ITUR 2 – dimensionamento das redes de cabos coaxiais

No último século, o sector das comunicações passou de um estado inicial de simples curiosidade tecnológica até um dos mais dinâmicos pilares económicos de vários países por todo o mundo. A procura por mais e melhores serviços de televisão e internet levaram à necessidade de evoluir as tecnologias existentes de modo a conseguir cumprir com a elevada procura ao mesmo tempo que apresentam um serviço mais rápido, mais fiável e de melhor qualidade. A União Europeia (EU) colocou como objetivo a conversão de todo o seu território de radiodifusão analógica para a tecnologia digital. Deste modo, não só se conseguiu uma mais eficiente utilização do espetro radioelétrico, como se conseguiu aumentar o número de canais a transmitir, sendo estes de melhor qualidade que a tecnologia analógica, pois deu a possibilidade de várias emissoras poderem emitir em High Definition (HD)

Construção de websites com ferramentas open-source: duas experiências de implementação em bibliotecas de ensino superior

As Tecnologias da Informação e da Comunicação (TIC) têm influenciado de forma inequívoca o desenvolvimento das bibliotecas à escala global. Nas últimas décadas, as TIC mudaram a dinâmica das bibliotecas permitindo a sua modernização (pelo desenvolvimento da eficiência das tarefas já realizadas), favorecendo a inovação (pela utilização das tecnologias como base para o desenvolvimento de novos serviços/técnicas) e promovendo a sua transformação (ao nível do paradigma funcional, da disponibilização de conteúdos, etc.) – criando, em suma, uma nova relação com os seus público

A General Hybrid Modeling Framework for Systems Biology Applications: Combining Mechanistic Knowledge with Deep Neural Networks under the SBML Standard

This work was supported by the Associate Laboratory for Green Chemistry—LAQV which is financed by national funds from FCT/MCTES (UIDB/50006/2020 and UIDP/50006/2020). This work has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement number 870292 (BioICEP project). J.P. acknowledges a PhD grant (SFRD/BD14610472019), Fundação para a Ciência e Tecnologia (FCT) and R.S.C. the contract CEECIND/01399/2017In this paper, a computational framework is proposed that merges mechanistic modeling with deep neural networks obeying the Systems Biology Markup Language (SBML) standard. Over the last 20 years, the systems biology community has developed a large number of mechanistic models that are currently stored in public databases in SBML. With the proposed framework, existing SBML models may be redesigned into hybrid systems through the incorporation of deep neural networks into the model core, using a freely available python tool. The so-formed hybrid mechanistic/neural network models are trained with a deep learning algorithm based on the adaptive moment estimation method (ADAM), stochastic regularization and semidirect sensitivity equations. The trained hybrid models are encoded in SBML and uploaded in model databases, where they may be further analyzed as regular SBML models. This approach is illustrated with three well-known case studies: the Escherichia coli threonine synthesis model, the P58IPK signal transduction model, and the Yeast glycolytic oscillations model. The proposed framework is expected to greatly facilitate the widespread use of hybrid modeling techniques for systems biology applications.publishersversionpublishe

Introdução à Análise de Movimento usando Visão Computacional

Pretende-se com este trabalho fazer uma introdução ao que tem vindo a ser realizado no domínio do seguimento e análise de movimento recorrendo a visão computacional.Assim no primeiro capítulo deste relatório faremos referência aos vários tipos de movimento e analisaremos as fases que compõem um sistema comum de captura e análise de movimento, descrevendo sucintamente alguns trabalhos realizados nesta área.Seguidamente, no segundo capítulo, faremos uma apresentação mais detalhada da área do seguimento e análise de movimento humano de corpo inteiro; nomeadamente, no reconhecimento da pose e do reconhecimento do andar e de gestos.Finalmente, no terceiro e último capítulo, daremos ênfase à análise de imagem médica e exemplificaremos, sumariamente, algumas das suas aplicações.With this work we intend to introduce what has been done in the domain of tracking and motion analysis by using computational vision.Therefore in the first chapter of this report we will refer the various types of motion, and analyse the steps that compose a general system of movement capture and analysis, by succinctly describing some works done in this field.Then, in the second chapter we will do a more detailed study about the area of human entire body tracking and motion analysis; namely, in pose recognition and in the recognition of gait and gestures.Finally, in the third and last chapter, emphasis will be given to the medical images analysis and we will summarily exemplify some of its applications

Advances and Future Perspectives

Agharafeie , R., Ramos, J. R. C., Mendes, J. M., & Oliveira, R. M. F. (2023). From Shallow to Deep Bioprocess Hybrid Modeling: Advances and Future Perspectives. Fermentation, 9(10), 1-22. [922]. https://doi.org/10.20944/preprints202310.0107.v1, https://doi.org/10.3390/fermentation9100922--- This work was supported by the Associate Laboratory for Green Chemistry - LAQV which is financed by national funds from FCT/MCTES (UIDB/50006/2020 and UIDP/50006/2020). This work received funding from the European Union’s Horizon 2020 research and innovation program under the grant agreement no. 101099487- BioLaMer-HORIZON-EIC-2022-PATHFINDEROPEN-01 (BioLaMer)Deep learning is emerging in many industrial sectors in hand with big data analytics to streamline production. In the biomanufacturing sector, big data infrastructure is lagging comparatively to other industries. A promising approach is to combine Deep Neural Networks (DNN) with prior knowledge in Hybrid Neural Network (HNN) workflows that are less dependent on the quality and quantity of data. This paper reviews published articles over the past 30 years on the topic of HNN applications to bioprocesses. It revealed that HNNs were applied to various bioprocesses, including microbial cultures, animal cells cultures, mixed microbial cultures, and enzyme biocatalysis. HNNs were mainly applied for process analysis, process monitoring, development of software sensors, open- and closed-loop control, batch-to-batch control, model predictive control, intensified design of experiments, quality-by-design, and recently for the development of digital twins. Most previous HNN studies combined shallow Feedforward Neural Networks (FFNNs) with physical laws, such as macroscopic material balance equations, following the semiparametric design principle. Only recently, deep HNNs based on deep FFNNs, Convolution Neural Networks (CNN), Long Short-Term Memory (LSTM) networks and Physics Informed Neural Networks (PINNs) have been reported. The biopharma sector is currently a major driver but applications to biologics quality attributes, new modalities, and downstream processing are significant research gaps.publishersversionpublishe

Fatty acids composition in yellow-legged (Larus michahellis) and lesser black-backed (Larus fuscus) gulls from natural and urban habitats in relation to the ingestion of anthropogenic materials

Research Areas: Environmental Sciences & EcologyUrban habitats offer spatially and temporally predictable anthropogenic food sources for opportunistic species, such as several species of gulls that are known to exploit urban areas and take advantage of accessible and diverse food sources, reducing foraging time and energy expenditure. However, human-derived food may have a poorer nutritional quality than the typical natural food resources and foraging in urban habitats may increase birds' susceptibility of ingesting anthropogenic debris materials, with unknown physiological consequences for urban dwellers. Here we compare the fatty acids (FA) composition of two opportunistic gull species (the yellow-legged gull, Larus michahellis, and the lesser black-backed gull, Larus fuscus) from areas with different levels of urbanization, to assess differences in birds' diet quality among foraging habitats, and we investigate the effects of ingesting anthropogenic materials, a toxicological stressor, on gulls' FA composition. Using GC–MS, 23 FAs were identified in the adipose tissue of both gull species. Significant differences in gulls' FA composition were detected among the three urbanization levels, mainly due to physiologically important highly unsaturated FAs that had lower percentages in gulls from the most urbanized habitats, consistent with a diet based on anthropogenic food resources. The deficiency in omega (ω)-3 FAs and the higher ω-6:ω-3 FAs ratio in gulls from the most urbanized location may indicate a dietinduced susceptibility to inflammation. No significant differences in overall FA composition were detected between gull species.While we were unable to detect any effect of ingested anthropogenic materials on gulls' FA composition, these data constitute a valuable contribution to the limited FA literature in gulls.We encourage studies to explore the long-term physiological effects of the lower nutritional quality diet for urban dwellers, and to detect the sub-lethal impacts of the ingestion of anthropogenic materialsinfo:eu-repo/semantics/publishedVersio

Filtro de Kalman no Seguimento de Movimento em Visão Computacional

Este relatório aborda o problema de seguimento de entidades representadas em sequências de imagens usando Visão Computacional. Para tal utiliza-se um método estocástico, o filtro de Kalman, aliado a um método de optimização global, no sentido de obter os melhores conjuntos de correspondências, e portanto garantir a optimização global do seguimento. Nesta metodologia também se inclui um modelo de gestão de entidades seguidas que possibilita avaliar em cada instante se se deve continuar o seguimento de cada entidade considerado no modelo. Deste modo, a abordagem proposta permite lidar com casos de oclusão temporária, desaparecimento definitivo, aparecimento ou reaparecimento de entidades, mantendo um número controlado de entidades seguidas em cada instante, o que reduz o custo computacional associado ao estritamente necessário.A metodologia proposta é neste trabalho testada e validada em exemplos de seguimento de entidades representadas em imagens sintéticas e reais.This report contemplates feature tracking on image sequences using Computer Vision. To do so a stochastic method is used, the Kalman filter, allied to a global optimization method to obtain the best set of correspondences, and so to guarantee the global optimization of the tracking results. A management model is also included in this methodology to evaluate if each feature's tracking should be continued or not. By doing so, the proposed approach deals with temporary occlusion, permanent disappearance, appearance or reappearance of features, maintaining a controlled number of tracked features in each time instant, which reduces the computer cost to what is strictly necessary.The proposed methodology is here tested and validated with feature's tracking along synthetic and real image sequences

Análise de movimento humano por visão computacional: uma síntese

O movimento humano é complexo, não linear e varia com o tempo. Nos últimos tempos, inúmeros investigadores têm-se dedicado ao desenvolvimento de sistemas automáticos capazes de realizar o seguimento, a análise e o reconhecimento deste tipo de movimento, utilizando técnicas de Visão Computacional. Neste artigo, serão resumidamente enumeradas e descritas algumas das técnicas actualmente empregues neste domínio

A new cyanobacterial species with a protective effect on lettuce grown under salinity stress: envisaging sustainable agriculture practices

In this work, a new terrestrial cyanobacterial species, Oculatella lusitanica LEGE 161147, was isolated and characterized using a polyphasic approach. Morphologically, O. lusitanica shares characteristics with different Oculatella species (mainly with O. crustae-formantes), lacking distinctive features. However, the phylogeny based on the 16S rRNA gene sequence and the 16S-23S ITS secondary structures support the establishment of this isolate as a new species. O. lusitanica is placed within a clade mainly composed by other Oculatella terrestrial strains; however, it forms a separate lineage. In addition, our species differs from the other Oculatella described so far by lacking the V2 helix within the ITS region. Since cyanobacteria are known to release compounds that promote plant growth and/or increase their tolerance to stresses, the effect of this newly described cyanobacterial species on Lactuca sativa (lettuce) plants development and salinity stress resistance was evaluated. Our results showed that, although the cyanobacterium had no impact on plant growth under the conditions tested, it was able to mitigate the deleterious salinity stress effects on plant size, root and aerial part fresh weight, by eliciting the non-enzymatic antioxidant response system (proline, H2O2 and reduced glutathione). In addition, the microorganism was able to induce a priming effect on lettuce plants by stimulating defensive mechanisms under non-stress conditions, and enhances the activity of nitrogen metabolism-related enzymes glutamate dehydrogenase, glutamine synthetase and nitrate reductase. These results indicate that this native terrestrial cyanobacterial species could be employed as a tool in sustainable agricultural practices.This work was funded by National Funds through FCT—Fundação para a Ciência e a Tecnologia, I.P., under the projects PCIF/RPG/0077/2017, UIDB/04293/2020, UIDP/04293/2020, UIDB/05748/2020 and UIDP/05748/2020. This work was also funded by the FCT grant SFRH/BPD/115571/2016 (to AB) and LTAUSA 18008 (to JK)info:eu-repo/semantics/publishedVersio

Patient-physician discordance in assessment of adherence to inhaled controller medication: a cross-sectional analysis of two cohorts

We aimed to compare patient's and physician's ratings of inhaled medication adherence and to identify predictors of patient-physician discordance.(SFRH/BPD/115169/2016) funded by Fundação para a Ciência e Tecnologia (FCT); ERDF (European Regional Development Fund) through the operations: POCI-01-0145-FEDER-029130 ('mINSPIRERS—mHealth to measure and improve adherence to medication in chronic obstructive respiratory diseases—generalisation and evaluation of gamification, peer support and advanced image processing technologies') cofunded by the COMPETE2020 (Programa Operacional Competitividade e Internacionalização), Portugal 2020 and by Portuguese Funds through FCT (Fundação para a Ciência e a Tecnologia).info:eu-repo/semantics/publishedVersio