC cycle compared with the one obtained with the original control strategy.

Towards flexible parsing of structured textual model representations

Existing parsers for textual model representation formats such as XMI and HUTN are unforgiving and fail upon even the smallest inconsistency between the structure and naming of metamodel elements and the contents of serialised models. In this paper, we demonstrate how a fuzzy parsing approach can transparently and automatically resolve a number of these inconsistencies, and how it can eventually turn XML into a human-readable and editable textual model representation format for particular classes of models.

Structured professional judgement approach to risk assessment: generalisability across patient groups for the prediction of adverse outcomes in secure mental health care

This is a redacted version of the the final thesis. Copyright material has been removed to comply with UK Copyright Law.

Query routing in cooperative semi-structured peer-to-peer information retrieval networks

Conventional web search engines are centralised in that a single entity crawls and indexes the documents selected for future retrieval, and the relevance models used to determine which documents are relevant to a given user query. As a result, these search engines suffer from several technical drawbacks such as handling scale, timeliness and reliability, in addition to ethical concerns such as commercial manipulation and information censorship. Alleviating the need to rely entirely on a single entity, Peer-to-Peer (P2P) Information Retrieval (IR) has been proposed as a solution, as it distributes the functional components of a web search engine – from crawling and indexing documents, to query processing – across the network of users (or, peers) who use the search engine. This strategy for constructing an IR system poses several efficiency and effectiveness challenges which have been identified in past work. Accordingly, this thesis makes several contributions towards advancing the state of the art in P2P-IR effectiveness by improving the query processing and relevance scoring aspects of a P2P web search. Federated search systems are a form of distributed information retrieval model that route the user’s information need, formulated as a query, to distributed resources and merge the retrieved result lists into a final list. P2P-IR networks are one form of federated search in routing queries and merging result among participating peers. The query is propagated through disseminated nodes to hit the peers that are most likely to contain relevant documents, then the retrieved result lists are merged at different points along the path from the relevant peers to the query initializer (or namely, customer). However, query routing in P2P-IR networks is considered as one of the major challenges and critical part in P2P-IR networks; as the relevant peers might be lost in low-quality peer selection while executing the query routing, and inevitably lead to less effective retrieval results. This motivates this thesis to study and propose query routing techniques to improve retrieval quality in such networks. Cluster-based semi-structured P2P-IR networks exploit the cluster hypothesis to organise the peers into similar semantic clusters where each such semantic cluster is managed by super-peers. In this thesis, I construct three semi-structured P2P-IR models and examine their retrieval effectiveness. I also leverage the cluster centroids at the super-peer level as content representations gathered from cooperative peers to propose a query routing approach called Inverted PeerCluster Index (IPI) that simulates the conventional inverted index of the centralised corpus to organise the statistics of peers’ terms. The results show a competitive retrieval quality in comparison to baseline approaches. Furthermore, I study the applicability of using the conventional Information Retrieval models as peer selection approaches where each peer can be considered as a big document of documents. The experimental evaluation shows comparative and significant results and explains that document retrieval methods are very effective for peer selection that brings back the analogy between documents and peers. Additionally, Learning to Rank (LtR) algorithms are exploited to build a learned classifier for peer ranking at the super-peer level. The experiments show significant results with state-of-the-art resource selection methods and competitive results to corresponding classification-based approaches. Finally, I propose reputation-based query routing approaches that exploit the idea of providing feedback on a specific item in the social community networks and manage it for future decision-making. The system monitors users’ behaviours when they click or download documents from the final ranked list as implicit feedback and mines the given information to build a reputation-based data structure. The data structure is used to score peers and then rank them for query routing. I conduct a set of experiments to cover various scenarios including noisy feedback information (i.e, providing positive feedback on non-relevant documents) to examine the robustness of reputation-based approaches. The empirical evaluation shows significant results in almost all measurement metrics with approximate improvement more than 56% compared to baseline approaches. Thus, based on the results, if one were to choose one technique, reputation-based approaches are clearly the natural choices which also can be deployed on any P2P network.

Nanofibrous-structured polymers and their engineering applications

Monolithic materials cannot always satisfy the demands of today’s advanced requirements. Only by combining several materials at different length-scales, as nature does, the requested performances can be met. Polymer nanocomposites are intended to overcome the common drawbacks of pristine polymers, with a multidisciplinary collaboration of material science with chemistry, engineering, and nanotechnology. These materials are an active combination of polymers and nanomaterials, where at least one phase lies in the nanometer range. By mimicking nature’s materials is possible to develop new nanocomposites for structural applications demanding combinations of strength and toughness. In this perspective, nanofibers obtained by electrospinning have been increasingly adopted in the last decade to improve the fracture toughness of Fiber Reinforced Plastic (FRP) laminates. Although nanofibers have already found applications in various fields, their widespread introduction in the industrial context is still a long way to go. This thesis aims to develop methodologies and models able to predict the behaviour of nanofibrous-reinforced polymers, paving the way for their practical engineering applications. It consists of two main parts. The first one investigates the mechanisms that act at the nanoscale, systematically evaluating the mechanical properties of both the nanofibrous reinforcement phase (Chapter 1) and hosting polymeric matrix (Chapter 2). The second part deals with the implementation of different types of nanofibers for novel pioneering applications, trying to combine the well-known fracture toughness enhancement in composite laminates with improving other mechanical properties or including novel functionalities. Chapter 3 reports the development of novel adhesive carriers made of nylon 6,6 nanofibrous mats to increase the fracture toughness of epoxy-bonded joints. In Chapter 4, recently developed rubbery nanofibers are used to enhance the damping properties of unidirectional carbon fiber laminates. Lastly, in Chapter 5, a novel self-sensing composite laminate capable of detecting impacts on its surface using PVDF-TrFE piezoelectric nanofibers is presented.

The space for social media in structured online learning

In this paper, we explore the benefits of using social media in an online educational setting, with a particular focus on the use of Facebook and Twitter by participants in a Massive Open Online Course (MOOC) developed to enable educators to learn about the Carpe Diem learning design process. We define social media as digital social tools and environments located outside of the provision of a formal university-provided Learning Management System. We use data collected via interviews and surveys with the MOOC participants as well as social media postings made by the participants throughout the MOOC to offer insights into how participants’ usage and perception of social media in their online learning experiences differed and why. We identified that, although some participants benefitted from social media by crediting it, for example, with networking and knowledge-sharing opportunities, others objected or refused to engage with social media, perceiving it as a waste of their time. We make recommendations for the usage of social media for educational purposes within MOOCs and formal digital learning environments.

Learning representations for graph-structured socio-technical systems

The recent widespread use of social media platforms and web services has led to a vast amount of behavioral data that can be used to model socio-technical systems. A significant part of this data can be represented as graphs or networks, which have become the prevalent mathematical framework for studying the structure and the dynamics of complex interacting systems. However, analyzing and understanding these data presents new challenges due to their increasing complexity and diversity. For instance, the characterization of real-world networks includes the need of accounting for their temporal dimension, together with incorporating higher-order interactions beyond the traditional pairwise formalism. The ongoing growth of AI has led to the integration of traditional graph mining techniques with representation learning and low-dimensional embeddings of networks to address current challenges. These methods capture the underlying similarities and geometry of graph-shaped data, generating latent representations that enable the resolution of various tasks, such as link prediction, node classification, and graph clustering. As these techniques gain popularity, there is even a growing concern about their responsible use. In particular, there has been an increased emphasis on addressing the limitations of interpretability in graph representation learning. This thesis contributes to the advancement of knowledge in the field of graph representation learning and has potential applications in a wide range of complex systems domains. We initially focus on forecasting problems related to face-to-face contact networks with time-varying graph embeddings. Then, we study hyperedge prediction and reconstruction with simplicial complex embeddings. Finally, we analyze the problem of interpreting latent dimensions in node embeddings for graphs. The proposed models are extensively evaluated in multiple experimental settings and the results demonstrate their effectiveness and reliability, achieving state-of-the-art performances and providing valuable insights into the properties of the learned representations.

Towards a sustainable approach for Cultural Heritage Conservation: developing micro-structured green materials and analytical protocols for their performance assessment

Cleaning is one of the most important and delicate procedures that are part of the restoration process. When developing new systems, it is fundamental to consider its selectivity towards the layer to-be-removed, non-invasiveness towards the one to-be-preserved, its sustainability and non-toxicity. Besides assessing its efficacy, it is important to understand its mechanism by analytical protocols that strike a balance between cost, practicality, and reliable interpretation of results. In this thesis, the development of cleaning systems based on the coupling of electrospun fabrics (ES) and greener organic solvents is proposed. Electrospinning is a versatile technique that allows the production of micro/nanostructured non-woven mats, which have already been used as absorbents in various scientific fields, but to date, not in the restoration field. The systems produced proved to be effective for the removal of dammar varnish from paintings, where the ES not only act as solvent-binding agents but also as adsorbents towards the partially solubilised varnish due to capillary rise, thus enabling a one-step procedure. They have also been successfully applied for the removal of spray varnish from marble substrates and wall paintings. Due to the materials' complexity, the procedure had to be adapted case-by-case and mechanical action was still necessary. According to the spinning solution, three types of ES mats have been produced: polyamide 6,6, pullulan and pullulan with melanin nanoparticles. The latter, under irradiation, allows for a localised temperature increase accelerating and facilitating the removal of less soluble layers (e.g. reticulated alkyd-based paints). All the systems produced, and the mock-ups used were extensively characterised using multi-analytical protocols. Finally, a monitoring protocol and image treatment based on photoluminescence macro-imaging is proposed. This set-up allowed the study of the removal mechanism of dammar varnish and semi-quantify its residues. These initial results form the basis for optimising the acquisition set-up and data processing.

[the Sociology Of Health In Brazil - The Creation Of An Identity].

This article analyzes the historical, social and cognitive dimensions of the sociology of medicine in the construction of its identity, from Wolf Lepenies' perspective. It is understood that the construction of an identity does not end with the first historical manifestations, but is consolidated when it is institutionalized and structured as a field of knowledge by creating its own forms of cognitive expression. The text is divided into three parts: in the first the precursors are presented, highlighting the role played by some travelers, naturalists and folklore scholars, followed by social physicians-scientists and the first social scientists (1940-1969). In the second part, aspects of the consolidation of the social sciences in health are presented at two significant moments, namely the 1970s and 1980s. In the third part, the issues raised by the field are addressed in general terms. It is considered that once the main structural stages are in place there is still a need for the formation of new generations of social scientists in health. It is also essential to disseminate scientific production and to ensure that the relations are studied in depth and institutionalized with the sociological matrices on the one hand and with the field of health on the other.