Comparative effects of pyrolyzed oil shale and pyrolyzed burned oil shale used as fillers in poly(ethylene‐co‐vinyl alcohol)

Pyrolyzed oil shale (POS) obtained from the pyrolysis of bituminous rock was burned in a normal atmosphere (POSB) to remove the organic phase and then used as a filler in poly(ethylene‐co‐vinyl alcohol) (EVAL). The effects of vinyl alcohol content, POSB particle size, and POSB concentration on the composite were investigated through measurement of mechanical properties. Composites were prepared in a rotor mixer at 180°C. Stress–strain plots of compression‐molded composites showed synergic behavior of the mechanical properties with low concentrations (1–5 wt %) of POSB, regardless of particle size or type of EVAL. Such behavior suggests close packing and strong interactions between inorganic filler and polymer, with the effects reinforced by the mechanical properties. It was observed that the absence of the organic phase in the modified material improved the mechanical properties of the composites. Increasing the vinyl alcohol content improved the compatibility between polymer and filler in the EVAL/POS but did not affect the compatibility in EVAL/POSB composites. The relationship of mechanical and morphological behavior in the EVAL/POS and EVAL/POSB composites indicated that different factors were at play to explain the compatibility between the EVAL and the inorganic phase. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 99: 1859–1864, 2006     

Synthesis and x-ray diffraction characterization of nanocrystalline ZnO obtained by Pechini method

Nanocrystalline zinc oxide powders were successfully prepared by Pechini method. The polymeric precursors were prepared using zinc acetate and a mixed solution of citric acid and ethylene glycol as a chelating agent and reaction medium respectively. The polymeric precursors were calcined at temperatures from 500 to 900°C for 1 h. The resulting powders were characterized by x-ray powder diffraction, thermogravimetry, and Fourier-transform infrared spectroscopy. Well-crystallized zinc oxide was obtained at low-temperature about 500°C. The average crystallite size was estimated as 47–73 nm in the range of 500–900°C and the lattice parameters were compatible with the values found in literature. The text was submitted by the authors in English.     

Correction of long term joint contractures of the hand by distraction. A case report

Joint contractures are a common complication of hand trauma. The conventional treatment consists of arthrolysis, tenolysis and occasionally arthrodesis. Frequently, this does not achieve a good result, particularly when there has been a long delay in presentation. Progressive lengthening of a joint by distraction (joint distraction) allows the release of joint contractures even in cases of failure of traditional methods.We present a case of a delayed (20 years) work related traumatic flexion deformity of the PIP joint of the left index and middle fingers. This was the result of a complete division of both flexor tendons of both fingers.The range of movements, both active and passive, was limited to 90/100° in the index finger and 95/100° in the middle finger. Following joint distraction using our lengthening device (Antão™, Portugal) the patient was able to achieve an active and passive range of movements of 10/100° for the PIP joint of the index finger and 40/100° of the middle.This clinical case shows the simplicity and application of our technique for the correction of joint contractures.     

Learning in the combinatorial neural model

The combinatorial neural model (CNM) is a type of fuzzy neural network for classification problems. Learning in CNM is a complex task spanning the learning of input-neuron membership functions, the network topology and connection weights. We deal with these various aspects of learning in CNM, most notably with the learning of connection weights, whose complexity comes from the existence of nondifferentiable, nonconvex error functions associated with the learning process. We introduce several algorithms for weight learning. All the algorithms are based on "local" rules, and are therefore amenable to distributed/parallel implementations. Experimental results are provided on the large-scale problem of monitoring the deforestation of the Amazon region on satellite images. These results show that a hybrid CNM system outperforms previous results obtained with variations of error backpropagation techniques. In addition, this hybrid system has demonstrated robustness in the context under consideration.     

Robust mixture modeling based on scale mixtures of skew-normal distributions

A flexible class of probability distributions, convenient for modeling data with skewness behavior, discrepant observations and population heterogeneity is presented. The elements of this family are convex linear combinations of densities that are scale mixtures of skew-normal distributions. An EM-type algorithm for maximum likelihood estimation is developed and the observed information matrix is obtained. These procedures are discussed with emphasis on finite mixtures of skew-normal, skew-t, skew-slash and skew contaminated normal distributions. In order to examine the performance of the proposed methods, some simulation studies are presented to show the advantage of this flexible class in clustering heterogeneous data and that the maximum likelihood estimates based on the EM-type algorithm do provide good asymptotic properties. A real data set is analyzed, illustrating the usefulness of the proposed methodology.     

An algorithm for clock synchronization with the gradient property in sensor networks

We introduce a distributed algorithm for clock synchronization in sensor networks. Our algorithm assumes that nodes in the network only know their immediate neighborhoods and an upper bound on the network’s diameter. Clock-synchronization messages are only sent as part of the communication–assumed to be reasonably frequent–that already takes place among nodes. The algorithm has the gradient property of [R. Fan, N. Lynch, Gradient clock synchronization, Distributed Computing 18 (2006) 255–266], achieving an O(1)$O\left(1\right)$ worst-case skew between the logical clocks of neighbors. The algorithm’s actions are such that no constant lower bound exists on the rate at which logical clocks progress in time, and for this reason the lower bound of [R. Fan, N. Lynch, Gradient clock synchronization, Distributed Computing 18 (2006) 255–266; L. Meier, L. Thiele, Brief announcement: Gradient clock synchronization in sensor networks, in: Proceedings of the Twenty-Fourth Annual ACM Symposium on Principles of Distributed Computing, 2005, p. 238] that forbids a constant clock skew between neighbors does not apply.     

A MODIS assessment of the summer 2007 extent burned in Greece

Devastating fires affected Greece in the summer 2007, with the loss of more than 60 human lives, the destruction of more than 100 villages and hundreds of square kilometres of forest burned. This Letter presents a map of the extent burned and the approximate day of burning in Greece mapped by the MODIS burned area product for 22 June to 30 August 2007 and the burned areas mapped independently by the European Forest Fires Information Service (EFFIS). The characteristics of the two datasets, and an evaluation of the areas burned comparing the MODIS and EFFIS data for the same temporal interval are described.     

A model for learning objects adaptation in light of mobile and context-aware computing

The growth usage of mobile technologies and devices such as smartphones and tablets, and the almost ubiquitous wireless communication set the stage for the development of novel kinds of applications. One possibility is exploiting this scenario in the field of education, so creating more intelligent, flexible and customizable systems. Mobile devices can be used to help students to learn, considering their learning styles, surroundings, devices and profiles. In this way, the main goal of this article is to propose EduAdapt, an architectural model for the adaptation of learning objects considering device characteristics, learning style and other student’s context information. To make this adaptation we used inferences and rules in a proposed ontology, named OntoAdapt. We believe that such ontology can help recommending learning objects to students or adapt these objects according to the context (context-aware computing). We evaluate this proposal in two ways. Firstly, we used scenarios and metrics to assess the ontology. Secondly, we developed a prototype of EduAdapt model and submitted to a class of 20 students with the intention of evaluating the usability and adherence to adapted objects, resulting in a 78 % of acceptance. In brief, the evaluation presented encouraging results, indicating that the proposed model would be useful in the learning process.     

Rethinking universal accessibility: a broader approach considering the digital gap

The universal accessibility concept is usually formulated in terms that ignore the socioeconomic and sociopolitical contexts. Therefore, it has impact only on a small fraction of the global population of people with disabilities. This issue raises the need for a comprehensive approach that takes into account issues related to literacy, availability of technology, digital literacy, the use of minority languages, etc.