Predictors of adherence to the Mediterranean diet from the first to the second trimester of pregnancy

Background: Although changes in eating patterns may occur during gestation, predictors of these changes have not been explored. This study aimed to identify predictors of adherence to the Mediterranean diet (MD) from the first to second trimester of pregnancy. Methods: A prospective study was conducted with 102 pregnant women aged 18-40, from the city of Porto, Portugal. Socio-demographic and lifestyle characteristics were assessed through a questionnaire. Food consumption was assessed with a three-day food diary completed during the first and second trimesters. Participants were categorized according to their change in adherence to the MD into the negative change group (i.e., women who had low adherence in each trimester or had high adherence in the first trimester and then low adherence in the second) and the positive change group (i.e., women who had high adherence in both trimesters or had low adherence in the first trimester and then high adherence in the second). Conditional stepwise logistic regression models were performed to assess the potential predictors of negative MD change. Results: Among the 102 women, 39.2% had negative change from the first to the second trimester. The logistic model´s results show that being married (OR=0.26, 95%CI: 0.10, 0.76) and having a higher intake of vegetables in the first trimester (OR=0.17, 95%CI: 0.10, 0.43) were associated with lower odds of having a negative change in adherence to the MD from the first to second trimester. Conclusion: Marital status and vegetable consumption seem to be associated with a lower occurrence of negative change in adherence to the MD from early to middle pregnancy.

Non-linear time series models

The last three decades have seen quite dramatic changes the way we modeled time dependent data. Linear processes have been in the center stage in modeling time series. As far as the second order properties are concerned, the theory and the methodology are very adequate.However, there are more and more evidences that linear models are not sufficiently flexible and rich enough for modeling purposes and that failure to account for non-linearities can be very misleading and have undesired consequences.

A score test for non-nested hypotheses with applications to discrete data models

This paper suggests that a convenient score test against non-nested alternatives can be constructed from the linear combination of the likelihood functions of the competing models. It is shown that this procedure is essentially a test for the correct specification of the conditional distribution of the variable of interest.

Comparing the performance of geostatistical models with additional information from covariates for sewage plume characterization

In this work, kriging with covariates is used to model and map the spatial distribution of salinity measurements gathered by an autonomous underwater vehicle in a sea outfall monitoring campaign aiming to distinguish the effluent plume from the receiving waters and characterize its spatial variability in the vicinity of the discharge. Four different geostatistical linear models for salinity were assumed, where the distance to diffuser, the west-east positioning, and the south-north positioning were used as covariates. Sample variograms were fitted by the Mat`ern models using weighted least squares and maximum likelihood estimation methods as a way to detect eventual discrepancies. Typically, the maximum likelihood method estimated very low ranges which have limited the kriging process. So, at least for these data sets, weighted least squares showed to be the most appropriate estimation method for variogram fitting. The kriged maps show clearly the spatial variation of salinity, and it is possible to identify the effluent plume in the area studied. The results obtained show some guidelines for sewage monitoring if a geostatistical analysis of the data is in mind. It is important to treat properly the existence of anomalous values and to adopt a sampling strategy that includes transects parallel and perpendicular to the effluent dispersion.

Performance of state space and ARIMA models for consumer retail sales forecasting

Forecasting future sales is one of the most important issues that is beyond all strategic and planning decisions in effective operations of retail businesses. For profitable retail businesses, accurate demand forecasting is crucial in organizing and planning production, purchasing, transportation and labor force. Retail sales series belong to a special type of time series that typically contain trend and seasonal patterns, presenting challenges in developing effective forecasting models. This work compares the forecasting performance of state space models and ARIMA models. The forecasting performance is demonstrated through a case study of retail sales of five different categories of women footwear: Boots, Booties, Flats, Sandals and Shoes. On both methodologies the model with the minimum value of Akaike's Information Criteria for the in-sample period was selected from all admissible models for further evaluation in the out-of-sample. Both one-step and multiple-step forecasts were produced. The results show that when an automatic algorithm the overall out-of-sample forecasting performance of state space and ARIMA models evaluated via RMSE, MAE and MAPE is quite similar on both one-step and multi-step forecasts. We also conclude that state space and ARIMA produce coverage probabilities that are close to the nominal rates for both one-step and multi-step forecasts.

Modelos Teóricos de Difusão Dérmica: abordagens matemáticas e computacionais para terapias transdérmicas da Obesidade

É de senso comum que os nutrientes são fundamentais à vida e que a subnutrição leva à acumulação de gorduras que pode chegar a casos de obesidade, tendo como consequência inúmeras complicações de saúde. Diferentes estruturas neuroanatómicas do cérebro têm um papel essencial no comportamento digestivo. A ação de várias moléculas de sinalização (hormonas, neurotransmissores e neuropéptidos) resulta na regulação da ingestão de alimentos, sendo que, por exemplo, algumas hormonas podem aumentar a sensação de saciedade podendo diminuir o apetite e a ingestão calórica. A descoberta de hormonas envolvidas no balanço energético proporcionou novas oportunidades para desenvolver meios para o tratamento da obesidade. A transferência de medicação antiobesidade por via tópica ou transdérmica é um desafio pois a pele funciona como uma barreira natural e protetora. Sendo uma barreira com uma grande área de superfície e de fácil acessibilidade, a pele tem potencial interesse na libertação de fármacos específicos a cada terapia. Vários métodos têm sido estudados de modo a permitir um aumento da permeabilidade de moléculas terapêuticas para o interior da pele e através da pele. As biotecnologias transdérmicas são um campo de interesse cada vez maior, devido as aplicações dérmicas e farmacêuticas que lhes estão subjacentes. Existem vários modelos computacionais e matemáticos em uso que permite uma visão mais abrangente de puros dados experimentais e até mesmo permite a extrapolação prática de novas metodologias de difusão dérmica. Contudo, eles compreendem uma complexa variedade de teorias e suposições que atribuem a sua utilização para situações específicas. Este trabalho, primeiramente analisa, de forma extensiva, as várias metodologias teóricas para o estudo da difusão dérmica e sistematiza as suas características, realizando depois a fase prévia duma nova abordagem computacional para o estudo da difusão dérmica, que determina características microscópicas de moléculas capazes de provocar a perda de peso, tais como a Leptina e/ou os seus agonistas.

Tuple-based morphisms for interoperability establishment of financial information models

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e Computadores

ANIMAL MODELS FOR THE STUDY OF LEISHMANIASIS IMMUNOLOGY

Leishmaniasis remains a major public health problem worldwide and is classified as Category I by the TDR/WHO, mainly due to the absence of control. Many experimental models like rodents, dogs and monkeys have been developed, each with specific features, in order to characterize the immune response to Leishmania species, but none reproduces the pathology observed in human disease. Conflicting data may arise in part because different parasite strains or species are being examined, different tissue targets (mice footpad, ear, or base of tail) are being infected, and different numbers (“low” 1×102 and “high” 1×106) of metacyclic promastigotes have been inoculated. Recently, new approaches have been proposed to provide more meaningful data regarding the host response and pathogenesis that parallels human disease. The use of sand fly saliva and low numbers of parasites in experimental infections has led to mimic natural transmission and find new molecules and immune mechanisms which should be considered when designing vaccines and control strategies. Moreover, the use of wild rodents as experimental models has been proposed as a good alternative for studying the host-pathogen relationships and for testing candidate vaccines. To date, using natural reservoirs to study Leishmania infection has been challenging because immunologic reagents for use in wild rodents are lacking. This review discusses the principal immunological findings against Leishmania infection in different animal models highlighting the importance of using experimental conditions similar to natural transmission and reservoir species as experimental models to study the immunopathology of the disease.

Landslide susceptibility assessment in Karanganyar regency - Indonesia - Comparison of knowledge-based and Data-driven Models

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Algorithm for the Parkinson’s disease behavioural models characterization using a biosensor

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Development of novel human cellular models for neurotoxicity studies

Dissertation to obtain master degree in Genética Molecular e Biomedicina

Analysis of mental health service financial models with a particular emphasis of Ireland

ABSTRACT: Financing is a critical factor in ensuring the optimal development and delivery of a mental health system. The primary method of financing worldwide is tax-based. However many low income countries depend on out-of-pocket payments. There is a report on Irish Health Care funding but none that deals exclusively with mental health care. This paper analyses the various financial models that exist globally with respect to financing the mental health sector, examines the impact of various models on service users, especially in terms of relative ‘financial burden’ and provides a more detailed examination of the current mental health funding situation in Ireland After extensive internet and hardcopy research on the above topics, the findings were analysed and a number of recommendations were reached. Mental health service should be free at the point of delivery to achieve universal coverage. Government tax-based funding or mandatory social insurance with government top-ups, as required, appears the optimal option, although there is no one funding system applicable everywhere. Out-of-pocket funding can create a crippling financial burden for service users. It is important to employ improved revenue collection systems, eliminate waste, provide equitable resource distribution, ring fence mental health funding and cap the number of visits, where necessary. Political, economic, social and cultural factors play a role in funding decisions and this can be clearly seen in the context of the current economic recession in Ireland. Only 33% of the Irish population has access to free public health care and the number health insurance policy holders has dramatically declined, resulting in increased out-of-pocket payments. This approach risks negatively impacting on the social determinants of health, increasing health inequalities and negatively affecting economic productivity. It is therefore important the Irish government examines other options to provide funding for mental health services.

Empirical models for quantification of machining damage in composite materials

Dissertação para obtenção do Grau de Doutor em Engenharia Mecânica

Derivation and consistency checking of models in early software product line engineering

Dissertação para obtenção do Grau de Doutor em Engenharia Informática