Pontifícia Universidade Católica do Paraná

About: Pontifícia Universidade Católica do Paraná is a education organization based out in Curitiba, Brazil. It is known for research contribution in the topics: Population & Context (language use). The organization has 6491 authors who have published 9206 publications receiving 104051 citations.

Past, present and future of Industry 4.0 - a systematic literature review and research agenda proposal

Abstract: Over the last few years, the fourth industrial revolution has attracted more and more attentions all around the world. In the current literature, there is still a lack of efforts to systematically review the state of the art of this new industrial revolution wave. The aim of this study is to address this gap by investigating the academic progresses in Industry 4.0. A systematic literature review was carried out to analyse the academic articles within the Industry 4.0 topic that were published online until the end of June 2016. In this paper, the obtained results from both the general data analysis of included papers (e.g. relevant journals, their subject areas and categories, conferences, keywords) and the specific data analysis corresponding to four research sub-questions are illustrated and discussed. These results not only summarise the current research activities (e.g. main research directions, applied standards, employed software and hardware), but also indicate existing deficiencies and potential re...

Multi-objective grey wolf optimizer

Abstract: Due to the novelty of the Grey Wolf Optimizer (GWO), there is no study in the literature to design a multi-objective version of this algorithm. This paper proposes a Multi-Objective Grey Wolf Optimizer (MOGWO) in order to optimize problems with multiple objectives for the first time. A fixed-sized external archive is integrated to the GWO for saving and retrieving the Pareto optimal solutions. This archive is then employed to define the social hierarchy and simulate the hunting behavior of grey wolves in multi-objective search spaces. The proposed method is tested on 10 multi-objective benchmark problems and compared with two well-known meta-heuristics: Multi-Objective Evolutionary Algorithm Based on Decomposition (MOEA/D) and Multi-Objective Particle Swarm Optimization (MOPSO). The qualitative and quantitative results show that the proposed algorithm is able to provide very competitive results and outperforms other algorithms. Note that the source codes of MOGWO are publicly available at http://www.alimirjalili.com/GWO.html. A novel multi-objective algorithm called Multi-objective Grey Wolf Optimizer is proposed.MOGWO is benchmarked on 10 challenging multi-objective test problems.The quantitative results show the superior convergence and coverage of MOGWO.The coverage ability of MOGWO is confirmed by the qualitative results as well.

The genome sequence of the plant pathogen Xylella fastidiosa

Abstract: Instituto Ludwig de Pesquisa sobre o Câncer, Rua Prof. Antonio Prudente, 109-4 andar, 01509-010, Sao Paulo-SP

A novel classification system for spinal instability in neoplastic disease: an evidence-based approach and expert consensus from the Spine Oncology Study Group.

Abstract: Study design Systematic review and modified Delphi technique. Objective To use an evidence-based medicine process using the best available literature and expert opinion consensus to develop a comprehensive classification system to diagnose neoplastic spinal instability. Summary of background data Spinal instability is poorly defined in the literature and presently there is a lack of guidelines available to aid in defining the degree of spinal instability in the setting of neoplastic spinal disease. The concept of spinal instability remains important in the clinical decision-making process for patients with spine tumors. Methods We have integrated the evidence provided by systematic reviews through a modified Delphi technique to generate a consensus of best evidence and expert opinion to develop a classification system to define neoplastic spinal instability. Results A comprehensive classification system based on patient symptoms and radiographic criteria of the spine was developed to aid in predicting spine stability of neoplastic lesions. The classification system includes global spinal location of the tumor, type and presence of pain, bone lesion quality, spinal alignment, extent of vertebral body collapse, and posterolateral spinal element involvement. Qualitative scores were assigned based on relative importance of particular factors gleaned from the literature and refined by expert consensus. Conclusion The Spine Instability Neoplastic Score is a comprehensive classification system with content validity that can guide clinicians in identifying when patients with neoplastic disease of the spine may benefit from surgical consultation. It can also aid surgeons in assessing the key components of spinal instability due to neoplasia and may become a prognostic tool for surgical decision-making when put in context with other key elements such as neurologic symptoms, extent of disease, prognosis, patient health factors, oncologic subtype, and radiosensitivity of the tumor.