Scaling up a chemically-defined aggregate-based suspension culture system for neural commitment of human pluripotent stem cells

The demand of high cell numbers for applications in cellular therapies and drug screening requires the development of scalable platforms capable to generating highly pure populations of tissue-specific cells from human pluripotent stem cells. This work describes the scaling-up of an aggregate-based culture system for neural induction of human induced pluripotent stem cells (hiPSCs) under chemically-defined conditions. Since initial cell density and aggregate size have an important impact in the expansion and commitment of these cells into a particular lineage, a combination of non-enzymatic dissociation and rotary agitation was successfully used to produce homogeneous populations of hiPSC aggregates with an optimal (140 µm) and narrow distribution of diameters (coefficient of variation of 21.6%). Scalable neural commitment of hiPSCs as 3D aggregates was then performed in 50 mL spinner flasks, and process optimization using a factorial design approach was developed involving parameters such as agitation rate and seeding density. We were able to produce neural progenitor cell cultures, that at the end of a 6-day neural induction process contained less than 3% of Oct4-positive cells and that, after replating, retained more than 60% of Pax6-positive neural cells. Furthermore, after scalable differentiation, hiPSC-derived neural progenitors still retained their multipotent potential, being able to give rise to neuronal and glial cells. The results presented in this work should set the stage for the future generation of a clinically relevant number of human neural progenitors for transplantation and other biomedical applications using totally controlled, automated and reproducible large-scale bioreactor culture systems

Embedding a competitive ranking method in the artificial fish swarm algorithm for global optimization

Nonlinear programming problems are known to be difficult to solve, especially those that involve a multimodal objective function and/or non-convex and at the same time disjointed solution space. Heuristic methods that do not require derivative calculations have been used to solve this type of constrained problems. The most used constraint-handling technique has been the penalty method. This method converts the constrained optimization problem to a sequence of unconstrained problems by adding, to the objective function, terms that penalize constraint violation. The selection of the appropriate penalty parameter value is the main difficulty with this type of method. To address this issue, we use a global competitive ranking method. This method is embedded in a stochastic population based technique known as the artificial fish swarm (AFS) algorithm. The AFS search for better points is mainly based on four simulated movements: chasing, swarming, searching, and random. For each point, the movement that gives the best position is chosen. To assess the quality of each point in the population, the competitive ranking method is used to rank the points with respect to objective function and constraint violation independently. When points have equal constraint violations then the objective function values are used to define their relative fitness. The AFS algorithm also relies on a very simple and random local search to refine the search towards the global optimal solution in the solution space. A benchmarking set of global problems is used to assess this AFS algorithm performance

Neural gliding versus neural tensioning: effects on heat and cold thresholds, pain thresholds and hand grip strength in asymptomatic individuals

Introduction: Neural mobilization can be performed in a way that facilitates movement through a stretching technique (tensioning) or in a way that maximizes the gliding of peripheral nerves in relation to adjacent structures (gliding). Evidence on how these techniques compare in terms of effects are scarce. The aim of this study is to compare the effects of neural gliding and neural tensioning targeting the median nerve on heat and cold temperature threshold, heat pain threshold, pressure pain thresholds and hand grip strength in asymptomatic participants. Methods: Participants received 4 series of 10 repetitions of either neural gliding (n = 30) or neural tensioning (n = 30) and were assessed for heat and cold temperature threshold, heat pain threshold, pressure pain threshold, and hand grip strength at baseline, immediately after the intervention, and 30 min post-intervention. Results: A significant main interaction between time and intervention was found for the PPT at the forearm (F(2,55) = 5.98; p = 0.004), favouring the tensioning neural mobilization. No significant differences were found for the other variables. Conclusions: Four series of 10 repetitions of neural tensioning targeting the median nerve in asymptomatic subjects seem to be enough to induce hypoalgesia and have no negative effects on A-delta and C mediated sensory function and on hand grip strength production.publishe

Performance comparison of a typical nonlinear load connected to Ac and Dc power grids

This paper presents a performance comparison of a typical nonlinear load used in domestic appliances (electronic load), when supplied by an ac and a dc voltage of the same rms value. The performance of the nonlinear load towards its connection to ac and dc power grids is accomplished in terms of the waveforms which are registered in the consumed current, internal dc-link voltage and output voltage. A simulation model was developed using realistic database models of the power semiconductors comprising a nonlinear load with input ac-dc converter, so that the efficiency can be calculated and compared for three distinct cases: (1) load supplied by an ac voltage; (2) load supplied by a dc voltage; (3) load without the input ac-dc converter supplied by a dc voltage. Thus, besides the comparison between the ac and dc power grids supplying the same nonlinear load (cases 1 and 2), a third case is considered, which consists of removing the input ac-dc converter (eliminating needless components of the nonlinear load when supplied by a dc voltage). The obtained results show that supplying nonlinear loads with dc power grids is advantageous in relation to the ac power grid, and therefore it can be beneficial to adapt nonlinear loads to be powered by dc power grids.This work has been supported by COMPETE: POCI-01-0145–FEDER–007043 and FCT –Fundação para a Ciência eTecnologia within the Project Scope: UID/CEC/00319/2013. This work is financed by the ERDF –European Regional De-velopment Fund through the Operational Programme for Competitiveness and Interna-tionalisation –COMPETE 2020 Programme, and by National Funds through the Por-tuguese funding agency, FCT –Fundação para a Ciência e a Tecnologia,within project SAICTPAC/0004/2015 –POCI –01–0145–FEDER–016434. Mr. Tiago Sousa is sup-ported by the doctoral scholarship SFRH/BD/134353/2017 granted by the Portuguese FCT agency

Performance comparison of a typical nonlinear load supplied by ac and dc voltages

This paper presents a performance comparison of a typical nonlinear load when supplied by ac or dc voltages with the same rms value. The performance of the nonlinear load towards its connection to ac and dc power grids is accomplished in terms of the waveforms and efficiency. A simulation model was developed using realistic database models of the power semiconductors comprising the load, and an experimental setup was assembled, so that the efficiency can be determined and compared for simulation and real operating conditions. Three distinct cases were considered for this study: (1) Load supplied by ac voltage; (2) Load supplied by dc voltage; and (3) Load without the input ac-dc converter supplied by dc voltage. The obtained results show that supplying nonlinear loads with dc power grids is advantageous in relation to the ac power grid, and therefore it can be beneficial to adapt nonlinear loads to be powered by dc power grids.This work has been supported by COMPETE: POCI-01-0145–FEDER–007043 and FCT –Fundação para a Ciência e Tecnologiawithin the Project Scope: UID/CEC/00319/2013. This work is financed by the ERDF –European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation –COMPETE 2020 Programme, and by National Funds through thePortuguese funding agency, FCT –Fundação para a Ciência e a Tecnologia, within project SAICTPAC/0004/2015 –POCI –01–0145–FEDER–016434. Mr. Tiago Sousa is supported by the doctoral scholarship SFRH/BD/134353/2017 granted by the Portuguese FCT agenc

A novel front-end multilevel converter for renewable energy systems in smart grids

The integration of renewable energy systems into smart grids requires dc-to-ac power electronics converters for adapting the voltage levels of both sides. In this context, a novel topology of front-end multilevel dc-to-ac converter is proposed in order to enhance the integration of renewable energy systems into smart grids, preventing power quality problems. The proposed converter is designed to operate as a grid-tied inverter, imposing controlled sinusoidal grid currents in phase opposition with the power grid voltage, and establishing five distinct voltage levels to improve the current waveform. The dc side is suitable to be connected directly to a set of photovoltaic solar panels with an appropriated voltage level, or to an external dc-to-dc intermediary converter used to interface other renewable energy sources. An entire analysis of the hardware design and the operation principle is presented, including the adopted control strategy for the proposed front-end converter in conditions of current control. An accurate computational validation under realistic operating conditions for a significant operating power range is presented using a dedicated power electronics simulation software, where the obtained results show the advantages and the convenience of the proposed front-end converter in detriment of the classical solutions.Fundação para a Ciência e Tecnologia (FCT); COMPETE: POCI-01-0145 –FEDER–007043 and FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013. This work is financed by the ERDF – European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation – COMPETE 2020 Programme, and by National Funds through the Portuguese funding agency, FCT – Fundação para a Ciência e a Tecnologia, within project SAICTPAC/0004/2015 – POCI – 01–0145– FEDER–016434info:eu-repo/semantics/publishedVersio

An augmented lagrangian fish swarm based method for global optimization

This paper presents an augmented Lagrangian methodology with a stochastic population based algorithm for solving nonlinear constrained global optimization problems. The method approximately solves a sequence of simple bound global optimization subproblems using a fish swarm intelligent algorithm. A stochastic convergence analysis of the fish swarm iterative process is included. Numerical results with a benchmark set of problems are shown, including a comparison with other stochastic-type algorithms.Fundação para a Ciência e a Tecnologia (FCT

Novel fish swarm heuristics for bound constrained global optimization problems

The heuristics herein presented are modified versions of the artificial fish swarm algorithm for global optimization. The new ideas aim to improve solution accuracy and reduce computational costs, in particular the number of function evaluations. The modifications also focus on special point movements, such as the random, search and the leap movements. A local search is applied to refine promising regions. An extension to bound constrained problems is also presented. To assess the performance of the two proposed heuristics, we use the performance profiles as proposed by Dolan and More in 2002. A comparison with three stochastic methods from the literature is included.Fundação para a Ciência e a Tecnologia (FCT

Fish swarm intelligent algorithm for bound constrained global optimization

The algorithm herein presented is a modified version of the artificial fish swarm algorithm for global optimization. The new ideas are focused on a set of movements, closely related to the random, the searching and the leaping fish behaviors. An extension to bound constrained problems is also presented. To assess the performance of the new fish swarm intelligent algorithm, a set of seven benchmark problems is used. A sensitivity analysis concerning some of the user defined parameters is presented

Unified architecture of single-phase active power filter with battery interface for UPS operation

This paper presents a shunt active power filter with battery interface for uninterruptible power supply (UPS) operation. The proposed unified architecture is composed by a single-phase ac-dc converter from the power grid side and by a bidirectional isolated dc-dc converter to interface the batteries, allowing the operation in three distinct modes: (1) Shunt active power filter; (2) Off-line UPS to supply a set of priority loads during power outages; (3) Energy storage system to support the power grid. The proposed architecture and the developed control algorithms were validated with a reduced-scale laboratorial prototype in all the three different operation modes. The presented experimental results highlight the benefits of the proposed architecture.Fundação para a Ciência e Tecnologia (FCT)info:eu-repo/semantics/publishedVersio