Extracellular Vesicles in CNS Developmental Disorders

The central nervous system (CNS) is the most complex structure in the body, consisting of multiple cell types with distinct morphology and function. Development of the neuronal circuit and its function rely on a continuous crosstalk between neurons and non-neural cells. It has been widely accepted that extracellular vesicles (EVs), mainly exosomes, are effective entities responsible for intercellular CNS communication. They contain membrane and cytoplasmic proteins, lipids, non-coding RNAs, microRNAs and mRNAs. Their cargo modulates gene and protein expression in recipient cells. Several lines of evidence indicate that EVs play a role in modifying signal transduction with subsequent physiological changes in neurogenesis, gliogenesis, synaptogenesis and network circuit formation and activity, as well as synaptic pruning and myelination. Several studies demonstrate that neural and non-neural EVs play an important role in physiological and pathological neurodevelopment. The present review discusses the role of EVs in various neurodevelopmental disorders and the prospects of using EVs as disease biomarkers and therapeutics.     

Evaluation of Atmospheric and Vacuum Residues Using Molecular Distillation and Optimization

The term atmospheric residue describes the material at the bottom of the atmospheric distillation tower having a lower boiling point limit of about 340°C; the term vacuum residue (heavy petroleum fractions) refers to the bottom of the vacuum distillation, which has an atmospheric equivalent boiling point (AEBP) above 540°C. In this work, the objective is to evaluate the behavior of different kinds of Brazilian atmospheric and vacuum residues using molecular distillation. The Falling Film Molecular Distillator was used. For the results obtained through this process, a significant range of temperature can be explored avoiding the thermal decomposition of the material. So these results are very important to the refinery decisions and improvements. The Experimental Factorial Design results showed that the temperature has more influence on the process than the feed flow rate, when a higher percentage of distillate is required.     

Approximation of ill-posed boussinesq equations

In this paper we compare the dynamics on the centre manifold of the solutions of an ill-posed Boussinesq equation with a well-posed version. We show that the dynamics in the centre manifold of the ill-posed equation tracks the dynamics of the well-posed equation. Our results give partial justification to the long-wave perturbation theory.     

Development of a predictive model for polymer/solvent diffusion coefficient calculations

A new calculation procedure for free‐volume parameters is considered in this work by using viscosity prediction methods and the Levenberg‐Marquardt calculation scheme. All parameters used in the Vrentas–Duda free‐volume theory can be estimated from pure component properties. The prediction results are compared with experimental data for some polymer/solvent systems. The diffusion coefficient calculated by Vrentas–Duda theory can be used in the modeling of membrane separation processes. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

Lifetime Measurements on a High-Reliability RF-MEMS Contact Switch

Radio frequency microelectromechanical systems (RF MEMS) cantilever contact switches have been tested for lifetime. The mean cycles-to-failure measured on an ensemble of switches was 430 billion switch cycles. The longest lifetime exhibited without degradation of the switch was 914 billion switch cycles. The devices were switched at 20 kHz with an incident RF frequency of 10 GHz and an incident RF power of 20 dBm. Testing was performed continuously over a period of approximately 18 months. The switches were operated in a cold-switched mode.     

Image segmentation towards new image representation methods

Very low bit-rate video coding has recently become one of the most important areas of image communication and a large variety of applications have already been identified. Since conventional approaches are reaching a saturation point, in terms of coding efficiency, a new generation of video coding techniques, aiming at a deeper “understanding” of the image, is being studied. In this context, image analysis, particularly the identification of objects or regions in images (segmentation), is a very important step. This paper describes a segmentation algorithm based on split and merge. Images are first simplified using mathematical morphology operators, which eliminate perceptually less relevant details. The simplified image is then split according to a quad tree structure and the resulting regions are finally merged in three steps: merge, elimination of small regions and control of the number of regions.     

In vivo aging of gutta‐percha dental cone

Gutta‐percha cone is the most widely used material for root canal filling. The in vivo aging of this cone focus on the degradation of its main organic component, trans‐1,4‐polyisoprene, was studied. Aged cones (25 samples) from 2 to 30 years of root canal filling were extracted from different patients in the occasion of retreatment by mechanical way. The information about the aging time was given by the patients. Gel‐permeation chromatography (GPC) and infrared spectroscopy (FTIR) were the analytical techniques used. Polyisoprene degrades with time of aging, but in a slow process. Decrease in polymer molar mass from 5.7 × 10⁵ to 1.7 × 10⁵ g/mol was observed in polyisoprene from cone after 30 years of root canal filling and inside a noninfected tooth. In tooth with caries and periodontal infection, the decrease in molar mass is higher (4.6 × 10⁴ g/mol in cone with 10 years of aging). The production of carbonyl and hydroxyl groups in the aged material indicates that the process is oxidative, even in closed teeth. In these cases, the oxygen could be provided from tissue fluid. The degradation mechanism is complex and depends on many factors, besides time of root canal filling. The dental problem caused by the aging could be the production and migration of cytotoxic substances to periodontal ligament and the reduction on the canal sealing property due to the polymer weight loss. Both of them could contribute to the root canal treatment failure. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 100:4082–4088, 2006     

Improving process models by mining mappings of low-level events to high-level activities

While it is possible to analyze the run-time behavior of a business process through process mining techniques, in practice there is often a gap between the low-level nature of the events recorded in an event log and the high-level of abstraction at which the process is modeled. This makes it difficult to understand the recorded behavior in terms of the high-level activities in the process model. Also, it makes it difficult to improve the model based on run-time data about the process. In this work we present an approach to mine mappings between the events in the log and the activities in the model. These mappings can be used to generate suggestions of how the process model can be extended in order to capture the behavior recorded in the event log. Using a real-world and publicly available event log, we show how the approach can improve the model in a stepwise manner, until it covers all the behavior recorded in the event log.     

Nickel Activation for Hydrogenolysis Reaction on USY Zeolite

The effects of the SAR (14 and 38) and of the methodology of introduction of nickel (wetness impregnation and ion exchange) on catalyst activation were investigated in Ni/USY model catalysts submitted to two activation treatments: reduction (A) and reduction/calcination/reduction, successively (B). the catalysts prepared by wetness impregnation, a marked increase in the catalytic activity after treatment B was observed. On the basis of the catalyst efficiency toward ethane hydrogenolysis, the lower SAR catalyst presents a threefold higher activity. On the contrary, the catalysts prepared by ion exchange, as well as a model catalyst prepared by wetness impregnation over a USY exhaustively exchanged with nickel ions, do not present measurable increasing of the catalytic activity under the same activation conditions. Monitoring the catalyst activation by EXAFS indicates the formation of nickel clusters in the impregnated catalysts after activation treatment B, which should be responsible for the high catalytic activity. However, TEM images reveal a bimodal particle size distribution, with large (ca. 20 nm) and small nickel particles. Temperature-programmed reduction performed under the same conditions of catalyst activation suggests that only the small nickel particles are activated under the experimental conditions adopted in this work.     

Evaluation of optimisation techniques and control variable formulations for a batch cooling crystallization process

The mathematical optimisation of a batch cooling crystallization process is considered in this work. The objective is to minimize the standard deviation of the final crystal size distribution (CSD), which is an important feature in many industrial processes. The results with the problem written as a nonlinear programming and solved with the successive quadratic programming (SQP) coupled with the discretization of the control variable are compared with those obtained when SQP coupled with the parameterisation of the control variable is applied. Also it is proposed the implementation of the genetic algorithm (GA) coupled with parameterisation of the control variable. Extensive evaluations show that the SQP method is sensitive both to the parameterisation formulation and to the initial estimate. The solution with GA provided the control variable profile that leads to the minimum standard deviation of the final CSD. Nevertheless, it is a very time-consuming technique, which hampers its utilization in real time applications. However, its feature of global searching suggests its suitability in solving offline problems, in order to provide initial setup profiles. Bearing this in mind, it is proposed an algorithm which allows for the implementation of GA solution in a real time fashion, taking advantage of its robustness to find out the optimal solution.