SOFHIA: a CAD environment to design digital control systems

"Series Title: IFIP - The International Federation for Information Processing, ISSN 1868-4238"Petri Nets (PNs) prove to be an e cient methodology to model discrete-event systems with parallel activities. The main advantages lie on the graphical interface and on the availability of a set of techniques for formal analysis, including the validation and the test of the modelled system. A proposal to modify the normal PN behaviour is presented, which aims a fast speci cation of synchronous parallel digital systems, including both the data path and the control unit. A CAD environment, SOFHIA, was developed to model digital systems, to validate their properties and to simulate their behaviour. The environment includes the automatic generation of VHDL code to allow simulation and synthesis on existing CAD tools

Urban planning law in Liberia: the case for a transformational approach

This article discusses the need for a fundamental rethinking of urban planning in Liberia with special reference to Monrovia, the capital. Liberia is a post-conflict country and is facing a multitude of problems. One is the very rapid urbanisation of the country. Well over 50% of the population live in urban areas, and over one million people—one third of the population—live in Monrovia, for the most part in informal ‘illegal’ settlements with few facilities. Despite land issues being acknowledged as in need of being tackled as a matter of urgency, little has been done by the Johnson-Sirleaf government since it came to power in 2006. What is needed and what this article argues for is a plan for the development of Monrovia based on the Right to the City with residents given clear rights to land and to participate in the governance of their city. The approach is denominated as a transformational one, taking its inspiration from van der Walt’s approach set out in his Property in the Margins. The need for and the outline of an Urban Transformation Act are set out in the article which concludes with a warning that it cannot be supposed that the residents of Monrovia will continue indefinitely to put up with their very poor living conditions

Etiologic Evaluation and Investigation of Global Development Delay and Intellectual Disability

Developmental Delay (DD) and Intellectual Disability (ID), depending on the affected individual being under or above five years-old, result from environmental or genetic causes during the developmental period, that manifest as a subnormal functioning of intellectual abilities. In western countries there is a prevalence of about 3%, with a great impact in the individuals, their families, as well as in the society. Etiologic diagnosis remains unknown in about 65-80% of the cases. It is a clinically heterogeneous condition as it can be sporadic or familiar, encompassing an autosomal dominant, recessive or X-linked transmission. Etiologic investigation emphasizes the importance of the clinical and family history as well as the physical examination, with special care for dysmorphologic evaluation. The authors reviewed DD/ ID focusing not only on clinical diagnosis but mostly on genetic causes and etiologic investigation. The protocol presented is followed by the Medical Genetics Department of Coimbra’s Paediatrics Hospital, in accordance to the international consensus

Metastatic small bowel occlusion as initial presentation of squamous cell carcinoma of the lung

info:eu-repo/semantics/publishedVersio

Inverse Classification for Comparison-based Interpretability in Machine Learning

In the context of post-hoc interpretability, this paper addresses the task of explaining the prediction of a classifier, considering the case where no information is available, neither on the classifier itself, nor on the processed data (neither the training nor the test data). It proposes an instance-based approach whose principle consists in determining the minimal changes needed to alter a prediction: given a data point whose classification must be explained, the proposed method consists in identifying a close neighbour classified differently, where the closeness definition integrates a sparsity constraint. This principle is implemented using observation generation in the Growing Spheres algorithm. Experimental results on two datasets illustrate the relevance of the proposed approach that can be used to gain knowledge about the classifier.Comment: preprin

Hemangiopericytoma

A propósito de um caso clínico de hemangiopericitoma com localização no membro inferior esquerdo, os autores fazem uma breve revisão desta entidade patológica. Destacam-se as suas principais características clínicas e salienta-se o contributo da arteriografia, no diagnóstico, e tratamento coadjuvante da cirurgia

Evolution in the number of authors of computer science publications

This article analyses the evolution in the number of authors of scientific publications in computer science (CS). This analysis is based on a framework that structures CS into 17 constituent areas, proposed by Wainer et al. (Commun ACM 56(8):67–63, 2013), so that indicators can be calculated for each one in order to make comparisons. We collected and mined over 200,000 article references from 81 conferences and journals in the considered CS areas, spanning a 60-year period (1954–2014). The main insights of this article are that all CS areas witness an increase in the average number of authors, in every decade, with just one slight exception. We ordered the article references by number of authors, in ascending chronological order and grouped them into decades. For each CS area, we provide a perspective of how many groups (1-author papers, 2-author papers and so on) must be considered to reach certain proportions of the total for that CS area, e.g., the 90th and 95th percentiles. Different CS areas require different number of groups to reach those percentiles. For all 17 CS areas, an analysis of the point in time in which publications with n+1 authors overtake the publications with n authors is presented. Finally, we analyse the average number of authors and their rate of increase.This work was supported by FCT - Fundação para a Ciência e Tecnologia within the Project Scope UID/CEC/00319/2013

A machine learning approach for single cell interphase cell cycle staging

The cell nucleus is a tightly regulated organelle and its architectural structure is dynamically orchestrated to maintain normal cell function. Indeed, fluctuations in nuclear size and shape are known to occur during the cell cycle and alterations in nuclear morphology are also hallmarks of many diseases including cancer. Regrettably, automated reliable tools for cell cycle staging at single cell level using in situ images are still limited. It is therefore urgent to establish accurate strategies combining bioimaging with high-content image analysis for a bona fide classification. In this study we developed a supervised machine learning method for interphase cell cycle staging of individual adherent cells using in situ fluorescence images of nuclei stained with DAPI. A Support Vector Machine (SVM) classifier operated over normalized nuclear features using more than 3500 DAPI stained nuclei. Molecular ground truth labels were obtained by automatic image processing using fluorescent ubiquitination-based cell cycle indicator (Fucci) technology. An average F1-Score of 87.7% was achieved with this framework. Furthermore, the method was validated on distinct cell types reaching recall values higher than 89%. Our method is a robust approach to identify cells in G1 or S/G2 at the individual level, with implications in research and clinical applications.This work was supported by FEDER funds through the Operational Programme for Competitiveness Factors (COMPETE 2020), Programa Operacional de Competitividade e Internacionalização (POCI), Programa Opera-cional Regional do Norte (Norte 2020) and by National Funds through the Portuguese Foundation for Science and Technology (FCT), under the projects PTDC/BBB-IMG/0283/2014, PTDC/BTM-SAL/30383/2017, LARSyS-UIDB/50009/2020, LARSyS-UID/EEA/50009/2019, NORTE-01-0145-FEDER-000029 and doctoral grant SFRH/ BD/114687/2016. The authors acknowledge the American Association of Patients with Hereditary Gastric Cancer “No Stomach for Cancer” for funding Seruca’s research and the support of the i3S Scientific Platform Advanced Light Microscopy, member of the PPBI (PPBI-POCI-01-0145-FEDER-022122)

Evolutionary Computation on Road Safety

This study examines the psychological research that focuses on road safety in Smart Cities as proposed by the Vulnerable Road Users (VRUs) sphere. It takes into account qualities such as VRUs’ personal information, their habits, environmental measurements and things data. With the goal of seeing VRUs as active and proactive actors with differentiated feelings and behaviours, we are committed to integrating the social factors that characterize each VRU into our social machinery. As a result, we will focus on the development of a VRU Social Machine to assess VRUs’ behaviour in order to improve road safety. The formal background will be to use Logic Programming to define its architecture based on a Deep Learning approach to Knowledge Representation and Reasoning, complemented with an Evolutionary approach to Computing