New findings on the dynamics of HIV and TB coinfection models

In this paper we study a model for HIV and TB coinfection. We consider the integer order and the fractional order versions of the model. Let α∈[0.78,1.0] be the order of the fractional derivative, then the integer order model is obtained for α=1.0. The model includes vertical transmission for HIV and treatment for both diseases. We compute the reproduction number of the integer order model and HIV and TB submodels, and the stability of the disease free equilibrium. We sketch the bifurcation diagrams of the integer order model, for variation of the average number of sexual partners per person and per unit time, and the tuberculosis transmission rate. We analyze numerical results of the fractional order model for different values of α, including α=1. The results show distinct types of transients, for variation of α. Moreover, we speculate, from observation of the numerical results, that the order of the fractional derivative may behave as a bifurcation parameter for the model. We conclude that the dynamics of the integer and the fractional order versions of the model are very rich and that together these versions may provide a better understanding of the dynamics of HIV and TB coinfection.

An integer programming model for the minimum interval graph completion problem

The minimum interval graph completion problem consists of, given a graph G = ( V, E ), finding a supergraph H = ( V, E ∪ F ) that is an interval graph, while adding the least number of edges |F| . We present an integer programming formulation for solving the minimum interval graph completion problem recurring to a characteri- zation of interval graphs that produces a linear ordering of the maximal cliques of the solution graph.

Fractional model for malaria transmission under control strategies

We study a fractional model for malaria transmission under control strategies.Weconsider the integer order model proposed by Chiyaka et al. (2008) in [15] and modify it to become a fractional order model. We study numerically the model for variation of the values of the fractional derivative and of the parameter that models personal protection, b. From observation of the figures we conclude that as b is increased from 0 to 1 there is a corresponding decrease in the number of infectious humans and infectious mosquitoes, for all values of α. This means that this result is invariant for variation of fractional derivative, in the values tested. These results are in agreement with those obtained in Chiyaka et al.(2008) [15] for α = 1.0 and suggest that our fractional model is epidemiologically wellposed.

Integer vs. fractional order control of a hexapod robot

This paper studies the performance of integer and fractional order controllers in a hexapod robot with joints at the legs having viscous friction and flexibility. For that objective the robot prescribed motion is characterized in terms of several locomotion variables. The controller performance is analised through the Nyquist stability criterion. A set of model-based experiments reveals the influence of the different controller implementations upon the proposed metrics.

An integer programming framework for sequencing cutting patterns based on interval graph completion

We derived a framework in integer programming, based on the properties of a linear ordering of the vertices in interval graphs, that acts as an edge completion model for obtaining interval graphs. This model can be applied to problems of sequencing cutting patterns, namely the minimization of open stacks problem (MOSP). By making small modifications in the objective function and using only some of the inequalities, the MOSP model is applied to another pattern sequencing problem that aims to minimize, not only the number of stacks, but also the order spread (the minimization of the stack occupation problem), and the model is tested.

Scheduling aircraft’s engines repair process: a mathematical model

In this talk, we discuss a scheduling problem that originated at TAP - Maintenance & Engineering - the maintenance, repair and overhaul organization of Portugal’s leading airline. In the repair process of aircrafts’ engines, the operations to be scheduled may be executed on a certain workstation by any processor of a given set, and the objective is to minimize the total weighted tardiness. A mixed integer linear programming formulation, based on the flexible job shop scheduling, is presented here, along with computational experiment on a real instance, provided by TAP-ME, from a regular working week. The model was also tested using benchmarking instances available in literature.

Thinking over b‐learning strategy: the MIPO model approach

This article describes the main research results in a new methodology, in which the stages and strategies of the technology integration process are identified and described. A set of principles and recommendations are therefore presented. The MIPO model described in this paper is a result of the effort made regarding the understanding of the main success features of good practices, in the web environment, integrated in the information systems/information technology context. The initial model has been created, based on experiences and literature review. After that, it was tested in the information and technology system units at higher school and also adapted as a result of four cycles of an actionresearch work combined with a case study research. The information, concepts and procedures presented here give support to teachers and instructors, instructional designers and planning teams – anyone who wants to develop effective b‐learning instructions.

Identificação de compostos que modulam a patogénese da doença de Machado-Joseph em C.elegans: autofagia como alvo terapêutico: identification of small compounds that modulate pathogenesis of Machado-Joseph disease in a C.elegans model: targeting autophagy

A doença de Machado-Joseph (DMJ) ou ataxia espinocerebelosa do tipo 3 (SCA3), conhecida por ser a mais comum das ataxias hereditárias dominantes em todo o mundo, é uma doença neurodegenerativa autossómica dominante que leva a uma grande incapacidade motora, embora sem alterar o intelecto, culminando com a morte do doente. Atualmente não existe nenhum tratamento eficaz para esta doença. A DMJ é resultado de uma alteração genética causada pela expansão de uma sequência poliglutamínica (poliQ), na região C-terminal do gene que codifica a proteína ataxina-3 (ATXN3). Os mecanismos celulares das doenças de poliglutaminas que provocam toxicidade, bem como a função da ATXN3, não são ainda totalmente conhecidos. Neste trabalho, usamos, pela sua simplicidade e potencial genético, um pequeno animal invertebrado, o nemátode C. elegans, com o objetivo de identificar fármacos eficazes para o combate contra a patogénese da DMJ, analisando simultaneamente o seu efeito na agregação da ATXN3 mutante nas células neuronais in vivo e o seu impacto no comportamento motor dos animais. Este pequeno invertebrado proporciona grandes vantagens no estudo dos efeitos tóxicos de proteínas poliQ nos neurónios, uma vez que a transparência das suas 959 células (das quais 302 são neurónios) facilita a deteção de proteínas fluorescentes in vivo. Para além disso, esta espécie tem um ciclo de vida curto, é económica e de fácil manutenção. Neste trabalho testámos no nosso modelo transgénico da DMJ com 130Qs em C.elegans dois compostos potencialmente moduladores da agregação da ATXN3 mutante e da resultante disfunção neurológica, atuando pela via da autofagia. De modo a validar a possível importância terapêutica da ativação da autofagia os compostos candidatos escolhidos foram o Litío e o análogo da Rapamicina CCI-779, testados independentemente e em combinação. A neuroproteção conferida pelo Litío e pelo CCI-779 independentemente sugere que o uso destes fármacos possa ser considerado uma boa estratégia como terapia para a DMJ, a testar em organismos evolutivamente mais próximos do humano. A manipulação da autofagia, segundo vários autores, parece ser benéfica e pode ser a chave para o desenvolvimento de novos tratamentos para várias doenças relacionadas com a agregação proteica e o envelhecimento.

Conceptual model for decomposing the value for the customer

Value has been defined in different theoretical contexts as need, desire, interest, standard /criteria, beliefs, attitudes, and preferences. The creation of value is key to any business, and any business activity is about exchanging some tangible and/or intangible good or service and having its value accepted and rewarded by customers or clients, either inside the enterprise or collaborative network or outside. “Perhaps surprising then is that firms often do not know how to define value, or how to measure it” (Anderson and Narus, 1998 cited by [1]). Woodruff echoed that we need “richer customer value theory” for providing an “important tool for locking onto the critical things that managers need to know”. In addition, he emphasized, “we need customer value theory that delves deeply into customer’s world of product use in their situations” [2]. In this sense, we proposed and validated a novel “Conceptual Model for Decomposing the Value for the Customer”. To this end, we were aware that time has a direct impact on customer perceived value, and the suppliers’ and customers’ perceptions change from the pre-purchase to the post-purchase phases, causing some uncertainty and doubts.We wanted to break down value into all its components, as well as every built and used assets (both endogenous and/or exogenous perspectives). This component analysis was then transposed into a mathematical formulation using the Fuzzy Analytic Hierarchy Process (AHP), so that the uncertainty and vagueness of value perceptions could be embedded in this model that relates used and built assets in the tangible and intangible deliverable exchange among the involved parties, with their actual value perceptions.

Increase of the delivered energy probability in DES using a fuzzy probabilistic modeling

The paper proposes a methodology to increase the probability of delivering power to any load point by identifying new investments in distribution energy systems. The proposed methodology is based on statistical failure and repair data of distribution components and it uses a fuzzy-probabilistic modeling for the components outage parameters. The fuzzy membership functions of the outage parameters of each component are based on statistical records. A mixed integer nonlinear programming optimization model is developed in order to identify the adequate investments in distribution energy system components which allow increasing the probability of delivering power to any customer in the distribution system at the minimum possible cost for the system operator. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 180 bus distribution network.

Optimization model for medium term natural gas commitment

In this paper we study the optimal natural gas commitment for a known demand scenario. This study implies the best location of GSUs to supply all demands and the optimal allocation from sources to gas loads, through an appropriate transportation mode, in order to minimize total system costs. Our emphasis is on the formulation and use of a suitable optimization model, reflecting real-world operations and the constraints of natural gas systems. The mathematical model is based on a Lagrangean heuristic, using the Lagrangean relaxation, an efficient approach to solve the problem. Computational results are presented for Iberian and American natural gas systems, geographically organized in 65 and 88 load nodes, respectively. The location model results, supported by the computational application GasView, show the optimal location and allocation solution, system total costs and suggest a suitable gas transportation mode, presented in both numerical and graphic supports.

Hybrid fuzzy Monte Carlo and logic programming model for distribution network reconfiguration in the presence of outages

This paper presents a methodology for distribution networks reconfiguration in outage presence in order to choose the reconfiguration that presents the lower power losses. The methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modelling for system component outage parameters. Fuzzy membership functions of system component outage parameters are obtained by statistical records. A 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. Once obtained the system states by Monte Carlo simulation, a logical programming algorithm is applied to get all possible reconfigurations for every system state. In order to evaluate the line flows and bus voltages and to identify if there is any overloading, and/or voltage violation a distribution power flow has been applied to select the feasible reconfiguration with lower power losses. To illustrate the application of the proposed methodology to a practical case, the paper includes a case study that considers a real distribution network.

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.

Optimal scheduling of a renewable micro-grid in an isolated load area using mixed-integer linear programming

In the energy management of the isolated operation of small power system, the economic scheduling of the generation units is a crucial problem. Applying right timing can maximize the performance of the supply. The optimal operation of a wind turbine, a solar unit, a fuel cell and a storage battery is searched by a mixed-integer linear programming implemented in General Algebraic Modeling Systems (GAMS). A Virtual Power Producer (VPP) can optimal operate the generation units, assured the good functioning of equipment, including the maintenance, operation cost and the generation measurement and control. A central control at system allows a VPP to manage the optimal generation and their load control. The application of methodology to a real case study in Budapest Tech, demonstrates the effectiveness of this method to solve the optimal isolated dispatch of the DC micro-grid renewable energy park. The problem has been converged in 0.09 s and 30 iterations.

Optimal methodology for renewable energy dispatching in islanded operation

The management of energy resources for islanded operation is of crucial importance for the successful use of renewable energy sources. A Virtual Power Producer (VPP) can optimally operate the resources taking into account the maintenance, operation and load control considering all the involved cost. This paper presents the methodology approach to formulate and solve the problem of determining the optimal resource allocation applied to a real case study in Budapest Tech’s. The problem is formulated as a mixed-integer linear programming model (MILP) and solved by a deterministic optimization technique CPLEX-based implemented in General Algebraic Modeling Systems (GAMS). The problem has also been solved by Evolutionary Particle Swarm Optimization (EPSO). The obtained results are presented and compared.