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Publisher Copyright: © 2022. The Author(s). BACKGROUND: Tuberculosis (TB) diagnosis and treatment delays increase the period of infectiousness, making TB control difficult and increasing the fatality rates. This study aimed to determine the evolution of health care service delay (time between the patient's first contact with the health service and the diagnosis/start of treatment) and patient delay (time between onset symptoms date and the date of first contact with health services) for Pulmonary Tuberculosis (PTB) in Portugal between 2008 and 2017 across different regions, age groups and gender. METHODS: An exploratory analysis was performed, trends of both delays were studied, and 36 months forecasts were generated. We used the permutation test to test differences between groups and the Seasonal and Trend decomposition using Loess (STL) method and Autoregressive Integrated Moving Average (ARIMA) models for forecasting for both Health and Patient delays. We used data from notified PTB cases in mainland Portugal between 2008 and 2017, provided by the national surveillance system. RESULTS: Health delays remained relatively constant while patient delays increased. Females had significantly higher health delays in some regions. Individuals older than 64 had higher health delays than younger individuals, while patient delay for working-age individuals between 15 and 64 years old, presents higher patient delay. CONCLUSIONS: Forecasts presage that the upward trend of the delays is unlikely to fall in the coming years. It is important to understand the evolution of the delays and predict how these will evolve. Our understanding of the delays behaviours will contribute to better health policies and resources allocation. publishersversion published

Submitted by Maria da Luz Antunes (mluz.antunes@estesl.ipl.pt) on 2021-03-26T16:06:49Z No. of bitstreams: 1 Structured additive regression modeling of pulmonary tuberculosis infection.pdf: 806280 bytes, checksum: eb12663db17b1f4ea5b431381453408d (MD5) Made available in DSpace on 2021-03-26T16:06:50Z (GMT). No. of bitstreams: 1 Structured additive regression modeling of pulmonary tuberculosis infection.pdf: 806280 bytes, checksum: eb12663db17b1f4ea5b431381453408d (MD5) Previous issue date: 2020-02 info:eu-repo/semantics/publishedVersion

Submitted by azevedo@ufp.pt (azevedo@ufp.pt) on 2019-02-27T11:31:26Z No. of bitstreams: 1 PPG_28167.pdf: 47304833 bytes, checksum: 7a2b1ec774793990eb28bdd17968985e (MD5) Approved for entry into archive by halves@ufp.pt (halves@ufp.pt) on 2019-02-27T11:43:56Z (GMT) No. of bitstreams: 1 PPG_28167.pdf: 47304833 bytes, checksum: 7a2b1ec774793990eb28bdd17968985e (MD5) Made available in DSpace on 2019-02-27T11:43:56Z (GMT). No. of bitstreams: 1 PPG_28167.pdf: 47304833 bytes, checksum: 7a2b1ec774793990eb28bdd17968985e (MD5) Previous issue date: 2018-09-19

Data insufficiency hampered the academic research of discrimination based on sexual orientation. This is a particular concern in Portugal, a country that in spite of the strong legal recognition of homosexuals still scores low in their acceptance. Resorting to a selfdesigned web-survey, this study provides for the first time academic investigation of homosexuals in Portugal and contributes with an evaluation of wage discrimination in the primary employment. The empirical results point in the direction of absence of discrimination, but there is imprecise and small evidence that some homosexual individuals may be subject to discrimination.

Tese de mestrado, Medicina do Adolescente, Faculdade de Medicina, Universidade de Lisboa, 2015 Submitted by Lucília Mateus (luciliamateus@fm.ul.pt) on 2016-04-01T09:58:01Z No. of bitstreams: 1 10902_Tese.pdf.pdf: 952470 bytes, checksum: 4796a981b0d65a8c6d0644718a0a3e47 (MD5) Made available in DSpace on 2016-04-01T11:09:44Z (GMT). No. of bitstreams: 1 10902_Tese.pdf.pdf: 952470 bytes, checksum: 4796a981b0d65a8c6d0644718a0a3e47 (MD5) Previous issue date: 2015

Since the mid-80s Tuberculosis declining trend became softer and even reversed in some countries. HIV/AIDS frequently appears as the main cause for the resurgence of Tuberculosis. This work aims at identifying critical areas for the joint occurrence of these conditions in Portugal, and at confirming the belief that HIV is not a major explanation for the slow Tuberculosis incidence decline. Based on correlation analyses and space-time scan statistics, a weak statistical correlation between HIV and TB incidence rates were observed (0.279; p

Parameter estimation and bootstrap methods in stochastic differential equation models for the growth of individual animals in randomly varyoung environments with application to the growth of mertolengo cattle

Refereed scientific paper on stochastic differential equation models of individual animal growth (from birth to maturity) in random environments with estimation methods for several trajectories (several animals). The paper is in press in the Bulletin of ISI containing the Proceedings of the 56th Session of the ISI (2007). An electronic version is available.

Tese de mestrado em Estudos Curatoriais apresentada à Universidade de Lisboa através da Faculdade de Belas Artes, 2008 Submitted by Licínia Santos (biblioteca@fba.ul.pt) on 2013-01-21T11:38:57Z No. of bitstreams: 8 ULFBA_tes 280_1_CAPA.jpg: 57581 bytes, checksum: e32947f81da33020ce2c33a467edca99 (MD5) ULFBA_tes 280_1.pdf: 762700 bytes, checksum: 1435fad2d0c3bdc4fafb31450f066c51 (MD5) tes 280_2_000-104.pdf: 450953 bytes, checksum: 6aa878f952db42cc9719fd7c023c88be (MD5) tes 280_2_105 a 106.pdf: 54120 bytes, checksum: 3cd84a17a1b246e938180468cef223a7 (MD5) tes 280_2_107-144.pdf: 173501 bytes, checksum: 05ad07140d0519ff62bad800dee8cb83 (MD5) tes 280_2_145 a 195.pdf: 18400507 bytes, checksum: 197e02b01df158c2acf6b8234e742b77 (MD5) tes 280_2_196 a 197.pdf: 9557 bytes, checksum: 242c7566281ec7d1474eabeb7f8ff263 (MD5) tes 280_2_198 a 204.pdf: 1243088 bytes, checksum: 558acdec84f8827038084cb880048064 (MD5) Made available in DSpace on 2013-01-21T11:39:08Z (GMT). No. of bitstreams: 8 ULFBA_tes 280_1_CAPA.jpg: 57581 bytes, checksum: e32947f81da33020ce2c33a467edca99 (MD5) ULFBA_tes 280_1.pdf: 762700 bytes, checksum: 1435fad2d0c3bdc4fafb31450f066c51 (MD5) tes 280_2_000-104.pdf: 450953 bytes, checksum: 6aa878f952db42cc9719fd7c023c88be (MD5) tes 280_2_105 a 106.pdf: 54120 bytes, checksum: 3cd84a17a1b246e938180468cef223a7 (MD5) tes 280_2_107-144.pdf: 173501 bytes, checksum: 05ad07140d0519ff62bad800dee8cb83 (MD5) tes 280_2_145 a 195.pdf: 18400507 bytes, checksum: 197e02b01df158c2acf6b8234e742b77 (MD5) tes 280_2_196 a 197.pdf: 9557 bytes, checksum: 242c7566281ec7d1474eabeb7f8ff263 (MD5) tes 280_2_198 a 204.pdf: 1243088 bytes, checksum: 558acdec84f8827038084cb880048064 (MD5) Previous issue date: 2008

Refereed scientific paper on stochastic differential equation models of individual growth (from birth to maturity) in a random environment, with parameter estimation, prediction and application to bovine data.

Individual animal growth in a randomly varying environment is modeled using stochastic differential equation models. These models are generalizations of the classical deterministic growth models used in regression methods, but incorporate a random dynamical term describing the effects of environmental and other random fluctuations on the growth process. We describe parameter estimation and prediction methods, illustrating with data on cow growth of the Mertolengo breed raised in Alentejo (Portugal) under natural conditions; see models, their properties and statistical techniques in the references below. We first show that these models outperform the traditional regression models in predictive power for they take into account the dynamical nature of the growth process and its interaction with environmental fluctuations. We then apply the models to profit optimization in livestock production, taking into account production costs and sales revenues. Assuming the animal is to be sold when it reaches some prescribed age, we determine the optimal age at which an animal should be sold in order to maximize profit. Another possibility is to sell the animal when it reaches a prescribed size. The first passage time distribution through a prescribed size is studied and used to determine the optimal size at which the animal should be sold. We then determine which policy (selling at a fixed age or selling at a fixed size) is preferable in terms of profit and compare results with the deterministic case.

A água é um bem essencial e escasso nos dias de hoje, pelo que é necessário conservá-lo e distribuí-lo de maneira eficiente e sustentável. Com a ajuda dos novos medidores digitais é possível medir os consumos com uma cadência horária, e através de técnicas de Machine Learning, produzir informações sobre padrões de consumo, comportamento dos consumidores, deteção de eventos nas redes de distribuição de água e feedback aos clientes. A deteção de anomalias, como fugas de água domésticas e na rede de saneamento, avaria dos medidores e fraude, são algumas das causas que provocam desperdícios de água e que muitas autarquias não têm como detetar de forma eficaz. A presente dissertação tem como objetivo desenvolver uma metodologia, baseada em séries temporais, para a previsão de consumos de água e a deteção de anomalias, recorrendo a dados dos consumidores domésticos, de uma zona situada na Quinta do Lago, Algarve. Para isso, são utilizados métodos de Clustering para agrupar os consumidores com padrões de consumo idênticos, e modelos de Machine Learning, como o ARIMA, Neural Networks e Random Forest, utilizados para prever os consumos de água. São apresentados os resultados de vários modelos para previsão de consumos e, por fim, são desenvolvidos dashboards que auxiliam na deteção de possíveis anomalias. Water is an essential and limited resource these days, so it is necessary to conserve and distribute it efficiently and sustainably. With the help of the new digital meters, it is possible to measure consumption on an hourly basis, and through Machine Learning techniques, produce information on consumption patterns, consumer behavior, detection of events in water distribution networks and feedback to customers. The detection of anomalies, such as domestic water leaks and in the sanitation network, meter failure and fraud, are some of the causes that cause water waste and that many municipalities are unable to detect effectively. This dissertation aims to develop a methodology, based on time series, for forecasting water consumption and detecting anomalies, using data from domestic consumers in an area located in Quinta do Lago, Algarve. For this, Clustering methods are used to group consumers with identical consumption patterns, and Machine Learning models such as ARIMA, Neural Networks and Random Forest, used to predict water consumption. The results of several models for forecasting consumption are presented, and finally, dashboards are developed to help detect possible anomalies.

Recentes avanços em campos como deep learning e computer vision, trouxeram novas possibilidades à área do retalho. Tais avanços forneceram novas ideias e capacidades às lojas de explorarem novos tipos de informação, devido às múltiplas câmaras implementadas no estabelecimento. Nesta dissertação, é desenvolvida uma investigação que estuda possíveis comportamentos de clientes que esses estabelecimentos podem explorar a partir da análise de imagens. Neste seguimento, é necessário perceber como se pode analisar e tirar proveito das mesmas e ter a capacidade de reconhecer intervenientes no processo de compra, através da parametrização do melhor modelo, utilizando técnicas de deep learning. Com os objetivos da investigação em mente, é realizada uma extensa pesquisa através de uma Revisão Sistemática da Literatura na área de Big Data aplicada a computer vision, deep learning e os métodos de análise de sensores. Adicionalmente, é efetuada uma análise aos resultados de um questionário, aplicado a consumidores nacionais, que pretenderia criar empatia com os mesmo, de modo a tentar traduzir as suas posições em propostas de valor. Paralelamente, foram recolhidos e analisados dados de imagem provenientes de um retalhista português e utilizados os algoritmos Yolo e Hidden Markov Model, considerando a sua rapidez e características, mas também a presença em estudos modernos. Os resultados permitiram identificar pessoas com uma accuracy média de 85%. Foram ainda construídos mapas de frequências e heat maps, com o principal contributo de enaltecer padrões de consumo e afluências na loja, para aferir o impacto que este tipo de informação pode ter na experiência do consumidor. Recent advances in fields such as deep learning and computer vision have brought new possibilities in the retail area. Such advances have provided new insights and capabilities for shops to exploit new types of information due to the multiple cameras deployed in the establishment. In this dissertation, an investigation is developed that studies possible customer behaviours that these establishments can exploit from image analysis. In this follow up, it is necessary to understand how one can analyse and take advantage of them and have the ability to recognise actors in the shopping process by parameterising the best model using deep learning techniques. With the research objectives in mind, an extensive literature review is carried out in the area of Big Data applied to computer vision and deep learning, but also in sensor analysis methods. Additionally, a survey was implemented to a portuguese consumers sample that intended to create empathy with consumers in order to understand their wishes to try to translate them into value propositions. In parallel, image data from a portuguese retailer was collected and the Yolo algorithm was used together with Hidden Markov Model to analyse it, considering its speed and characteristics, but also its presence in modern studies. The results allow identifying people with an average accuracy of 85%. Frequency maps and heat maps were also generated, with the main contribution of highlighting consumption patterns and affluence in the shop, to assess the impact that this type of information can have on consumer experience.

RESUMO - O presente estudo tem como objetivo contribuir para a Saúde Pública no controlo da tuberculose pulmonar (TBP), estudando a demora desde o aparecimento dos primeiros sintomas até ao diagnóstico da doença. As consequências da demora no diagnóstico podem ser fatais para os doentes e intensificar a proliferação do bacilo, influenciando a incidência da doença. Este estudo analisou os casos notificados com TBP pelo SVIG-TB, em Portugal Continental, no período de 2000 a 2009, com demora no diagnóstico de 1 a 365 dias. Foram utilizadas técnicas de estatística clássica para caracterização da base de dados e de análise de sobrevivência para caracterizar a demora até ao diagnóstico e modelar o risco de diagnóstico. As variáveis incluídas no estudo foram: género, idade, grupo etário, distrito de residência, área crítica de incidência da tuberculose, presença ou ausência da infeção pelo VIH, caso novo e reincidência, número de tratamentos anteriores, presença ou ausência de fatores de risco (álcool, tabaco, outras drogas, reclusão e sem-abrigo) e número de fatores de risco. Verificou-se que nos 35 711 casos notificados a mediana da demora até ao diagnóstico foi de 55 dias. Todas as variáveis referidas anteriormente demostraram estar correlacionadas com a demora, exceto no que diz respeito às áreas críticas ou não críticas e aos sem-abrigo. No modelo de Cox as variáveis que se mostraram relevantes ao diagnóstico foram o género em 10,2%, grupos etários, distritos, presença ou ausência de VIH em 12%, dependência alcoólica em 6,3% e dependência de tabaco em 8,8%. Estes resultados apontam para a efetividade de medidas de controlo da tuberculose, principalmente no caso de a pessoa apresentar alguns fatores de risco. ABSTRACT - The aim of this study is to contribute to public health on pulmonary tuberculosis control, studying the delay from onset of the first symptoms and the diagnosis of pulmonary tuberculosis. The consequences of delay in diagnosis can be fatal to patients and spread the proliferation of bacillus, influencing the disease incidence. This study analyzes the reported cases by SVIG-TB in Portugal in the period between 2000 and 2009, with delay in diagnosis of 1 to 365 days. There were used classical statistical analysis techniques to database characterization and survival analysis to characterize the delay in diagnosis of pulmonary tuberculosis and to modeling diagnosis risk. The variables included in the study are: gender, age, age group, residence district, critical area of tuberculosis incidence, presence or absence of HIV infection, new case and recurrence, number of previous treatments, presence or absence of risk factors (alcohol, tobacco, other drugs, incarceration and homelessness) and number of risk factors. In 35 711 cases it was found that the median of delay in diagnosis was 55 days. All variables mentioned above have shown to be correlated with the delay, except for critical or not critical areas and in the case of the homelessness. In the Cox model, the variables that were relevant to the diagnosis were gender in 10,2%, age groups, districts, presence or absence of HIV in 12%, alcohol in 6,3% and tobacco dependence in 8,8%. These results indicate the effectiveness of some measures of TB control, especially if the person has some risk factors.