Hospital costs and random demand

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics

A random access MAC protocol for MPR satellite networks

Dissertação apresentada para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Problems and perspectives for Chagas disease control: in search of a realistic analysis

Chagas disease was an important medical and social problem in almost all of Latin America throughout the twentieth century. It has been combated over a broad swath of this continent over recent decades, with very satisfactory results in terms of vector and transfusional transmission. Today, a surveillance stage still remains to be consolidated, in parallel with appropriate care required for some millions of infected individuals who are today living in endemic and non-endemic areas. Contradictorily, the good results attained have generated excessive optimism and even disregard among health authorities, in relation to this disease and its control. The loss of visibility and priority may be a logical consequence, particularly in Latin American healthcare systems that are still disorganized and overburdened due to insufficiencies of financial and human resources. Consolidation of the victories against Chagas disease is attainable but depends on political will and continual attention from the most consequential protagonists in this struggle, especially the Latin American scientific community.

Identification and differentiation of Candida species from pediatric patients by random amplified polymorphic DNA

Thirty-four Candida isolates were analyzed by random amplified polymorphic DNA using the primer OPG-10:24 Candida albicans; 4 Candida tropicalis; 2 Candida parapsilosis; 2 Candida dubliniensis; 1 Candida glabrata and 1 Candida krusei. The UPGMA-Pearson correlation coefficient was used to calculate the genetic distance between the different Candida groupings. Samples were classified as identical (correlation of 100%); highly related samples (90%); moderately related samples (80%) and unrelated samples (< 70%). The results showed that the RAPD proposed was capable of classifying the isolates coherently (such that same species were in the same dendrogram), except for two isolates of Candida parapsilosis and the positive control (Netherlands, 1973), probably because they are now recognized as three different species. Concerning the only fluconazole-resistant Candida tropicalis isolate with a genotype that was different to the others, the data were insufficient to affirm that the only difference was the sensitivity to fluconazole. We concluded that the Random Amplified Polymorphic DNA proposed might be used to confirm Candida species identified by microbiological methods.

Probabilistic constraint reasoning with Monte Carlo integration to robot localization

This work studies the combination of safe and probabilistic reasoning through the hybridization of Monte Carlo integration techniques with continuous constraint programming. In continuous constraint programming there are variables ranging over continuous domains (represented as intervals) together with constraints over them (relations between variables) and the goal is to find values for those variables that satisfy all the constraints (consistent scenarios). Constraint programming “branch-and-prune” algorithms produce safe enclosures of all consistent scenarios. Special proposed algorithms for probabilistic constraint reasoning compute the probability of sets of consistent scenarios which imply the calculation of an integral over these sets (quadrature). In this work we propose to extend the “branch-and-prune” algorithms with Monte Carlo integration techniques to compute such probabilities. This approach can be useful in robotics for localization problems. Traditional approaches are based on probabilistic techniques that search the most likely scenario, which may not satisfy the model constraints. We show how to apply our approach in order to cope with this problem and provide functionality in real time.

Leprosy in Buriticupu, state of Maranhão: active search in the general population

INTRODUCTION: This study was developed to evaluate the situation of leprosy in the general population of the municipality of Buriticupu, State of Maranhão, Brazil. METHODS: We used the method of active search to identify new cases from 2008 to 2010. Bacilloscopy of intradermal scrapings was performed in all patients with skin lesions compatible with leprosy, and histopathological examination in those who had doubts on the definition of the clinical form. RESULTS: The study included 19,104 individuals, with 42 patients diagnosed with leprosy after clinical examination, representing a detection rate of 219.84 per 100,000 inhabitants. The predominant clinical presentation was tuberculoid with 24 (57.1%) cases, followed by borderline with 11, indeterminate with four, and lepromatous with three cases. The study also allowed the identification of 81 patients with a history of leprosy and other skin diseases, such as pityriasis versicolor, dermatophytosis, scabies, vitiligo, and skin carcinoma. The binomial test showed that the proportion of cases in the headquarters was significantly higher than that in the villages (p = 0.04), and the generalized exact test showed that there was no association between age and clinical form (p = 0.438) and between age and gender (p = 0.083). CONCLUSIONS: The elevated detection rate defines the city as hyperendemic for leprosy; the active search for cases, as well as the organization of health services, is an important method for disease control.

Triatomines in dwellings and outbuildings in an endemic area of Chagas disease in northeastern Brazil

INTRODUCTION: The present study identified the triatomines collected in intra and peri-domestic environments, observed the occurrence of Trypanosoma cruzi infection in triatomines and correlated this information with housing conditions and the fauna associated with the rural areas of the City of Itabaianinha, located in the State of Sergipe, Brazil. METHODS: Quarterly visits were conducted between March 2009 and March 2010, and the homes to be visited for the active search of insects were determined by random selection. In each housing unit, the insects were collected by a manual search with a metal clip and flashlight to inspect openings and cavities, with a collection time of one hour/home/individual. The Pirisa® dislodge chemical was used to force the insects to leave their ecotopes. Analysis of the intestinal contents of triatomines was performed in the laboratory to establish the presence of Trypanosomatidae. RESULTS: Of the 103 dwellings surveyed, 17.5% were infested with Panstrongylus megistus. The village of Mutuca exhibited the highest infestation rate (38.1%). All the villages with relevant infestation rates were situated in the northern area of the city. The highest percentage of vector infection was found in the village of Água Boa (56.5%). The rural dwellings were found to be primarily brick or wooden house with or without roughcast or plastered walls, and the outbuilding most frequently associated with triatomines was the chicken run. CONCLUSIONS: These results emphasise the need for broader vector control and surveillance and for educational campaigns in the context of the Chagas Disease Control Program.

Search-for-yield in Portuguese fixed-income mutual funds and monetary policy

This paper studies the effects of monetary policy on mutual fund risk taking using a sample of Portuguese fixed-income mutual funds in the 2000-2012 period. Firstly I estimate time-varying measures of risk exposure (betas) for the individual funds, for the benchmark portfolio, as well as for a representative equally-weighted portfolio, through 24-month rolling regressions of a two-factor model with two systematic risk factors: interest rate risk (TERM) and default risk (DEF). Next, in the second phase, using the estimated betas, I try to understand what portion of the risk exposure is in excess of the benchmark (active risk) and how it relates to monetary policy proxies (one-month rate, Taylor residual, real rate and first principal component of a cross-section of government yields and rates). Using this methodology, I provide empirical evidence that Portuguese fixed-income mutual funds respond to accommodative monetary policy by significantly increasing exposure, in excess of their benchmarks, to default risk rate and slightly to interest risk rate as well. I also find that the increase in funds’ risk exposure to gain a boost in return (search-for-yield) is more pronounced following the 2007-2009 global financial crisis, indicating that the current historic low interest rates may incentivize excessive risk taking. My results suggest that monetary policy affects the risk appetite of non-bank financial intermediaries.

Do hospitals react to random demand pressure by early discharges?

This project tries to assess whether hospitals react to random demand pressure by discharging patients earlier than expected. As a matter of fact, combining an unpredictable demand for medical services with limited and, to some extent, fixed medical resources, generates strong incentives to discharge patients earlier than expected when demand is high − increasing the risk of readmission and decreasing the benefit from treatment. This work was conducted as a way to determine whether those incentives actually affect discharging decisions. Analysis of Portuguese hospitals data shows that hospital utilization levels at the time of admission, prior to the admission and post admission do have a negative impact over the length of stay in hospital, although this impact is quantitatively irrelevant. More than that, larger utilization levels have a positive impact over the probability of being discharged at certain days of the week, indicating that an early discharges problem may exist.

A public transport bus assignment problem: parallel metaheuristics assessment

Combinatorial Optimization Problems occur in a wide variety of contexts and generally are NP-hard problems. At a corporate level solving this problems is of great importance since they contribute to the optimization of operational costs. In this thesis we propose to solve the Public Transport Bus Assignment problem considering an heterogeneous fleet and line exchanges, a variant of the Multi-Depot Vehicle Scheduling Problem in which additional constraints are enforced to model a real life scenario. The number of constraints involved and the large number of variables makes impracticable solving to optimality using complete search techniques. Therefore, we explore metaheuristics, that sacrifice optimality to produce solutions in feasible time. More concretely, we focus on the development of algorithms based on a sophisticated metaheuristic, Ant-Colony Optimization (ACO), which is based on a stochastic learning mechanism. For complex problems with a considerable number of constraints, sophisticated metaheuristics may fail to produce quality solutions in a reasonable amount of time. Thus, we developed parallel shared-memory (SM) synchronous ACO algorithms, however, synchronism originates the straggler problem. Therefore, we proposed three SM asynchronous algorithms that break the original algorithm semantics and differ on the degree of concurrency allowed while manipulating the learned information. Our results show that our sequential ACO algorithms produced better solutions than a Restarts metaheuristic, the ACO algorithms were able to learn and better solutions were achieved by increasing the amount of cooperation (number of search agents). Regarding parallel algorithms, our asynchronous ACO algorithms outperformed synchronous ones in terms of speedup and solution quality, achieving speedups of 17.6x. The cooperation scheme imposed by asynchronism also achieved a better learning rate than the original one.

In Search of the Origins of Modernism: Venice and the Crisis of Classical Architecture in the mid-eighteenth century

This paper attempts to prove that in the years 1735 to 1755 Venice was the birthplace and cradle of Modern architectural theory, generating a major crisis in classical architecture traditionally based on the Vitruvian assumption that it imitates early wooden structures in stone or in marble. According to its rationalist critics such as the Venetian Observant Franciscan friar and architectural theorist Carlo Lodoli (1690-1761) and his nineteenth-century followers, classical architecture is singularly deceptive and not true to the nature of materials, in other words, dishonest and fallacious. This questioning did not emanate from practising architects, but from Lodoli himself– a philosopher and educator of the Venetian patriciate – who had not been trained as an architect. The roots of this crisis lay in a new approach to architecture stemming from the new rationalist philosophy of the Enlightenment age with its emphasis on reason and universal criticism.

Learning domain-specific sentiment lexicons with applications to recommender systems

Search is now going beyond looking for factual information, and people wish to search for the opinions of others to help them in their own decision-making. Sentiment expressions or opinion expressions are used by users to express their opinion and embody important pieces of information, particularly in online commerce. The main problem that the present dissertation addresses is how to model text to find meaningful words that express a sentiment. In this context, I investigate the viability of automatically generating a sentiment lexicon for opinion retrieval and sentiment classification applications. For this research objective we propose to capture sentiment words that are derived from online users’ reviews. In this approach, we tackle a major challenge in sentiment analysis which is the detection of words that express subjective preference and domain-specific sentiment words such as jargon. To this aim we present a fully generative method that automatically learns a domain-specific lexicon and is fully independent of external sources. Sentiment lexicons can be applied in a broad set of applications, however popular recommendation algorithms have somehow been disconnected from sentiment analysis. Therefore, we present a study that explores the viability of applying sentiment analysis techniques to infer ratings in a recommendation algorithm. Furthermore, entities’ reputation is intrinsically associated with sentiment words that have a positive or negative relation with those entities. Hence, is provided a study that observes the viability of using a domain-specific lexicon to compute entities reputation. Finally, a recommendation system algorithm is improved with the use of sentiment-based ratings and entities reputation.

How different generations contact and search for brands on social media? Comparing gen X and Y

This research intends to examine if there were significant differences on the brand engagement and on the electronic word of mouth (e-WOM)1 referral intention through Facebook between Generation X and Generation Y (also called millennials). Also, this study intends to examine if there are differences in the motivations that drive these generations to interact with brands through Facebook. Results indicated that Generation Y members consumed more content on Facebook brands’ pages than Generation X. Also, they were more likely to have an e-WOM referral intention as well as being more driven by brand affiliation and opportunity seeking. Finally, currently employed individuals were found to contribute with more content than students. This study fills the gap in the literature by addressing how marketing professionals should market their brand and interact and engage with their customers, based on customers’ generational cohort.

Genetic algorithms for the non emergency patients transport service

The authors would like to thank the anonymous reviewers for their valuable comments and suggestions to improve the paper. The authors would like to thank Dr. Elaine DeBock for reviewing the manuscript.