For profit social entrepreneurship: milestones to develop an efficient social venture

Inúmeras questões terríveis e alarmantes são ainda mal resolvidas, apesar da mobilização de ONGs para aliviá-los. Por muito tempo, o setor privado deu as costas a preocupações tal qual estas. Ate que um novo tipo de empreendedor revolucionário apareceu com um novo conceito para combater a pobreza. Mohamed Yunus desbravou empreendedorismo social quando criou a Grameen Bank 36 anos atrás: ele desafiou regras convencionais e estritas alugando dinheiro para Bengalis desmerecidos de credito, tudo isso obtendo lucro no mesmo tempo. Hoje, empreendedorismo social esta um fenômeno mas a maioria dos empreendedores do setor dos e meia ainda enfrentam dificuldades. A pesquisa acadêmica sobre o empreendedorismo social com fins lucrativos ainda está hesitante. O presente trabalho é uma modesta tentativa de analisar quais são os desafios que um empreendedor social com fins lucrativos enfrentará ao longo do caminho para criar seu empreendimento e sustentar os seus objetivos. O exame da literatura mostra que as dificuldades enfrentadas pelos empreendedores são devido a vários fatores, compreendo questões diretamente relacionadas a incerteza do mercado e o contexto local, questões organizacionais, de financiamento, de ética e questões relacionadas a resistência do modelo de negocio. As proposições derivando do exame da literatura foram confrontadas a casos concretos através de entrevistas com empreendedores sociais, investidores de impacto e instituições de apoio. Resultados da pesquisa corroboram as proposições do inicio mas enfatizam necessidade de resolver, com consideração cuidadosa, as questões relacionadas a incerteza do mercado e ao desenho duma governança adequada. A respeito da incerteza do mercado, a identificação das partes interessadas no empreendimento social e a adoção duma mentalidade eficaz para ajustar suposições iniciais para a realidade local, são um padrão chave de sucesso para o empreendimento social. No nível organizacional, a constituição dum time perito e comprometido junto com o desenho duma governança certa para equilibrar o desejo de obter lucro e a necessidade de sustentabilidade financeira é uma garantia de sucesso para o empreendedor social.

Efficient semiparametric estimation of quantile treatment effects

This paper presents calculations of semiparametric efficiency bounds for quantile treatment effects parameters when se1ection to treatment is based on observable characteristics. The paper also presents three estimation procedures forthese parameters, alI ofwhich have two steps: a nonparametric estimation and a computation ofthe difference between the solutions of two distinct minimization problems. Root-N consistency, asymptotic normality, and the achievement ofthe semiparametric efficiency bound is shown for one ofthe three estimators. In the final part ofthe paper, an empirical application to a job training program reveals the importance of heterogeneous treatment effects, showing that for this program the effects are concentrated in the upper quantiles ofthe earnings distribution.

Parallel Cyclostationarity-Exploiting Algorithm for Energy-Efficient Spectrum Sensing

The evolution of wireless communication systems leads to Dynamic Spectrum Allocation for Cognitive Radio, which requires reliable spectrum sensing techniques. Among the spectrum sensing methods proposed in the literature, those that exploit cyclostationary characteristics of radio signals are particularly suitable for communication environments with low signal-to-noise ratios, or with non-stationary noise. However, such methods have high computational complexity that directly raises the power consumption of devices which often have very stringent low-power requirements. We propose a strategy for cyclostationary spectrum sensing with reduced energy consumption. This strategy is based on the principle that p processors working at slower frequencies consume less power than a single processor for the same execution time. We devise a strict relation between the energy savings and common parallel system metrics. The results of simulations show that our strategy promises very significant savings in actual devices.

Fast and efficient synthesis of pyrano[3,2-c]quinolines catalyzed by niobium(V) chloride

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Organophosphorus-induced delayed neuropathy: A simple and efficient therapeutic strategy

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

On developing efficient applications using conservative distributed simulation paradigm

This paper aims to present, using a set of guidelines, how to apply the conservative distributed simulation paradigm (CMB protocol) to develop efficient applications. Using these guidelines, even a user with little experience on distributed simulation and computer architecture can have good performance on distributed simulations using conservative synchronization protocols for parallel processes.The set of guidelines is focus on a specific application domain, the performance evaluation of computer systems, considering models with coarse granularity and few logical processes and running over two platforms: parallel (high performance communication environment) and distributed (low performance communication environment).

EFFICIENT FAULT LOCATION IN UNDERGROUND DISTRIBUTION SYSTEMS THROUGH OPTIMUM-PATH FOREST

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Efficient supervised optimum-path forest classification for large datasets

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

An efficient Hopfield network to solve economic dispatch problems with transmission system representation

Economic dispatch (ED) problems have recently been solved by artificial neural network approaches. Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements. The ability of neural networks to realize some complex non-linear function makes them attractive for system optimization. All ED models solved by neural approaches described in the literature fail to represent the transmission system. Therefore, such procedures may calculate dispatch policies, which do not take into account important active power constraints. Another drawback pointed out in the literature is that some of the neural approaches fail to converge efficiently toward feasible equilibrium points. A modified Hopfield approach designed to solve ED problems with transmission system representation is presented in this paper. The transmission system is represented through linear load flow equations and constraints on active power flows. The internal parameters of such modified Hopfield networks are computed using the valid-subspace technique. These parameters guarantee the network convergence to feasible equilibrium points, which represent the solution for the ED problem. Simulation results and a sensitivity analysis involving IEEE 14-bus test system are presented to illustrate efficiency of the proposed approach. (C) 2004 Elsevier Ltd. All rights reserved.

Design and analysis of an efficient neural network model for solving nonlinear optimization problems

This paper presents an efficient approach based on a recurrent neural network for solving constrained nonlinear optimization. More specifically, a modified Hopfield network is developed, and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the convergence of the network to the equilibrium points that represent an optimal feasible solution. The main advantage of the developed network is that it handles optimization and constraint terms in different stages with no interference from each other. Moreover, the proposed approach does not require specification for penalty and weighting parameters for its initialization. A study of the modified Hopfield model is also developed to analyse its stability and convergence. Simulation results are provided to demonstrate the performance of the proposed neural network.

An efficient neural approach to economic load dispatch in power systems

A neural approach to solve the problem defined by the economic load dispatch in power systems is presented in this paper, Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements the ability of neural networks to realize some complex nonlinear function makes them attractive for system optimization the neural networks applyed in economic load dispatch reported in literature sometimes fail to converge towards feasible equilibrium points the internal parameters of the modified Hopfield network developed here are computed using the valid-subspace technique These parameters guarantee the network convergence to feasible quilibrium points, A solution for the economic load dispatch problem corresponds to an equilibrium point of the network. Simulation results and comparative analysis in relation to other neural approaches are presented to illustrate efficiency of the proposed approach.

Repair Welding Effects on the Bending Fatigue Strength of AISI 4130 Aeronautical Steel used in a Critical to the Flight-Safety Structure

The aim of this study was to analyze the effect of successive TIG (tungsten inert gas) welding repairs on the reverse bending fatigue strength of AISI 4130 steel, which is widely used in components critical to the flight-safety. In order to simulate the abrupt maneuvers, wind bursts, motor vibration and helixes efforts, which generate cyclic bending loadings at the welded joints of a specific aircraft component called motor cradle, experimental reverse bending fatigue tests were carried out on specimens made from hot-rolled steel plate, 1.10 mm (0.043 in) thick, by mean of a SCHENK PWS equipment, with load ratio R = -1, under constant amplitude, at 30 Hz frequency and room temperature. It was observed that the bending fatigue strength decreases after the TIG (Tungsten Inert Gas) welding process application on AISI 4130 steel, with subsequent decrease due to re-welding sequence as well. Microstructural analyses and microhardness measurements on the base material, heat-affected zone (HAZ) and weld metal, as well as the effects of the weld bead geometry on the obtained results, have complemented this study.

Considerations about the welding repair effects on the structural integrity of an airframe critical to the flight-safety

Structures critical to the flight-safety are commonly submitted to several maintenance repairs at the welded joints in order to prolong the in-service life of aircrafts. The aim of this study is to analyze the effects of Tungsten Inert Gas (TIG) welding repair on the structural integrity of the AISI 4130 aeronautical steel by means of experimental fatigue crack growth tests in base-material, heat-affected zone (HAZ) and weld metal. The tests were performed on hot-rolled steel plate specimens, 0.89 mm thick, with load ratio R = 0.1, constant amplitude, at 10 Hz frequency and room temperature. Increase of the fracture resistance was observed in the weld metal but decreasing in the HAZ after repair. The results were associated to microhardness and microstructural changes with the welding sequence. (C) 2010 Published by Elsevier Ltd.

Efficient method for AC transmission network expansion planning

A combinatorial mathematical model in tandem with a metaheuristic technique for solving transmission network expansion planning (TNEP) using an AC model associated with reactive power planning (RPP) is presented in this paper. AC-TNEP is handled through a prior DC model while additional lines as well as VAr-plants are used as reinforcements to cope with real network requirements. The solution of the reinforcement stage can be obtained by assuming all reactive demands are supplied locally to achieve a solution for AC-TNEP and by neglecting the local reactive sources, a reactive power planning (RPP) will be managed to find the minimum required reactive power sources. Binary GA as well as a real genetic algorithm (RCA) are employed as metaheuristic optimization techniques for solving this combinatorial TNEP as well as the RPP problem. High quality results related with lower investment costs through case studies on test systems show the usefulness of the proposal when working directly with the AC model in transmission network expansion planning, instead of relaxed models. (C) 2010 Elsevier B.V. All rights reserved.

An Efficient Codification to Solve Distribution Network Reconfiguration for Loss Reduction Problem

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)