Existence of global attractor for a nonautonomous state-dependent delay differential equation of neuronal type

The analysis of the long-term behavior of the mathematical model of a neural network constitutes a suitable framework to develop new tools for the dynamical description of nonautonomous state-dependent delay equations (SDDEs). The concept of global attractor is given, and some results which establish properties ensuring its existence and providing a description of its shape, are proved. Conditions for the exponential stability of the global attractor are also studied. Some properties of comparison of solutions constitute a key in the proof of the main results, introducing methods of monotonicity in the dynamical analysis of nonautonomous SDDEs. Numerical simulations of some illustrative models show the applicability of the theory.Ministerio de Economía y Competitividad / FEDER, MTM2015-66330-PMinisterio de Ciencia, Innovación y Universidades, RTI2018-096523-B-I00European Commission, H2020-MSCA-ITN-201

Exponential dichotomy on the real line: SVD and QR methods

In this work we show when and how techniques based on the singular value decomposition (SVD) and the QR decomposition of a fundamental matrix solution can be used to infer if a system enjoys—or not—exponential dichotomy on the whole real line

Some Remarks on Numerical Methods for Second Order Differential Equations on the Orthogonal Matrix Group

n/

Role of nutraceuticals in cancer therapy.

Nutraceuticals are natural bioactive products with food value and promising therapeutic properties in several diseases. Current cancer treatments, such as chemotherapy, radiotherapy and surgery, induce unintended side effects compromising also health and well-being of patients. Emerging studies suggest that some plant-based agents may impact cellular and molecular processes underlying tumor progression. However, some of these molecules might also play an antagonistic activity against classic therapeutic agents. The aim of this article is to review the current knowledge underpinning the use of nutraceuticals in cancer prevention and therapy.</p

Quantum Cascade Laser-Based Photoacoustic Sensor for Trace Detection of Formaldehyde Gas

We report on the development of a photoacoustic sensor for the detection of formaldehyde (CH2O) using a thermoelectrically cooled distributed-feedback quantum cascade laser operating in pulsed mode at 5.6 μm. A resonant photoacoustic cell, equipped with four electret microphones, is excited in its first longitudinal mode at 1,380 Hz. The absorption line at 1,778.9 cm−1 is selected for CH2O detection. A detection limit of 150 parts per billion in volume in nitrogen is achieved using a 10 seconds time constant and 4 mW laser power. Measurements in ambient air will require water vapour filters

Single-agent rituximab is an effective salvage therapy in pretreated patients with hairy cell leukemia

No abstract availabl

Photoacoustic Techniques for Trace Gas Sensing Based on Semiconductor Laser Sources

The paper provides an overview on the use of photoacoustic sensors based on semiconductor laser sources for the detection of trace gases. We review the results obtained using standard, differential and quartz enhanced photoacoustic techniques

An Integrated Big and Fast Data Analytics Platform for Smart Urban Transportation Management

(c) 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.[EN] Smart urban transportation management can be considered as a multifaceted big data challenge. It strongly relies on the information collected into multiple, widespread, and heterogeneous data sources as well as on the ability to extract actionable insights from them. Besides data, full stack (from platform to services and applications) Information and Communications Technology (ICT) solutions need to be specifically adopted to address smart cities challenges. Smart urban transportation management is one of the key use cases addressed in the context of the EUBra-BIGSEA (Europe-Brazil Collaboration of Big Data Scientific Research through Cloud-Centric Applications) project. This paper specifically focuses on the City Administration Dashboard, a public transport analytics application that has been developed on top of the EUBra-BIGSEA platform and used by the Municipality stakeholders of Curitiba, Brazil, to tackle urban traffic data analysis and planning challenges. The solution proposed in this paper joins together a scalable big and fast data analytics platform, a flexible and dynamic cloud infrastructure, data quality and entity matching algorithms as well as security and privacy techniques. By exploiting an interoperable programming framework based on Python Application Programming Interface (API), it allows an easy, rapid and transparent development of smart cities applications.This work was supported by the European Commission through the Cooperation Programme under EUBra-BIGSEA Horizon 2020 Grant [Este projeto e resultante da 3a Chamada Coordenada BR-UE em Tecnologias da Informacao e Comunicacao (TIC), anunciada pelo Ministerio de Ciencia, Tecnologia e Inovacao (MCTI)] under Grant 690116.Fiore, S.; Elia, D.; Pires, CE.; Mestre, DG.; Cappiello, C.; Vitali, M.; Andrade, N.... (2019). An Integrated Big and Fast Data Analytics Platform for Smart Urban Transportation Management. IEEE Access. 7:117652-117677. https://doi.org/10.1109/ACCESS.2019.2936941S117652117677