Equivalence of Faddeev-Jackiw and Dirac approaches for gauge theories

The equivalence between the Dirac method and Faddeev-Jackiw analysis for gauge theories is proved. In particular we trace out, in a stage by stage procedure, the standard classification of first and second class constraints of Dirac's method in the F-J approach. We also find that the Darboux transformation implied in the F-J reduction process can be viewed as a canonical transformation in Dirac approach. Unlike Dirac's method the F-J analysis is a classical reduction procedure, then the quantization can be achieved only in the framework of reduce and then quantize approach with all the know problems that this type of procedures presents. Finally we illustrate the equivalence by means of a particular example.Comment: Latex v2.09, 15 pages, to appear in Int. J. Mod. Phys.

Faddeev-Jackiw approach to gauge theories and ineffective constraints

The general conditions for the applicability of the Faddeev-Jackiw approach to gauge theories are studied. When the constraints are effective a new proof in the Lagrangian framework of the equivalence between this method and the Dirac approach is given. We find, however, that the two methods may give different descriptions for the reduced phase space when ineffective constraints are present. In some cases the Faddeev-Jackiw approach may lose some constraints or some equations of motion. We believe that this inequivalence can be related to the failure of the Dirac conjecture (that says that the Dirac Hamiltonian can be enlarged to an Extended Hamiltonian including all first class constraints, without changes in the dynamics) and we suggest that when the Dirac conjecture fails the Faddeev-Jackiw approach fails to give the correct dynamics. Finally we present some examples that illustrate this inequivalence.Comment: 21 pages, Latex. To be published in Int. J. Mod. Phys.

Quantifying sudden changes in dynamical systems using symbolic networks

We characterise the evolution of a dynamical system by combining two well-known complex systems' tools, namely, symbolic ordinal analysis and networks. From the ordinal representation of a time-series we construct a network in which every node weights represents the probability of an ordinal patterns (OPs) to appear in the symbolic sequence and each edges weight represents the probability of transitions between two consecutive OPs. Several network-based diagnostics are then proposed to characterize the dynamics of different systems: logistic, tent and circle maps. We show that these diagnostics are able to capture changes produced in the dynamics as a control parameter is varied. We also apply our new measures to empirical data from semiconductor lasers and show that they are able to anticipate the polarization switchings, thus providing early warning signals of abrupt transitions.Comment: 18 pages, 9 figures, to appear in New Journal of Physic

Rheology of acid suspensions containing cassava bagasse: Effect of biomass loading, acid content and temperature

[EN] Understanding the characterization and rheological behavior of acid suspensions of cassava bagasse provides essential information for the design of conversion processes. Samples with different cassava bagasse concentrations (0-10% w.w-1), phosphoric acid (0-10% w.w(-1)) at temperatures between 278.13 and 318.13 K were submitted to steady-state flow over a wide range of shear rates (1-265 s(-1)). The biomass particles had considerable residual starch (similar to 50% db), low lignin content and adequate particle size (<200 mu m) for the conversion process. Flow curves were well-fitted to the Herschel-Bulkley model, presenting a Newtonian domain at low solids and acid content and a non-Newtonian behavior with noticeable yield stress and shear-thinning characteristic (n < 1) at above 6% of cassava bagasse. Resistance to flow increased as the solids loading and acid content increased. Temperature dependence could be expressed as a function of an Arrhenius-type equation with good accuracy of fit. (C) 2019 Elsevier B.V. All rights reserved.The authors would like to thank Prof. Rosiane Lopes Cunha and Prof. Ana Carla Kawazoe Sato from University of Campinas (UNICAMP) for their support with particle size analyses. The authors also acknowledge the Sao Paulo Research Foundation - FAPESP (Grant number 2017/06518-2) and the Coordination for the Improvement of Higher Education Personnel -CAPES (Grant number 88881.132626/2016-01) for their financial support.Carregari-Polachini, T.; Mulet Pons, A.; Carcel, JA.; Telis Romero, J. (2019). Rheology of acid suspensions containing cassava bagasse: Effect of biomass loading, acid content and temperature. Powder Technology. 354:271-280. https://doi.org/10.1016/j.powtec.2019.05.086S27128035

Mechanistic modelling to address process analysis: Kibbles of carob (Ceratonia siliqua, L.) pod extraction

[EN] The daily challenge involved in operating a process is the attainment of the objectives. Process management requires the use of tools adapted to the system s complexity. In order to obtain real time results, simplified mechanistic modeling offers a way to deal with this. To this end, carob pod (Ceratonia siliqua, L.) kibbles extraction is addressed in this work. They are a source of different, valuable components and have a complex structure and a highly variable concentration of components. The components considered are sugars and soluble polyphenols. Obtaining the extracts with an optimal composition of a particular component, while avoiding or limiting other components in the extract, is a challenge to be addressed. Two steps can be considered: solubilization and diffusion, modeled by means of a first order reaction and by considering slab geometry. The optimal processing time and temperature are obtained by taking a particular kibble size and composition into accountThe support from Generalitat Valenciana PROMETEO/2014/005 is acknowledged.Mulet Pons, A.; Fernández-Salguero, J.; García Pérez, JV.; Bon Corbín, J. (2016). Mechanistic modelling to address process analysis: Kibbles of carob (Ceratonia siliqua, L.) pod extraction. Journal of Food Engineering. 176:71-76. https://doi.org/10.1016/j.jfoodeng.2015.06.011S717617

Stabilization of apple peel by drying. Influence of temperature and ultrasound application on drying kinetics and product quality

This is an Accepted Manuscript of an article published by Taylor & Francis Group in Drying Technology on 2019, available online at: http://www.tandfonline.com/10.1080/07373937.2018.1474476[EN] Increasing the value of the waste generated by food processing is a must from an environmental and economic point of view. This paper addresses the influence of drying temperature and ultrasound application on the drying kinetics and quality of apple peel (Royal Gala var.). Samples were dried at -10, 30, 50 and 70 ºC without and with (50 W) ultrasound application. Color, antioxidant capacity, total phenolic and ascorbic acid content were measured. Ultrasound application and drying temperature significantly shortened the drying time and affected the quality parameters. The drying carried out at 30 ºC with ultrasound application was a fast process that provided samples with good color and antioxidant attributes.The authors acknowledge the financial support of INIA-ERDF throughout the project RTA2015-00060-C04-02.Martins, MP.; Cortés, EJ.; Eim, V.; Mulet Pons, A.; Carcel, JA. (2019). Stabilization of apple peel by drying. Influence of temperature and ultrasound application on drying kinetics and product quality. Drying Technology. 37(5):559-568. https://doi.org/10.1080/07373937.2018.1474476S55956837

Advances in selective activation of muscles for non-invasive motor neuroprostheses

Non-invasive neuroprosthetic (NP) technologies for movement compensation and rehabilitation remain with challenges for their clinical application. Two of those major challenges are selective activation of muscles and fatigue management. This review discusses how electrode arrays improve the efficiency and selectivity of functional electrical stimulation (FES) applied via transcutaneous electrodes. In this paper we review the principles and achievements during the last decade on techniques for artificial motor unit recruitment to improve the selective activation of muscles. We review the key factors affecting the outcome of muscle force production via multi-pad transcutaneous electrical stimulation and discuss how stimulation parameters can be set to optimize external activation of body segments. A detailed review of existing electrode array systems proposed by different research teams is also provided. Furthermore, a review of the targeted applications of existing electrode arrays for control of upper and lower limb NPs is provided. Eventually, last section demonstrates the potential of electrode arrays to overcome the major challenges of NPs for compensation and rehabilitation of patient-specific impairments.This work has been done with partial financial support of the Ministry of Science and Innovation, in the framework of national project HYPER(CSD 2009-00067- Hybrid Neuroprosthetic and Neurorobotic Devices for Functional Compensation and Rehabilitation of Motor Disorders) and European Union in the framework of TREMOR Project: “TREMOR: An ambulatory BCI-driven tremor suppression system based on functional electrical stimulation”, ICT-2007-224051, and “NeuroTREMOR: A novel concept for support to diagnosis and remote management of tremor”, ICT-2011.5.1-287739.Peer reviewe

SMS Spam Filtering using Probabilistic Topic Modelling and Stacked Denoising Autoencoder

In This paper we present a novel approach to spam filtering and demonstrate its applicability with respect to SMS messages. Our approach requires minimum features engineering and a small set of labelled data samples. Features are extracted using topic modelling based on latent Dirichlet allocation, and then a comprehensive data model is created using a Stacked Denoising Autoencoder (SDA). Topic modelling summarises the data providing ease of use and high interpretability by visualising the topics using word clouds. Given that the SMS messages can be regarded as either spam (unwanted) or ham (wanted), the SDA is able to model the messages and accurately discriminate between the two classes without the need for a pre-labelled training set. The results are compared against the state-of-the-art spam detection algorithms with our proposed approach achieving over 97 % accuracy which compares favourably to the best reported algorithms presented in the literature