Disruption Prediction in Fusion Devices through Feature Extraction and Logistic Regression

This document describes an approach used in the Multi-Machine Disruption Prediction Challenge for Fusion Energy by ITU, a data science competition which ran from September to November 2023, on the online platform Zindi. The competition involved data from three fusion devices - C-Mod, HL-2A, and J-TEXT - with most of the training data coming from the last two, and the test data coming from the first one. Each device has multiple diagnostics and signals, and it turns out that a critical issue in this competition was to identify which signals, and especially which features from those signals, were most relevant to achieve accurate predictions. The approach described here is based on extracting features from signals, and then applying logistic regression on top of those features. Each signal is treated as a separate predictor and, in the end, a combination of such predictors achieved the first place on the leaderboard

Specifying Adaptations through a DSL with an Application to Mobile Robot Navigation

Developing applications for resource-constrained embedded systems is a challenging task specially when applications must adapt to changes in their operating conditions or environment. To ensure an appropriate response at all times, it is highly desirable to develop applications that can dynamically adapt their behavior at run-time. In this paper we introduce an architecture that allows the specification of adaptable behavior through an external, high-level and platform-independent domain-specific language (DSL). The DSL is used here to define adaptation rules that change the run-time behavior of the application depending on various operational factors, such as time constraints. We illustrate the use of the DSL in an application to mobile robot navigation using smartphones, where experimental results highlight the benefits of specifying the adaptable behavior in a flexible and external way to the main application logic

Building a collaboratory in an engineering R&D organization

This paper presents the results achieved throughout the process of preparing the ground to develop a collaboratory in an Engineering R&D organization. This case study is part of a broader research project engaged in building a collaboratory in order to share knowledge and resources among the Portuguese State laboratories. In the process of preparing the ground to develop the collaboratory in the first of the laboratories studied, an information audit was conducted and an online survey was launched. The survey targeted 241 people, including mainly professional researchers, but also research trainees and some technical staff integrating the research teams. The questionnaire was designed so as to collect data on the organization’s information management and information culture, and on the information flows taking place, and their relationship with the objectives of the organization. The questionnaire comprised two distinct and independent parts. The first (on the organization’s information culture and information management) obtained seventy nine responses, while the second (information flows) achieved ninety two, corresponding to 32,8% and 38,2% of the total population, respectively. The work carried out provided the basic requirements for the task of developing a software infrastructure to support the collaboratory, addressing the various aspects of collaborative tools, information archiving, hierarchical tag classification, search, transparent integration of the user local environment with the platform and remote control of scientific instruments

Insuficiencia hepática aguda asociada a enfermedades metabólicas hereditarias en ninos pequenos

INTRODUCTION: Pediatric acute liver failure (ALF) due to inherited metabolic diseases (IMD) is a rare life-threatening condition with a poor prognosis. Early intervention may be lifesaving. OBJECTIVE: To describe clinical presentation, investigation and outcomes of ALF related to IMD in young children. MATERIAL AND METHODS: Retrospective review of the medical records of children aged up to 24 months, admitted to a tertiary pediatric and neonatal Intensive Care Unit during a 27-year period, fulfilling the ALF criteria, with documented metabolic etiology. RESULTS: From 34 ALF cases, 18 were related to IMD: galactosemia (4), mitochondrial DNA depletion syndrome (MDS) (3), ornithine transcarbamilase deficiency (3), congenital defects of glycosylation (2), tyrosinemia type 1 (2), long-chain 3-hydroxyacyl-CoA dehydrogenase deficiency (1), hereditary fructose intolerance (1), classic methylmalonic aciduria (1) and citrulinemia type 1 (1). The median age was 1.3 months. At least one previous suggestive sign/symptom of IMD (vomiting, failure to thrive, hypotonia or developmental delay) was observed in 67% of the cases. The most common physical signs at admission included: hepatomegaly (72%), jaundice (67%) and encephalopathy (44%). The peak laboratorial findings were: mean international normalizad ratio 4.5, median lactate 5mmol/L, mean bilirubin 201μmol/L, median alanine aminotransferase (ALT) 137 UI/L and median ammonia 177μmol/L. One patient was submitted to liver transplant in ALF context (MSD). The mortality rate was 44%. DISCUSSION: The identification of IMD as a frequent cause of ALF allowed specific therapeutic measures and adequate family counselling. Particular clinical features and moderated ALT and bilirubin levels can lead to its suspicion.info:eu-repo/semantics/publishedVersio