Carbon Nano���ber Type and Content Dependence of the Physical Properties of Carbon Nano���ber Reinforced Polypropylene Composites

The variation of the physical properties of four differ- ent carbon nano���bers (CNFs), based-polymer nano- composites incorporated in the same polypropylene (PP) matrix by twin-screw extrusion process was investigated. Nanocomposites fabricated with CNFs with highly graphitic outer layer revealed electrical isolation-to-conducting behaviors as function of CNF���s content. Nanocomposites fabricated with CNFs with an outer layer consisting on a disordered pyro- litically stripped layer, in contrast, revealed better mechanical performance and enhanced thermal sta- bility. Further, CNF���s incorporation into the polymer increased the thermal stability and the degree of crystallinity of the polymer, independently on the ���ller content and type. In addition, dispersion of the CNFs��� clusters in PP was analyzed by transmitted light opti- cal microscopy, and grayscale analysis (GSA). The results showed a correlation between the ���ller concentration and the variance, a parameter which measures quantitatively the dispersion, for all composites. This method indicated a value of 1.4 vol% above which large clusters of CNFs cannot be dispersed effectively and as a consequence only slight changes in mechanical performance are observed. Finally, this study establishes that for tailoring the physical properties of CNF based-polymer nanocomposites, both adequate CNFs structure and content have to be chosen.

Virtual simulation of the postsurgical cosmetic outcome in patientswith pectus excavatum

Pectus excavatum is the most common congenital deformity of the anterior chest wall, in which several ribs and the sternum grow abnormally. Nowadays, the surgical correction is carried out in children and adults through Nuss technic. This technic has been shown to be safe with major drivers as cosmesis and the prevention of psychological problems and social stress. Nowadays, no application is known to predict the cosmetic outcome of the pectus excavatum surgical correction. Such tool could be used to help the surgeon and the patient in the moment of deciding the need for surgery correction. This work is a first step to predict postsurgical outcome in pectus excavatum surgery correction. Facing this goal, it was firstly determined a point cloud of the skin surface along the thoracic wall using Computed Tomography (before surgical correction) and the Polhemus FastSCAN (after the surgical correction). Then, a surface mesh was reconstructed from the two point clouds using a Radial Basis Function algorithm for further affine registration between the meshes. After registration, one studied the surgical correction influence area (SCIA) of the thoracic wall. This SCIA was used to train, test and validate artificial neural networks in order to predict the surgical outcome of pectus excavatum correction and to determine the degree of convergence of SCIA in different patients. Often, ANN did not converge to a satisfactory solution (each patient had its own deformity characteristics), thus invalidating the creation of a mathematical model capable of estimating, with satisfactory results, the postsurgical outcome

Error bounds for low-rank approximations of the first exponential integral kernel

A hierarchical matrix is an efficient data-sparse representation of a matrix, especially useful for large dimensional problems. It consists of low-rank subblocks leading to low memory requirements as well as inexpensive computational costs. In this work, we discuss the use of the hierarchical matrix technique in the numerical solution of a large scale eigenvalue problem arising from a finite rank discretization of an integral operator. The operator is of convolution type, it is defined through the first exponential-integral function and, hence, it is weakly singular. We develop analytical expressions for the approximate degenerate kernels and deduce error upper bounds for these approximations. Some computational results illustrating the efficiency and robustness of the approach are presented.

The Main Determinants of the Use of the Cost Accounting System in Portuguese Local Government

This paper explores the main determinants of the use of the cost accounting system (CAS) in Portuguese local government (PLG). Regression analysis is used to study the fit of a model of accounting changes in PLG, focused on cost accounting systems oriented to activities and outputs. Based on survey data gathered from PLG, we have found that the use of information in decision-making and external reporting is still a mirage. We obtain evidence about the influence of the internal organizational context (especially the lack of support and difficulties in the CAS implementation) in the use for internal purposes, while the institutional environment (like external pressures to implement the CAS) appears to be more deterministic of the external use. Results strengthen the function of external reporting to legitimate the organization���s activities to external stakeholders. On the other hand, some control variables (like political competition, usefulness and experience) also evidence some explanatory power in the model. Some mixed results were found that appeal to further research in the future. Our empirical results contribute to understand the importance of interconnecting the contingency and institutional approaches to gain a clear picture of cost accounting changes in the public sector.