Current advances concerning the most cited metal ions doped bioceramics and silicate-based bioactive glasses for bone tissue engineering

Studies related to biomaterials that stimulate the repair of living tissue have increased considerably, improving the quality of many people's lives that require surgery due to traumatic accidents, bone diseases, bone defects, and reconstructions. Among these biomaterials, bioceramics and bioactive glasses (BGs) have proved to be suitable for coating materials, cement, scaffolds, and nanoparticles, once they present good biocompatibility and degradability, able to generate osteoconduction on the surrounding tissue. However, the role of biomaterials in hard tissue engineering is not restricted to a structural replacement or for guiding tissue regeneration. Nowadays, it is expected that biomaterials develop a multifunctional role when implanted, orchestrating the process of tissue regeneration and providing to the body the capacity to heal itself. In this way, the incorporation of specific metal ions in bioceramics and BGs structure, including magnesium, silver, strontium, lithium, copper, iron, zinc, cobalt, and manganese are currently receiving enhanced interest as biomaterials for biomedical applications. When an ion is incorporated into the bioceramic structure, a new category of material is created, which has several unique properties that overcome the disadvantages of primitive material and favors its use in different biomedical applications. The doping can enhance handling properties, angiogenic and osteogenic performance, and antimicrobial activity. Therefore, this review aims to summarize the effect of selected metal ion dopants into bioceramics and silicate-based BGs in bone tissue engineering. Furthermore, new applications for doped bioceramics and BGs are highlighted, including cancer treatment and drug delivery.     

Pre-operational environmental survey at the uranium mine and mill site,Poços de Caldas,Minas Gerais,Brazil

The first Brazilian uranium mine and mill are located on the Poços de Caldas plateau, in the Central State of Minas Gerais. The pre-operational environmental survey was carried out over a period of two years by the Brazilian Nuclear Energy Commission (CNEN), through the Instituto de Radioproteção e Dosimetria (IRD). The selection of the materials to be monitored, the sampling points and the radionuclides to be analysed were based on critical parameters taking into account the meteorological and hydrological characteristics of the site as well as land use. The results obtained are sufficient to characterize the environmental background of the area, and will allow an assessment of the environmental impact due to the operation of the facility and an evaluation of the adequacy of the effluent emmission control measures. In relation to their contribution to the population dose, the results indicated that ²²⁶Ra and ²¹⁰Pb will be the important radionuclides.     

Electrochemical behaviour of Invar in phosphate solutions at pH=6.0

Electrochemical studies were carried out with disk electrodes of Invar (Fe-36%Ni) in phosphate solution at pH 6.0, using cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) techniques, comparing the results with those for low carbon steel and pure Ni. Invar shows a reduced corrosion when compared to carbon steel in the weakly inhibitive solution though inferior to pure Ni. Phosphate anion is responsible for the formation of a protecting and stable film on the alloy surface at pH 6.0.Cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) with Invar disk electrodes (Fe-36%Ni) in phosphate solutions at pH=6.0 were carried out. Results were compared with those of carbon steel and pure Ni.     

Inductive Model Generation for Text Classification Using a Bipartite Heterogeneous Network

Algorithms for numeric data classification have been applied for text classification. Usually the vector space model is used to represent text collections. The characteristics of this representation such as sparsity and high dimensionality sometimes impair the quality of general-purpose classifiers. Networks can be used to represent text collections, avoiding the high sparsity and allowing to model relationships among different objects that compose a text collection. Such network- based representations can improve the quality of the classification results. One of the simplest ways to represent textual collections by a network is through a bipartite heterogeneous network, which is composed of objects that represent the documents connected to objects that represent the terms. Heterogeneous bipartite networks do not require computation of similarities or relations among the objects and can be used to model any type of text collection. Due to the advantages of representing text collections through bipartite heterogeneous networks, in this article we present a text classifier which builds a classification model using the structure of a bipartite heterogeneous network. Such an algorithm, referred to as IMBHN （Inductive Model Based on Bipartite Heterogeneous Network）, induces a classification model assigning weights to objects that represent the terms for each class of the text collection. An empirical evaluation using a large amount of text collections from different domains shows that the proposed IMBHN algorithm produces significantly better results than k-NN, C4.5, SVM, and Naive Bayes algorithms.     

OpenCOPI: middleware integration for Ubiquitous Computing

In this paper, we present OpenCOPI (Open COntext Platform Integration), a Service-Oriented Architecture-based middleware platform that supports the integration of services provided by distinct sources, ranging from services offered by simple systems to more complex services provided by context-provision middleware. OpenCOPI offers selection and composition mechanisms to, respectively, select and compose services provided by different sources, considering applications of both Quality of Service and Quality of Context requirements. It also offers an adaptation mechanism that enables to adapt the application execution due to service failures, service quality fluctuation and user mobility. OpenCOPI allows the definition of applications in a higher abstraction level by the specification of a semantic workflow that contains abstract activities. This paper illustrates the use of OpenCOPI in an application from the Gas & Oil Industry and it also shows the evaluation of the main mechanisms of OpenCOPI: the service selection, composition, adaptation and workflow execution.     

Analysis of surface integrity for minimum quantity lubricant—MQL in grinding

The quality of machined components is currently of high interest, for the market demands mechanical components of increasingly high performance, not only from the standpoint of functionality but also from that of safety. Components produced through operations involving the removal of material display surface irregularities resulting not only from the action of the tool itself, but also from other factors that contribute to their superficial texture. This texture can exert a decisive influence on the application and performance of the machined component. This article analyzes the behavior of the minimum quantity lubricant (MQL) technique and compares it with the conventional cooling method. To this end, an optimized fluid application method was devised using a specially designed nozzle, by the authors, through which a minimum amount of oil is sprayed in a compressed air flow, thus meeting environmental requirements. This paper, therefore, explores and discusses the concept of the MQL in the grinding process. The performance of the MQL technique in the grinding process was evaluated based on an analysis of the surface integrity (roughness, residual stress, microstructure and microhardness). The results presented here are expected to lead to technological and ecological gains in the grinding process using MQL.