Arthroscopy or ultrasound in undergraduate anatomy education: a randomized cross-over controlled trial

Background: The exponential growth of image-based diagnostic and minimally invasive interventions requires a detailed three-dimensional anatomical knowledge and increases the demand towards the undergraduate anatomical curriculum. This randomized controlled trial investigates whether musculoskeletal ultrasound (MSUS) or arthroscopic methods can increase the anatomical knowledge uptake. Methods: Second-year medical students were randomly allocated to three groups. In addition to the compulsory dissection course, the ultrasound group (MSUS) was taught by eight, didactically and professionally trained, experienced student-teachers and the arthroscopy group (ASK) was taught by eight experienced physicians. The control group (CON) acquired the anatomical knowledge only via the dissection course. Exposure (MSUS and ASK) took place in two separate lessons (75 minutes each, shoulder and knee joint) and introduced standard scan planes using a 10-MHz ultrasound system as well as arthroscopy tutorials at a simulator combined with video tutorials. The theoretical anatomic learning outcomes were tested using a multiple-choice questionnaire (MCQ), and after cross-over an objective structured clinical examination (OSCE). Differences in student's perceptions were evaluated using Likert scale-based items. Results: The ASK-group (n = 70, age 23.4 (20--36) yrs.) performed moderately better in the anatomical MC exam in comparison to the MSUS-group (n = 84, age 24.2 (20--53) yrs.) and the CON-group (n = 88, 22.8 (20--33) yrs.; p = 0.019). After an additional arthroscopy teaching 1 % of students failed the MC exam, in contrast to 10 % in the MSUS- or CON-group, respectively. The benefit of the ASK module was limited to the shoulder area (p < 0.001). The final examination (OSCE) showed no significant differences between any of the groups with good overall performances. In the evaluation, the students certified the arthroscopic tutorial a greater advantage concerning anatomical skills with higher spatial imagination in comparison to the ultrasound tutorial (p = 0.002; p < 0.001). Conclusions: The additional implementation of arthroscopy tutorials to the dissection course during the undergraduate anatomy training is profitable and attractive to students with respect to complex joint anatomy. Simultaneous teaching of basic-skills in musculoskeletal ultrasound should be performed by medical experts, but seems to be inferior to the arthroscopic 2D-3D-transformation, and is regarded by students as more difficult to learn. Although arthroscopy and ultrasound teaching do not have a major effect on learning joint anatomy, they have the potency to raise the interest in surgery

Proceedings of the ECCS 2005 satellite workshop: embracing complexity in design - Paris 17 November 2005

Embracing complexity in design is one of the critical issues and challenges of the 21st century. As the realization grows that design activities and artefacts display properties associated with complex adaptive systems, so grows the need to use complexity concepts and methods to understand these properties and inform the design of better artifacts. It is a great challenge because complexity science represents an epistemological and methodological swift that promises a holistic approach in the understanding and operational support of design. But design is also a major contributor in complexity research. Design science is concerned with problems that are fundamental in the sciences in general and complexity sciences in particular. For instance, design has been perceived and studied as a ubiquitous activity inherent in every human activity, as the art of generating hypotheses, as a type of experiment, or as a creative co-evolutionary process. Design science and its established approaches and practices can be a great source for advancement and innovation in complexity science. These proceedings are the result of a workshop organized as part of the activities of a UK government AHRB/EPSRC funded research cluster called Embracing Complexity in Design (www.complexityanddesign.net) and the European Conference in Complex Systems (complexsystems.lri.fr). Embracing complexity in design is one of the critical issues and challenges of the 21st century. As the realization grows that design activities and artefacts display properties associated with complex adaptive systems, so grows the need to use complexity concepts and methods to understand these properties and inform the design of better artifacts. It is a great challenge because complexity science represents an epistemological and methodological swift that promises a holistic approach in the understanding and operational support of design. But design is also a major contributor in complexity research. Design science is concerned with problems that are fundamental in the sciences in general and complexity sciences in particular. For instance, design has been perceived and studied as a ubiquitous activity inherent in every human activity, as the art of generating hypotheses, as a type of experiment, or as a creative co-evolutionary process. Design science and its established approaches and practices can be a great source for advancement and innovation in complexity science. These proceedings are the result of a workshop organized as part of the activities of a UK government AHRB/EPSRC funded research cluster called Embracing Complexity in Design (www.complexityanddesign.net) and the European Conference in Complex Systems (complexsystems.lri.fr)

Simulating Light-Weight Personalised Recommender Systems in Learning Networks: A Case for Pedagogy-Oriented and Rating-Based Hybrid Recommendation Strategies

Recommender systems for e-learning demand specific pedagogy-oriented and hybrid recommendation strategies. Current systems are often based on time-consuming, top down information provisioning combined with intensive data-mining collaborative filtering approaches. However, such systems do not seem appropriate for Learning Networks where distributed information can often not be identified beforehand. Providing sound way-finding support for lifelong learners in Learning Networks requires dedicated personalised recommender systems (PRS), that offer the learners customised advise on which learning actions or programs to study next. Such systems should also be practically feasible and be developed with minimized effort. Currently, such so called light-weight PRS systems are scarcely available. This study shows that simulation studies can support the analysis and optimisation of PRS requirements prior to starting the costly process of their development, and practical implementation (including testing and revision) during field experiments in real-life learning situations. This simulation study confirms that providing recommendations leads towards more effective, more satisfied, and faster goal achievement. Furthermore, this study reveals that a light-weight hybrid PRS-system based on ratings is a good alternative for an ontology-based system, in particular for low-level goal achievement. Finally, it is found that rating-based light-weight hybrid PRS-systems enable more effective, more satisfied, and faster goal attainment than peer-based light-weight hybrid PRS-systems (incorporating collaborative techniques without rating).Recommendation Strategy; Simulation Study; Way-Finding; Collaborative Filtering; Rating

Developing serious games for cultural heritage: a state-of-the-art review

Although the widespread use of gaming for leisure purposes has been well documented, the use of games to support cultural heritage purposes, such as historical teaching and learning, or for enhancing museum visits, has been less well considered. The state-of-the-art in serious game technology is identical to that of the state-of-the-art in entertainment games technology. As a result, the field of serious heritage games concerns itself with recent advances in computer games, real-time computer graphics, virtual and augmented reality and artificial intelligence. On the other hand, the main strengths of serious gaming applications may be generalised as being in the areas of communication, visual expression of information, collaboration mechanisms, interactivity and entertainment. In this report, we will focus on the state-of-the-art with respect to the theories, methods and technologies used in serious heritage games. We provide an overview of existing literature of relevance to the domain, discuss the strengths and weaknesses of the described methods and point out unsolved problems and challenges. In addition, several case studies illustrating the application of methods and technologies used in cultural heritage are presented

Serious Games in Cultural Heritage

Although the widespread use of gaming for leisure purposes has been well documented, the use of games to support cultural heritage purposes, such as historical teaching and learning, or for enhancing museum visits, has been less well considered. The state-of-the-art in serious game technology is identical to that of the state-of-the-art in entertainment games technology. As a result the field of serious heritage games concerns itself with recent advances in computer games, real-time computer graphics, virtual and augmented reality and artificial intelligence. On the other hand, the main strengths of serious gaming applications may be generalised as being in the areas of communication, visual expression of information, collaboration mechanisms, interactivity and entertainment. In this report, we will focus on the state-of-the-art with respect to the theories, methods and technologies used in serious heritage games. We provide an overview of existing literature of relevance to the domain, discuss the strengths and weaknesses of the described methods and point out unsolved problems and challenges. In addition, several case studies illustrating the application of methods and technologies used in cultural heritage are presented

UAV Simulation Environment for Autonomous Flight Control Algorithms

This thesis presents the development of a UAV simulation environment for the design, analysis, and comparison of autonomous flight control laws. The simulation environment was developed in MATLAB/Simulink, with custom map generation software and FlightGear 3-D visualization. Graphical user interface of the simulation environment is user-friendly and all available options are discussed in detail. Aircraft dynamic models are presented, with emphasis on newly designed UAV models. Five different aircraft models are available, with several path planning and trajectory tracking algorithms implemented. Emphasis is given to simulation of failures and other abnormal conditions, so that appropriate tools for failure detection, evaluation, and accommodation can be designed. The development of new path planning methodologies, such as optimized point of interest or automatic landing algorithms, is introduced. New developments in trajectory tracking algorithms, including adaptive controllers are discussed. An example simulation study is presented to investigate obstacle avoidance path planning algorithms, as well as the performance of trajectory tracking algorithms under both nominal and failure conditions. The results of this study are discussed with respect to optimum algorithm choice, as well as the user-friendliness of the UAV simulation environment as a whole. Finally, possible strategies for future improvements and expansion of the UAV simulation environment and its components are introduced

Cognitive Task Planning for Smart Industrial Robots

This research work presents a novel Cognitive Task Planning framework for Smart Industrial Robots. The framework makes an industrial mobile manipulator robot Cognitive by applying Semantic Web Technologies. It also introduces a novel Navigation Among Movable Obstacles algorithm for robots navigating and manipulating inside a firm. The objective of Industrie 4.0 is the creation of Smart Factories: modular firms provided with cyber-physical systems able to strong customize products under the condition of highly flexible mass-production. Such systems should real-time communicate and cooperate with each other and with humans via the Internet of Things. They should intelligently adapt to the changing surroundings and autonomously navigate inside a firm while moving obstacles that occlude free paths, even if seen for the first time. At the end, in order to accomplish all these tasks while being efficient, they should learn from their actions and from that of other agents. Most of existing industrial mobile robots navigate along pre-generated trajectories. They follow ectrified wires embedded in the ground or lines painted on th efloor. When there is no expectation of environment changes and cycle times are critical, this planning is functional. When workspaces and tasks change frequently, it is better to plan dynamically: robots should autonomously navigate without relying on modifications of their environments. Consider the human behavior: humans reason about the environment and consider the possibility of moving obstacles if a certain goal cannot be reached or if moving objects may significantly shorten the path to it. This problem is named Navigation Among Movable Obstacles and is mostly known in rescue robotics. This work transposes the problem on an industrial scenario and tries to deal with its two challenges: the high dimensionality of the state space and the treatment of uncertainty. The proposed NAMO algorithm aims to focus exploration on less explored areas. For this reason it extends the Kinodynamic Motion Planning by Interior-Exterior Cell Exploration algorithm. The extension does not impose obstacles avoidance: it assigns an importance to each cell by combining the efforts necessary to reach it and that needed to free it from obstacles. The obtained algorithm is scalable because of its independence from the size of the map and from the number, shape, and pose of obstacles. It does not impose restrictions on actions to be performed: the robot can both push and grasp every object. Currently, the algorithm assumes full world knowledge but the environment is reconfigurable and the algorithm can be easily extended in order to solve NAMO problems in unknown environments. The algorithm handles sensor feedbacks and corrects uncertainties. Usually Robotics separates Motion Planning and Manipulation problems. NAMO forces their combined processing by introducing the need of manipulating multiple objects, often unknown, while navigating. Adopting standard precomputed grasps is not sufficient to deal with the big amount of existing different objects. A Semantic Knowledge Framework is proposed in support of the proposed algorithm by giving robots the ability to learn to manipulate objects and disseminate the information gained during the fulfillment of tasks. The Framework is composed by an Ontology and an Engine. The Ontology extends the IEEE Standard Ontologies for Robotics and Automation and contains descriptions of learned manipulation tasks and detected objects. It is accessible from any robot connected to the Cloud. It can be considered a data store for the efficient and reliable execution of repetitive tasks; and a Web-based repository for the exchange of information between robots and for the speed up of the learning phase. No other manipulation ontology exists respecting the IEEE Standard and, regardless the standard, the proposed ontology differs from the existing ones because of the type of features saved and the efficient way in which they can be accessed: through a super fast Cascade Hashing algorithm. The Engine lets compute and store the manipulation actions when not present in the Ontology. It is based on Reinforcement Learning techniques that avoid massive trainings on large-scale databases and favors human-robot interactions. The overall system is flexible and easily adaptable to different robots operating in different industrial environments. It is characterized by a modular structure where each software block is completely reusable. Every block is based on the open-source Robot Operating System. Not all industrial robot controllers are designed to be ROS-compliant. This thesis presents the method adopted during this research in order to Open Industrial Robot Controllers and create a ROS-Industrial interface for them

Efeitos das intervenções de autogestão em pessoas com doença pulmonar intersticial: revisão sistemática e meta-análise

Background: Self-management interventions (SMIs) aim to empower people with chronic diseases to manage their health more effectively. In people with chronic respiratory diseases, such as asthma, SMIs significantly improve health-related quality of life (HRQoL). However, their effectiveness has not yet been systematized in people with interstitial lung disease (ILD), which limits their implementation in healthcare. Objectives: To review and summarize the effects of SMIs on HRQoL (primary outcome), functional capacity and performance, psychological and social factors, symptoms, exacerbations, healthcare utilization, and survival, in people with ILD. Methods: The protocol of this systematic review has been registered (PROSPERO ID: CRD42022329199). A search was performed for randomized controlled studies in 6 databases, on May 31, 2022, with monthly updates until February 2023. Studies implementing SMIs in people with any type of ILD were included. Two independent reviewers implemented the Cochrane tool for risk of bias assessment (RoB2) and the grading of recommendations, assessment, development, and evaluations (GRADE) system. Between groups differences, effect direction plots, and meta-analysis were used to summarize the results. Results: Four studies that examined 217 participants (81% men, 71 years old, 91% idiopathic pulmonary fibrosis) were included. There was great heterogeneity in the duration, content, and structure of SMIs, and little detail in the reporting of control interventions. There were no statistically significant between-groups differences in HRQoL (standardized mean difference: 0.08; 95% confidence interval: -0.21 to 0.37; p-value: 0.58) nor in the secondary measures. The quality of evidence ranged from low to very low. Conclusions: There is low to very low evidence that SMIs do not significantly change HRQoL, functional performance, psychological and social factors, symptoms, and healthcare utilization, in people with ILD. No evidence for the effects of SMIs on functional capacity, exacerbations, and survival was found. It is necessary to find a universal and consensual definition of SMIs to implement comparable interventions and provide more reliable results.Introdução: As intervenções de autogestão (IA) visam capacitar as pessoas com doença crónica para realizarem uma gestão mais eficaz da sua saúde. Em pessoas com doenças respiratórias crónicas, como por exemplo a asma, as IA resultam em aumentos significativos da qualidade de vida relacionada com a saúde (QVRS). Contudo, a sua eficácia ainda não foi sistematizada em pessoas com doença pulmonar intersticial (DPI), o que limita a sua implementação nos cuidados de saúde. Objetivos: Rever e sumariar os efeitos das IA na QVRS (medida principal), capacidade e performance funcional, fatores psicológicos e sociais, sintomas, exacerbações, utilização dos serviços de saúde, e sobrevida, em pessoas com DPI. Métodos: O protocolo desta revisão sistemática foi registado (PROSPERO ID: CRD42022329199). Realizou-se uma pesquisa por estudos randomizados e controlados em 6 bases de dados, a 31 de maio de 2022 com atualizações mensais até fevereiro de 2023. Foram incluídos estudos que implementaram IA em pessoas com qualquer tipo de DPI. Dois revisores independentes implementaram a avaliação do risco de viés da Cochrane (RoB2) e o sistema de classificação de recomendações, avaliação, desenvolvimento e apreciação (GRADE). As diferenças entre grupos, tabelas de direção do efeito e meta-analises foram utilizadas para sintetizar os resultados. Resultados: Quatro estudos que examinaram 217 participantes (81% homens, 71 anos, 91% fibrose pulmonar idiopática) foram incluídos. Verificou-se grande heterogeneidade na duração, conteúdo e estrutura das IA e pouco detalhe no reporte das intervenções de controlo. Não se verificaram diferenças estatisticamente significativas entre grupos na QVRS (diferença média padronizada: 0.08; 95% intervalo de confiança: -0.21 a 0.37; p-value: 0.58), nem nas medidas secundárias. A qualidade da evidência variou entre baixa e muito baixa. Conclusões: Existe evidência baixa a muito baixa de que as IA não alterem significativamente a QVRS, performance funcional, fatores psicológicos e sociais, sintomas, e a utilização dos serviços de saúde em pessoas com DPI. Não foi encontrada evidência para os efeitos da IA na capacidade funcional, exacerbações e sobrevida. É necessário encontrar uma definição universal e consensual de IA de forma a implementar intervenções comparáveis e fornecer resultados mais confiáveis.Mestrado em Fisioterapi

Schematic Structure of National Data Harmonization System for Identity Management

Imagine a web-application in which a user can query varieties of information about an individual (like name, age, state of origin, driver’s license number, national identification number, etc.). This information would be stored on different databases, each having its own schema. Often times, these resources are replicated in different locations and on different platforms. Hence, the need for data harmonization or integration. Data harmonization addresses this issue by considering these external resources as materialized views over a virtual mediated schema resulting in “virtual data integration”. When mediated schema is queried, the solution transforms the result into appropriate queries over the various and existing data sources. This paper focuses on data harmonization that cuts across different governmental database and incorporating them all into a centralized view and this is possible as a result of development and implementation of a webbased databank application

Re-distributed Manufacturing (RdM) Studio: Simulation Model Development

[EN] Consumer Goods Industry has gone through significant changes during the last years. A challenging economic climate, advances in technology and shifts in the consumer¿s attitude have led manufacturers to transform their operating models. Re-Distributed Manufacturing (RdM) aims to address these changes moving towards smaller-scale local manufacture to create a more resilient and connected system, providing not only an agile, user-driven approach that will allow for personalisation and customisation for Product-Service Systems (PSS); but also sustainability through the circular economy. This research aims to develop a simulation environment based on a current RdM business model, also predicting a future RdM business model based on data-driven decisions. Thus, the model has been employed to compare existing and future RdM scenarios to quantify and spot potential benefits of future RdM models. To achieve this, a System Dynamics Simulation has been built. For this study, changing input parameters regarding recyclability, transportation, the level of automation and level of servitization has been the way of representing the future that RdM will bring to this particular case; showing their impact on operating costs and service efficiency. The SD business simulation has been validated by experts and is a good example of how data-driven experimentation can predict the future of RdM, with the parameters and variables selected being critical for the model. The simulation model produced by this research showed promising results: operating costs reduced by 40%, PSS revenues in 6 months and immediate response of the system to customer demand.Rivas Pizarroso, JL. (2016). Re-distributed Manufacturing (RdM) Studio: Simulation Model Development. Universitat Politècnica de València. http://hdl.handle.net/10251/144650TFG