How to engage low category users through social media- The case of the make-up sector in Portugal

Purpose: This work project should be inevitably deemed as a practical approach to a marketing problem; “How to engage low category users through the social media – the case of the make-up sector in Portugal”. Design/methodology/approach: Online structured questionnaires and in-depth interviews were used. The questionnaire was answered by 110 women aged from 15 to 45 years old and the interviews were conducted with 14 women of the same age. The interviews provided key insights for the questionnaire formulation. Findings: Women are poorly informed on make-up properties and characteristics, feeling a genuine concern in regard to this subject. Lack of time, occasional usage and skin damage are the main barriers for make-up usage by low category users. Overcoming these aspects pass by demystifying the association of make-up with skin damage and emphasise the functional and emotional benefits of make-up. Further, brands need to create contents more consumer-oriented and ask directly to fans/followers suggestions and other insights. Resort to Portuguese “common” women for greater empathy in campaigns, promote online meetings between followers and make-up professionals on social media; and finally take advantage of the hybrid condition of Facebook, which incorporates multiple forms of content presentation, including videos, the most appealing format of make-up presentation for women. Research limitations/implications: Further studies addressing this topic, by using larger samples and study of specific make-up brands and campaign programs, over social media to reach a solid growth potential of make-up market evidences in Portugal. Originality/ value: Make-up brands are emphasising their interest in linking social media and marketing their promotional mix around social marketing.

Essays on bounded rationality: Individual decision and strategic interaction

Economics is a social science which, therefore, focuses on people and on the decisions they make, be it in an individual context, or in group situations. It studies human choices, in face of needs to be fulfilled, and a limited amount of resources to fulfill them. For a long time, there was a convergence between the normative and positive views of human behavior, in that the ideal and predicted decisions of agents in economic models were entangled in one single concept. That is, it was assumed that the best that could be done in each situation was exactly the choice that would prevail. Or, at least, that the facts that economics needed to explain could be understood in the light of models in which individual agents act as if they are able to make ideal decisions. However, in the last decades, the complexity of the environment in which economic decisions are made and the limits on the ability of agents to deal with it have been recognized, and incorporated into models of decision making in what came to be known as the bounded rationality paradigm. This was triggered by the incapacity of the unboundedly rationality paradigm to explain observed phenomena and behavior. This thesis contributes to the literature in three different ways. Chapter 1 is a survey on bounded rationality, which gathers and organizes the contributions to the field since Simon (1955) first recognized the necessity to account for the limits on human rationality. The focus of the survey is on theoretical work rather than the experimental literature which presents evidence of actual behavior that differs from what classic rationality predicts. The general framework is as follows. Given a set of exogenous variables, the economic agent needs to choose an element from the choice set that is avail- able to him, in order to optimize the expected value of an objective function (assuming his preferences are representable by such a function). If this problem is too complex for the agent to deal with, one or more of its elements is simplified. Each bounded rationality theory is categorized according to the most relevant element it simplifes. Chapter 2 proposes a novel theory of bounded rationality. Much in the same fashion as Conlisk (1980) and Gabaix (2014), we assume that thinking is costly in the sense that agents have to pay a cost for performing mental operations. In our model, if they choose not to think, such cost is avoided, but they are left with a single alternative, labeled the default choice. We exemplify the idea with a very simple model of consumer choice and identify the concept of isofin curves, i.e., sets of default choices which generate the same utility net of thinking cost. Then, we apply the idea to a linear symmetric Cournot duopoly, in which the default choice can be interpreted as the most natural quantity to be produced in the market. We find that, as the thinking cost increases, the number of firms thinking in equilibrium decreases. More interestingly, for intermediate levels of thinking cost, an equilibrium in which one of the firms chooses the default quantity and the other best responds to it exists, generating asymmetric choices in a symmetric model. Our model is able to explain well-known regularities identified in the Cournot experimental literature, such as the adoption of different strategies by players (Huck et al. , 1999), the inter temporal rigidity of choices (Bosch-Dom enech & Vriend, 2003) and the dispersion of quantities in the context of di cult decision making (Bosch-Dom enech & Vriend, 2003). Chapter 3 applies a model of bounded rationality in a game-theoretic set- ting to the well-known turnout paradox in large elections, pivotal probabilities vanish very quickly and no one should vote, in sharp contrast with the ob- served high levels of turnout. Inspired by the concept of rhizomatic thinking, introduced by Bravo-Furtado & Côrte-Real (2009a), we assume that each per- son is self-delusional in the sense that, when making a decision, she believes that a fraction of the people who support the same party decides alike, even if no communication is established between them. This kind of belief simplifies the decision of the agent, as it reduces the number of players he believes to be playing against { it is thus a bounded rationality approach. Studying a two-party first-past-the-post election with a continuum of self-delusional agents, we show that the turnout rate is positive in all the possible equilibria, and that it can be as high as 100%. The game displays multiple equilibria, at least one of which entails a victory of the bigger party. The smaller one may also win, provided its relative size is not too small; more self-delusional voters in the minority party decreases this threshold size. Our model is able to explain some empirical facts, such as the possibility that a close election leads to low turnout (Geys, 2006), a lower margin of victory when turnout is higher (Geys, 2006) and high turnout rates favoring the minority (Bernhagen & Marsh, 1997).

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.

Snakebites as a largely neglected problem in the Brazilian Amazon: highlights of the epidemiological trends in the State of Amazonas

Envenoming snakebites are thought to be a particularly important threat to public health worldwide, especially in rural areas of tropical and subtropical countries. The true magnitude of the public health threat posed by snakebites is unknown, making it difficult for public health officials to optimize prevention and treatment. The objective of this work was to conduct a systematic review of the literature to gather data on snakebite epidemiology in the Amazon region and describe a case series of snakebites from epidemiological surveillance in the State of Amazonas (1974-2012). Only 11 articles regarding snakebites were found. In the State of Amazonas, information regarding incidents involving snakes is scarce. Historical trends show an increasing number of cases after the second half of the 1980s. Snakebites predominated among adults (20-39 years old; 38%), in the male gender (78.9%) and in those living in rural areas (85.6%). The predominant snake envenomation type was bothropic. The incidence reported by the epidemiological surveillance in the State of Amazonas, reaching up to 200 cases/100,000 inhabitants in some areas, is among the highest annual snakebite incidence rates of any region in the world. The majority of the cases were reported in the rainy season with a case-fatality rate of 0.6%. Snakebite envenomation is a great disease burden in the State of Amazonas, representing a challenge for future investigations, including approaches to estimating incidence under-notification and case-fatality rates as well as the factors related to severity and disabilities.

Prevalence of intestinal parasites and risk factors forspecific and multiple helminth infections in a remote city of the Brazilian Amazon

Abstract: INTRODUCTION: Few studies have described the risk factors of intestinal parasitic infections in the Amazon. METHODS: A cross-sectional survey was performed in a City of the State of Amazonas (Brazil) to estimate the prevalence of intestinal parasites and determine the risk factors for helminth infections. RESULTS: Ascaris lumbricoides was the most prevalent parasite. The main risk factors determined were: not having a latrine for A. lumbricoides infection; being male and having earth or wood floors for hookworm infection; and being male for multiple helminth infections. CONCLUSIONS: We reported a high prevalence of intestinal parasites and determined some poverty-related risk factors.

Improving the early diagnostic of prostate cancer by multiple biomarker detection with new biosensing devices

Prostate cancer (PCa) is the most common form of cancer in men, in Europe (World Health Organization data). The most recent statistics, in Portuguese territory, confirm this scenario, which states that about 50% of Portuguese men may suffer from prostate cancer and 15% of these will die from this condition. Its early detection is therefore fundamental. This is currently being done by Prostate Specific Antigen (PSA) screening in urine but false positive and negative results are quite often obtained and many patients are sent to unnecessary biopsy procedures. This early detection protocol may be improved, by the development of point-of-care cancer detection devices, not only to PSA but also to other biomarkers recently identified. Thus, the present work aims to screen several biomarkers in cultured human prostate cell lines, serum and urine samples, developing low cost sensors based on new synthetic biomaterials. Biomarkers considered in this study are the following: prostate specific antigen (PSA), annexin A3 (ANXA3), microseminoprotein-beta (MSMB) and sarcosine (SAR). The biomarker recognition may occurs by means of molecularly imprinted polymers (MIP), which are a kind of plastic antibodies, and enzymatic approaches. The growth of a rigid polymer, chemically stable, using the biomarker as a template allows the synthesis of the plastic antibody. MIPs show high sensitivity/selectivity and present much longer stability and much lower price than natural antibodies. This nanostructured material was prepared on a carbon solid. The interaction between the biomarker and the sensing-material produces electrical signals generating quantitative or semi-quantitative data. These devices allow inexpensive and portable detection in point-of-care testing.

New migraine preventive options: an update with pathophysiological considerations

BACKGROUND: The pharmacological treatment of migraine may be acute or preventive. Frequent, severe and long-lasting migraine attacks require prophylaxis. Multiple threads of research over the last 15 years have led to the concept that migraine is generated from a hyperexcitable brain. A variety of causes for hyperexcitability of the brain in migraine have been suggested. These causes include low cerebral magnesium levels, mitochondrial abnormalities, dysfunctions related to increased nitric oxide or the existence of a P/Q type calcium channelopathy. The better knowledge about migraine pathophisiology led us to discuss new treatment options. OBJECTIVES: The aim of the present study is to present an evidence-based review of some new drugs or some agents that even though available for a long time, are not frequently used. METHODS/RESULTS: We present a review of anticonvulsants with various mechanisms of action such as lamotrigine, gabapentin, topiramate, tiagabine, levetiracetam and zonisamide. We also review natural products, like riboflavin and magnesium, botulinum toxin A, a specific CGRP antagonist and the anti-asthma medication montelukast, with pathophysiological discussion. CONCLUSIONS: We aimed to present an update of newer or less frequently used preventive migraine therapies, drugs that might reduce the burden and the costs of a disease that should be considered as a public health problem all around the world.

Analysis of a controversial decision process: the case of the pumped hydro storage power plant Atdorf in Germany

Based on the report for the unit “Métodos Interactivos de Participação e Decisão A” (Interactive methods of participation and decision A), coordinated by Prof. Lia Maldonado Teles de Vasconcelos and Prof. Nuno Miguel Ribeiro Videira Costa. This unit was provided for the PhD Program in Technology Assessment in 2015/2016.

The effect of intravenous zoledronic acid on glucocorticoid-induced multiple vertebral fractures in juvenile systemic lupus erythematosus

Glucocorticoids are widely used in the treatment of lupus patients, and adverse effects, which include osteoporosis and associated fractures, are frequent. Treatment of osteoporosis of young patients should be effective and not harmful to bone growth and remodeling. Bisphosphonates are drugs that decrease the incidence of bone fractures, but their use in juvenile patients is still controversial because of their possible side effects on the growing skeleton. However, recently published studies showed that linear growth continued normally after treatment with these drugs, and there was no excessive suppression of bone remodeling or mineralization defects. Zoledronic acid is a new intravenous bisphosphonate that has been approved by the US FDA for use with hypercalcemia of malignancies and might be an effective treatment for postmenopausal osteoporosis. The authors report a case of a young girl with systemic lupus who developed multiple vertebral collapses due to glucocorticoid therapy, and zoledronic acid was used producing significant clinical and densitometric improvement.

Is Modernity Multiple?

Fundação para a Ciência e a Tecnologia (FCT), Fundação Millennium bcp

The effect of deforestation on the water cycle in the amazon basin: an attempt reformulate the problem

If widespread deforestation in Amazon results in reduced evaporative water flux, then either a decrease in evaporation is compensated locally by reduced rainfall,or else changed moisture balance expresses itself downwind in the yet undisturbed forest. The question of where rain will occur is crucial. It is suggested that the appearance of clouds and the occurrence of rainout is governed primarily by the interplay of local meteorologic and physical geography parameters with the atmospheric stability structure except for a few well-defined periods when rain is dominated by large scale atmospheric instability. This means that the study of these phenomena (local heat balances,studies on cloud formation mechanism, vertical atmospheric stability, etc.) must be made on the scale of the cloud size, a few tens of kilometers at most.

A type system for value-dependent information flow analysis

Information systems are widespread and used by anyone with computing devices as well as corporations and governments. It is often the case that security leaks are introduced during the development of an application. Reasons for these security bugs are multiple but among them one can easily identify that it is very hard to define and enforce relevant security policies in modern software. This is because modern applications often rely on container sharing and multi-tenancy where, for instance, data can be stored in the same physical space but is logically mapped into different security compartments or data structures. In turn, these security compartments, to which data is classified into in security policies, can also be dynamic and depend on runtime data. In this thesis we introduce and develop the novel notion of dependent information flow types, and focus on the problem of ensuring data confidentiality in data-centric software. Dependent information flow types fit within the standard framework of dependent type theory, but, unlike usual dependent types, crucially allow the security level of a type, rather than just the structural data type itself, to depend on runtime values. Our dependent function and dependent sum information flow types provide a direct, natural and elegant way to express and enforce fine grained security policies on programs. Namely programs that manipulate structured data types in which the security level of a structure field may depend on values dynamically stored in other fields The main contribution of this work is an efficient analysis that allows programmers to verify, during the development phase, whether programs have information leaks, that is, it verifies whether programs protect the confidentiality of the information they manipulate. As such, we also implemented a prototype typechecker that can be found at http://ctp.di.fct.unl.pt/DIFTprototype/.

The non-emergency patient transport modelled as a team orienteering problem

This work presents an improved model to solve the non-emergency patients transport (NEPT) service issues given the new rules recently established in Portugal. The model follows the same principle of the Team Orienteering Problem by selecting the patients to be included in the routes attending the maximum reduction in costs when compared with individual transportation. This model establishes the best sets of patients to be transported together. The model was implemented in AMPL and a compact formulation was solved using NEOS Server. A heuristic procedure based on iteratively solving Orienteering Problems is presented, and this heuristic provides good results in terms of accuracy and computation time. Euclidean instances as well as asymmetric real data gathered from Google maps were used, and the model has a promising performance mainly with asymmetric cost matrices.