Setting the agenda for dental education in Scotland: a priority setting exercise including multiple stakehiolders

Introduction The Scottish Oral Health Research Collaboration identified dental education research (DER) as a key strand of their strategy,(1) leading to the formation of the Dental Education Research Group. The starting point for this group was to understand various stakeholders’ perceptions of research priorities, yet no existing studies were found. The aim of the current study was to identify DER priorities for Scotland in the next 3-5 years. Methods The study utilised a similar methodology to that of Dennis et al,(2) in medical education. Data were collected sequentially using two online questionnaires with multiple dental stakeholders represented at undergraduate and postgraduate levels across urban and rural Scotland. 85 participants completed questionnaire 1 (qualitative) and 649 participants completed questionnaire 2 (quantitative). Qualitative and quantitative data analysis approaches were used. Results Of the 24 priorities identified, the top priorities were: role of assessments in identifying competence; undergraduate curriculum prepares for practice; and promoting teamwork within the dental team. Following factor analysis, the priorities loaded on four factors: teamwork and professionalism, measuring and enhancing performance, personal and professional development challenges, and curriculum integration and innovation. The top barriers were lack of time, funding, staff motivation, valuing of DER, and resources/ infrastructure. Discussion There were many similarities between the identified priorities for dental and medical education research2, but also some notable differences, which will be discussed. Overwhelmingly, the identified priorities in dentistry related to fitness for practice and robust assessment practices. Take home message Priority setting exercises with multiple stakeholders are an important first step in developing a national research strategy. References 1. Bagg J, Macpherson L, Mossey P, Rennie J, Saunders B, Taylor M (2010) Strategy for Oral Health Research in Scotland. Edinburgh: The Scottish Government. 2. Dennis A A, Cleland J A, Johnston P, Ker JS, Lough, M Rees CE (2014) Exploring stakeholders’ views of medical education research priorities: a national study. Medical Education, 48(11): 1078-1091.

The impacts of environmental and anthropogenic stressors on largemouth bass: an integration of field and laboratory studies

Several environmental stressors can impact the physiology and survival of fishes. Fish experience natural fluctuations in temperature and dissolved oxygen, but variations in these parameters due to anthropogenic sources are typically greater in magnitude and duration. Changes in temperature and oxygen of anthropogenic origins may therefore have larger negative impacts on fish than those occurring during natural events. Physiological parameters are sensitive indicators of the impacts of stressors by providing insight into the manner in which fish are disturbed by the stressor. Fish may display cumulative physiological responses to successive stressors, but the concept of synergy among multiple thermal stressors is poorly understood. Further, some fish species can be subjected to competitive angling events, which expose fish to an array of additional stressors that can increase mortality. The impacts of these events may change over seasons as fish display seasonal changes in behavior and physiology. Latitudinal origin may also affect the physiological response and mortality of fish exposed to common environmental stressors as individual populations are adapted to local environmental conditions. This thesis focuses on addressing these potential impacts on physiological parameters and mortality of largemouth bass (Micropterus salmoides) and provides implications for management and conservation. Largemouth bass were relatively robust to abrupt changes in temperature and oxygen, but were perturbed from physiological homeostasis during large (12°C) temperature shocks and low (< 4 mg O2/L) levels of dissolved oxygen. Cumulative physiological impacts of multiple cold shocks were only slightly greater than the disturbances sustained during a single cold shock, suggesting largemouth bass are able to tolerate successive thermal stressors. Largemouth bass exhibited seasonal changes in physiological parameters but the responses of fish to angling tournaments were relatively similar across seasons when compared with seasonal controls. Mortality was low during angling tournaments held during four seasons and no apparent seasonal trends were observed. Lastly, largemouth bass from two latitudinally separated populations exhibited differences in their physiological responses to acute cold stressors and overwinter mortality, characterized by greater mortality and physiological disturbances of southern fish than northern fish. Knowledge gained from this study can be used to make management and conservation decisions regarding a host of environmental factors and provides insight into the mechanisms by which fish species can persist over large latitudinal ranges.

Leveraging Multiple Features for Image Retrieval and Matching

The goal of image retrieval and matching is to find and locate object instances in images from a large-scale image database. While visual features are abundant, how to combine them to improve performance by individual features remains a challenging task. In this work, we focus on leveraging multiple features for accurate and efficient image retrieval and matching. We first propose two graph-based approaches to rerank initially retrieved images for generic image retrieval. In the graph, vertices are images while edges are similarities between image pairs. Our first approach employs a mixture Markov model based on a random walk model on multiple graphs to fuse graphs. We introduce a probabilistic model to compute the importance of each feature for graph fusion under a naive Bayesian formulation, which requires statistics of similarities from a manually labeled dataset containing irrelevant images. To reduce human labeling, we further propose a fully unsupervised reranking algorithm based on a submodular objective function that can be efficiently optimized by greedy algorithm. By maximizing an information gain term over the graph, our submodular function favors a subset of database images that are similar to query images and resemble each other. The function also exploits the rank relationships of images from multiple ranked lists obtained by different features. We then study a more well-defined application, person re-identification, where the database contains labeled images of human bodies captured by multiple cameras. Re-identifications from multiple cameras are regarded as related tasks to exploit shared information. We apply a novel multi-task learning algorithm using both low level features and attributes. A low rank attribute embedding is joint learned within the multi-task learning formulation to embed original binary attributes to a continuous attribute space, where incorrect and incomplete attributes are rectified and recovered. To locate objects in images, we design an object detector based on object proposals and deep convolutional neural networks (CNN) in view of the emergence of deep networks. We improve a Fast RCNN framework and investigate two new strategies to detect objects accurately and efficiently: scale-dependent pooling (SDP) and cascaded rejection classifiers (CRC). The SDP improves detection accuracy by exploiting appropriate convolutional features depending on the scale of input object proposals. The CRC effectively utilizes convolutional features and greatly eliminates negative proposals in a cascaded manner, while maintaining a high recall for true objects. The two strategies together improve the detection accuracy and reduce the computational cost.

Mobility in vehicular networks with multiple access points to the infrastructure

Nowadays there is a huge evolution in the technological world and in the wireless networks. The electronic devices have more capabilities and resources over the years, which makes the users more and more demanding. The necessity of being connected to the global world leads to the arising of wireless access points in the cities to provide internet access to the people in order to keep the constant interaction with the world. Vehicular networks arise to support safety related applications and to improve the traffic flow in the roads; however, nowadays they are also used to provide entertainment to the users present in the vehicles. The best way to increase the utilization of the vehicular networks is to give to the users what they want: a constant connection to the internet. Despite of all the advances in the vehicular networks, there were several issues to be solved. The presence of dedicated infrastructure to vehicular networks is not wide yet, which leads to the need of using the available Wi-Fi hotspots and the cellular networks as access networks. In order to make all the management of the mobility process and to keep the user’s connection and session active, a mobility protocol is needed. Taking into account the huge number of access points present at the range of a vehicle for example in a city, it will be beneficial to take advantage of all available resources in order to improve all the vehicular network, either to the users and to the operators. The concept of multihoming allows to take advantage of all available resources with multiple simultaneous connections. This dissertation has as objectives the integration of a mobility protocol, the Network-Proxy Mobile IPv6 protocol, with a host-multihoming per packet solution in order to increase the performance of the network by using more resources simultaneously, the support of multi-hop communications, either in IPv6 or IPv4, the capability of providing internet access to the users of the network, and the integration of the developed protocol in the vehicular environment, with the WAVE, Wi-Fi and cellular technologies. The performed tests focused on the multihoming features implemented on this dissertation, and on the IPv4 network access for the normal users. The obtained results show that the multihoming addition to the mobility protocol improves the network performance and provides a better resource management. Also, the results show the correct operation of the developed protocol in a vehicular environment.

Establishing continental sovereignty in Africa: risk and opportunity in financial integration - lessons for Africa from a legal perspective

This thesis identifies and defines the new African sovereignty. It establishes a modern sovereignty in Africa hatched from the changing nature of sovereignty in which countries come together at various levels or grades of partial surrender of national sovereignty in order to work closer together for their mutual advantage and benefit. To this end, the narrative zooms in on the central issues within the realms of money matters whereby a new model of monetary sovereignty and monetary solutions is designed in an attempt to ease the recurring tensions and challenges of modern national sovereignty in the continent of Africa. As such, this discussion will offer a historical journey through the constitution of sovereignty, to the birth of the nation state and international public law. It develops the theory of the changing nature of sovereignty within the modern state and opens new lines of inquiry for Africa. In this regard, it draws from juxtaposing and mixing elements of regional and global financial integration as well as retaining national financial sovereignty features to form this new design which I dub continental sovereignty. At its core, the thesis will deal with the legal aspects that stem from the co-mingling of legal systems of nation states and communities at the regional and global levels within the context of financial integration. The argument is that the rule of law remains sacrosanct in monetary management. Effective financial integration is the result of properly structured and managed legal frameworks with robust laws and institutions whether at a national, regional or global level. However, the thesis reveals that in order to avoid undermining the progress of Africa’s financial integration project, any solution for Africa must be immersed within a broader global solution where development issues are addressed and resolved and Africa can form a more central part in all relevant international discussion fora. The work will expound these issues by applying them within a regional and global context, with the state of affairs in Africa forming the nucleus. This application consequently presents the six key themes of the thesis which will be considered therein. They are: a.) regional advantage: which exploits the possibilities of deeper and further financial integration between smaller communal arrangements; b.) regional risk and exposure: the extent to which this deeper form of financial integration can spiral out of control if effected too quickly and too ambitiously; c.) global advantage: which considers the merits of global financial integration and the influence exerted by financial laws on the global financial architecture; d.) global risk and exposure: which considers the challenges of global financial integration especially within the background of the Global Financial Crisis 2007-2008; e.) African challenge: which considers the extent to which this analysis impacts the African economic and financial integration agenda; and f.) development challenge: which examines the extent to which global development issues impact the African solution (continental sovereignty) and the need for any solution for the continent to be roped into a broader global solution within which Africa can form an important part. Even though the thesis requests an optimistic undertone on the progress made so far, it unearths the African problem of multiple national sovereignty and multiple overlapping regional sovereignty constituted as the ‘spaghetti bowl’ dilemma. As such, the unique contribution to knowledge on financial integration in Africa can be echoed in these words: Africa‘s financial integration agenda has had little success in authenticating a systematic and dependable legal framework for monetary management. Efforts made have been incomplete, substandard, and not carefully followed through particularly reflected in the impuissant nature of the judicial enforcement mechanisms. Thus, the thesis argues that, any meaningful answer to the problems dogging the continent is inter alia deeply entrenched within a new form of cooperative monetary sovereignty. In other words, the thesis does not prescribe the creation of new laws; rather it advocates the effective enforcement of existing laws.

Multiple solutions and numerical analysis to the dynamic and stationary models coupling a delayed energy balance model involving latent heat and discontinuous albedo with a deep ocean

We study a climatologically important interaction of two of the main components of the geophysical system by adding an energy balance model for the averaged atmospheric temperature as dynamic boundary condition to a diagnostic ocean model having an additional spatial dimension. In this work, we give deeper insight than previous papers in the literature, mainly with respect to the 1990 pioneering model by Watts and Morantine. We are taking into consideration the latent heat for the two phase ocean as well as a possible delayed term. Non-uniqueness for the initial boundary value problem, uniqueness under a non-degeneracy condition and the existence of multiple stationary solutions are proved here. These multiplicity results suggest that an S-shaped bifurcation diagram should be expected to occur in this class of models generalizing previous energy balance models. The numerical method applied to the model is based on a finite volume scheme with nonlinear weighted essentially non-oscillatory reconstruction and Runge–Kutta total variation diminishing for time integration.

The Road to Bali: ERIA Perspectives on the WTO Ministerial and Asian Integration

The World Trade Organization’s (WTO) forthcoming Ninth Ministerial Conference in Bali comes at a critical juncture for the multilateral trade body, long mired in the Doha Round stalemate. Beyond offering a critical first test at consensus-building and institutional renewal, the Bali Ministerial affords a unique opportunity to gauge contrasting perceptions across ASEAN and East Asian countries of the continued relevance of the WTO to trade and economic governance within the region and beyond. Resulting from the collaborative efforts of the Economic Research Institute for ASEAN and East Asia (ERIA), the Universitas Pelita Harapan (UPH) and the World Trade Institute at the University of Bern (WTI), this policy research initiative offers comparative scholarship on some of the key questions arising from the forthcoming WTO Ministerial gathering from an East Asian perspective. Specifically, it explores what scholars in the region expect the Bali Ministerial to produce by way of tangible outcomes and whether the Ministerial will restore the momentum needed to bring the Doha Round to a successful conclusion. Contributors also investigate how relevant the WTO remains to the multiple processes of deepening economic integration in ASEAN and East Asia (e.g. AEC, TPP, RCEP) and, importantly, what lessons in rule-design and market opening WTO Members could usefully draw from the ongoing march towards the establishment of an ASEAN Economic Community.

Evolution of classifiers for pitch estimation of piano music using cartesian genetic programming

Pitch Estimation, also known as Fundamental Frequency (F0) estimation, has been a popular research topic for many years, and is still investigated nowadays. The goal of Pitch Estimation is to find the pitch or fundamental frequency of a digital recording of a speech or musical notes. It plays an important role, because it is the key to identify which notes are being played and at what time. Pitch Estimation of real instruments is a very hard task to address. Each instrument has its own physical characteristics, which reflects in different spectral characteristics. Furthermore, the recording conditions can vary from studio to studio and background noises must be considered. This dissertation presents a novel approach to the problem of Pitch Estimation, using Cartesian Genetic Programming (CGP).We take advantage of evolutionary algorithms, in particular CGP, to explore and evolve complex mathematical functions that act as classifiers. These classifiers are used to identify piano notes pitches in an audio signal. To help us with the codification of the problem, we built a highly flexible CGP Toolbox, generic enough to encode different kind of programs. The encoded evolutionary algorithm is the one known as 1 + , and we can choose the value for . The toolbox is very simple to use. Settings such as the mutation probability, number of runs and generations are configurable. The cartesian representation of CGP can take multiple forms and it is able to encode function parameters. It is prepared to handle with different type of fitness functions: minimization of f(x) and maximization of f(x) and has a useful system of callbacks. We trained 61 classifiers corresponding to 61 piano notes. A training set of audio signals was used for each of the classifiers: half were signals with the same pitch as the classifier (true positive signals) and the other half were signals with different pitches (true negative signals). F-measure was used for the fitness function. Signals with the same pitch of the classifier that were correctly identified by the classifier, count as a true positives. Signals with the same pitch of the classifier that were not correctly identified by the classifier, count as a false negatives. Signals with different pitch of the classifier that were not identified by the classifier, count as a true negatives. Signals with different pitch of the classifier that were identified by the classifier, count as a false positives. Our first approach was to evolve classifiers for identifying artifical signals, created by mathematical functions: sine, sawtooth and square waves. Our function set is basically composed by filtering operations on vectors and by arithmetic operations with constants and vectors. All the classifiers correctly identified true positive signals and did not identify true negative signals. We then moved to real audio recordings. For testing the classifiers, we picked different audio signals from the ones used during the training phase. For a first approach, the obtained results were very promising, but could be improved. We have made slight changes to our approach and the number of false positives reduced 33%, compared to the first approach. We then applied the evolved classifiers to polyphonic audio signals, and the results indicate that our approach is a good starting point for addressing the problem of Pitch Estimation.

A systemic model for differentiating school technology integration

School technology integration rarely begins with school or educator choice. It is part of a wider context where external and internal factors have direct influence on the goals and tools that are adopted over time. The objective of this study is to investigate the systemic conditions that contribute or inhibit the development of different activities by teachers making use of new media. We compiled a list of well-known conditions for technology integration success and mapped these in the historical and culturally bound perspective of activity theory (cultural historical activity theory). We conducted a multiple case study analysis of four schools, public and private. The results point to unique and distinctive scenarios even when homogeneity would be expected, reinforcing the argument that material conditions do not determine pedagogical outcomes nor do they determine changes in practice. Beyond this, the study proposes a methodology that can help elicit tensions in technology integration, pointing to avenues for school development.

Towards Unstructured Knowledge Integration in Natural Language Processing

In the last decades, Artificial Intelligence has witnessed multiple breakthroughs in deep learning. In particular, purely data-driven approaches have opened to a wide variety of successful applications due to the large availability of data. Nonetheless, the integration of prior knowledge is still required to compensate for specific issues like lack of generalization from limited data, fairness, robustness, and biases. In this thesis, we analyze the methodology of integrating knowledge into deep learning models in the field of Natural Language Processing (NLP). We start by remarking on the importance of knowledge integration. We highlight the possible shortcomings of these approaches and investigate the implications of integrating unstructured textual knowledge. We introduce Unstructured Knowledge Integration (UKI) as the process of integrating unstructured knowledge into machine learning models. We discuss UKI in the field of NLP, where knowledge is represented in a natural language format. We identify UKI as a complex process comprised of multiple sub-processes, different knowledge types, and knowledge integration properties to guarantee. We remark on the challenges of integrating unstructured textual knowledge and bridge connections with well-known research areas in NLP. We provide a unified vision of structured knowledge extraction (KE) and UKI by identifying KE as a sub-process of UKI. We investigate some challenging scenarios where structured knowledge is not a feasible prior assumption and formulate each task from the point of view of UKI. We adopt simple yet effective neural architectures and discuss the challenges of such an approach. Finally, we identify KE as a form of symbolic representation. From this perspective, we remark on the need of defining sophisticated UKI processes to verify the validity of knowledge integration. To this end, we foresee frameworks capable of combining symbolic and sub-symbolic representations for learning as a solution.

Development of machine learning methods for multi-modal biomarkers detection and integration

In medicine, innovation depends on a better knowledge of the human body mechanism, which represents a complex system of multi-scale constituents. Unraveling the complexity underneath diseases proves to be challenging. A deep understanding of the inner workings comes with dealing with many heterogeneous information. Exploring the molecular status and the organization of genes, proteins, metabolites provides insights on what is driving a disease, from aggressiveness to curability. Molecular constituents, however, are only the building blocks of the human body and cannot currently tell the whole story of diseases. This is why nowadays attention is growing towards the contemporary exploitation of multi-scale information. Holistic methods are then drawing interest to address the problem of integrating heterogeneous data. The heterogeneity may derive from the diversity across data types and from the diversity within diseases. Here, four studies conducted data integration using customly designed workflows that implement novel methods and views to tackle the heterogeneous characterization of diseases. The first study devoted to determine shared gene regulatory signatures for onco-hematology and it showed partial co-regulation across blood-related diseases. The second study focused on Acute Myeloid Leukemia and refined the unsupervised integration of genomic alterations, which turned out to better resemble clinical practice. In the third study, network integration for artherosclerosis demonstrated, as a proof of concept, the impact of network intelligibility when it comes to model heterogeneous data, which showed to accelerate the identification of new potential pharmaceutical targets. Lastly, the fourth study introduced a new method to integrate multiple data types in a unique latent heterogeneous-representation that facilitated the selection of important data types to predict the tumour stage of invasive ductal carcinoma. The results of these four studies laid the groundwork to ease the detection of new biomarkers ultimately beneficial to medical practice and to the ever-growing field of Personalized Medicine.

Integration of the computer controlled screwdriver for Robotic manufacturing in the ROS environment

The computer controlled screwdriver is a modern technique to perform automatic screwing/unscrewing operations.The main focus is to study the integration of the computer controlled screwdriver for Robotic manufacturing in the ROS environment.This thesis describes a concept of automatic screwing mechanism composed by universal robots, in which one arm of the robot is for inserting cables and the other is for screwing the cables on the control panel switch gear box. So far this mechanism is carried out by human operators and is a fairly complex one to perform, due to the multiple cables and connections involved. It's for this reason that an automatic cabling and screwing process would be highly preferred within automotive/automation industries. A study is carried out to analyze the difficulties currently faced and a controller based algorithm is developed to replace the manual human efforts using universal robots, thereby allowing robot arms to insert the cables and screw them onto the control panel switch gear box. Experiments were conducted to evaluate the insertion and screwing strategy, which shows the result of inserting and screwing cables on the control panel switch gearbox precisely.

Integration of ROS for the control of industrial robotic systems in a proprietary environment

The paper deals with the integration of ROS, in the proprietary environment of the Marchesini Group company, for the control of industrial robotic systems. The basic tools of this open-source software are deeply studied to model a full proprietary Pick and Place manipulator inside it, and to develop custom ROS nodes to calculate trajectories; speaking of which, the URDF format is the standard to represent robots in ROS and the motion planning framework MoveIt offers user-friendly high-level methods. The communication between ROS and the Marchesini control architecture is established using the OPC UA standard; the tasks computed are transmitted offline to the PLC, supervisor controller of the physical robot, because the performances of the protocol don’t allow any kind of active control by ROS. Once the data are completely stored at the Marchesini side, the industrial PC makes the real robot execute a trajectory computed by MoveIt, so that it replicates the behaviour of the simulated manipulator in Rviz. Multiple experiments are performed to evaluate in detail the potential of ROS in the planning of movements for the company proprietary robots. The project ends with a small study regarding the use of ROS as a simulation platform. First, it is necessary to understand how a robotic application of the company can be reproduced in the Gazebo real world simulator. Then, a ROS node extracts information and examines the simulated robot behaviour, through the subscription to specific topics.

The Clinical Impact Of Cerebellar Grey Matter Pathology In Multiple Sclerosis.

The cerebellum is an important site for cortical demyelination in multiple sclerosis, but the functional significance of this finding is not fully understood. To evaluate the clinical and cognitive impact of cerebellar grey-matter pathology in multiple sclerosis patients. Forty-two relapsing-remitting multiple sclerosis patients and 30 controls underwent clinical assessment including the Multiple Sclerosis Functional Composite, Expanded Disability Status Scale (EDSS) and cerebellar functional system (FS) score, and cognitive evaluation, including the Paced Auditory Serial Addition Test (PASAT) and the Symbol-Digit Modalities Test (SDMT). Magnetic resonance imaging was performed with a 3T scanner and variables of interest were: brain white-matter and cortical lesion load, cerebellar intracortical and leukocortical lesion volumes, and brain cortical and cerebellar white-matter and grey-matter volumes. After multivariate analysis high burden of cerebellar intracortical lesions was the only predictor for the EDSS (p<0.001), cerebellar FS (p = 0.002), arm function (p = 0.049), and for leg function (p<0.001). Patients with high burden of cerebellar leukocortical lesions had lower PASAT scores (p = 0.013), while patients with greater volumes of cerebellar intracortical lesions had worse SDMT scores (p = 0.015). Cerebellar grey-matter pathology is widely present and contributes to clinical dysfunction in relapsing-remitting multiple sclerosis patients, independently of brain grey-matter damage.

Multiple Desmoid Tumors In A Patient With Gardner's Syndrome - Report Of A Case.

Desmoid tumor (DT) is a common manifestation of Gardner's Syndrome (GS), although it is a rare condition in the general population. DT in patients with GS is usually located in the abdominal wall and/or intra-abdominal cavity. We report a case of a 32 years-old female patient with familial adenomatous polyposis (FAP), who was already submitted to total colectomy and developed multiple DT, located in the abdominal wall and in the left breast. The patient underwent several surgical procedures, with a multidisciplinary team of surgeons. Wide surgical resections of the left breast and the abdominal wall tumors were performed in separate steps. Polypropylene mesh reconstruction and muscle flaps were needed to cover the defects of the thoracic and abdominal walls. After partial necrosis of the adipose-cutaneous flap in the abdomen that required a new skin graft, she had a satisfactory outcome with complete healing of the surgical incisions. DT is frequent in GS, however, breast localization is very rare, with few cases reported in the literature. Recurrence of DT is not negligible, even after a wide surgical resection. GS patients must be followed up closely, and clinical examination, associated with imaging studies, should be performed to detect any signs of tumor. DT represents one of the most significant causes of the morbidity and mortality that affects FAP patients following colectomy. In general, the surgical procedures to excise DT are highly complex, requiring a multidisciplinary team.