Personality, presence, and the virtual self: A five-factor model approach to behavioral analysis within a virtual environment

For several decades, researchers have explored the existence of the virtual self, or digital embodiment of self found within an avatar. It was surmised that this new component of one’s overall identity not only existed in conjunction with the public and private persona, but was replete with the necessary physical and psychological characteristics that facilitate a broad range of cognitive, cultural, and socio-emotional outcomes found within a virtual environment (e.g., Second Life, World of Warcraft). However, little is known with regard to whether these characteristics do indeed impact behavioral outcomes. For this reason, this study employed an observational assessment method to explore the virtual self as more than a set of characteristics attributed to an avatar, but rather as a relationship between personality (i.e., individual and avatar) and actualized behavior exhibited within a virtual environment. Further, presence measures were introduced to better understand whether feelings of immersion impact this relationship. Results indicated a burgeoning virtual self, linking personality with behavior along the domain of agreeableness. In other words, behavior is not solely the product of the environment but also is influenced by participant predispositions. Findings also suggest that the construct presence may now need to incorporate variables that account for this virtual self. Implications for educators, instructional designers, and psychologists are discussed

Harmful to Whom? Panelists Consider the Conservative Backlash Against Judith Levine\u27s New Book

Judith Levine jokingly says that at least she\u27s in good company: Margaret Sanger, Alfred Kinsey, and Jocelyn Elders all were vilified for allegedly promoting sex between adults and children (though of course none of them did any such thing). Levine, a journalist and founder of the National Writers Union, has been vilified and worse because of her new book, Harmful to Minors: The Perils of Protecting Children from Sex (University of Minnesota Press). In it, she argues that sex is not inherently harmful to teenagers, but can be healthy and empowering. Furthermore, she claims that society\u27s responses to fears of young people\u27s sexuality—such as abstinence campaigns and prosecutions of statutory rape—are not only pointless, but can be detrimental to the very children they claim to protect

Electrochemistry at carbon nanotube forests : sidewalls and closed ends allow fast electron transfer

The electrochemical properties of the closed ends and sidewalls of pristine carbon nanotube forests are investigated directly using a nanopipet electrochemical cell. Both are shown to promote fast electron transfer, without any activation or processing of the carbon nanotube material required, in contrast to the current model in the literature

A new view of electrochemistry at highly oriented pyrolytic graphite

Major new insights on electrochemical processes at graphite electrodes are reported, following extensive investigations of two of the most studied redox couples, Fe(CN)64–/3– and Ru(NH3)63+/2+. Experiments have been carried out on five different grades of highly oriented pyrolytic graphite (HOPG) that vary in step-edge height and surface coverage. Significantly, the same electrochemical characteristic is observed on all surfaces, independent of surface quality: initial cyclic voltammetry (CV) is close to reversible on freshly cleaved surfaces (>400 measurements for Fe(CN)64–/3– and >100 for Ru(NH3)63+/2+), in marked contrast to previous studies that have found very slow electron transfer (ET) kinetics, with an interpretation that ET only occurs at step edges. Significantly, high spatial resolution electrochemical imaging with scanning electrochemical cell microscopy, on the highest quality mechanically cleaved HOPG, demonstrates definitively that the pristine basal surface supports fast ET, and that ET is not confined to step edges. However, the history of the HOPG surface strongly influences the electrochemical behavior. Thus, Fe(CN)64–/3– shows markedly diminished ET kinetics with either extended exposure of the HOPG surface to the ambient environment or repeated CV measurements. In situ atomic force microscopy (AFM) reveals that the deterioration in apparent ET kinetics is coupled with the deposition of material on the HOPG electrode, while conducting-AFM highlights that, after cleaving, the local surface conductivity of HOPG deteriorates significantly with time. These observations and new insights are not only important for graphite, but have significant implications for electrochemistry at related carbon materials such as graphene and carbon nanotubes

Pseudo-single crystal electrochemistry on polycrystalline electrodes : visualizing activity at grains and grain boundaries on platinum for the Fe2+/Fe3+ redox reaction

The influence of electrode surface structure on electrochemical reaction rates and mechanisms is a major theme in electrochemical research, especially as electrodes with inherent structural heterogeneities are used ubiquitously. Yet, probing local electrochemistry and surface structure at complex surfaces is challenging. In this paper, high spatial resolution scanning electrochemical cell microscopy (SECCM) complemented with electron backscatter diffraction (EBSD) is demonstrated as a means of performing ‘pseudo-single-crystal’ electrochemical measurements at individual grains of a polycrystalline platinum electrode, while also allowing grain boundaries to be probed. Using the Fe2+/3+ couple as an illustrative case, a strong correlation is found between local surface structure and electrochemical activity. Variations in electrochemical activity for individual high index grains, visualized in a weakly adsorbing perchlorate medium, show that there is higher activity on grains with a significant (101) orientation contribution, compared to those with (001) and (111) contribution, consistent with findings on single-crystal electrodes. Interestingly, for Fe2+ oxidation in a sulfate medium a different pattern of activity emerges. Here, SECCM reveals only minor variations in activity between individual grains, again consistent with single-crystal studies, with a greatly enhanced activity at grain boundaries. This suggests that these sites may contribute significantly to the overall electrochemical behavior measured on the macroscale

Generating Synthetic Solar Granulation using Machine Learning Techniques

Solar granulation, a consequence of convection below the photosphere, displays broad, strong&nbsp;upflow regions bordered by sharp sinking plasma lanes. The distinct and specific spatial relations&nbsp;between granules make solar granulation, with lifetimes around 10 minutes, recognizable to the eye.&nbsp;However, it is not well understood if recognition machine learning models are also able to recognize&nbsp;or generate solar granulation. Machine learning (ML) applications require extensive, large data&nbsp;sets, which are expensive for solar telescopes to gather; if a machine is able to learn to generate&nbsp;synthetic solar granulation, then researchers can use a synthetic datasets to train neural networks&nbsp;to perform tasks in preparation of real data. Classic machine learning applications to date involve simple, well-defined images, such as im-&nbsp;ages of cats, dogs, human faces, or handwritten digits. Solar granulation, on the contrary, includes&nbsp;complicated, specific, high frequency phase relations, which presents a barrier for a machine to generate real-like solar granulation. Convolutional neural networks (CNN) are well-equipped to extract&nbsp;complex patterns in images, while variational autoencoders are well-equipped to generalize inputs&nbsp;and generate novel results derived from the training data. The combination of pattern-recognizing&nbsp;convolutional neural networks and generalizing variational autoencoders creates a convolutional&nbsp;variational autoencoder (CVAE), which displays promise in not only generating solar granulation,&nbsp;but in recognizing complex phase relations in images. Currently, generative models are quite successful in areas such as facial recognition/generation,&nbsp;handwriting generation, voice/signal generation, and much more. Many fields in which generative&nbsp;models are successful have a plethora of data for machine learning algorithms to learn from &ndash; like&nbsp;handwriting databases. Essentially, any field with a large amount of data will have a relatively easy&nbsp;time implementing generative models. Solar physics does not have the same availability of stan-dardized images of the solar surface as other fields do of their own observations, like handwritten&nbsp;digits, meaning machine learning applications will present difficulties in solar physics. Our project&nbsp;attempts to blend generative ML models with solar physics applications &ndash; generating novel images&nbsp;of solar granulation from restricted datasets. Although CVAEs are able to recreate and roughly generate solar granulation, the edges&nbsp;(downflow boundaries) and spatial scales of solar granulation continue to prove difficult for a machine learning algorithm to completely reproduce. This work discusses the complexities of the&nbsp;neural network&rsquo;s ability to learn specific, high-frequency phase relations, serves as a first step and&nbsp;proof of concept for generating synthetic solar granulation, and reviews current neural networks&rsquo;&nbsp;ability to recognize specific phase relations. This work also presents further research required and&nbsp;possible avenues to improve synthetic granulation generation.</p

Critical thinking skills for education students

This book has been written to help education students develop their understanding of critical analysis. It outlines the skills needed to examine and challenge data and encourages an appreciation of how this way of thinking can enrich the personal and professional development of students. It gives clear definitions of key terms and examples of how to analyse data. The book sets out how Action Learning Sets can contribute to analytical skills and helps students develop self-evaluation skills in order to recognize personal values and perceptions. This book will help develop confidence in using critical analysis through modelling, case studies and reflective tasks

Critical thinking skills for education students

ix, 115 p.; 24.5 c