Functionalized-radiolabeled hydroxyapatite/tenorite nanoparticles as theranostic agents for osteosarcoma

Hydroxyapatite (HA) nanoparticles (NPs) doped with different radioisotopes for use as theranostic systems play an important role in scientific research nowadays due to their ability to simultaneously act in the treatment and diagnosis of various types of cancers. In this work, we describe the synthesis and characterization of a hydroxyapatite/tenorite nanocomposite functionalized with folic acid, representing a nanotheranostic material with potential for application as an agent in positron emission tomography imaging systems and to act specifically in the treatment and diagnosis of osteosarcoma. ⁶⁴Cu and ³²P were produced by nuclear activation in the TRIGA reactor at CDTN. The obtained samples were characterized by XRD with Rietveld refinement, XAFS, SEM, BET, TGA, FTIR, CHN, ICP-AES, XPS and gamma spectroscopy. We investigated how CuO grows in HA NPs, the stability of the interactions between CuO and HA constituents and the interactions between folic acid and the surface of the HA NPs. The results indicate the formation of a second phase (tenorite) besides hydroxyapatite, and that the interactions between the two phases are stable, resulting in a nanocomposite. Furthermore, the activation of ⁶⁴Cu and ³²P inside the HA matrix, through the exposition to a neutron flux, produces a theranostic material of interest for biological tests.     

Designing robust volunteer-based evolutionary algorithms

This paper tackles the design of scalable and fault-tolerant evolutionary algorithms computed on volunteer platforms. These platforms aggregate computational resources from contributors all around the world. Given that resources may join the system only for a limited period of time, the challenge of a volunteer-based evolutionary algorithm is to take advantage of a large amount of computational power that in turn is volatile. The paper analyzes first the speed of convergence of massively parallel evolutionary algorithms. Then, it provides some guidance about how to design efficient policies to overcome the algorithmic loss of quality when the system undergoes high rates of transient failures, i.e. computers fail only for a limited period of time and then become available again. In order to provide empirical evidence, experiments were conducted for two well-known problems which require large population sizes to be solved, the first based on a genetic algorithm and the second on genetic programming. Results show that, in general, evolutionary algorithms undergo a graceful degradation under the stress of losing computing nodes. Additionally, new available nodes can also contribute to improving the search process. Despite losing up to 90 % of the initial computing resources, volunteer-based evolutionary algorithms can find the same solutions in a failure-prone as in a failure-free run.     

Impedance spectra for aluminum 7075 during the early stages of immersion in sodium chloride

The impedance spectra obtained at short exposure times for Al 7075-T6 immersed in 0.5 N NaCl do not agree with the pitting model proposed by Mansfeld and co-workers. Instead of a transmission line impedance, an inductive loop is observed at low frequencies. This result is due to the non-linearity of the system at short exposure times, when E_corr is close to E_pit. The application of the anodic portion of the ac signal causes this non-linear behavior. The observed impedance is therefore a system response and not a true impedance. For longer exposure times agreement with the pitting model is observed.     

At-Site Flood Frequency Analysis Coupled with Multiparameter Probability Distributions

The proper design of hydraulic structures as well as river basin management are directly dependent on adequate estimates of maximum streamflow, preferably obtained from long historical series. However, the scarce hydrological monitoring, recurrent in developing countries and the need for estimates associated with high return periods (RPs) have led to the use of estimation methods based statistical procedures, such as at-site flood frequency analysis. This study presents a framework for at-site flood frequency analysis coupled with multiparameter probability distribution functions (PDFs) (GEV, LN3, PE3, GLO, GPA, KAP and WAK), in which all the statistical procedures are derived from L-moments, in order to investigate the applicability of these PDFs in comparison to those of 2-parameters (EV1, LN2 and Gamma). The modeling framework was evaluated considering 106 maximum annual streamflow (MAS) series for the Rio Grande do Sul State - Brazil. PDFs’ goodness-of-fit was studied in accordance with the Anderson-Darling test. It can be concluded that: i) the multiparameter distributions, especially KAP and WAK, had performance superior to the traditional 2-parameter distributions, providing a greater number of historical series better adjusted by such multiparameter PDFs; ii) shorter series were usually better represented by GEV when compared to the other PDFs, which is an important characteristic when long historical series are not frequently available; and iii) the quantile estimates derived from multiparameter PDFs presented lower Relative Absolute Error, thus emphasizing the importance of using such PDFs in water resources management and engineering projects.