Hydroxyapatite nanoparticles formed under a wet mechanochemical method.

Hydroxyapatite (HA) nanoparticles were synthesized using a wet mechanochemical method without a calcination process. Dicalcium phosphate dihydrate (CaHPO4 ·2H2 O) and calcium carbonate (CaCO3 ) were mixed and milled in a planary mill using ethanol or water as liquid media in the two different synthesized routes. Effects of rotation speed and milling time on the final products formed have been studied. Experimental results showed that HA phase having a characteristic of low crystallinity could be formed under the synthesis route using water. The original phases of both starting chemicals were remained without HA formation in the synthesis route using ethanol. Particle size and morphology of HA nanoparticles were obviously depended on optimum conditions of rotation speed and milling time. Differences on phase formation in both synthesized routes have been considered and discussed based on occurring chemical reaction possibilities. © 2015 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 105B: 679-688, 2017.

Neural signatures of team coordination are revealed by multifractal analysis.

The quality of a team depends on its ability to deliver information through a hierarchy of team members and negotiate processes spanning different time scales. That structure and the behavior that results from it pose problems for researchers because multiply-nested interactions are not easily separated. We explored the behavior of a six-person team engaged in a Submarine Piloting and Navigation (SPAN) task using the tools of dynamical systems. The data were a single entropy time series that showed the distribution of activity across six team members, as recorded by nine-channel electroencephalography (EEG). A single team's data were analyzed for the purposes of illustrating the utility of multifractal analysis and allowing for in-depth exploratory analysis of temporal characteristics. Could the meaningful events experienced by one of these teams be captured using multifractal analysis, a dynamical systems tool that is specifically designed to extract patterns across levels of analysis? Results indicate that nested patterns of team activity can be identified from neural data streams, including both routine and novel events. The novelty of this tool is the ability to identify social patterns from the brain activity of individuals in the social interaction. Implications for application and future directions of this research are discussed.

3D interconnected porous HA scaffolds with SiO2 additions: effect of SiO2 content and macropore size on the viability of human osteoblast cells.

3D interconnected porous scaffolds of HA and HA with various additions of SiO2 were fabricated using a polymeric template technique, to make bioceramic scaffolds consisting of macrostructures of the interconnected macropores. Three different sizes of the polyurethane template were used in the fabrication process to form different size interconnected macropores, to study the effect of pore size on human osteoblast cell viability. The template used allowed fabrication of scaffolds with pore sizes of 45, 60, and 75 ppi, respectively. Scanning microscopy was used extensively to observe the microstructure of the sintered samples and the characteristics of cells growing on the HA surfaces of the interconnected macropores. It has been clearly demonstrated that the SiO2 addition has influenced both the phase transformation of HA to TCP (ß-TCP and α-TCP) and also affected the human osteoblast cell viability grown on these scaffolds.

Probabilities and predictions: modeling the development of scientific problem-solving skills.

The IMMEX (Interactive Multi-Media Exercises) Web-based problem set platform enables the online delivery of complex, multimedia simulations, the rapid collection of student performance data, and has already been used in several genetic simulations. The next step is the use of these data to understand and improve student learning in a formative manner. This article describes the development of probabilistic models of undergraduate student problem solving in molecular genetics that detailed the spectrum of strategies students used when problem solving, and how the strategic approaches evolved with experience. The actions of 776 university sophomore biology majors from three molecular biology lecture courses were recorded and analyzed. Each of six simulations were first grouped by artificial neural network clustering to provide individual performance measures, and then sequences of these performances were probabilistically modeled by hidden Markov modeling to provide measures of progress. The models showed that students with different initial problem-solving abilities choose different strategies. Initial and final strategies varied across different sections of the same course and were not strongly correlated with other achievement measures. In contrast to previous studies, we observed no significant gender differences. We suggest that instructor interventions based on early student performances with these simulations may assist students to recognize effective and efficient problem-solving strategies and enhance learning.

Design and performance frameworks for constructing problem-solving simulations.

Rapid advancements in hardware, software, and connectivity are helping to shorten the times needed to develop computer simulations for science education. These advancements, however, have not been accompanied by corresponding theories of how best to design and use these technologies for teaching, learning, and testing. Such design frameworks ideally would be guided less by the strengths/limitations of the presentation media and more by cognitive analyses detailing the goals of the tasks, the needs and abilities of students, and the resulting decision outcomes needed by different audiences. This article describes a problem-solving environment and associated theoretical framework for investigating how students select and use strategies as they solve complex science problems. A framework is first described for designing on-line problem spaces that highlights issues of content, scale, cognitive complexity, and constraints. While this framework was originally designed for medical education, it has proven robust and has been successfully applied to learning environments from elementary school through medical school. Next, a similar framework is detailed for collecting student performance and progress data that can provide evidence of students' strategic thinking and that could potentially be used to accelerate student progress. Finally, experimental validation data are presented that link strategy selection and use with other metrics of scientific reasoning and student achievement.

Porous PZT ceramics for receiving transducers.

PZT-air (porous PZT) and PZT-polymer (polymer impregnated porous PZT) piezocomposites with varying porosity/polymer volume fractions have been manufactured. The composites were characterized in terms of hydrostatic charge (dh) and voltage (gh) coefficients, permittivity, hydrostatic figure of merit (dh.gh), and absolute sensitivity (M). With decreasing PZT ceramic volume, gh increased, and dh.gh had a broad maximum around 80 to 90% porosity/polymer content. The absolute sensitivity was also increased. In each case, PZT-air piezocomposites performed better than PZT-polymer piezocomposites. Hydrophones constructed from piezocomposites showed slightly lower measured receiving sensitivities than calculated values for piezocomposite materials, which was due to the loading effect of the cable and the low permittivity associated with the piezocomposites.