In-line rheo-optical characterization during small-scale polymer processing and compounding

As increasingly more sophisticated materials and products are being developed and times-to-market need to be minimized, it is important to make available fast response characterization tools using small amounts of sample, capable of conveying data on the relationships between rheological response, process-induced material structure and product characteristics. For this purpose, a single / twin-screw mini-extrusion system of modular construction, with well-controlled outputs in the range 30-300 g/h, was coupled to a in- house developed rheo-optical slit die able to measure shear viscosity and normal-stress differences, as well as performing rheo-optical experiments, namely small angle light scattering (SALS) and polarized optical microscopy (POM). In addition, the mini-extruder is equipped with ports that allow sample collection, and the extrudate can be further processed into products to be tested later. Here, we present the concept and experimental set-up [1, 2]. As a typical application, we report on the characterization of the processing of a polymer blend and of the properties of extruded sheets. The morphological evolution of a PS/PMMA industrial blend along the extruder, the flow-induced structures developed and the corresponding rheological characteristics are presented, together with the mechanical and structural characteristics of produced sheets. The application of this experimental tool to other material systems will also be discussed.

Implementation of a lean six sigma project in a production line

Companies from the motorcycles components branch are dealing with a dynamic environment, resulting from the introduction of new products and the increase of market demand. This dynamic environment requires frequent changes in production lines and requires flexibility in the processes, which can cause reductions in the level of quality and productivity. This paper presents a Lean Six Sigma improvement project performed in a production line of the company's machining sector, in order to eliminate losses that cause low productivity, affecting the fulfillment of the production plan and customer satisfaction. The use of Lean methodology following the DMAIC stages allowed analyzing the factors that influence the line productivity loss. The major problems and causes that contribute to a reduction on productivity and that were identified in this study are the lack of standardization in the setup activities and the excessive stoppages for adjustment of the processes that caused an increase of defects. Control charts, Pareto analysis and cause-and-effect diagrams were used to analyze the problem. On the improvement stage, the changes were based on the reconfiguration of the line layout as well as the modernization of the process. Overall, the project justified an investment in new equipment, the defective product units were reduced by 84% and an increase of 29% of line capacity was noticed.

Off-line simulation inspires insight: a neurodynamics approach to efficient robot task learning

There is currently an increasing demand for robots able to acquire the sequential organization of tasks from social learning interactions with ordinary people. Interactive learning-by-demonstration and communication is a promising research topic in current robotics research. However, the efficient acquisition of generalized task representations that allow the robot to adapt to different users and contexts is a major challenge. In this paper, we present a dynamic neural field (DNF) model that is inspired by the hypothesis that the nervous system uses the off-line re-activation of initial memory traces to incrementally incorporate new information into structured knowledge. To achieve this, the model combines fast activation-based learning to robustly represent sequential information from single task demonstrations with slower, weight-based learning during internal simulations to establish longer-term associations between neural populations representing individual subtasks. The efficiency of the learning process is tested in an assembly paradigm in which the humanoid robot ARoS learns to construct a toy vehicle from its parts. User demonstrations with different serial orders together with the correction of initial prediction errors allow the robot to acquire generalized task knowledge about possible serial orders and the longer term dependencies between subgoals in very few social learning interactions. This success is shown in a joint action scenario in which ARoS uses the newly acquired assembly plan to construct the toy together with a human partner.

Exploring the role of O-Mannosylation in the modulation of E-Cadherin function in Gastric Cancer cell line models

Dissertação de mestrado em Bioquímica Aplicada – Biomedicina

Estudo das tecnologias de interatividade no processo de compra em contexto das lojas de vestuário on-line

Dissertação de mestrado em Design de Comunicação de Moda

Single line for assembly just-in-sequence multiple models

Programa Doutoral em Líderes para as Indústrias Tecnológicas

Brazelton Neonatal Behavioral Assessment Scale: a psychometric study in a Portuguese sample

Background: The Neonatal Behavioral Assessment Scale (NBAS, Brazelton & Nugent, 1995) is an instrument conceived to observe the neonatal neurobehavior. Data analysis is usually performed by organizing items into groups. The most widely used data reduction for the NBAS was developed by Lester, Als, and Brazelton (1982). Objective: Examine the psychometric properties of the NBAS items in a sample of 213 Portuguese infants. Method: The NBAS was performed in the first week of infant life (3 days±2) and in the seventh week of life (52 days±5). Results: Principal component analyses yielded a solution of four components explaining 55.13% of total variance. Construct validity was supported by better neurobehavioral performance of 7-week-old infants compared with 1-week-old infants. Conclusion: Changes in the NBAS structure for the Portuguese sample are suggested compared to Lester factors in order to reach better internal consistency of the scale.

Comorbid depression and anxiety effects on pregnancy and neonatal outcome

The effects of comorbid depression and anxiety were compared to the effects of depression alone and anxiety alone on pregnancy mood states and biochemistry and on neonatal outcomes in a large multi-ethnic sample. At the prenatal period the comorbid and depressed groups had higher scores than the other groups on the depression measure. But, the comorbid group had higher anxiety, anger and daily hassles scores than the other groups, and they had lower dopamine levels. As compared to the non-depressed group, they also reported more sleep disturbances and relationship problems. The comorbid group also experienced a greater incidence of prematurity than the depressed, the high anxiety and the non-depressed groups. Although the comorbid and anxiety groups were lower birthweight than the non-depressed and depressed groups, the comorbid group did not differ from the depressed and anxiety groups on birth length. The neonates of the comorbid and depressed groups had higher cortisol and norepinephrine and lower dopamine and serotonin levels than the neonates of the anxiety and non-depressed groups as well as greater relative right frontal EEG. These data suggest that for some measures comorbidity of depression and anxiety is the worst condition (e.g., incidence of prematurity), while for others, comorbidity is no more impactful than depression alone.

Prenatal dopamine and neonatal behavior and biochemistry

Depressed pregnant women (N=126) were divided into high and low prenatal maternal dopamine (HVA) groups based on a tertile split on their dopamine levels at 20 weeks gestation. The high versus the low dopamine group had lower Center for Epidemiological Studies-Depression Scale (CES-D) scores, higher norepinephrine levels at the 20-week gestational age visit and higher dopamine and serotonin levels at both the 20- and the 32-week gestational age visits. The neonates of the mothers with high versus low prenatal dopamine levels also had higher dopamine and serotonin levels as well as lower cortisol levels. Finally, the neonates in the high dopamine group had better autonomic stability and excitability scores on the Brazelton Neonatal Behavior Assessment Scale. Thus, prenatal maternal dopamine levels appear to be negatively related to prenatal depression scores and positively related to neonatal dopamine and behavioral regulation, although these effects are confounded by elevated serotonin levels.

Prenatal serotonin and neonatal outcome: brief report

The purpose of the present study was to determine the relationships between prenatal serotonin levels and other biochemical values during pregnancy as well as their relationships to neonatal biochemical and behavioral variables. To address that question, the pregnant women were divided into the top and bottom tertiles based on their serotonin levels at 20 weeks gestational age.

Chronic prenatal depression and neonatal outcome

Four hundred and thirty pregnant women were recruited at approximately 22 weeks gestation at prenatal clinics. Of these, 86 (20%) were diagnosed as depressed. The women were seen again at approximately 32 weeks gestation and after delivery. Chronicity of depression was evidenced by continuing high depression scores in those women diagnosed as depressed. Comorbid problems were chronically high anxiety, anger, sleep disturbance, and pain scores. Less optimal outcomes for the depressed women included lower gestational age and lower birthweight of their newborns.

In-line rheo-optical microstructural characterization of complex polymer systems

Tese de Doutoramento em Ciência e Engenharia de Polímeros e Compósitos.

A tradução de negócios e projetos on-line na empresa Bloomidea

Relatório de estágio de mestrado em Tradução e Comunicação Multilingue