Malaria transmission model for different levels of acquired immunity and temperature-dependent parameters (vector)

OBJECTIVE: Describe the overall transmission of malaria through a compartmental model, considering the human host and mosquito vector. METHODS: A mathematical model was developed based on the following parameters: human host immunity, assuming the existence of acquired immunity and immunological memory, which boosts the protective response upon reinfection; mosquito vector, taking into account that the average period of development from egg to adult mosquito and the extrinsic incubation period of parasites (transformation of infected but non-infectious mosquitoes into infectious mosquitoes) are dependent on the ambient temperature. RESULTS: The steady state equilibrium values obtained with the model allowed the calculation of the basic reproduction ratio in terms of the model's parameters. CONCLUSIONS: The model allowed the calculation of the basic reproduction ratio, one of the most important epidemiological variables.

Clinical and laboratory parameters in dapsone acute intoxication

OBJECTIVE: To determine the severity of dapsone (DDS) acute intoxication – an uncommon medical event – using clinical and laboratory parameters. METHODS: Two hundred and seventy four patients with acute DDS intoxication, aged 1 month to 50 years old, were studied and classified into four age groups. Clinical evaluation was assessed through a protocol and correlated with laboratory parameters. Spectrophotometric methods were used to analyze methemoglobinemia (MHbp) and dapsonemia (DDSp). RESULTS: The most prevalent clinical sign of intoxication was cyanosis, seen in 65.7% of the patients and in 100% of children less than 5 years of age. According to laboratory criteria, MHbp-related severe clinical intoxication was seen in 56.2% and DDSp-related occurred in 58% of the patients. Regarding DDSp, intoxication was considered severe when 20 tablets (100 mg each) were ingested, a median of 29 mug/ml. Regarding MHbp, intoxication was severe when 7.5 tablets were ingested, a median of 38% of the total Hb. The correlation between MHbp and DDSp was statistically significant (n=144, r=0.32, p<0.05). Negative correlation was observed between MHbp and the time elapsed since DDS intake (n=124, r=-0.34, p<0.001). There was also a negative correlation between DDSp and the time elapsed since DDS intake (n=63, r=-0.35, p<0.0001). CONCLUSIONS: Longitudinal analysis showed a significant association between methemoglobinemia and the time elapsed after the intake (t), according to the equation: Dapsonemia = 12.9256 - 0.0682t + 0.234 methemoglobinemia

Quantificação da difusão na ressonância magnética da mama: ADC e Kurtosis

Mestrado em Radiações Aplicadas às Tecnologias da Saúde. Área de especialização: Ressonância Magnética

CVD of CrO2 thin films: Influence of the deposition parameters on their structural and magnetic properties

This work reports on the synthesis of CrO2 thin films by atmospheric pressure CVD using chromium trioxide (CrO3) and oxygen. Highly oriented (100) CrO2 films containing highly oriented (0001) Cr2O3 were grown onto Al2O3(0001) substrates. Films display a sharp magnetic transition at 375 K and a saturation magnetization of 1.92 mu(B)/f.u., close to the bulk value of 2 mu(B)/f.u. for the CrO2.

Effective teaching and optimal experiences: possible link

ISME, Thessaloniki, 2012

Comfort and functionality of pregnant women's feet study of kinetic parameters with silicon insoles

As gestantes, fruto das suas alterações fisiológicas e biomecânicas, constituem uma população de risco relativamente a dores ou lesões do sistema músculo-esquelético, nomeadamente, nos membros inferiores e coluna. Os objectivos deste estudo consistiram em avaliar: (i) a dor e o conforto dos pés durante a marcha: sem o uso de qualquer palmilha nas gestantes e no grupo de controlo; com a aplicação de uma palmilha de retropé e com a aplicação de uma palmilha completa (nas gestantes); (ii) a distribuição das pressões plantares e, (iii) as forças de reacção do solo nas mesmas condições experimentais. Avaliámos ainda a duração das diferentes fases do ciclo de marcha nas gestantes, com e sem palmilhas, e no grupo de controlo, sem o uso de palmilha. Os nossos resultados mostraram que: (i) as gestantes demoram mais tempo a completar a fase de apoio da marcha, (ii) têm um aumento significativo de dores nos pés, face ao grupo de controlo, (iii) as gestantes sentem menos dor e mais conforto quando realizam marcha, com palmilhas, especialmente com a palmilha completa, (iv) a palmilha completa redistribui as forças, diminui os valores de pressão e aumenta a área de contacto do pé com o solo. Os nossos resultados sugerem que, o uso da palmilha completa de silicone, durante a marcha, pode ser eficaz na melhoria da sintomatologia dolorosa e no aumento do conforto da grávida.

An heuristic approach for optimal location of gas supply units in transportation system

The best places to locate the Gas Supply Units (GSUs) on a natural gas systems and their optimal allocation to loads are the key factors to organize an efficient upstream gas infrastructure. The number of GSUs and their optimal location in a gas network is a decision problem that can be formulated as a linear programming problem. Our emphasis is on the formulation and use of a suitable location model, reflecting real-world operations and constraints of a natural gas system. This paper presents a heuristic model, based on lagrangean approach, developed for finding the optimal GSUs location on a natural gas network, minimizing expenses and maximizing throughput and security of supply.The location model is applied to the Iberian high pressure natural gas network, a system modelised with 65 demand nodes. These nodes are linked by physical and virtual pipelines – road trucks with gas in liquefied form. The location model result shows the best places to locate, with the optimal demand allocation and the most economical gas transport mode: by pipeline or by road truck.

Investment optimization in distribution network based on fuzzy outage parameters

This paper presents a methodology that aims to increase the probability of delivering power to any load point of the electrical distribution system by identifying new investments in distribution components. The methodology is based on statistical failure and repair data of the distribution power system components and it uses fuzzy-probabilistic modelling for system component outage parameters. Fuzzy membership functions of system component outage parameters are obtained by statistical records. A mixed integer non-linear optimization technique is developed to identify adequate investments in distribution networks components that allow increasing the availability level for any customer in the distribution system at minimum cost for the system operator. To illustrate the application of the proposed methodology, the paper includes a case study that considers a real distribution network.

Optimal location of gas supply units in natural gas system network

Natural gas industry has been confronted with big challenges: great growth in demand, investments on new GSUs – gas supply units, and efficient technical system management. The right number of GSUs, their best location on networks and the optimal allocation to loads is a decision problem that can be formulated as a combinatorial programming problem, with the objective of minimizing system expenses. Our emphasis is on the formulation, interpretation and development of a solution algorithm that will analyze the trade-off between infrastructure investment expenditure and operating system costs. The location model was applied to a 12 node natural gas network, and its effectiveness was tested in five different operating scenarios.

An efficient method for optimal location and sizing of fixed and switched shunt capacitors in large distribution systems

This paper proposes a computationally efficient methodology for the optimal location and sizing of static and switched shunt capacitors in large distribution systems. The problem is formulated as the maximization of the savings produced by the reduction in energy losses and the avoided costs due to investment deferral in the expansion of the network. The proposed method selects the nodes to be compensated, as well as the optimal capacitor ratings and their operational characteristics, i.e. fixed or switched. After an appropriate linearization, the optimization problem was formulated as a large-scale mixed-integer linear problem, suitable for being solved by means of a widespread commercial package. Results of the proposed optimizing method are compared with another recent methodology reported in the literature using two test cases: a 15-bus and a 33-bus distribution network. For the both cases tested, the proposed methodology delivers better solutions indicated by higher loss savings, which are achieved with lower amounts of capacitive compensation. The proposed method has also been applied for compensating to an actual large distribution network served by AES-Venezuela in the metropolitan area of Caracas. A convergence time of about 4 seconds after 22298 iterations demonstrates the ability of the proposed methodology for efficiently handling large-scale compensation problems.

An optimal scheduling problem in distribution networks considering V2G

This paper addresses the problem of energy resource scheduling. An aggregator will manage all distributed resources connected to its distribution network, including distributed generation based on renewable energy resources, demand response, storage systems, and electrical gridable vehicles. The use of gridable vehicles will have a significant impact on power systems management, especially in distribution networks. Therefore, the inclusion of vehicles in the optimal scheduling problem will be very important in future network management. The proposed particle swarm optimization approach is compared with a reference methodology based on mixed integer non-linear programming, implemented in GAMS, to evaluate the effectiveness of the proposed methodology. The paper includes a case study that consider a 32 bus distribution network with 66 distributed generators, 32 loads and 50 electric vehicles.

Transmission costs allocation based on optimal re-dispatch

Congestion management of transmission power systems has achieve high relevance in competitive environments, which require an adequate approach both in technical and economic terms. This paper proposes a new methodology for congestion management and transmission tariff determination in deregulated electricity markets. The congestion management methodology is based on a reformulated optimal power flow, whose main goal is to obtain a feasible solution for the re-dispatch minimizing the changes in the transactions resulting from market operation. The proposed transmission tariffs consider the physical impact caused by each market agents in the transmission network. The final tariff considers existing system costs and also costs due to the initial congestion situation and losses. This paper includes a case study for the 118 bus IEEE test case.

Simulated annealing metaheuristic to solve the optimal power flow

The optimal power flow problem has been widely studied in order to improve power systems operation and planning. For real power systems, the problem is formulated as a non-linear and as a large combinatorial problem. The first approaches used to solve this problem were based on mathematical methods which required huge computational efforts. Lately, artificial intelligence techniques, such as metaheuristics based on biological processes, were adopted. Metaheuristics require lower computational resources, which is a clear advantage for addressing the problem in large power systems. This paper proposes a methodology to solve optimal power flow on economic dispatch context using a Simulated Annealing algorithm inspired on the cooling temperature process seen in metallurgy. The main contribution of the proposed method is the specific neighborhood generation according to the optimal power flow problem characteristics. The proposed methodology has been tested with IEEE 6 bus and 30 bus networks. The obtained results are compared with other wellknown methodologies presented in the literature, showing the effectiveness of the proposed method.

Ant colony search algorithm for the optimal power flow problem

To maintain a power system within operation limits, a level ahead planning it is necessary to apply competitive techniques to solve the optimal power flow (OPF). OPF is a non-linear and a large combinatorial problem. The Ant Colony Search (ACS) optimization algorithm is inspired by the organized natural movement of real ants and has been successfully applied to different large combinatorial optimization problems. This paper presents an implementation of Ant Colony optimization to solve the OPF in an economic dispatch context. The proposed methodology has been developed to be used for maintenance and repairing planning with 48 to 24 hours antecipation. The main advantage of this method is its low execution time that allows the use of OPF when a large set of scenarios has to be analyzed. The paper includes a case study using the IEEE 30 bus network. The results are compared with other well-known methodologies presented in the literature.

Fuzzy Monte Carlo mathematical model for load curtailment minimization in transmission power systems

This paper presents a methodology which is based on statistical failure and repair data of the transmission power system components and uses fuzzyprobabilistic modeling for system component outage parameters. Using statistical records allows developing the fuzzy membership functions of system component outage parameters. The proposed hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. A network contingency analysis to identify any overloading or voltage violation in the network is performed once obtained the system states by Monte Carlo simulation. This is followed by a remedial action algorithm, based on optimal power flow, to reschedule generations and alleviate constraint violations and, at the same time, to avoid any load curtailment, if possible, or, otherwise, to minimize the total load curtailment, for the states identified by the contingency analysis. In order to illustrate the application of the proposed methodology to a practical case, the paper will include a case study for the Reliability Test System (RTS) 1996 IEEE 24 BUS.