949 resultados para Scientific apparatus and instruments


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Objectives: To discuss how current research in the area of smart homes and ambient assisted living will be influenced by the use of big data. Methods: A scoping review of literature published in scientific journals and conference proceedings was performed, focusing on smart homes, ambient assisted living and big data over the years 2011-2014. Results: The health and social care market has lagged behind other markets when it comes to the introduction of innovative IT solutions and the market faces a number of challenges as the use of big data will increase. First, there is a need for a sustainable and trustful information chain where the needed information can be transferred from all producers to all consumers in a structured way. Second, there is a need for big data strategies and policies to manage the new situation where information is handled and transferred independently of the place of the expertise. Finally, there is a possibility to develop new and innovative business models for a market that supports cloud computing, social media, crowdsourcing etc. Conclusions: The interdisciplinary area of big data, smart homes and ambient assisted living is no longer only of interest for IT developers, it is also of interest for decision makers as customers make more informed choices among today's services. In the future it will be of importance to make information usable for managers and improve decision making, tailor smart home services based on big data, develop new business models, increase competition and identify policies to ensure privacy, security and liability.

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Students may need explicit training in informal statistical reasoning in order to design experiments or use formal statistical tests effectively. By using scientific scandals and media misinterpretation, we can explore the need for good experimental design in an informal way. This article describes the use of a paper that reviews the measles mumps rubella vaccine and autism controversy in the UK to illustrate a number of threshold concepts underlying good study design and interpretation of scientific evidence. These include the necessity of sufficient sample size, representative and random sampling, appropriate controls and inferring causation.

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Rapport de stage présenté à la Faculté des Arts et Sciences en vue de l’obtention du grade de Maître des Sciences (M. Sc.) en Criminologie, Option Stage en Intervention

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On November 19, 2012, Iowa Gov. Terry Branstad, Iowa Secretary of Agriculture Bill Northey, Director Chuck Gipp from the Iowa Department of Natural Resources and Dr. John Lawrence of Iowa State University announced the release of the Iowa Nutrient Reduction Strategy for public comment. A two-month public comment period and several informational meetings allowed the public to provide feedback on the draft strategy. Updates and improvements were made to the draft based on the public comments. The final version of the strategy was released May 29, 2013. The Iowa Nutrient Reduction Strategy is a science and technology-based approach to assess and reduce nutrients delivered to Iowa waterways and the Gulf of Mexico. The strategy outlines voluntary efforts to reduce nutrients in surface water from both point sources, such as wastewater treatment plants and industrial facilities, and nonpoint sources, including farm fields and urban areas, in a scientific, reasonable and cost effective manner. The development of the strategy reflects more than two years of work led by the Iowa Department of Agriculture and Land Stewardship, Iowa Department of Natural Resources and Iowa State University. The scientific assessment to evaluate and model the effects of practices was developed through the efforts of 23 individuals representing five agencies or organizations, including scientists from ISU, IDALS, DNR, USDA Agricultural Research Service and USDA Natural Resources Conservation Service. The strategy was developed in response to the 2008 Gulf Hypoxia Action Plan that calls for the 12 states along the Mississippi River to develop strategies to reduce nutrient loading to the Gulf of Mexico. The Iowa strategy follows the recommended framework provided by EPA in 2011 and is only the second state to complete a statewide nutrient reduction strategy. This strategy is the beginning. Operational plans are being developed and work is underway. This is a dynamic document that will evolve over time, and is a key step towards improving Iowa’s water quality. The impetus for this report comes from the Water Resources Coordination Council (WRCC) which states in its 2014‐15 Annual Report “Efforts are underway to improve understanding of the multiple nutrient monitoring efforts that may be available and can be compared to the nutrient WQ monitoring framework to identify opportunities and potential data gaps to better coordinate and prioritize future nutrient monitoring efforts.” This report is the culmination of those efforts.

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On November 19, 2012, Iowa Gov. Terry Branstad, Iowa Secretary of Agriculture Bill Northey, Director Chuck Gipp from the Iowa Department of Natural Resources and Dr. John Lawrence of Iowa State University announced the release of the Iowa Nutrient Reduction Strategy for public comment. A two-month public comment period and several informational meetings allowed the public to provide feedback on the draft strategy. Updates and improvements were made to the draft based on the public comments. The final version of the strategy was released May 29, 2013. The Iowa Nutrient Reduction Strategy is a science and technology-based approach to assess and reduce nutrients delivered to Iowa waterways and the Gulf of Mexico. The strategy outlines voluntary efforts to reduce nutrients in surface water from both point sources, such as wastewater treatment plants and industrial facilities, and nonpoint sources, including farm fields and urban areas, in a scientific, reasonable and cost effective manner. The development of the strategy reflects more than two years of work led by the Iowa Department of Agriculture and Land Stewardship, Iowa Department of Natural Resources and Iowa State University. The scientific assessment to evaluate and model the effects of practices was developed through the efforts of 23 individuals representing five agencies or organizations, including scientists from ISU, IDALS, DNR, USDA Agricultural Research Service and USDA Natural Resources Conservation Service. The strategy was developed in response to the 2008 Gulf Hypoxia Action Plan that calls for the 12 states along the Mississippi River to develop strategies to reduce nutrient loading to the Gulf of Mexico. The Iowa strategy follows the recommended framework provided by EPA in 2011 and is only the second state to complete a statewide nutrient reduction strategy. This strategy is the beginning. Operational plans are being developed and work is underway. This is a dynamic document that will evolve over time, and is a key step towards improving Iowa’s water quality. The impetus for this report comes from the Water Resources Coordination Council (WRCC) which states in its 2014‐15 Annual Report “Efforts are underway to improve understanding of the multiple nutrient monitoring efforts that may be available and can be compared to the nutrient WQ monitoring framework to identify opportunities and potential data gaps to better coordinate and prioritize future nutrient monitoring efforts.” This report is the culmination of those efforts.

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On November 19, 2012, Iowa Gov. Terry Branstad, Iowa Secretary of Agriculture Bill Northey, Director Chuck Gipp from the Iowa Department of Natural Resources and Dr. John Lawrence of Iowa State University announced the release of the Iowa Nutrient Reduction Strategy for public comment. A two-month public comment period and several informational meetings allowed the public to provide feedback on the draft strategy. Updates and improvements were made to the draft based on the public comments. The final version of the strategy was released May 29, 2013. The Iowa Nutrient Reduction Strategy is a science and technology-based approach to assess and reduce nutrients delivered to Iowa waterways and the Gulf of Mexico. The strategy outlines voluntary efforts to reduce nutrients in surface water from both point sources, such as wastewater treatment plants and industrial facilities, and nonpoint sources, including farm fields and urban areas, in a scientific, reasonable and cost effective manner. The development of the strategy reflects more than two years of work led by the Iowa Department of Agriculture and Land Stewardship, Iowa Department of Natural Resources and Iowa State University. The scientific assessment to evaluate and model the effects of practices was developed through the efforts of 23 individuals representing five agencies or organizations, including scientists from ISU, IDALS, DNR, USDA Agricultural Research Service and USDA Natural Resources Conservation Service. The strategy was developed in response to the 2008 Gulf Hypoxia Action Plan that calls for the 12 states along the Mississippi River to develop strategies to reduce nutrient loading to the Gulf of Mexico. The Iowa strategy follows the recommended framework provided by EPA in 2011 and is only the second state to complete a statewide nutrient reduction strategy. This strategy is the beginning. Operational plans are being developed and work is underway. This is a dynamic document that will evolve over time, and is a key step towards improving Iowa’s water quality. The impetus for this report comes from the Water Resources Coordination Council (WRCC) which states in its 2014‐15 Annual Report “Efforts are underway to improve understanding of the multiple nutrient monitoring efforts that may be available and can be compared to the nutrient WQ monitoring framework to identify opportunities and potential data gaps to better coordinate and prioritize future nutrient monitoring efforts.” This report is the culmination of those efforts.

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Este trabalho é a base científica, e também podemos dizer, ideológica, de um relatório solicitado pelo Parlamento Europeu à Comissão dos Direitos das Mulheres e da Igualdade dos Géneros que pretende assegurar uma educação democrática e a educação para a igualdade dos géneros. Em Setembro de 2015 este relatório foi aprovado como resolução por uma larga maioria parlamentar, apoiando a ideia da educação e do currículo como instrumentos de poder. Acredito que a educação tem um papel fundamental na mudança e que é responsável pelo desenvolvimento da personalidade e pela criação de ideias que determinam atitudes, acções e perspectivas sobre o mundo, guiando-nos na vida pessoal e influenciando as escolhas profissionais. Este trabalho foi o primeiro momento de reflexão sobre esta questão e mostra o importante papel da investigação em educação e do currículo no âmbito das políticas europeias.

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This is a CoLab Workshop organized as an initiative of the UT Austin | Portugal Program to reinforce the Portuguese competences in Nonlinear Mechanics and in complex problems arising from applications to the mathematical modeling and simulations in the Life Sciences. The Workshop provides a place to exchange recent developments, discoveries and progresses in this challenging research field. The main goal is to bring together doctoral candidates, postdoctoral scientists and graduates interested in the field, giving them the opportunity to make scientific interactions and new connections with established experts in the interdisciplinary topics covered by the event. Another important goal of the Workshop is to promote collaboration between members of the different areas of the UT Austin | Portugal community.

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This thesis argues the attitude control problem of nanosatellites, which has been a challenging issue over the years for the scientific community and still constitutes an active area of research. The interest is increasing as more than 70% of future satellite launches are nanosatellites. Therefore, new challenges appear with the miniaturisation of the subsystems and improvements must be reached. In this framework, the aim of this thesis is to develop novel control approaches for three-axis stabilisation of nanosatellites equipped with magnetorquers and reaction wheels, to improve the performance of the existent control strategies and demonstrate the stability of the system. In particular, this thesis is focused on the development of non-linear control techniques to stabilise full-actuated nanosatellites, and in the case of underactuation, in which the number of control variables is less than the degrees of freedom of the system. The main contributions are, for the first control strategy proposed, to demonstrate global asymptotic stability derived from control laws that stabilise the system in a target frame, a fixed direction of the orbit frame. Simulation results show good performance, also in presence of disturbances, and a theoretical selection of the magnetic control gain is given. The second control approach presents instead, a novel stable control methodology for three-axis stabilisation in underactuated conditions. The control scheme consists of the dynamical implementation of an attitude manoeuvre planning by means of a switching control logic. A detailed numerical analysis of the control law gains and the effect on the convergence time, total integrated and maximum torque is presented demonstrating the good performance and robustness also in the presence of disturbances.

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The ever-growing interest in scientific techniques, able to characterise the materials and rediscover the steps behind the execution of a painting, makes them widely accepted in its investigation. This research discusses issues emerging from attribution and authentication studies and proposes best practise for the characterisation of materials and techniques, favouring the contextualisation of the results in an integrated approach; the work aims to systematically classify paintings in categories that aid the examination of objects. A first grouping of paintings is based on the information initially available on them, identifying four categories. A focus of this study is the examination of case studies, spanning from the 16th to the 20th century, to evaluate and validate different protocols associated to each category, to show problems arising from paintings and explain advantages and limits of the approach. The research methodology incorporates a combined set of scientific techniques (non-invasive, such as technical imaging and XRF, micro-invasive, such as optical microscopy, SEM-EDS, FTIR, Raman microscopy and in one case radiocarbon dating) to answer the questions and, if necessary for the classification, exhaustively characterise the materials of the paintings, as the creation and contribution of shared technical databases related to various artists and their evolution over time is an objective tool that benefits this kind of study. The reliability of a close collaboration among different professionals is an essential aspect of this research to comprehensively study a painting, as the integration of stylistic, documentary and provenance studies corroborates the scientific findings and helps in the successful contextualisation of the results and the reconstruction of the history of the object.

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La tesi consiste in un commento scientifico ai versi 703-1089 del VI libro di Lucrezio, dove sono discussi vari mirabilia della natura (le piene estive del Nilo, i luoghi Averni, l’escursione termica dei pozzi, alcune fonti prodigiose e il magnete). Nell’introduzione, si traccia una rapida panoramica del VI libro per contestualizzare al suo interno il passo oggetto del commento; ci si concentra, poi, sul significato della meraviglia e del meraviglioso nell’opera, anche a confronto con la tradizione paradossografica. Seguono il testo, corredato di un sintetico apparato critico, e la traduzione. Nel commento, che intende valorizzare il côté letterario, filosofico e scientifico dell’opera, sono affrontati i più rilevanti problemi testuali ed esegetici, oltre a questioni di ordine grammaticale, linguistico, stilistico e metrico. Chiudono il lavoro due appendici di natura critico-testuale.

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Machine (and deep) learning technologies are more and more present in several fields. It is undeniable that many aspects of our society are empowered by such technologies: web searches, content filtering on social networks, recommendations on e-commerce websites, mobile applications, etc., in addition to academic research. Moreover, mobile devices and internet sites, e.g., social networks, support the collection and sharing of information in real time. The pervasive deployment of the aforementioned technological instruments, both hardware and software, has led to the production of huge amounts of data. Such data has become more and more unmanageable, posing challenges to conventional computing platforms, and paving the way to the development and widespread use of the machine and deep learning. Nevertheless, machine learning is not only a technology. Given a task, machine learning is a way of proceeding (a way of thinking), and as such can be approached from different perspectives (points of view). This, in particular, will be the focus of this research. The entire work concentrates on machine learning, starting from different sources of data, e.g., signals and images, applied to different domains, e.g., Sport Science and Social History, and analyzed from different perspectives: from a non-data scientist point of view through tools and platforms; setting a problem stage from scratch; implementing an effective application for classification tasks; improving user interface experience through Data Visualization and eXtended Reality. In essence, not only in a quantitative task, not only in a scientific environment, and not only from a data-scientist perspective, machine (and deep) learning can do the difference.

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The discovery of new materials and their functions has always been a fundamental component of technological progress. Nowadays, the quest for new materials is stronger than ever: sustainability, medicine, robotics and electronics are all key assets which depend on the ability to create specifically tailored materials. However, designing materials with desired properties is a difficult task, and the complexity of the discipline makes it difficult to identify general criteria. While scientists developed a set of best practices (often based on experience and expertise), this is still a trial-and-error process. This becomes even more complex when dealing with advanced functional materials. Their properties depend on structural and morphological features, which in turn depend on fabrication procedures and environment, and subtle alterations leads to dramatically different results. Because of this, materials modeling and design is one of the most prolific research fields. Many techniques and instruments are continuously developed to enable new possibilities, both in the experimental and computational realms. Scientists strive to enforce cutting-edge technologies in order to make progress. However, the field is strongly affected by unorganized file management, proliferation of custom data formats and storage procedures, both in experimental and computational research. Results are difficult to find, interpret and re-use, and a huge amount of time is spent interpreting and re-organizing data. This also strongly limit the application of data-driven and machine learning techniques. This work introduces possible solutions to the problems described above. Specifically, it talks about developing features for specific classes of advanced materials and use them to train machine learning models and accelerate computational predictions for molecular compounds; developing method for organizing non homogeneous materials data; automate the process of using devices simulations to train machine learning models; dealing with scattered experimental data and use them to discover new patterns.

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In this thesis, we investigate the role of applied physics in epidemiological surveillance through the application of mathematical models, network science and machine learning. The spread of a communicable disease depends on many biological, social, and health factors. The large masses of data available make it possible, on the one hand, to monitor the evolution and spread of pathogenic organisms; on the other hand, to study the behavior of people, their opinions and habits. Presented here are three lines of research in which an attempt was made to solve real epidemiological problems through data analysis and the use of statistical and mathematical models. In Chapter 1, we applied language-inspired Deep Learning models to transform influenza protein sequences into vectors encoding their information content. We then attempted to reconstruct the antigenic properties of different viral strains using regression models and to identify the mutations responsible for vaccine escape. In Chapter 2, we constructed a compartmental model to describe the spread of a bacterium within a hospital ward. The model was informed and validated on time series of clinical measurements, and a sensitivity analysis was used to assess the impact of different control measures. Finally (Chapter 3) we reconstructed the network of retweets among COVID-19 themed Twitter users in the early months of the SARS-CoV-2 pandemic. By means of community detection algorithms and centrality measures, we characterized users’ attention shifts in the network, showing that scientific communities, initially the most retweeted, lost influence over time to national political communities. In the Conclusion, we highlighted the importance of the work done in light of the main contemporary challenges for epidemiological surveillance. In particular, we present reflections on the importance of nowcasting and forecasting, the relationship between data and scientific research, and the need to unite the different scales of epidemiological surveillance.

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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.