Assisted ventilation modes reduce the expression of lung inflammatory and fibrogenic mediators in a model of mild acute lung injury

The goal of the study was to compare the effects of different assisted ventilation modes with pressure controlled ventilation (PCV) on lung histology, arterial blood gases, inflammatory and fibrogenic mediators in experimental acute lung injury (ALI). Paraquat-induced ALI rats were studied. At 24 h, animals were anaesthetised and further randomized as follows (n = 6/group): (1) pressure controlled ventilation mode (PCV) with tidal volume (V (T)) = 6 ml/kg and inspiratory to expiratory ratio (I:E) = 1:2; (2) three assisted ventilation modes: (a) assist-pressure controlled ventilation (APCV1:2) with I:E = 1:2, (b) APCV1:1 with I:E = 1:1; and (c) biphasic positive airway pressure and pressure support ventilation (BiVent + PSV), and (3) spontaneous breathing without PEEP in air. PCV, APCV1:1, and APCV1:2 were set with P (insp) = 10 cmH(2)O and PEEP = 5 cmH(2)O. BiVent + PSV was set with two levels of CPAP [inspiratory pressure (P (High) = 10 cmH(2)O) and positive end-expiratory pressure (P (Low) = 5 cmH(2)O)] and inspiratory/expiratory times: T (High) = 0.3 s and T (Low) = 0.3 s. PSV was set as follows: 2 cmH(2)O above P (High) and 7 cmH(2)O above P (Low). All rats were mechanically ventilated in air and PEEP = 5 cmH(2)O for 1 h. Assisted ventilation modes led to better functional improvement and less lung injury compared to PCV. APCV1:1 and BiVent + PSV presented similar oxygenation levels, which were higher than in APCV1:2. Bivent + PSV led to less alveolar epithelium injury and lower expression of tumour necrosis factor-alpha, interleukin-6, and type III procollagen. In this experimental ALI model, assisted ventilation modes presented greater beneficial effects on respiratory function and a reduction in lung injury compared to PCV. Among assisted ventilation modes, Bi-Vent + PSV demonstrated better functional results with less lung damage and expression of inflammatory mediators.

Estimação em pequenos domínios

Neste artigo pretende-se apresentar algumas questões relacionadas com a estimação em domínios no âmbito de sondagens. São abordadas as etapas de planeamento e desenho da sondagem, sublinhando que o problema deve de ser visto numa perspectiva global. O ênfase é no entanto colocado na etapa de estimação, através de uma identificação abrangente de métodos de estimação, com referências às suas aplicações e qualidades relativas. É dada uma atenção especial ao problema de estimação em pequenos domínios, onde a dimensão das amostras é normalmente insuficiente para obter estimativas directas de apreciação aceitável.

Diagnóstico do nível de maturidade do processo de desenvolvimento de produtos: um estudo de caso em empresa calçadista

The process of product development (PPD) is a strategic factor in which companies seek to identify consumer needs. The relationship of the practices adopted, tools, techniques, among others, can determinate the maturity level of the company in this process. The purpose of this paper is to understand and diagnose the level of maturity of the PDP in footwear segment industry. For the case study, a company inserted into one of the largest poles of women’s footwear in Brazil, located in Jaú, São Paulo State, was researched. The diagnosis is based on the maturity levels of the unified model, reference in the process of product development, proposed by Rozenfeld et al. (2006). The application of the model assisted to diagnose the current maturity level of the company in this process, providing useful information to achieve higher levels of maturity in the PDP.

Parallel Problem Solving from Nature – PPSN XIV:14th International Conference, Edinburgh, UK, September 17-21, 2016, Proceedings

This book constitutes the refereed proceedings of the 14th International Conference on Parallel Problem Solving from Nature, PPSN 2016, held in Edinburgh, UK, in September 2016. The total of 93 revised full papers were carefully reviewed and selected from 224 submissions. The meeting began with four workshops which offered an ideal opportunity to explore specific topics in intelligent transportation Workshop, landscape-aware heuristic search, natural computing in scheduling and timetabling, and advances in multi-modal optimization. PPSN XIV also included sixteen free tutorials to give us all the opportunity to learn about new aspects: gray box optimization in theory; theory of evolutionary computation; graph-based and cartesian genetic programming; theory of parallel evolutionary algorithms; promoting diversity in evolutionary optimization: why and how; evolutionary multi-objective optimization; intelligent systems for smart cities; advances on multi-modal optimization; evolutionary computation in cryptography; evolutionary robotics - a practical guide to experiment with real hardware; evolutionary algorithms and hyper-heuristics; a bridge between optimization over manifolds and evolutionary computation; implementing evolutionary algorithms in the cloud; the attainment function approach to performance evaluation in EMO; runtime analysis of evolutionary algorithms: basic introduction; meta-model assisted (evolutionary) optimization. The papers are organized in topical sections on adaption, self-adaption and parameter tuning; differential evolution and swarm intelligence; dynamic, uncertain and constrained environments; genetic programming; multi-objective, many-objective and multi-level optimization; parallel algorithms and hardware issues; real-word applications and modeling; theory; diversity and landscape analysis.

Qualification of optical fiber sensors for the structural health monitoring of aerospace structures

In recent years, composite materials have revolutionized the design of many structures. Their superior mechanical properties and light weight make composites convenient over traditional metal structures for many applications. However, composite materials are susceptible to complex and challenging to predict damage behaviors due to their anisotropy nature. Therefore, structural Health Monitoring (SHM) can be a valuable tool to assess the damage and understand the physics underneath. Distributed Optical Fiber Sensors (DOFS) can be used to monitor several types of damage in composites. However, their implementation outside academia is still unsatisfactory. One of the hindrances is the lack of a rigorous methodology for uncertainty quantification, which is essential for the performance assessment of the monitoring system. The concept of Probability of Detection (POD) must function as the guiding light in this process. However, precautions must be taken since this tool was established for Non-Destructive Evaluation (NDE) rather than Structural Health Monitoring (SHM). In addition, although DOFS have been the object of numerous studies, a well-established POD methodology for their performance assessment is still missing. This thesis aims to develop a methodology to produce POD curves for DOFS in composite materials. The problem is analyzed considering several critical points, such as the strain transfer characterizing the DOFS and the development of an experimental and model-assisted methodology to understand the parameters that affect the DOFS performance.

Assisted Reproductive Technologies (ART) in a Model of Fertility Choice

This paper provides a simple theoretical framework to discuss the relationship between assisted reproductive technologies and the microeconomics of fertility choice. Individuals make choices of education and work along with decisions about whether and when to have children. Decisions regarding fertility are influenced by policy and labor market factors that affect the earnings opportunities of mothers and the costs of raising children. We show how observed differences in these economic factors across countries explain observed different fertility and childbearing age patterns. We then use the model to predict behavioral responses to biomedical improvements in assisted reproductive technologies, and hence the impact of these technologies on fertility.

Stent-assisted coiling of bifurcation aneurysms may improve endovascular treatment: a critical evaluation in an experimental model.

BACKGROUND AND PURPOSE: Endovascular treatment of wide-neck bifurcation aneurysms often results in incomplete occlusion or aneurysm recurrence. The goals of this study were to compare results of coil embolization with or without the assistance of self-expandable stents and to examine how stents may influence neointima formation. MATERIALS AND METHODS: Wide-neck bifurcation aneurysms were constructed in 24 animals and, after 4-6 weeks, were randomly allocated to 1 of 5 groups: 1) coil embolization using the assistance of 1 braided stent (n = 5); 2) coil embolization using the assistance of 2 braided stents in a Y configuration (n = 5); 3) coil embolization without stent assistance (n = 6); 4) Y-stenting alone (n = 4); and 5) untreated controls (n = 4). Angiographic results were compared at baseline and at 12 weeks, by using an ordinal scale. Neointima formation at the neck at 12 weeks was compared among groups by using a semiquantitative grading scale. Bench studies were performed to assess stent porosities. RESULTS: Initial angiographic results were improved with single stent-assisted coiling compared with simple coiling (P = .013). Angiographic results at 12 weeks were improved with any stent assistance (P = .014). Neointimal closure of the aneurysm neck was similar with or without stent assistance (P = .908), with neointima covering coil loops but rarely stent struts. Y-stent placement alone had no therapeutic effect. Bench studies showed that porosities can be decreased with stent compaction, but a relatively stable porous transition zone was a limiting factor. CONCLUSIONS: Stent-assisted coiling may improve results of embolization by allowing more complete initial coiling, but these high-porosity stents did not provide a scaffold for more complete neointimal closure of aneurysms.

CAMCR: Computer assisted mixture model analysis for capture-recapture count data

Population size estimation with discrete or nonparametric mixture models is considered, and reliable ways of construction of the nonparametric mixture model estimator are reviewed and set into perspective. Construction of the maximum likelihood estimator of the mixing distribution is done for any number of components up to the global nonparametric maximum likelihood bound using the EM algorithm. In addition, the estimators of Chao and Zelterman are considered with some generalisations of Zelterman’s estimator. All computations are done with CAMCR, a special software developed for population size estimation with mixture models. Several examples and data sets are discussed and the estimators illustrated. Problems using the mixture model-based estimators are highlighted.

CAMCR: Computer-Assisted Mixture model analysis for Capture–Recapture count data

Population size estimation with discrete or nonparametric mixture models is considered, and reliable ways of construction of the nonparametric mixture model estimator are reviewed and set into perspective. Construction of the maximum likelihood estimator of the mixing distribution is done for any number of components up to the global nonparametric maximum likelihood bound using the EM algorithm. In addition, the estimators of Chao and Zelterman are considered with some generalisations of Zelterman’s estimator. All computations are done with CAMCR, a special software developed for population size estimation with mixture models. Several examples and data sets are discussed and the estimators illustrated. Problems using the mixture model-based estimators are highlighted.

Legal LEGO: Model based computer assisted teaching in evidence courses

This paper describes the development of a new approach to the use of ICT for the teaching of courses in the interpretation and evaluation of evidence. It is based on ideas developed for the teaching of science to school children, in particular the importance of models and qualitative reasoning skills. In the first part, we make an analysis of the basis of current research into “evidence scholarship” and the demands such a system would have to meet. In the second part, we introduce the details of such a system that we developed initially to assist police in the interpretation of evidence.

Study of using marker assisted selection on a beef cattle breeding program by model comparison

A data set of a commercial Nellore beef cattle selection program was used to compare breeding models that assumed or not markers effects to estimate the breeding values, when a reduced number of animals have phenotypic, genotypic and pedigree information available. This herd complete data set was composed of 83,404 animals measured for weaning weight (WW), post-weaning gain (PWG), scrotal circumference (SC) and muscle score (MS), corresponding to 116,652 animals in the relationship matrix. Single trait analyses were performed by MTDFREML software to estimate fixed and random effects solutions using this complete data. The additive effects estimated were assumed as the reference breeding values for those animals. The individual observed phenotype of each trait was adjusted for fixed and random effects solutions, except for direct additive effects. The adjusted phenotype composed of the additive and residual parts of observed phenotype was used as dependent variable for models' comparison. Among all measured animals of this herd, only 3160 animals were genotyped for 106 SNP markers. Three models were compared in terms of changes on animals' rank, global fit and predictive ability. Model 1 included only polygenic effects, model 2 included only markers effects and model 3 included both polygenic and markers effects. Bayesian inference via Markov chain Monte Carlo methods performed by TM software was used to analyze the data for model comparison. Two different priors were adopted for markers effects in models 2 and 3, the first prior assumed was a uniform distribution (U) and, as a second prior, was assumed that markers effects were distributed as normal (N). Higher rank correlation coefficients were observed for models 3_U and 3_N, indicating a greater similarity of these models animals' rank and the rank based on the reference breeding values. Model 3_N presented a better global fit, as demonstrated by its low DIC. The best models in terms of predictive ability were models 1 and 3_N. Differences due prior assumed to markers effects in models 2 and 3 could be attributed to the better ability of normal prior in handle with collinear effects. The models 2_U and 2_N presented the worst performance, indicating that this small set of markers should not be used to genetically evaluate animals with no data, since its predictive ability is restricted. In conclusion, model 3_N presented a slight superiority when a reduce number of animals have phenotypic, genotypic and pedigree information. It could be attributed to the variation retained by markers and polygenic effects assumed together and the normal prior assumed to markers effects, that deals better with the collinearity between markers. (C) 2012 Elsevier B.V. All rights reserved.

Validation of a novel robotic-assisted partial nephrectomy surgical training model

What's known on the subject? and What does the study add? One area of particular growth for robotic surgery has been partial nephrectomy. Despite a perceived notion that robotic-assisted partial nephrectomy is more easily adaptable compared to laparoscopic partial nephrectomy, there is nonetheless an associated learning curve. Validated training models with a corresponding assessment method for robotic-assisted partial nephrectomy were previously unavailable. We have designed and validated a RAPN surgical model appropriate for resident and fellow training.

AALUMO: a user model ontology for ambient assisted living services supported in next-generation networks

Ambient Assisted Living (AAL) services are emerging as context-awareness solutions to support elderly people?s autonomy. The context-aware paradigm makes applications more user-adaptive. In this way, context and user models expressed in ontologies are employed by applications to describe user and environment characteristics. The rapid advance of technology allows creating context server to relieve applications of context reasoning techniques. Specifically, the Next Generation Networks (NGN) provides by means of the presence service a framework to manage the current user's state as well as the user's profile information extracted from Internet and mobile context. This paper propose a user modeling ontology for AAL services which can be deployed in a NGN environment with the aim at adapting their functionalities to the elderly's context information and state.