A multilevel model for the study of breastfeeding determinants in Brazil

The benefits of breastfeeding for the children`s health have been highlighted in many studies. The innovative aspect of the present study lies in its use of a multilevel model, a technique that has rarely been applied to studies on breastfeeding. The data reported were collected from a larger study, the Family Budget Survey-Pesquisa de Orcamentos Familiares, carried out between 2002 and 2003 in Brazil that involved a sample of 48 470 households. A representative national sample of 1477 infants aged 0-6 months was used. The statistical analysis was performed using a multilevel model, with two levels grouped by region. In Brazil, breastfeeding prevalence was 58%. The factors that bore a negative influence on breastfeeding were over four residents living in the same household [odds ratio (OR) = 0.68, 90% confidence interval (CI) = 0.51-0.89] and mothers aged 30 years or more (OR = 0.68, 90% CI = 0.53-0.89). The factors that positively influenced breastfeeding were the following: higher socio-economic levels (OR = 1.37, 90% CI = 1.01-1.88), families with over two infants under 5 years (OR = 1.25, 90% CI = 1.00-1.58) and being a resident in rural areas (OR = 1.25, 90% CI = 1.00-1.58). Although majority of the mothers was aware of the value of maternal milk and breastfed their babies, the prevalence of breastfeeding remains lower than the rate advised by the World Health Organization, and the number of residents living in the same household along with mothers aged 30 years or older were both factors associated with early cessation of infant breastfeeding before 6 months.

Signed likelihood ratio tests in the Birnbaum-Saunders regression model

The Birnbaum-Saunders regression model is becoming increasingly popular in lifetime analyses and reliability studies. In this model, the signed likelihood ratio statistic provides the basis for testing inference and construction of confidence limits for a single parameter of interest. We focus on the small sample case, where the standard normal distribution gives a poor approximation to the true distribution of the statistic. We derive three adjusted signed likelihood ratio statistics that lead to very accurate inference even for very small samples. Two empirical applications are presented. (C) 2010 Elsevier B.V. All rights reserved.

Predicting random effects with an expanded finite population mixed model

Prediction of random effects is an important problem with expanding applications. In the simplest context, the problem corresponds to prediction of the latent value (the mean) of a realized cluster selected via two-stage sampling. Recently, Stanek and Singer [Predicting random effects from finite population clustered samples with response error. J. Amer. Statist. Assoc. 99, 119-130] developed best linear unbiased predictors (BLUP) under a finite population mixed model that outperform BLUPs from mixed models and superpopulation models. Their setup, however, does not allow for unequally sized clusters. To overcome this drawback, we consider an expanded finite population mixed model based on a larger set of random variables that span a higher dimensional space than those typically applied to such problems. We show that BLUPs for linear combinations of the realized cluster means derived under such a model have considerably smaller mean squared error (MSE) than those obtained from mixed models, superpopulation models, and finite population mixed models. We motivate our general approach by an example developed for two-stage cluster sampling and show that it faithfully captures the stochastic aspects of sampling in the problem. We also consider simulation studies to illustrate the increased accuracy of the BLUP obtained under the expanded finite population mixed model. (C) 2007 Elsevier B.V. All rights reserved.

Estimation of the mean quality-adjusted survival using a multistate model for the sojourn times

In clinical trials, it may be of interest taking into account physical and emotional well-being in addition to survival when comparing treatments. Quality-adjusted survival time has the advantage of incorporating information about both survival time and quality-of-life. In this paper, we discuss the estimation of the expected value of the quality-adjusted survival, based on multistate models for the sojourn times in health states. Semiparametric and parametric (with exponential distribution) approaches are considered. A simulation study is presented to evaluate the performance of the proposed estimator and the jackknife resampling method is used to compute bias and variance of the estimator. (C) 2007 Elsevier B.V. All rights reserved.

A proposed Model for Country Branding : an experimental Application on Nigeria

In the era of globalization, countries compete with each other for attention, respect and trust of potential consumers, investors, tourists, media and governments of other nations. Branding is the most powerful tool that a nation can utilize for effective differentiation strategies and for creating competitive advantage over other nations. Unfortunately, not every nations or destination marketers have a broad understanding of the concept of branding and how a country can be successfully branded. Hence, this study has proposed a model that could be used as a valuable guide for country branding. Also the model is recommended for countries struggling with image crisis; on the mission to improve the image internationally. Nigeria is a good example of countries with image crisis; it is one of the most populated countries in the world with a population of about 160 million inhabitants and growth rate of 2.553percent annually. Despite the abundant resources (e.g. coal, petroleum, natural gas etc.) that the nation is endowed with, it is quite disappointing that the population below poverty line is still at the alarming rate of 70percent of the total population. The mismanagement and poor leadership of the nation characterised by corruption, fraud, embezzlement of public fund etc. has culminated into serious image crisis that is slowing down the potential for investment and economic growth. However, there has been series of image rebranding campaigns but no tangible achievement has been recorded. It is quite questionable though, if image rebranding will provide the kind of future that Nigeria envisaged, considering the socio-political situation and the economic imbalance; compounded by the obvious fact that the nation has no known brand. Therefore, this paper argues that there is need to redirect the effort invested on image rebranding to the creation of a unique and competitive brand for the country. It was established from the study that a nation’s brand is capable of improving the reputation of the nation as well as stimulate the expectation of the target audience. However, it was also established from the study that a wrong approach to branding could mislead the target audience and attract negative publicity. Hence, as a contribution of the study to the field of branding, a model was proposed as a functional guide for country branding. Also, considering the abysmal performance of Nigeria’s image in the international community and to strengthen the argument that brand creation is required for the country; an experimental application of the proposed model was conducted using Nigeria as the case country. The first phase of the model suggested a major improvement in the society; this is required to further enhance the strengths of the country and to motivate the much needed community participation and confidence in the brand creation. It is the conclusion of the study that a strong nation brand can offset the image problem if it is built on something concrete, genuine, and uniquely identifiable with the country, capable of connecting to the cognitive psychology of the target audience.

Simulation model using meta heuristic algorithms for achieving optimal arrangement of storage bins in a sawmill yard

Bin planning (arrangements) is a key factor in the timber industry. Improper planning of the storage bins may lead to inefficient transportation of resources, which threaten the overall efficiency and thereby limit the profit margins of sawmills. To address this challenge, a simulation model has been developed. However, as numerous alternatives are available for arranging bins, simulating all possibilities will take an enormous amount of time and it is computationally infeasible. A discrete-event simulation model incorporating meta-heuristic algorithms has therefore been investigated in this study. Preliminary investigations indicate that the results achieved by GA based simulation model are promising and better than the other meta-heuristic algorithm. Further, a sensitivity analysis has been done on the GA based optimal arrangement which contributes to gaining insights and knowledge about the real system that ultimately leads to improved and enhanced efficiency in sawmill yards. It is expected that the results achieved in the work will support timber industries in making optimal decisions with respect to arrangement of storage bins in a sawmill yard.

Reuse-based test planning for core-based systems-on-chip

Electronic applications are currently developed under the reuse-based paradigm. This design methodology presents several advantages for the reduction of the design complexity, but brings new challenges for the test of the final circuit. The access to embedded cores, the integration of several test methods, and the optimization of the several cost factors are just a few of the several problems that need to be tackled during test planning. Within this context, this thesis proposes two test planning approaches that aim at reducing the test costs of a core-based system by means of hardware reuse and integration of the test planning into the design flow. The first approach considers systems whose cores are connected directly or through a functional bus. The test planning method consists of a comprehensive model that includes the definition of a multi-mode access mechanism inside the chip and a search algorithm for the exploration of the design space. The access mechanism model considers the reuse of functional connections as well as partial test buses, cores transparency, and other bypass modes. The test schedule is defined in conjunction with the access mechanism so that good trade-offs among the costs of pins, area, and test time can be sought. Furthermore, system power constraints are also considered. This expansion of concerns makes it possible an efficient, yet fine-grained search, in the huge design space of a reuse-based environment. Experimental results clearly show the variety of trade-offs that can be explored using the proposed model, and its effectiveness on optimizing the system test plan. Networks-on-chip are likely to become the main communication platform of systemson- chip. Thus, the second approach presented in this work proposes the reuse of the on-chip network for the test of the cores embedded into the systems that use this communication platform. A power-aware test scheduling algorithm aiming at exploiting the network characteristics to minimize the system test time is presented. The reuse strategy is evaluated considering a number of system configurations, such as different positions of the cores in the network, power consumption constraints and number of interfaces with the tester. Experimental results show that the parallelization capability of the network can be exploited to reduce the system test time, whereas area and pin overhead are strongly minimized. In this manuscript, the main problems of the test of core-based systems are firstly identified and the current solutions are discussed. The problems being tackled by this thesis are then listed and the test planning approaches are detailed. Both test planning techniques are validated for the recently released ITC’02 SoC Test Benchmarks, and further compared to other test planning methods of the literature. This comparison confirms the efficiency of the proposed methods.

Innovation districts: an investigation of the replication of the 22@ Barcelona’s Model in Boston

In 2000, the city of Barcelona launched 22@ Barcelona, dubbed the innovation district. The city sees the project as a means to accelerate Barcelona’s transition toward the knowledge economy. Other cities around the world have since followed the example of Barcelona, building or planning to build their own innovation districts. Boston began to establish its innovation district in 2010. Cities’ ultimate goal for these initiatives is to become more innovative and thus more competitive. Innovative districts are different from technology parks in that they aim to respond to a new economic paradigm in which economic production flows back to cities. The 22@ Barcelona model involves theoretical designs regarding five layers of innovation: economics, urban planning, productive, innovative, and creative. The comparative approach between 22@ Barcelona and Boston’s Innovation District intends to highlight the similarities and differences between those two innovation districts as well as providing a framework to define innovation districts.

A novel neural model to electrical load forecasting in transformers

The paper describes a novel neural model to electrical load forecasting in transformers. The network acts as identifier of structural features to forecast process. So that output parameters can be estimated and generalized from an input parameter set. The model was trained and assessed through load data extracted from a Brazilian Electric Utility taking into account time, current, tension, active power in the three phases of the system. The results obtained in the simulations show that the developed technique can be used as an alternative tool to become more appropriate for planning of electric power systems.

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.

A Bilevel Approach to Transmission Expansion Planning Within a Market Environment

We present a bilevel model for transmission expansion planning within a market environment, where producers and consumers trade freely electric energy through a pool. The target of the transmission planner, modeled through the upper-level problem, is to minimize network investment cost while facilitating energy trading. This upper-level problem is constrained by a collection of lower-level market clearing problems representing pool trading, and whose individual objective functions correspond to social welfare. Using the duality theory the proposed bilevel model is recast as a mixed-integer linear programming problem, which is solvable using branch-and-cut solvers. Detailed results from an illustrative example and a case study are presented and discussed. Finally, some relevant conclusions are drawn.

Primary power distribution systems planning taking into account reliability, operation and expansion costs

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Evaluation of hybrid models for static and multistage transmission system planning

Neste trabalho é analisada a aplicação de algoritmos heurísticos para o Modelo Híbrido Linear - Hybrid Linear Model (HLM) - no problema de planejamento da expansão de sistemas de transmissão. O HLM é um modelo relaxado que ainda não foi suficientemente explorado. Assim, é realizada uma análise das características do modelo matemático e das técnicas de solução que podem ser usadas para resolver este tipo de modelo. O trabalho analisa em detalhes um algoritmo heurístico construtivo para o HLM e faz uma extensão da modelagem e da técnica de solução para o planejamento multi-estágio da expansão de sistemas de transmissão. Dentro deste contexto, também é realizada uma avaliação da qualidade das soluções encontradas pelo HLM e as possibilidades de aplicação deste modelo em planejamento de sistemas de transmissão. Finalmente, são apresentados testes com sistemas conhecidos na literatura especializada.

Rapid Prototyping applied to surgical planning for correcting craniofacial malformations in wild animals. A case study of a brazilian fox

Veterinary surgery for treatment of wild animals is becoming an increasingly demanding task because it involves animals of different anatomy, many of them are already stressed and treatment must be performed to the highest standard in the minimum period of time. Craniofacial alterations may occur for three main reasons: genetic, functional or a combination of both. It is possible to modify the functional cause using intraoral devices like inclined plane. The treatment planning can be made based on virtual 3D models and rapid prototyping. An approximately 9 months old, 3.7 kg male Brazilian fox (Lycalopex vetulus) was referred to the Veterinary Hospital. Physical examination showed malocclusion with a deviation of the mandible to the right side. The virtual 3D model of the head was generated based on CT image data. The 3D models and rapid prototyping opened up new possibilities for the surgical planning and treatment of wild animals.

Assessment of aquatic plants in the reservoirs of AES-Tiete and development of an integrated control model for the most important species

The general objective of this work was to develop a monitoring and management model for aquatic plants that could be used in reservoir cascades in Brazil, using the reservoirs of AES-Tiete as a study case. The investigations were carried out at the reservoirs of Barra-Bonita, Bariri, Ibitinga, Promissao, and Nova-Avanhandava, located in the Tiete River Basin; Agua Vermelha, located in the Grande River Basin; Caconde, Limoeiro, and Euclides da Cunha, which are part of the Pardo River Basin; and the Mogi-Guacu reservoir, which belongs to the Mogi-Guacu River basin. The main products of this work were: development of techniques using satellite-generated images for monitoring and planning aquatic plant control; planning and construction of a boat to move floating plant masses and an airboat equipped with a DGPS navigation and application flow control system. Results allowed to conclude that the occurrence of all types of aquatic plants is directly associated with sedimentation process and, consequently, with nutrient and light availability. Reservoirs placed at the beginning of cascades are more subject to sedimentation and occurrence of marginal, floating and emerged plants, and are the priority when it comes to controlling these plants, since they provide a supply of weeds for the other reservoirs. Reservoirs placed downstream show smaller amounts of water-suspended solids, with greater transmission of light and occurrence of submerged plants.