Search results for "INSPIRE"
showing 10 items of 52 documents
Mechanical ventilation parameters in critically ill COVID-19 patients: a scoping review
2021
Abstract Background The mortality of critically ill patients with COVID-19 is high, particularly among those receiving mechanical ventilation (MV). Despite the high number of patients treated worldwide, data on respiratory mechanics are currently scarce and the optimal setting of MV remains to be defined. This scoping review aims to provide an overview of available data about respiratory mechanics, gas exchange and MV settings in patients admitted to intensive care units (ICUs) for COVID-19-associated acute respiratory failure, and to identify knowledge gaps. Main text PubMed, EMBASE, and MEDLINE databases were searched from inception to October 30, 2020 for studies providing at least one v…
Hyperoxemia and excess oxygen use in early acute respiratory distress syndrome: Insights from the LUNG SAFE study
2020
Abstract Background Concerns exist regarding the prevalence and impact of unnecessary oxygen use in patients with acute respiratory distress syndrome (ARDS). We examined this issue in patients with ARDS enrolled in the Large observational study to UNderstand the Global impact of Severe Acute respiratory FailurE (LUNG SAFE) study. Methods In this secondary analysis of the LUNG SAFE study, we wished to determine the prevalence and the outcomes associated with hyperoxemia on day 1, sustained hyperoxemia, and excessive oxygen use in patients with early ARDS. Patients who fulfilled criteria of ARDS on day 1 and day 2 of acute hypoxemic respiratory failure were categorized based on the presence o…
A Survey on Nature-Inspired Medical Image Analysis: A Step Further in Biomedical Data Integration
2019
Natural phenomena and mechanisms have always intrigued humans, inspiring the design of effective solutions for real-world problems. Indeed, fascinating processes occur in nature, giving rise to an ever-increasing scientific interest. In everyday life, the amount of heterogeneous biomedical data is increasing more and more thanks to the advances in image acquisition modalities and high-throughput technologies. The automated analysis of these large-scale datasets creates new compelling challenges for data-driven and model-based computational methods. The application of intelligent algorithms, which mimic natural phenomena, is emerging as an effective paradigm for tackling complex problems, by…
A spiking network for body size learning inspired by the fruit fly
2013
The concept of peripersonal space is an interesting research topics for psychologists, neurobiologists and for robotic applications. A living being can learn the representation of its own body to take the correct behavioral decision when interacting with the world. To transfer these important learning mechanisms on bio-robots, simple and efficient solutions can be found in the insect world. In this paper a neural-based model for body-size learning is proposed taking into account the results obtained in experiments with fruit flies. Simulations and experimental results on a roving platform are reported and compared with the biological counterpart.
Bio-inspired security analysis for IoT scenarios
2020
Computer security has recently become more and more important as the world economy dependency from data has kept growing. The complexity of the systems that need to be kept secure calls for new models capable of abstracting the interdependencies among heterogeneous components that cooperate at providing the desired service. A promising approach is attack graph analysis, however, the manual analysis of attack graphs is tedious and error prone. In this paper we propose to apply the metabolic network model to attack graph analysis, using three interacting bio-inspired algorithms: topological analysis, flux balance analysis, and extreme pathway analysis. A developed framework for graph building…
A bio-inspired approach to attack graphs analysis
2018
Computer security has recently become more and more important as the world economy dependency from data has kept growing. The complexity of the systems that need to be kept secure calls for new models capable of abstracting the interdependencies among heterogeneous components that cooperate at providing the desired service. A promising approach is attack graph analysis, however the manual analysis of attack graphs is tedious and error prone. In this paper we propose to apply the metabolic network model to attack graphs analysis, using three interacting bio-inspired algorithms: topological analysis, flux balance analysis, and extreme pathway analysis. A developed framework for graph building…
CADASTRAL MODELS IN EU MEMBER STATES
2019
Abstract Cadastres are always related to land: they are a creation of man as effect of his relationship with land. The different conditions of the Cadastre in 14 EU Member States, including the former EU Candidate States (that nowadays are also EU members), are shown in this paper. Half of EU countries store cadastral and registration data in the same database. Basically two original models of cadastral system exist in the EU, related with systems of land registration : 1) in the Central European model (beyond the area of the Germanic “Grundbuch”) Cadastre emerges as a graphic basis (map) of land registration (Land Registry), so that physical changes must be reflected in the Cadastre and le…
A facile way to build up branched high functional polyaminoacids with tunable physicochemical and biological properties
2016
Abstract Here, for the first time, branched polyaminoacids bearing α-amino acids as side functions, namely PAA-co-AA and PGA-co-AA, are prepared by heterophase ring opening of polysuccinimide (PSI) with l -arginine or glycine in aqueous environment and at controlled pH. The modulation of the pH of the reaction leads to high-molecular-weight copolymers with tunable functionalization and, as consequence, with tailor-made physicochemical properties. Furthermore, a branched polyaminoacid carrying a preformed bioactive peptide ( l -trileucine) and l -arginine as side pendants, named PATA-co-AA, was synthesized via a similar pathway thus leading to complex biomimetic materials potentially exploit…
How to engineer biologically inspired cognitive architectures
2013
Biologically inspired cognitive architectures are complex systems where different modules of cognition interact in order to reach the global goals of the system in a changing environment. Engineering and modeling this kind of systems is a hard task due to the lack of techniques for developing and implementing features like learning, knowledge, experience, memory, adaptivity in an inter-modular fashion. We propose a new concept of intelligent agent as abstraction for developing biologically cognitive architectures. © 2013 Springer-Verlag.
[Editorial] Special issue on computational intelligence and nature-inspired algorithms for real-world data analytics and pattern recognition
2018
Cagnoni, S., & Castelli, M. (2018). [Editorial]. Special issue on computational intelligence and nature-inspired algorithms for real-world data analytics and pattern recognition. Algorithms, 11(3), 1-2. DOI: 10.3390/a11030025 This special issue of Algorithms is devoted to the study of Computational Intelligence and Nature-Inspired Algorithms for Real-World Data Analytics and Pattern Recognition. The special issue considered both theoretical contributions able to advance the state-of-the-art in this field and practical applications that describe novel approaches for solving real-world problems. published