Aplicação de ferramentas de marketing digital nas empresas turísticas

Nas últimas décadas, o turismo consolidou-se como uma das atividades que mais tem contribuído para o desenvolvimento de inúmeros países, regiões e cidades. Em Portugal, tornou-se a maior atividade económica exportadora, contribuindo fortemente para o crescimento do Produto Interno Bruto (PIB) nacional. Tais factos, espelham, de forma evidente, a importância que este deteve no desenvolvimento socioeconómico do país, na coesão territorial e na diminuição de assimetrias. Tal como nos anos antecessores, esperava-se que 2020 fosse mais um ano de excelência para o turismo nacional, de alcançar novos recordes e distinções. Porém, em março, com o início do surto pandémico de Covid-19, o cenário alterou-se por completo e rapidamente se tornou num ano dramático, sem precedentes. No entanto, em momentos de crise, também surgem oportunidades e novas formas de as empresas se reinventarem. Esta pandemia, veio acelerar a transformação digital em todos os setores, e o turismo não se revelou uma exceção. Mais do que nunca, os potenciais consumidores turísticos relacionam-se com as agências de viagem e turismo, e com os estabelecimentos hoteleiros através das plataformas digitais. É através deste meio que interagem mutuamente e que partilham informações sobre os produtos e serviços, de forma eficiente e instantânea. O marketing digital assume aqui um papel de destaque, sendo um verdadeiro desafio para as empresas turísticas, no âmbito da gestão dos seus canais de promoção, comunicação e distribuição. Num mercado altamente competitivo como o do turismo, torna-se imperativo para as empresas tentarem diferenciar-se das demais, sendo que o marketing digital pode desempenhar um papel muito importante nesse processo, afirmando-se como uma vantagem competitiva. A presente dissertação é composta por um estudo sobre a aplicação de ferramentas de marketing digital nas empresas turísticas. É imperatório abordar esta temática tão atual, de forma a avaliar e a perceber como o marketing digital e as respetivas ferramentas estão a ser utilizadas neste período pós-pandemia, pautada pela recuperação turística.Como instrumento de recolha de dados, foi utilizado o questionário, sendo que a amostra do estudo é constituída por cerca de 232 inquiridos, representantes de agências de viagem e turismo e estabelecimentos hoteleiros. Através dos resultados provenientes do tratamento dos dados, conclui-se que as ferramentas de marketing digital ainda não assumem um papel de relevo junto da maioria empresas turísticas, especialmente nas de menor dimensão como as microempresas. Dispor de um website próprio ou estar presentes nas rede sociais, é insuficiente quando olhamos para o marketing digital e para as ferramentas associadas como um todo. Verifica-se que no processo de recuperação pós-pandemia, somente uma baixa percentagem de estabelecimentos hoteleiros e agências de viagem e turismo procederam ao seu investimento, embora a promoção turística esteja na ordem do dia.In the last decades, tourism has been consolidated as one of the activities that has most contributed to the development of countless countries, regions and cities. In Portugal, it has become the largest exporting economic activity, contributing strongly to the growth of the national Gross Domestic Product (GDP). Such facts clearly reflect the importance it has held in the socio-economic development of the country, in territorial cohesion and in reducing asymmetries. As in previous years, it was expected that 2020 would be another year of excellence for national tourism, to achieve new records and distinctions. However, in March, with the beginning of the Covid-19 pandemic outbreak, the scenario changed completely and quickly became a dramatic, unprecedented year. However, in times of crisis, opportunities also arise and new ways for companies to reinvent themselves. This pandemic has accelerated digital transformation in all sectors, and tourism is no exception. More than ever, potential tourism consumers relate to travel agencies and hotels through digital platforms. It is through this medium that they interact with each other and share information about products and services, efficiently and instantaneously. Digital marketing assumes here a prominent role, being a real challenge for tourism companies in the management of their promotion, communication, and distribution channels. In a highly competitive market such as tourism, it becomes imperative for companies to try to differentiate themselves from others, and digital marketing can play a very important role in this process, asserting itself as a competitive advantage. This dissertation is composed by a study on the application of digital marketing tools in tourism companies. It is imperative to address this very current theme, in order to evaluate and understand how digital marketing and its tools are being used in this post-pandemic period, marked by tourism recovery. As an instrument of data collection, the questionnaire was used, and the study sample consists of about 232 respondents, representatives of travel and tourism agencies and hotels. Through the results of data processing, it can be concluded that digital marketing tools do not yet play a major role in most tourism businesses, especially in smaller ones such as micro-enterprises. Having their own website or being present in social networks is insufficient when we look at digital marketing and the associated tools as a whole. It is verified that in the post-pandemic recovery process, only a low percentage of hotel establishments and travel and tourism agencies proceeded with their investment, although tourism promotion is on the agenda

Estudo de recuperação energética em sistema de abastecimento de água através de bombas funcionando como turbinas. Estudo de caso: cidade de Elói Mendes

The use of the potential energy embedded in water supply systems through Pumps as Turbines (PATs) is an alternative that has been showing technical and economic viability due to the reduced cost of the pumps used. However, the system implementation may become economically unviable due to low potential energy available at each point and the need to project on-site infrastructure. In order to ease of maintenance, safety and guarantee of the pressure established in technical standards it is necessary to contain equipment such as drawer, filter, water meter and Pressure Reducing Valve (PRV) registers in a by-pass system contained in a protection box, which can lead to higher deployment costs. In view of the referenced problems, this paper proposes to analyze the economic feasibility for the installation of BFT and its attached equipment, considering the available potential energy, the present infrastructure, the installation cost and the future energy generation for each section studied. This analysis will be performed by calculating the Net Present Value (NPV), Internal Rate of Return (IRR), Levelized Cost of Electricity (LCOE) and payback, measuring three scenarios with different infrastructure levels on site. The ideal scenario, that considers the existence of the entire infrastructure, obtained the result of R$7,251.17 (NPV), 21$ 0.55/kWh levelized cost of electricity and approximately payback in six years, with power generation range of 0.11 kW up to 0.32 kW and annual generation of 1,772,81 kWh. The scenario that only presents civil works as existing infrastructure did not present deployment feasibility, resulting in a R$12,653.10 demage, 2$ 1.58/kWh. The real scenario, which depends on the installation of the entire infrastructure, also did not present deployment feasibility, resulting in a R$22,714.19 damage, -1IRR and R$2.10/kWh Levelized Cost of Electricity (LCOE).O aproveitamento do potencial energético presente em sistemas de abastecimento de água através de Bombas Funcionando como Turbinas (BFTs) é uma alternativa que vem apresentando viabilidade técnica e econômica devido ao custo reduzido das bombas utilizadas, porém o baixo potencial energético disponível em cada ponto e a infraestrutura necessária no local pode inviabilizar economicamente a implantação deste sistema. Para facilidade de manutenção, segurança e garantia da pressão estabelecida em normas técnicas, é necessário conter equipamentos como registros, filtro, hidrômetro e Válvula Redutora de Pressão (VRP) em sistema de by pass contido em caixa de proteção, o que pode levar na elevação do custo de implantação. Desta forma, este trabalho analisou a viabilidade econômica para a instalação da BFT e seus equipamentos anexos, considerando o potencial energético disponível, a infraestrutura presente, o custo de instalação e a geração energética futura para a seção estudada. Esta análise foi realizada através do cálculo do Valor Presente Líquido (VPL), Taxa Interna de Retorno (TIR), Custo Nivelado de Energia – ou Levelized Cost of Electricity (LCOE) – e payback, avaliando três cenários com diferentes níveis de infraestrutura no local. O cenário ideal, que considera a existência de toda infraestrutura, obteve como resultado R$7.251,17 de VPL, 21$ 0,55/kWh e payback de aproximadamente seis anos, com intervalo de potência de geração de 0,11 kW a 0,32 kW e geração anual de 1.772,81 kWh. O cenário que apresenta apenas a obra civil como infraestrutura existente não apresentou viabilidade econômica, resultando em um prejuízo de R$12.653,10, 2Nivelado de Energia de R$ 1,58/kWh. O cenário real, que necessita a instalação de toda infraestrutura, também não apresentou viabilidade de implantação, resultando em um prejuízo de R$22.714,19, -1$ 2,10/kWh

Development of novel genome-scale reconstruction strategies for production of terpenoids in Saccharomyces cerevisiae

info:eu-repo/semantics/publishedVersio

Predicting the number of biochemical transformations needed to synthesize a compound

Exploiting the natural metabolic abilities of microorganisms for the production of bioactive compounds has been a research problem of great interest. The economical and environmental costs associated with petrochemical-derived industries have promoted the emergence of biochemical processes from renewable carbon sources. However, optimally rewiring microbial metabolism in a competitive and sustainable manner is still a challenge. Recently, some retrobiosynthesis tools for the design of de novo biosynthetic pathways have been proposed. These tools generate a large number of intermediate compounds that are beyond experimental feasibility. Thus, effective methods to reduce the number of compounds by selecting the most promising ones are still needed. Here, we propose the use of classification and regression deep learning models, such as fully-connected neural networks and 1D convolutional neural networks, to predict the number of biochemical transformations needed to produce a compound. The data to train and evaluate the models was generated using a set of 13055 reaction rules and 673 compounds from Escherichia coli metabolism as starting compounds. The data was generated up to 5 steps resulting in a dataset of over 2.6 million compounds. This approach can be effectively used in biochemical applications, including retrobiosyntesis, to prioritize compounds that can be produced using fewer biochemical transformations.info:eu-repo/semantics/publishedVersio

Deep learning method for aortic root detection

Background: Computed tomography angiography (CTA) is a preferred imaging technique for a wide range of vascular diseases. However, extensive manual analysis is required to detect and identify several anatomical landmarks for clinical application. This study demonstrates the feasibility of a fully automatic method for detecting the aortic root, which is a key anatomical landmark in this type of procedure. The approach is based on the use of deep learning techniques that attempt to mimic expert behavior. Methods: A total of 69 CTA scans (39 for training and 30 for validation) with different pathology types were selected to train the network. Furthermore, a total of 71 CTA scans were selected independently and applied as the test set to assess their performance. Results: The accuracy was evaluated by comparing the locations marked by the method with benchmark locations (which were manually marked by two experts). The interobserver error was 4.6 ± 2.3 mm. On an average, the differences between the locations marked by the two experts and those detected by the computer were 6.6 ± 3.0 mm and 6.8 ± 3.3 mm, respectively, when calculated using the test set. Conclusions: From an analysis of these results, we can conclude that the proposed method based on pre-trained CNN models can accurately detect the aortic root in CTA images without prior segmentationThis work was partially financed by Consellería de Cultura, Educación e Universidade (reference 2019–2021, ED431C 2018/19)S

Uncovering the metabolic capacities of H. pylori 26695 using 13C labeling experiments

The determination of nutritional requirements of pathogenic organisms is of great significance for understanding host-pathogen interactions. Despite the knowledge obtained so far concerning amino acid requirements in H. pylori, it is still unclear which are the metabolic pathways used for biosynthesis and catabolism. Thus, information on the carbon flow in this organism is required. Glutamate is a very important metabolite in bacterial metabolism that can be used as a carbon and nitrogen source. 13C flux analysis has been largely applied to characterize phenotypes by quantifying in vivo the carbon fluxes. One of the most important applications of this approach is the identification of active pathways in less-studied organisms. Thus, in order to clarify the metabolic pathways used by H. pylori 26695, 13C labeling experiments with 13C-glutamate were conducted and labeled amino acids in biomass hydrolysates were analyzed by GC-MS. The obtained results confirmed L-glutamate as a potential sole and effective carbon source for H. pylori. Overall, all non-essential amino acids, except proline, presented a 13C labeling pattern. We hypothesized that L-proline is produced from L-arginine, while L-alanine is probably produced from pyruvate by alanine dehydrogenase. Additionally, the full usage of complete TCA cycle, under the conditions used, was also demonstrated

Algorithms to infer metabolic flux ratios from fluxomics data

In silico cell simulation approaches based in the use of genome-scale metabolic models (GSMMs) and constraint-based methods such as Flux Balance Analysis are gaining importance, but methods to integrate these approaches with omics data are still greatly needed. In this work, the focus relies on fluxomics data that provide valuable information on the intracellular fluxes, although in many cases in an indirect, incomplete and noisy way. The proposed framework enables the integration of fluxomics data, in the form of 13C labeling distribution for metabolite fragments, with GSMMs enriched with carbon atom transition maps. The algorithms implemented allow to infer labeling distributions for fragments/metabolites not measured and to build expressions for the relevant flux ratios that can be then used to enrich constraint-based methods for flux determination. This approach does not require any assumptions on the metabolic network and reaction reversibility, allowing to compute ratios originating from coupled joint points of the network. Also, when enough data do not exist, the system tries to infer ratio bounds from the measurements

Determinação de fatores de sombreamento com recurso a modelos 3D

Tese de mestrado integrado, Engenharia da Energia e do Ambiente, Universidade de Lisboa, Faculdade de Ciências, 2017O setor dos edifícios representa uma parte significativa do consumo elétrico mundial. Numa era em que se fala cada vez mais no conceito de sustentabilidade urbana, a contribuição deste setor pode passar por favorecer um design que consiga explorar o recurso solar, não só com vista à produção de energia, mas também como um meio para a diminuição do consumo elétrico. Uma das estratégias passivas mais atraentes é a incorporação propositada de elementos de sombra, para controlar os ganhos solares através de vãos envidraçados, tendo em conta as necessidades térmicas dos espaços. Esta modelação é feita com recurso ao cálculo do fator de sombreamento nas estações de aquecimento e arrefecimento. O objetivo desta dissertação é explorar procedimentos para estimar este fator, com o auxílio de duas abordagens inovadoras neste âmbito, comparando os resultados com os dois métodos previstos na regulamentação portuguesa, selecionando a metodologia mais fiável e económica neste contexto. As abordagens atuais para determinação do fator de sombreamento são enquadradas pela legislação portuguesa: i) uma metodologia de cálculo que envolve a contabilização de ângulos de obstrução para cada fonte causadora de sombra; ii) em alternativa, pode ser usado um sistema de atribuição de três classes de sombreamento, apoiada numa avaliação qualitativa no local do perfil de obstrução, denominada de regras de simplificação. Os métodos inovadores propostos consistem no cálculo do fator de sombreamento com recurso a um modelo 3D construído a partir de dados LiDAR e através da sobreposição de um diagrama solar em fotografias fisheye. Avaliando a precisão da metodologia fisheye, os resultados gerados apontam para erros relativos inferiores a 15% para as orientações mais relevantes, validando a aplicação deste método em situações onde os vãos envidraçados não possuem obstruções relevantes provenientes de palas verticais ou horizontais. Os dois métodos propostos nesta dissertação revelam uma precisão que lhes permite serem considerados para o cálculo do fator de sombreamento em edifícios, constituindo alternativas vantajosas do ponto de vista da análise do desempenho energético face à metodologia atual. O método fisheye é aquele que representa uma maior viabilidade económica que, associada a uma possível portabilidade para dispositivos móveis, pode trazer benefícios ao nível da certificação energética e tornar-se a referência no que toca ao cálculo do fator de sombreamento em edifícios.The buildings sector represents a significant part of the world's electricity consumption. At a time where the concept of urban sustainability is increasingly being a topic of discussion, the contribution of this sector may favor a design that can exploit the solar resource, not only as a way to produce energy, but also as a means to reduce the consumption. One of the most attractive passive strategies is the deliberate incorporation of shade elements to control solar gains through glazed spans, taking into account the thermal needs of the spaces. This modeling is accomplished using the calculation of the shading reduction factor in the heating and cooling seasons. The objective of this dissertation is to explore procedures to estimate this factor, with the help of two innovative approaches in this field, comparing the results with the two methods provided in the Portuguese regulation, selecting the most reliable and economic methodology in this context. The current approaches to determining the shading reduction factor are framed by the Portuguese legislation: i) a calculation methodology that involves the accounting of obstruction angles for each source causing shade; ii) Alternatively, a system of three shading classes can be used, based on a qualitative on-site assessment of the obstruction profile, called simplification rules. The proposed innovative methods consist of the calculation of the shading reduction factor using a 3D model constructed from LiDAR data and through the superposition of a solar diagram in fisheye photographs. Evaluating the accuracy of the fisheye methodology, the generated results point to relative errors of less than 15% for the most relevant orientations, validating the application of this method in situations where the glazed spans do not have relevant obstructions from fins or overhangs. The two methods proposed in this dissertation reveal a precision that allows them to be considered for the calculation of the shading reduction factor in buildings, constituting advantageous alternatives from the point of view of the energy performance analysis against the current methodology. The fisheye method is the one that represents greater economic viability that coupled with possible portability for mobile devices can bring benefits to experts in energy certification and become the benchmark for shading reduction factor calculation in buildings

Development of an integrated metabolic and transcriptional regulatory model for Saccharomyces cerevisiae

Saccharomyces cerevisiae (S. cerevisiae) is commonly used as a cell factory for research and industrial applications. The development of optimization strategies for S. cerevisiae was extensively driven by the establishment of genome-scale metabolic models. Additionally, to aid metabolic modeling, multiple attempts to infer transcriptional regulatory networks from expression data have been made. However, these data-based regulatory networks may show limited applicability. Therefore, we propose a general, knowledge-based approach involving a pipeline to evaluate regulatory interactions of transcription factors (TFs) and target genes from the YEASTRACT database, and form a regulatory network from these filtered datasets. So far, we filtered regulatory interactions based on two criteria: the existence of direct binding evidence of the TFs and their target genes, and the consensus over the regulatory effects identified among multiple studies that investigated each interaction, respectively. From 230 TFs and over 6000 genes contained in YEASTRACT, we obtained a regulatory network of 69 TFs and 1187 target genes with 1813 regulatory interactions, including 346 metabolic genes with 622 regulatory interactions. These interactions cover the majority of genes in the central carbon metabolism. Next, these regulatory interactions will be evaluated by identifying the networks attractor states and simulating their effect on the metabolic system via steady-state regulatory flux balance analysis. Finally, this integrated metabolic and regulatory model may be used to identify efficient optimization strategies for S. cerevisiae.info:eu-repo/semantics/publishedVersio