DisBot: a portuguese disaster support dynamic knowledge chatbot

This paper presents DisBot, the first Portuguese speaking chatbot that uses social media retrieved knowledge to support citizens and first-responders in disaster scenarios, in order to improve community resilience and decision-making. It was developed and tested using Design Science Research Methodology (DSRM), being progressively matured with field specialists through several design and development iterations. DisBot uses a state-of-the-art Dual Intent Entity Transformer (DIET) architecture to classify user intents, and makes use of several dialogue policies for managing user conversations, as well as storing relevant information to be used in further dialogue turns. To generate responses, it uses real-world safety knowledge, and infers a dynamic knowledge graph that is dynamically updated in real-time by a disaster-related knowledge extraction tool, presented in previous works. Through its development iterations, DisBot has been validated by field specialists, who have considered it to be a valuable asset in disaster management.info:eu-repo/semantics/publishedVersio

DisKnow: a social-driven disaster support knowledge extraction system

This research is aimed at creating and presenting DisKnow, a data extraction system with the capability of filtering and abstracting tweets, to improve community resilience and decision-making in disaster scenarios. Nowadays most people act as human sensors, exposing detailed information regarding occurring disasters, in social media. Through a pipeline of natural language processing (NLP) tools for text processing, convolutional neural networks (CNNs) for classifying and extracting disasters, and knowledge graphs (KG) for presenting connected insights, it is possible to generate real-time visual information about such disasters and affected stakeholders, to better the crisis management process, by disseminating such information to both relevant authorities and population alike. DisKnow has proved to be on par with the state-of-the-art Disaster Extraction systems, and it contributes with a way to easily manage and present such happenings.info:eu-repo/semantics/publishedVersio

Clinical and anatomopathological features of eosinophilic oesophagitis in children and adults

Introduction: Eosinophilic oesophagitis (EoE) is a chronic clinical-pathological disorder with an immunological basis characterised by symptoms of oesophageal dysfunction and, histologically, eosinophilic inflammation. Objective: To evaluate the clinical characteristics and differences in children and adults diagnosed with EoE in a tertiary level hospital. Method: Descriptive, retrospective and cross-sectional study. We randomly selected 40 children and 40 adults diagnosed with EoE between 2009 and 2016. The patient characteristics were analysed by means of epidemiological, clinical, diagnostic and therapeutic variables. Results: The average age at diagnosis was 10 years (children) and 34 years (adults), with a higher frequency in males. The majority were sensitised to aeroallergens (77.5% children vs. 82.5% adults) and foods (75% children vs. 82.5% adults). Statistically significant differences were detected in sensitisation to fruits (p = 0.007) and grains (p < 0.001). Differences were observed in impaction (22.5% children vs. 82.5% adults), dysphagia (42.5% children vs. 77.5% adults) and abdominal pain (25% children vs. 7.5% adults). Endoscopy showed that children had a higher frequency of exudates (92.5%) and adults, trachealisation (50% vs. 5%) and stenosis (17.5% vs. 2.5%). Statistically significant differences were found in treatment with topical corticosteroids (30% children vs. 77.5% adults), with a variable positive response. 77.5% of the patients received elimination diets. Conclusions: Statistically significant differences were observed between the paediatric and adult populations in the food sensitisation profiles, clinical manifestations, endoscopic findings and treatments received. This is a complex pathology that calls for a multidisciplinary team and would require new non-invasive techniques to facilitate its management

Digital twins para sustentabilidade e gestão de acidentes

Os modelos BIM são maioritariamente gerados e usados no contexto do projeto e construção. Contudo, a informação que contêm é cada vez mais utilizada na gestão dos edifícios e cidade. Este trabalho descreve o desenvolvimento de ferramentas baseadas em modelos BIM que são enquadradas no conceito de Smart City. Estas aplicações contêm informação geométrica e funcional da construção e trocam dados com outras fontes tal como sensores ambientais, de consumo de energia ou água ou com os responsáveis técnicos e utilizadores, tornando-se em Gémeos Digitais/Digital Twins. São apresentadas duas aplicações onde são usados modelos BIM de pequena e grande escala como suporte de visualização e interação com os utilizadores. Em ambas são feitas integrações de informação de várias origens que são integradas numa plataforma agregadora. Nestas aplicações o modelo BIM é uma das peças do sistema que compreende sensores, bases de dados, algoritmos de filtragem e tratamento de dados, sendo por isso necessário recorrer a técnicas de extração, compatibilização de informação de várias fontes e apresentação ao utilizador em suportes acessíveis, o que aponta caminhos para a utilização do BIM em novos cenários.info:eu-repo/semantics/publishedVersio

Orquiectomía en canino criptorquido unilateral

El presente trabajo corresponde a un caso quirúrgico de un paciente canino de 5 años de edad, que presentaba criptorquidismo. Se decidió la resolución quirúrgica, con el objetivo de evitar posibles complicaciones futuras. El procedimiento se realizó con éxito y el paciente se recuperó perfectamente. En pacientes criptórquidos, se recomienda realizar la esterilización a temprana edad

Allergic proctocolitis refractory to maternal hypoallergenic diet in exclusively breast-fed infants: a clinical observation

<p>Abstract</p> <p>Background</p> <p>Allergic proctocolitis (APC) in exclusively breast-fed infants is caused by food proteins, deriving from maternal diet, transferred through lactation. In most cases a maternal cow milk-free diet leads to a prompt resolution of rectal bleeding, while in some patients a multiple food allergy can occur. The aim of this study was to assess whether the atopy patch test (APT) could be helpful to identify this subgroup of patients requiring to discontinue breast-feeding due to polisensitization. Additionally, we assessed the efficacy of an amino acid-based formula (AAF) when multiple food allergy is suspected. amino acid-based formula</p> <p>Methods</p> <p>We have prospectively enrolled 14 exclusively breast-fed infants with APC refractory to maternal allergen avoidance. The diagnosis was confirmed by endoscopy with biopsies. Skin prick tests and serum specific IgE for common foods, together with APTs for common foods plus breast milk, were performed. After a 1 month therapy of an AAF all patients underwent a follow-up rectosigmoidoscopy.</p> <p>Results</p> <p>Prick tests and serum specific IgE were negative. APTs were positive in 100% infants, with a multiple positivity in 50%. Sensitization was found for breast milk in 100%, cow's milk (50%), soy (28%), egg (21%), rice (14%), wheat (7%). Follow-up rectosigmoidoscopy confirmed the remission of APC in all infants.</p> <p>Conclusions</p> <p>These data suggest that APT might become a useful tool to identify subgroups of infants with multiple gastrointestinal food allergy involving a delayed immunogenic mechanism, with the aim to avoid unnecessary maternal dietary restrictions before discontinuing breast-feeding.</p

Named Entity Recognition for Sensitive Data Discovery in Portuguese

The process of protecting sensitive data is continually growing and becoming increasingly important, especially as a result of the directives and laws imposed by the European Union. The effort to create automatic systems is continuous, but, in most cases, the processes behind them are still manual or semi-automatic. In this work, we have developed a component that can extract and classify sensitive data, from unstructured text information in European Portuguese. The objective was to create a system that allows organizations to understand their data and comply with legal and security purposes. We studied a hybrid approach to the problem of Named Entity Recognition for the Portuguese language. This approach combines several techniques such as rule-based/lexical-based models, machine learning algorithms, and neural networks. The rule-based and lexical-based approaches were used only for a set of specific classes. For the remaining classes of entities, two statistical models were tested&mdash;Conditional Random Fields and Random Forest and, finally, a Bidirectional-LSTM approach as experimented. Regarding the statistical models, we realized that Conditional Random Fields is the one that can obtain the best results, with a f1-score of 65.50%. With the Bi-LSTM approach, we have achieved a result of 83.01%. The corpora used for training and testing were HAREM Golden Collection, SIGARRA News Corpus, and DataSense NER Corpus

The High-contrast End-to-End Performance Simulator (HEEPS): influence of ELT/METIS instrumental effects

Instrumentatio