Reverse Engineering Static Content and Dynamic Behaviour of E-Commerce Websites for Fun and Profit

Atualmente os websites de comércio eletrónico são uma das ferramentas principais para a realização de transações entre comerciantes online e consumidores ou empresas. Estes websites apoiam- se fortemente na sumarização e análise dos hábitos de navegação dos consumidores, de forma a influenciar as suas ações no website com o intuito de otimizar métricas de sucesso como o CTR (Click through Rate), CPC (Cost per Conversion), Basket e Lifetime Value e User Engagement. A utilização de técnicas de data mining e machine learning na extração de conhecimento a partir dos conjuntos de dados existentes nos websites de comércio eletrónico tem vindo a ter uma crescente influência nas campanhas de marketing realizadas na Internet.Quando o provedor de serviços de machine learning se deparada com um novo website de comércio eletrónico, inicia um processo de web mining, fazendo recolha de dados, tanto históricos como em tempo real, do website e analisando/transformando estes dados de forma a tornar os mesmos utilizáveis para fins de extração de informação tanto sobre a estrutura e conteúdo de um website assim como dos hábitos de navegação dos seus utilizadores típicos. Apenas após este processo é que os data scientists são capazes de desenvolver modelos relevantes e algoritmos para melhorar e otimizar as atividades de marketing online.Este processo é, na sua generalidade, moroso em tempo e recursos, dependendo sempre da condição em que os dados são apresentados ao data scientist. Dados com mais qualidade (p.ex. dados completos), facilitam o trabalho dos data scientists e tornam o mesmo mais rápido. Por outro lado, na generalidade dos casos, os data scientists tem de recorrer a técnicas de monitorização de eventos específicos ao domínio do website de forma a atingir o objetivo de conhecer os hábitos dos utlizadores, tornando-se necessário a realização de modificações ao código fonte do website para a captura desses mesmos eventos, aumentando assim o risco de não capturar toda a informação relevante por não ativar os mecanismos de monitorização em todas as páginas do web- site. Por exemplo, podemos não ter conhecimento a priori que uma visita à página de Condições de Entrega é relevante para prever o desejo de um dado consumidor efetuar uma compra e, desta forma, os mecanismos de monitorização nessas páginas podem não ser ativados.No contexto desta problemática, a solução proposta consiste numa metodologia capaz de ex- trair e combinar a informação sobre um dado website de comércio eletrónico através de um pro- cesso de web mining, compreendendo a estrutura de páginas de um website, assim como do conteúdo das mesmas, baseando-se para isso na identificação de conteúdo dinâmico das páginas assim como informação semântica recolhida de locais predefinidos. Adicionalmente esta informação é complementada, usando dados presente nos registos de acesso de utilizadores, com modelos preditivos do futuro comportamento dos utilizadores no website. Torna-se assim possível a apresentação de um modelo de dados representando a informação sobre um dado website de comércio eletrónico e os seus utilizadores arquetípicos, podendo posteriormente estes dados serem utiliza- dos, por exemplo, em sistemas de simulação.Nowadays electronic commerce websites are one of the main transaction tools between on-line merchants and consumers or businesses. These e-commerce websites rely heavily on summarizing and analyzing the behavior of customers, making an effort to influence user actions towards the optimization of success metrics such as CTR (Click through Rate), CPC (Cost per Conversion), Basket and Lifetime Value and User Engagement. Knowledge extraction from the existing e- commerce websites datasets, using data mining and machine learning techniques, has been greatly influencing the Internet marketing activities.When faced with a new e-commerce website, the machine learning practitioner starts a web mining process by collecting historical and real-time data of the website and analyzing/transforming this data in order to be capable of extracting information about the website structure and content and its users' behavior. Only after this process the data scientists are able to build relevant models and algorithms to enhance marketing activities.This is an expensive process in resources and time since it will always depend on the condition in which the data is presented to the data scientist, since data with more quality (i.e. no incomplete data) will make the data scientist work easier and faster. On the other hand, in most of the cases, data scientists would usually resort to tracking domain-specific events throughout a user's visit to the website in order to fulfill the objective of discovering the users' behavior and, for this, it is necessary to perform code modifications to the pages themselves, that will result in a larger risk of not capturing all the relevant information by not enabling tracking mechanisms in certain pages. For example, we may not know a priori that a visit to a Delivery Conditions page is relevant to the prediction of a user's willingness to buy and therefore would not enable tracking on those pages.Within this problem context, the proposed solution consists in a methodology capable of extracting and combining information about a e-commerce website through a process of web mining, comprehending the structure as well as the content of the website pages, relying mostly on identifying dynamic content and semantic information in predefined locations, complemented with the capability of, using the user's access logs, extracting more accurate models to predict the users future behavior. This allows for the creation of a data model representing an e-commerce website and its archetypical users that can be useful, for example, in simulation systems

MAMMALS IN PORTUGAL : A data set of terrestrial, volant, and marine mammal occurrences in P ortugal

Mammals are threatened worldwide, with 26% of all species being includedin the IUCN threatened categories. This overall pattern is primarily associatedwith habitat loss or degradation, and human persecution for terrestrial mam-mals, and pollution, open net fishing, climate change, and prey depletion formarine mammals. Mammals play a key role in maintaining ecosystems func-tionality and resilience, and therefore information on their distribution is cru-cial to delineate and support conservation actions. MAMMALS INPORTUGAL is a publicly available data set compiling unpublishedgeoreferenced occurrence records of 92 terrestrial, volant, and marine mam-mals in mainland Portugal and archipelagos of the Azores and Madeira thatincludes 105,026 data entries between 1873 and 2021 (72% of the data occur-ring in 2000 and 2021). The methods used to collect the data were: live obser-vations/captures (43%), sign surveys (35%), camera trapping (16%),bioacoustics surveys (4%) and radiotracking, and inquiries that represent lessthan 1% of the records. The data set includes 13 types of records: (1) burrowsjsoil moundsjtunnel, (2) capture, (3) colony, (4) dead animaljhairjskullsjjaws, (5) genetic confirmation, (6) inquiries, (7) observation of live animal (8),observation in shelters, (9) photo trappingjvideo, (10) predators dietjpelletsjpine cones/nuts, (11) scatjtrackjditch, (12) telemetry and (13) vocalizationjecholocation. The spatial uncertainty of most records ranges between 0 and100 m (76%). Rodentia (n=31,573) has the highest number of records followedby Chiroptera (n=18,857), Carnivora (n=18,594), Lagomorpha (n=17,496),Cetartiodactyla (n=11,568) and Eulipotyphla (n=7008). The data setincludes records of species classified by the IUCN as threatened(e.g.,Oryctolagus cuniculus[n=12,159],Monachus monachus[n=1,512],andLynx pardinus[n=197]). We believe that this data set may stimulate thepublication of other European countries data sets that would certainly contrib-ute to ecology and conservation-related research, and therefore assisting onthe development of more accurate and tailored conservation managementstrategies for each species. There are no copyright restrictions; please cite thisdata paper when the data are used in publications.info:eu-repo/semantics/publishedVersio

Mammals in Portugal: a data set of terrestrial, volant, and marine mammal occurrences in Portugal

Mammals are threatened worldwide, with ~26% of all species being included in the IUCN threatened categories. This overall pattern is primarily associated with habitat loss or degradation, and human persecution for terrestrial mammals, and pollution, open net fishing, climate change, and prey depletion for marine mammals. Mammals play a key role in maintaining ecosystems functionality and resilience, and therefore information on their distribution is crucial to delineate and support conservation actions. MAMMALS IN PORTUGAL is a publicly available data set compiling unpublished georeferenced occurrence records of 92 terrestrial, volant, and marine mammals in mainland Portugal and archipelagos of the Azores and Madeira that includes 105,026 data entries between 1873 and 2021 (72% of the data occurring in 2000 and 2021). The methods used to collect the data were: live observations/captures (43%), sign surveys (35%), camera trapping (16%), bioacoustics surveys (4%) and radiotracking, and inquiries that represent less than 1% of the records. The data set includes 13 types of records: (1) burrows | soil mounds | tunnel, (2) capture, (3) colony, (4) dead animal | hair | skulls | jaws, (5) genetic confirmation, (6) inquiries, (7) observation of live animal (8), observation in shelters, (9) photo trapping | video, (10) predators diet | pellets | pine cones/nuts, (11) scat | track | ditch, (12) telemetry and (13) vocalization | echolocation. The spatial uncertainty of most records ranges between 0 and 100 m (76%). Rodentia (n =31,573) has the highest number of records followed by Chiroptera (n = 18,857), Carnivora (n = 18,594), Lagomorpha (n = 17,496), Cetartiodactyla (n = 11,568) and Eulipotyphla (n = 7008). The data set includes records of species classified by the IUCN as threatened (e.g., Oryctolagus cuniculus [n = 12,159], Monachus monachus [n = 1,512], and Lynx pardinus [n = 197]). We believe that this data set may stimulate the publication of other European countries data sets that would certainly contribute to ecology and conservation-related research, and therefore assisting on the development of more accurate and tailored conservation management strategies for each species. There are no copyright restrictions; please cite this data paper when the data are used in publications

ATLANTIC EPIPHYTES: a data set of vascular and non-vascular epiphyte plants and lichens from the Atlantic Forest

Epiphytes are hyper-diverse and one of the frequently undervalued life forms in plant surveys and biodiversity inventories. Epiphytes of the Atlantic Forest, one of the most endangered ecosystems in the world, have high endemism and radiated recently in the Pliocene. We aimed to (1) compile an extensive Atlantic Forest data set on vascular, non-vascular plants (including hemiepiphytes), and lichen epiphyte species occurrence and abundance; (2) describe the epiphyte distribution in the Atlantic Forest, in order to indicate future sampling efforts. Our work presents the first epiphyte data set with information on abundance and occurrence of epiphyte phorophyte species. All data compiled here come from three main sources provided by the authors: published sources (comprising peer-reviewed articles, books, and theses), unpublished data, and herbarium data. We compiled a data set composed of 2,095 species, from 89,270 holo/hemiepiphyte records, in the Atlantic Forest of Brazil, Argentina, Paraguay, and Uruguay, recorded from 1824 to early 2018. Most of the records were from qualitative data (occurrence only, 88%), well distributed throughout the Atlantic Forest. For quantitative records, the most common sampling method was individual trees (71%), followed by plot sampling (19%), and transect sampling (10%). Angiosperms (81%) were the most frequently registered group, and Bromeliaceae and Orchidaceae were the families with the greatest number of records (27,272 and 21,945, respectively). Ferns and Lycophytes presented fewer records than Angiosperms, and Polypodiaceae were the most recorded family, and more concentrated in the Southern and Southeastern regions. Data on non-vascular plants and lichens were scarce, with a few disjunct records concentrated in the Northeastern region of the Atlantic Forest. For all non-vascular plant records, Lejeuneaceae, a family of liverworts, was the most recorded family. We hope that our effort to organize scattered epiphyte data help advance the knowledge of epiphyte ecology, as well as our understanding of macroecological and biogeographical patterns in the Atlantic Forest. No copyright restrictions are associated with the data set. Please cite this Ecology Data Paper if the data are used in publication and teaching events. © 2019 The Authors. Ecology © 2019 The Ecological Society of Americ

HANDBOOK do Curso Literacia Digital para o Mercado de Trabalho 2018-2020

O presente Relatório reúne um conjunto de informações sobre a 1.a Edição do Curso em Literacia Digital para o Mercado de Trabalho (LD_MT).info:eu-repo/semantics/publishedVersio

Revisão sistematizada da literatura e opinião de peritos

Objective: The 3E (Evidence, Expertise, Exchange) Initiative is a multinational effort of rheumatologists aimed at developing evidence-based recommendations addressing specific questions relevant to clinical practice. The objective of the Portuguese contribution for the 3E Initiative was to develop evidence-based recommendations on how to investigate, follow-up and treat undifferentiated peripheral inflammatory arthritis (UPIA) adapted to local reality and develop additional recommendations considered relevant in the national context. Methods: An international scientific committee from 17 countries selected a set of questions concerning the diagnosis and monitoring of UPIA using a Delphi procedure. Evidence-based answers to each question were sought by a systematic literature search, performed in Medline, Embase, the Cochrane Library and ACR/EULAR 2007-2009 meeting abstracts. Relevant articles were reviewed for quality assessment, data extraction and synthesis. In a national meeting, a panel of 63 Portuguese rheumatologists used the evidence which was gathered to develop recommendations, and filled the gaps in the evidence with their expert opinion. Finally, national recommendations were formulated and agreement among the participants was assessed. Results: A total of 54754 references were identified, of which 267 were systematically reviewed. Thirteen national key recommendations about the investigation, follow-up and treatment of UPIA were formulated. One recommendation addressed differential diagnosis and investigations prior to the established operational diagnosis of UPIA, eight recommendations were related to the diagnostic and prognostic value of clinical and laboratory assessments in established UPIA (history and physical examination, acute phase reactants, serologies, autoantibodies, radiographs, magnetic resonance imaging and ultrasound, genetic markers and synovial biopsy), one recommendation highlighted predictors of persistence (chronicity), one addressed monitoring of clinical disease activity in UPIA, one aimed to find an useful method/score to predict a definitive diagnosis and the last one was related to treatment. Conclusion: Portuguese evidence-based recommendations for the management of UPIA in everyday practice were developed. Their dissemination and implementation in daily clinical practice should help to improve practice uniformity and optimize the management of UPIA patients.publishersversionpublishe

Ciência, Crise e Mudança. 3.º Encontro Nacional de História das Ciências e da Tecnologia. ENHCT2012

III Encontro Nacional de História das Ciências e da Tecnologia. O Centro de Estudos de História e Filosofia da Ciência, organiza o 3.º Encontro Nacional de História da Ciência e da Técnica, sob o tema «Ciência, Crise e Mudança» que tem lugar na Universidade de Évora, nos dias 26, 27 e 28 de Setembro de 2012. O Primeiro Encontro Nacional de História da Ciência teve lugar em 21 e 22 Julho de 2009, no seguimento do programa de estímulo ao de¬senvolvimento da História da Ciência em Portugal e de valorização do património cultural e científico do País, lançado pelo Ministério da Ciência, Tecnologia e Ensino Superior (MCTES) em 31 de Janeiro desse ano. A sua organização coube a investigadores do Instituto de História Contemporânea (IHC), da FCSH da UNL, e do Centro Científico e Cultural de Macau (CCCM), em cujas instalações se realizou. De en¬tre as conclusões do Encontro, destacou-se a de realizar periodicamen¬te novos Encontros Nacionais, a serem organizados de forma rotativa por diferentes centros e núcleos de investigadores. Na sequência deste Primeiro Encontro, o Centro Interuniversitário de História das Ciências e da Tecnologia (CIUHCT) organizou, entre 26 e 28 de Julho de 2010, o II Encontro, dedicado ao tema “Comunicação das Ciências e da Tecnologia em Portugal: Agentes, Meios e Audiências”. Cabe agora ao CEHFCi cumprir o que foi decidido no final deste Encontro. Na situação económica e política que hoje vivemos torna-se particularmente urgente aprofundar o estudo e o debate sobre a interação entre a Sociedade, a Ciência e a sua História. Coordenação Científica e Executiva do encontro estiveram a cargo de dois investigadores CEHFCi: Maria de Fátima Nunes, José Pedro Sousa Dia