Reply to: Comments on “Particle Swarm Optimization with Fractional-Order Velocity”

We agree with Ling-Yun et al. [5] and Zhang and Duan comments [2] about the typing error in equation (9) of the manuscript [8]. The correct formula was initially proposed in [6, 7]. The formula adopted in our algorithms discussed in our papers [1, 3, 4, 8] is, in fact, the following: ...

Gelatin particle indirect agglutination test for serodiagnosis of schistosomiasis: comparative study with enzyme-linked immunosorbent assay

A new serological test, the gelatin particle agglutination test (GPAT), was used for the serodiagnosis of schistosomiasis mansoni. This technique showed the sensitivity (90.6%) and specificity (97.8%) close to those of enzyme-linked immunosorbent assay. The GPAT can be easily and rapidly performed without specialized equipment, by using lyophilized antigen-coated gelatin particles. The test also seems to be useful for mass screening of Schistosoma infection in field conditions.

Production optimization of rotavirus-like particles: a system biology approach

Dissertation presented to obtain a Ph.D. degree in Engineering and Technology Sciences, Systems Biology at the Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa

Studies on human anti-rabies immunization in Brazil: II - Preliminary evaluation of the 2-1-1 schedule for human pre-exposure anti-rabies immunization, employing suckling mouse brain vaccine

This study reports preliminary results of virus neutralizing antibody (VNA) titers obtained on different days in the course of human anti-rabies immunization with the 2-1-1 schedule (one dose is given in the right arm and one dose in the left arm at day 0, and one dose is apllied on days 7 and 21), recommended by WHO for post-exposure treatment with cell culture vaccines. A variant schedule (double dose on day zero and another on day 14) was also tested, both employing suckling mouse brain vaccine. A complete seroconversion rate was obtained after only 3 vaccine doses, and almost all patients (11 of 12) presented titers higher than 1.0 IU/ml. Both neutralizing response and seroconversion rates were lower in the group receiving only 3 doses, regardless of the sample collecting day. Although our results are lower than those found with cell culture vaccines, the geometry mean of VNA is fully satisfactory, overcoming the lower limit recommended by WHO of 0.5 IU/ml. The 2-1-1 schedule could be an alternative one for pre exposure immunization, shorter than the classical 3+1 regimen (one dose on days 0, 2, 4 and 30) with only three visits to the doctor, instead of four.

Serological findings during a measles outbreak occurring in a population with vaccine coverage

From March 1991 to April 1992, serum samples for IgM detection were collected from 112 clinical measles cases reported to the Health Department of Niterói, State of Rio de Janeiro. The positivity exceeded 90% for specimens collected from the 5th to the 29th day after the onset of the disease. After day 30 a decline in IgM detection was observed, although positivity has been detected up to 90 days after the onset of the symptoms. Forty-four patients (48.9%) with an IgM response had a history of prior measles vaccination. In 5 of the 22 measles-IgM negative cases the infection was due to other agents (rubella: 4 cases, dengue: 1 case). These results show that sensitivity of the test employed for confirming suspected measles cases is high, even in vaccinated patients.

Temporal association between the isolation of Sabin-related poliovirus vaccine strains and the Guillain-Barré syndrome

Thirty eight paralysis cases classified as Guillain-Barré syndrome (GBS) in Brazil were analysed. In all these cases Sabin-related poliovirus vaccine strains were isolated. In most of the cases the last vaccine dose was given months or years before the onset of GBS, suggesting a persistent infection or the transmission of the Sabin-related strains to the patients. The isolation of Sabin-related strains from GBS cases some days or weeks after the onset of the disease, demonstrated a temporal association between the isolation of the strains and the disease. Although the isolates from the GBS cases may not be the etiological agent of the disease, this study strongly indicates that infections caused by Sabin-related vaccine strains can trigger the GBS in certain cases.

Multi-objective Parallel Particle Swarm Optimization for Day-ahead Vehicle-To-Grid Scheduling

This paper presents a methodology for multi-objective day-ahead energy resource scheduling for smart grids considering intensive use of distributed generation and Vehicle- To-Grid (V2G). The main focus is the application of weighted Pareto to a multi-objective parallel particle swarm approach aiming to solve the dual-objective V2G scheduling: minimizing total operation costs and maximizing V2G income. A realistic mathematical formulation, considering the network constraints and V2G charging and discharging efficiencies is presented and parallel computing is applied to the Pareto weights. AC power flow calculation is included in the metaheuristics approach to allow taking into account the network constraints. A case study with a 33-bus distribution network and 1800 V2G resources is used to illustrate the performance of the proposed method.

Dispatch of distributed Energy Resources to Provide Energy and Reserve in Smart Grids using a Particle Swarm Optimization Approach

The smart grid concept is a key issue in the future power systems, namely at the distribution level, with deep concerns in the operation and planning of these systems. Several advantages and benefits for both technical and economic operation of the power system and of the electricity markets are recognized. The increasing integration of demand response and distributed generation resources, all of them mostly with small scale distributed characteristics, leads to the need of aggregating entities such as Virtual Power Players. The operation business models become more complex in the context of smart grid operation. Computational intelligence methods can be used to give a suitable solution for the resources scheduling problem considering the time constraints. This paper proposes a methodology for a joint dispatch of demand response and distributed generation to provide energy and reserve by a virtual power player that operates a distribution network. The optimal schedule minimizes the operation costs and it is obtained using a particle swarm optimization approach, which is compared with a deterministic approach used as reference methodology. The proposed method is applied to a 33-bus distribution network with 32 medium voltage consumers and 66 distributed generation units.

Decision support tool for Virtual Power Players: Hybrid Particle Swarm Optimization applied to Day-ahead Vehicle-To-Grid Scheduling

This paper presents a decision support tool methodology to help virtual power players (VPPs) in the Smart Grid (SGs) context to solve the day-ahead energy resource scheduling considering the intensive use of Distributed Generation (DG) and Vehicle-To-Grid (V2G). The main focus is the application of a new hybrid method combing a particle swarm approach and a deterministic technique based on mixedinteger linear programming (MILP) to solve the day-ahead scheduling minimizing total operation costs from the aggregator point of view. A realistic mathematical formulation, considering the electric network constraints and V2G charging and discharging efficiencies is presented. Full AC power flow calculation is included in the hybrid method to allow taking into account the network constraints. A case study with a 33-bus distribution network and 1800 V2G resources is used to illustrate the performance of the proposed method.

Particle Swarm Optimization of Electricity Market Negotiating Players Portfolio

Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors’ research group has developed a multi-agent system: MASCEM (Multi- Agent System for Competitive Electricity Markets), which performs realistic simulations of the electricity markets. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from each market context. However, it is still necessary to adequately optimize the players’ portfolio investment. For this purpose, this paper proposes a market portfolio optimization method, based on particle swarm optimization, which provides the best investment profile for a market player, considering different market opportunities (bilateral negotiation, market sessions, and operation in different markets) and the negotiation context such as the peak and off-peak periods of the day, the type of day (business day, weekend, holiday, etc.) and most important, the renewable based distributed generation forecast. The proposed approach is tested and validated using real electricity markets data from the Iberian operator – MIBEL.

Application-Specific Modified Particle Swarm Optimization for energy resource scheduling considering vehicle-to-grid

This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding the management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.

Electricity Markets Portfolio Optimization using a Particle Swarm Approach

Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors’ research group has developed a multi-agent system: MASCEM (Multi-Agent System for Competitive Electricity Markets), which simulates the electricity markets. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from the market context. However, it is still necessary to adequately optimize the player’s portfolio investment. For this purpose, this paper proposes a market portfolio optimization method, based on particle swarm optimization, which provides the best investment profile for a market player, considering the different markets the player is acting on in each moment, and depending on different contexts of negotiation, such as the peak and offpeak periods of the day, and the type of day (business day, weekend, holiday, etc.). The proposed approach is tested and validated using real electricity markets data from the Iberian operator – OMIE.

IMMUNOGENICITY OF LOW-DOSE INTRAMUSCULAR AND INTRADERMAL VACCINATION WITH RECOMBINANT HEPATITIS B VACCINE

The study is a randomized trial using recombinant DNA vaccine to determine whether an intramuscular 10 µg dose or intradermal 2 µg induces satisfactory anti-HBs levels compared to the standard dose of intramuscular 20 µg. participants were 359 healthy medical and nurse students randomly allocated to one of the three groups: Group I - IM 20 µg; Group II - IM 10 µg; Group III - ID 2 µg at 0, 1 and 6 months. Anti-HBs titres were measured after complete vaccine schedule by ELISA/Pasteur. Baseline variables were similar among groups and side effects were mild after any dose. Vaccinees in the IM-10 µg group had seroconversion rate and geometric mean titre (GMT 2344 IU L-1), not significant different from the IM-20 µg group (GMT 4570 IU L-1). On the contrary, 21.4% of the ID - 2 µg recipients mount antibody concentration below 10 IU L1 and GMT of 91 IU L-1, a statiscally significant difference compared with the standard schedule IM-20 µg (p < 0.001). A three dose regimen of half dosse IM could be considered an appropriate schedule to prevent hepatitis B in young health adults which is of relevance to the expansion of hepatitis B vaccine programme

PRELIMINARY REPORT OF THE USE ON ADULTS OF A RECOMBINANT YEAST-DERIVED HEPATITIS B VACCINE MANUFACTURED BY INSTITUTO BUTANTAN

Three 10 µg doses of the recombinant hepatitis B vaccine, manufactured by Instituto Butantan by original technology, were administered in a adult population, mean age 30 years old, following the 0, 1 and 6 months schedule immunization. The clinical trial was considered satisfactory in terms of immunogenicity (anti-HBs titers between 17.5-29500 IU/l, seroconversion 95.3%) and reactogenicity (no incapacitating side effects)