Cookies Policy
The website need some cookies and similar means to function. If you permit us, we will use those means to collect data on your visits for aggregated statistics to improve our service. Find out More
Accept Reject
  • Menu
Publications

2020

High-coverage whole-genome analysis of 1220 cancers reveals hundreds of genes deregulated by rearrangement-mediated cis-regulatory alterations

Authors
Zhang, Y; Chen, F; Fonseca, NA; He, Y; Fujita, M; Nakagawa, H; Zhang, Z; Brazma, A; Creighton, CJ;

Publication
Nature Communications

Abstract
The impact of somatic structural variants (SVs) on gene expression in cancer is largely unknown. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole-genome sequencing data and RNA sequencing from a common set of 1220 cancer cases, we report hundreds of genes for which the presence within 100 kb of an SV breakpoint associates with altered expression. For the majority of these genes, expression increases rather than decreases with corresponding breakpoint events. Up-regulated cancer-associated genes impacted by this phenomenon include TERT, MDM2, CDK4, ERBB2, CD274, PDCD1LG2, and IGF2. TERT-associated breakpoints involve ~3% of cases, most frequently in liver biliary, melanoma, sarcoma, stomach, and kidney cancers. SVs associated with up-regulation of PD1 and PDL1 genes involve ~1% of non-amplified cases. For many genes, SVs are significantly associated with increased numbers or greater proximity of enhancer regulatory elements near the gene. DNA methylation near the promoter is often increased with nearby SV breakpoint, which may involve inactivation of repressor elements. © 2020, The Author(s).

2020

Fundão, Portugal: Using STEM Education to Help Build a New ICT Technopolis

Authors
Aguiar, A; Pereira, S;

Publication
STEM in the Technopolis: The Power of STEM Education in Regional Technology Policy

Abstract
In 2015, to reverse a rise in unemployment, a decline in economic growth and the population aging, the Municipality of Fundão designed the Strategic Plan for Innovation. The plan was thought to attract companies and people to Fundão and to encourage families and younger generations already in Fundão to live and work in their home territory. This would be accomplished by attracting investments and new businesses based on new technologies. The strategy had a significant positive impact on the number of jobs created in the city, its economic growth, and attraction of businesses and population. In effect, the municipality started from scratch and built a new ICT industry cluster to transform the economy for a globalized, digital age, addressing needs in the areas of software development, robotics, and technology-based solutions for traditional sectors. The consortium supporting the plan includes governmental organizations, universities, schools, civic associations, businesses, financial institutions, and innovation centers. After four years, Fundão hosts 14 new companies, including four multinationals. Those companies have created over 500 highly qualified jobs. The municipality also has 70 new startups and over 200 privately funded innovative projects. The training of young students on digital technologies, namely on programming, as well as the reskilling of adults, was an essential first step in the plan’s implementation. This success was recognized with an award from the European Community-and it motivated the extension of the initiative into elementary schools, with the goal of covering all students of the municipality. This chapter examines the case within the lens of technopolis development and it includes interview insights from those involved in Fundão’s sustainability plan. © Springer Nature Switzerland AG 2020.

2020

Using a Choquet integral-based approach for incorporating decision-maker's preference judgments in a Data Envelopment Analysis model

Authors
Pereira, MA; Figueira, JR; Marques, RC;

Publication
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH

Abstract
In a world in permanent (r)evolution that revolves around money, seeking new ways to contain costs, better allocate resources, and, overall, improve performance is a constant across all fields. Hence, the use of computational methods based on operational research and statistical science is crucial for achieving an appropriate combination of efficiency and effectiveness, especially in domains where the decision-making process is a complex task. This is where Data Envelopment Analysis (DEA) comes in. However, as a non-parametric and, usually, purely objective technique, DEA makes up for what it lacks in incorporating preference information with flexibility and adaptability, which is particularly important in areas where the decision-makers' judgments are crucial. This work proposes a cutting-edge and original approach to fill in this knowledge gap by linking DEA and multiple criteria decision-making with an additive DEA model that takes into account criteria interactivity, by using an inference methodology to determine their weights, and decision-makers' preference information incorporation, by taking advantage of the Choquet multiple criteria preference aggregation model. Thus, this approach was applied to a case study of performance assessment of Portuguese National Healthcare Service secondary healthcare providers across robustness-testing perspectives, generating credible weights stemmed from the decision-maker's judgments and yielding acceptable and valid results.

2020

Autonomous Driving Car Competition

Authors
Alves, JP; Ferreira, NMF; Valente, A; Soares, S; Filipe, V;

Publication
ROBOTICS IN EDUCATION: CURRENT RESEARCH AND INNOVATIONS

Abstract
This paper presents the construction of an autonomous robot to participating in the autonomous driving competition of the National Festival of Robotics in Portugal, which relies on an open platform requiring basic knowledge of robotics, like mechanics, control, computer vision and energy management. The projet is an excellent way for teaching robotics concepts to engineering students, once the platform endows students with an intuitive learning for current technologies, development and testing of new algorithms in the area of mobile robotics and also in generating good team-building.

2020

Microaneurysm detection in color eye fundus images for diabetic retinopathy screening

Authors
Melo, T; Mendonça, AM; Campilho, A;

Publication
COMPUTERS IN BIOLOGY AND MEDICINE

Abstract
Diabetic retinopathy (DR) is a diabetes complication, which in extreme situations may lead to blindness. Since the first stages are often asymptomatic, regular eye examinations are required for an early diagnosis. As microaneurysms (MAs) are one of the first signs of DR, several automated methods have been proposed for their detection in order to reduce the ophthalmologists' workload. Although local convergence filters (LCFs) have already been applied for feature extraction, their potential as MA enhancement operators was not explored yet. In this work, we propose a sliding band filter for MA enhancement aiming at obtaining a set of initial MA candidates. Then, a combination of the filter responses with color, contrast and shape information is used by an ensemble of classifiers for final candidate classification. Finally, for each eye fundus image, a score is computed from the confidence values assigned to the MAs detected in the image. The performance of the proposed methodology was evaluated in four datasets. At the lesion level, sensitivities of 64% and 81% were achieved for an average of 8 false positives per image (FPIs) in e-ophtha MA and SCREEN-DR, respectively. In the last dataset, an AUC of 0.83 was also obtained for DR detection.

2020

A multi objective approach for DRT service using tabu search

Authors
Torgal, M; Dias, TG; Fontes, T;

Publication
Transportation Research Procedia

Abstract
Urban population is increasing fast. This is creating new challenges to public transport systems since some groups of citizens as elderly people may have sensory, cognitive or motor impairments that need to be addressed. This work explores the potential of a Demand Responsive Transport (DRT) system for people with reduced mobility in an urban environment. For this purpose, the Dial-A-Ride Problem (DARP) was implemented using a multivariable minimisation approach. In this approach, an Assigning Request to Vehicles (ARV) algorithm is used to obtain an initial solution. Then a Multi-Objective Tabu Search Algorithm (MOTSA) is applied to the initial solution to search for the non-dominated solution (optimisation phase). In this optimisation phase, the total travelled distance, the deadheading distance and the number of vehicles were minimised. The performance of the model was computed combining different parameters' values of the number of requests, boarding time for each user, the number of seats in each vehicle, vehicle's speed, the total number of iterations, and candidate threshold number (the algorithm's parameter). The computational results found a strong positive correlation between the number of requests and the: total travelled distance (rs = 0.977, p-value<0.001) and the number of vehicles (rs =0.883, p-value<0.001); and a low positive correlation between the number of requests and the optimised total travelled distance (rs =0.331, p-value<0.001) and the optimised number of vehicles (rs =0.340, p-value<0.001). © 2020 The Authors. Published by ELSEVIER B.V.

  • 1399
  • 4387